Resource Management in Constrained Dynamic Situations

NASA Astrophysics Data System (ADS)

Seok, Jinwoo

Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments for the planning level. To obtain a policy, dynamic programing is applied, and to obtain a solution, limited breadth-first search is applied to the recomposable restricted finite state machine. A multi-function phased array radar resource management problem and an unmanned aerial vehicle patrolling problem are treated using recomposable restricted finite state machines. Then, we use model predictive control for the control level, because it allows constraint handling and setpoint tracking for the schedule. An aircraft power system management problem is treated that aims to develop an integrated control system for an aircraft gas turbine engine and electrical power system using rate-based model predictive control. Our results indicate that at the planning level, limited breadth-first search for recomposable restricted finite state machines generates good scheduling solutions in limited resource situations and unpredictably dynamic environments. The importance of cooperation in the planning level is also verified. At the control level, a rate-based model predictive controller allows good schedule tracking and safe operations. The importance of considering the system constraints and interactions between the subsystems is indicated. For the best resource management in constrained dynamic situations, the planning level and the control level need to be considered together.

Neural Network Assisted Inverse Dynamic Guidance for Terminally Constrained Entry Flight

PubMed Central

Chen, Wanchun

2014-01-01

This paper presents a neural network assisted entry guidance law that is designed by applying Bézier approximation. It is shown that a fully constrained approximation of a reference trajectory can be made by using the Bézier curve. Applying this approximation, an inverse dynamic system for an entry flight is solved to generate guidance command. The guidance solution thus gotten ensures terminal constraints for position, flight path, and azimuth angle. In order to ensure terminal velocity constraint, a prediction of the terminal velocity is required, based on which, the approximated Bézier curve is adjusted. An artificial neural network is used for this prediction of the terminal velocity. The method enables faster implementation in achieving fully constrained entry flight. Results from simulations indicate improved performance of the neural network assisted method. The scheme is expected to have prospect for further research on automated onboard control of terminal velocity for both reentry and terminal guidance laws. PMID:24723821

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

Simonetto, Andrea; Dall'Anese, Emiliano

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays.

PubMed

Tang, Xiaoming; Qu, Hongchun; Wang, Ping; Zhao, Meng

2015-03-01

This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S-A) and controller to actuator (C-A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

NASA Astrophysics Data System (ADS)

Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

2017-10-01

Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

Probability-based constrained MPC for structured uncertain systems with state and random input delays

NASA Astrophysics Data System (ADS)

Lu, Jianbo; Li, Dewei; Xi, Yugeng

2013-07-01

This article is concerned with probability-based constrained model predictive control (MPC) for systems with both structured uncertainties and time delays, where a random input delay and multiple fixed state delays are included. The process of input delay is governed by a discrete-time finite-state Markov chain. By invoking an appropriate augmented state, the system is transformed into a standard structured uncertain time-delay Markov jump linear system (MJLS). For the resulting system, a multi-step feedback control law is utilised to minimise an upper bound on the expected value of performance objective. The proposed design has been proved to stabilise the closed-loop system in the mean square sense and to guarantee constraints on control inputs and system states. Finally, a numerical example is given to illustrate the proposed results.

Economic Analysis of Biological Invasions in Forests

Treesearch

Tomas P. Holmes; Julian Aukema; Jeffrey Englin; Robert G. Haight; Kent Kovacs; Brian Leung

2014-01-01

Biological invasions of native forests by nonnative pests result from complex stochastic processes that are difficult to predict. Although economic optimization models describe efficient controls across the stages of an invasion, the ability to calibrate such models is constrained by lack of information on pest population dynamics and consequent economic damages. Here...

Reduced mate availability leads to evolution of self-fertilization and purging of inbreeding depression in a hermaphrodite.

PubMed

Noël, Elsa; Chemtob, Yohann; Janicke, Tim; Sarda, Violette; Pélissié, Benjamin; Jarne, Philippe; David, Patrice

2016-03-01

Basic models of mating-system evolution predict that hermaphroditic organisms should mostly either cross-fertilize, or self-fertilize, due to self-reinforcing coevolution of inbreeding depression and outcrossing rates. However transitions between mating systems occur. A plausible scenario for such transitions assumes that a decrease in pollinator or mate availability temporarily constrains outcrossing populations to self-fertilize as a reproductive assurance strategy. This should trigger a purge of inbreeding depression, which in turn encourages individuals to self-fertilize more often and finally to reduce male allocation. We tested the predictions of this scenario using the freshwater snail Physa acuta, a self-compatible hermaphrodite that preferentially outcrosses and exhibits high inbreeding depression in natural populations. From an outbred population, we built two types of experimental evolution lines, controls (outcrossing every generation) and constrained lines (in which mates were often unavailable, forcing individuals to self-fertilize). After ca. 20 generations, individuals from constrained lines initiated self-fertilization earlier in life and had purged most of their inbreeding depression compared to controls. However, their male allocation remained unchanged. Our study suggests that the mating system can rapidly evolve as a response to reduced mating opportunities, supporting the reproductive assurance scenario of transitions from outcrossing to selfing. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

A Study of Interactions between Mixing and Chemical Reaction Using the Rate-Controlled Constrained-Equilibrium Method

NASA Astrophysics Data System (ADS)

Hadi, Fatemeh; Janbozorgi, Mohammad; Sheikhi, M. Reza H.; Metghalchi, Hameed

2016-10-01

The rate-controlled constrained-equilibrium (RCCE) method is employed to study the interactions between mixing and chemical reaction. Considering that mixing can influence the RCCE state, the key objective is to assess the accuracy and numerical performance of the method in simulations involving both reaction and mixing. The RCCE formulation includes rate equations for constraint potentials, density and temperature, which allows taking account of mixing alongside chemical reaction without splitting. The RCCE is a dimension reduction method for chemical kinetics based on thermodynamics laws. It describes the time evolution of reacting systems using a series of constrained-equilibrium states determined by RCCE constraints. The full chemical composition at each state is obtained by maximizing the entropy subject to the instantaneous values of the constraints. The RCCE is applied to a spatially homogeneous constant pressure partially stirred reactor (PaSR) involving methane combustion in oxygen. Simulations are carried out over a wide range of initial temperatures and equivalence ratios. The chemical kinetics, comprised of 29 species and 133 reaction steps, is represented by 12 RCCE constraints. The RCCE predictions are compared with those obtained by direct integration of the same kinetics, termed detailed kinetics model (DKM). The RCCE shows accurate prediction of combustion in PaSR with different mixing intensities. The method also demonstrates reduced numerical stiffness and overall computational cost compared to DKM.

Cultural and Environmental Predictors of Pre-European Deforestation on Pacific Islands

PubMed Central

Coomber, Ties; Passmore, Sam; Greenhill, Simon J.; Kushnick, Geoff

2016-01-01

The varied islands of the Pacific provide an ideal natural experiment for studying the factors shaping human impact on the environment. Previous research into pre-European deforestation across the Pacific indicated a major effect of environment but did not account for cultural variation or control for dependencies in the data due to shared cultural ancestry and geographic proximity. The relative importance of environment and culture on Pacific deforestation and forest replacement and the extent to which environmental impact is constrained by cultural ancestry therefore remain unexplored. Here we use comparative phylogenetic methods to model the effect of nine ecological and two cultural variables on pre-European Pacific forest outcomes at 80 locations across 67 islands. We show that some but not all ecological features remain important predictors of forest outcomes after accounting for cultural covariates and non-independence in the data. Controlling for ecology, cultural variation in agricultural intensification predicts deforestation and forest replacement, and there is some evidence that land tenure norms predict forest replacement. These findings indicate that, alongside ecology, cultural factors also predict pre-European Pacific forest outcomes. Although forest outcomes covary with cultural ancestry, this effect disappears after controlling for geographic proximity and ecology. This suggests that forest outcomes were not tightly constrained by colonists’ cultural ancestry, but instead reflect a combination of ecological constraints and the short-term responses of each culture in the face of those constraints. PMID:27232713

Cultural and Environmental Predictors of Pre-European Deforestation on Pacific Islands.

PubMed

Atkinson, Quentin D; Coomber, Ties; Passmore, Sam; Greenhill, Simon J; Kushnick, Geoff

2016-01-01

The varied islands of the Pacific provide an ideal natural experiment for studying the factors shaping human impact on the environment. Previous research into pre-European deforestation across the Pacific indicated a major effect of environment but did not account for cultural variation or control for dependencies in the data due to shared cultural ancestry and geographic proximity. The relative importance of environment and culture on Pacific deforestation and forest replacement and the extent to which environmental impact is constrained by cultural ancestry therefore remain unexplored. Here we use comparative phylogenetic methods to model the effect of nine ecological and two cultural variables on pre-European Pacific forest outcomes at 80 locations across 67 islands. We show that some but not all ecological features remain important predictors of forest outcomes after accounting for cultural covariates and non-independence in the data. Controlling for ecology, cultural variation in agricultural intensification predicts deforestation and forest replacement, and there is some evidence that land tenure norms predict forest replacement. These findings indicate that, alongside ecology, cultural factors also predict pre-European Pacific forest outcomes. Although forest outcomes covary with cultural ancestry, this effect disappears after controlling for geographic proximity and ecology. This suggests that forest outcomes were not tightly constrained by colonists' cultural ancestry, but instead reflect a combination of ecological constraints and the short-term responses of each culture in the face of those constraints.

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

NASA Astrophysics Data System (ADS)

Xavier, Marcelo A.; Trimboli, M. Scott

2015-07-01

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models.

Vibration control of beams using stand-off layer damping: finite element modeling and experiments

NASA Astrophysics Data System (ADS)

Chaudry, A.; Baz, A.

2006-03-01

Damping treatments with stand-off layer (SOL) have been widely accepted as an attractive alternative to conventional constrained layer damping (CLD) treatments. Such an acceptance stems from the fact that the SOL, which is simply a slotted spacer layer sandwiched between the viscoelastic layer and the base structure, acts as a strain magnifier that considerably amplifies the shear strain and hence the energy dissipation characteristics of the viscoelastic layer. Accordingly, more effective vibration suppression can be achieved by using SOL as compared to employing CLD. In this paper, a comprehensive finite element model of the stand-off layer constrained damping treatment is developed. The model accounts for the geometrical and physical parameters of the slotted SOL, the viscoelastic, layer the constraining layer, and the base structure. The predictions of the model are validated against the predictions of a distributed transfer function model and a model built using a commercial finite element code (ANSYS). Furthermore, the theoretical predictions are validated experimentally for passive SOL treatments of different configurations. The obtained results indicate a close agreement between theory and experiments. Furthermore, the obtained results demonstrate the effectiveness of the CLD with SOL in enhancing the energy dissipation as compared to the conventional CLD. Extension of the proposed one-dimensional CLD with SOL to more complex structures is a natural extension to the present study.

Reference governors for controlled belt restraint systems

NASA Astrophysics Data System (ADS)

van der Laan, E. P.; Heemels, W. P. M. H.; Luijten, H.; Veldpaus, F. E.; Steinbuch, M.

2010-07-01

Today's restraint systems typically include a number of airbags, and a three-point seat belt with load limiter and pretensioner. For the class of real-time controlled restraint systems, the restraint actuator settings are continuously manipulated during the crash. This paper presents a novel control strategy for these systems. The control strategy developed here is based on a combination of model predictive control and reference management, in which a non-linear device - a reference governor (RG) - is added to a primal closed-loop controlled system. This RG determines an optimal setpoint in terms of injury reduction and constraint satisfaction by solving a constrained optimisation problem. Prediction of the vehicle motion, required to predict future constraint violation, is included in the design and is based on past crash data, using linear regression techniques. Simulation results with MADYMO models show that, with ideal sensors and actuators, a significant reduction (45%) of the peak chest acceleration can be achieved, without prior knowledge of the crash. Furthermore, it is shown that the algorithms are sufficiently fast to be implemented online.

Controlling the extrudate swell in melt extrusion additive manufacturing of 3D scaffolds: a designed experiment.

PubMed

Yousefi, Azizeh-Mitra; Smucker, Byran; Naber, Alex; Wyrick, Cara; Shaw, Charles; Bennett, Katelyn; Szekely, Sarah; Focke, Carlie; Wood, Katherine A

2018-02-01

Tissue engineering using three-dimensional porous scaffolds has shown promise for the restoration of normal function in injured and diseased tissues and organs. Rigorous control over scaffold architecture in melt extrusion additive manufacturing is highly restricted mainly due to pronounced variations in the deposited strand diameter upon any variations in process conditions and polymer viscoelasticity. We have designed an I-optimal, split-plot experiment to study the extrudate swell in melt extrusion additive manufacturing and to control the scaffold architecture. The designed experiment was used to generate data to relate three responses (swell, density, and modulus) to a set of controllable factors (plotting needle diameter, temperature, pressure, and the dispensing speed). The fitted regression relationships were used to optimize the three responses simultaneously. The swell response was constrained to be close to 1 while maximizing the modulus and minimizing the density. Constraining the extrudate swell to 1 generates design-driven scaffolds, with strand diameters equal to the plotting needle diameter, and allows a greater control over scaffold pore size. Hence, the modulus of the scaffolds can be fully controlled by adjusting the in-plane distance between the deposited strands. To the extent of the model's validity, we can eliminate the effect of extrudate swell in designing these scaffolds, while targeting a range of porosity and modulus appropriate for bone tissue engineering. The result of this optimization was a predicted modulus of 14 MPa and a predicted density of 0.29 g/cm 3 (porosity ≈ 75%) using polycaprolactone as scaffold material. These predicted responses corresponded to factor levels of 0.6 μm for the plotting needle diameter, plotting pressure of 2.5 bar, melt temperature of 113.5 °C, and dispensing speed of 2 mm/s. The validation scaffold enabled us to quantify the percentage difference for the predictions, which was 9.5% for the extrudate swell, 19% for the density, and 29% for the modulus.

Constrained evolution in numerical relativity

NASA Astrophysics Data System (ADS)

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.

Chemical kinetic model uncertainty minimization through laminar flame speed measurements

PubMed Central

Park, Okjoo; Veloo, Peter S.; Sheen, David A.; Tao, Yujie; Egolfopoulos, Fokion N.; Wang, Hai

2016-01-01

Laminar flame speed measurements were carried for mixture of air with eight C3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso-butene, n-butane, and iso-butane) at the room temperature and ambient pressure. Along with C1-2 hydrocarbon data reported in a recent study, the entire dataset was used to demonstrate how laminar flame speed data can be utilized to explore and minimize the uncertainties in a reaction model for foundation fuels. The USC Mech II kinetic model was chosen as a case study. The method of uncertainty minimization using polynomial chaos expansions (MUM-PCE) (D.A. Sheen and H. Wang, Combust. Flame 2011, 158, 2358–2374) was employed to constrain the model uncertainty for laminar flame speed predictions. Results demonstrate that a reaction model constrained only by the laminar flame speed values of methane/air flames notably reduces the uncertainty in the predictions of the laminar flame speeds of C3 and C4 alkanes, because the key chemical pathways of all of these flames are similar to each other. The uncertainty in model predictions for flames of unsaturated C3-4 hydrocarbons remain significant without considering fuel specific laminar flames speeds in the constraining target data set, because the secondary rate controlling reaction steps are different from those in the saturated alkanes. It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C4 alcohol/air mixtures. Furthermore, it is demonstrated that an accurate prediction of the laminar flame speed of a particular C4 alcohol/air mixture is better achieved through measurements for key molecular intermediates formed during the pyrolysis and oxidation of the parent fuel. PMID:27890938

Chemical kinetic model uncertainty minimization through laminar flame speed measurements.

PubMed

Park, Okjoo; Veloo, Peter S; Sheen, David A; Tao, Yujie; Egolfopoulos, Fokion N; Wang, Hai

2016-10-01

Laminar flame speed measurements were carried for mixture of air with eight C 3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso -butene, n -butane, and iso -butane) at the room temperature and ambient pressure. Along with C 1-2 hydrocarbon data reported in a recent study, the entire dataset was used to demonstrate how laminar flame speed data can be utilized to explore and minimize the uncertainties in a reaction model for foundation fuels. The USC Mech II kinetic model was chosen as a case study. The method of uncertainty minimization using polynomial chaos expansions (MUM-PCE) (D.A. Sheen and H. Wang, Combust. Flame 2011, 158, 2358-2374) was employed to constrain the model uncertainty for laminar flame speed predictions. Results demonstrate that a reaction model constrained only by the laminar flame speed values of methane/air flames notably reduces the uncertainty in the predictions of the laminar flame speeds of C 3 and C 4 alkanes, because the key chemical pathways of all of these flames are similar to each other. The uncertainty in model predictions for flames of unsaturated C 3-4 hydrocarbons remain significant without considering fuel specific laminar flames speeds in the constraining target data set, because the secondary rate controlling reaction steps are different from those in the saturated alkanes. It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C 4 alcohol/air mixtures. Furthermore, it is demonstrated that an accurate prediction of the laminar flame speed of a particular C 4 alcohol/air mixture is better achieved through measurements for key molecular intermediates formed during the pyrolysis and oxidation of the parent fuel.

Prediction of noise constrained optimum takeoff procedures

NASA Technical Reports Server (NTRS)

Padula, S. L.

1980-01-01

An optimization method is used to predict safe, maximum-performance takeoff procedures which satisfy noise constraints at multiple observer locations. The takeoff flight is represented by two-degree-of-freedom dynamical equations with aircraft angle-of-attack and engine power setting as control functions. The engine thrust, mass flow and noise source parameters are assumed to be given functions of the engine power setting and aircraft Mach number. Effective Perceived Noise Levels at the observers are treated as functionals of the control functions. The method is demonstrated by applying it to an Advanced Supersonic Transport aircraft design. The results indicate that automated takeoff procedures (continuously varying controls) can be used to significantly reduce community and certification noise without jeopardizing safety or degrading performance.

Qualitative simulation for process modeling and control

NASA Technical Reports Server (NTRS)

Dalle Molle, D. T.; Edgar, T. F.

1989-01-01

A qualitative model is developed for a first-order system with a proportional-integral controller without precise knowledge of the process or controller parameters. Simulation of the qualitative model yields all of the solutions to the system equations. In developing the qualitative model, a necessary condition for the occurrence of oscillatory behavior is identified. Initializations that cannot exhibit oscillatory behavior produce a finite set of behaviors. When the phase-space behavior of the oscillatory behavior is properly constrained, these initializations produce an infinite but comprehensible set of asymptotically stable behaviors. While the predictions include all possible behaviors of the real system, a class of spurious behaviors has been identified. When limited numerical information is included in the model, the number of predictions is significantly reduced.

Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

PubMed Central

Chen, Qihong; Long, Rong; Quan, Shuhai

2014-01-01

This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

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

Xavier, MA; Trimboli, MS

This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggestmore » significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.« less

Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

PubMed

Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

2015-01-01

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

Periodic Forced Response of Structures Having Three-Dimensional Frictional Constraints

NASA Astrophysics Data System (ADS)

CHEN, J. J.; YANG, B. D.; MENQ, C. H.

2000-01-01

Many mechanical systems have moving components that are mutually constrained through frictional contacts. When subjected to cyclic excitations, a contact interface may undergo constant changes among sticks, slips and separations, which leads to very complex contact kinematics. In this paper, a 3-D friction contact model is employed to predict the periodic forced response of structures having 3-D frictional constraints. Analytical criteria based on this friction contact model are used to determine the transitions among sticks, slips and separations of the friction contact, and subsequently the constrained force which consists of the induced stick-slip friction force on the contact plane and the contact normal load. The resulting constrained force is often a periodic function and can be considered as a feedback force that influences the response of the constrained structures. By using the Multi-Harmonic Balance Method along with Fast Fourier Transform, the constrained force can be integrated with the receptance of the structures so as to calculate the forced response of the constrained structures. It results in a set of non-linear algebraic equations that can be solved iteratively to yield the relative motion as well as the constrained force at the friction contact. This method is used to predict the periodic response of a frictionally constrained 3-d.o.f. oscillator. The predicted results are compared with those of the direct time integration method so as to validate the proposed method. In addition, the effect of super-harmonic components on the resonant response and jump phenomenon is examined.

Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

NASA Astrophysics Data System (ADS)

Siampis, Efstathios; Velenis, Efstathios; Longo, Stefano

2015-11-01

In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.

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

PubMed

Zhao, Meng; Ding, Baocang

2015-03-01

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

Hemispheric processing of predictive inferences during reading: The influence of negatively emotional valenced stimuli.

PubMed

Virtue, Sandra; Schutzenhofer, Michael; Tomkins, Blaine

2017-07-01

Although a left hemisphere advantage is usually evident during language processing, the right hemisphere is highly involved during the processing of weakly constrained inferences. However, currently little is known about how the emotional valence of environmental stimuli influences the hemispheric processing of these inferences. In the current study, participants read texts promoting either strongly or weakly constrained predictive inferences and performed a lexical decision task to inference-related targets presented to the left visual field-right hemisphere or the right visual field-left hemisphere. While reading these texts, participants either listened to dissonant music (i.e., the music condition) or did not listen to music (i.e., the no music condition). In the no music condition, the left hemisphere showed an advantage for strongly constrained inferences compared to weakly constrained inferences, whereas the right hemisphere showed high facilitation for both strongly and weakly constrained inferences. In the music condition, both hemispheres showed greater facilitation for strongly constrained inferences than for weakly constrained inferences. These results suggest that negatively valenced stimuli (such as dissonant music) selectively influences the right hemisphere's processing of weakly constrained inferences during reading.

The surprisingly transparent sQGP at LHC

NASA Astrophysics Data System (ADS)

Horowitz, W. A.; Gyulassy, Miklos

2011-12-01

We present parameter-free predictions of the nuclear modification factor, RAAπ(p,s), of high p pions produced in Pb + Pb collisions at s=2.76 and 5.5 ATeV based on the WHDG/DGLV (radiative + elastic + geometric fluctuation) jet energy loss model. The initial quark gluon plasma (QGP) density at LHC is constrained from a rigorous statistical analysis of PHENIX/RHIC π quenching data at s=0.2 ATeV and the charged particle multiplicity at ALICE/LHC at 2.76 ATeV. Our perturbative QCD tomographic theory predicts significant differences between jet quenching at RHIC and LHC energies, which are qualitatively consistent with the p-dependence and normalization—within the large systematic uncertainty—of the first charged hadron nuclear modification factor, RAAch, data measured by ALICE. However, our constrained prediction of the central to peripheral pion modification, Rcpπ(p), for which large systematic uncertainties associated with unmeasured p + p reference data cancel, is found to be over-quenched relative to the charged hadron ALICE Rcpch data in the range 5

Orbit determination of the Next-Generation Beidou satellites with Intersatellite link measurements and a priori orbit constraints

NASA Astrophysics Data System (ADS)

Ren, Xia; Yang, Yuanxi; Zhu, Jun; Xu, Tianhe

2017-11-01

Intersatellite Link (ISL) technology helps to realize the auto update of broadcast ephemeris and clock error parameters for Global Navigation Satellite System (GNSS). ISL constitutes an important approach with which to both improve the observation geometry and extend the tracking coverage of China's Beidou Navigation Satellite System (BDS). However, ISL-only orbit determination might lead to the constellation drift, rotation, and even lead to the divergence in orbit determination. Fortunately, predicted orbits with good precision can be used as a priori information with which to constrain the estimated satellite orbit parameters. Therefore, the precision of satellite autonomous orbit determination can be improved by consideration of a priori orbit information, and vice versa. However, the errors of rotation and translation in a priori orbit will remain in the ultimate result. This paper proposes a constrained precise orbit determination (POD) method for a sub-constellation of the new Beidou satellite constellation with only a few ISLs. The observation model of dual one-way measurements eliminating satellite clock errors is presented, and the orbit determination precision is analyzed with different data processing backgrounds. The conclusions are as follows. (1) With ISLs, the estimated parameters are strongly correlated, especially the positions and velocities of satellites. (2) The performance of determined BDS orbits will be improved by the constraints with more precise priori orbits. The POD precision is better than 45 m with a priori orbit constrain of 100 m precision (e.g., predicted orbits by telemetry tracking and control system), and is better than 6 m with precise priori orbit constraints of 10 m precision (e.g., predicted orbits by international GNSS monitoring & Assessment System (iGMAS)). (3) The POD precision is improved by additional ISLs. Constrained by a priori iGMAS orbits, the POD precision with two, three, and four ISLs is better than 6, 3, and 2 m, respectively. (4) The in-plane link and out-of-plane link have different contributions to observation configuration and system observability. The POD with weak observation configuration (e.g., one in-plane link and one out-of-plane link) should be tightly constrained with a priori orbits.

Predictability of Subsurface Temperature and the AMOC

NASA Astrophysics Data System (ADS)

Chang, Y.; Schubert, S. D.

2013-12-01

GEOS 5 coupled model is extensively used for experimental decadal climate prediction. Understanding the limits of decadal ocean predictability is critical for making progress in these efforts. Using this model, we study the subsurface temperature initial value predictability, the variability of the Atlantic meridional overturning circulation (AMOC) and its impacts on the global climate. Our approach is to utilize the idealized data assimilation technology developed at the GMAO. The technique 'replay' allows us to assess, for example, the impact of the surface wind stresses and/or precipitation on the ocean in a very well controlled environment. By running the coupled model in replay mode we can in fact constrain the model using any existing reanalysis data set. We replay the model constraining (nudging) it to the MERRA reanalysis in various fields from 1948-2012. The fields, u,v,T,q,ps, are adjusted towards the 6-hourly analyzed fields in atmosphere. The simulated AMOC variability is studied with a 400-year-long segment of replay integration. The 84 cases of 10-year hindcasts are initialized from 4 different replay cycles. Here, the variability and predictability are examined further by a measure to quantify how much the subsurface temperature and AMOC variability has been influenced by atmospheric forcing and by ocean internal variability. The simulated impact of the AMOC on the multi-decadal variability of the SST, sea surface height (SSH) and sea ice extent is also studied.

A Multidimensional Item Response Model: Constrained Latent Class Analysis Using the Gibbs Sampler and Posterior Predictive Checks.

ERIC Educational Resources Information Center

Hoijtink, Herbert; Molenaar, Ivo W.

1997-01-01

This paper shows that a certain class of constrained latent class models may be interpreted as a special case of nonparametric multidimensional item response models. Parameters of this latent class model are estimated using an application of the Gibbs sampler, and model fit is investigated using posterior predictive checks. (SLD)

Sensitivity to gaze-contingent contrast increments in naturalistic movies: An exploratory report and model comparison

PubMed Central

Wallis, Thomas S. A.; Dorr, Michael; Bex, Peter J.

2015-01-01

Sensitivity to luminance contrast is a prerequisite for all but the simplest visual systems. To examine contrast increment detection performance in a way that approximates the natural environmental input of the human visual system, we presented contrast increments gaze-contingently within naturalistic video freely viewed by observers. A band-limited contrast increment was applied to a local region of the video relative to the observer's current gaze point, and the observer made a forced-choice response to the location of the target (≈25,000 trials across five observers). We present exploratory analyses showing that performance improved as a function of the magnitude of the increment and depended on the direction of eye movements relative to the target location, the timing of eye movements relative to target presentation, and the spatiotemporal image structure at the target location. Contrast discrimination performance can be modeled by assuming that the underlying contrast response is an accelerating nonlinearity (arising from a nonlinear transducer or gain control). We implemented one such model and examined the posterior over model parameters, estimated using Markov-chain Monte Carlo methods. The parameters were poorly constrained by our data; parameters constrained using strong priors taken from previous research showed poor cross-validated prediction performance. Atheoretical logistic regression models were better constrained and provided similar prediction performance to the nonlinear transducer model. Finally, we explored the properties of an extended logistic regression that incorporates both eye movement and image content features. Models of contrast transduction may be better constrained by incorporating data from both artificial and natural contrast perception settings. PMID:26057546

Maximum entropy modeling of metabolic networks by constraining growth-rate moments predicts coexistence of phenotypes

NASA Astrophysics Data System (ADS)

De Martino, Daniele

2017-12-01

In this work maximum entropy distributions in the space of steady states of metabolic networks are considered upon constraining the first and second moments of the growth rate. Coexistence of fast and slow phenotypes, with bimodal flux distributions, emerges upon considering control on the average growth (optimization) and its fluctuations (heterogeneity). This is applied to the carbon catabolic core of Escherichia coli where it quantifies the metabolic activity of slow growing phenotypes and it provides a quantitative map with metabolic fluxes, opening the possibility to detect coexistence from flux data. A preliminary analysis on data for E. coli cultures in standard conditions shows degeneracy for the inferred parameters that extend in the coexistence region.

Chemical kinetic model uncertainty minimization through laminar flame speed measurements

DOE PAGES

Park, Okjoo; Veloo, Peter S.; Sheen, David A.; ...

2016-07-25

Laminar flame speed measurements were carried for mixture of air with eight C 3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso-butene, n-butane, and iso-butane) at the room temperature and ambient pressure. Along with C 1-2 hydrocarbon data reported in a recent study, the entire dataset was used to demonstrate how laminar flame speed data can be utilized to explore and minimize the uncertainties in a reaction model for foundation fuels. The USC Mech II kinetic model was chosen as a case study. The method of uncertainty minimization using polynomial chaos expansions (MUM-PCE) (D.A. Sheen and H. Wang, Combust. Flame 2011,more » 158, 2358–2374) was employed to constrain the model uncertainty for laminar flame speed predictions. Results demonstrate that a reaction model constrained only by the laminar flame speed values of methane/air flames notably reduces the uncertainty in the predictions of the laminar flame speeds of C 3 and C 4 alkanes, because the key chemical pathways of all of these flames are similar to each other. The uncertainty in model predictions for flames of unsaturated C 3-4 hydrocarbons remain significant without considering fuel specific laminar flames speeds in the constraining target data set, because the secondary rate controlling reaction steps are different from those in the saturated alkanes. It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C 4 alcohol/air mixtures. Furthermore, it is demonstrated that an accurate prediction of the laminar flame speed of a particular C 4 alcohol/air mixture is better achieved through measurements for key molecular intermediates formed during the pyrolysis and oxidation of the parent fuel.« less

Chemical kinetic model uncertainty minimization through laminar flame speed measurements

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

Park, Okjoo; Veloo, Peter S.; Sheen, David A.

Laminar flame speed measurements were carried for mixture of air with eight C 3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso-butene, n-butane, and iso-butane) at the room temperature and ambient pressure. Along with C 1-2 hydrocarbon data reported in a recent study, the entire dataset was used to demonstrate how laminar flame speed data can be utilized to explore and minimize the uncertainties in a reaction model for foundation fuels. The USC Mech II kinetic model was chosen as a case study. The method of uncertainty minimization using polynomial chaos expansions (MUM-PCE) (D.A. Sheen and H. Wang, Combust. Flame 2011,more » 158, 2358–2374) was employed to constrain the model uncertainty for laminar flame speed predictions. Results demonstrate that a reaction model constrained only by the laminar flame speed values of methane/air flames notably reduces the uncertainty in the predictions of the laminar flame speeds of C 3 and C 4 alkanes, because the key chemical pathways of all of these flames are similar to each other. The uncertainty in model predictions for flames of unsaturated C 3-4 hydrocarbons remain significant without considering fuel specific laminar flames speeds in the constraining target data set, because the secondary rate controlling reaction steps are different from those in the saturated alkanes. It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C 4 alcohol/air mixtures. Furthermore, it is demonstrated that an accurate prediction of the laminar flame speed of a particular C 4 alcohol/air mixture is better achieved through measurements for key molecular intermediates formed during the pyrolysis and oxidation of the parent fuel.« less

A Two-stage Approach for Water Demand Prediction under Constrained total water use and Water Environmental Capacity

NASA Astrophysics Data System (ADS)

He, Y.; Xiaohong, C.; Lin, K.; Wang, Z.

2016-12-01

Water demand (WD) is the basis for water allocation (WA) because it can fully reflect the pressure on water resources from population and socioeconomic development. To deal with the great uncertainties and the absence of consideration of water environmental capacity (WEC) in traditional water demand prediction methods, e.g. Statistical models, System Dynamics and quota method, this study develops a two-stage approach to predict WD under constrained total water use from the perspective of ecological restraint. Regional total water demand (RTWD) is constrained by WEC, available water resources amount and total water use quota. Based on RTWD, WD is allocated in two stages according to the game theory, including predicting sub regional total water demand (SRWD) by calculating the sub region weights based on the selected indicators of socioeconomic development and predicting industrial water demand (IWD) according to the game theory. Taking the Dongjiang river basin, South China as an example of WD prediction, according to its constrained total water use quota and WEC, RTWD in 2020 is 9.83 billion m3, and IWD for agriculture, industry, service, ecology (off-stream), and domesticity are 2.32 billion m3, 3.79 billion m3, 0.75 billion m3 , 0.18 billion m3and 1.79 billion m3 respectively. The results from this study provide useful insights for effective water allocation under climate change and the strict policy of water resources management.

Dark matter, constrained minimal supersymmetric standard model, and lattice QCD.

PubMed

Giedt, Joel; Thomas, Anthony W; Young, Ross D

2009-11-13

Recent lattice measurements have given accurate estimates of the quark condensates in the proton. We use these results to significantly improve the dark matter predictions in benchmark models within the constrained minimal supersymmetric standard model. The predicted spin-independent cross sections are at least an order of magnitude smaller than previously suggested and our results have significant consequences for dark matter searches.

Modeling evapotranspiration based on plant hydraulic theory can predict spatial variability across an elevation gradient and link to biogeochemical fluxes

NASA Astrophysics Data System (ADS)

Mackay, D. S.; Frank, J.; Reed, D.; Whitehouse, F.; Ewers, B. E.; Pendall, E.; Massman, W. J.; Sperry, J. S.

2012-04-01

In woody plant systems transpiration is often the dominant component of total evapotranspiration, and so it is key to understanding water and energy cycles. Moreover, transpiration is tightly coupled to carbon and nutrient fluxes, and so it is also vital to understanding spatial variability of biogeochemical fluxes. However, the spatial variability of transpiration and its links to biogeochemical fluxes, within- and among-ecosystems, has been a challenge to constrain because of complex feedbacks between physical and biological controls. Plant hydraulics provides an emerging theory with the rigor needed to develop testable hypotheses and build useful models for scaling these coupled fluxes from individual plants to regional scales. This theory predicts that vegetative controls over water, energy, carbon, and nutrient fluxes can be determined from the limitation of plant water transport through the soil-xylem-stomata pathway. Limits to plant water transport can be predicted from measurable plant structure and function (e.g., vulnerability to cavitation). We present a next-generation coupled transpiration-biogeochemistry model based on this emerging theory. The model, TREEScav, is capable of predicting transpiration, along with carbon and nutrient flows, constrained by plant structure and function. The model incorporates tightly coupled mechanisms of the demand and supply of water through the soil-xylem-stomata system, with the feedbacks to photosynthesis and utilizable carbohydrates. The model is evaluated by testing it against transpiration and carbon flux data along an elevation gradient of woody plants comprising sagebrush steppe, mid-elevation lodgepole pine forests, and subalpine spruce/fir forests in the Rocky Mountains. The model accurately predicts transpiration and carbon fluxes as measured from gas exchange, sap flux, and eddy covariance towers. The results of this work demonstrate that credible spatial predictions of transpiration and related biogeochemical fluxes will be possible at regional scales using relatively easily obtained vegetation structural and functional information.

Effectiveness of a passive-active vibration isolation system with actuator constraints

NASA Astrophysics Data System (ADS)

Sun, Lingling; Sun, Wei; Song, Kongjie; Hansen, Colin H.

2014-05-01

In the prediction of active vibration isolation performance, control force requirements were ignored in previous work. This may limit the realization of theoretically predicted isolation performance if control force of large magnitude cannot be supplied by actuators. The behavior of a feed-forward active isolation system subjected to actuator output constraints is investigated. Distributed parameter models are developed to analyze the system response, and to produce a transfer matrix for the design of an integrated passive-active isolation system. Cost functions comprising a combination of the vibration transmission energy and the sum of the squared control forces are proposed. The example system considered is a rigid body connected to a simply supported plate via two passive-active isolation mounts. Vertical and transverse forces as well as a rotational moment are applied at the rigid body, and resonances excited in elastic mounts and the supporting plate are analyzed. The overall isolation performance is evaluated by numerical simulation. The simulation results are then compared with those obtained using unconstrained control strategies. In addition, the effects of waves in elastic mounts are analyzed. It is shown that the control strategies which rely on unconstrained actuator outputs may give substantial power transmission reductions over a wide frequency range, but also require large control force amplitudes to control excited vibration modes of the system. Expected power transmission reductions for modified control strategies that incorporate constrained actuator outputs are considerably less than typical reductions with unconstrained actuator outputs. In the frequency range in which rigid body modes are present, the control strategies can only achieve 5-10 dB power transmission reduction, when control forces are constrained to be the same order of the magnitude as the primary vertical force. The resonances of the elastic mounts result in a notable increase of power transmission in high frequency range and cannot be attenuated by active control. The investigation provides a guideline for design and evaluation of active vibration isolation systems.

SMA Hybrid Composites for Dynamic Response Abatement Applications

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2000-01-01

A recently developed constitutive model and a finite element formulation for predicting the thermomechanical response of Shape Memory Alloy (SMA) hybrid composite (SMAHC) structures is briefly described. Attention is focused on constrained recovery behavior in this study, but the constitutive formulation is also capable of modeling restrained or free recovery. Numerical results are shown for glass/epoxy panel specimens with embedded Nitinol actuators subjected to thermal and acoustic loads. Control of thermal buckling, random response, sonic fatigue, and transmission loss are demonstrated and compared to conventional approaches including addition of conventional composite layers and a constrained layer damping treatment. Embedded SMA actuators are shown to be significantly more effective in dynamic response abatement applications than the conventional approaches and are attractive for combination with other passive and/or active approaches.

Explaining postseismic and aseismic transient deformation in subduction zones with rate and state friction modeling constrained by lab and geodetic observations

NASA Astrophysics Data System (ADS)

Liu, Y.; Dedontney, N. L.; Rice, J. R.

2007-12-01

Rate and state friction, as applied to modeling subduction earthquake sequences, routinely predicts postseismic slip. It also predicts spontaneous aseismic slip transients, at least when pore pressure p is highly elevated near and downdip from the stability transition [Liu and Rice, 2007]. Here we address how to make such postseismic and transient predictions more fully compatible with geophysical observations. For example, lab observations can determine the a, b parameters and state evolution slip L of rate and state friction as functions of lithology and temperature and, with aid of a structural and thermal model of the subduction zone, as functions of downdip distance. Geodetic observations constrain interseismic, postseismic and aseismic transient deformations, which are controlled in the modeling by the distributions of a \\barσ and b \\barσ (parameters which also partly control the seismic rupture phase), where \\barσ = σ - p. Elevated p, controlled by tectonic compression and dehydration, may be constrained by petrologic and seismic observations. The amount of deformation and downdip extent of the slipping zone associated with the spontaneous quasi- periodic transients, as thus far modeled [Liu and Rice, 2007], is generally smaller than that observed during episodes of slow slip events in northern Cascadia and SW Japan subduction zones. However, the modeling was based on lab data for granite gouge under hydrothermal conditions because data is most complete for that case. We here report modeling based on lab data on dry granite gouge [Stesky, 1975; Lockner et al., 1986], involving no or lessened chemical interaction with water and hence being a possibly closer analog to dehydrated oceanic crust, and limited data on gabbro gouge [He et al., 2007], an expected lithology. Both data sets show a much less rapid increase of a-b with temperature above the stability transition (~ 350 °C) than does wet granite gouge; a-b increases to ~ 0.08 for wet granite at 600 °C, but to only ~ 0.01 in the dry granite and gabbro cases. We find that the lessened high-T a - b does, for the same \\barσ, modestly extend the transient slip episodes further downdip, although a majority of slip is still contributed near and in the updip rate-weakening region. However, postseismic slip, for the same \\barσ, propagates much further downdip into the rate-strengthening region. To better constrain the downdip distribution of (a - b) \\barσ, and possibly a \\barσ and L, we focus on the geodetically constrained [Hutton et al., 2001] space-time distribution of postseismic slip for the 1995 Mw = 8.0 Colima-Jalisco earthquake. This is a similarly shallow dipping subduction zone with a thermal profile [Currie et al., 2001] comparable to those that have thus far been shown to exhibit aseismic transients and non-volcanic tremor [Peacock et al., 2002]. We extrapolate the modeled 2-D postseismic slip, following a thrust earthquake with a coseismic slip similar to the 1995 event, to a spatial-temporal 3-D distribution. Surface deformation due to such slips on the thrust fault in an elastic half space is calculated and compared to that observed at western Mexico GPS stations, to constrain the above depth-variable model parameters.

Characterizing and modeling the free recovery and constrained recovery behavior of a polyurethane shape memory polymer

NASA Astrophysics Data System (ADS)

Volk, Brent L.; Lagoudas, Dimitris C.; Maitland, Duncan J.

2011-09-01

In this work, tensile tests and one-dimensional constitutive modeling were performed on a high recovery force polyurethane shape memory polymer that is being considered for biomedical applications. The tensile tests investigated the free recovery (zero load) response as well as the constrained displacement recovery (stress recovery) response at extension values up to 25%, and two consecutive cycles were performed during each test. The material was observed to recover 100% of the applied deformation when heated at zero load in the second thermomechanical cycle, and a stress recovery of 1.5-4.2 MPa was observed for the constrained displacement recovery experiments. After the experiments were performed, the Chen and Lagoudas model was used to simulate and predict the experimental results. The material properties used in the constitutive model—namely the coefficients of thermal expansion, shear moduli, and frozen volume fraction—were calibrated from a single 10% extension free recovery experiment. The model was then used to predict the material response for the remaining free recovery and constrained displacement recovery experiments. The model predictions match well with the experimental data.

Distinguishing between tectonic and lithologic controls on bedrock channel longitudinal profiles using cosmogenic 10Be erosion rates and channel steepness index

USGS Publications Warehouse

Cyr, Andrew J.; Granger, Darryl E.; Olivetti, Valerio; Molin, Paola

2014-01-01

Knickpoints in fluvial channel longitudinal profiles and channel steepness index values derived from digital elevation data can be used to detect tectonic structures and infer spatial patterns of uplift. However, changes in lithologic resistance to channel incision can also influence the morphology of longitudinal profiles. We compare the spatial patterns of both channel steepness index and cosmogenic 10Be-determined erosion rates from four landscapes in Italy, where the geology and tectonics are well constrained, to four theoretical predictions of channel morphologies, which can be interpreted as the result of primarily tectonic or lithologic controls. These data indicate that longitudinal profile forms controlled by unsteady or nonuniform tectonics can be distinguished from those controlled by nonuniform lithologic resistance. In each landscape the distribution of channel steepness index and erosion rates is consistent with model predictions and demonstrates that cosmogenic nuclide methods can be applied to distinguish between these two controlling factors.

Thermomechanical Fatigue of Ductile Cast Iron and Its Life Prediction

NASA Astrophysics Data System (ADS)

Wu, Xijia; Quan, Guangchun; MacNeil, Ryan; Zhang, Zhong; Liu, Xiaoyang; Sloss, Clayton

2015-06-01

Thermomechanical fatigue (TMF) behaviors of ductile cast iron (DCI) were investigated under out-of-phase (OP), in-phase (IP), and constrained strain-control conditions with temperature hold in various temperature ranges: 573 K to 1073 K, 723 K to 1073 K, and 433 K to 873 K (300 °C to 800 °C, 450 °C to 800 °C, and 160 °C to 600 °C). The integrated creep-fatigue theory (ICFT) model was incorporated into the finite element method to simulate the hysteresis behavior and predict the TMF life of DCI under those test conditions. With the consideration of four deformation/damage mechanisms: (i) plasticity-induced fatigue, (ii) intergranular embrittlement, (iii) creep, and (iv) oxidation, as revealed from the previous study on low cycle fatigue of the material, the model delineates the contributions of these physical mechanisms in the asymmetrical hysteresis behavior and the damage accumulation process leading to final TMF failure. This study shows that the ICFT model can simulate the stress-strain response and life of DCI under complex TMF loading profiles (OP and IP, and constrained with temperature hold).

Closed-Loop Control of Constrained Flapping Wing Micro Air Vehicles

DTIC Science & Technology

2014-03-27

insects , thus concealing their appearance while also providing benefits of unsteady aerodynamics. Consider- able research has been invested in the...small visibility signature that tends to hide in plain sight by resembling insects . 1.2 Research Challenges for Flapping Wing Micro Air Vehicles There are...predicts forces and moments for the class of flapping wing fliers that makes up most insects and hummingbirds. Large bird and butterfly “clap- and

Constraining climatic controls on hillslope dynamics using a coupled model for the transport of soil and tracers: Application to loess-mantled hillslopes, Charwell River, South Island, New Zealand

Treesearch

J.J. Roering; P. Almond; P. Tonkin; J. McKean

2004-01-01

Landscapes reflect a legacy of tectonic and climatic forcing as modulated by surface processes. Because the morphologic characteristics of landscapes often do not allow us to uniquely define the relative roles of tectonic deformation and climate, additional constraints are required to interpret and predict landscape dynamics. Here we describe a coupled model for the...

Cosmic shear as a probe of galaxy formation physics

DOE PAGES

Foreman, Simon; Becker, Matthew R.; Wechsler, Risa H.

2016-09-01

Here, we evaluate the potential for current and future cosmic shear measurements from large galaxy surveys to constrain the impact of baryonic physics on the matter power spectrum. We do so using a model-independent parametrization that describes deviations of the matter power spectrum from the dark-matter-only case as a set of principal components that are localized in wavenumber and redshift. We perform forecasts for a variety of current and future data sets, and find that at least ~90 per cent of the constraining power of these data sets is contained in no more than nine principal components. The constraining powermore » of different surveys can be quantified using a figure of merit defined relative to currently available surveys. With this metric, we find that the final Dark Energy Survey data set (DES Y5) and the Hyper Suprime-Cam Survey will be roughly an order of magnitude more powerful than existing data in constraining baryonic effects. Upcoming Stage IV surveys (Large Synoptic Survey Telescope, Euclid, and Wide Field Infrared Survey Telescope) will improve upon this by a further factor of a few. We show that this conclusion is robust to marginalization over several key systematics. The ultimate power of cosmic shear to constrain galaxy formation is dependent on understanding systematics in the shear measurements at small (sub-arcminute) scales. Lastly, if these systematics can be sufficiently controlled, cosmic shear measurements from DES Y5 and other future surveys have the potential to provide a very clean probe of galaxy formation and to strongly constrain a wide range of predictions from modern hydrodynamical simulations.« less

Analysis of explicit model predictive control for path-following control

PubMed Central

2018-01-01

In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits the range of its target application to relatively small and/or slow problems. Explicit MPC can reduce this computational burden using a multi-parametric quadratic programming technique(mp-QP). The control objective is to derive an optimal front steering wheel angle at each sampling time so that autonomous vehicles travel along desired paths, including straight, circular, and clothoid parts, at high entry speeds. In terms of the design of the proposed controller, a method of choosing weighting matrices in an optimization problem and the range of horizons for path-following control are described through simulations. For the verification of the proposed controller, simulation results obtained using other control methods such as MPC, Linear-Quadratic Regulator(LQR), and driver model are employed, and CarSim, which reflects the features of a vehicle more realistically than MATLAB/Simulink, is used for reliable demonstration. PMID:29534080

Analysis of explicit model predictive control for path-following control.

PubMed

Lee, Junho; Chang, Hyuk-Jun

2018-01-01

In this paper, explicit Model Predictive Control(MPC) is employed for automated lane-keeping systems. MPC has been regarded as the key to handle such constrained systems. However, the massive computational complexity of MPC, which employs online optimization, has been a major drawback that limits the range of its target application to relatively small and/or slow problems. Explicit MPC can reduce this computational burden using a multi-parametric quadratic programming technique(mp-QP). The control objective is to derive an optimal front steering wheel angle at each sampling time so that autonomous vehicles travel along desired paths, including straight, circular, and clothoid parts, at high entry speeds. In terms of the design of the proposed controller, a method of choosing weighting matrices in an optimization problem and the range of horizons for path-following control are described through simulations. For the verification of the proposed controller, simulation results obtained using other control methods such as MPC, Linear-Quadratic Regulator(LQR), and driver model are employed, and CarSim, which reflects the features of a vehicle more realistically than MATLAB/Simulink, is used for reliable demonstration.

Multidisciplinary Optimization Approach for Design and Operation of Constrained and Complex-shaped Space Systems

NASA Astrophysics Data System (ADS)

Lee, Dae Young

The design of a small satellite is challenging since they are constrained by mass, volume, and power. To mitigate these constraint effects, designers adopt deployable configurations on the spacecraft that result in an interesting and difficult optimization problem. The resulting optimization problem is challenging due to the computational complexity caused by the large number of design variables and the model complexity created by the deployables. Adding to these complexities, there is a lack of integration of the design optimization systems into operational optimization, and the utility maximization of spacecraft in orbit. The developed methodology enables satellite Multidisciplinary Design Optimization (MDO) that is extendable to on-orbit operation. Optimization of on-orbit operations is possible with MDO since the model predictive controller developed in this dissertation guarantees the achievement of the on-ground design behavior in orbit. To enable the design optimization of highly constrained and complex-shaped space systems, the spherical coordinate analysis technique, called the "Attitude Sphere", is extended and merged with an additional engineering tools like OpenGL. OpenGL's graphic acceleration facilitates the accurate estimation of the shadow-degraded photovoltaic cell area. This technique is applied to the design optimization of the satellite Electric Power System (EPS) and the design result shows that the amount of photovoltaic power generation can be increased more than 9%. Based on this initial methodology, the goal of this effort is extended from Single Discipline Optimization to Multidisciplinary Optimization, which includes the design and also operation of the EPS, Attitude Determination and Control System (ADCS), and communication system. The geometry optimization satisfies the conditions of the ground development phase; however, the operation optimization may not be as successful as expected in orbit due to disturbances. To address this issue, for the ADCS operations, controllers based on Model Predictive Control that are effective for constraint handling were developed and implemented. All the suggested design and operation methodologies are applied to a mission "CADRE", which is space weather mission scheduled for operation in 2016. This application demonstrates the usefulness and capability of the methodology to enhance CADRE's capabilities, and its ability to be applied to a variety of missions.

Constraining 3-PG with a new δ13C submodel: a test using the δ13C of tree rings.

PubMed

Wei, Liang; Marshall, John D; Link, Timothy E; Kavanagh, Kathleen L; DU, Enhao; Pangle, Robert E; Gag, Peter J; Ubierna, Nerea

2014-01-01

A semi-mechanistic forest growth model, 3-PG (Physiological Principles Predicting Growth), was extended to calculate δ(13)C in tree rings. The δ(13)C estimates were based on the model's existing description of carbon assimilation and canopy conductance. The model was tested in two ~80-year-old natural stands of Abies grandis (grand fir) in northern Idaho. We used as many independent measurements as possible to parameterize the model. Measured parameters included quantum yield, specific leaf area, soil water content and litterfall rate. Predictions were compared with measurements of transpiration by sap flux, stem biomass, tree diameter growth, leaf area index and δ(13)C. Sensitivity analysis showed that the model's predictions of δ(13)C were sensitive to key parameters controlling carbon assimilation and canopy conductance, which would have allowed it to fail had the model been parameterized or programmed incorrectly. Instead, the simulated δ(13)C of tree rings was no different from measurements (P > 0.05). The δ(13)C submodel provides a convenient means of constraining parameter space and avoiding model artefacts. This δ(13)C test may be applied to any forest growth model that includes realistic simulations of carbon assimilation and transpiration. © 2013 John Wiley & Sons Ltd.

Conditional Entropy-Constrained Residual VQ with Application to Image Coding

NASA Technical Reports Server (NTRS)

Kossentini, Faouzi; Chung, Wilson C.; Smith, Mark J. T.

1996-01-01

This paper introduces an extension of entropy-constrained residual vector quantization (VQ) where intervector dependencies are exploited. The method, which we call conditional entropy-constrained residual VQ, employs a high-order entropy conditioning strategy that captures local information in the neighboring vectors. When applied to coding images, the proposed method is shown to achieve better rate-distortion performance than that of entropy-constrained residual vector quantization with less computational complexity and lower memory requirements. Moreover, it can be designed to support progressive transmission in a natural way. It is also shown to outperform some of the best predictive and finite-state VQ techniques reported in the literature. This is due partly to the joint optimization between the residual vector quantizer and a high-order conditional entropy coder as well as the efficiency of the multistage residual VQ structure and the dynamic nature of the prediction.

Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

PubMed

Medvigy, David; Moorcroft, Paul R

2012-01-19

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

Fusing human and machine skills for remote robotic operations

NASA Technical Reports Server (NTRS)

Schenker, Paul S.; Kim, Won S.; Venema, Steven C.; Bejczy, Antal K.

1991-01-01

The question of how computer assists can improve teleoperator trajectory tracking during both free and force-constrained motions is addressed. Computer graphics techniques which enable the human operator to both visualize and predict detailed 3D trajectories in real-time are reported. Man-machine interactive control procedures for better management of manipulator contact forces and positioning are also described. It is found that collectively, these novel advanced teleoperations techniques both enhance system performance and significantly reduce control problems long associated with teleoperations under time delay. Ongoing robotic simulations of the 1984 space shuttle Solar Maximum EVA Repair Mission are briefly described.

The in situ transverse lamina strength of composite laminates

NASA Technical Reports Server (NTRS)

Flaggs, D. L.

1983-01-01

The objective of the work reported in this presentation is to determine the in situ transverse strength of a lamina within a composite laminate. From a fracture mechanics standpoint, in situ strength may be viewed as constrained cracking that has been shown to be a function of both lamina thickness and the stiffness of adjacent plies that serve to constrain the cracking process. From an engineering point of view, however, constrained cracking can be perceived as an apparent increase in lamina strength. With the growing need to design more highly loaded composite structures, the concept of in situ strength may prove to be a viable means of increasing the design allowables of current and future composite material systems. A simplified one dimensional analytical model is presented that is used to predict the strain at onset of transverse cracking. While it is accurate only for the most constrained cases, the model is important in that the predicted failure strain is seen to be a function of a lamina's thickness d and of the extensional stiffness bE theta of the adjacent laminae that constrain crack propagation in the 90 deg laminae.

Working-memory capacity predicts the executive control of visual search among distractors: the influences of sustained and selective attention.

PubMed

Poole, Bradley J; Kane, Michael J

2009-07-01

Variation in working-memory capacity (WMC) predicts individual differences in only some attention-control capabilities. Whereas higher WMC subjects outperform lower WMC subjects in tasks requiring the restraint of prepotent but inappropriate responses, and the constraint of attentional focus to target stimuli against distractors, they do not differ in prototypical visual-search tasks, even those that yield steep search slopes and engender top-down control. The present three experiments tested whether WMC, as measured by complex memory span tasks, would predict search latencies when the 1-8 target locations to be searched appeared alone, versus appearing among distractor locations to be ignored, with the latter requiring selective attentional focus. Subjects viewed target-location cues and then fixated on those locations over either long (1,500-1,550 ms) or short (300 ms) delays. Higher WMC subjects identified targets faster than did lower WMC subjects only in the presence of distractors and only over long fixation delays. WMC thus appears to affect subjects' ability to maintain a constrained attentional focus over time.

Simulations of Water Migration in the Lunar Exosphere

NASA Astrophysics Data System (ADS)

Hurley, D.; Benna, M.; Mahaffy, P. R.; Elphic, R. C.; Goldstein, D. B.

2014-12-01

We perform modeling and analysis of water in the lunar exosphere. There were two controlled experiments of water interactions with the surface of the Moon observed by the Lunar Atmosphere and Dust Environment Explorer (LADEE) Neutral Mass Spectrometer (NMS). The Chang'e 3 landing on the Moon on 14 Dec 2013 putatively sprayed ~120 kg of water on the surface on the Moon at a mid-morning local time. Observations by LADEE near the noon meridian on six of the orbits in the 24 hours following the landing constrain the propagation of water vapor. Further, on 4 Apr 2014, LADEE's Orbital Maintenance Manuever (OMM) #21 sprayed the surface of the Moon with an estimated 0.73 kg of water in the pre-dawn sector. Observations of this maneuver and later in the day constrain the adsorption and release at dawn of adsorbed materials. Using the Chang'e 3 exhaust plume and LADEE's OMM-21 as control experiments, we set limits to the adsorption and thermalization of water with lunar regolith. This enables us to predict the efficiency of the migration of water as a delivery mechanism to the lunar poles. Then we simulate the migration of water through the lunar exosphere using the rate of sporadic inputs from meteoritic sources (Benna et al., this session). Simulations predict the amount of water adsorbed to the surface of the Moon and the effective delivery rate to the lunar polar cold traps.

Characterizing and modeling the free recovery and constrained recovery behavior of a polyurethane shape memory polymer

PubMed Central

Volk, Brent L; Lagoudas, Dimitris C; Maitland, Duncan J

2011-01-01

In this work, tensile tests and one-dimensional constitutive modeling are performed on a high recovery force polyurethane shape memory polymer that is being considered for biomedical applications. The tensile tests investigate the free recovery (zero load) response as well as the constrained displacement recovery (stress recovery) response at extension values up to 25%, and two consecutive cycles are performed during each test. The material is observed to recover 100% of the applied deformation when heated at zero load in the second thermomechanical cycle, and a stress recovery of 1.5 MPa to 4.2 MPa is observed for the constrained displacement recovery experiments. After performing the experiments, the Chen and Lagoudas model is used to simulate and predict the experimental results. The material properties used in the constitutive model – namely the coefficients of thermal expansion, shear moduli, and frozen volume fraction – are calibrated from a single 10% extension free recovery experiment. The model is then used to predict the material response for the remaining free recovery and constrained displacement recovery experiments. The model predictions match well with the experimental data. PMID:22003272

Design of sidewall treatment of cabin noise control of a twin engine turboprop aircraft

NASA Technical Reports Server (NTRS)

Vaicaitis, R.; Slazak, M.

1983-01-01

An analytical procedure was used to predict the noise transmission into the cabin of a twin engine general aviation aircraft. This model was then used to optimize the interior A weighted noise levels to an average value of about 85 dBA. The surface pressure noise spectral levels were selected utilizing experimental flight data and empirical predictions. The add on treatments considered in this optimization study include aluminum honeycomb panels, constrained layer damping tape, porous acoustic blankets, acoustic foams, septum barriers and limp trim panels which are isolated from the vibration of the main sidewall structure. To reduce the average noise level in the cabin from about 102 kBA (baseline) to 85 dBA (optimized), the added weight of the noise control treatment is about 2% of the total gross takeoff weight of the aircraft.

Design of sidewall treatment of cabin noise control of a twin engine turboprop aircraft

NASA Astrophysics Data System (ADS)

Vaicaitis, R.; Slazak, M.

1983-12-01

An analytical procedure was used to predict the noise transmission into the cabin of a twin engine general aviation aircraft. This model was then used to optimize the interior A weighted noise levels to an average value of about 85 dBA. The surface pressure noise spectral levels were selected utilizing experimental flight data and empirical predictions. The add on treatments considered in this optimization study include aluminum honeycomb panels, constrained layer damping tape, porous acoustic blankets, acoustic foams, septum barriers and limp trim panels which are isolated from the vibration of the main sidewall structure. To reduce the average noise level in the cabin from about 102 kBA (baseline) to 85 dBA (optimized), the added weight of the noise control treatment is about 2% of the total gross takeoff weight of the aircraft.

Prediction in a visual language: real-time sentence processing in American Sign Language across development.

PubMed

Lieberman, Amy M; Borovsky, Arielle; Mayberry, Rachel I

2018-01-01

Prediction during sign language comprehension may enable signers to integrate linguistic and non-linguistic information within the visual modality. In two eyetracking experiments, we investigated American Sign language (ASL) semantic prediction in deaf adults and children (aged 4-8 years). Participants viewed ASL sentences in a visual world paradigm in which the sentence-initial verb was either neutral or constrained relative to the sentence-final target noun. Adults and children made anticipatory looks to the target picture before the onset of the target noun in the constrained condition only, showing evidence for semantic prediction. Crucially, signers alternated gaze between the stimulus sign and the target picture only when the sentential object could be predicted from the verb. Signers therefore engage in prediction by optimizing visual attention between divided linguistic and referential signals. These patterns suggest that prediction is a modality-independent process, and theoretical implications are discussed.

Balancing computation and communication power in power constrained clusters

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

Piga, Leonardo; Paul, Indrani; Huang, Wei

Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agentmore » may be configured to reassign the unused power to the active nodes to expedite workload processing.« less

Active constrained layer damping treatments for shell structures: a deep-shell theory, some intuitive results, and an energy analysis

NASA Astrophysics Data System (ADS)

Shen, I. Y.

1997-02-01

This paper studies vibration control of a shell structure through use of an active constrained layer (ACL) damping treatment. A deep-shell theory that assumes arbitrary Lamé parameters 0964-1726/6/1/011/img1 and 0964-1726/6/1/011/img2 is first developed. Application of Hamilton's principle leads to the governing Love equations, the charge equation of electrostatics, and the associated boundary conditions. The Love equations and boundary conditions imply that the control action of the ACL for shell treatments consists of two components: free-end boundary actuation and membrane actuation. The free-end boundary actuation is identical to that of beam and plate ACL treatments, while the membrane actuation is unique to shell treatments as a result of the curvatures of the shells. In particular, the membrane actuation may reinforce or counteract the boundary actuation, depending on the location of the ACL treatment. Finally, an energy analysis is developed to determine the proper control law that guarantees the stability of ACL shell treatments. Moreover, the energy analysis results in a simple rule predicting whether or not the membrane actuation reinforces the boundary actuation.

Lithospheric strength of Ganymede: Clues to early thermal profiles from extensional tectonic features

NASA Technical Reports Server (NTRS)

Golombek, M. P.; Banerdt, W. B.

1985-01-01

While it is generally agreed that the strength of a planet's lithosphere is controlled by a combination of brittle sliding and ductile flow laws, predicting the geometry and initial characteristics of faults due to failure from stresses imposed on the lithospheric strength envelope has not been thoroughly explored. Researchers used lithospheric strength envelopes to analyze the extensional features found on Ganymede. This application provides a quantitative means of estimating early thermal profiles on Ganymede, thereby constraining its early thermal evolution.

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

Dall-Anese, Emiliano; Simonetto, Andrea

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 establishedmore » to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.« less

Vibration control of multiferroic fibrous composite plates using active constrained layer damping

NASA Astrophysics Data System (ADS)

Kattimani, S. C.; Ray, M. C.

2018-06-01

Geometrically nonlinear vibration control of fiber reinforced magneto-electro-elastic or multiferroic fibrous composite plates using active constrained layer damping treatment has been investigated. The piezoelectric (BaTiO3) fibers are embedded in the magnetostrictive (CoFe2O4) matrix forming magneto-electro-elastic or multiferroic smart composite. A three-dimensional finite element model of such fiber reinforced magneto-electro-elastic plates integrated with the active constrained layer damping patches is developed. Influence of electro-elastic, magneto-elastic and electromagnetic coupled fields on the vibration has been studied. The Golla-Hughes-McTavish method in time domain is employed for modeling a constrained viscoelastic layer of the active constrained layer damping treatment. The von Kármán type nonlinear strain-displacement relations are incorporated for developing a three-dimensional finite element model. Effect of fiber volume fraction, fiber orientation and boundary conditions on the control of geometrically nonlinear vibration of the fiber reinforced magneto-electro-elastic plates is investigated. The performance of the active constrained layer damping treatment due to the variation of piezoelectric fiber orientation angle in the 1-3 Piezoelectric constraining layer of the active constrained layer damping treatment has also been emphasized.

The design of multirate digital control systems

NASA Technical Reports Server (NTRS)

Berg, M. C.

1986-01-01

The successive loop closures synthesis method is the only method for multirate (MR) synthesis in common use. A new method for MR synthesis is introduced which requires a gradient-search solution to a constrained optimization problem. Some advantages of this method are that the control laws for all control loops are synthesized simultaneously, taking full advantage of all cross-coupling effects, and that simple, low-order compensator structures are easily accomodated. The algorithm and associated computer program for solving the constrained optimization problem are described. The successive loop closures , optimal control, and constrained optimization synthesis methods are applied to two example design problems. A series of compensator pairs are synthesized for each example problem. The succesive loop closure, optimal control, and constrained optimization synthesis methods are compared, in the context of the two design problems.

Constraining the Mechanism of D" Anisotropy: Diversity of Observation Types Required

NASA Astrophysics Data System (ADS)

Creasy, N.; Pisconti, A.; Long, M. D.; Thomas, C.

2017-12-01

A variety of different mechanisms have been proposed as explanations for seismic anisotropy at the base of the mantle, including crystallographic preferred orientation of various minerals (bridgmanite, post-perovskite, and ferropericlase) and shape preferred orientation of elastically distinct materials such as partial melt. Investigations of the mechanism for D" anisotropy are usually ambiguous, as seismic observations rarely (if ever) uniquely constrain a mechanism. Observations of shear wave splitting and polarities of SdS and PdP reflections off the D" discontinuity are among our best tools for probing D" anisotropy; however, typical data sets cannot constrain a unique scenario suggested by the mineral physics literature. In this work, we determine what types of body wave observations are required to uniquely constrain a mechanism for D" anisotropy. We test multiple possible models based on both single-crystal and poly-phase elastic tensors provided by mineral physics studies. We predict shear wave splitting parameters for SKS, SKKS, and ScS phases and reflection polarities off the D" interface for a range of possible propagation directions. We run a series of tests that create synthetic data sets by random selection over multiple iterations, controlling the total number of measurements, the azimuthal distribution, and the type of phases. We treat each randomly drawn synthetic dataset with the same methodology as in Ford et al. (2015) to determine the possible mechanism(s), carrying out a grid search over all possible elastic tensors and orientations to determine which are consistent with the synthetic data. We find is it difficult to uniquely constrain the starting model with a realistic number of seismic anisotropy measurements with only one measurement technique or phase type. However, having a mix of SKS, SKKS, and ScS measurements, or a mix of shear wave splitting and reflection polarity measurements, dramatically increases the probability of uniquely constraining the starting model. We also explore what types of datasets are needed to uniquely constrain the orientation(s) of anisotropic symmetry if the mechanism is assumed.

Chance-Constrained AC Optimal Power Flow for Distribution Systems With Renewables

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

DallAnese, Emiliano; Baker, Kyri; Summers, Tyler

This paper focuses on distribution systems featuring renewable energy sources (RESs) and energy storage systems, and presents an AC optimal power flow (OPF) approach to optimize system-level performance objectives while coping with uncertainty in both RES generation and loads. The proposed method hinges on a chance-constrained AC OPF formulation where probabilistic constraints are utilized to enforce voltage regulation with prescribed probability. A computationally more affordable convex reformulation is developed by resorting to suitable linear approximations of the AC power-flow equations as well as convex approximations of the chance constraints. The approximate chance constraints provide conservative bounds that hold for arbitrarymore » distributions of the forecasting errors. An adaptive strategy is then obtained by embedding the proposed AC OPF task into a model predictive control framework. Finally, a distributed solver is developed to strategically distribute the solution of the optimization problems across utility and customers.« less

Trajectory-Based Takeoff Time Predictions Applied to Tactical Departure Scheduling: Concept Description, System Design, and Initial Observations

NASA Technical Reports Server (NTRS)

Engelland, Shawn A.; Capps, Alan

2011-01-01

Current aircraft departure release times are based on manual estimates of aircraft takeoff times. Uncertainty in takeoff time estimates may result in missed opportunities to merge into constrained en route streams and lead to lost throughput. However, technology exists to improve takeoff time estimates by using the aircraft surface trajectory predictions that enable air traffic control tower (ATCT) decision support tools. NASA s Precision Departure Release Capability (PDRC) is designed to use automated surface trajectory-based takeoff time estimates to improve en route tactical departure scheduling. This is accomplished by integrating an ATCT decision support tool with an en route tactical departure scheduling decision support tool. The PDRC concept and prototype software have been developed, and an initial test was completed at air traffic control facilities in Dallas/Fort Worth. This paper describes the PDRC operational concept, system design, and initial observations.

Control of Warm Compression Stations Using Model Predictive Control: Simulation and Experimental Results

NASA Astrophysics Data System (ADS)

Bonne, F.; Alamir, M.; Bonnay, P.

2017-02-01

This paper deals with multivariable constrained model predictive control for Warm Compression Stations (WCS). WCSs are subject to numerous constraints (limits on pressures, actuators) that need to be satisfied using appropriate algorithms. The strategy is to replace all the PID loops controlling the WCS with an optimally designed model-based multivariable loop. This new strategy leads to high stability and fast disturbance rejection such as those induced by a turbine or a compressor stop, a key-aspect in the case of large scale cryogenic refrigeration. The proposed control scheme can be used to achieve precise control of pressures in normal operation or to avoid reaching stopping criteria (such as excessive pressures) under high disturbances (such as a pulsed heat load expected to take place in future fusion reactors, expected in the cryogenic cooling systems of the International Thermonuclear Experimental Reactor ITER or the Japan Torus-60 Super Advanced fusion experiment JT-60SA). The paper details the simulator used to validate this new control scheme and the associated simulation results on the SBTs WCS. This work is partially supported through the French National Research Agency (ANR), task agreement ANR-13-SEED-0005.

Thermodynamic Constraints Improve Metabolic Networks.

PubMed

Krumholz, Elias W; Libourel, Igor G L

2017-08-08

In pursuit of establishing a realistic metabolic phenotypic space, the reversibility of reactions is thermodynamically constrained in modern metabolic networks. The reversibility constraints follow from heuristic thermodynamic poise approximations that take anticipated cellular metabolite concentration ranges into account. Because constraints reduce the feasible space, draft metabolic network reconstructions may need more extensive reconciliation, and a larger number of genes may become essential. Notwithstanding ubiquitous application, the effect of reversibility constraints on the predictive capabilities of metabolic networks has not been investigated in detail. Instead, work has focused on the implementation and validation of the thermodynamic poise calculation itself. With the advance of fast linear programming-based network reconciliation, the effects of reversibility constraints on network reconciliation and gene essentiality predictions have become feasible and are the subject of this study. Networks with thermodynamically informed reversibility constraints outperformed gene essentiality predictions compared to networks that were constrained with randomly shuffled constraints. Unconstrained networks predicted gene essentiality as accurately as thermodynamically constrained networks, but predicted substantially fewer essential genes. Networks that were reconciled with sequence similarity data and strongly enforced reversibility constraints outperformed all other networks. We conclude that metabolic network analysis confirmed the validity of the thermodynamic constraints, and that thermodynamic poise information is actionable during network reconciliation. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

CCTOP: a Consensus Constrained TOPology prediction web server.

PubMed

Dobson, László; Reményi, István; Tusnády, Gábor E

2015-07-01

The Consensus Constrained TOPology prediction (CCTOP; http://cctop.enzim.ttk.mta.hu) server is a web-based application providing transmembrane topology prediction. In addition to utilizing 10 different state-of-the-art topology prediction methods, the CCTOP server incorporates topology information from existing experimental and computational sources available in the PDBTM, TOPDB and TOPDOM databases using the probabilistic framework of hidden Markov model. The server provides the option to precede the topology prediction with signal peptide prediction and transmembrane-globular protein discrimination. The initial result can be recalculated by (de)selecting any of the prediction methods or mapped experiments or by adding user specified constraints. CCTOP showed superior performance to existing approaches. The reliability of each prediction is also calculated, which correlates with the accuracy of the per protein topology prediction. The prediction results and the collected experimental information are visualized on the CCTOP home page and can be downloaded in XML format. Programmable access of the CCTOP server is also available, and an example of client-side script is provided. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Parametric study of the physical properties of hydrate-bearing sand, silt, and clay sediments: 1. Electromagnetic properties

USGS Publications Warehouse

Lee, J.Y.; Santamarina, J.C.; Ruppel, C.

2010-01-01

The marked decrease in bulk electrical conductivity of sediments in the presence of gas hydrates has been used to interpret borehole electrical resistivity logs and, to a lesser extent, the results of controlled source electromagnetic surveys to constrain the spatial distribution and predicted concentration of gas hydrate in natural settings. Until now, an exhaustive laboratory data set that could be used to assess the impact of gas hydrate on the electromagnetic properties of different soils (sand, silt, and clay) at different effective stress and with different saturations of hydrate has been lacking. The laboratory results reported here are obtained using a standard geotechnical cell and the hydrate-formed tetrahydrofuran (THF), a liquid that is fully miscible in water and able to produce closely controlled saturations of hydrate from dissolved phase. Both permittivity and electrical conductivity are good indicators of the volume fraction of free water in the sediment, which is in turn dependent on hydrate saturation. Permittivity in the microwave frequency range is particularly predictive of free water content since it is barely affected by ionic concentration, pore structure, and surface conduction. Electrical conductivity (or resistivity) is less reliable for constraining water content or hydrate saturation: In addition to fluid-filled porosity, other factors, such as the ionic concentration of the pore fluid and possibly other conduction effects (e.g., surface conduction in high specific surface soils having low conductivity pore fluid), also influence electrical conductivity.

Constrained target controllability of complex networks

NASA Astrophysics Data System (ADS)

Guo, Wei-Feng; Zhang, Shao-Wu; Wei, Ze-Gang; Zeng, Tao; Liu, Fei; Zhang, Jingsong; Wu, Fang-Xiang; Chen, Luonan

2017-06-01

It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

Minimal complexity control law synthesis

NASA Technical Reports Server (NTRS)

Bernstein, Dennis S.; Haddad, Wassim M.; Nett, Carl N.

1989-01-01

A paradigm for control law design for modern engineering systems is proposed: Minimize control law complexity subject to the achievement of a specified accuracy in the face of a specified level of uncertainty. Correspondingly, the overall goal is to make progress towards the development of a control law design methodology which supports this paradigm. Researchers achieve this goal by developing a general theory of optimal constrained-structure dynamic output feedback compensation, where here constrained-structure means that the dynamic-structure (e.g., dynamic order, pole locations, zero locations, etc.) of the output feedback compensation is constrained in some way. By applying this theory in an innovative fashion, where here the indicated iteration occurs over the choice of the compensator dynamic-structure, the paradigm stated above can, in principle, be realized. The optimal constrained-structure dynamic output feedback problem is formulated in general terms. An elegant method for reducing optimal constrained-structure dynamic output feedback problems to optimal static output feedback problems is then developed. This reduction procedure makes use of star products, linear fractional transformations, and linear fractional decompositions, and yields as a byproduct a complete characterization of the class of optimal constrained-structure dynamic output feedback problems which can be reduced to optimal static output feedback problems. Issues such as operational/physical constraints, operating-point variations, and processor throughput/memory limitations are considered, and it is shown how anti-windup/bumpless transfer, gain-scheduling, and digital processor implementation can be facilitated by constraining the controller dynamic-structure in an appropriate fashion.

Configuration of the thermal landscape determines thermoregulatory performance of ectotherms

PubMed Central

Sears, Michael W.; Angilletta, Michael J.; Schuler, Matthew S.; Borchert, Jason; Dilliplane, Katherine F.; Stegman, Monica; Rusch, Travis W.; Mitchell, William A.

2016-01-01

Although most organisms thermoregulate behaviorally, biologists still cannot easily predict whether mobile animals will thermoregulate in natural environments. Current models fail because they ignore how the spatial distribution of thermal resources constrains thermoregulatory performance over space and time. To overcome this limitation, we modeled the spatially explicit movements of animals constrained by access to thermal resources. Our models predict that ectotherms thermoregulate more accurately when thermal resources are dispersed throughout space than when these resources are clumped. This prediction was supported by thermoregulatory behaviors of lizards in outdoor arenas with known distributions of environmental temperatures. Further, simulations showed how the spatial structure of the landscape qualitatively affects responses of animals to climate. Biologists will need spatially explicit models to predict impacts of climate change on local scales. PMID:27601639

Inverse and Predictive Modeling

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

Syracuse, Ellen Marie

The LANL Seismo-Acoustic team has a strong capability in developing data-driven models that accurately predict a variety of observations. These models range from the simple – one-dimensional models that are constrained by a single dataset and can be used for quick and efficient predictions – to the complex – multidimensional models that are constrained by several types of data and result in more accurate predictions. Team members typically build models of geophysical characteristics of Earth and source distributions at scales of 1 to 1000s of km, the techniques used are applicable for other types of physical characteristics at an evenmore » greater range of scales. The following cases provide a snapshot of some of the modeling work done by the Seismo- Acoustic team at LANL.« less

Phase-field model of domain structures in ferroelectric thin films

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

Li, Y. L.; Hu, S. Y.; Liu, Z. K.

A phase-field model for predicting the coherent microstructure evolution in constrained thin films is developed. It employs an analytical elastic solution derived for a constrained film with arbitrary eigenstrain distributions. The domain structure evolution during a cubic{r_arrow}tetragonal proper ferroelectric phase transition is studied. It is shown that the model is able to simultaneously predict the effects of substrate constraint and temperature on the volume fractions of domain variants, domain-wall orientations, domain shapes, and their temporal evolution. {copyright} 2001 American Institute of Physics.

Common Crime and Domestic Violence Victimization of Older Chinese in Urban China: The Prevalence and Its Impact on Mental Health and Constrained Behavior.

PubMed

Qin, Nan; Yan, Elsie

2018-03-01

This article examines the prevalence of victimization among older Chinese living in urban China and its psychological and behavioral impacts. A representative sample of 453 older adults aged 60 or above was recruited from Kunming, the People's Republic of China, using multistage sampling method. Participants were individually interviewed on their demographic characteristics, experience of common crime and domestic violence victimization, fear of common crime and domestic violence, mental health, and constrained behavior. Results showed that 254 participants (56.1%) reported one or more types of common crime and 21 (4.6%) reported experiencing domestic violence in the past. Seventeen participants (3.8%) reportedly experienced both common crime and domestic violence victimization. There was no gender difference in the overall incidence of victimization but in some subtypes. Regression analyses indicated that past experience of common crime victimization was significantly associated with greater fear of common crime (β = .136, p = .004), poorer mental health (β = .136, p = .003), and more constrained behavior (β = .108, p = .025). Fear of common crime predicted increased constrained behavior (β = .240, p < .001) independent of gender, age, education, household finances, living arrangement, and physical health. Domestic violence victimization was not significant in predicting poor mental health and constrained behavior but was significant in predicting fear of domestic violence (β = .266, p < .001), which was related to poorer mental health (β = .102, p = .039). The study suggests the importance of taking older people's risk and experience of victimization into consideration in gerontological research, practice, and policymaking.

Fault tolerant and lifetime control architecture for autonomous vehicles

NASA Astrophysics Data System (ADS)

Bogdanov, Alexander; Chen, Yi-Liang; Sundareswaran, Venkataraman; Altshuler, Thomas

2008-04-01

Increased vehicle autonomy, survivability and utility can provide an unprecedented impact on mission success and are one of the most desirable improvements for modern autonomous vehicles. We propose a general architecture of intelligent resource allocation, reconfigurable control and system restructuring for autonomous vehicles. The architecture is based on fault-tolerant control and lifetime prediction principles, and it provides improved vehicle survivability, extended service intervals, greater operational autonomy through lower rate of time-critical mission failures and lesser dependence on supplies and maintenance. The architecture enables mission distribution, adaptation and execution constrained on vehicle and payload faults and desirable lifetime. The proposed architecture will allow managing missions more efficiently by weighing vehicle capabilities versus mission objectives and replacing the vehicle only when it is necessary.

Adaptive Fuzzy Output Constrained Control Design for Multi-Input Multioutput Stochastic Nonstrict-Feedback Nonlinear Systems.

PubMed

Li, Yongming; Tong, Shaocheng

2017-12-01

In this paper, an adaptive fuzzy output constrained control design approach is addressed for multi-input multioutput uncertain stochastic nonlinear systems in nonstrict-feedback form. The nonlinear systems addressed in this paper possess unstructured uncertainties, unknown gain functions and unknown stochastic disturbances. Fuzzy logic systems are utilized to tackle the problem of unknown nonlinear uncertainties. The barrier Lyapunov function technique is employed to solve the output constrained problem. In the framework of backstepping design, an adaptive fuzzy control design scheme is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Sensitivity of Space Station alpha joint robust controller to structural modal parameter variations

NASA Technical Reports Server (NTRS)

Kumar, Renjith R.; Cooper, Paul A.; Lim, Tae W.

1991-01-01

The photovoltaic array sun tracking control system of Space Station Freedom is described. A synthesis procedure for determining optimized values of the design variables of the control system is developed using a constrained optimization technique. The synthesis is performed to provide a given level of stability margin, to achieve the most responsive tracking performance, and to meet other design requirements. Performance of the baseline design, which is synthesized using predicted structural characteristics, is discussed and the sensitivity of the stability margin is examined for variations of the frequencies, mode shapes and damping ratios of dominant structural modes. The design provides enough robustness to tolerate a sizeable error in the predicted modal parameters. A study was made of the sensitivity of performance indicators as the modal parameters of the dominant modes vary. The design variables are resynthesized for varying modal parameters in order to achieve the most responsive tracking performance while satisfying the design requirements. This procedure of reoptimization design parameters would be useful in improving the control system performance if accurate model data are provided.

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

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

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

DOE PAGES

Thomas, R. Quinn; Brooks, Evan B.; Jersild, Annika L.; ...

2017-07-26

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions,more » DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO 2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 10 5 km 2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO 2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO 2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO 2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO 2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.« less

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

NASA Astrophysics Data System (ADS)

Quinn Thomas, R.; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; Gonzalez-Benecke, Carlos A.; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O.

2017-07-01

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model-data fusion, allows the use of past observations to constrain model parameters and estimate prediction uncertainty. Data assimilation (DA) focused on the regional scale has the opportunity to integrate data from both environmental gradients and experimental studies to constrain model parameters. Here, we introduce a hierarchical Bayesian DA approach (Data Assimilation to Predict Productivity for Ecosystems and Regions, DAPPER) that uses observations of carbon stocks, carbon fluxes, water fluxes, and vegetation dynamics from loblolly pine plantation ecosystems across the southeastern US to constrain parameters in a modified version of the Physiological Principles Predicting Growth (3-PG) forest growth model. The observations included major experiments that manipulated atmospheric carbon dioxide (CO2) concentration, water, and nutrients, along with nonexperimental surveys that spanned environmental gradients across an 8.6 × 105 km2 region. We optimized regionally representative posterior distributions for model parameters, which dependably predicted data from plots withheld from the data assimilation. While the mean bias in predictions of nutrient fertilization experiments, irrigation experiments, and CO2 enrichment experiments was low, future work needs to focus modifications to model structures that decrease the bias in predictions of drought experiments. Predictions of how growth responded to elevated CO2 strongly depended on whether ecosystem experiments were assimilated and whether the assimilated field plots in the CO2 study were allowed to have different mortality parameters than the other field plots in the region. We present predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

A receding horizon sliding control approach for electric powertrains with backlash and flexible half-shafts

NASA Astrophysics Data System (ADS)

Li, Yutong; Hansen, Andreas; Karl Hedrick, J.; Zhang, Junzhi

2017-12-01

Active control of electric powertrains is challenging, due to the fact that backlash and structural flexibility in transmission components can cause severe performance degradation or even instability of the control system. Furthermore, high impact forces in transmissions reduce driving comfort and possibly lead to damage of the mechanical elements in contact. In this paper, a nonlinear electric powertrain is modelled as a piecewise affine (PWA) system. The novel receding horizon sliding control (RHSC) idea is extended to constrained PWA systems and utilised to systematically address the active control problem for electric powertrains. Simulations are conducted in Matlab/Simulink in conjunction with the high fidelity Carsim software. RHSC shows superior jerk suppression and target wheel speed tracking performance as well as reduced computational cost over classical model predictive control (MPC). This indicates the newly proposed RHSC is an effective method to address the active control problem for electric powertrains.

PREDICTING EVAPORATION RATES AND TIMES FOR SPILLS OF CHEMICAL MIXTURES

EPA Science Inventory

Spreadsheet and short-cut methods have been developed for predicting evaporation rates and evaporation times for spills (and constrained baths) of chemical mixtures. Steady-state and time-varying predictions of evaporation rates can be made for six-component mixtures, includ...

Adaptive model-predictive controller for magnetic resonance guided focused ultrasound therapy.

PubMed

de Bever, Joshua; Todd, Nick; Payne, Allison; Christensen, Douglas A; Roemer, Robert B

2014-11-01

Minimising treatment time and protecting healthy tissues are conflicting goals that play major roles in making magnetic resonance image-guided focused ultrasound (MRgFUS) therapies clinically practical. We have developed and tested in vivo an adaptive model-predictive controller (AMPC) that reduces treatment time, ensures safety and efficacy, and provides flexibility in treatment set-up. The controller realises time savings by modelling the heated treatment cell's future temperatures and thermal dose accumulation in order to anticipate the optimal time to switch to the next cell. Selected tissues are safeguarded by a configurable temperature constraint. Simulations quantified the time savings realised by each controller feature as well as the trade-offs between competing safety and treatment time parameters. In vivo experiments in rabbit thighs established the controller's effectiveness and reliability. In all in vivo experiments the target thermal dose of at least 240 CEM43 was delivered everywhere in the treatment volume. The controller's temperature safety limit reliably activated and constrained all protected tissues to <9 CEM43. Simulations demonstrated the path independence of the controller, and that a path which successively proceeds to the hottest untreated neighbouring cell leads to significant time savings, e.g. when compared to a concentric spiral path. Use of the AMPC produced a compounding time-saving effect; reducing the treatment cells' heating times concurrently reduced heating of normal tissues, which eliminated cooling periods. Adaptive model-predictive control can automatically deliver safe, effective MRgFUS treatments while significantly reducing treatment times.

Extracting electron transfer coupling elements from constrained density functional theory

NASA Astrophysics Data System (ADS)

Wu, Qin; Van Voorhis, Troy

2006-10-01

Constrained density functional theory (DFT) is a useful tool for studying electron transfer (ET) reactions. It can straightforwardly construct the charge-localized diabatic states and give a direct measure of the inner-sphere reorganization energy. In this work, a method is presented for calculating the electronic coupling matrix element (Hab) based on constrained DFT. This method completely avoids the use of ground-state DFT energies because they are known to irrationally predict fractional electron transfer in many cases. Instead it makes use of the constrained DFT energies and the Kohn-Sham wave functions for the diabatic states in a careful way. Test calculations on the Zn2+ and the benzene-Cl atom systems show that the new prescription yields reasonable agreement with the standard generalized Mulliken-Hush method. We then proceed to produce the diabatic and adiabatic potential energy curves along the reaction pathway for intervalence ET in the tetrathiafulvalene-diquinone (Q-TTF-Q) anion. While the unconstrained DFT curve has no reaction barrier and gives Hab≈17kcal /mol, which qualitatively disagrees with experimental results, the Hab calculated from constrained DFT is about 3kcal /mol and the generated ground state has a barrier height of 1.70kcal/mol, successfully predicting (Q-TTF-Q)- to be a class II mixed-valence compound.

Synergism and Antagonism of Proximate Mechanisms Enable and Constrain the Response to Simultaneous Selection on Body Size and Development Time: An Empirical Test Using Experimental Evolution.

PubMed

Davidowitz, Goggy; Roff, Derek; Nijhout, H Frederik

2016-11-01

Natural selection acts on multiple traits simultaneously. How mechanisms underlying such traits enable or constrain their response to simultaneous selection is poorly understood. We show how antagonism and synergism among three traits at the developmental level enable or constrain evolutionary change in response to simultaneous selection on two focal traits at the phenotypic level. After 10 generations of 25% simultaneous directional selection on all four combinations of body size and development time in Manduca sexta (Sphingidae), the changes in the three developmental traits predict 93% of the response of development time and 100% of the response of body size. When the two focal traits were under synergistic selection, the response to simultaneous selection was enabled by juvenile hormone and ecdysteroids and constrained by growth rate. When the two focal traits were under antagonistic selection, the response to selection was due primarily to change in growth rate and constrained by the two hormonal traits. The approach used here reduces the complexity of the developmental and endocrine mechanisms to three proxy traits. This generates explicit predictions for the evolutionary response to selection that are based on biologically informed mechanisms. This approach has broad applicability to a diverse range of taxa, including algae, plants, amphibians, mammals, and insects.

A Test of the Sophisticated Guessing Theory of Word Perception

ERIC Educational Resources Information Center

Johnston, James C.

1978-01-01

Experiments tested the predictions that words are perceived more accurately in strongly constraining word contexts than in weakly constraining word contexts, and that a strong perceptual advantage would be present for letters in words vs. letters alone or in unrelated-letter strings. Several alternative theories of word perception are discussed.…

Directional constraint of endpoint force emerges from hindlimb anatomy.

PubMed

Bunderson, Nathan E; McKay, J Lucas; Ting, Lena H; Burkholder, Thomas J

2010-06-15

Postural control requires the coordination of force production at the limb endpoints to apply an appropriate force to the body. Subjected to horizontal plane perturbations, quadruped limbs stereotypically produce force constrained along a line that passes near the center of mass. This phenomenon, referred to as the force constraint strategy, may reflect mechanical constraints on the limb or body, a specific neural control strategy or an interaction among neural controls and mechanical constraints. We used a neuromuscular model of the cat hindlimb to test the hypothesis that the anatomical constraints restrict the mechanical action of individual muscles during stance and constrain the response to perturbations to a line independent of perturbation direction. In a linearized neuromuscular model of the cat hindlimb, muscle lengthening directions were highly conserved across 10,000 different muscle activation patterns, each of which produced an identical, stance-like endpoint force. These lengthening directions were closely aligned with the sagittal plane and reveal an anatomical structure for directionally constrained force responses. Each of the 10,000 activation patterns was predicted to produce stable stance based on Lyapunov stability analysis. In forward simulations of the nonlinear, seven degree of freedom model under the action of 200 random muscle activation patterns, displacement of the endpoint from its equilibrium position produced restoring forces, which were also biased toward the sagittal plane. The single exception was an activation pattern based on minimum muscle stress optimization, which produced destabilizing force responses in some perturbation directions. The sagittal force constraint increased during simulations as the system shifted from an inertial response during the acceleration phase to a viscoelastic response as peak velocity was obtained. These results qualitatively match similar experimental observations and suggest that the force constraint phenomenon may result from the anatomical arrangement of the limb.

Directional constraint of endpoint force emerges from hindlimb anatomy

PubMed Central

Bunderson, Nathan E.; McKay, J. Lucas; Ting, Lena H.; Burkholder, Thomas J.

2010-01-01

Postural control requires the coordination of force production at the limb endpoints to apply an appropriate force to the body. Subjected to horizontal plane perturbations, quadruped limbs stereotypically produce force constrained along a line that passes near the center of mass. This phenomenon, referred to as the force constraint strategy, may reflect mechanical constraints on the limb or body, a specific neural control strategy or an interaction among neural controls and mechanical constraints. We used a neuromuscular model of the cat hindlimb to test the hypothesis that the anatomical constraints restrict the mechanical action of individual muscles during stance and constrain the response to perturbations to a line independent of perturbation direction. In a linearized neuromuscular model of the cat hindlimb, muscle lengthening directions were highly conserved across 10,000 different muscle activation patterns, each of which produced an identical, stance-like endpoint force. These lengthening directions were closely aligned with the sagittal plane and reveal an anatomical structure for directionally constrained force responses. Each of the 10,000 activation patterns was predicted to produce stable stance based on Lyapunov stability analysis. In forward simulations of the nonlinear, seven degree of freedom model under the action of 200 random muscle activation patterns, displacement of the endpoint from its equilibrium position produced restoring forces, which were also biased toward the sagittal plane. The single exception was an activation pattern based on minimum muscle stress optimization, which produced destabilizing force responses in some perturbation directions. The sagittal force constraint increased during simulations as the system shifted from an inertial response during the acceleration phase to a viscoelastic response as peak velocity was obtained. These results qualitatively match similar experimental observations and suggest that the force constraint phenomenon may result from the anatomical arrangement of the limb. PMID:20511528

Universally Sloppy Parameter Sensitivities in Systems Biology Models

PubMed Central

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-01-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a “sloppy” spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters. PMID:17922568

Universally sloppy parameter sensitivities in systems biology models.

PubMed

Gutenkunst, Ryan N; Waterfall, Joshua J; Casey, Fergal P; Brown, Kevin S; Myers, Christopher R; Sethna, James P

2007-10-01

Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling model that collective fitting could yield well-constrained predictions, even when it left individual parameters very poorly constrained. We also showed that the model had a "sloppy" spectrum of parameter sensitivities, with eigenvalues roughly evenly distributed over many decades. Here we use a collection of models from the literature to test whether such sloppy spectra are common in systems biology. Strikingly, we find that every model we examine has a sloppy spectrum of sensitivities. We also test several consequences of this sloppiness for building predictive models. In particular, sloppiness suggests that collective fits to even large amounts of ideal time-series data will often leave many parameters poorly constrained. Tests over our model collection are consistent with this suggestion. This difficulty with collective fits may seem to argue for direct parameter measurements, but sloppiness also implies that such measurements must be formidably precise and complete to usefully constrain many model predictions. We confirm this implication in our growth-factor-signaling model. Our results suggest that sloppy sensitivity spectra are universal in systems biology models. The prevalence of sloppiness highlights the power of collective fits and suggests that modelers should focus on predictions rather than on parameters.

Developments in Stochastic Fuel Efficient Cruise Control and Constrained Control with Applications to Aircraft

NASA Astrophysics Data System (ADS)

McDonough, Kevin K.

The dissertation presents contributions to fuel-efficient control of vehicle speed and constrained control with applications to aircraft. In the first part of this dissertation a stochastic approach to fuel-efficient vehicle speed control is developed. This approach encompasses stochastic modeling of road grade and traffic speed, modeling of fuel consumption through the use of a neural network, and the application of stochastic dynamic programming to generate vehicle speed control policies that are optimized for the trade-off between fuel consumption and travel time. The fuel economy improvements with the proposed policies are quantified through simulations and vehicle experiments. It is shown that the policies lead to the emergence of time-varying vehicle speed patterns that are referred to as time-varying cruise. Through simulations and experiments it is confirmed that these time-varying vehicle speed profiles are more fuel-efficient than driving at a comparable constant speed. Motivated by these results, a simpler implementation strategy that is more appealing for practical implementation is also developed. This strategy relies on a finite state machine and state transition threshold optimization, and its benefits are quantified through model-based simulations and vehicle experiments. Several additional contributions are made to approaches for stochastic modeling of road grade and vehicle speed that include the use of Kullback-Liebler divergence and divergence rate and a stochastic jump-like model for the behavior of the road grade. In the second part of the dissertation, contributions to constrained control with applications to aircraft are described. Recoverable sets and integral safe sets of initial states of constrained closed-loop systems are introduced first and computational procedures of such sets based on linear discrete-time models are given. The use of linear discrete-time models is emphasized as they lead to fast computational procedures. Examples of these sets for aircraft longitudinal and lateral aircraft dynamics are reported, and it is shown that these sets can be larger in size compared to the more commonly used safe sets. An approach to constrained maneuver planning based on chaining recoverable sets or integral safe sets is described and illustrated with a simulation example. To facilitate the application of this maneuver planning approach in aircraft loss of control (LOC) situations when the model is only identified at the current trim condition but when these sets need to be predicted at other flight conditions, the dependence trends of the safe and recoverable sets on aircraft flight conditions are characterized. The scaling procedure to estimate subsets of safe and recoverable sets at one trim condition based on their knowledge at another trim condition is defined. Finally, two control schemes that exploit integral safe sets are proposed. The first scheme, referred to as the controller state governor (CSG), resets the controller state (typically an integrator) to enforce the constraints and enlarge the set of plant states that can be recovered without constraint violation. The second scheme, referred to as the controller state and reference governor (CSRG), combines the controller state governor with the reference governor control architecture and provides the capability of simultaneously modifying the reference command and the controller state to enforce the constraints. Theoretical results that characterize the response properties of both schemes are presented. Examples are reported that illustrate the operation of these schemes on aircraft flight dynamics models and gas turbine engine dynamic models.

Attentional control constrains visual short-term memory: Insights from developmental and individual differences

PubMed Central

Astle, D.E.; Nobre, A.C.; Scerif, G.

2014-01-01

The mechanisms by which attentional control biases mnemonic representations have attracted much interest but remain poorly understood. As attention and memory develop gradually over childhood and variably across individuals, assessing how participants of different ages and ability attend to mnemonic contents can elucidate their interplay. In Experiment 1, 7-, 10-year-olds and adults were asked to report whether a probe item had been part of a previously presented four-item array. The initial array could either be uncued, preceded (“pre-cued”) or followed (“retro-cued”) by a spatial cue orienting attention to one of the potential item locations. Performance across groups was significantly improved by both cue types and individual differences in children’s retrospective attentional control predicted their visual short-term and working memory span, whereas their basic ability to remember in the absence of cues did not. Experiment 2 imposed a variable delay between the array and the subsequent orienting cue. Cueing benefits were greater in adults compared to 10-year-olds, but they persisted even when cues followed the array by nearly 3 seconds, suggesting that orienting operated on durable short-term representations for both age groups. The findings indicate that there are substantial developmental and individual differences in the ability to control attention to memory and that in turn these differences constrain visual short-term memory capacity. PMID:20680889

Attentional control constrains visual short-term memory: insights from developmental and individual differences.

PubMed

Astle, Duncan E; Nobre, Anna C; Scerif, Gaia

2012-01-01

The mechanisms by which attentional control biases mnemonic representations have attracted much interest but remain poorly understood. As attention and memory develop gradually over childhood and variably across individuals, assessing how participants of different ages and ability attend to mnemonic contents can elucidate their interplay. In Experiment 1, 7-year-olds, 10-year-olds, and adults were asked to report whether a probe item had been part of a previously presented four-item array. The initial array could either be uncued, be preceded ("precued"), or followed ("retrocued") by a spatial cue orienting attention to one of the potential item locations. Performance across groups was significantly improved by both cue types, and individual differences in children's retrospective attentional control predicted their visual short-term and working memory span, whereas their basic ability to remember in the absence of cues did not. Experiment 2 imposed a variable delay between the array and the subsequent orienting cue. Cueing benefits were greater in adults than in 10-year-olds, but they persisted even when cues followed the array by nearly 3 seconds, suggesting that orienting operated on durable short-term representations for both age groups. The findings indicate that there are substantial developmental and individual differences in the ability to control attention to memory and that in turn these differences constrain visual short-term memory capacity.

Finite Time Control Design for Bilateral Teleoperation System With Position Synchronization Error Constrained.

PubMed

Yang, Yana; Hua, Changchun; Guan, Xinping

2016-03-01

Due to the cognitive limitations of the human operator and lack of complete information about the remote environment, the work performance of such teleoperation systems cannot be guaranteed in most cases. However, some practical tasks conducted by the teleoperation system require high performances, such as tele-surgery needs satisfactory high speed and more precision control results to guarantee patient' health status. To obtain some satisfactory performances, the error constrained control is employed by applying the barrier Lyapunov function (BLF). With the constrained synchronization errors, some high performances, such as, high convergence speed, small overshoot, and an arbitrarily predefined small residual constrained synchronization error can be achieved simultaneously. Nevertheless, like many classical control schemes only the asymptotic/exponential convergence, i.e., the synchronization errors converge to zero as time goes infinity can be achieved with the error constrained control. It is clear that finite time convergence is more desirable. To obtain a finite-time synchronization performance, the terminal sliding mode (TSM)-based finite time control method is developed for teleoperation system with position error constrained in this paper. First, a new nonsingular fast terminal sliding mode (NFTSM) surface with new transformed synchronization errors is proposed. Second, adaptive neural network system is applied for dealing with the system uncertainties and the external disturbances. Third, the BLF is applied to prove the stability and the nonviolation of the synchronization errors constraints. Finally, some comparisons are conducted in simulation and experiment results are also presented to show the effectiveness of the proposed method.

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

PubMed

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

2018-06-01

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

Combined constraints on the structure and physical properties of the East Antarctic lithosphere from geology and geophysics.

NASA Astrophysics Data System (ADS)

Reading, A. M.; Staal, T.; Halpin, J.; Whittaker, J. M.; Morse, P. E.

2017-12-01

The lithosphere of East Antarctica is one of the least explored regions of the planet, yet it is gaining in importance in global scientific research. Continental heat flux density and 3D glacial isostatic adjustment studies, for example, rely on a good knowledge of the deep structure in constraining model inputs.In this contribution, we use a multidisciplinary approach to constrain lithospheric domains. To seismic tomography models, we add constraints from magnetic studies and also new geological constraints. Geological knowledge exists around the periphery of East Antarctica and is reinforced in the knowledge of plate tectonic reconstructions. The subglacial geology of the Antarctic hinterland is largely unknown but the plate reconstructions allow the well-posed extrapolation of major terranes into the interior of the continent, guided by the seismic tomography and magnetic images. We find that the northern boundary of the lithospheric domain centred on the Gamburtsev Subglacial Mountains has a possible trend that runs south of the Lambert Glacier region, turning coastward through Wilkes Land. Other periphery-to-interior connections are less well constrained and the possibility of lithospheric domains that are entirely sub-glacial is high. We develop this framework to include a probabilistic method of handling alternate models and quantifiable uncertainties. We also show first results in using a Bayesian approach to predicting lithospheric boundaries from multivariate data.Within the newly constrained domains, we constrain heat flux (density) as the sum of basal heat flux and upper crustal heat flux. The basal heat flux is constrained by geophysical methods while the upper crustal heat flux is constrained by geology or predicted geology. In addition to heat flux constraints, we also consider the variations in friction experienced by moving ice sheets due to varying geology.

Controllability of switched singular mix-valued logical control networks with constraints

NASA Astrophysics Data System (ADS)

Deng, Lei; Gong, Mengmeng; Zhu, Peiyong

2018-03-01

The present paper investigates the controllability problem of switched singular mix-valued logical control networks (SSMLCNs) with constraints on states and controls. First, using the semi-tenser product (STP) of matrices, the SSMLCN is expressed in an algebraic form, based on which a necessary and sufficient condition is given for the uniqueness of solution of SSMLCNs. Second, a necessary and sufficient criteria is derived for the controllability of constrained SSMLCNs, by converting a constrained SSMLCN into a parallel constrained switched mix-valued logical control network. Third, an algorithm is presented to design a proper switching sequence and a control scheme which force a state to a reachable state. Finally, a numerical example is given to demonstrate the efficiency of the results obtained in this paper.

Effects of modeling errors on trajectory predictions in air traffic control automation

NASA Technical Reports Server (NTRS)

Jackson, Michael R. C.; Zhao, Yiyuan; Slattery, Rhonda

1996-01-01

Air traffic control automation synthesizes aircraft trajectories for the generation of advisories. Trajectory computation employs models of aircraft performances and weather conditions. In contrast, actual trajectories are flown in real aircraft under actual conditions. Since synthetic trajectories are used in landing scheduling and conflict probing, it is very important to understand the differences between computed trajectories and actual trajectories. This paper examines the effects of aircraft modeling errors on the accuracy of trajectory predictions in air traffic control automation. Three-dimensional point-mass aircraft equations of motion are assumed to be able to generate actual aircraft flight paths. Modeling errors are described as uncertain parameters or uncertain input functions. Pilot or autopilot feedback actions are expressed as equality constraints to satisfy control objectives. A typical trajectory is defined by a series of flight segments with different control objectives for each flight segment and conditions that define segment transitions. A constrained linearization approach is used to analyze trajectory differences caused by various modeling errors by developing a linear time varying system that describes the trajectory errors, with expressions to transfer the trajectory errors across moving segment transitions. A numerical example is presented for a complete commercial aircraft descent trajectory consisting of several flight segments.

Communication: CDFT-CI couplings can be unreliable when there is fractional charge transfer

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

Mavros, Michael G.; Van Voorhis, Troy, E-mail: tvan@mit.edu

2015-12-21

Constrained density functional theory with configuration interaction (CDFT-CI) is a useful, low-cost tool for the computational prediction of electronic couplings between pseudo-diabatic constrained electronic states. Such couplings are of paramount importance in electron transfer theory and transition state theory, among other areas of chemistry. Unfortunately, CDFT-CI occasionally fails significantly, predicting a coupling that does not decay exponentially with distance and/or overestimating the expected coupling by an order of magnitude or more. In this communication, we show that the eigenvalues of the difference density matrix between the two constrained states can be used as an a priori metric to determine whenmore » CDFT-CI are likely to be reliable: when the eigenvalues are near 0 or ±1, transfer of a whole electron is occurring, and CDFT-CI can be trusted. We demonstrate the utility of this metric with several illustrative examples.« less

Communication: CDFT-CI couplings can be unreliable when there is fractional charge transfer

NASA Astrophysics Data System (ADS)

Mavros, Michael G.; Van Voorhis, Troy

2015-12-01

Constrained density functional theory with configuration interaction (CDFT-CI) is a useful, low-cost tool for the computational prediction of electronic couplings between pseudo-diabatic constrained electronic states. Such couplings are of paramount importance in electron transfer theory and transition state theory, among other areas of chemistry. Unfortunately, CDFT-CI occasionally fails significantly, predicting a coupling that does not decay exponentially with distance and/or overestimating the expected coupling by an order of magnitude or more. In this communication, we show that the eigenvalues of the difference density matrix between the two constrained states can be used as an a priori metric to determine when CDFT-CI are likely to be reliable: when the eigenvalues are near 0 or ±1, transfer of a whole electron is occurring, and CDFT-CI can be trusted. We demonstrate the utility of this metric with several illustrative examples.

Hydrogeomorphic controls on hyporheic and riparian transport in two headwater mountain streams during base flow recession

NASA Astrophysics Data System (ADS)

Ward, Adam S.; Schmadel, Noah M.; Wondzell, Steven M.; Harman, Ciaran; Gooseff, Michael N.; Singha, Kamini

2016-02-01

Solute transport along riparian and hyporheic flow paths is broadly expected to respond to dynamic hydrologic forcing by streams, aquifers, and hillslopes. However, direct observation of these dynamic responses is lacking, as is the relative control of geologic setting as a control on responses to dynamic hydrologic forcing. We conducted a series of four stream solute tracer injections through base flow recession in each of two watersheds with contrasting valley morphology in the H.J. Andrews Experimental Forest, monitoring tracer concentrations in the stream and in a network of shallow riparian wells in each watershed. We found hyporheic mean arrival time, temporal variance, and fraction of stream water in the bedrock-constrained valley bottom and near large roughness elements in the wider valley bottom were not variable with discharge, suggesting minimal control by hydrologic forcing. Conversely, we observed increases in mean arrival time and temporal variance and decreasing fraction stream water with decreasing discharge near the hillslopes in the wider valley bottom. This may indicate changes in stream discharge and valley bottom hydrology control transport in less constrained locations. We detail five hydrogeomorphic responses to base flow recession to explain observed spatial and temporal patterns in the interactions between streams and their valley bottoms. Models able to account for the transition from geologically dominated processes in the near-stream subsurface to hydrologically dominated processes near the hillslope will be required to predict solute transport and fate in valley bottoms of headwater mountain streams.

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

PubMed

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Constrained surface controllers for three-dimensional image data reformatting.

PubMed

Graves, Martin J; Black, Richard T; Lomas, David J

2009-07-01

This study did not require ethical approval in the United Kingdom. The aim of this work was to create two controllers for navigating a two-dimensional image plane through a volumetric data set, providing two important features of the ultrasonographic paradigm: orientation matching of the navigation device and the desired image plane in the three-dimensional (3D) data and a constraining surface to provide a nonvisual reference for the image plane location in the 3D data. The first constrained surface controller (CSC) uses a planar constraining surface, while the second CSC uses a hemispheric constraining surface. Ten radiologists were asked to obtain specific image reformations by using both controllers and a commercially available medical imaging workstation. The time taken to perform each reformatting task was recorded. The users were also asked structured questions comparing the utility of both methods. There was a significant reduction in the time taken to perform the specified reformatting tasks by using the simpler planar controller as compared with a standard workstation, whereas there was no significant difference for the more complex hemispheric controller. The majority of users reported that both controllers allowed them to concentrate entirely on the reformatting task and the related image rather than being distracted by the need for interaction with the workstation interface. In conclusion, the CSCs provide an intuitive paradigm for interactive reformatting of volumetric data. (c) RSNA, 2009.

Intraclass reliability for assessing how well Taiwan constrained hospital-provided medical services using statistical process control chart techniques

PubMed Central

2012-01-01

Background Few studies discuss the indicators used to assess the effect on cost containment in healthcare across hospitals in a single-payer national healthcare system with constrained medical resources. We present the intraclass correlation coefficient (ICC) to assess how well Taiwan constrained hospital-provided medical services in such a system. Methods A custom Excel-VBA routine to record the distances of standard deviations (SDs) from the central line (the mean over the previous 12 months) of a control chart was used to construct and scale annual medical expenditures sequentially from 2000 to 2009 for 421 hospitals in Taiwan to generate the ICC. The ICC was then used to evaluate Taiwan’s year-based convergent power to remain unchanged in hospital-provided constrained medical services. A bubble chart of SDs for a specific month was generated to present the effects of using control charts in a national healthcare system. Results ICCs were generated for Taiwan’s year-based convergent power to constrain its medical services from 2000 to 2009. All hospital groups showed a gradually well-controlled supply of services that decreased from 0.772 to 0.415. The bubble chart identified outlier hospitals that required investigation of possible excessive reimbursements in a specific time period. Conclusion We recommend using the ICC to annually assess a nation’s year-based convergent power to constrain medical services across hospitals. Using sequential control charts to regularly monitor hospital reimbursements is required to achieve financial control in a single-payer nationwide healthcare system. PMID:22587736

Intraclass reliability for assessing how well Taiwan constrained hospital-provided medical services using statistical process control chart techniques.

PubMed

Chien, Tsair-Wei; Chou, Ming-Ting; Wang, Wen-Chung; Tsai, Li-Shu; Lin, Weir-Sen

2012-05-15

Few studies discuss the indicators used to assess the effect on cost containment in healthcare across hospitals in a single-payer national healthcare system with constrained medical resources. We present the intraclass correlation coefficient (ICC) to assess how well Taiwan constrained hospital-provided medical services in such a system. A custom Excel-VBA routine to record the distances of standard deviations (SDs) from the central line (the mean over the previous 12 months) of a control chart was used to construct and scale annual medical expenditures sequentially from 2000 to 2009 for 421 hospitals in Taiwan to generate the ICC. The ICC was then used to evaluate Taiwan's year-based convergent power to remain unchanged in hospital-provided constrained medical services. A bubble chart of SDs for a specific month was generated to present the effects of using control charts in a national healthcare system. ICCs were generated for Taiwan's year-based convergent power to constrain its medical services from 2000 to 2009. All hospital groups showed a gradually well-controlled supply of services that decreased from 0.772 to 0.415. The bubble chart identified outlier hospitals that required investigation of possible excessive reimbursements in a specific time period. We recommend using the ICC to annually assess a nation's year-based convergent power to constrain medical services across hospitals. Using sequential control charts to regularly monitor hospital reimbursements is required to achieve financial control in a single-payer nationwide healthcare system.

Extracting electron transfer coupling elements from constrained density functional theory

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

Wu Qin; Van Voorhis, Troy

2006-10-28

Constrained density functional theory (DFT) is a useful tool for studying electron transfer (ET) reactions. It can straightforwardly construct the charge-localized diabatic states and give a direct measure of the inner-sphere reorganization energy. In this work, a method is presented for calculating the electronic coupling matrix element (H{sub ab}) based on constrained DFT. This method completely avoids the use of ground-state DFT energies because they are known to irrationally predict fractional electron transfer in many cases. Instead it makes use of the constrained DFT energies and the Kohn-Sham wave functions for the diabatic states in a careful way. Test calculationsmore » on the Zn{sub 2}{sup +} and the benzene-Cl atom systems show that the new prescription yields reasonable agreement with the standard generalized Mulliken-Hush method. We then proceed to produce the diabatic and adiabatic potential energy curves along the reaction pathway for intervalence ET in the tetrathiafulvalene-diquinone (Q-TTF-Q) anion. While the unconstrained DFT curve has no reaction barrier and gives H{sub ab}{approx_equal}17 kcal/mol, which qualitatively disagrees with experimental results, the H{sub ab} calculated from constrained DFT is about 3 kcal/mol and the generated ground state has a barrier height of 1.70 kcal/mol, successfully predicting (Q-TTF-Q){sup -} to be a class II mixed-valence compound.« less

How peer-review constrains cognition: on the frontline in the knowledge sector.

PubMed

Cowley, Stephen J

2015-01-01

Peer-review is neither reliable, fair, nor a valid basis for predicting 'impact': as quality control, peer-review is not fit for purpose. Endorsing the consensus, I offer a reframing: while a normative social process, peer-review also shapes the writing of a scientific paper. In so far as 'cognition' describes enabling conditions for flexible behavior, the practices of peer-review thus constrain knowledge-making. To pursue cognitive functions of peer-review, however, manuscripts must be seen as 'symbolizations', replicable patterns that use technologically enabled activity. On this bio-cognitive view, peer-review constrains knowledge-making by writers, editors, reviewers. Authors are prompted to recursively re-aggregate symbolizations to present what are deemed acceptable knowledge claims. How, then, can recursive re-embodiment be explored? In illustration, I sketch how the paper's own content came to be re-aggregated: agonistic review drove reformatting of argument structure, changes in rhetorical ploys and careful choice of wordings. For this reason, the paper's knowledge-claims can be traced to human activity that occurs in distributed cognitive systems. Peer-review is on the frontline in the knowledge sector in that it delimits what can count as knowing. Its systemic nature is therefore crucial to not only discipline-centered 'real' science but also its 'post-academic' counterparts.

Halo effective field theory constrains the solar 7Be + p → 8B + γ rate

DOE PAGES

Zhang, Xilin; Nollett, Kenneth M.; Phillips, D. R.

2015-11-06

In this study, we report an improved low-energy extrapolation of the cross section for the process 7Be(p,γ) 8B, which determines the 8B neutrino flux from the Sun. Our extrapolant is derived from Halo Effective Field Theory (EFT) at next-to-leading order. We apply Bayesian methods to determine the EFT parameters and the low-energy S-factor, using measured cross sections and scattering lengths as inputs. Asymptotic normalization coefficients of 8B are tightly constrained by existing radiative capture data, and contributions to the cross section beyond external direct capture are detected in the data at E < 0.5 MeV. Most importantly, the S-factor atmore » zero energy is constrained to be S(0) = 21.3 ± 0.7 eV b, which is an uncertainty smaller by a factor of two than previously recommended. That recommendation was based on the full range for S(0) obtained among a discrete set of models judged to be reasonable. In contrast, Halo EFT subsumes all models into a controlled low-energy approximant, where they are characterized by nine parameters at next-to-leading order. These are fit to data, and marginalized over via Monte Carlo integration to produce the improved prediction for S(E).« less

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model - Part 1: Assessing the influence of constrained multi-generational ageing

NASA Astrophysics Data System (ADS)

Jathar, S. H.; Cappa, C. D.; Wexler, A. S.; Seinfeld, J. H.; Kleeman, M. J.

2015-09-01

Multi-generational oxidation of volatile organic compound (VOC) oxidation products can significantly alter the mass, chemical composition and properties of secondary organic aerosol (SOA) compared to calculations that consider only the first few generations of oxidation reactions. However, the most commonly used state-of-the-science schemes in 3-D regional or global models that account for multi-generational oxidation (1) consider only functionalization reactions but do not consider fragmentation reactions, (2) have not been constrained to experimental data; and (3) are added on top of existing parameterizations. The incomplete description of multi-generational oxidation in these models has the potential to bias source apportionment and control calculations for SOA. In this work, we used the Statistical Oxidation Model (SOM) of Cappa and Wilson (2012), constrained by experimental laboratory chamber data, to evaluate the regional implications of multi-generational oxidation considering both functionalization and fragmentation reactions. SOM was implemented into the regional UCD/CIT air quality model and applied to air quality episodes in California and the eastern US. The mass, composition and properties of SOA predicted using SOM are compared to SOA predictions generated by a traditional "two-product" model to fully investigate the impact of explicit and self-consistent accounting of multi-generational oxidation. Results show that SOA mass concentrations predicted by the UCD/CIT-SOM model are very similar to those predicted by a two-product model when both models use parameters that are derived from the same chamber data. Since the two-product model does not explicitly resolve multi-generational oxidation reactions, this finding suggests that the chamber data used to parameterize the models captures the majority of the SOA mass formation from multi-generational oxidation under the conditions tested. Consequently, the use of low and high NOx yields perturbs SOA concentrations by a factor of two and are probably a much stronger determinant in 3-D models than constrained multi-generational oxidation. While total predicted SOA mass is similar for the SOM and two-product models, the SOM model predicts increased SOA contributions from anthropogenic (alkane, aromatic) and sesquiterpenes and decreased SOA contributions from isoprene and monoterpene relative to the two-product model calculations. The SOA predicted by SOM has a much lower volatility than that predicted by the traditional model resulting in better qualitative agreement with volatility measurements of ambient OA. On account of its lower-volatility, the SOA mass produced by SOM does not appear to be as strongly influenced by the inclusion of oligomerization reactions, whereas the two-product model relies heavily on oligomerization to form low volatility SOA products. Finally, an unconstrained contemporary hybrid scheme to model multi-generational oxidation within the framework of a two-product model in which "ageing" reactions are added on top of the existing two-product parameterization is considered. This hybrid scheme formed at least three times more SOA than the SOM during regional simulations as a result of excessive transformation of semi-volatile vapors into lower volatility material that strongly partitions to the particle phase. This finding suggests that these "hybrid" multi-generational schemes should be used with great caution in regional models.

Robust Constrained Optimization Approach to Control Design for International Space Station Centrifuge Rotor Auto Balancing Control System

NASA Technical Reports Server (NTRS)

Postma, Barry Dirk

2005-01-01

This thesis discusses application of a robust constrained optimization approach to control design to develop an Auto Balancing Controller (ABC) for a centrifuge rotor to be implemented on the International Space Station. The design goal is to minimize a performance objective of the system, while guaranteeing stability and proper performance for a range of uncertain plants. The Performance objective is to minimize the translational response of the centrifuge rotor due to a fixed worst-case rotor imbalance. The robustness constraints are posed with respect to parametric uncertainty in the plant. The proposed approach to control design allows for both of these objectives to be handled within the framework of constrained optimization. The resulting controller achieves acceptable performance and robustness characteristics.

Global velocity constrained cloud motion prediction for short-term solar forecasting

NASA Astrophysics Data System (ADS)

Chen, Yanjun; Li, Wei; Zhang, Chongyang; Hu, Chuanping

2016-09-01

Cloud motion is the primary reason for short-term solar power output fluctuation. In this work, a new cloud motion estimation algorithm using a global velocity constraint is proposed. Compared to the most used Particle Image Velocity (PIV) algorithm, which assumes the homogeneity of motion vectors, the proposed method can capture the accurate motion vector for each cloud block, including both the motional tendency and morphological changes. Specifically, global velocity derived from PIV is first calculated, and then fine-grained cloud motion estimation can be achieved by global velocity based cloud block researching and multi-scale cloud block matching. Experimental results show that the proposed global velocity constrained cloud motion prediction achieves comparable performance to the existing PIV and filtered PIV algorithms, especially in a short prediction horizon.

Robust model predictive control of nonlinear systems with unmodeled dynamics and bounded uncertainties based on neural networks.

PubMed

Yan, Zheng; Wang, Jun

2014-03-01

This paper presents a neural network approach to robust model predictive control (MPC) for constrained discrete-time nonlinear systems with unmodeled dynamics affected by bounded uncertainties. The exact nonlinear model of underlying process is not precisely known, but a partially known nominal model is available. This partially known nonlinear model is first decomposed to an affine term plus an unknown high-order term via Jacobian linearization. The linearization residue combined with unmodeled dynamics is then modeled using an extreme learning machine via supervised learning. The minimax methodology is exploited to deal with bounded uncertainties. The minimax optimization problem is reformulated as a convex minimization problem and is iteratively solved by a two-layer recurrent neural network. The proposed neurodynamic approach to nonlinear MPC improves the computational efficiency and sheds a light for real-time implementability of MPC technology. Simulation results are provided to substantiate the effectiveness and characteristics of the proposed approach.

A mathematical tool to generate complex whole body motor tasks and test hypotheses on underlying motor planning.

PubMed

Tagliabue, Michele; Pedrocchi, Alessandra; Pozzo, Thierry; Ferrigno, Giancarlo

2008-01-01

In spite of the complexity of human motor behavior, difficulties in mathematical modeling have restricted to rather simple movements attempts to identify the motor planning criterion used by the central nervous system. This paper presents a novel-simulation technique able to predict the "desired trajectory" corresponding to a wide range of kinematic and kinetic optimality criteria for tasks involving many degrees of freedom and the coordination between goal achievement and balance maintenance. Employment of proper time discretization, inverse dynamic methods and constrained optimization technique are combined. The application of this simulator to a planar whole body pointing movement shows its effectiveness in managing system nonlinearities and instability as well as in ensuring the anatomo-physiological feasibility of predicted motor plans. In addition, the simulator's capability to simultaneously optimize competing movement aspects represents an interesting opportunity for the motor control community, in which the coexistence of several controlled variables has been hypothesized.

Do needs for security and certainty predict cultural and economic conservatism? A cross-national analysis.

PubMed

Malka, Ariel; Soto, Christopher J; Inzlicht, Michael; Lelkes, Yphtach

2014-06-01

We examine whether individual differences in needs for security and certainty predict conservative (vs. liberal) position on both cultural and economic political issues and whether these effects are conditional on nation-level characteristics and individual-level political engagement. Analyses with cross-national data from 51 nations reveal that valuing conformity, security, and tradition over self-direction and stimulation (a) predicts ideological self-placement on the political right, but only among people high in political engagement and within relatively developed nations, ideologically constrained nations, and non-Eastern European nations, (b) reliably predicts right-wing cultural attitudes and does so more strongly within developed and ideologically constrained nations, and (c) on average predicts left-wing economic attitudes but does so more weakly among people high in political engagement, within ideologically constrained nations, and within non-Eastern European nations. These findings challenge the prevailing view that needs for security and certainty organically yield a broad right-wing ideology and that exposure to political discourse better equips people to select the broad ideology that is most need satisfying. Rather, these findings suggest that needs for security and certainty generally yield culturally conservative but economically left-wing preferences and that exposure to political discourse generally weakens the latter relation. We consider implications for the interactive influence of personality characteristics and social context on political attitudes and discuss the importance of assessing multiple attitude domains, assessing political engagement, and considering national characteristics when studying the psychological origins of political attitudes.

Robust vector quantization for noisy channels

NASA Technical Reports Server (NTRS)

Demarca, J. R. B.; Farvardin, N.; Jayant, N. S.; Shoham, Y.

1988-01-01

The paper briefly discusses techniques for making vector quantizers more tolerant to tranmsission errors. Two algorithms are presented for obtaining an efficient binary word assignment to the vector quantizer codewords without increasing the transmission rate. It is shown that about 4.5 dB gain over random assignment can be achieved with these algorithms. It is also proposed to reduce the effects of error propagation in vector-predictive quantizers by appropriately constraining the response of the predictive loop. The constrained system is shown to have about 4 dB of SNR gain over an unconstrained system in a noisy channel, with a small loss of clean-channel performance.

Using an Ecological Land Hierarchy to Predict Seasonal-Wetland Abundance in Upland Forests

Treesearch

Brian J. Palik; Richard Buech; Leanne Egeland

2003-01-01

Hierarchy theory, when applied to landscapes, predicts that broader-scale ecosystems constrain the development of finer-scale, nested ecosystems. This prediction finds application in hierarchical land classifications. Such classifications typically apply to physiognomically similar ecosystems, or ecological land units, e.g., a set of multi-scale forest ecosystems. We...

Design and Evaluation of the Terminal Area Precision Scheduling and Spacing System

NASA Technical Reports Server (NTRS)

Swenson, Harry N.; Thipphavong, Jane; Sadovsky, Alex; Chen, Liang; Sullivan, Chris; Martin, Lynne

2011-01-01

This paper describes the design, development and results from a high fidelity human-in-the-loop simulation of an integrated set of trajectory-based automation tools providing precision scheduling, sequencing and controller merging and spacing functions. These integrated functions are combined into a system called the Terminal Area Precision Scheduling and Spacing (TAPSS) system. It is a strategic and tactical planning tool that provides Traffic Management Coordinators, En Route and Terminal Radar Approach Control air traffic controllers the ability to efficiently optimize the arrival capacity of a demand-impacted airport while simultaneously enabling fuel-efficient descent procedures. The TAPSS system consists of four-dimensional trajectory prediction, arrival runway balancing, aircraft separation constraint-based scheduling, traffic flow visualization and trajectory-based advisories to assist controllers in efficient metering, sequencing and spacing. The TAPSS system was evaluated and compared to today's ATC operation through extensive series of human-in-the-loop simulations for arrival flows into the Los Angeles International Airport. The test conditions included the variation of aircraft demand from a baseline of today's capacity constrained periods through 5%, 10% and 20% increases. Performance data were collected for engineering and human factor analysis and compared with similar operations both with and without the TAPSS system. The engineering data indicate operations with the TAPSS show up to a 10% increase in airport throughput during capacity constrained periods while maintaining fuel-efficient aircraft descent profiles from cruise to landing.

The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

PubMed

Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

2017-05-01

Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty where more observations are required or environmental controls are hard to constrain. © 2016 John Wiley & Sons Ltd.

Yeast 5 – an expanded reconstruction of the Saccharomyces cerevisiae metabolic network

PubMed Central

2012-01-01

Background Efforts to improve the computational reconstruction of the Saccharomyces cerevisiae biochemical reaction network and to refine the stoichiometrically constrained metabolic models that can be derived from such a reconstruction have continued since the first stoichiometrically constrained yeast genome scale metabolic model was published in 2003. Continuing this ongoing process, we have constructed an update to the Yeast Consensus Reconstruction, Yeast 5. The Yeast Consensus Reconstruction is a product of efforts to forge a community-based reconstruction emphasizing standards compliance and biochemical accuracy via evidence-based selection of reactions. It draws upon models published by a variety of independent research groups as well as information obtained from biochemical databases and primary literature. Results Yeast 5 refines the biochemical reactions included in the reconstruction, particularly reactions involved in sphingolipid metabolism; updates gene-reaction annotations; and emphasizes the distinction between reconstruction and stoichiometrically constrained model. Although it was not a primary goal, this update also improves the accuracy of model prediction of viability and auxotrophy phenotypes and increases the number of epistatic interactions. This update maintains an emphasis on standards compliance, unambiguous metabolite naming, and computer-readable annotations available through a structured document format. Additionally, we have developed MATLAB scripts to evaluate the model’s predictive accuracy and to demonstrate basic model applications such as simulating aerobic and anaerobic growth. These scripts, which provide an independent tool for evaluating the performance of various stoichiometrically constrained yeast metabolic models using flux balance analysis, are included as Additional files 1, 2 and 3. Conclusions Yeast 5 expands and refines the computational reconstruction of yeast metabolism and improves the predictive accuracy of a stoichiometrically constrained yeast metabolic model. It differs from previous reconstructions and models by emphasizing the distinction between the yeast metabolic reconstruction and the stoichiometrically constrained model, and makes both available as Additional file 4 and Additional file 5 and at http://yeast.sf.net/ as separate systems biology markup language (SBML) files. Through this separation, we intend to make the modeling process more accessible, explicit, transparent, and reproducible. PMID:22663945

Deterministic Reconfigurable Control Design for the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Wagner, Elaine A.; Burken, John J.; Hanson, Curtis E.; Wohletz, Jerry M.

1998-01-01

In the event of a control surface failure, the purpose of a reconfigurable control system is to redistribute the control effort among the remaining working surfaces such that satisfactory stability and performance are retained. Four reconfigurable control design methods were investigated for the X-33 vehicle: Redistributed Pseudo-Inverse, General Constrained Optimization, Automated Failure Dependent Gain Schedule, and an Off-line Nonlinear General Constrained Optimization. The Off-line Nonlinear General Constrained Optimization approach was chosen for implementation on the X-33. Two example failures are shown, a right outboard elevon jam at 25 deg. at a Mach 3 entry condition, and a left rudder jam at 30 degrees. Note however, that reconfigurable control laws have been designed for the entire flight envelope. Comparisons between responses with the nominal controller and reconfigurable controllers show the benefits of reconfiguration. Single jam aerosurface failures were considered, and failure detection and identification is considered accomplished in the actuator controller. The X-33 flight control system will incorporate reconfigurable flight control in the baseline system.

Hierarchical Bayesian Model Averaging for Chance Constrained Remediation Designs

NASA Astrophysics Data System (ADS)

Chitsazan, N.; Tsai, F. T.

2012-12-01

Groundwater remediation designs are heavily relying on simulation models which are subjected to various sources of uncertainty in their predictions. To develop a robust remediation design, it is crucial to understand the effect of uncertainty sources. In this research, we introduce a hierarchical Bayesian model averaging (HBMA) framework to segregate and prioritize sources of uncertainty in a multi-layer frame, where each layer targets a source of uncertainty. The HBMA framework provides an insight to uncertainty priorities and propagation. In addition, HBMA allows evaluating model weights in different hierarchy levels and assessing the relative importance of models in each level. To account for uncertainty, we employ a chance constrained (CC) programming for stochastic remediation design. Chance constrained programming was implemented traditionally to account for parameter uncertainty. Recently, many studies suggested that model structure uncertainty is not negligible compared to parameter uncertainty. Using chance constrained programming along with HBMA can provide a rigorous tool for groundwater remediation designs under uncertainty. In this research, the HBMA-CC was applied to a remediation design in a synthetic aquifer. The design was to develop a scavenger well approach to mitigate saltwater intrusion toward production wells. HBMA was employed to assess uncertainties from model structure, parameter estimation and kriging interpolation. An improved harmony search optimization method was used to find the optimal location of the scavenger well. We evaluated prediction variances of chloride concentration at the production wells through the HBMA framework. The results showed that choosing the single best model may lead to a significant error in evaluating prediction variances for two reasons. First, considering the single best model, variances that stem from uncertainty in the model structure will be ignored. Second, considering the best model with non-dominant model weight may underestimate or overestimate prediction variances by ignoring other plausible propositions. Chance constraints allow developing a remediation design with a desirable reliability. However, considering the single best model, the calculated reliability will be different from the desirable reliability. We calculated the reliability of the design for the models at different levels of HBMA. The results showed that by moving toward the top layers of HBMA, the calculated reliability converges to the chosen reliability. We employed the chance constrained optimization along with the HBMA framework to find the optimal location and pumpage for the scavenger well. The results showed that using models at different levels in the HBMA framework, the optimal location of the scavenger well remained the same, but the optimal extraction rate was altered. Thus, we concluded that the optimal pumping rate was sensitive to the prediction variance. Also, the prediction variance was changed by using different extraction rate. Using very high extraction rate will cause prediction variances of chloride concentration at the production wells to approach zero regardless of which HBMA models used.

An Algorithmic, Pie-Crusting Medial Soft Tissue Release Reduces the Need for Constrained Inserts Patients With Severe Varus Deformity Undergoing Total Knee Arthroplasty.

PubMed

Goudarz Mehdikhani, Kaveh; Morales Moreno, Beatriz; Reid, Jeremy J; de Paz Nieves, Ana; Lee, Yuo-Yu; González Della Valle, Alejandro

2016-07-01

We studied the need to use a constrained insert for residual intraoperative instability and the 1-year result of patients undergoing total knee arthroplasty (TKA) for a varus deformity. In a control group, a "classic" subperiosteal release of the medial soft tissue sleeve was performed as popularized by pioneers of TKA. In the study group, an algorithmic approach that selectively releases and pie-crusts posteromedial structures in extension and anteromedial structures in flexion was used. All surgeries were performed by a single surgeon using measured resection technique, and posterior-stabilized, cemented implants. There were 228 TKAs in the control group and 188 in the study group. Outcome variables included the use of a constrained insert, and the Knee Society Score at 6 weeks, 4 months, and 1 year postoperatively. The effect of the release technique on use of constrained inserts and clinical outcomes were analyzed in a multivariate model controlling for age, sex, body mass index, and severity of deformity. The use of constrained inserts was significantly lower in study than in control patients (8% vs 18%; P = .002). There was no difference in the Knee Society Score and range of motion between the groups at last follow-up. No patient developed postoperative medial instability. This algorithmic, pie-crusting release technique resulted in a significant reduction in the use of constrained inserts with no detrimental effects in clinical results, joint function, and stability. As constrained TKA implants are more costly than nonconstrained ones, if the adopted technique proves to be safe in the long term, it may cause a positive shift in value for hospitals and cost savings in the health care system. Copyright © 2016 Elsevier Inc. All rights reserved.

Imposing constraints on parameter values of a conceptual hydrological model using baseflow response

NASA Astrophysics Data System (ADS)

Dunn, S. M.

Calibration of conceptual hydrological models is frequently limited by a lack of data about the area that is being studied. The result is that a broad range of parameter values can be identified that will give an equally good calibration to the available observations, usually of stream flow. The use of total stream flow can bias analyses towards interpretation of rapid runoff, whereas water quality issues are more frequently associated with low flow condition. This paper demonstrates how model distinctions between surface an sub-surface runoff can be used to define a likelihood measure based on the sub-surface (or baseflow) response. This helps to provide more information about the model behaviour, constrain the acceptable parameter sets and reduce uncertainty in streamflow prediction. A conceptual model, DIY, is applied to two contrasting catchments in Scotland, the Ythan and the Carron Valley. Parameter ranges and envelopes of prediction are identified using criteria based on total flow efficiency, baseflow efficiency and combined efficiencies. The individual parameter ranges derived using the combined efficiency measures still cover relatively wide bands, but are better constrained for the Carron than the Ythan. This reflects the fact that hydrological behaviour in the Carron is dominated by a much flashier surface response than in the Ythan. Hence, the total flow efficiency is more strongly controlled by surface runoff in the Carron and there is a greater contrast with the baseflow efficiency. Comparisons of the predictions using different efficiency measures for the Ythan also suggest that there is a danger of confusing parameter uncertainties with data and model error, if inadequate likelihood measures are defined.

Flexible Energy Scheduling Tool for Integrating Variable Generation | Grid

Science.gov Websites

, security-constrained economic dispatch, and automatic generation control programs. DOWNLOAD PAPER Electric commitment, security-constrained economic dispatch, and automatic generation control sub-models. Each sub resolutions and operating strategies can be explored. FESTIV produces not only economic metrics but also

OCO-2 Column Carbon Dioxide and Biometric Data Jointly Constrain Parameterization and Projection of a Global Land Model

NASA Astrophysics Data System (ADS)

Shi, Z.; Crowell, S.; Luo, Y.; Rayner, P. J.; Moore, B., III

2015-12-01

Uncertainty in predicted carbon-climate feedback largely stems from poor parameterization of global land models. However, calibration of global land models with observations has been extremely challenging at least for two reasons. First we lack global data products from systematical measurements of land surface processes. Second, computational demand is insurmountable for estimation of model parameter due to complexity of global land models. In this project, we will use OCO-2 retrievals of dry air mole fraction XCO2 and solar induced fluorescence (SIF) to independently constrain estimation of net ecosystem exchange (NEE) and gross primary production (GPP). The constrained NEE and GPP will be combined with data products of global standing biomass, soil organic carbon and soil respiration to improve the community land model version 4.5 (CLM4.5). Specifically, we will first develop a high fidelity emulator of CLM4.5 according to the matrix representation of the terrestrial carbon cycle. It has been shown that the emulator fully represents the original model and can be effectively used for data assimilation to constrain parameter estimation. We will focus on calibrating those key model parameters (e.g., maximum carboxylation rate, turnover time and transfer coefficients of soil carbon pools, and temperature sensitivity of respiration) for carbon cycle. The Bayesian Markov chain Monte Carlo method (MCMC) will be used to assimilate the global databases into the high fidelity emulator to constrain the model parameters, which will be incorporated back to the original CLM4.5. The calibrated CLM4.5 will be used to make scenario-based projections. In addition, we will conduct observing system simulation experiments (OSSEs) to evaluate how the sampling frequency and length could affect the model constraining and prediction.

Reinterpreting maximum entropy in ecology: a null hypothesis constrained by ecological mechanism.

PubMed

O'Dwyer, James P; Rominger, Andrew; Xiao, Xiao

2017-07-01

Simplified mechanistic models in ecology have been criticised for the fact that a good fit to data does not imply the mechanism is true: pattern does not equal process. In parallel, the maximum entropy principle (MaxEnt) has been applied in ecology to make predictions constrained by just a handful of state variables, like total abundance or species richness. But an outstanding question remains: what principle tells us which state variables to constrain? Here we attempt to solve both problems simultaneously, by translating a given set of mechanisms into the state variables to be used in MaxEnt, and then using this MaxEnt theory as a null model against which to compare mechanistic predictions. In particular, we identify the sufficient statistics needed to parametrise a given mechanistic model from data and use them as MaxEnt constraints. Our approach isolates exactly what mechanism is telling us over and above the state variables alone. © 2017 John Wiley & Sons Ltd/CNRS.

Guidance and Control Architecture Design and Demonstration for Low Ballistic Coefficient Atmospheric Entry

NASA Technical Reports Server (NTRS)

Swei, Sean

2014-01-01

We propose to develop a robust guidance and control system for the ADEPT (Adaptable Deployable Entry and Placement Technology) entry vehicle. A control-centric model of ADEPT will be developed to quantify the performance of candidate guidance and control architectures for both aerocapture and precision landing missions. The evaluation will be based on recent breakthroughs in constrained controllability/reachability analysis of control systems and constrained-based energy-minimum trajectory optimization for guidance development operating in complex environments.

Hamiltonian Effective Field Theory Study of the N^{*}(1535) Resonance in Lattice QCD.

PubMed

Liu, Zhan-Wei; Kamleh, Waseem; Leinweber, Derek B; Stokes, Finn M; Thomas, Anthony W; Wu, Jia-Jun

2016-02-26

Drawing on experimental data for baryon resonances, Hamiltonian effective field theory (HEFT) is used to predict the positions of the finite-volume energy levels to be observed in lattice QCD simulations of the lowest-lying J^{P}=1/2^{-} nucleon excitation. In the initial analysis, the phenomenological parameters of the Hamiltonian model are constrained by experiment and the finite-volume eigenstate energies are a prediction of the model. The agreement between HEFT predictions and lattice QCD results obtained on volumes with spatial lengths of 2 and 3 fm is excellent. These lattice results also admit a more conventional analysis where the low-energy coefficients are constrained by lattice QCD results, enabling a determination of resonance properties from lattice QCD itself. Finally, the role and importance of various components of the Hamiltonian model are examined.

Using seismically constrained magnetotelluric inversion to recover velocity structure in the shallow lithosphere

NASA Astrophysics Data System (ADS)

Moorkamp, M.; Fishwick, S.; Jones, A. G.

2015-12-01

Typical surface wave tomography can recover well the velocity structure of the upper mantle in the depth range between 70-200km. For a successful inversion, we have to constrain the crustal structure and assess the impact on the resulting models. In addition,we often observe potentially interesting features in the uppermost lithosphere which are poorly resolved and thus their interpretationhas to be approached with great care.We are currently developing a seismically constrained magnetotelluric (MT) inversion approach with the aim of better recovering the lithospheric properties (and thus seismic velocities) in these problematic areas. We perform a 3D MT inversion constrained by a fixed seismic velocity model from surface wave tomography. In order to avoid strong bias, we only utilize information on structural boundaries to combine these two methods. Within the region that is well resolved by both methods, we can then extract a velocity-conductivity relationship. By translating the conductivitiesretrieved from MT into velocities in areas where the velocity model is poorly resolved, we can generate an updated velocity model and test what impactthe updated velocities have on the predicted data.We test this new approach using a MT dataset acquired in central Botswana over the Okwa terrane and the adjacent Kaapvaal and Zimbabwe Cratons togetherwith a tomographic models for the region. Here, both datasets have previously been used to constrain lithospheric structure and show some similarities.We carefully asses the validity of our results by comparing with observations and petrophysical predictions for the conductivity-velocity relationship.

A multidisciplinary approach to constrain incoming plate hydration in the Central American Margin

NASA Astrophysics Data System (ADS)

Hu, Y.; Guild, M. R.; Naif, S.; Eimer, M. O.; Evans, O.; Fornash, K.; Plank, T. A.; Shillington, D. J.; Vervelidou, F.; Warren, J. M.; Wiens, D.

2017-12-01

The oceanic crust and mantle of the incoming plate are potentially the greatest source of water to the subduction zone, but their extent of hydration is poorly constrained. Hydrothermal alteration of the oceanic crust is an important source of mineral-bound water that ultimately dehydrates during subduction. Bend faults at the trench-outer rise provide another viable mechanism to further hydrate the down-going plate. Here, we take a multidisciplinary approach to constrain the fluid budget of the subducting plate at the Northern Central American margin; this site was chosen since it has an unusually wet subducting slab at the Nicaragua segment. Abundant geophysical and geochemical datasets are available for this region and this work is an analysis of these data. Controlled-source electromagnetic (CSEM) and wide-angle seismic (WAS) observations show significant resistivity and velocity reductions in the incoming oceanic crust associated with bend faults, which suggests seawater infiltration and hydrous alteration. We used the CSEM porosity constraints to predict P-wave velocity and find that the WAS data require an additional reduction of up to 0.3 km/s in the lower crust at the trench, equivalent to 2 wt% H2O. We implemented the porosity structure together with constraints on fluid flow and reaction kinetics into two-phase flow numerical models to quantify the degree of serpentinization possible relative to WAS estimates. Thermodynamic modeling of basalt and peridotite bulk compositions were used to predict the alteration assemblages and associated water contents in the bend faulting region as well as the dehydration fluxes during subduction. In Nicaragua, the major fluid pulse at sub-arc depths results from chlorite and antigorite breakdown in the upper 10 km of the slab mantle, whereas in Costa Rica, the slab mantle is not predicted to dehydrate at sub-arc depths. In addition, comparisons between observed and predicted magnetic anomalies and geochemical variations along strike and across arc provide insights into the relative contribution of fluids from the subducted crust and mantle. Our findings suggest that, in addition to mantle serpentinization, the incoming oceanic crust also experiences a high degree of bending-induced hydration and transports a substantial flux of H2O to the mantle wedge.

Statistics based sampling for controller and estimator design

NASA Astrophysics Data System (ADS)

Tenne, Dirk

The purpose of this research is the development of statistical design tools for robust feed-forward/feedback controllers and nonlinear estimators. This dissertation is threefold and addresses the aforementioned topics nonlinear estimation, target tracking and robust control. To develop statistically robust controllers and nonlinear estimation algorithms, research has been performed to extend existing techniques, which propagate the statistics of the state, to achieve higher order accuracy. The so-called unscented transformation has been extended to capture higher order moments. Furthermore, higher order moment update algorithms based on a truncated power series have been developed. The proposed techniques are tested on various benchmark examples. Furthermore, the unscented transformation has been utilized to develop a three dimensional geometrically constrained target tracker. The proposed planar circular prediction algorithm has been developed in a local coordinate framework, which is amenable to extension of the tracking algorithm to three dimensional space. This tracker combines the predictions of a circular prediction algorithm and a constant velocity filter by utilizing the Covariance Intersection. This combined prediction can be updated with the subsequent measurement using a linear estimator. The proposed technique is illustrated on a 3D benchmark trajectory, which includes coordinated turns and straight line maneuvers. The third part of this dissertation addresses the design of controller which include knowledge of parametric uncertainties and their distributions. The parameter distributions are approximated by a finite set of points which are calculated by the unscented transformation. This set of points is used to design robust controllers which minimize a statistical performance of the plant over the domain of uncertainty consisting of a combination of the mean and variance. The proposed technique is illustrated on three benchmark problems. The first relates to the design of prefilters for a linear and nonlinear spring-mass-dashpot system and the second applies a feedback controller to a hovering helicopter. Lastly, the statistical robust controller design is devoted to a concurrent feed-forward/feedback controller structure for a high-speed low tension tape drive.

Testing constrained sequential dominance models of neutrinos

NASA Astrophysics Data System (ADS)

Björkeroth, Fredrik; King, Stephen F.

2015-12-01

Constrained sequential dominance (CSD) is a natural framework for implementing the see-saw mechanism of neutrino masses which allows the mixing angles and phases to be accurately predicted in terms of relatively few input parameters. We analyze a class of CSD(n) models where, in the flavour basis, two right-handed neutrinos are dominantly responsible for the ‘atmospheric’ and ‘solar’ neutrino masses with Yukawa couplings to ({ν }e,{ν }μ ,{ν }τ ) proportional to (0,1,1) and (1,n,n-2), respectively, where n is a positive integer. These coupling patterns may arise in indirect family symmetry models based on A 4. With two right-handed neutrinos, using a χ 2 test, we find a good agreement with data for CSD(3) and CSD(4) where the entire Pontecorvo-Maki-Nakagawa-Sakata mixing matrix is controlled by a single phase η, which takes simple values, leading to accurate predictions for mixing angles and the magnitude of the oscillation phase | {δ }{CP}| . We carefully study the perturbing effect of a third ‘decoupled’ right-handed neutrino, leading to a bound on the lightest physical neutrino mass {m}1{{≲ }}1 meV for the viable cases, corresponding to a normal neutrino mass hierarchy. We also discuss a direct link between the oscillation phase {δ }{CP} and leptogenesis in CSD(n) due to the same see-saw phase η appearing in both the neutrino mass matrix and leptogenesis.

A physically-based method for predicting peak discharge of floods caused by failure of natural and constructed earthen dams

USGS Publications Warehouse

Walder, J.S.; O'Connor, J. E.; Costa, J.E.; ,

1997-01-01

We analyse a simple, physically-based model of breach formation in natural and constructed earthen dams to elucidate the principal factors controlling the flood hydrograph at the breach. Formation of the breach, which is assumed trapezoidal in cross-section, is parameterized by the mean rate of downcutting, k, the value of which is constrained by observations. A dimensionless formulation of the model leads to the prediction that the breach hydrograph depends upon lake shape, the ratio r of breach width to depth, the side slope ?? of the breach, and the parameter ?? = (V.D3)(k/???gD), where V = lake volume, D = lake depth, and g is the acceleration due to gravity. Calculations show that peak discharge Qp depends weakly on lake shape r and ??, but strongly on ??, which is the product of a dimensionless lake volume and a dimensionless erosion rate. Qp(??) takes asymptotically distinct forms depending on whether < ??? 1 or < ??? 1. Theoretical predictions agree well with data from dam failures for which k could be reasonably estimated. The analysis provides a rapid and in many cases graphical way to estimate plausible values of Qp at the breach.We analyze a simple, physically-based model of breach formation in natural and constructed earthen dams to elucidate the principal factors controlling the flood hydrograph at the breach. Formation of the breach, which is assumed trapezoidal in cross-section, is parameterized by the mean rate of downcutting, k, the value of which is constrained by observations. A dimensionless formulation of the model leads to the prediction that the breach hydrograph depends upon lake shape, the ratio r of breach width to depth, the side slope ?? of the breach, and the parameter ?? = (V/D3)(k/???gD), where V = lake volume, D = lake depth, and g is the acceleration due to gravity. Calculations show that peak discharge Qp depends weakly on lake shape r and ??, but strongly on ??, which is the product of a dimensionless lake volume and a dimensionless erosion rate. Qp(??) takes asymptotically distinct forms depending on whether ?????1 or ?????1. Theoretical predictions agree well with data from dam failures for which k could be reasonably estimated. The analysis provides a rapid and in many cases graphical way to estimate plausible values of Qp at the breach.

The export and fate of organic matter in the ocean: New constraints from combining satellite and oceanographic tracer observations

NASA Astrophysics Data System (ADS)

DeVries, Tim; Weber, Thomas

2017-03-01

The ocean's biological pump transfers carbon from the surface euphotic zone into the deep ocean, reducing the atmospheric CO2 concentration. Despite its climatic importance, there are large uncertainties in basic metrics of the biological pump. Previous estimates of the strength of the biological pump, as measured by the amount of organic carbon exported from the euphotic zone, range from about 4 to 12 Pg C yr-1. The fate of exported carbon, in terms of how efficiently it is transferred into the deep ocean, is even more uncertain. Here we present a new model of the biological pump that assimilates satellite and oceanographic tracer observations to constrain rates and patterns of organic matter production, export, and remineralization in the ocean. The data-assimilated model predicts a global particulate organic carbon (POC) flux out of the euphotic zone of ˜9 Pg C yr-1. The particle export ratio (the ratio of POC export to net primary production) is highest at high latitudes and lowest at low latitudes, but low-latitude export is greater than predicted by previous models, in better agreement with observed patterns of long-term carbon export. Particle transfer efficiency (Teff) through the mesopelagic zone is controlled by temperature and oxygen, with highest Teff for high-latitude regions and oxygen minimum zones. In contrast, Teff in the deep ocean (below 1000 m) is controlled by particle sinking speed, with highest deep ocean Teff below the subtropical gyres. These results emphasize the utility of both remote sensing and oceanographic tracer observations for constraining the operation of the biological pump.

Shear wave prediction using committee fuzzy model constrained by lithofacies, Zagros basin, SW Iran

NASA Astrophysics Data System (ADS)

Shiroodi, Sadjad Kazem; Ghafoori, Mohammad; Ansari, Hamid Reza; Lashkaripour, Golamreza; Ghanadian, Mostafa

2017-02-01

The main purpose of this study is to introduce the geological controlling factors in improving an intelligence-based model to estimate shear wave velocity from seismic attributes. The proposed method includes three main steps in the framework of geological events in a complex sedimentary succession located in the Persian Gulf. First, the best attributes were selected from extracted seismic data. Second, these attributes were transformed into shear wave velocity using fuzzy inference systems (FIS) such as Sugeno's fuzzy inference (SFIS), adaptive neuro-fuzzy inference (ANFIS) and optimized fuzzy inference (OFIS). Finally, a committee fuzzy machine (CFM) based on bat-inspired algorithm (BA) optimization was applied to combine previous predictions into an enhanced solution. In order to show the geological effect on improving the prediction, the main classes of predominate lithofacies in the reservoir of interest including shale, sand, and carbonate were selected and then the proposed algorithm was performed with and without lithofacies constraint. The results showed a good agreement between real and predicted shear wave velocity in the lithofacies-based model compared to the model without lithofacies especially in sand and carbonate.

How peer-review constrains cognition: on the frontline in the knowledge sector

PubMed Central

Cowley, Stephen J.

2015-01-01

Peer-review is neither reliable, fair, nor a valid basis for predicting ‘impact’: as quality control, peer-review is not fit for purpose. Endorsing the consensus, I offer a reframing: while a normative social process, peer-review also shapes the writing of a scientific paper. In so far as ‘cognition’ describes enabling conditions for flexible behavior, the practices of peer-review thus constrain knowledge-making. To pursue cognitive functions of peer-review, however, manuscripts must be seen as ‘symbolizations’, replicable patterns that use technologically enabled activity. On this bio-cognitive view, peer-review constrains knowledge-making by writers, editors, reviewers. Authors are prompted to recursively re-aggregate symbolizations to present what are deemed acceptable knowledge claims. How, then, can recursive re-embodiment be explored? In illustration, I sketch how the paper’s own content came to be re-aggregated: agonistic review drove reformatting of argument structure, changes in rhetorical ploys and careful choice of wordings. For this reason, the paper’s knowledge-claims can be traced to human activity that occurs in distributed cognitive systems. Peer-review is on the frontline in the knowledge sector in that it delimits what can count as knowing. Its systemic nature is therefore crucial to not only discipline-centered ‘real’ science but also its ‘post-academic’ counterparts. PMID:26579064

SITE CHARACTERIZATION TO SUPPORT MODEL DEVELOPMENT FOR CONTAMINANTS IN GROUND WATER

EPA Science Inventory

The development of conceptual and predictive models is an important tool to guide site characterization in support of monitoring contaminants in ground water. The accuracy of predictive models is limited by the adequacy of the input data and the assumptions made to constrain mod...

Text familiarity, word frequency, and sentential constraints in error detection.

PubMed

Pilotti, Maura; Chodorow, Martin; Schauss, Frances

2009-12-01

The present study examines whether the frequency of an error-bearing word and its predictability, arising from sentential constraints and text familiarity, either independently or jointly, would impair error detection by making proofreading driven by top-down processes. Prior to a proofreading task, participants were asked to read, copy, memorize, or paraphrase sentences, half of which contained errors. These tasks represented a continuum of progressively more demanding and time-consuming activities, which were thought to lead to comparable increases in text familiarity and thus predictability. Proofreading times were unaffected by whether the sentences had been encountered earlier. Proofreading was slower and less accurate for high-frequency words and for highly constrained sentences. Prior memorization produced divergent effects on accuracy depending on sentential constraints. The latter finding suggested that a substantial level of predictability, such as that produced by memorizing highly constrained sentences, can increase the probability of overlooking errors.

Uncertainty assessment and implications for data acquisition in support of integrated hydrologic models

NASA Astrophysics Data System (ADS)

Brunner, Philip; Doherty, J.; Simmons, Craig T.

2012-07-01

The data set used for calibration of regional numerical models which simulate groundwater flow and vadose zone processes is often dominated by head observations. It is to be expected therefore, that parameters describing vadose zone processes are poorly constrained. A number of studies on small spatial scales explored how additional data types used in calibration constrain vadose zone parameters or reduce predictive uncertainty. However, available studies focused on subsets of observation types and did not jointly account for different measurement accuracies or different hydrologic conditions. In this study, parameter identifiability and predictive uncertainty are quantified in simulation of a 1-D vadose zone soil system driven by infiltration, evaporation and transpiration. The worth of different types of observation data (employed individually, in combination, and with different measurement accuracies) is evaluated by using a linear methodology and a nonlinear Pareto-based methodology under different hydrological conditions. Our main conclusions are (1) Linear analysis provides valuable information on comparative parameter and predictive uncertainty reduction accrued through acquisition of different data types. Its use can be supplemented by nonlinear methods. (2) Measurements of water table elevation can support future water table predictions, even if such measurements inform the individual parameters of vadose zone models to only a small degree. (3) The benefits of including ET and soil moisture observations in the calibration data set are heavily dependent on depth to groundwater. (4) Measurements of groundwater levels, measurements of vadose ET or soil moisture poorly constrain regional groundwater system forcing functions.

A Method to Constrain Genome-Scale Models with 13C Labeling Data

PubMed Central

García Martín, Héctor; Kumar, Vinay Satish; Weaver, Daniel; Ghosh, Amit; Chubukov, Victor; Mukhopadhyay, Aindrila; Arkin, Adam; Keasling, Jay D.

2015-01-01

Current limitations in quantitatively predicting biological behavior hinder our efforts to engineer biological systems to produce biofuels and other desired chemicals. Here, we present a new method for calculating metabolic fluxes, key targets in metabolic engineering, that incorporates data from 13C labeling experiments and genome-scale models. The data from 13C labeling experiments provide strong flux constraints that eliminate the need to assume an evolutionary optimization principle such as the growth rate optimization assumption used in Flux Balance Analysis (FBA). This effective constraining is achieved by making the simple but biologically relevant assumption that flux flows from core to peripheral metabolism and does not flow back. The new method is significantly more robust than FBA with respect to errors in genome-scale model reconstruction. Furthermore, it can provide a comprehensive picture of metabolite balancing and predictions for unmeasured extracellular fluxes as constrained by 13C labeling data. A comparison shows that the results of this new method are similar to those found through 13C Metabolic Flux Analysis (13C MFA) for central carbon metabolism but, additionally, it provides flux estimates for peripheral metabolism. The extra validation gained by matching 48 relative labeling measurements is used to identify where and why several existing COnstraint Based Reconstruction and Analysis (COBRA) flux prediction algorithms fail. We demonstrate how to use this knowledge to refine these methods and improve their predictive capabilities. This method provides a reliable base upon which to improve the design of biological systems. PMID:26379153

Automation for Accommodating Fuel-Efficient Descents in Constrained Airspace

NASA Technical Reports Server (NTRS)

Coopenbarger, Richard A.

2010-01-01

Continuous descents at low engine power are desired to reduce fuel consumption, emissions and noise during arrival operations. The challenge is to allow airplanes to fly these types of efficient descents without interruption during busy traffic conditions. During busy conditions today, airplanes are commonly forced to fly inefficient, step-down descents as airtraffic controllers work to ensure separation and maximize throughput. NASA in collaboration with government and industry partners is developing new automation to help controllers accommodate continuous descents in the presence of complex traffic and airspace constraints. This automation relies on accurate trajectory predictions to compute strategic maneuver advisories. The talk will describe the concept behind this new automation and provide an overview of the simulations and flight testing used to develop and refine its underlying technology.

Natural changes in light interact with circadian regulation at promoters to control gene expression in cyanobacteria

PubMed Central

2017-01-01

The circadian clock interacts with other regulatory pathways to tune physiology to predictable daily changes and unexpected environmental fluctuations. However, the complexity of circadian clocks in higher organisms has prevented a clear understanding of how natural environmental conditions affect circadian clocks and their physiological outputs. Here, we dissect the interaction between circadian regulation and responses to fluctuating light in the cyanobacterium Synechococcus elongatus. We demonstrate that natural changes in light intensity substantially affect the expression of hundreds of circadian-clock-controlled genes, many of which are involved in key steps of metabolism. These changes in expression arise from circadian and light-responsive control of RNA polymerase recruitment to promoters by a network of transcription factors including RpaA and RpaB. Using phenomenological modeling constrained by our data, we reveal simple principles that underlie the small number of stereotyped responses of dusk circadian genes to changes in light. PMID:29239721

Flowering time and seed dormancy control use external coincidence to generate life history strategy.

PubMed

Springthorpe, Vicki; Penfield, Steven

2015-03-31

Climate change is accelerating plant developmental transitions coordinated with the seasons in temperate environments. To understand the importance of these timing advances for a stable life history strategy, we constructed a full life cycle model of Arabidopsis thaliana. Modelling and field data reveal that a cryptic function of flowering time control is to limit seed set of winter annuals to an ambient temperature window which coincides with a temperature-sensitive switch in seed dormancy state. This coincidence is predicted to be conserved independent of climate at the expense of flowering date, suggesting that temperature control of flowering time has evolved to constrain seed set environment and therefore frequency of dormant and non-dormant seed states. We show that late flowering can disrupt this bet-hedging germination strategy. Our analysis shows that life history modelling can reveal hidden fitness constraints and identify non-obvious selection pressures as emergent features.

Stimulation-Based Control of Dynamic Brain Networks

PubMed Central

Pasqualetti, Fabio; Gu, Shi; Cieslak, Matthew

2016-01-01

The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing interest in brain stimulation as a form of neuromodulation, much remains unknown about the network-level impact of these focal perturbations. To study the system wide impact of regional stimulation, we employ a data-driven computational model of nonlinear brain dynamics to systematically explore the effects of targeted stimulation. Validating predictions from network control theory, we uncover the relationship between regional controllability and the focal versus global impact of stimulation, and we relate these findings to differences in the underlying network architecture. Finally, by mapping brain regions to cognitive systems, we observe that the default mode system imparts large global change despite being highly constrained by structural connectivity. This work forms an important step towards the development of personalized stimulation protocols for medical treatment or performance enhancement. PMID:27611328

Self-regulation and social pressure reduce prejudiced responding and increase the motivation to be non-prejudiced.

PubMed

Buzinski, Steven G; Kitchens, Michael B

2017-01-01

Self-regulation constrains the expression of prejudice, but when self-regulation falters, the immediate environment can act as an external source of prejudice regulation. This hypothesis derives from work demonstrating that external controls and internal self-regulation can prompt goal pursuit in the absence of self-imposed controls. Across four studies, we found support for this complementary model of prejudice regulation. In Study 1, self-regulatory fatigue resulted in less motivation to be non-prejudiced, compared to a non-fatigued control. In Study 2, strong (vs. weak) perceived social pressure was related to greater motivation to be non-prejudiced. In Study 3, dispositional self-regulation predicted non-prejudice motivation when perceived social pressure was weak or moderate, but not when it was strong. Finally, in Study 4 self-regulatory fatigue increased prejudice when social pressure was weak but not when it was strong.

Controlled elastic postbuckling of bilaterally constrained non-prismatic columns: application to enhanced quasi-static energy harvesters

NASA Astrophysics Data System (ADS)

Liu, Suihan; Burgueño, Rigoberto

2016-12-01

Axially compressed bilaterally constrained columns, which can attain multiple snap-through buckling events in their elastic postbuckling response, can be used as energy concentrators and mechanical triggers to transform external quasi-static displacement input to local high-rate motions and excite vibration-based piezoelectric transducers for energy harvesting devices. However, the buckling location with highest kinetic energy release along the element, and where piezoelectric oscillators should be optimally placed, cannot be controlled or isolated due to the changing buckling configurations. This paper proposes the concept of stiffness variations along the column to gain control of the buckling location for optimal placement of piezoelectric transducers. Prototyped non-prismatic columns with piece-wise varying thickness were fabricated through 3D printing for experimental characterization and numerical simulations were conducted using the finite element method. A simple theoretical model was also developed based on the stationary potential energy principle for predicting the critical line contact segment that triggers snap-through events and the buckling morphologies as compression proceeds. Results confirm that non-prismatic column designs allow control of the buckling location in the elastic postbuckling regime. Compared to prismatic columns, non-prismatic designs can attain a concentrated kinetic energy release spot and a higher number of snap-buckling mode transitions under the same global strain. The direct relation between the column’s dynamic response and the output voltage from piezoelectric oscillator transducers allows the tailorable postbuckling response of non-prismatic columns to be used as multi-stable energy concentrators with enhanced performance in micro-energy harvesters.

Measurements and Modeling of Stress in Precipitation-Hardened Aluminum Alloy AA2618 during Gleeble Interrupted Quenching and Constrained Cooling

NASA Astrophysics Data System (ADS)

Chobaut, Nicolas; Carron, Denis; Saelzle, Peter; Drezet, Jean-Marie

2016-11-01

Solutionizing and quenching are the key steps in the fabrication of heat-treatable aluminum parts such as AA2618 compressor impellers for turbochargers as they highly impact the mechanical characteristics of the product. In particular, quenching induces residual stresses that can cause unacceptable distortions during machining and unfavorable stresses in service. Predicting and controlling stress generation during quenching of large AA2618 forgings are therefore of particular interest. Since possible precipitation during quenching may affect the local yield strength of the material and thus impact the level of macroscale residual stresses, consideration of this phenomenon is required. A material model accounting for precipitation in a simple but realistic way is presented. Instead of modeling precipitation that occurs during quenching, the model parameters are identified using a limited number of tensile tests achieved after representative interrupted cooling paths in a Gleeble machine. This material model is presented, calibrated, and validated against constrained coolings in a Gleeble blocked-jaws configuration. Applications of this model are FE computations of stress generation during quenching of large AA2618 forgings for compressor impellers.

Adaptive Multi-Agent Systems for Constrained Optimization

NASA Technical Reports Server (NTRS)

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.

Search for standard model production of four top quarks with same-sign and multilepton final states in proton-proton collisions at √{s} = 13 {TeV}

NASA Astrophysics Data System (ADS)

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Ambrogi, F.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Escalante Del Valle, A.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Grossmann, J.; Hrubec, J.; Jeitler, M.; König, A.; Krammer, N.; Krätschmer, I.; Liko, D.; Madlener, T.; Mikulec, I.; Pree, E.; Rad, N.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Spanring, M.; Spitzbart, D.; Taurok, A.; Waltenberger, W.; Wittmann, J.; Wulz, C.-E.; Zarucki, M.; Chekhovsky, V.; Mossolov, V.; Suarez Gonzalez, J.; De Wolf, E. A.; Di Croce, D.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; De Bruyn, I.; De Clercq, J.; Deroover, K.; Flouris, G.; Lontkovskyi, D.; Lowette, S.; Marchesini, I.; Moortgat, S.; Moreels, L.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Beghin, D.; Bilin, B.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Dorney, B.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Kalsi, A. K.; Lenzi, T.; Luetic, J.; Maerschalk, T.; Marinov, A.; Seva, T.; Starling, E.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Roskas, C.; Salva, S.; Trocino, D.; Tytgat, M.; Verbeke, W.; Zaganidis, N.; Bakhshiansohi, H.; Bondu, O.; Brochet, S.; Bruno, G.; Caputo, C.; Caudron, A.; David, P.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Saggio, A.; Vidal Marono, M.; Wertz, S.; Zobec, J.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correia Silva, G.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Coelho, E.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Melo De Almeida, M.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Sanchez Rosas, L. J.; Santoro, A.; Sznajder, A.; Thiel, M.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Misheva, M.; Rodozov, M.; Shopova, M.; Sultanov, G.; Dimitrov, A.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Gao, X.; Yuan, L.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Jiang, C. H.; Leggat, D.; Liao, H.; Liu, Z.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Yazgan, E.; Yu, T.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, J.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Zhang, F.; Wang, Y.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Segura Delgado, M. A.; Courbon, B.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Starodumov, A.; Susa, T.; Ather, M. W.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Assran, Y.; Elgammal, S.; Mahrous, A.; Bhowmik, S.; Dewanjee, R. K.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Kirschenmann, H.; Pekkanen, J.; Voutilainen, M.; Havukainen, J.; Heikkilä, J. K.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Laurila, S.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Siikonen, H.; Tuominen, E.; Tuominiemi, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Faure, J. L.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Leloup, C.; Locci, E.; Machet, M.; Malcles, J.; Negro, G.; Rander, J.; Rosowsky, A.; Sahin, M. Ö.; Titov, M.; Abdulsalam, A.; Amendola, C.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Charlot, C.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Lobanov, A.; Martin Blanco, J.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Stahl Leiton, A. G.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Drouhin, F.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Jansová, M.; Juillot, P.; Le Bihan, A.-C.; Tonon, N.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fay, J.; Finco, L.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sordini, V.; Vander Donckt, M.; Viret, S.; Zhang, S.; Khvedelidze, A.; Bagaturia, I.; Autermann, C.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Teroerde, M.; Wittmer, B.; Zhukov, V.; Albert, A.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Teyssier, D.; Thüer, S.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bermúdez Martínez, A.; Bin Anuar, A. A.; Borras, K.; Botta, V.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Guthoff, M.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Missiroli, M.; Mittag, G.; Mnich, J.; Mussgiller, A.; Ntomari, E.; Pitzl, D.; Raspereza, A.; Savitskyi, M.; Saxena, P.; Shevchenko, R.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wen, Y.; Wichmann, K.; Wissing, C.; Zenaiev, O.; Aggleton, R.; Bein, S.; Blobel, V.; Centis Vignali, M.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hinzmann, A.; Hoffmann, M.; Karavdina, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Kurz, S.; Lapsien, T.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Sonneveld, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baselga, M.; Baur, S.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Faltermann, N.; Freund, B.; Friese, R.; Giffels, M.; Harrendorf, M. A.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Kassel, F.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Karathanasis, G.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Kousouris, K.; Evangelou, I.; Foudas, C.; Gianneios, P.; Katsoulis, P.; Kokkas, P.; Mallios, S.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Triantis, F. A.; Tsitsonis, D.; Csanad, M.; Filipovic, N.; Pasztor, G.; Surányi, O.; Veres, G. I.; Bencze, G.; Hajdu, C.; Horvath, D.; Hunyadi, Á.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Choudhury, S.; Komaragiri, J. R.; Bahinipati, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Dhingra, N.; Kaur, A.; Kaur, M.; Kaur, S.; Kumar, R.; Kumari, P.; Mehta, A.; Singh, J. B.; Walia, G.; Kumar, Ashok; Shah, Aashaq; Bhardwaj, A.; Chauhan, S.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Bhardwaj, R.; Bhattacharya, R.; Bhattacharya, S.; Bhawandeep, U.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Sur, N.; Sutar, B.; Banerjee, S.; Bhattacharya, S.; Chatterjee, S.; Das, P.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Errico, F.; Fiore, L.; Iaselli, G.; Lezki, S.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Borgonovi, L.; Braibant-Giacomelli, S.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Chatterjee, K.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Ravera, F.; Robutti, E.; Tosi, S.; Benaglia, A.; Beschi, A.; Brianza, L.; Brivio, F.; Ciriolo, V.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Khan, W. A.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Lujan, P.; Margoni, M.; Meneguzzo, A. T.; Pozzobon, N.; Ronchese, P.; Rossin, R.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Ressegotti, M.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Biasini, M.; Bilei, G. M.; Cecchi, C.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Manoni, E.; Mantovani, G.; Mariani, V.; Menichelli, M.; Rossi, A.; Santocchia, A.; Spiga, D.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Boccali, T.; Borrello, L.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Fedi, G.; Giannini, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Manca, E.; Mandorli, G.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Daci, N.; Del Re, D.; Di Marco, E.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, J.; Lee, S.; Lee, S. W.; Moon, C. S.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Kim, H.; Moon, D. H.; Oh, G.; Brochero Cifuentes, J. A.; Goh, J.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Kim, J. S.; Lee, H.; Lee, K.; Nam, K.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. H.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Choi, Y.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Md Ali, M. A. B.; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Reyes-Almanza, R.; Ramirez-Sanchez, G.; Duran-Osuna, M. C.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Rabadan-Trejo, R. I.; Lopez-Fernandez, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Eysermans, J.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Pyskir, A.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E. Silva, C.; Di Francesco, A.; Faccioli, P.; Galinhas, B.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Seixas, J.; Strong, G.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Baginyan, A.; Golunov, A.; Golutvin, I.; Karjavin, V.; Korenkov, V.; Kozlov, G.; Lanev, A.; Malakhov, A.; Matveev, V.; Mitsyn, V. V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Shmatov, S.; Smirnov, V.; Voytishin, N.; Yuldashev, B. S.; Zarubin, A.; Zhiltsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sosnov, D.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Stepennov, A.; Stolin, V.; Toms, M.; Vlasov, E.; Zhokin, A.; Aushev, T.; Bylinkin, A.; Chistov, R.; Danilov, M.; Parygin, P.; Philippov, D.; Polikarpov, S.; Tarkovskii, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Rusakov, S. V.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Gribushin, A.; Klyukhin, V.; Korneeva, N.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Perfilov, M.; Savrin, V.; Volkov, P.; Blinov, V.; Shtol, D.; Skovpen, Y.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Godizov, A.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Mandrik, P.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Alcaraz Maestre, J.; Bachiller, I.; Barrio Luna, M.; Cerrada, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Moran, D.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Redondo, I.; Romero, L.; Soares, M. S.; Triossi, A.; Álvarez Fernández, A.; Albajar, C.; de Trocóniz, J. F.; Cuevas, J.; Erice, C.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Vischia, P.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Chazin Quero, B.; Curras, E.; Duarte Campderros, J.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Martinez Ruiz del Arbol, P.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Akgun, B.; Auffray, E.; Baillon, P.; Ball, A. H.; Barney, D.; Bendavid, J.; Bianco, M.; Bocci, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; Chapon, E.; Chen, Y.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Deelen, N.; Dobson, M.; du Pree, T.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Fallavollita, F.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gilbert, A.; Gill, K.; Glege, F.; Gulhan, D.; Harris, P.; Hegeman, J.; Innocente, V.; Jafari, A.; Janot, P.; Karacheban, O.; Kieseler, J.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Krammer, M.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Mulders, M.; Neugebauer, H.; Ngadiuba, J.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Rabady, D.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Seidel, M.; Selvaggi, M.; Sharma, A.; Silva, P.; Sphicas, P.; Stakia, A.; Steggemann, J.; Stoye, M.; Tosi, M.; Treille, D.; Tsirou, A.; Veckalns, V.; Verweij, M.; Zeuner, W. D.; Bertl, W.; Caminada, L.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Wiederkehr, S. A.; Backhaus, M.; Bäni, L.; Berger, P.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dorfer, C.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Klijnsma, T.; Lustermann, W.; Mangano, B.; Marionneau, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Reichmann, M.; Sanz Becerra, D. A.; Schönenberger, M.; Shchutska, L.; Tavolaro, V. R.; Theofilatos, K.; Vesterbacka Olsson, M. L.; Wallny, R.; Zhu, D. H.; Aarrestad, T. K.; Amsler, C.; Canelli, M. F.; De Cosa, A.; Del Burgo, R.; Donato, S.; Galloni, C.; Hreus, T.; Kilminster, B.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Schweiger, K.; Seitz, C.; Takahashi, Y.; Zucchetta, A.; Candelise, V.; Chang, Y. H.; Cheng, K. y.; Doan, T. H.; Jain, Sh.; Khurana, R.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Paganis, E.; Psallidas, A.; Steen, A.; Tsai, J. F.; Asavapibhop, B.; Kovitanggoon, K.; Singh, G.; Srimanobhas, N.; Bat, A.; Boran, F.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Eskut, E.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. E.; Kara, O.; Kayis Topaksu, A.; Kiminsu, U.; Oglakci, M.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Tok, U. G.; Topakli, H.; Tali, B.; Turkcapar, S.; Zorbakir, I. S.; Zorbilmez, C.; Karapinar, G.; Ocalan, K.; Yalvac, M.; Zeyrek, M.; Gülmez, E.; Kaya, M.; Kaya, O.; Tekten, S.; Yetkin, E. A.; Agaras, M. N.; Atay, S.; Cakir, A.; Cankocak, K.; Komurcu, Y.; Grynyov, B.; Levchuk, L.; Ball, F.; Beck, L.; Brooke, J. J.; Burns, D.; Clement, E.; Cussans, D.; Davignon, O.; Flacher, H.; Goldstein, J.; Heath, G. P.; Heath, H. F.; Kreczko, L.; Newbold, D. M.; Paramesvaran, S.; Sakuma, T.; Seif El Nasr-storey, S.; Smith, D.; Smith, V. J.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Calligaris, L.; Cieri, D.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Linacre, J.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Williams, T.; Womersley, W. J.; Auzinger, G.; Bainbridge, R.; Bloch, P.; Borg, J.; Breeze, S.; Buchmuller, O.; Bundock, A.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Elwood, A.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Matsushita, T.; Nash, J.; Nikitenko, A.; Palladino, V.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Shtipliyski, A.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wardle, N.; Winterbottom, D.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Teodorescu, L.; Zahid, S.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Smith, C.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Hadley, M.; Hakala, J.; Heintz, U.; Hogan, J. M.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Lee, J.; Mao, Z.; Narain, M.; Pazzini, J.; Piperov, S.; Sagir, S.; Syarif, R.; Yu, D.; Band, R.; Brainerd, C.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Stolp, D.; Tos, K.; Tripathi, M.; Wang, Z.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Regnard, S.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Karapostoli, G.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Si, W.; Wang, L.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Gilbert, D.; Hashemi, B.; Holzner, A.; Klein, D.; Kole, G.; Krutelyov, V.; Letts, J.; Masciovecchio, M.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; Gouskos, L.; Heller, R.; Incandela, J.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bornheim, A.; Bunn, J.; Lawhorn, J. M.; Newman, H. B.; Nguyen, T. Q.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhang, Z.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Mudholkar, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Patterson, J. R.; Quach, D.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Abdullin, S.; Albrow, M.; Alyari, M.; Apollinari, G.; Apresyan, A.; Apyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Canepa, A.; Cerati, G. B.; Cheung, H. W. K.; Chlebana, F.; Cremonesi, M.; Duarte, J.; Elvira, V. D.; Freeman, J.; Gecse, Z.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Schneider, B.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Wu, W.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Joshi, B. M.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Shi, K.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Joshi, Y. R.; Linn, S.; Markowitz, P.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Kolberg, T.; Martinez, G.; Perry, T.; Prosper, H.; Saha, A.; Santra, A.; Sharma, V.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Cavanaugh, R.; Chen, X.; Evdokimov, O.; Gerber, C. E.; Hangal, D. A.; Hofman, D. J.; Jung, K.; Kamin, J.; Sandoval Gonzalez, I. D.; Tonjes, M. B.; Trauger, H.; Varelas, N.; Wang, H.; Wu, Z.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Rogan, C.; Royon, C.; Sanders, S.; Schmitz, E.; Tapia Takaki, J. D.; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Rebassoo, F.; Wright, D.; Baden, A.; Baron, O.; Belloni, A.; Eno, S. C.; Feng, Y.; Ferraioli, C.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Azzolini, V.; Barbieri, R.; Baty, A.; Bauer, G.; Bi, R.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Hu, M.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Tatar, K.; Velicanu, D.; Wang, J.; Wang, T. W.; Wyslouch, B.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Hiltbrand, J.; Kalafut, S.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Turkewitz, J.; Wadud, M. A.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Golf, F.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Freer, C.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Orimoto, T.; Teixeira De Lima, R.; Wamorkar, T.; Wang, B.; Wisecarver, A.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Mucia, N.; Odell, N.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Bucci, R.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Li, W.; Loukas, N.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Siddireddy, P.; Smith, G.; Taroni, S.; Wayne, M.; Wightman, A.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Ji, W.; Ling, T. Y.; Liu, B.; Luo, W.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Higginbotham, S.; Kalogeropoulos, A.; Lange, D.; Luo, J.; Marlow, D.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Malik, S.; Norberg, S.; Barker, A.; Barnes, V. E.; Das, S.; Folgueras, S.; Gutay, L.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Peng, C. C.; Qiu, H.; Schulte, J. F.; Sun, J.; Wang, F.; Xiao, R.; Xie, W.; Cheng, T.; Parashar, N.; Stupak, J.; Chen, Z.; Ecklund, K. M.; Freed, S.; Geurts, F. J. M.; Guilbaud, M.; Kilpatrick, M.; Li, W.; Michlin, B.; Padley, B. P.; Roberts, J.; Rorie, J.; Shi, W.; Tu, Z.; Zabel, J.; Zhang, A.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. T.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Ciesielski, R.; Goulianos, K.; Mesropian, C.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Kyriacou, S.; Lath, A.; Montalvo, R.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Akchurin, N.; Damgov, J.; De Guio, F.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Mengke, T.; Muthumuni, S.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Padeken, K.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Hirosky, R.; Joyce, M.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Wang, Y.; Wolfe, E.; Xia, F.; Harr, R.; Karchin, P. E.; Poudyal, N.; Sturdy, J.; Thapa, P.; Zaleski, S.; Brodski, M.; Buchanan, J.; Caillol, C.; Carlsmith, D.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Hussain, U.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Rekovic, V.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.

2018-02-01

A search for standard model production of four top quarks (t\\overline{t} t\\overline{t} ) is reported using events containing at least three leptons (e, μ) or a same-sign lepton pair. The events are produced in proton-proton collisions at a center-of-mass energy of 13 {TeV} at the LHC, and the data sample, recorded in 2016, corresponds to an integrated luminosity of 35.9 {fb}^{-1}. Jet multiplicity and flavor are used to enhance signal sensitivity, and dedicated control regions are used to constrain the dominant backgrounds. The observed and expected signal significances are, respectively, 1.6 and 1.0 standard deviations, and the t\\overline{t} t\\overline{t} cross section is measured to be 16.9^{+13.8}_{-11.4} {fb}, in agreement with next-to-leading-order standard model predictions. These results are also used to constrain the Yukawa coupling between the top quark and the Higgs boson to be less than 2.1 times its expected standard model value at 95% confidence level.

Liquid-bridge stability and breakup on surfaces with contact-angle hysteresis.

PubMed

Akbari, Amir; Hill, Reghan J

2016-08-10

We study the stability and breakup of liquid bridges with a free contact line on surfaces with contact-angle hysteresis (CAH) under zero-gravity conditions. Non-ideal surfaces exhibit CAH because of surface imperfections, by which the constraints on three-phase contact lines are influenced. Given that interfacial instabilities are constraint-sensitive, understanding how CAH affects the stability and breakup of liquid bridges is crucial for predicting the drop size in contact-drop dispensing. Unlike ideal surfaces on which contact lines are always free irrespective of surface wettability, contact lines may undergo transitions from pinned to free and vice versa during drop deposition on non-ideal surfaces. Here, we experimentally and theoretically examine how stability and breakup are affected by CAH, highlighting cases where stability is lost during a transition from a pinned-pinned (more constrained) to pinned-free (less constrained) interface-rather than a critical state. This provides a practical means of expediting or delaying stability loss. We also demonstrate how the dynamic contact angle can control the contact-line radius following stability loss.

Hydrograph Predictions of Glacial Lake Outburst Floods From an Ice-Dammed Lake

NASA Astrophysics Data System (ADS)

McCoy, S. W.; Jacquet, J.; McGrath, D.; Koschitzki, R.; Okuinghttons, J.

2017-12-01

Understanding the time evolution of glacial lake outburst floods (GLOFs), and ultimately predicting peak discharge, is crucial to mitigating the impacts of GLOFs on downstream communities and understanding concomitant surface change. The dearth of in situ measurements taken during GLOFs has left many GLOF models currently in use untested. Here we present a dataset of 13 GLOFs from Lago Cachet Dos, Aysen Region, Chile in which we detail measurements of key environmental variables (total volume drained, lake temperature, and lake inflow rate) and high temporal resolution discharge measurements at the source lake, in addition to well-constrained ice thickness and bedrock topography. Using this dataset we test two common empirical equations as well as the physically-based model of Spring-Hutter-Clarke. We find that the commonly used empirical relationships based solely on a dataset of lake volume drained fail to predict the large variability in observed peak discharges from Lago Cachet Dos. This disagreement is likely because these equations do not consider additional environmental variables that we show also control peak discharge, primarily, lake water temperature and the rate of meltwater inflow to the source lake. We find that the Spring-Hutter-Clarke model can accurately simulate the exponentially rising hydrographs that are characteristic of ice-dammed GLOFs, as well as the order of magnitude variation in peak discharge between events if the hydraulic roughness parameter is allowed to be a free fitting parameter. However, the Spring-Hutter-Clarke model over predicts peak discharge in all cases by 10 to 35%. The systematic over prediction of peak discharge by the model is related to its abrupt flood termination that misses the observed steep falling limb of the flood hydrograph. Although satisfactory model fits are produced, the range in hydraulic roughness required to obtain these fits across all events was large, which suggests that current models do not completely capture the physics of these systems, thus limiting their ability to truly predict peak discharges using only independently constrained parameters. We suggest what some of these missing physics might be.

Flight Test of the F/A-18 Active Aeroelastic Wing Airplane

NASA Technical Reports Server (NTRS)

Clarke, Robert; Allen, Michael J.; Dibley, Ryan P.; Gera, Joseph; Hodgkinson, John

2005-01-01

Successful flight-testing of the Active Aeroelastic Wing airplane was completed in March 2005. This program, which started in 1996, was a joint activity sponsored by NASA, Air Force Research Laboratory, and industry contractors. The test program contained two flight test phases conducted in early 2003 and early 2005. During the first phase of flight test, aerodynamic models and load models of the wing control surfaces and wing structure were developed. Design teams built new research control laws for the Active Aeroelastic Wing airplane using these flight-validated models; and throughout the final phase of flight test, these new control laws were demonstrated. The control laws were designed to optimize strategies for moving the wing control surfaces to maximize roll rates in the transonic and supersonic flight regimes. Control surface hinge moments and wing loads were constrained to remain within hydraulic and load limits. This paper describes briefly the flight control system architecture as well as the design approach used by Active Aeroelastic Wing project engineers to develop flight control system gains. Additionally, this paper presents flight test techniques and comparison between flight test results and predictions.

Exploring stellar evolution with gravitational-wave observations

NASA Astrophysics Data System (ADS)

Dvorkin, Irina; Uzan, Jean-Philippe; Vangioni, Elisabeth; Silk, Joseph

2018-05-01

Recent detections of gravitational waves from merging binary black holes opened new possibilities to study the evolution of massive stars and black hole formation. In particular, stellar evolution models may be constrained on the basis of the differences in the predicted distribution of black hole masses and redshifts. In this work we propose a framework that combines galaxy and stellar evolution models and use it to predict the detection rates of merging binary black holes for various stellar evolution models. We discuss the prospects of constraining the shape of the time delay distribution of merging binaries using just the observed distribution of chirp masses. Finally, we consider a generic model of primordial black hole formation and discuss the possibility of distinguishing it from stellar-origin black holes.

Hardiness scales in Iranian managers: evidence of incremental validity in relationships with the five factor model and with organizational and psychological adjustment.

PubMed

Ghorbani, Nima; Watson, P J

2005-06-01

This study examined the incremental validity of Hardiness scales in a sample of Iranian managers. Along with measures of the Five Factor Model and of Organizational and Psychological Adjustment, Hardiness scales were administered to 159 male managers (M age = 39.9, SD = 7.5) who had worked in their organizations for 7.9 yr. (SD=5.4). Hardiness predicted greater Job Satisfaction, higher Organization-based Self-esteem, and perceptions of the work environment as being less stressful and constraining. Hardiness also correlated positively with Assertiveness, Emotional Stability, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness and negatively with Depression, Anxiety, Perceived Stress, Chance External Control, and a Powerful Others External Control. Evidence of incremental validity was obtained when the Hardiness scales supplemented the Five Factor Model in predicting organizational and psychological adjustment. These data documented the incremental validity of the Hardiness scales in a non-Western sample and thus confirmed once again that Hardiness has a relevance that extends beyond the culture in which it was developed.

Using magma flow indicators to infer flow dynamics in sills

NASA Astrophysics Data System (ADS)

Hoyer, Lauren; Watkeys, Michael K.

2017-03-01

Fabrics from Anisotropy of Magnetic Susceptibility (AMS) analyses and Shape Preferred Orientation (SPO) of plagioclase are compared with field structures (such as bridge structures, intrusive steps and magma lobes) formed during magma intrusion in Jurassic sills. This is to constrain magma flow directions in the sills of the Karoo Igneous Province along the KwaZulu-Natal North Coast and to show how accurately certain structures predict a magma flow sense, thus improving the understanding of the Karoo sub-volcanic dynamics. The AMS fabrics are derived from magnetite grains and are well constrained, however the SPO results are commonly steeply inclined, poorly constrained and differ to the AMS fabrics. Both techniques resulted in asymmetrical fabrics. Successful relationships were established between the AMS fabric and the long axes of the magma flow indicators, implying adequate magma flow prediction. However, where numerous sill segments merge, either in the form of magma lobes or bridge structures, the coalescence process creates a new fabric between the segments preserving late-stage magma migration between the merged segments, overprinting the initial magma flow direction.

Nucleation and growth constraints and outcome in the natural gas hydrate system

NASA Astrophysics Data System (ADS)

Osegovic, J. P.; Max, M. D.

2016-12-01

Hydrate formation processes are functions of energy distribution constrained by physical and kinetic parameters. The generation of energy and energy derivative plots of a constrained growth crucible are used to demonstrate nucleation probability zones (phase origin(s)). Nucleation sets the stage for growth by further constraining the pathways through changes in heat capacity, heat flow coefficient, and enthalpy which in turn modify the mass and energy flow into the hydrate formation region. Nucleation events result from the accumulation of materials and energy relative to pressure, temperature, and composition. Nucleation induction is predictive (a frequency parameter) rather than directly dependent on time. Growth, as mass tranfer into a new phase, adds time as a direct parameter. Growth has direct feedback on phase transfer, energy dynamics, and mass export/import rates. Many studies have shown that hydrate growth is largely an equilibrium process controlled by either mass or energy flows. Subtle changes in the overall energy distribution shift the equilibrium in a predictable fashion. We will demonstrate the localization of hydrate nucleation in a reservoir followed by likely evolution of growth in a capped, sand filled environment. The gas hydrate stability zone (GHSZ) can be characterized as a semi-batch crystallizer in which nucleation and growth of natural gas hydrate (NGH) is a continuous process that may result in very large concentrations of NGH. Gas flux, or the relative concentration of hydrate-forming gas is the critical factor in a GHSZ. In an open groundwater system in which flow rate exceeds diffusion transport rate, dissolved natural gas is transported into and through the GHSZ. In a closed system, such as a geological trap, diffusion of hydrate-forming gas from a free gas zone below the GHSZ is the primary mechanism for movement of gas reactants. Because of the lower molecular weight of methane, where diffusion is the principal transport mechanism, the natural system can be a purification process for formation of increasingly pure NGH from a mixed gas solution over time.

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

Saide, Pablo E.; Peterson, David A.; de Silva, Arlindo

We couple airborne, ground-based, and satellite observations; conduct regional simulations; and develop and apply an inversion technique to constrain hourly smoke emissions from the Rim Fire, the third largest observed in California, USA. Emissions constrained with multiplatform data show notable nocturnal enhancements (sometimes over a factor of 20), correlate better with daily burned area data, and are a factor of 2–4 higher than a priori estimates, highlighting the need for improved characterization of diurnal profiles and day-to-day variability when modeling extreme fires. Constraining only with satellite data results in smaller enhancements mainly due to missing retrievals near the emissions source,more » suggesting that top-down emission estimates for these events could be underestimated and a multiplatform approach is required to resolve them. Predictions driven by emissions constrained with multiplatform data present significant variations in downwind air quality and in aerosol feedback on meteorology, emphasizing the need for improved emissions estimates during exceptional events.« less

Predicting Dynamic Postural Instability Using Center of Mass Time-to-Contact Information

PubMed Central

Hasson, Christopher J.; Van Emmerik, Richard E.A.; Caldwell, Graham E.

2008-01-01

Our purpose was to determine whether spatiotemporal measures of center of mass motion relative to the base of support boundary could predict stepping strategies after upper-body postural perturbations in humans. We expected that inclusion of center of mass acceleration in such time-to-contact (TtC) calculations would give better predictions and more advanced warning of perturbation severity. TtC measures were compared with traditional postural variables, which don’t consider support boundaries, and with an inverted pendulum model of dynamic stability developed by Hof et al. (2005). A pendulum was used to deliver sequentially increasing perturbations to 10 young adults, who were strapped to a wooden backboard that constrained motion to sagittal plane rotation about the ankle joint. Subjects were instructed to resist the perturbations, stepping only if necessary to prevent a fall. Peak center of mass and center of pressure velocity and acceleration demonstrated linear increases with postural challenge. In contrast, boundary relevant minimum TtC values decreased nonlinearly with postural challenge, enabling prediction of stepping responses using quadratic equations. When TtC calculations incorporated center of mass acceleration, the quadratic fits were better and gave more accurate predictions of the TtC values that would trigger stepping responses. In addition, TtC minima occurred earlier with acceleration inclusion, giving more advanced warning of perturbation severity. Our results were in agreement with TtC predictions based on Hof’s model, and suggest that TtC may function as a control parameter, influencing the postural control system’s decision to transition from a stationary base of support to a stepping strategy. PMID:18556003

Models of volcanic eruption hazards

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

Wohletz, K.H.

1992-01-01

Volcanic eruptions pose an ever present but poorly constrained hazard to life and property for geothermal installations in volcanic areas. Because eruptions occur sporadically and may limit field access, quantitative and systematic field studies of eruptions are difficult to complete. Circumventing this difficulty, laboratory models and numerical simulations are pivotal in building our understanding of eruptions. For example, the results of fuel-coolant interaction experiments show that magma-water interaction controls many eruption styles. Applying these results, increasing numbers of field studies now document and interpret the role of external water eruptions. Similarly, numerical simulations solve the fundamental physics of high-speed fluidmore » flow and give quantitative predictions that elucidate the complexities of pyroclastic flows and surges. A primary goal of these models is to guide geologists in searching for critical field relationships and making their interpretations. Coupled with field work, modeling is beginning to allow more quantitative and predictive volcanic hazard assessments.« less

Day length unlikely to constrain climate-driven shifts in leaf-out times of northern woody plants

NASA Astrophysics Data System (ADS)

Zohner, Constantin M.; Benito, Blas M.; Svenning, Jens-Christian; Renner, Susanne S.

2016-12-01

The relative roles of temperature and day length in driving spring leaf unfolding are known for few species, limiting our ability to predict phenology under climate warming. Using experimental data, we assess the importance of photoperiod as a leaf-out regulator in 173 woody species from throughout the Northern Hemisphere, and we also infer the influence of winter duration, temperature seasonality, and inter-annual temperature variability. We combine results from climate- and light-controlled chambers with species’ native climate niches inferred from georeferenced occurrences and range maps. Of the 173 species, only 35% relied on spring photoperiod as a leaf-out signal. Contrary to previous suggestions, these species come from lower latitudes, whereas species from high latitudes with long winters leafed out independent of photoperiod. The strong effect of species’ geographic-climatic history on phenological strategies complicates the prediction of community-wide phenological change.

Models of volcanic eruption hazards

NASA Astrophysics Data System (ADS)

Wohletz, K. H.

Volcanic eruptions pose an ever present but poorly constrained hazard to life and property for geothermal installations in volcanic areas. Because eruptions occur sporadically and may limit field access, quantitative and systematic field studies of eruptions are difficult to complete. Circumventing this difficulty, laboratory models and numerical simulations are pivotal in building our understanding of eruptions. For example, the results of fuel-coolant interaction experiments show that magma-water interaction controls many eruption styles. Applying these results, increasing numbers of field studies now document and interpret the role of external water eruptions. Similarly, numerical simulations solve the fundamental physics of high-speed fluid flow and give quantitative predictions that elucidate the complexities of pyroclastic flows and surges. A primary goal of these models is to guide geologists in searching for critical field relationships and making their interpretations. Coupled with field work, modeling is beginning to allow more quantitative and predictive volcanic hazard assessments.

Modelling and Vibration Control of Beams with Partially Debonded Active Constrained Layer Damping Patch

NASA Astrophysics Data System (ADS)

SUN, D.; TONG, L.

2002-05-01

A detailed model for the beams with partially debonded active constraining damping (ACLD) treatment is presented. In this model, the transverse displacement of the constraining layer is considered to be non-identical to that of the host structure. In the perfect bonding region, the viscoelastic core is modelled to carry both peel and shear stresses, while in the debonding area, it is assumed that no peel and shear stresses be transferred between the host beam and the constraining layer. The adhesive layer between the piezoelectric sensor and the host beam is also considered in this model. In active control, the positive position feedback control is employed to control the first mode of the beam. Based on this model, the incompatibility of the transverse displacements of the active constraining layer and the host beam is investigated. The passive and active damping behaviors of the ACLD patch with different thicknesses, locations and lengths are examined. Moreover, the effects of debonding of the damping layer on both passive and active control are examined via a simulation example. The results show that the incompatibility of the transverse displacements is remarkable in the regions near the ends of the ACLD patch especially for the high order vibration modes. It is found that a thinner damping layer may lead to larger shear strain and consequently results in a larger passive and active damping. In addition to the thickness of the damping layer, its length and location are also key factors to the hybrid control. The numerical results unveil that edge debonding can lead to a reduction of both passive and active damping, and the hybrid damping may be more sensitive to the debonding of the damping layer than the passive damping.

Concurrent prediction of muscle and tibiofemoral contact forces during treadmill gait.

PubMed

Guess, Trent M; Stylianou, Antonis P; Kia, Mohammad

2014-02-01

Detailed knowledge of knee kinematics and dynamic loading is essential for improving the design and outcomes of surgical procedures, tissue engineering applications, prosthetics design, and rehabilitation. This study used publicly available data provided by the "Grand Challenge Competition to Predict in-vivo Knee Loads" for the 2013 American Society of Mechanical Engineers Summer Bioengineering Conference (Fregly et al., 2012, "Grand Challenge Competition to Predict in vivo Knee Loads," J. Orthop. Res., 30, pp. 503-513) to develop a full body, musculoskeletal model with subject specific right leg geometries that can concurrently predict muscle forces, ligament forces, and knee and ground contact forces. The model includes representation of foot/floor interactions and predicted tibiofemoral joint loads were compared to measured tibial loads for two different cycles of treadmill gait. The model used anthropometric data (height and weight) to scale the joint center locations and mass properties of a generic model and then used subject bone geometries to more accurately position the hip and ankle. The musculoskeletal model included 44 muscles on the right leg, and subject specific geometries were used to create a 12 degrees-of-freedom anatomical right knee that included both patellofemoral and tibiofemoral articulations. Tibiofemoral motion was constrained by deformable contacts defined between the tibial insert and femoral component geometries and by ligaments. Patellofemoral motion was constrained by contact between the patellar button and femoral component geometries and the patellar tendon. Shoe geometries were added to the feet, and shoe motion was constrained by contact between three shoe segments per foot and the treadmill surface. Six-axis springs constrained motion between the feet and shoe segments. Experimental motion capture data provided input to an inverse kinematics stage, and the final forward dynamics simulations tracked joint angle errors for the left leg and upper body and tracked muscle length errors for the right leg. The one cycle RMS errors between the predicted and measured tibia contact were 178 N and 168 N for the medial and lateral sides for the first gait cycle and 209 N and 228 N for the medial and lateral sides for the faster second gait cycle. One cycle RMS errors between predicted and measured ground reaction forces were 12 N, 13 N, and 65 N in the anterior-posterior, medial-lateral, and vertical directions for the first gait cycle and 43 N, 15 N, and 96 N in the anterior-posterior, medial-lateral, and vertical directions for the second gait cycle.

Empirical models of Jupiter's interior from Juno data. Moment of inertia and tidal Love number k2

NASA Astrophysics Data System (ADS)

Ni, Dongdong

2018-05-01

Context. The Juno spacecraft has significantly improved the accuracy of gravitational harmonic coefficients J4, J6 and J8 during its first two perijoves. However, there are still differences in the interior model predictions of core mass and envelope metallicity because of the uncertainties in the hydrogen-helium equations of state. New theoretical approaches or observational data are hence required in order to further constrain the interior models of Jupiter. A well constrained interior model of Jupiter is helpful for understanding not only the dynamic flows in the interior, but also the formation history of giant planets. Aims: We present the radial density profiles of Jupiter fitted to the Juno gravity field observations. Also, we aim to investigate our ability to constrain the core properties of Jupiter using its moment of inertia and tidal Love number k2 which could be accessible by the Juno spacecraft. Methods: In this work, the radial density profile was constrained by the Juno gravity field data within the empirical two-layer model in which the equations of state are not needed as an input model parameter. Different two-layer models are constructed in terms of core properties. The dependence of the calculated moment of inertia and tidal Love number k2 on the core properties was investigated in order to discern their abilities to further constrain the internal structure of Jupiter. Results: The calculated normalized moment of inertia (NMOI) ranges from 0.2749 to 0.2762, in reasonable agreement with the other predictions. There is a good correlation between the NMOI value and the core properties including masses and radii. Therefore, measurements of NMOI by Juno can be used to constrain both the core mass and size of Jupiter's two-layer interior models. For the tidal Love number k2, the degeneracy of k2 is found and analyzed within the two-layer interior model. In spite of this, measurements of k2 can still be used to further constrain the core mass and size of Jupiter's two-layer interior models.

Method of texturing a superconductive oxide precursor

DOEpatents

DeMoranville, Kenneth L.; Li, Qi; Antaya, Peter D.; Christopherson, Craig J.; Riley, Jr., Gilbert N.; Seuntjens, Jeffrey M.

1999-01-01

A method of forming a textured superconductor wire includes constraining an elongated superconductor precursor between two constraining elongated members placed in contact therewith on opposite sides of the superconductor precursor, and passing the superconductor precursor with the two constraining members through flat rolls to form the textured superconductor wire. The method includes selecting desired cross-sectional shape and size constraining members to control the width of the formed superconductor wire. A textured superconductor wire formed by the method of the invention has regular-shaped, curved sides and is free of flashing. A rolling assembly for single-pass rolling of the elongated precursor superconductor includes two rolls, two constraining members, and a fixture for feeding the precursor superconductor and the constraining members between the rolls. In alternate embodiments of the invention, the rolls can have machined regions which will contact only the elongated constraining members and affect the lateral deformation and movement of those members during the rolling process.

Optimal vibration control of a rotating plate with self-sensing active constrained layer damping

NASA Astrophysics Data System (ADS)

Xie, Zhengchao; Wong, Pak Kin; Lo, Kin Heng

2012-04-01

This paper proposes a finite element model for optimally controlled constrained layer damped (CLD) rotating plate with self-sensing technique and frequency-dependent material property in both the time and frequency domain. Constrained layer damping with viscoelastic material can effectively reduce the vibration in rotating structures. However, most existing research models use complex modulus approach to model viscoelastic material, and an additional iterative approach which is only available in frequency domain has to be used to include the material's frequency dependency. It is meaningful to model the viscoelastic damping layer in rotating part by using the anelastic displacement fields (ADF) in order to include the frequency dependency in both the time and frequency domain. Also, unlike previous ones, this finite element model treats all three layers as having the both shear and extension strains, so all types of damping are taken into account. Thus, in this work, a single layer finite element is adopted to model a three-layer active constrained layer damped rotating plate in which the constraining layer is made of piezoelectric material to work as both the self-sensing sensor and actuator under an linear quadratic regulation (LQR) controller. After being compared with verified data, this newly proposed finite element model is validated and could be used for future research.

Control of the constrained planar simple inverted pendulum

NASA Technical Reports Server (NTRS)

Bavarian, B.; Wyman, B. F.; Hemami, H.

1983-01-01

Control of a constrained planar inverted pendulum by eigenstructure assignment is considered. Linear feedback is used to stabilize and decouple the system in such a way that specified subspaces of the state space are invariant for the closed-loop system. The effectiveness of the feedback law is tested by digital computer simulation. Pre-compensation by an inverse plant is used to improve performance.

A Test of Carbon and Oxygen Stable Isotope Ratio Process Models in Tree Rings.

NASA Astrophysics Data System (ADS)

Roden, J. S.; Farquhar, G. D.

2008-12-01

Stable isotopes ratios of carbon and oxygen in tree ring cellulose have been used to infer environmental change. Process-based models have been developed to clarify the potential of historic tree ring records for meaningful paleoclimatic reconstructions. However, isotopic variation can be influenced by multiple environmental factors making simplistic interpretations problematic. Recently, the dual isotope approach, where the variation in one stable isotope ratio (e.g. oxygen) is used to constrain the interpretation of variation in another (e.g. carbon), has been shown to have the potential to de-convolute isotopic analysis. However, this approach requires further testing to determine its applicability for paleo-reconstructions using tree-ring time series. We present a study where the information needed to parameterize mechanistic models for both carbon and oxygen stable isotope ratios were collected in controlled environment chambers for two species (Pinus radiata and Eucalyptus globulus). The seedlings were exposed to treatments designed to modify leaf temperature, transpiration rates, stomatal conductance and photosynthetic capacity. Both species were grown for over 100 days under two humidity regimes that differed by 20%. Stomatal conductance was significantly different between species and for seedlings under drought conditions but not between other treatments or humidity regimes. The treatments produced large differences in transpiration rate and photosynthesis. Treatments that effected photosynthetic rates but not stomatal conductance influenced carbon isotope discrimination more than those that influenced primarily conductance. The various treatments produced a range in oxygen isotope ratios of 7 ‰. Process models predicted greater oxygen isotope enrichment in tree ring cellulose than observed. The oxygen isotope ratios of bulk leaf water were reasonably well predicted by current steady-state models. However, the fractional difference between models that predict bulk leaf water versus the site of evaporation did not increase with transpiration rates. In conclusion, although the dual isotope approach may better constrain interpretation of isotopic variation, more work is required before its predictive power can be applied to tree-ring archives.

Current-State Constrained Filter Bank for Wald Testing of Spacecraft Conjunctions

NASA Technical Reports Server (NTRS)

Carpenter, J. Russell; Markley, F. Landis

2012-01-01

We propose a filter bank consisting of an ordinary current-state extended Kalman filter, and two similar but constrained filters: one is constrained by a null hypothesis that the miss distance between two conjuncting spacecraft is inside their combined hard body radius at the predicted time of closest approach, and one is constrained by an alternative complementary hypothesis. The unconstrained filter is the basis of an initial screening for close approaches of interest. Once the initial screening detects a possibly risky conjunction, the unconstrained filter also governs measurement editing for all three filters, and predicts the time of closest approach. The constrained filters operate only when conjunctions of interest occur. The computed likelihoods of the innovations of the two constrained filters form a ratio for a Wald sequential probability ratio test. The Wald test guides risk mitigation maneuver decisions based on explicit false alarm and missed detection criteria. Since only current-state Kalman filtering is required to compute the innovations for the likelihood ratio, the present approach does not require the mapping of probability density forward to the time of closest approach. Instead, the hard-body constraint manifold is mapped to the filter update time by applying a sigma-point transformation to a projection function. Although many projectors are available, we choose one based on Lambert-style differential correction of the current-state velocity. We have tested our method using a scenario based on the Magnetospheric Multi-Scale mission, scheduled for launch in late 2014. This mission involves formation flight in highly elliptical orbits of four spinning spacecraft equipped with antennas extending 120 meters tip-to-tip. Eccentricities range from 0.82 to 0.91, and close approaches generally occur in the vicinity of perigee, where rapid changes in geometry may occur. Testing the method using two 12,000-case Monte Carlo simulations, we found the method achieved a missed detection rate of 0.1%, and a false alarm rate of 2%.

SITE CHARACTERIZATION TO SUPPORT DEVELOPMENT OF CONCEPTUAL SITE MODELS AND TRANSPORT MODELS FOR MONITORING CONTAMINANTS IN GROUND WATER

EPA Science Inventory

The development of conceptual and predictive models is an important tool to guide site characterization in support of monitoring contaminants in ground water. The accuracy of predictive models is limited by the adequacy of the input data and the assumptions made to constrain mod...

A Thermodynamically-consistent FBA-based Approach to Biogeochemical Reaction Modeling

NASA Astrophysics Data System (ADS)

Shapiro, B.; Jin, Q.

2015-12-01

Microbial rates are critical to understanding biogeochemical processes in natural environments. Recently, flux balance analysis (FBA) has been applied to predict microbial rates in aquifers and other settings. FBA is a genome-scale constraint-based modeling approach that computes metabolic rates and other phenotypes of microorganisms. This approach requires a prior knowledge of substrate uptake rates, which is not available for most natural microbes. Here we propose to constrain substrate uptake rates on the basis of microbial kinetics. Specifically, we calculate rates of respiration (and fermentation) using a revised Monod equation; this equation accounts for both the kinetics and thermodynamics of microbial catabolism. Substrate uptake rates are then computed from the rates of respiration, and applied to FBA to predict rates of microbial growth. We implemented this method by linking two software tools, PHREEQC and COBRA Toolbox. We applied this method to acetotrophic methanogenesis by Methanosarcina barkeri, and compared the simulation results to previous laboratory observations. The new method constrains acetate uptake by accounting for the kinetics and thermodynamics of methanogenesis, and predicted well the observations of previous experiments. In comparison, traditional methods of dynamic-FBA constrain acetate uptake on the basis of enzyme kinetics, and failed to reproduce the experimental results. These results show that microbial rate laws may provide a better constraint than enzyme kinetics for applying FBA to biogeochemical reaction modeling.

Statistical Modeling to Predict N2O Production Within the Hyporheic Zone by Coupling Denitrifying Microbial Community Abundance to Geochemical and Hydrological Parameters

NASA Astrophysics Data System (ADS)

Farrell, T. B.; Quick, A. M.; Reeder, W. J.; Benner, S. G.; Tonina, D.; Feris, K. P.

2015-12-01

The hyporheic zone (HZ) of streams may be a significant source of nitrous oxide (N2O). However, the biogeochemical processes controlling N2O emissions remain poorly constrained due to difficulties in obtaining high-resolution chemical, physical, and biological data from streams. Our research elucidates specific controls on N2O production within the HZ by coupling the distribution of denitrifying microbial communities to flow dynamics (i.e. hydraulics and streambed morphology) and biogeochemical processes. We conducted a large-scale flume experiment that allowed us to constrain streambed morphology, flow rate, organic carbon loading, grain size distribution, and exogenous nitrate loading while enabling regular monitoring of dissolved oxygen, pH, alkalinity, nitrogen species, and elemental concentrations in the HZ. We also employed real-time PCR (qPCR) to quantify the distribution of denitrifying functional genes (nirS and nosZ, nitrite reductase and nitrous oxide reductase genes, respectively) in HZ sediment cores as a measure of denitrifying microorganism abundance. A steady increase in N2O was observed after 8 hours of residence time with a peak in concentration (9.5 μg-N/L) recorded at hour 18. Abundance of nosZ increased an order of magnitude between hours 8 and 18 (2.6x106 to 2.1x107 gene copy #/g dry sediment). nirS abundance remained within the same order of magnitude between hours 8 and 18 (1.7x107 to 3.8x107). Linear and nonlinear mixed-effects models were used to investigate N2O production in the HZ as a function of total nitrogen, nirS, nosZ, residence time, and dissolved oxygen. N2O production was localized at redox-controlled hotspots within the subsurface and concentrations were strongly correlated with the availability of nitrogen when an interaction with nosZ abundance was considered. On-going analysis will provide predictions of N2O production and support for conditions under which the HZ could be a significant contributor of N2O emissions. These results are also being used to parameterize a reactive transport model for predicting N2O production from stream sediments with different bedform morphologies, flow rates, and reactant concentrations.

Understanding tectonic stress and rock strength in the Nankai Trough accretionary prism, offshore SW Japan

NASA Astrophysics Data System (ADS)

Huffman, Katelyn A.

Understanding the orientation and magnitude of tectonic stress in active tectonic margins like subduction zones is important for understanding fault mechanics. In the Nankai Trough subduction zone, faults in the accretionary prism are thought to have historically slipped during or immediately following deep plate boundary earthquakes, often generating devastating tsunamis. I focus on quantifying stress at two locations of interest in the Nankai Trough accretionary prism, offshore Southwest Japan. I employ a method to constrain stress magnitude that combines observations of compressional borehole failure from logging-while-drilling resistivity-at-the-bit generated images (RAB) with estimates of rock strength and the relationship between tectonic stress and stress at the wall of a borehole. I use the method to constrain stress at Ocean Drilling Program (ODP) Site 808 and Integrated Ocean Drilling Program (IODP) Site C0002. At Site 808, I consider a range of parameters (assumed rock strength, friction coefficient, breakout width, and fluid pressure) in the method to constrain stress to explore uncertainty in stress magnitudes and discuss stress results in terms of the seismic cycle. I find a combination of increased fluid pressure and decreased friction along the frontal thrust or other weak faults could produce thrust-style failure, without the entire prism being at critical state failure, as other kinematic models of accretionary prism behavior during earthquakes imply. Rock strength is typically inferred using a failure criterion and unconfined compressive strength from empirical relations with P-wave velocity. I minimize uncertainty in rock strength by measuring rock strength in triaxial tests on Nankai core. I find strength of Nankai core is significantly less than empirical relations predict. I create a new empirical fit to our experiments and explore implications of this on stress magnitude estimates. I find using the new empirical fit can decrease stress predicted in the method by as much as 4 MPa at Site C0002. I constrain stress at Site C0002 using geophysical logging data from two adjacent boreholes drilled into the same sedimentary sequence with different drilling conditions in a forward model that predicts breakout width over a range of horizontal stresses (where SHmax is constrained by the ratio of stresses that would produce active faulting and Shmin is constrained from leak-off-tests) and rock strength. I then compare predicted breakout widths to observations of breakout widths from RAB images to determine the combination of stresses in the model that best match real world observations. This is the first published method to constrain both stress and strength simultaneously. Finally, I explore uncertainty in rock behavior during compressional breakout formation using a finite element model (FEM) that predicts Biot poroelastic changes in fluid pressure in rock adjacent to the borehole upon its excavation and explore the effect this has on rock failure. I test a range of permeability and rock stiffness. I find that when rock stiffness and permeability are in the range of what exists at Nankai, pore fluid pressure increase +/- 45° from Shmin and can lead to weakening of wall rock and a wider compressional failure zone than what would exist at equilibrium conditions. In a case example at, we find this can lead to an overestimate of tectonic stress using compressional failures of ~2 MPa in the area of the borehole where fluid pressure increases. In areas around the borehole where pore fluid decreases (+/- 45° from SHmax), the wall rock can strengthen which suppresses tensile failure. The implications of this research is that there are many potential pitfalls in the method to constrain stress using borehole breakouts in Nankai Trough mudstone, mostly due to uncertainty in parameters such as strength and underlying assumptions regarding constitutive rock behavior. More laboratory measurement and/or models of rock properties and rock constitutive behavior is needed to ensure the method is accurately providing constraints on stress magnitude. (Abstract shortened by ProQuest.).

Dynamics simulations for engineering macromolecular interactions

NASA Astrophysics Data System (ADS)

Robinson-Mosher, Avi; Shinar, Tamar; Silver, Pamela A.; Way, Jeffrey

2013-06-01

The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20 000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

Dynamics simulations for engineering macromolecular interactions.

PubMed

Robinson-Mosher, Avi; Shinar, Tamar; Silver, Pamela A; Way, Jeffrey

2013-06-01

The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20,000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions.

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

Cembranos, Jose A. R.; Diaz-Cruz, J. Lorenzo; Prado, Lilian

Dark Matter direct detection experiments are able to exclude interesting parameter space regions of particle models which predict an important amount of thermal relics. We use recent data to constrain the branon model and to compute the region that is favored by CDMS measurements. Within this work, we also update present colliders constraints with new studies coming from the LHC. Despite the present low luminosity, it is remarkable that for heavy branons, CMS and ATLAS measurements are already more constraining than previous analyses performed with TEVATRON and LEP data.

Strain doping: Reversible single-axis control of a complex oxide lattice via helium implantation

DOE PAGES

Guo, Hangwen; Dong, Shuai; Rack, Philip D.; ...

2015-06-25

We report on the use of helium ion implantation to independently control the out-of-plane lattice constant in epitaxial La 0.7Sr 0.3MnO 3 thin films without changing the in-plane lattice constants. The process is reversible by a vacuum anneal. Resistance and magnetization measurements show that even a small increase in the out-of-plane lattice constant of less than 1% can shift the metal-insulator transition and Curie temperatures by more than 100 °C. Unlike conventional epitaxy-based strain tuning methods which are constrained not only by the Poisson effect but by the limited set of available substrates, the present study shows that strain canmore » be independently and continuously controlled along a single axis. This permits novel control over orbital populations through Jahn-Teller effects, as shown by Monte Carlo simulations on a double-exchange model. As a result, the ability to reversibly control a single lattice parameter substantially broadens the phase space for experimental exploration of predictive models and leads to new possibilities for control over materials’ functional properties.« less

Internal mechanisms underlying anticipatory language processing: Evidence from event-related-potentials and neural oscillations.

PubMed

Li, Xiaoqing; Zhang, Yuping; Xia, Jinyan; Swaab, Tamara Y

2017-07-28

Although numerous studies have demonstrated that the language processing system can predict upcoming content during comprehension, there is still no clear picture of the anticipatory stage of predictive processing. This electroencephalograph study examined the cognitive and neural oscillatory mechanisms underlying anticipatory processing during language comprehension, and the consequences of this prediction for bottom-up processing of predicted/unpredicted content. Participants read Mandarin Chinese sentences that were either strongly or weakly constraining and that contained critical nouns that were congruent or incongruent with the sentence contexts. We examined the effects of semantic predictability on anticipatory processing prior to the onset of the critical nouns and on integration of the critical nouns. The results revealed that, at the integration stage, the strong-constraint condition (compared to the weak-constraint condition) elicited a reduced N400 and reduced theta activity (4-7Hz) for the congruent nouns, but induced beta (13-18Hz) and theta (4-7Hz) power decreases for the incongruent nouns, indicating benefits of confirmed predictions and potential costs of disconfirmed predictions. More importantly, at the anticipatory stage, the strongly constraining context elicited an enhanced sustained anterior negativity and beta power decrease (19-25Hz), which indicates that strong prediction places a higher processing load on the anticipatory stage of processing. The differences (in the ease of processing and the underlying neural oscillatory activities) between anticipatory and integration stages of lexical processing were discussed with regard to predictive processing models. Copyright © 2017 Elsevier Ltd. All rights reserved.

Extracting falsifiable predictions from sloppy models.

PubMed

Gutenkunst, Ryan N; Casey, Fergal P; Waterfall, Joshua J; Myers, Christopher R; Sethna, James P

2007-12-01

Successful predictions are among the most compelling validations of any model. Extracting falsifiable predictions from nonlinear multiparameter models is complicated by the fact that such models are commonly sloppy, possessing sensitivities to different parameter combinations that range over many decades. Here we discuss how sloppiness affects the sorts of data that best constrain model predictions, makes linear uncertainty approximations dangerous, and introduces computational difficulties in Monte-Carlo uncertainty analysis. We also present a useful test problem and suggest refinements to the standards by which models are communicated.

Explicit Low-Thrust Guidance for Reference Orbit Targeting

NASA Technical Reports Server (NTRS)

Lam, Try; Udwadia, Firdaus E.

2013-01-01

The problem of a low-thrust spacecraft controlled to a reference orbit is addressed in this paper. A simple and explicit low-thrust guidance scheme with constrained thrust magnitude is developed by combining the fundamental equations of motion for constrained systems from analytical dynamics with a Lyapunov-based method. Examples are given for a spacecraft controlled to a reference trajectory in the circular restricted three body problem.

Solving constrained minimum-time robot problems using the sequential gradient restoration algorithm

NASA Technical Reports Server (NTRS)

Lee, Allan Y.

1991-01-01

Three constrained minimum-time control problems of a two-link manipulator are solved using the Sequential Gradient and Restoration Algorithm (SGRA). The inequality constraints considered are reduced via Valentine-type transformations to nondifferential path equality constraints. The SGRA is then used to solve these transformed problems with equality constraints. The results obtained indicate that at least one of the two controls is at its limits at any instant in time. The remaining control then adjusts itself so that none of the system constraints is violated. Hence, the minimum-time control is either a pure bang-bang control or a combined bang-bang/singular control.

Constrained minimization of smooth functions using a genetic algorithm

NASA Technical Reports Server (NTRS)

Moerder, Daniel D.; Pamadi, Bandu N.

1994-01-01

The use of genetic algorithms for minimization of differentiable functions that are subject to differentiable constraints is considered. A technique is demonstrated for converting the solution of the necessary conditions for a constrained minimum into an unconstrained function minimization. This technique is extended as a global constrained optimization algorithm. The theory is applied to calculating minimum-fuel ascent control settings for an energy state model of an aerospace plane.

Statistical Issues in Galaxy Cluster Cosmology

NASA Technical Reports Server (NTRS)

Mantz, Adam

2013-01-01

The number and growth of massive galaxy clusters are sensitive probes of cosmological structure formation. Surveys at various wavelengths can detect clusters to high redshift, but the fact that cluster mass is not directly observable complicates matters, requiring us to simultaneously constrain scaling relations of observable signals with mass. The problem can be cast as one of regression, in which the data set is truncated, the (cosmology-dependent) underlying population must be modeled, and strong, complex correlations between measurements often exist. Simulations of cosmological structure formation provide a robust prediction for the number of clusters in the Universe as a function of mass and redshift (the mass function), but they cannot reliably predict the observables used to detect clusters in sky surveys (e.g. X-ray luminosity). Consequently, observers must constrain observable-mass scaling relations using additional data, and use the scaling relation model in conjunction with the mass function to predict the number of clusters as a function of redshift and luminosity.

Affective-cognitive meta-bases versus structural bases of attitudes predict processing interest versus efficiency.

PubMed

See, Ya Hui Michelle; Petty, Richard E; Fabrigar, Leandre R

2013-08-01

We proposed that (a) processing interest for affective over cognitive information is captured by meta-bases (i.e., the extent to which people subjectively perceive themselves to rely on affect or cognition in their attitudes) and (b) processing efficiency for affective over cognitive information is captured by structural bases (i.e., the extent to which attitudes are more evaluatively congruent with affect or cognition). Because processing speed can disentangle interest from efficiency by being manifest as longer or shorter reading times, we hypothesized and found that more affective meta-bases predicted longer affective than cognitive reading time when processing efficiency was held constant (Study 1). In contrast, more affective structural bases predicted shorter affective than cognitive reading time when participants were constrained in their ability to allocate resources deliberatively (Study 2). When deliberation was neither encouraged nor constrained, effects for meta-bases and structural bases emerged (Study 3). Implications for affective-cognitive processing and other attitudes-relevant constructs are discussed.

Deep cultural ancestry and human development indicators across nation states

PubMed Central

Sookias, Roland B.; Passmore, Samuel

2018-01-01

How historical connections, events and cultural proximity can influence human development is being increasingly recognized. One aspect of history that has only recently begun to be examined is deep cultural ancestry, i.e. the vertical relationships of descent between cultures, which can be represented by a phylogenetic tree of descent. Here, we test whether deep cultural ancestry predicts the United Nations Human Development Index (HDI) for 44 Eurasian countries, using language ancestry as a proxy for cultural relatedness and controlling for three additional factors—geographical proximity, religion and former communism. While cultural ancestry alone predicts HDI and its subcomponents (income, health and education indices), when geographical proximity is included only income and health indices remain significant and the effect is small. When communism and religion variables are included, cultural ancestry is no longer a significant predictor; communism significantly negatively predicts HDI, income and health indices, and Muslim percentage of the population significantly negatively predicts education index, although the latter result may not be robust. These findings indicate that geographical proximity and recent cultural history—especially communism—are more important than deep cultural factors in current human development and suggest the efficacy of modern policy initiatives is not tightly constrained by cultural ancestry. PMID:29765628

Deep cultural ancestry and human development indicators across nation states.

PubMed

Sookias, Roland B; Passmore, Samuel; Atkinson, Quentin D

2018-04-01

How historical connections, events and cultural proximity can influence human development is being increasingly recognized. One aspect of history that has only recently begun to be examined is deep cultural ancestry, i.e. the vertical relationships of descent between cultures, which can be represented by a phylogenetic tree of descent. Here, we test whether deep cultural ancestry predicts the United Nations Human Development Index (HDI) for 44 Eurasian countries, using language ancestry as a proxy for cultural relatedness and controlling for three additional factors-geographical proximity, religion and former communism. While cultural ancestry alone predicts HDI and its subcomponents (income, health and education indices), when geographical proximity is included only income and health indices remain significant and the effect is small. When communism and religion variables are included, cultural ancestry is no longer a significant predictor; communism significantly negatively predicts HDI, income and health indices, and Muslim percentage of the population significantly negatively predicts education index, although the latter result may not be robust. These findings indicate that geographical proximity and recent cultural history-especially communism-are more important than deep cultural factors in current human development and suggest the efficacy of modern policy initiatives is not tightly constrained by cultural ancestry.

A new algorithm for stand table projection models.

Treesearch

Quang V. Cao; V. Clark Baldwin

1999-01-01

The constrained least squares method is proposed as an algorithm for projecting stand tables through time. This method consists of three steps: (1) predict survival in each diameter class, (2) predict diameter growth, and (3) use the least squares approach to adjust the stand table to satisfy the constraints of future survival, average diameter, and stand basal area....

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

PubMed

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.

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

WANG,YIFENG; XU,HUIFANG

Correctly identifying the possible alteration products and accurately predicting their occurrence in a repository-relevant environment are the key for the source-term calculation in a repository performance assessment. Uraninite in uranium deposits has long been used as a natural analog to spent fuel in a repository because of their chemical and structural similarity. In this paper, a SEM/AEM investigation has been conducted on a partially alternated uraninite sample from a uranium ore deposit of Shinkolobwe of Congo. The mineral formation sequences were identified: uraninite {yields} uranyl hydrates {yields} uranyl silicates {yields} Ca-uranyl silicates or uraninite {yields} uranyl silicates {yields} Ca-uranyl silicates.more » Reaction-path calculations were conducted for the oxidative dissolution of spent fuel in a representative Yucca Mountain groundwater. The predicted sequence is in general consistent with the SEM observations. The calculations also show that uranium carbonate minerals are unlikely to become major solubility-controlling mineral phases in a Yucca Mountain environment. Some discrepancies between model predictions and field observations are observed. Those discrepancies may result from poorly constrained thermodynamic data for uranyl silicate minerals.« less

A mixture model with a reference-based automatic selection of components for disease classification from protein and/or gene expression levels

PubMed Central

2011-01-01

Background Bioinformatics data analysis is often using linear mixture model representing samples as additive mixture of components. Properly constrained blind matrix factorization methods extract those components using mixture samples only. However, automatic selection of extracted components to be retained for classification analysis remains an open issue. Results The method proposed here is applied to well-studied protein and genomic datasets of ovarian, prostate and colon cancers to extract components for disease prediction. It achieves average sensitivities of: 96.2 (sd = 2.7%), 97.6% (sd = 2.8%) and 90.8% (sd = 5.5%) and average specificities of: 93.6% (sd = 4.1%), 99% (sd = 2.2%) and 79.4% (sd = 9.8%) in 100 independent two-fold cross-validations. Conclusions We propose an additive mixture model of a sample for feature extraction using, in principle, sparseness constrained factorization on a sample-by-sample basis. As opposed to that, existing methods factorize complete dataset simultaneously. The sample model is composed of a reference sample representing control and/or case (disease) groups and a test sample. Each sample is decomposed into two or more components that are selected automatically (without using label information) as control specific, case specific and not differentially expressed (neutral). The number of components is determined by cross-validation. Automatic assignment of features (m/z ratios or genes) to particular component is based on thresholds estimated from each sample directly. Due to the locality of decomposition, the strength of the expression of each feature across the samples can vary. Yet, they will still be allocated to the related disease and/or control specific component. Since label information is not used in the selection process, case and control specific components can be used for classification. That is not the case with standard factorization methods. Moreover, the component selected by proposed method as disease specific can be interpreted as a sub-mode and retained for further analysis to identify potential biomarkers. As opposed to standard matrix factorization methods this can be achieved on a sample (experiment)-by-sample basis. Postulating one or more components with indifferent features enables their removal from disease and control specific components on a sample-by-sample basis. This yields selected components with reduced complexity and generally, it increases prediction accuracy. PMID:22208882

An Agent-Based Model for Analyzing Control Policies and the Dynamic Service-Time Performance of a Capacity-Constrained Air Traffic Management Facility

NASA Technical Reports Server (NTRS)

Conway, Sheila R.

2006-01-01

Simple agent-based models may be useful for investigating air traffic control strategies as a precursory screening for more costly, higher fidelity simulation. Of concern is the ability of the models to capture the essence of the system and provide insight into system behavior in a timely manner and without breaking the bank. The method is put to the test with the development of a model to address situations where capacity is overburdened and potential for propagation of the resultant delay though later flights is possible via flight dependencies. The resultant model includes primitive representations of principal air traffic system attributes, namely system capacity, demand, airline schedules and strategy, and aircraft capability. It affords a venue to explore their interdependence in a time-dependent, dynamic system simulation. The scope of the research question and the carefully-chosen modeling fidelity did allow for the development of an agent-based model in short order. The model predicted non-linear behavior given certain initial conditions and system control strategies. Additionally, a combination of the model and dimensionless techniques borrowed from fluid systems was demonstrated that can predict the system s dynamic behavior across a wide range of parametric settings.

Network centrality and seasonality interact to predict lice load in a social primate

PubMed Central

Duboscq, Julie; Romano, Valeria; Sueur, Cédric; MacIntosh, Andrew J.J.

2016-01-01

Lice are socially-transmitted ectoparasites. Transmission depends upon their host’s degree of contact with conspecifics. While grooming facilitates ectoparasite transmission via body contact, it also constrains their spread through parasite removal. We investigated relations between parasite burden and sociality in female Japanese macaques following two opposing predictions: i) central females in contact/grooming networks harbour more lice, related to their numerous contacts; ii) central females harbour fewer lice, related to receiving more grooming. We estimated lice load non-invasively using the conspicuous louse egg-picking behaviour performed by macaques during grooming. We tested for covariation in several centrality measures and lice load, controlling for season, female reproductive state and dominance rank. Results show that the interaction between degree centrality (number of partners) and seasonality predicted lice load: females interacting with more partners had fewer lice than those interacting with fewer partners in winter and summer, whereas there was no relationship between lice load and centrality in spring and fall. This is counter to the prediction that increased contact leads to greater louse burden but fits the prediction that social grooming limits louse burden. Interactions between environmental seasonality and both parasite and host biology appeared to mediate the role of social processes in louse burden. PMID:26915589

Network centrality and seasonality interact to predict lice load in a social primate.

PubMed

Duboscq, Julie; Romano, Valeria; Sueur, Cédric; MacIntosh, Andrew J J

2016-02-26

Lice are socially-transmitted ectoparasites. Transmission depends upon their host's degree of contact with conspecifics. While grooming facilitates ectoparasite transmission via body contact, it also constrains their spread through parasite removal. We investigated relations between parasite burden and sociality in female Japanese macaques following two opposing predictions: i) central females in contact/grooming networks harbour more lice, related to their numerous contacts; ii) central females harbour fewer lice, related to receiving more grooming. We estimated lice load non-invasively using the conspicuous louse egg-picking behaviour performed by macaques during grooming. We tested for covariation in several centrality measures and lice load, controlling for season, female reproductive state and dominance rank. Results show that the interaction between degree centrality (number of partners) and seasonality predicted lice load: females interacting with more partners had fewer lice than those interacting with fewer partners in winter and summer, whereas there was no relationship between lice load and centrality in spring and fall. This is counter to the prediction that increased contact leads to greater louse burden but fits the prediction that social grooming limits louse burden. Interactions between environmental seasonality and both parasite and host biology appeared to mediate the role of social processes in louse burden.

Uncertainty analysis of depth predictions from seismic reflection data using Bayesian statistics

NASA Astrophysics Data System (ADS)

Michelioudakis, Dimitrios G.; Hobbs, Richard W.; Caiado, Camila C. S.

2018-03-01

Estimating the depths of target horizons from seismic reflection data is an important task in exploration geophysics. To constrain these depths we need a reliable and accurate velocity model. Here, we build an optimum 2D seismic reflection data processing flow focused on pre - stack deghosting filters and velocity model building and apply Bayesian methods, including Gaussian process emulation and Bayesian History Matching (BHM), to estimate the uncertainties of the depths of key horizons near the borehole DSDP-258 located in the Mentelle Basin, south west of Australia, and compare the results with the drilled core from that well. Following this strategy, the tie between the modelled and observed depths from DSDP-258 core was in accordance with the ± 2σ posterior credibility intervals and predictions for depths to key horizons were made for the two new drill sites, adjacent the existing borehole of the area. The probabilistic analysis allowed us to generate multiple realizations of pre-stack depth migrated images, these can be directly used to better constrain interpretation and identify potential risk at drill sites. The method will be applied to constrain the drilling targets for the upcoming International Ocean Discovery Program (IODP), leg 369.

Uncertainty analysis of depth predictions from seismic reflection data using Bayesian statistics

NASA Astrophysics Data System (ADS)

Michelioudakis, Dimitrios G.; Hobbs, Richard W.; Caiado, Camila C. S.

2018-06-01

Estimating the depths of target horizons from seismic reflection data is an important task in exploration geophysics. To constrain these depths we need a reliable and accurate velocity model. Here, we build an optimum 2-D seismic reflection data processing flow focused on pre-stack deghosting filters and velocity model building and apply Bayesian methods, including Gaussian process emulation and Bayesian History Matching, to estimate the uncertainties of the depths of key horizons near the Deep Sea Drilling Project (DSDP) borehole 258 (DSDP-258) located in the Mentelle Basin, southwest of Australia, and compare the results with the drilled core from that well. Following this strategy, the tie between the modelled and observed depths from DSDP-258 core was in accordance with the ±2σ posterior credibility intervals and predictions for depths to key horizons were made for the two new drill sites, adjacent to the existing borehole of the area. The probabilistic analysis allowed us to generate multiple realizations of pre-stack depth migrated images, these can be directly used to better constrain interpretation and identify potential risk at drill sites. The method will be applied to constrain the drilling targets for the upcoming International Ocean Discovery Program, leg 369.

Influence of central set on anticipatory and triggered grip-force adjustments

NASA Technical Reports Server (NTRS)

Winstein, C. J.; Horak, F. B.; Fisher, B. E.; Peterson, B. W. (Principal Investigator)

2000-01-01

The effects of predictability of load magnitude on anticipatory and triggered grip-force adjustments were studied as nine normal subjects used a precision grip to lift, hold, and replace an instrumented test object. Experience with a predictable stimulus has been shown to enhance magnitude scaling of triggered postural responses to different amplitudes of perturbations. However, this phenomenon, known as a central-set effect, has not been tested systematically for grip-force responses in the hand. In our study, predictability was manipulated by applying load perturbations of different magnitudes to the test object under conditions in which the upcoming load magnitude was presented repeatedly or under conditions in which the load magnitudes were presented randomly, each with two different pre-load grip conditions (unconstrained and constrained). In constrained conditions, initial grip forces were maintained near the minimum level necessary to prevent pre-loaded object slippage, while in unconstrained conditions, no initial grip force restrictions were imposed. The effect of predictable (blocked) and unpredictable (random) load presentations on scaling of anticipatory and triggered grip responses was tested by comparing the slopes of linear regressions between the imposed load and grip response magnitude. Anticipatory and triggered grip force responses were scaled to load magnitude in all conditions. However, regardless of pre-load grip force constraint, the gains (slopes) of grip responses relative to load magnitudes were greater when the magnitude of the upcoming load was predictable than when the load increase was unpredictable. In addition, a central-set effect was evidenced by the fewer number of drop trials in the predictable relative to unpredictable load conditions. Pre-load grip forces showed the greatest set effects. However, grip responses showed larger set effects, based on prediction, when pre-load grip force was constrained to lower levels. These results suggest that anticipatory processes pertaining to load magnitude permit the response gain of both voluntary and triggered rapid grip force adjustments to be set, at least partially, prior to perturbation onset. Comparison of anticipatory set effects for reactive torque and lower extremity EMG postural responses triggered by surface translation perturbations suggests a more general rule governing anticipatory processes.

PREDICTING CME EJECTA AND SHEATH FRONT ARRIVAL AT L1 WITH A DATA-CONSTRAINED PHYSICAL MODEL

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

Hess, Phillip; Zhang, Jie, E-mail: phess4@gmu.edu

2015-10-20

We present a method for predicting the arrival of a coronal mass ejection (CME) flux rope in situ, as well as the sheath of solar wind plasma accumulated ahead of the driver. For faster CMEs, the front of this sheath will be a shock. The method is based upon geometrical separate measurement of the CME ejecta and sheath. These measurements are used to constrain a drag-based model, improved by including both a height dependence and accurate de-projected velocities. We also constrain the geometry of the model to determine the error introduced as a function of the deviation of the CMEmore » nose from the Sun–Earth line. The CME standoff-distance in the heliosphere fit is also calculated, fit, and combined with the ejecta model to determine sheath arrival. Combining these factors allows us to create predictions for both fronts at the L1 point and compare them against observations. We demonstrate an ability to predict the sheath arrival with an average error of under 3.5 hr, with an rms error of about 1.58 hr. For the ejecta the error is less than 1.5 hr, with an rms error within 0.76 hr. We also discuss the physical implications of our model for CME expansion and density evolution. We show the power of our method with ideal data and demonstrate the practical implications of having a permanent L5 observer with space weather forecasting capabilities, while also discussing the limitations of the method that will have to be addressed in order to create a real-time forecasting tool.« less

Active constrained layer damping of geometrically nonlinear vibrations of functionally graded plates using piezoelectric fiber-reinforced composites

NASA Astrophysics Data System (ADS)

Panda, Satyajit; Ray, M. C.

2008-04-01

In this paper, a geometrically nonlinear dynamic analysis has been presented for functionally graded (FG) plates integrated with a patch of active constrained layer damping (ACLD) treatment and subjected to a temperature field. The constraining layer of the ACLD treatment is considered to be made of the piezoelectric fiber-reinforced composite (PFRC) material. The temperature field is assumed to be spatially uniform over the substrate plate surfaces and varied through the thickness of the host FG plates. The temperature-dependent material properties of the FG substrate plates are assumed to be graded in the thickness direction of the plates according to a power-law distribution while the Poisson's ratio is assumed to be a constant over the domain of the plate. The constrained viscoelastic layer of the ACLD treatment is modeled using the Golla-Hughes-McTavish (GHM) method. Based on the first-order shear deformation theory, a three-dimensional finite element model has been developed to model the open-loop and closed-loop nonlinear dynamics of the overall FG substrate plates under the thermal environment. The analysis suggests the potential use of the ACLD treatment with its constraining layer made of the PFRC material for active control of geometrically nonlinear vibrations of FG plates in the absence or the presence of the temperature gradient across the thickness of the plates. It is found that the ACLD treatment is more effective in controlling the geometrically nonlinear vibrations of FG plates than in controlling their linear vibrations. The analysis also reveals that the ACLD patch is more effective for controlling the nonlinear vibrations of FG plates when it is attached to the softest surface of the FG plates than when it is bonded to the stiffest surface of the plates. The effect of piezoelectric fiber orientation in the active constraining PFRC layer on the damping characteristics of the overall FG plates is also discussed.

Experimental Validation of a Thermoelastic Model for SMA Hybrid Composites

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2001-01-01

This study presents results from experimental validation of a recently developed model for predicting the thermomechanical behavior of shape memory alloy hybrid composite (SMAHC) structures, composite structures with an embedded SMA constituent. The model captures the material nonlinearity of the material system with temperature and is capable of modeling constrained, restrained, or free recovery behavior from experimental measurement of fundamental engineering properties. A brief description of the model and analysis procedures is given, followed by an overview of a parallel effort to fabricate and characterize the material system of SMAHC specimens. Static and dynamic experimental configurations for the SMAHC specimens are described and experimental results for thermal post-buckling and random response are presented. Excellent agreement is achieved between the measured and predicted results, fully validating the theoretical model for constrained recovery behavior of SMAHC structures.

Constraining Lyman continuum escape using Machine Learning

NASA Astrophysics Data System (ADS)

Giri, Sambit K.; Zackrisson, Erik; Binggeli, Christian; Pelckmans, Kristiaan; Cubo, Rubén; Mellema, Garrelt

2018-05-01

The James Webb Space Telescope (JWST) will observe the rest-frame ultraviolet/optical spectra of galaxies from the epoch of reionization (EoR) in unprecedented detail. While escaping into the intergalactic medium, hydrogen-ionizing (Lyman continuum; LyC) photons from the galaxies will contribute to the bluer end of the UV slope and make nebular emission lines less prominent. We present a method to constrain leakage of the LyC photons using the spectra of high redshift (z >~ 6) galaxies. We simulate JWST/NIRSpec observations of galaxies at z =6-9 by matching the fluxes of galaxies observed in the Frontier Fields observations of galaxy cluster MACS-J0416. Our method predicts the escape fraction fesc with a mean absolute error Δfesc ~ 0.14. The method also predicts the redshifts of the galaxies with an error .

Search for standard model production of four top quarks with same-sign and multilepton final states in proton–proton collisions at $$\\sqrt{s} = 13\\,\\text {TeV} $$

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

Sirunyan, A. M.; Tumasyan, A.; Adam, W.

A search for standard model production of four top quarks (more » $$\\mathrm{t}\\overline{\\mathrm{t}}\\mathrm{t}\\overline{\\mathrm{t}})$$ is reported using events containing at least three leptons (e, $$\\mu$$) or a same-sign lepton pair. The events are produced in proton-proton collisions at a center-of-mass energy of 13 TeV at the LHC, and the data sample, recorded in 2016, corresponds to an integrated luminosity of 35.9 fb$$^{-1}$$. Jet multiplicity and flavor are used to enhance signal sensitivity, and dedicated control regions are used to constrain the dominant backgrounds. The observed and expected signal significances are, respectively, 1.6 and 1.0 standard deviations, and the $$\\mathrm{t}\\overline{\\mathrm{t}}\\mathrm{t}\\overline{\\mathrm{t}}$$ cross section is measured to be 16.9 $$^{+13.8}_{-11.4}$$ fb, in agreement with next-to-leading-order standard model predictions. These results are also used to constrain the Yukawa coupling between the top quark and the Higgs boson to be less than 2.1 times its expected standard model value at 95% confidence level.« less

Search for standard model production of four top quarks with same-sign and multilepton final states in proton–proton collisions at $$\\sqrt{s} = 13\\,\\text {TeV} $$

DOE PAGES

Sirunyan, A. M.; Tumasyan, A.; Adam, W.; ...

2018-02-19

A search for standard model production of four top quarks (more » $$\\mathrm{t}\\overline{\\mathrm{t}}\\mathrm{t}\\overline{\\mathrm{t}})$$ is reported using events containing at least three leptons (e, $$\\mu$$) or a same-sign lepton pair. The events are produced in proton-proton collisions at a center-of-mass energy of 13 TeV at the LHC, and the data sample, recorded in 2016, corresponds to an integrated luminosity of 35.9 fb$$^{-1}$$. Jet multiplicity and flavor are used to enhance signal sensitivity, and dedicated control regions are used to constrain the dominant backgrounds. The observed and expected signal significances are, respectively, 1.6 and 1.0 standard deviations, and the $$\\mathrm{t}\\overline{\\mathrm{t}}\\mathrm{t}\\overline{\\mathrm{t}}$$ cross section is measured to be 16.9 $$^{+13.8}_{-11.4}$$ fb, in agreement with next-to-leading-order standard model predictions. These results are also used to constrain the Yukawa coupling between the top quark and the Higgs boson to be less than 2.1 times its expected standard model value at 95% confidence level.« less

Tongue Images Classification Based on Constrained High Dispersal Network.

PubMed

Meng, Dan; Cao, Guitao; Duan, Ye; Zhu, Minghua; Tu, Liping; Xu, Dong; Xu, Jiatuo

2017-01-01

Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM). However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue. Inspired by deep convolutional neural network (CNN), we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet) to extract unbiased features and reduce human labor for tongue diagnosis in TCM. Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution. We introduce high dispersal and local response normalization operation to address the issue of redundancy. We also add multiscale feature analysis to avoid the problem of sensitivity to deformation. Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples. We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers. Test results show that CHDNet is a promising method in tongue image classification for the TCM study.

A compact and accurate semi-global potential energy surface for malonaldehyde from constrained least squares regression

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

Mizukami, Wataru, E-mail: wataru.mizukami@bristol.ac.uk; Tew, David P., E-mail: david.tew@bristol.ac.uk; Habershon, Scott, E-mail: S.Habershon@warwick.ac.uk

2014-10-14

We present a new approach to semi-global potential energy surface fitting that uses the least absolute shrinkage and selection operator (LASSO) constrained least squares procedure to exploit an extremely flexible form for the potential function, while at the same time controlling the risk of overfitting and avoiding the introduction of unphysical features such as divergences or high-frequency oscillations. Drawing from a massively redundant set of overlapping distributed multi-dimensional Gaussian functions of inter-atomic separations we build a compact full-dimensional surface for malonaldehyde, fit to explicitly correlated coupled cluster CCSD(T)(F12*) energies with a root mean square deviations accuracy of 0.3%–0.5% up tomore » 25 000 cm{sup −1} above equilibrium. Importance-sampled diffusion Monte Carlo calculations predict zero point energies for malonaldehyde and its deuterated isotopologue of 14 715.4(2) and 13 997.9(2) cm{sup −1} and hydrogen transfer tunnelling splittings of 21.0(4) and 3.2(4) cm{sup −1}, respectively, which are in excellent agreement with the experimental values of 21.583 and 2.915(4) cm{sup −1}.« less

Solution of nonlinear multivariable constrained systems using a gradient projection digital algorithm that is insensitive to the initial state

NASA Technical Reports Server (NTRS)

Hargrove, A.

1982-01-01

Optimal digital control of nonlinear multivariable constrained systems was studied. The optimal controller in the form of an algorithm was improved and refined by reducing running time and storage requirements. A particularly difficult system of nine nonlinear state variable equations was chosen as a test problem for analyzing and improving the controller. Lengthy analysis, modeling, computing and optimization were accomplished. A remote interactive teletype terminal was installed. Analysis requiring computer usage of short duration was accomplished using Tuskegee's VAX 11/750 system.

Necessary optimality conditions for infinite dimensional state constrained control problems

NASA Astrophysics Data System (ADS)

Frankowska, H.; Marchini, E. M.; Mazzola, M.

2018-06-01

This paper is concerned with first order necessary optimality conditions for state constrained control problems in separable Banach spaces. Assuming inward pointing conditions on the constraint, we give a simple proof of Pontryagin maximum principle, relying on infinite dimensional neighboring feasible trajectories theorems proved in [20]. Further, we provide sufficient conditions guaranteeing normality of the maximum principle. We work in the abstract semigroup setting, but nevertheless we apply our results to several concrete models involving controlled PDEs. Pointwise state constraints (as positivity of the solutions) are allowed.

Maximum principle for a stochastic delayed system involving terminal state constraints.

PubMed

Wen, Jiaqiang; Shi, Yufeng

2017-01-01

We investigate a stochastic optimal control problem where the controlled system is depicted as a stochastic differential delayed equation; however, at the terminal time, the state is constrained in a convex set. We firstly introduce an equivalent backward delayed system depicted as a time-delayed backward stochastic differential equation. Then a stochastic maximum principle is obtained by virtue of Ekeland's variational principle. Finally, applications to a state constrained stochastic delayed linear-quadratic control model and a production-consumption choice problem are studied to illustrate the main obtained result.

Integrated detection of fractures and caves in carbonate fractured-vuggy reservoirs based on seismic data and well data

NASA Astrophysics Data System (ADS)

Cao, Zhanning; Li, Xiangyang; Sun, Shaohan; Liu, Qun; Deng, Guangxiao

2018-04-01

Aiming at the prediction of carbonate fractured-vuggy reservoirs, we put forward an integrated approach based on seismic and well data. We divide a carbonate fracture-cave system into four scales for study: micro-scale fracture, meso-scale fracture, macro-scale fracture and cave. Firstly, we analyze anisotropic attributes of prestack azimuth gathers based on multi-scale rock physics forward modeling. We select the frequency attenuation gradient attribute to calculate azimuth anisotropy intensity, and we constrain the result with Formation MicroScanner image data and trial production data to predict the distribution of both micro-scale and meso-scale fracture sets. Then, poststack seismic attributes, variance, curvature and ant algorithms are used to predict the distribution of macro-scale fractures. We also constrain the results with trial production data for accuracy. Next, the distribution of caves is predicted by the amplitude corresponding to the instantaneous peak frequency of the seismic imaging data. Finally, the meso-scale fracture sets, macro-scale fractures and caves are combined to obtain an integrated result. This integrated approach is applied to a real field in Tarim Basin in western China for the prediction of fracture-cave reservoirs. The results indicate that this approach can well explain the spatial distribution of carbonate reservoirs. It can solve the problem of non-uniqueness and improve fracture prediction accuracy.

Estimating radiative feedbacks from stochastic fluctuations in surface temperature and energy imbalance

NASA Astrophysics Data System (ADS)

Proistosescu, C.; Donohoe, A.; Armour, K.; Roe, G.; Stuecker, M. F.; Bitz, C. M.

2017-12-01

Joint observations of global surface temperature and energy imbalance provide for a unique opportunity to empirically constrain radiative feedbacks. However, the satellite record of Earth's radiative imbalance is relatively short and dominated by stochastic fluctuations. Estimates of radiative feedbacks obtained by regressing energy imbalance against surface temperature depend strongly on sampling choices and on assumptions about whether the stochastic fluctuations are primarily forced by atmospheric or oceanic variability (e.g. Murphy and Forster 2010, Dessler 2011, Spencer and Braswell 2011, Forster 2016). We develop a framework around a stochastic energy balance model that allows us to parse the different contributions of atmospheric and oceanic forcing based on their differing impacts on the covariance structure - or lagged regression - of temperature and radiative imbalance. We validate the framework in a hierarchy of general circulation models: the impact of atmospheric forcing is examined in unforced control simulations of fixed sea-surface temperature and slab ocean model versions; the impact of oceanic forcing is examined in coupled simulations with prescribed ENSO variability. With the impact of atmospheric and oceanic forcing constrained, we are able to predict the relationship between temperature and radiative imbalance in a fully coupled control simulation, finding that both forcing sources are needed to explain the structure of the lagged-regression. We further model the dependence of feedback estimates on sampling interval by considering the effects of a finite equilibration time for the atmosphere, and issues of smoothing and aliasing. Finally, we develop a method to fit the stochastic model to the short timeseries of temperature and radiative imbalance by performing a Bayesian inference based on a modified version of the spectral Whittle likelihood. We are thus able to place realistic joint uncertainty estimates on both stochastic forcing and radiative feedbacks derived from observational records. We find that these records are, as of yet, too short to be useful in constraining radiative feedbacks, and we provide estimates of how the uncertainty narrows as a function of record length.

A hierarchical spatial model for well yield in complex aquifers

NASA Astrophysics Data System (ADS)

Montgomery, J.; O'sullivan, F.

2017-12-01

Efficiently siting and managing groundwater wells requires reliable estimates of the amount of water that can be produced, or the well yield. This can be challenging to predict in highly complex, heterogeneous fractured aquifers due to the uncertainty around local hydraulic properties. Promising statistical approaches have been advanced in recent years. For instance, kriging and multivariate regression analysis have been applied to well test data with limited but encouraging levels of prediction accuracy. Additionally, some analytical solutions to diffusion in homogeneous porous media have been used to infer "effective" properties consistent with observed flow rates or drawdown. However, this is an under-specified inverse problem with substantial and irreducible uncertainty. We describe a flexible machine learning approach capable of combining diverse datasets with constraining physical and geostatistical models for improved well yield prediction accuracy and uncertainty quantification. Our approach can be implemented within a hierarchical Bayesian framework using Markov Chain Monte Carlo, which allows for additional sources of information to be incorporated in priors to further constrain and improve predictions and reduce the model order. We demonstrate the usefulness of this approach using data from over 7,000 wells in a fractured bedrock aquifer.

Constrained dynamics approach for motion synchronization and consensus

NASA Astrophysics Data System (ADS)

Bhatia, Divya

In this research we propose to develop constrained dynamical systems based stable attitude synchronization, consensus and tracking (SCT) control laws for the formation of rigid bodies. The generalized constrained dynamics Equations of Motion (EOM) are developed utilizing constraint potential energy functions that enforce communication constraints. Euler-Lagrange equations are employed to develop the non-linear constrained dynamics of multiple vehicle systems. The constraint potential energy is synthesized based on a graph theoretic formulation of the vehicle-vehicle communication. Constraint stabilization is achieved via Baumgarte's method. The performance of these constrained dynamics based formations is evaluated for bounded control authority. The above method has been applied to various cases and the results have been obtained using MATLAB simulations showing stability, synchronization, consensus and tracking of formations. The first case corresponds to an N-pendulum formation without external disturbances, in which the springs and the dampers connected between the pendulums act as the communication constraints. The damper helps in stabilizing the system by damping the motion whereas the spring acts as a communication link relaying relative position information between two connected pendulums. Lyapunov stabilization (energy based stabilization) technique is employed to depict the attitude stabilization and boundedness. Various scenarios involving different values of springs and dampers are simulated and studied. Motivated by the first case study, we study the formation of N 2-link robotic manipulators. The governing EOM for this system is derived using Euler-Lagrange equations. A generalized set of communication constraints are developed for this system using graph theory. The constraints are stabilized using Baumgarte's techniques. The attitude SCT is established for this system and the results are shown for the special case of three 2-link robotic manipulators. These methods are then applied to the formation of N-spacecraft. Modified Rodrigues Parameters (MRP) are used for attitude representation of the spacecraft because of their advantage of being a minimum parameter representation. Constrained non-linear equations of motion for this system are developed and stabilized using a Proportional-Derivative (PD) controller derived based on Baumgarte's method. A system of 3 spacecraft is simulated and the results for SCT are shown and analyzed. Another problem studied in this research is that of maintaining SCT under unknown external disturbances. We use an adaptive control algorithm to derive control laws for the actuator torques and develop an estimation law for the unknown disturbance parameters to achieve SCT. The estimate of the disturbance is added as a feed forward term in the actual control law to obtain the stabilization of a 3-spacecraft formation. The disturbance estimates are generated via a Lyapunov analysis of the closed loop system. In summary, the constrained dynamics method shows a lot of potential in formation control, achieving stabilization, synchronization, consensus and tracking of a set of dynamical systems.

Constraining modified gravitational theories by weak lensing with Euclid

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

Martinelli, Matteo; Calabrese, Erminia; De Bernardis, Francesco

2011-01-15

Future proposed satellite missions such as Euclid can offer the opportunity to test general relativity on cosmic scales through mapping of the galaxy weak-lensing signal. In this paper we forecast the ability of these experiments to constrain modified gravity scenarios such as those predicted by scalar-tensor and f(R) theories. We find that Euclid will improve constraints expected from the Planck satellite on these modified theories of gravity by 2 orders of magnitude. We discuss parameter degeneracies and the possible biases introduced by modifications to gravity.

Flowering time and seed dormancy control use external coincidence to generate life history strategy

PubMed Central

Springthorpe, Vicki; Penfield, Steven

2015-01-01

Climate change is accelerating plant developmental transitions coordinated with the seasons in temperate environments. To understand the importance of these timing advances for a stable life history strategy, we constructed a full life cycle model of Arabidopsis thaliana. Modelling and field data reveal that a cryptic function of flowering time control is to limit seed set of winter annuals to an ambient temperature window which coincides with a temperature-sensitive switch in seed dormancy state. This coincidence is predicted to be conserved independent of climate at the expense of flowering date, suggesting that temperature control of flowering time has evolved to constrain seed set environment and therefore frequency of dormant and non-dormant seed states. We show that late flowering can disrupt this bet-hedging germination strategy. Our analysis shows that life history modelling can reveal hidden fitness constraints and identify non-obvious selection pressures as emergent features. DOI: http://dx.doi.org/10.7554/eLife.05557.001 PMID:25824056

A closed-form trim solution yielding minimum trim drag for airplanes with multiple longitudinal-control effectors

NASA Technical Reports Server (NTRS)

Goodrich, Kenneth H.; Sliwa, Steven M.; Lallman, Frederick J.

1989-01-01

Airplane designs are currently being proposed with a multitude of lifting and control devices. Because of the redundancy in ways to generate moments and forces, there are a variety of strategies for trimming each airplane. A linear optimum trim solution (LOTS) is derived using a Lagrange formulation. LOTS enables the rapid calculation of the longitudinal load distribution resulting in the minimum trim drag in level, steady-state flight for airplanes with a mixture of three or more aerodynamic surfaces and propulsive control effectors. Comparisons of the trim drags obtained using LOTS, a direct constrained optimization method, and several ad hoc methods are presented for vortex-lattice representations of a three-surface airplane and two-surface airplane with thrust vectoring. These comparisons show that LOTS accurately predicts the results obtained from the nonlinear optimization and that the optimum methods result in trim drag reductions of up to 80 percent compared to the ad hoc methods.

Interoceptive predictions in the brain

PubMed Central

Barrett, Lisa Feldman; Simmons, W. Kyle

2016-01-01

Intuition suggests that perception follows sensation and therefore bodily feelings originate in the body. However, recent evidence goes against this logic: interoceptive experience may largely reflect limbic predictions about the expected state of the body that are constrained by ascending visceral sensations. In this Opinion article, we introduce the Embodied Predictive Interoception Coding model, which integrates an anatomical model of corticocortical connections with Bayesian active inference principles, to propose that agranular visceromotor cortices contribute to interoception by issuing interoceptive predictions. We then discuss how disruptions in interoceptive predictions could function as a common vulnerability for mental and physical illness. PMID:26016744

SO(10) × S 4 grand unified theory of flavour and leptogenesis

NASA Astrophysics Data System (ADS)

de Anda, Francisco J.; King, Stephen F.; Perdomo, Elena

2017-12-01

We propose a Grand Unified Theory of Flavour, based on SO(10) together with a non-Abelian discrete group S 4, under which the unified three quark and lepton 16-plets are unified into a single triplet 3'. The model involves a further discrete group ℤ 4 R × ℤ 4 3 which controls the Higgs and flavon symmetry breaking sectors. The CSD2 flavon vacuum alignment is discussed, along with the GUT breaking potential and the doublet-triplet splitting, and proton decay is shown to be under control. The Yukawa matrices are derived in detail, from renormalisable diagrams, and neutrino masses emerge from the type I seesaw mechanism. A full numerical fit is performed with 15 input parameters generating 19 presently constrained observables, taking into account supersymmetry threshold corrections. The model predicts a normal neutrino mass ordering with a CP oscillation phase of 260°, an atmospheric angle in the first octant and neutrinoless double beta decay with m ββ = 11 meV. We discuss N 2 leptogenesis, which fixes the second right-handed neutrino mass to be M 2 ≃ 2 × 1011 GeV, in the natural range predicted by the model.

Scaling relationships among drivers of aquatic respiration from the smallest to the largest freshwater ecosystems

USGS Publications Warehouse

Hall, Ed K; Schoolmaster, Donald; Amado, A.M; Stets, Edward G.; Lennon, J.T.; Domaine, L.; Cotner, J.B.

2016-01-01

To address how various environmental parameters control or constrain planktonic respiration (PR), we used geometric scaling relationships and established biological scaling laws to derive quantitative predictions for the relationships among key drivers of PR. We then used empirical measurements of PR and environmental (soluble reactive phosphate [SRP], carbon [DOC], chlorophyll a [Chl-a)], and temperature) and landscape parameters (lake area [LA] and watershed area [WA]) from a set of 44 lakes that varied in size and trophic status to test our hypotheses. We found that landscape-level processes affected PR through direct effects on DOC and temperature and indirectly via SRP. In accordance with predictions made from known relationships and scaling laws, scale coefficients (the parameter that describes the shape of a relationship between 2 variables) were found to be negative and have an absolute value 1, others <1). We also found evidence of a significant relationship between temperature and SRP. Because our dataset included measurements of respiration from small pond catchments to the largest body of freshwater on the planet, Lake Superior, these findings should be applicable to controls of PR for the great majority of temperate aquatic ecosystems.

An historical survey of computational methods in optimal control.

NASA Technical Reports Server (NTRS)

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.

Coupled hydrological and geochemical process evolution at the Landscape Evolution Observatory

NASA Astrophysics Data System (ADS)

Troch, P. A. A.

2015-12-01

Predictions of hydrologic and biogeochemical responses to natural and anthropogenic forcing at the landscape scale are highly uncertain due to the effects of heterogeneity on the scaling of reaction, flow and transport phenomena. The physical, chemical and biological structures and processes controlling reaction, flow and transport in natural landscapes interact at multiple space and time scales and are difficult to quantify. The current paradigm of hydrological and geochemical theory is that process descriptions derived from observations at small scales in controlled systems can be applied to predict system response at much larger scales, as long as some 'equivalent' or 'effective' values of the scale-dependent parameters can be identified. Furthermore, natural systems evolve in time in a way that is hard to observe in short-run laboratory experiments or in natural landscapes with unknown initial conditions and time-variant forcing. The spatial structure of flow pathways along hillslopes determines the rate, extent and distribution of geochemical reactions (and biological colonization) that drive weathering, the transport and precipitation of solutes and sediments, and the further evolution of soil structure. The resulting evolution of structures and processes, in turn, produces spatiotemporal variability of hydrological states and flow pathways. There is thus a need for experimental research to improve our understanding of hydrology-biogeochemistry interactions and feedbacks at appropriate spatial scales larger than laboratory soil column experiments. Such research is complicated in real-world settings because of poorly constrained impacts of initial conditions, climate variability, ecosystems dynamics, and geomorphic evolution. The Landscape Evolution Observatory (LEO) at Biosphere 2 offers a unique research facility that allows real-time observations of incipient hydrologic and biogeochemical response under well-constrained initial conditions and climate forcing. The LEO allows to close the water, carbon and energy budgets at hillslope scales, thereby enabling elucidation of the tight coupling between the time water spends along subsurface flow paths and geochemical weathering reactions, including the feedbacks between flow and pedogenesis.

Crustal tracers in the atmosphere and ocean: Relating their concentrations, fluxes, and ages

NASA Astrophysics Data System (ADS)

Han, Qin

Crustal tracers are important sources of key limiting nutrients (e.g., iron) in remote ocean regions where they have a large impact on global biogeochemical cycles. However, the atmospheric delivery of bio-available iron to oceans via mineral dust aerosol deposition is poorly constrained. This dissertation aims to improve understanding and model representation of oceanic dust deposition and to provide soluble iron flux maps by testing observations of crustal tracer concentrations and solubilities against predictions from two conceptual solubility models. First, we assemble a database of ocean surface dissolved Al and incorporate Al cycling into the global Biogeochemical Elemental Cycling (BEC) model. The observed Al concentrations show clear basin-scale differences that are useful for constraining dust deposition. The dynamic mixed layer depth and Al residence time in the BEC model significantly improve the simulated dissolved Al field. Some of the remaining model-data discrepancies appear related to the neglect of aerosol size, age, and air mass characteristics in estimating tracer solubility. Next, we develop the Mass-Age Tracking method (MAT) to efficiently and accurately estimate the mass-weighted age of tracers. We apply MAT to four sizes of desert dust aerosol and simulate, for the first time, global distributions of aerosol age in the atmosphere and at deposition. These dust size and age distributions at deposition, together with independent information on air mass acidity, allow us to test two simple yet plausible models for predicting the dissolution of mineral dust iron and aluminum during atmospheric transport. These models represent aerosol solubility as controlled (1) by a diffusive process leaching nutrients from the dust into equilibrium with the liquid water coating or (2) by a process that continually dissolves nutrients in proportion to the particle surface area. The surface-controlled model better captures the spatial pattern of observed solubility in the Atlantic. Neither model improves previous estimates of the solubility in the Pacific, nor do they significantly improve the global BEC simulation of dissolved iron or aluminum.

Mentalizing Deficits Constrain Belief in a Personal God

PubMed Central

Norenzayan, Ara; Gervais, Will M.; Trzesniewski, Kali H.

2012-01-01

Religious believers intuitively conceptualize deities as intentional agents with mental states who anticipate and respond to human beliefs, desires and concerns. It follows that mentalizing deficits, associated with the autistic spectrum and also commonly found in men more than in women, may undermine this intuitive support and reduce belief in a personal God. Autistic adolescents expressed less belief in God than did matched neuro-typical controls (Study 1). In a Canadian student sample (Study 2), and two American national samples that controlled for demographic characteristics and other correlates of autism and religiosity (Study 3 and 4), the autism spectrum predicted reduced belief in God, and mentalizing mediated this relationship. Systemizing (Studies 2 and 3) and two personality dimensions related to religious belief, Conscientiousness and Agreeableness (Study 3), failed as mediators. Mentalizing also explained the robust and well-known, but theoretically debated, gender gap in religious belief wherein men show reduced religious belief (Studies 2–4). PMID:22666332

Planetary Transmission Diagnostics

NASA Technical Reports Server (NTRS)

Lewicki, David G. (Technical Monitor); Samuel, Paul D.; Conroy, Joseph K.; Pines, Darryll J.

2004-01-01

This report presents a methodology for detecting and diagnosing gear faults in the planetary stage of a helicopter transmission. This diagnostic technique is based on the constrained adaptive lifting algorithm. The lifting scheme, developed by Wim Sweldens of Bell Labs, is a time domain, prediction-error realization of the wavelet transform that allows for greater flexibility in the construction of wavelet bases. Classic lifting analyzes a given signal using wavelets derived from a single fundamental basis function. A number of researchers have proposed techniques for adding adaptivity to the lifting scheme, allowing the transform to choose from a set of fundamental bases the basis that best fits the signal. This characteristic is desirable for gear diagnostics as it allows the technique to tailor itself to a specific transmission by selecting a set of wavelets that best represent vibration signals obtained while the gearbox is operating under healthy-state conditions. However, constraints on certain basis characteristics are necessary to enhance the detection of local wave-form changes caused by certain types of gear damage. The proposed methodology analyzes individual tooth-mesh waveforms from a healthy-state gearbox vibration signal that was generated using the vibration separation (synchronous signal-averaging) algorithm. Each waveform is separated into analysis domains using zeros of its slope and curvature. The bases selected in each analysis domain are chosen to minimize the prediction error, and constrained to have the same-sign local slope and curvature as the original signal. The resulting set of bases is used to analyze future-state vibration signals and the lifting prediction error is inspected. The constraints allow the transform to effectively adapt to global amplitude changes, yielding small prediction errors. However, local wave-form changes associated with certain types of gear damage are poorly adapted, causing a significant change in the prediction error. The constrained adaptive lifting diagnostic algorithm is validated using data collected from the University of Maryland Transmission Test Rig and the results are discussed.

Dynamic causal modelling of brain-behaviour relationships.

PubMed

Rigoux, L; Daunizeau, J

2015-08-15

In this work, we expose a mathematical treatment of brain-behaviour relationships, which we coin behavioural Dynamic Causal Modelling or bDCM. This approach aims at decomposing the brain's transformation of stimuli into behavioural outcomes, in terms of the relative contribution of brain regions and their connections. In brief, bDCM places the brain at the interplay between stimulus and behaviour: behavioural outcomes arise from coordinated activity in (hidden) neural networks, whose dynamics are driven by experimental inputs. Estimating neural parameters that control network connectivity and plasticity effectively performs a neurobiologically-constrained approximation to the brain's input-outcome transform. In other words, neuroimaging data essentially serves to enforce the realism of bDCM's decomposition of input-output relationships. In addition, post-hoc artificial lesions analyses allow us to predict induced behavioural deficits and quantify the importance of network features for funnelling input-output relationships. This is important, because this enables one to bridge the gap with neuropsychological studies of brain-damaged patients. We demonstrate the face validity of the approach using Monte-Carlo simulations, and its predictive validity using empirical fMRI/behavioural data from an inhibitory control task. Lastly, we discuss promising applications of this work, including the assessment of functional degeneracy (in the healthy brain) and the prediction of functional recovery after lesions (in neurological patients). Copyright © 2015 Elsevier Inc. All rights reserved.

Importance of Geodetically Controlled Topography to Constrain Rates of Volcanism and Internal Magma Plumbing Systems

NASA Astrophysics Data System (ADS)

Glaze, L. S.; Baloga, S. M.; Garvin, J. B.; Quick, L. C.

2014-05-01

Lava flows and flow fields on Venus lack sufficient topographic data for any type of quantitative modeling to estimate eruption rates and durations. Such modeling can constrain rates of resurfacing and provide insights into magma plumbing systems.

Using a constrained formulation based on probability summation to fit receiver operating characteristic (ROC) curves

NASA Astrophysics Data System (ADS)

Swensson, Richard G.; King, Jill L.; Good, Walter F.; Gur, David

2000-04-01

A constrained ROC formulation from probability summation is proposed for measuring observer performance in detecting abnormal findings on medical images. This assumes the observer's detection or rating decision on each image is determined by a latent variable that characterizes the specific finding (type and location) considered most likely to be a target abnormality. For positive cases, this 'maximum- suspicion' variable is assumed to be either the value for the actual target or for the most suspicious non-target finding, whichever is the greater (more suspicious). Unlike the usual ROC formulation, this constrained formulation guarantees a 'well-behaved' ROC curve that always equals or exceeds chance- level decisions and cannot exhibit an upward 'hook.' Its estimated parameters specify the accuracy for separating positive from negative cases, and they also predict accuracy in locating or identifying the actual abnormal findings. The present maximum-likelihood procedure (runs on PC with Windows 95 or NT) fits this constrained formulation to rating-ROC data using normal distributions with two free parameters. Fits of the conventional and constrained ROC formulations are compared for continuous and discrete-scale ratings of chest films in a variety of detection problems, both for localized lesions (nodules, rib fractures) and for diffuse abnormalities (interstitial disease, infiltrates or pnumothorax). The two fitted ROC curves are nearly identical unless the conventional ROC has an ill behaved 'hook,' below the constrained ROC.

Ratios of W and Z cross sections at large boson $$p_T$$ as a constraint on PDFs and background to new physics

DOE PAGES

Malik, Sarah Alam; Watt, Graeme

2014-02-05

We motivate a measurement of various ratios of W and Z cross sections at the Large Hadron Collider (LHC) at large values of the boson transverse momentum (p T ≳ M W,Z ). We study the dependence of predictions for these cross-section ratios on the multiplicity of associated jets, the boson p T and the LHC centre-of-mass energy. We present the flavour decomposition of the initial-state partons and an evaluation of the theoretical uncertainties. We also show that the W + /W - ratio is sensitive to the up-quark to down-quark ratio of parton distribution functions (PDFs), while other theoreticalmore » uncertainties are negligible, meaning that a precise measurement of the W + /W - ratio at large boson p T values could constrain the PDFs at larger momentum fractions x than the usual inclusive W charge asymmetry. The W ± /Z ratio is insensitive to PDFs and most other theoretical uncertainties, other than possibly electroweak corrections, and a precise measurement will therefore be useful in validating theoretical predictions needed in data-driven methods, such as using W (→ ℓν) + jets events to estimate the Z(→ νν¯) + jets background in searches for new physics at the LHC. Furthermore, the differential W and Z cross sections themselves, dσ/dp T , have the potential to constrain the gluon distribution, provided that theoretical uncertainties from higher-order QCD and electroweak corrections are brought under control, such as by inclusion of anticipated next-to-next-to-leading order QCD corrections.« less

Phi Index: A New Metric to Test the Flush Early and Avoid the Rush Hypothesis

PubMed Central

Samia, Diogo S. M.; Blumstein, Daniel T.

2014-01-01

Optimal escape theory states that animals should counterbalance the costs and benefits of flight when escaping from a potential predator. However, in apparent contradiction with this well-established optimality model, birds and mammals generally initiate escape soon after beginning to monitor an approaching threat, a phenomena codified as the “Flush Early and Avoid the Rush” (FEAR) hypothesis. Typically, the FEAR hypothesis is tested using correlational statistics and is supported when there is a strong relationship between the distance at which an individual first responds behaviorally to an approaching predator (alert distance, AD), and its flight initiation distance (the distance at which it flees the approaching predator, FID). However, such correlational statistics are both inadequate to analyze relationships constrained by an envelope (such as that in the AD-FID relationship) and are sensitive to outliers with high leverage, which can lead one to erroneous conclusions. To overcome these statistical concerns we develop the phi index (Φ), a distribution-free metric to evaluate the goodness of fit of a 1∶1 relationship in a constraint envelope (the prediction of the FEAR hypothesis). Using both simulation and empirical data, we conclude that Φ is superior to traditional correlational analyses because it explicitly tests the FEAR prediction, is robust to outliers, and it controls for the disproportionate influence of observations from large predictor values (caused by the constrained envelope in AD-FID relationship). Importantly, by analyzing the empirical data we corroborate the strong effect that alertness has on flight as stated by the FEAR hypothesis. PMID:25405872

Phi index: a new metric to test the flush early and avoid the rush hypothesis.

PubMed

Samia, Diogo S M; Blumstein, Daniel T

2014-01-01

Optimal escape theory states that animals should counterbalance the costs and benefits of flight when escaping from a potential predator. However, in apparent contradiction with this well-established optimality model, birds and mammals generally initiate escape soon after beginning to monitor an approaching threat, a phenomena codified as the "Flush Early and Avoid the Rush" (FEAR) hypothesis. Typically, the FEAR hypothesis is tested using correlational statistics and is supported when there is a strong relationship between the distance at which an individual first responds behaviorally to an approaching predator (alert distance, AD), and its flight initiation distance (the distance at which it flees the approaching predator, FID). However, such correlational statistics are both inadequate to analyze relationships constrained by an envelope (such as that in the AD-FID relationship) and are sensitive to outliers with high leverage, which can lead one to erroneous conclusions. To overcome these statistical concerns we develop the phi index (Φ), a distribution-free metric to evaluate the goodness of fit of a 1:1 relationship in a constraint envelope (the prediction of the FEAR hypothesis). Using both simulation and empirical data, we conclude that Φ is superior to traditional correlational analyses because it explicitly tests the FEAR prediction, is robust to outliers, and it controls for the disproportionate influence of observations from large predictor values (caused by the constrained envelope in AD-FID relationship). Importantly, by analyzing the empirical data we corroborate the strong effect that alertness has on flight as stated by the FEAR hypothesis.

Carbonate system parameters of an algal-dominated reef along west Maui

USGS Publications Warehouse

Prouty, Nancy G.; Yates, Kimberly K.; Smiley, Nathan A.; Gallagher, Christopher; Cheriton, Olivia; Storlazzi, Curt

2018-01-01

Constraining coral reef metabolism and carbon chemistry dynamics are fundamental for understanding and predicting reef vulnerability to rising coastal CO2 concentrations and decreasing seawater pH. However, few studies exist along reefs occupying densely inhabited shorelines with known input from land-based sources of pollution. The shallow coral reefs off Kahekili, West Maui, are exposed to nutrient-enriched, low-pH submarine groundwater discharge (SGD) and are particularly vulnerable to the compounding stressors from land-based sources of pollution and lower seawater pH. To constrain the carbonate chemistry system, nutrients and carbonate chemistry were measured along the Kahekili reef flat every 4 h over a 6-d sampling period in March 2016. Abiotic process – primarily SGD fluxes – controlled the carbonate chemistry adjacent to the primary SGD vent site, with nutrient-laden freshwater decreasing pH levels and favoring undersaturated aragonite saturation (Ωarag) conditions. In contrast, diurnal variability in the carbonate chemistry at other sites along the reef flat was driven by reef community metabolism. Superimposed on the diurnal signal was a transition during the second sampling period to a surplus of total alkalinity (TA) and dissolved inorganic carbon (DIC) compared to ocean end-member TA and DIC measurements. A shift from net community production and calcification to net respiration and carbonate dissolution was identified. This transition occurred during a period of increased SGD-driven nutrient loading, lower wave height, and reduced current speeds. This detailed study of carbon chemistry dynamics highlights the need to incorporate local effects of nearshore oceanographic processes into predictions of coral reef vulnerability and resilience.

Call Admission Control on Single Node Networks under Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) Scheduler

NASA Astrophysics Data System (ADS)

Hanada, Masaki; Nakazato, Hidenori; Watanabe, Hitoshi

Multimedia applications such as music or video streaming, video teleconferencing and IP telephony are flourishing in packet-switched networks. Applications that generate such real-time data can have very diverse quality-of-service (QoS) requirements. In order to guarantee diverse QoS requirements, the combined use of a packet scheduling algorithm based on Generalized Processor Sharing (GPS) and leaky bucket traffic regulator is the most successful QoS mechanism. GPS can provide a minimum guaranteed service rate for each session and tight delay bounds for leaky bucket constrained sessions. However, the delay bounds for leaky bucket constrained sessions under GPS are unnecessarily large because each session is served according to its associated constant weight until the session buffer is empty. In order to solve this problem, a scheduling policy called Output Rate-Controlled Generalized Processor Sharing (ORC-GPS) was proposed in [17]. ORC-GPS is a rate-based scheduling like GPS, and controls the service rate in order to lower the delay bounds for leaky bucket constrained sessions. In this paper, we propose a call admission control (CAC) algorithm for ORC-GPS, for leaky-bucket constrained sessions with deterministic delay requirements. This CAC algorithm for ORC-GPS determines the optimal values of parameters of ORC-GPS from the deterministic delay requirements of the sessions. In numerical experiments, we compare the CAC algorithm for ORC-GPS with one for GPS in terms of schedulable region and computational complexity.

Robust LS-SVM-based adaptive constrained control for a class of uncertain nonlinear systems with time-varying predefined performance

NASA Astrophysics Data System (ADS)

Luo, Jianjun; Wei, Caisheng; Dai, Honghua; Yuan, Jianping

2018-03-01

This paper focuses on robust adaptive control for a class of uncertain nonlinear systems subject to input saturation and external disturbance with guaranteed predefined tracking performance. To reduce the limitations of classical predefined performance control method in the presence of unknown initial tracking errors, a novel predefined performance function with time-varying design parameters is first proposed. Then, aiming at reducing the complexity of nonlinear approximations, only two least-square-support-vector-machine-based (LS-SVM-based) approximators with two design parameters are required through norm form transformation of the original system. Further, a novel LS-SVM-based adaptive constrained control scheme is developed under the time-vary predefined performance using backstepping technique. Wherein, to avoid the tedious analysis and repeated differentiations of virtual control laws in the backstepping technique, a simple and robust finite-time-convergent differentiator is devised to only extract its first-order derivative at each step in the presence of external disturbance. In this sense, the inherent demerit of backstepping technique-;explosion of terms; brought by the recursive virtual controller design is conquered. Moreover, an auxiliary system is designed to compensate the control saturation. Finally, three groups of numerical simulations are employed to validate the effectiveness of the newly developed differentiator and the proposed adaptive constrained control scheme.

Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model - Part 1: Assessing the influence of constrained multi-generational ageing

NASA Astrophysics Data System (ADS)

Jathar, S. H.; Cappa, C. D.; Wexler, A. S.; Seinfeld, J. H.; Kleeman, M. J.

2016-02-01

Multi-generational oxidation of volatile organic compound (VOC) oxidation products can significantly alter the mass, chemical composition and properties of secondary organic aerosol (SOA) compared to calculations that consider only the first few generations of oxidation reactions. However, the most commonly used state-of-the-science schemes in 3-D regional or global models that account for multi-generational oxidation (1) consider only functionalization reactions but do not consider fragmentation reactions, (2) have not been constrained to experimental data and (3) are added on top of existing parameterizations. The incomplete description of multi-generational oxidation in these models has the potential to bias source apportionment and control calculations for SOA. In this work, we used the statistical oxidation model (SOM) of Cappa and Wilson (2012), constrained by experimental laboratory chamber data, to evaluate the regional implications of multi-generational oxidation considering both functionalization and fragmentation reactions. SOM was implemented into the regional University of California at Davis / California Institute of Technology (UCD/CIT) air quality model and applied to air quality episodes in California and the eastern USA. The mass, composition and properties of SOA predicted using SOM were compared to SOA predictions generated by a traditional two-product model to fully investigate the impact of explicit and self-consistent accounting of multi-generational oxidation.Results show that SOA mass concentrations predicted by the UCD/CIT-SOM model are very similar to those predicted by a two-product model when both models use parameters that are derived from the same chamber data. Since the two-product model does not explicitly resolve multi-generational oxidation reactions, this finding suggests that the chamber data used to parameterize the models captures the majority of the SOA mass formation from multi-generational oxidation under the conditions tested. Consequently, the use of low and high NOx yields perturbs SOA concentrations by a factor of two and are probably a much stronger determinant in 3-D models than multi-generational oxidation. While total predicted SOA mass is similar for the SOM and two-product models, the SOM model predicts increased SOA contributions from anthropogenic (alkane, aromatic) and sesquiterpenes and decreased SOA contributions from isoprene and monoterpene relative to the two-product model calculations. The SOA predicted by SOM has a much lower volatility than that predicted by the traditional model, resulting in better qualitative agreement with volatility measurements of ambient OA. On account of its lower-volatility, the SOA mass produced by SOM does not appear to be as strongly influenced by the inclusion of oligomerization reactions, whereas the two-product model relies heavily on oligomerization to form low-volatility SOA products. Finally, an unconstrained contemporary hybrid scheme to model multi-generational oxidation within the framework of a two-product model in which ageing reactions are added on top of the existing two-product parameterization is considered. This hybrid scheme formed at least 3 times more SOA than the SOM during regional simulations as a result of excessive transformation of semi-volatile vapors into lower volatility material that strongly partitions to the particle phase. This finding suggests that these hybrid multi-generational schemes should be used with great caution in regional models.

Warming and Resource Availability Shift Food Web Structure and Metabolism

PubMed Central

O'Connor, Mary I.; Piehler, Michael F.; Leech, Dina M.; Anton, Andrea; Bruno, John F.

2009-01-01

Climate change disrupts ecological systems in many ways. Many documented responses depend on species' life histories, contributing to the view that climate change effects are important but difficult to characterize generally. However, systematic variation in metabolic effects of temperature across trophic levels suggests that warming may lead to predictable shifts in food web structure and productivity. We experimentally tested the effects of warming on food web structure and productivity under two resource supply scenarios. Consistent with predictions based on universal metabolic responses to temperature, we found that warming strengthened consumer control of primary production when resources were augmented. Warming shifted food web structure and reduced total biomass despite increases in primary productivity in a marine food web. In contrast, at lower resource levels, food web production was constrained at all temperatures. These results demonstrate that small temperature changes could dramatically shift food web dynamics and provide a general, species-independent mechanism for ecological response to environmental temperature change. PMID:19707271

Theory of chaotic orbital variations confirmed by Cretaceous geological evidence

NASA Astrophysics Data System (ADS)

Ma, Chao; Meyers, Stephen R.; Sageman, Bradley B.

2017-02-01

Variations in the Earth’s orbit and spin vector are a primary control on insolation and climate; their recognition in the geological record has revolutionized our understanding of palaeoclimate dynamics, and has catalysed improvements in the accuracy and precision of the geological timescale. Yet the secular evolution of the planetary orbits beyond 50 million years ago remains highly uncertain, and the chaotic dynamical nature of the Solar System predicted by theoretical models has yet to be rigorously confirmed by well constrained (radioisotopically calibrated and anchored) geological data. Here we present geological evidence for a chaotic resonance transition associated with interactions between the orbits of Mars and the Earth, using an integrated radioisotopic and astronomical timescale from the Cretaceous Western Interior Basin of what is now North America. This analysis confirms the predicted chaotic dynamical behaviour of the Solar System, and provides a constraint for refining numerical solutions for insolation, which will enable a more precise and accurate geological timescale to be produced.

A novel phenomenological multi-physics model of Li-ion battery cells

NASA Astrophysics Data System (ADS)

Oh, Ki-Yong; Samad, Nassim A.; Kim, Youngki; Siegel, Jason B.; Stefanopoulou, Anna G.; Epureanu, Bogdan I.

2016-09-01

A novel phenomenological multi-physics model of Lithium-ion battery cells is developed for control and state estimation purposes. The model can capture electrical, thermal, and mechanical behaviors of battery cells under constrained conditions, e.g., battery pack conditions. Specifically, the proposed model predicts the core and surface temperatures and reaction force induced from the volume change of battery cells because of electrochemically- and thermally-induced swelling. Moreover, the model incorporates the influences of changes in preload and ambient temperature on the force considering severe environmental conditions electrified vehicles face. Intensive experimental validation demonstrates that the proposed multi-physics model accurately predicts the surface temperature and reaction force for a wide operational range of preload and ambient temperature. This high fidelity model can be useful for more accurate and robust state of charge estimation considering the complex dynamic behaviors of the battery cell. Furthermore, the inherent simplicity of the mechanical measurements offers distinct advantages to improve the existing power and thermal management strategies for battery management.

Peer influence processes for youth delinquency and depression.

PubMed

Reynolds, Andrew D; Crea, Thomas M

2015-08-01

This study explores the multiple factors that account for peer influence processes of adolescent delinquency and depression using data from Waves I and II of the National Longitudinal Study of Adolescent to Adult Health (Add Health). Random-effects longitudinal negative binomial models were used to predict depression and delinquency, controlling for social connection variables to account for selection bias. Findings suggest peer depression and delinquency are both predictive of youth delinquency, while peer influences of depression are much more modest. Youth who are more connected to parents and communities and who are more popular within their networks are more susceptible to peer influence, while self-regulating youth are less susceptible. We find support for theories of popularity-socialization as well as weak-ties in explaining social network factors that amplify or constrain peer influence. We argue that practitioners working with youth should consider network-informed interventions to improve program efficacy and avoid iatrogenic effects. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Theory of chaotic orbital variations confirmed by Cretaceous geological evidence.

PubMed

Ma, Chao; Meyers, Stephen R; Sageman, Bradley B

2017-02-22

Variations in the Earth's orbit and spin vector are a primary control on insolation and climate; their recognition in the geological record has revolutionized our understanding of palaeoclimate dynamics, and has catalysed improvements in the accuracy and precision of the geological timescale. Yet the secular evolution of the planetary orbits beyond 50 million years ago remains highly uncertain, and the chaotic dynamical nature of the Solar System predicted by theoretical models has yet to be rigorously confirmed by well constrained (radioisotopically calibrated and anchored) geological data. Here we present geological evidence for a chaotic resonance transition associated with interactions between the orbits of Mars and the Earth, using an integrated radioisotopic and astronomical timescale from the Cretaceous Western Interior Basin of what is now North America. This analysis confirms the predicted chaotic dynamical behaviour of the Solar System, and provides a constraint for refining numerical solutions for insolation, which will enable a more precise and accurate geological timescale to be produced.

Towards spatially constrained gust models

NASA Astrophysics Data System (ADS)

Bos, René; Bierbooms, Wim; van Bussel, Gerard

2014-06-01

With the trend of moving towards 10-20 MW turbines, rotor diameters are growing beyond the size of the largest turbulent structures in the atmospheric boundary layer. As a consequence, the fully uniform transients that are commonly used to predict extreme gust loads are losing their connection to reality and may lead to gross overdimensioning. More suiting would be to represent gusts by advecting air parcels and posing certain physical constraints on size and position. However, this would introduce several new degrees of freedom that significantly increase the computational burden of extreme load prediction. In an attempt to elaborate on the costs and benefits of such an approach, load calculations were done on the DTU 10 MW reference turbine where a single uniform gust shape was given various spatial dimensions with the transverse wavelength ranging up to twice the rotor diameter (357 m). The resulting loads displayed a very high spread, but remained well under the level of a uniform gust. Moving towards spatially constrained gust models would therefore yield far less conservative, though more realistic predictions at the cost of higher computation time.

Phenomenological Consequences of the Constrained Exceptional Supersymmetric Standard Model

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

Athron, Peter; King, S. F.; Miller, D. J.

2010-02-10

The Exceptional Supersymmetric Standard Model (E{sub 6}SSM) provides a low energy alternative to the MSSM, with an extra gauged U(1){sub N} symmetry, solving the mu-problem of the MSSM. Inspired by the possible embedding into an E{sub 6} GUT, the matter content fills three generations of E{sub 6} multiplets, thus predicting exciting exotic matter such as diquarks or leptoquarks. We present predictions from a constrained version of the model (cE{sub 6}SSM), with a universal scalar mass m{sub 0}, trilinear mass A and gaugino mass M{sub 1/2}. We reveal a large volume of the cE{sub 6}SSM parameter space where the correct breakdownmore » of the gauge symmetry is achieved and all experimental constraints satisfied. We predict a hierarchical particle spectrum with heavy scalars and light gauginos, while the new exotic matter can be light or heavy depending on parameters. We present representative cE{sub 6}SSM scenarios, demonstrating that there could be light exotic particles, like leptoquarks and a U(1){sub N} Z' boson, with spectacular signals at the LHC.« less

Evaluation of three force-position hybrid control methods for a robot-based biological joint-testing system.

PubMed

Hsieh, Hong-Jung; Hu, Chih-Chung; Lu, Tung-Wu; Lu, Hsuan-Lun; Kuo, Mei-Ying; Kuo, Chien-Chung; Hsu, Horng-Chaung

2016-06-07

Robot-based joint-testing systems (RJTS) can be used to perform unconstrained laxity tests, measuring the stiffness of a degree of freedom (DOF) of the joint at a fixed flexion angle while allowing the other DOFs unconstrained movement. Previous studies using the force-position hybrid (FPH) control method proposed by Fujie et al. (J Biomech Eng 115(3):211-7, 1993) focused on anterior/posterior tests. Its convergence and applicability on other clinically relevant DOFs such as valgus/varus have not been demonstrated. The current s1tudy aimed to develop a 6-DOF RJTS using an industrial robot, to propose two new force-position hybrid control methods, and to evaluate the performance of the methods and FPH in controlling the RJTS for anterior/posterior and valgus/varus laxity tests of the knee joint. An RJTS was developed using an industrial 6-DOF robot with a 6-component load-cell attached at the effector. The performances of FPH and two new control methods, namely force-position alternate control (FPA) and force-position hybrid control with force-moment control (FPHFM), for unconstrained anterior/posterior and valgus/varus laxity tests were evaluated and compared with traditional constrained tests (CT) in terms of the number of control iterations, total time and the constraining forces and moments. As opposed to CT, the other three control methods successfully reduced the constraining forces and moments for both anterior/posterior and valgus/varus tests, FPHFM being the best followed in order by FPA and FPH. FPHFM had root-mean-squared constraining forces and moments of less than 2.2 N and 0.09 Nm, respectively at 0° flexion, and 2.3 N and 0.14 Nm at 30° flexion. The corresponding values for FPH were 8.5 N and 0.33 Nm, and 11.5 N and 0.45 Nm, respectively. Given the same control parameters including the compliance matrix, FPHFM and FPA reduced the constraining loads of FPH at the expense of additional control iterations, and thus increased total time, FPA taking about 10 % longer than FPHFM. The FPHFM would be the best choice among the methods considered when longer total time is acceptable in the intended clinical applications. The current results will be useful for selecting a force-position hybrid control method for unconstrained laxity tests using an RJTS.

Linking erosion history and mantle processes in southern Africa

NASA Astrophysics Data System (ADS)

Stanley, J. R.; Braun, J.; Flowers, R. M.; Baby, G.; Wildman, M.; Guillocheau, F.; Robin, C.; Beucher, R.; Brown, R. W.

2017-12-01

The large, low relief, high elevation plateau of southern Africa has been the focus of many studies, but there is still considerable debate about how it formed. Lack of tectonic convergence and crustal thickening suggests mantle dynamics play an important role in the evolution of topography there, but the time and specific mechanisms of topographic development are still contested. Many mantle mechanisms of topographic support have been suggested including dynamic topography associated with either deep or shallow mantle thermal anomalies, thermochemical modification of the lithosphere, and plume tails related to Mesozoic magmatic activity. These mechanisms predict different timing and patterns of surface uplift such that better constraints on the uplift history have the potential to constrain the nature of the source of topographic support. Here we test several of these geodynamic hypotheses using a landscape evolution model that is used to predict the erosional response to surface uplift. Several recent studies have provided a clearer picture of the erosion history of the plateau surface and margins using low temperature thermochronology and the geometries of the surrounding offshore depositional systems. Model results are directly compared with these data. We use an inversion method (the Neighborhood Algorithm) to constrain the range in erosional and uplift parameters that can best reproduce the observed data. The combination of different types of geologic information including sedimentary flux, landscape shape, and thermochronolology is valuable for constraining many of these parameters. We show that both the characteristics of the geodynamic forcing as well as the physical characteristics of the eroding plateau have significant control on the plateau erosion patterns. Models that match the erosion history data well suggest uplift of the eastern margin in the Cretaceous ( 100 Ma) followed by uplift of the western margin 20 Myr later. The amplitude of this uplift is on the order of 1000 m. The data cannot resolve whether there was smaller amplitude phase of uplift in the Cenozoic. These results suggest that the scenario proposed by Braun et al. (2014) of uplift caused by the continent moving over the African superswell is viable. We are currently investigating the compatibility of other uplift geometries.

A weakly-constrained data assimilation approach to address rainfall-runoff model structural inadequacy in streamflow prediction

NASA Astrophysics Data System (ADS)

Lee, Haksu; Seo, Dong-Jun; Noh, Seong Jin

2016-11-01

This paper presents a simple yet effective weakly-constrained (WC) data assimilation (DA) approach for hydrologic models which accounts for model structural inadequacies associated with rainfall-runoff transformation processes. Compared to the strongly-constrained (SC) DA, WC DA adjusts the control variables less while producing similarly or more accurate analysis. Hence the adjusted model states are dynamically more consistent with those of the base model. The inadequacy of a rainfall-runoff model was modeled as an additive error to runoff components prior to routing and penalized in the objective function. Two example modeling applications, distributed and lumped, were carried out to investigate the effects of the WC DA approach on DA results. For distributed modeling, the distributed Sacramento Soil Moisture Accounting (SAC-SMA) model was applied to the TIFM7 Basin in Missouri, USA. For lumped modeling, the lumped SAC-SMA model was applied to nineteen basins in Texas. In both cases, the variational DA (VAR) technique was used to assimilate discharge data at the basin outlet. For distributed SAC-SMA, spatially homogeneous error modeling yielded updated states that are spatially much more similar to the a priori states, as quantified by Earth Mover's Distance (EMD), than spatially heterogeneous error modeling by up to ∼10 times. DA experiments using both lumped and distributed SAC-SMA modeling indicated that assimilating outlet flow using the WC approach generally produce smaller mean absolute difference as well as higher correlation between the a priori and the updated states than the SC approach, while producing similar or smaller root mean square error of streamflow analysis and prediction. Large differences were found in both lumped and distributed modeling cases between the updated and the a priori lower zone tension and primary free water contents for both WC and SC approaches, indicating possible model structural deficiency in describing low flows or evapotranspiration processes for the catchments studied. Also presented are the findings from this study and key issues relevant to WC DA approaches using hydrologic models.

A proof for loop-law constraints in stoichiometric metabolic networks

PubMed Central

2012-01-01

Background Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops) from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well. Results Here we apply Gordan’s theorem from linear algebra to prove for the first time that the constraints added in loopless-COBRA do not over-constrain the problem beyond the elimination of the loops themselves. Conclusions The loopless-COBRA constraints can be reliably applied. Furthermore, this proof may be adapted to evaluate the theoretical soundness for other methods in constraint-based modeling. PMID:23146116

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

Dall'Anese, Emiliano; Baker, Kyri; Summers, Tyler

The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative boundsmore » that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.« less

The transcriptional network that controls growth arrest and differentiation in a human myeloid leukemia cell line.

PubMed

Suzuki, Harukazu; Forrest, Alistair R R; van Nimwegen, Erik; Daub, Carsten O; Balwierz, Piotr J; Irvine, Katharine M; Lassmann, Timo; Ravasi, Timothy; Hasegawa, Yuki; de Hoon, Michiel J L; Katayama, Shintaro; Schroder, Kate; Carninci, Piero; Tomaru, Yasuhiro; Kanamori-Katayama, Mutsumi; Kubosaki, Atsutaka; Akalin, Altuna; Ando, Yoshinari; Arner, Erik; Asada, Maki; Asahara, Hiroshi; Bailey, Timothy; Bajic, Vladimir B; Bauer, Denis; Beckhouse, Anthony G; Bertin, Nicolas; Björkegren, Johan; Brombacher, Frank; Bulger, Erika; Chalk, Alistair M; Chiba, Joe; Cloonan, Nicole; Dawe, Adam; Dostie, Josee; Engström, Pär G; Essack, Magbubah; Faulkner, Geoffrey J; Fink, J Lynn; Fredman, David; Fujimori, Ko; Furuno, Masaaki; Gojobori, Takashi; Gough, Julian; Grimmond, Sean M; Gustafsson, Mika; Hashimoto, Megumi; Hashimoto, Takehiro; Hatakeyama, Mariko; Heinzel, Susanne; Hide, Winston; Hofmann, Oliver; Hörnquist, Michael; Huminiecki, Lukasz; Ikeo, Kazuho; Imamoto, Naoko; Inoue, Satoshi; Inoue, Yusuke; Ishihara, Ryoko; Iwayanagi, Takao; Jacobsen, Anders; Kaur, Mandeep; Kawaji, Hideya; Kerr, Markus C; Kimura, Ryuichiro; Kimura, Syuhei; Kimura, Yasumasa; Kitano, Hiroaki; Koga, Hisashi; Kojima, Toshio; Kondo, Shinji; Konno, Takeshi; Krogh, Anders; Kruger, Adele; Kumar, Ajit; Lenhard, Boris; Lennartsson, Andreas; Lindow, Morten; Lizio, Marina; Macpherson, Cameron; Maeda, Norihiro; Maher, Christopher A; Maqungo, Monique; Mar, Jessica; Matigian, Nicholas A; Matsuda, Hideo; Mattick, John S; Meier, Stuart; Miyamoto, Sei; Miyamoto-Sato, Etsuko; Nakabayashi, Kazuhiko; Nakachi, Yutaka; Nakano, Mika; Nygaard, Sanne; Okayama, Toshitsugu; Okazaki, Yasushi; Okuda-Yabukami, Haruka; Orlando, Valerio; Otomo, Jun; Pachkov, Mikhail; Petrovsky, Nikolai; Plessy, Charles; Quackenbush, John; Radovanovic, Aleksandar; Rehli, Michael; Saito, Rintaro; Sandelin, Albin; Schmeier, Sebastian; Schönbach, Christian; Schwartz, Ariel S; Semple, Colin A; Sera, Miho; Severin, Jessica; Shirahige, Katsuhiko; Simons, Cas; St Laurent, George; Suzuki, Masanori; Suzuki, Takahiro; Sweet, Matthew J; Taft, Ryan J; Takeda, Shizu; Takenaka, Yoichi; Tan, Kai; Taylor, Martin S; Teasdale, Rohan D; Tegnér, Jesper; Teichmann, Sarah; Valen, Eivind; Wahlestedt, Claes; Waki, Kazunori; Waterhouse, Andrew; Wells, Christine A; Winther, Ole; Wu, Linda; Yamaguchi, Kazumi; Yanagawa, Hiroshi; Yasuda, Jun; Zavolan, Mihaela; Hume, David A; Arakawa, Takahiro; Fukuda, Shiro; Imamura, Kengo; Kai, Chikatoshi; Kaiho, Ai; Kawashima, Tsugumi; Kawazu, Chika; Kitazume, Yayoi; Kojima, Miki; Miura, Hisashi; Murakami, Kayoko; Murata, Mitsuyoshi; Ninomiya, Noriko; Nishiyori, Hiromi; Noma, Shohei; Ogawa, Chihiro; Sano, Takuma; Simon, Christophe; Tagami, Michihira; Takahashi, Yukari; Kawai, Jun; Hayashizaki, Yoshihide

2009-05-01

Using deep sequencing (deepCAGE), the FANTOM4 study measured the genome-wide dynamics of transcription-start-site usage in the human monocytic cell line THP-1 throughout a time course of growth arrest and differentiation. Modeling the expression dynamics in terms of predicted cis-regulatory sites, we identified the key transcription regulators, their time-dependent activities and target genes. Systematic siRNA knockdown of 52 transcription factors confirmed the roles of individual factors in the regulatory network. Our results indicate that cellular states are constrained by complex networks involving both positive and negative regulatory interactions among substantial numbers of transcription factors and that no single transcription factor is both necessary and sufficient to drive the differentiation process.

Constrained variational calculus for higher order classical field theories

NASA Astrophysics Data System (ADS)

Campos, Cédric M.; de León, Manuel; Martín de Diego, David

2010-11-01

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.

CVB: The Constrained Vapor Bubble 40 mm Capillary Experiment on the ISS

NASA Technical Reports Server (NTRS)

Wayner, Peter C., Jr.; Kundan, Akshay; Plawsky, Joel

2013-01-01

Discuss the Constrained Vapor Bubble (CVB) 40mm Fin experiment on the ISS and how it aims to achieve a better understanding of the physics of evaporation and condensation and how they affect cooling processes in microgravity using a remotely controlled microscope and a small cooling device

Helicopter Control Energy Reduction Using Moving Horizontal Tail

PubMed Central

Oktay, Tugrul; Sal, Firat

2015-01-01

Helicopter moving horizontal tail (i.e., MHT) strategy is applied in order to save helicopter flight control system (i.e., FCS) energy. For this intention complex, physics-based, control-oriented nonlinear helicopter models are used. Equations of MHT are integrated into these models and they are together linearized around straight level flight condition. A specific variance constrained control strategy, namely, output variance constrained Control (i.e., OVC) is utilized for helicopter FCS. Control energy savings due to this MHT idea with respect to a conventional helicopter are calculated. Parameters of helicopter FCS and dimensions of MHT are simultaneously optimized using a stochastic optimization method, namely, simultaneous perturbation stochastic approximation (i.e., SPSA). In order to observe improvement in behaviors of classical controls closed loop analyses are done. PMID:26180841

Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563

Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.

Sex-specific genetic variance and the evolution of sexual dimorphism: a systematic review of cross-sex genetic correlations.

PubMed

Poissant, Jocelyn; Wilson, Alastair J; Coltman, David W

2010-01-01

The independent evolution of the sexes may often be constrained if male and female homologous traits share a similar genetic architecture. Thus, cross-sex genetic covariance is assumed to play a key role in the evolution of sexual dimorphism (SD) with consequent impacts on sexual selection, population dynamics, and speciation processes. We compiled cross-sex genetic correlations (r(MF)) estimates from 114 sources to assess the extent to which the evolution of SD is typically constrained and test several specific hypotheses. First, we tested if r(MF) differed among trait types and especially between fitness components and other traits. We also tested the theoretical prediction of a negative relationship between r(MF) and SD based on the expectation that increases in SD should be facilitated by sex-specific genetic variance. We show that r(MF) is usually large and positive but that it is typically smaller for fitness components. This demonstrates that the evolution of SD is typically genetically constrained and that sex-specific selection coefficients may often be opposite in sign due to sub-optimal levels of SD. Most importantly, we confirm that sex-specific genetic variance is an important contributor to the evolution of SD by validating the prediction of a negative correlation between r(MF) and SD.

Language for Winning Hearts and Minds: Verb Aspect in U.S. Presidential Campaign Speeches for Engaging Emotion.

PubMed

Havas, David A; Chapp, Christopher B

2016-01-01

How does language influence the emotions and actions of large audiences? Functionally, emotions help address environmental uncertainty by constraining the body to support adaptive responses and social coordination. We propose emotions provide a similar function in language processing by constraining the mental simulation of language content to facilitate comprehension, and to foster alignment of mental states in message recipients. Consequently, we predicted that emotion-inducing language should be found in speeches specifically designed to create audience alignment - stump speeches of United States presidential candidates. We focused on phrases in the past imperfective verb aspect ("a bad economy was burdening us") that leave a mental simulation of the language content open-ended, and thus unconstrained, relative to past perfective sentences ("we were burdened by a bad economy"). As predicted, imperfective phrases appeared more frequently in stump versus comparison speeches, relative to perfective phrases. In a subsequent experiment, participants rated phrases from presidential speeches as more emotionally intense when written in the imperfective aspect compared to the same phrases written in the perfective aspect, particularly for sentences perceived as negative in valence. These findings are consistent with the notion that emotions have a role in constraining the comprehension of language, a role that may be used in communication with large audiences.

A Morphing Radiator for High-Turndown Thermal Control of Crewed Space Exploration Vehicles

NASA Technical Reports Server (NTRS)

Cognata, Thomas J.; Hartl, Darren J.; Sheth, Rubik; Dinsmore, Craig

2014-01-01

Spacecraft designed for missions beyond low earth orbit (LEO) face a difficult thermal control challenge, particularly in the case of crewed vehicles where the thermal control system (TCS) must maintain a relatively constant internal environment temperature despite a vastly varying external thermal environment and despite heat rejection needs that are contrary to the potential of the environment. A thermal control system may be required to reject a higher heat load to warm environments and a lower heat load to cold environments, necessitating a relatively high turndown ratio. A modern thermal control system is capable of a turndown ratio of on the order of 12:1, but crew safety and environment compatibility have constrained these solutions to massive multi-loop fluid systems. This paper discusses the analysis of a unique radiator design that employs the behavior of shape memory alloys (SMAs) to vary the turndown of, and thus enable, a single-loop vehicle thermal control system for space exploration vehicles. This design, a morphing radiator, varies its shape in response to facesheet temperature to control view of space and primary surface emissivity. Because temperature dependence is inherent to SMA behavior, the design requires no accommodation for control, instrumentation, or power supply in order to operate. Thermal and radiation modeling of the morphing radiator predict a turndown ranging from 11.9:1 to 35:1 independent of TCS configuration. Coupled thermal-stress analyses predict that the desired morphing behavior of the concept is attainable. A system level mass analysis shows that by enabling a single loop architecture this design could reduce the TCS mass by between 139 kg and 225 kg. The concept has been demonstrated in proof-of-concept benchtop tests.

PANATIKI: A Network Access Control Implementation Based on PANA for IoT Devices

PubMed Central

Sanchez, Pedro Moreno; Lopez, Rafa Marin; Gomez Skarmeta, Antonio F.

2013-01-01

Internet of Things (IoT) networks are the pillar of recent novel scenarios, such as smart cities or e-healthcare applications. Among other challenges, these networks cover the deployment and interaction of small devices with constrained capabilities and Internet protocol (IP)-based networking connectivity. These constrained devices usually require connection to the Internet to exchange information (e.g., management or sensing data) or access network services. However, only authenticated and authorized devices can, in general, establish this connection. The so-called authentication, authorization and accounting (AAA) services are in charge of performing these tasks on the Internet. Thus, it is necessary to deploy protocols that allow constrained devices to verify their credentials against AAA infrastructures. The Protocol for Carrying Authentication for Network Access (PANA) has been standardized by the Internet engineering task force (IETF) to carry the Extensible Authentication Protocol (EAP), which provides flexible authentication upon the presence of AAA. To the best of our knowledge, this paper is the first deep study of the feasibility of EAP/PANA for network access control in constrained devices. We provide light-weight versions and implementations of these protocols to fit them into constrained devices. These versions have been designed to reduce the impact in standard specifications. The goal of this work is two-fold: (1) to demonstrate the feasibility of EAP/PANA in IoT devices; (2) to provide the scientific community with the first light-weight interoperable implementation of EAP/PANA for constrained devices in the Contiki operating system (Contiki OS), called PANATIKI. The paper also shows a testbed, simulations and experimental results obtained from real and simulated constrained devices. PMID:24189332

PANATIKI: a network access control implementation based on PANA for IoT devices.

PubMed

Moreno Sanchez, Pedro; Marin Lopez, Rafa; Gomez Skarmeta, Antonio F

2013-11-01

Internet of Things (IoT) networks are the pillar of recent novel scenarios, such as smart cities or e-healthcare applications. Among other challenges, these networks cover the deployment and interaction of small devices with constrained capabilities and Internet protocol (IP)-based networking connectivity. These constrained devices usually require connection to the Internet to exchange information (e.g., management or sensing data) or access network services. However, only authenticated and authorized devices can, in general, establish this connection. The so-called authentication, authorization and accounting (AAA) services are in charge of performing these tasks on the Internet. Thus, it is necessary to deploy protocols that allow constrained devices to verify their credentials against AAA infrastructures. The Protocol for Carrying Authentication for Network Access (PANA) has been standardized by the Internet engineering task force (IETF) to carry the Extensible Authentication Protocol (EAP), which provides flexible authentication upon the presence of AAA. To the best of our knowledge, this paper is the first deep study of the feasibility of EAP/PANA for network access control in constrained devices. We provide light-weight versions and implementations of these protocols to fit them into constrained devices. These versions have been designed to reduce the impact in standard specifications. The goal of this work is two-fold: (1) to demonstrate the feasibility of EAP/PANA in IoT devices; (2) to provide the scientific community with the first light-weight interoperable implementation of EAP/PANA for constrained devices in the Contiki operating system (Contiki OS), called PANATIKI. The paper also shows a testbed, simulations and experimental results obtained from real and simulated constrained devices.

A robust approach to chance constrained optimal power flow with renewable generation

DOE PAGES

Lubin, Miles; Dvorkin, Yury; Backhaus, Scott N.

2016-09-01

Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to operational constraints on generation and transmission assets. The uncertainty and variability of intermittent renewable generation is challenging current deterministic OPF approaches. Recent formulations of OPF use chance constraints to limit the risk from renewable generation uncertainty, however, these new approaches typically assume the probability distributions which characterize the uncertainty and variability are known exactly. We formulate a robust chance constrained (RCC) OPF that accounts for uncertainty in the parameters of these probability distributions by allowing them to be within an uncertainty set. The RCC OPF is solved usingmore » a cutting-plane algorithm that scales to large power systems. We demonstrate the RRC OPF on a modified model of the Bonneville Power Administration network, which includes 2209 buses and 176 controllable generators. In conclusion, deterministic, chance constrained (CC), and RCC OPF formulations are compared using several metrics including cost of generation, area control error, ramping of controllable generators, and occurrence of transmission line overloads as well as the respective computational performance.« less

Dynamics simulations for engineering macromolecular interactions

PubMed Central

Robinson-Mosher, Avi; Shinar, Tamar; Silver, Pamela A.; Way, Jeffrey

2013-01-01

The predictable engineering of well-behaved transcriptional circuits is a central goal of synthetic biology. The artificial attachment of promoters to transcription factor genes usually results in noisy or chaotic behaviors, and such systems are unlikely to be useful in practical applications. Natural transcriptional regulation relies extensively on protein-protein interactions to insure tightly controlled behavior, but such tight control has been elusive in engineered systems. To help engineer protein-protein interactions, we have developed a molecular dynamics simulation framework that simplifies features of proteins moving by constrained Brownian motion, with the goal of performing long simulations. The behavior of a simulated protein system is determined by summation of forces that include a Brownian force, a drag force, excluded volume constraints, relative position constraints, and binding constraints that relate to experimentally determined on-rates and off-rates for chosen protein elements in a system. Proteins are abstracted as spheres. Binding surfaces are defined radially within a protein. Peptide linkers are abstracted as small protein-like spheres with rigid connections. To address whether our framework could generate useful predictions, we simulated the behavior of an engineered fusion protein consisting of two 20 000 Da proteins attached by flexible glycine/serine-type linkers. The two protein elements remained closely associated, as if constrained by a random walk in three dimensions of the peptide linker, as opposed to showing a distribution of distances expected if movement were dominated by Brownian motion of the protein domains only. We also simulated the behavior of fluorescent proteins tethered by a linker of varying length, compared the predicted Förster resonance energy transfer with previous experimental observations, and obtained a good correspondence. Finally, we simulated the binding behavior of a fusion of two ligands that could simultaneously bind to distinct cell-surface receptors, and explored the landscape of linker lengths and stiffnesses that could enhance receptor binding of one ligand when the other ligand has already bound to its receptor, thus, addressing potential mechanisms for improving targeted signal transduction proteins. These specific results have implications for the design of targeted fusion proteins and artificial transcription factors involving fusion of natural domains. More broadly, the simulation framework described here could be extended to include more detailed system features such as non-spherical protein shapes and electrostatics, without requiring detailed, computationally expensive specifications. This framework should be useful in predicting behavior of engineered protein systems including binding and dissociation reactions. PMID:23822508

Gravitational Self-Energy as the Litmus of Reality

NASA Astrophysics Data System (ADS)

Jones, K. R. W.

It is argued that the correct physical treatment of self-energy in Newtonian quantum gravity offers a constrained and predictive discriminator for the interpretation of ψ, and thus a clear point of departure for the unification of modern physics.

Controls on Nitrous Oxide Emissions from the Hyporheic Zones of Streams.

PubMed

Quick, Annika M; Reeder, W Jeffery; Farrell, Tiffany B; Tonina, Daniele; Feris, Kevin P; Benner, Shawn G

2016-11-01

The magnitude and mechanisms of nitrous oxide (N 2 O) release from rivers and streams are actively debated. The complex interactions of hydrodynamic and biogeochemical controls on emissions of this important greenhouse gas preclude prediction of when and where N 2 O emissions will be significant. We present observations from column and large-scale flume experiments supporting an integrative model of N 2 O emissions from stream sediments. Our results show a distinct, replicable, pattern of nitrous oxide generation and consumption dictated by subsurface (hyporheic) residence times and biological nitrogen reduction rates. Within this model, N 2 O emission from stream sediments requires subsurface residence times (and microbially mediated reduction rates) be sufficiently long (and fast reacting) to produce N 2 O by nitrate reduction but also sufficiently short (or slow reacting) to limit N 2 O conversion to dinitrogen gas. Most subsurface exchange will not result in N 2 O emissions; only specific, intermediate, residence times (reaction rates) will both produce and release N 2 O to the stream. We also confirm previous observations that elevated nitrate and declining organic carbon reactivity increase N 2 O production, highlighting the importance of associated reaction rates in controlling N 2 O accumulation. Combined, these observations help constrain when N 2 O release will occur, providing a predictive link between stream geomorphology, hydrodynamics, and N 2 O emissions.

Constant-Time Pattern Matching For Real-Time Production Systems

NASA Astrophysics Data System (ADS)

Parson, Dale E.; Blank, Glenn D.

1989-03-01

Many intelligent systems must respond to sensory data or critical environmental conditions in fixed, predictable time. Rule-based systems, including those based on the efficient Rete matching algorithm, cannot guarantee this result. Improvement in execution-time efficiency is not all that is needed here; it is important to ensure constant, 0(1) time limits for portions of the matching process. Our approach is inspired by two observations about human performance. First, cognitive psychologists distinguish between automatic and controlled processing. Analogously, we partition the matching process across two networks. The first is the automatic partition; it is characterized by predictable 0(1) time and space complexity, lack of persistent memory, and is reactive in nature. The second is the controlled partition; it includes the search-based goal-driven and data-driven processing typical of most production system programming. The former is responsible for recognition and response to critical environmental conditions. The latter is responsible for the more flexible problem-solving behaviors consistent with the notion of intelligence. Support for learning and refining the automatic partition can be placed in the controlled partition. Our second observation is that people are able to attend to more critical stimuli or requirements selectively. Our match algorithm uses priorities to focus matching. It compares priority of information during matching, rather than deferring this comparison until conflict resolution. Messages from the automatic partition are able to interrupt the controlled partition, enhancing system responsiveness. Our algorithm has numerous applications for systems that must exhibit time-constrained behavior.

Mixed-Strategy Chance Constrained Optimal Control

NASA Technical Reports Server (NTRS)

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

2013-01-01

This paper presents a novel chance constrained optimal control (CCOC) algorithm that chooses a control action probabilistically. A CCOC problem is to find a control input that minimizes the expected cost while guaranteeing that the probability of violating a set of constraints is below a user-specified threshold. We show that a probabilistic control approach, which we refer to as a mixed control strategy, enables us to obtain a cost that is better than what deterministic control strategies can achieve when the CCOC problem is nonconvex. The resulting mixed-strategy CCOC problem turns out to be a convexification of the original nonconvex CCOC problem. Furthermore, we also show that a mixed control strategy only needs to "mix" up to two deterministic control actions in order to achieve optimality. Building upon an iterative dual optimization, the proposed algorithm quickly converges to the optimal mixed control strategy with a user-specified tolerance.

Chaos control for the output-constrained system by using adaptive dynamic surface technology and application to the brushless DC motor

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

Luo, Shaohua, E-mail: hua66com@163.com; School of Automation, Chongqing University, Chongqing 400044; Hou, Zhiwei

2015-12-15

In this paper, chaos control is proposed for the output- constrained system with uncertain control gain and time delay and is applied to the brushless DC motor. Using the dynamic surface technology, the controller overcomes the repetitive differentiation of backstepping and boundedness hypothesis of pre-determined control gain by incorporating radial basis function neural network and adaptive technology. The tangent barrier Lyapunov function is employed for time-delay chaotic system to prevent constraint violation. It is proved that the proposed control approach can guarantee asymptotically stable in the sense of uniformly ultimate boundedness without constraint violation. Finally, the effectiveness of the proposedmore » approach is demonstrated on the brushless DC motor example.« less

Evolution of Inbreeding Avoidance and Inbreeding Preference through Mate Choice among Interacting Relatives.

PubMed

Duthie, A Bradley; Reid, Jane M

2016-12-01

While extensive population genetic theory predicts conditions favoring evolution of self-fertilization versus outcrossing, there is no analogous theory that predicts conditions favoring evolution of inbreeding avoidance or inbreeding preference enacted through mate choice given obligate biparental reproduction. Multiple interacting processes complicate the dynamics of alleles underlying such inbreeding strategies, including sexual conflict, distributions of kinship, genetic drift, purging of mutation load, direct costs, and restricted kin discrimination. We incorporated these processes into an individual-based model to predict conditions where selection should increase or decrease frequencies of alleles causing inbreeding avoidance or inbreeding preference when females or males controlled mating. Selection for inbreeding avoidance occurred given strong inbreeding depression when either sex chose mates, while selection for inbreeding preference occurred given very weak inbreeding depression when females chose but never occurred when males chose. Selection for both strategies was constrained by direct costs and restricted kin discrimination. Purging was negligible, but allele frequencies were strongly affected by drift in small populations, while selection for inbreeding avoidance was weak in larger populations because inbreeding risk decreased. Therefore, while selection sometimes favored alleles underlying inbreeding avoidance or preference, evolution of such strategies may be much more restricted and stochastic than is commonly presumed.

A physically-based method for predicting peak discharge of floods caused by failure of natural and constructed earthen dams

USGS Publications Warehouse

Walder, J.S.

1997-01-01

We analyse a simple, physically-based model of breach formation in natural and constructed earthen dams to elucidate the principal factors controlling the flood hydrograph at the breach. Formation of the breach, which is assumed trapezoidal in cross-section, is parameterized by the mean rate of downcutting, k, the value of which is constrained by observations. A dimensionless formulation of the model leads to the prediction that the breach hydrograph depends upon lake shape, the ratio r of breach width to depth, the side slope ?? of the breach, and the parameter ?? = (V/ D3)(k/???gD), where V = lake volume, D = lake depth, and g is the acceleration due to gravity. Calculations show that peak discharge Qp depends weakly on lake shape r and ??, but strongly on ??, which is the product of a dimensionless lake volume and a dimensionless erosion rate. Qp(??) takes asymptotically distinct forms depending on whether ?? > 1. Theoretical predictions agree well with data from dam failures for which k could be reasonably estimated. The analysis provides a rapid and in many cases graphical way to estimate plausible values of Qp at the breach.

Management of Occupational Exposure to Engineered Nanoparticles Through a Chance-Constrained Nonlinear Programming Approach

PubMed Central

Chen, Zhi; Yuan, Yuan; Zhang, Shu-Shen; Chen, Yu; Yang, Feng-Lin

2013-01-01

Critical environmental and human health concerns are associated with the rapidly growing fields of nanotechnology and manufactured nanomaterials (MNMs). The main risk arises from occupational exposure via chronic inhalation of nanoparticles. This research presents a chance-constrained nonlinear programming (CCNLP) optimization approach, which is developed to maximize the nanaomaterial production and minimize the risks of workplace exposure to MNMs. The CCNLP method integrates nonlinear programming (NLP) and chance-constrained programming (CCP), and handles uncertainties associated with both the nanomaterial production and workplace exposure control. The CCNLP method was examined through a single-walled carbon nanotube (SWNT) manufacturing process. The study results provide optimal production strategies and alternatives. It reveal that a high control measure guarantees that environmental health and safety (EHS) standards regulations are met, while a lower control level leads to increased risk of violating EHS regulations. The CCNLP optimization approach is a decision support tool for the optimization of the increasing MNMS manufacturing with workplace safety constraints under uncertainties. PMID:23531490

Management of occupational exposure to engineered nanoparticles through a chance-constrained nonlinear programming approach.

PubMed

Chen, Zhi; Yuan, Yuan; Zhang, Shu-Shen; Chen, Yu; Yang, Feng-Lin

2013-03-26

Critical environmental and human health concerns are associated with the rapidly growing fields of nanotechnology and manufactured nanomaterials (MNMs). The main risk arises from occupational exposure via chronic inhalation of nanoparticles. This research presents a chance-constrained nonlinear programming (CCNLP) optimization approach, which is developed to maximize the nanaomaterial production and minimize the risks of workplace exposure to MNMs. The CCNLP method integrates nonlinear programming (NLP) and chance-constrained programming (CCP), and handles uncertainties associated with both the nanomaterial production and workplace exposure control. The CCNLP method was examined through a single-walled carbon nanotube (SWNT) manufacturing process. The study results provide optimal production strategies and alternatives. It reveal that a high control measure guarantees that environmental health and safety (EHS) standards regulations are met, while a lower control level leads to increased risk of violating EHS regulations. The CCNLP optimization approach is a decision support tool for the optimization of the increasing MNMS manufacturing with workplace safety constraints under uncertainties.

Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

Treesearch

R. Quinn Thomas; Evan B. Brooks; Annika L. Jersild; Eric J. Ward; Randolph H. Wynne; Timothy J. Albaugh; Heather Dinon-Aldridge; Harold E. Burkhart; Jean-Christophe Domec; Timothy R. Fox; Carlos A. Gonzalez-Benecke; Timothy A. Martin; Asko Noormets; David A. Sampson; Robert O. Teskey

2017-01-01

Predicting how forest carbon cycling will change in response to climate change and management depends on the collective knowledge from measurements across environmental gradients, ecosystem manipulations of global change factors, and mathematical models. Formally integrating these sources of knowledge through data assimilation, or model–data fusion, allows the use of...

Constraint shapes convergence in tetrodotoxin-resistant sodium channels of snakes.

PubMed

Feldman, Chris R; Brodie, Edmund D; Brodie, Edmund D; Pfrender, Michael E

2012-03-20

Natural selection often produces convergent changes in unrelated lineages, but the degree to which such adaptations occur via predictable genetic paths is unknown. If only a limited subset of possible mutations is fixed in independent lineages, then it is clear that constraint in the production or function of molecular variants is an important determinant of adaptation. We demonstrate remarkably constrained convergence during the evolution of resistance to the lethal poison, tetrodotoxin, in six snake species representing three distinct lineages from around the globe. Resistance-conferring amino acid substitutions in a voltage-gated sodium channel, Na(v)1.4, are clustered in only two regions of the protein, and a majority of the replacements are confined to the same three positions. The observed changes represent only a small fraction of the experimentally validated mutations known to increase Na(v)1.4 resistance to tetrodotoxin. These results suggest that constraints resulting from functional tradeoffs between ion channel function and toxin resistance led to predictable patterns of evolutionary convergence at the molecular level. Our data are consistent with theoretical predictions and recent microcosm work that suggest a predictable path is followed during an adaptive walk along a mutational landscape, and that natural selection may be frequently constrained to produce similar genetic outcomes even when operating on independent lineages.

EMG prediction from Motor Cortical Recordings via a Non-Negative Point Process Filter

PubMed Central

Nazarpour, Kianoush; Ethier, Christian; Paninski, Liam; Rebesco, James M.; Miall, R. Chris; Miller, Lee E.

2012-01-01

A constrained point process filtering mechanism for prediction of electromyogram (EMG) signals from multi-channel neural spike recordings is proposed here. Filters from the Kalman family are inherently sub-optimal in dealing with non-Gaussian observations, or a state evolution that deviates from the Gaussianity assumption. To address these limitations, we modeled the non-Gaussian neural spike train observations by using a generalized linear model (GLM) that encapsulates covariates of neural activity, including the neurons’ own spiking history, concurrent ensemble activity, and extrinsic covariates (EMG signals). In order to predict the envelopes of EMGs, we reformulated the Kalman filter (KF) in an optimization framework and utilized a non-negativity constraint. This structure characterizes the non-linear correspondence between neural activity and EMG signals reasonably. The EMGs were recorded from twelve forearm and hand muscles of a behaving monkey during a grip-force task. For the case of limited training data, the constrained point process filter improved the prediction accuracy when compared to a conventional Wiener cascade filter (a linear causal filter followed by a static non-linearity) for different bin sizes and delays between input spikes and EMG output. For longer training data sets, results of the proposed filter and that of the Wiener cascade filter were comparable. PMID:21659018

Inhibitory Control Interacts with Core Knowledge in Toddlers' Manual Search for an Occluded Object

ERIC Educational Resources Information Center

Baker, Sara T.; Gjersoe, Nathalia L.; Sibielska-Woch, Kasia; Leslie, Alan M.; Hood, Bruce M.

2011-01-01

Core knowledge theories advocate the primacy of fundamental principles that constrain cognitive development from early infancy. However, there is concern that core knowledge of object properties does not constrain older preschoolers' reasoning during manual search. Here we address in detail both failure and success on two well-established search…

Evaluation of the performance of a passive-active vibration isolation system

NASA Astrophysics Data System (ADS)

Sun, L. L.; Hansen, C. H.; Doolan, C.

2015-01-01

The behavior of a feedforward active isolation system subjected to actuator output constraints is investigated. Distributed parameter models are developed to analyze the system response, and to produce a transfer matrix for the design of an integrated passive-active isolation system. Cost functions considered here comprise a combination of the vibration transmission energy and the sum of the squared control forces. The example system considered is a rigid body connected to a simply supported plate via two isolation mounts. The overall isolation performance is evaluated by numerical simulation. The results show that the control strategies which rely on unconstrained actuator outputs may give substantial power transmission reductions over a wide frequency range, but also require large control force amplitudes to control excited vibration modes of the system. Expected power transmission reductions for modified control strategies that incorporate constrained actuator outputs are considerably less than typical reductions with unconstrained actuator outputs. The active system with constrained control force outputs is shown to be more effective at the resonance frequencies of the supporting plate. However, in the frequency range in which rigid body modes are present, the control strategies employed using constrained actuator outputs can only achieve 5-10 dB power transmission reduction, while at off-resonance frequencies, little or no power transmission reduction can be obtained with realistic control forces. Analysis of the wave effects in the passive mounts is also presented.

Vibroacoustic study of a point-constrained plate mounted in a duct

NASA Astrophysics Data System (ADS)

Sapkale, Swapnil L.; Sucheendran, Mahesh M.; Gupta, Shakti S.; Kanade, Shantanu V.

2018-04-01

The vibroacoustic study of the interaction of sound with a point-constrained, simply-supported square plate is considered in this paper. The plate is mounted flush on one of the walls of an infinite duct of rectangular cross section and is backed by a cavity. The plate response and the acoustic field is predicted by solving the coupled governing equations using modal expansion with the relevant eigenmodes of the plate dynamics and acoustic fields in the duct and cavity. By varying the location of the point constraint, the frequency characteristics of the transmission loss in the duct can be tuned. The point constraint can also alter the amplitude and spectral characteristics of the plate's response. Interestingly, some new peaks are observed in the response because of the excitation of unsymmetric modes which are otherwise dormant. Mode-localization phenomenon, which is the localization of vibration in specific regions of the plate, is observed for selected constrained points.

Sequential Probability Ratio Test for Collision Avoidance Maneuver Decisions Based on a Bank of Norm-Inequality-Constrained Epoch-State Filters

NASA Technical Reports Server (NTRS)

Carpenter, J. R.; Markley, F. L.; Alfriend, K. T.; Wright, C.; Arcido, J.

2011-01-01

Sequential probability ratio tests explicitly allow decision makers to incorporate false alarm and missed detection risks, and are potentially less sensitive to modeling errors than a procedure that relies solely on a probability of collision threshold. Recent work on constrained Kalman filtering has suggested an approach to formulating such a test for collision avoidance maneuver decisions: a filter bank with two norm-inequality-constrained epoch-state extended Kalman filters. One filter models 1he null hypothesis 1ha1 the miss distance is inside the combined hard body radius at the predicted time of closest approach, and one filter models the alternative hypothesis. The epoch-state filter developed for this method explicitly accounts for any process noise present in the system. The method appears to work well using a realistic example based on an upcoming highly-elliptical orbit formation flying mission.

The role of motor simulation in action perception: a neuropsychological case study.

PubMed

Eskenazi, Terry; Grosjean, Marc; Humphreys, Glyn W; Knoblich, Guenther

2009-07-01

Research on embodied cognition stresses that bodily and motor processes constrain how we perceive others. Regarding action perception the most prominent hypothesis is that observed actions are matched to the observer's own motor representations. Previous findings demonstrate that the motor laws that constrain one's performance also constrain one's perception of others' actions. The present neuropsychological case study asked whether neurological impairments affect a person's performance and action perception in the same way. The results showed that patient DS, who suffers from a frontal brain lesion, not only ignored target size when performing movements but also when asked to judge whether others can perform the same movements. In other words DS showed the same violation of Fitts's law when performing and observing actions. These results further support the assumption of close perception action links and the assumption that these links recruit predictive mechanisms residing in the motor system.

The effect of imperfections on the vertical buckling of railroad tracks

DOT National Transportation Integrated Search

1976-06-30

This report deals with an analytical prediction of the effect of geometric imperfections on the post-buckling characteristics of railroad tracks. The analysis is restricted to the case of vertical track buckling due to constrained thermal expansion i...

Dispatching power system for preventive and corrective voltage collapse problem in a deregulated power system

NASA Astrophysics Data System (ADS)

Alemadi, Nasser Ahmed

Deregulation has brought opportunities for increasing efficiency of production and delivery and reduced costs to customers. Deregulation has also bought great challenges to provide the reliability and security customers have come to expect and demand from the electrical delivery system. One of the challenges in the deregulated power system is voltage instability. Voltage instability has become the principal constraint on power system operation for many utilities. Voltage instability is a unique problem because it can produce an uncontrollable, cascading instability that results in blackout for a large region or an entire country. In this work we define a system of advanced analytical methods and tools for secure and efficient operation of the power system in the deregulated environment. The work consists of two modules; (a) contingency selection module and (b) a Security Constrained Optimization module. The contingency selection module to be used for voltage instability is the Voltage Stability Security Assessment and Diagnosis (VSSAD). VSSAD shows that each voltage control area and its reactive reserve basin describe a subsystem or agent that has a unique voltage instability problem. VSSAD identifies each such agent. VS SAD is to assess proximity to voltage instability for each agent and rank voltage instability agents for each contingency simulated. Contingency selection and ranking for each agent is also performed. Diagnosis of where, why, when, and what can be done to cure voltage instability for each equipment outage and transaction change combination that has no load flow solution is also performed. A security constrained optimization module developed solves a minimum control solvability problem. A minimum control solvability problem obtains the reactive reserves through action of voltage control devices that VSSAD determines are needed in each agent to obtain solution of the load flow. VSSAD makes a physically impossible recommendation of adding reactive generation capability to specific generators to allow a load flow solution to be obtained. The minimum control solvability problem can also obtain solution of the load flow without curtailing transactions that shed load and generation as recommended by VSSAD. A minimum control solvability problem will be implemented as a corrective control, that will achieve the above objectives by using minimum control changes. The control includes; (1) voltage setpoint on generator bus voltage terminals; (2) under load tap changer tap positions and switchable shunt capacitors; and (3) active generation at generator buses. The minimum control solvability problem uses the VSSAD recommendation to obtain the feasible stable starting point but completely eliminates the impossible or onerous recommendation made by VSSAD. This thesis reviews the capabilities of Voltage Stability Security Assessment and Diagnosis and how it can be used to implement a contingency selection module for the Open Access System Dispatch (OASYDIS). The OASYDIS will also use the corrective control computed by Security Constrained Dispatch. The corrective control would be computed off line and stored for each contingency that produces voltage instability. The control is triggered and implemented to correct the voltage instability in the agent experiencing voltage instability only after the equipment outage or operating changes predicted to produce voltage instability have occurred. The advantages and the requirements to implement the corrective control are also discussed.

Integrated identification, modeling and control with applications

NASA Astrophysics Data System (ADS)

Shi, Guojun

This thesis deals with the integration of system design, identification, modeling and control. In particular, six interdisciplinary engineering problems are addressed and investigated. Theoretical results are established and applied to structural vibration reduction and engine control problems. First, the data-based LQG control problem is formulated and solved. It is shown that a state space model is not necessary to solve this problem; rather a finite sequence from the impulse response is the only model data required to synthesize an optimal controller. The new theory avoids unnecessary reliance on a model, required in the conventional design procedure. The infinite horizon model predictive control problem is addressed for multivariable systems. The basic properties of the receding horizon implementation strategy is investigated and the complete framework for solving the problem is established. The new theory allows the accommodation of hard input constraints and time delays. The developed control algorithms guarantee the closed loop stability. A closed loop identification and infinite horizon model predictive control design procedure is established for engine speed regulation. The developed algorithms are tested on the Cummins Engine Simulator and desired results are obtained. A finite signal-to-noise ratio model is considered for noise signals. An information quality index is introduced which measures the essential information precision required for stabilization. The problems of minimum variance control and covariance control are formulated and investigated. Convergent algorithms are developed for solving the problems of interest. The problem of the integrated passive and active control design is addressed in order to improve the overall system performance. A design algorithm is developed, which simultaneously finds: (i) the optimal values of the stiffness and damping ratios for the structure, and (ii) an optimal output variance constrained stabilizing controller such that the active control energy is minimized. A weighted q-Markov COVER method is introduced for identification with measurement noise. The result is use to develop an iterative closed loop identification/control design algorithm. The effectiveness of the algorithm is illustrated by experimental results.

Constraining the physical properties of compositionally distinctive surfaces on Mars from overlapping THEMIS observations

NASA Astrophysics Data System (ADS)

Ahern, A.; Rogers, D.

2017-12-01

Better constraints on the physical properties (e.g. grain size, rock abundance, cohesion, porosity and amount of induration) of Martian surface materials can lead to greater understanding of outcrop origin (e.g. via sedimentary, effusive volcanic, pyroclastic processes). Many outcrop surfaces on Mars likely contain near-surface (<3 cm) vertical heterogeneity in physical properties due to thin sediment cover, induration, and physical weathering, that can obscure measurement of the bulk thermal conductivity of the outcrop materials just below. Fortunately, vertical heterogeneity within near-surface materials can result in unique, and possibly predictable, diurnal and seasonal temperature patterns. The KRC thermal model has been utilized in a number of previous studies to predict thermal inertia of surface materials on Mars. Here we use KRC to model surface temperatures from overlapping Mars Odyssey THEMIS surface temperature observations that span multiple seasons and local times, in order to constrain both the nature of vertical heterogeneity and the underlying outcrop thermal inertia for various spectrally distinctive outcrops on Mars. We utilize spectral observations from TES and CRISM to constrain the particle size of the uppermost surface. For this presentation, we will focus specifically on chloride-bearing units in Terra Sirenum and Meridiani Planum, as well as mafic and feldspathic bedrock locations with distinct spectral properties, yet uncertain origins, in Noachis Terra and Nili Fossae. We find that many of these surfaces exhibit variations in apparent thermal inertia with season and local time that are consistent with low thermal inertia materials overlying higher thermal inertia substrates. Work is ongoing to compare surface temperature measurements with modeled two-layer scenarios in order to constrain the top layer thickness and bottom layer thermal inertia. The information will be used to better interpret the origins of these distinctive outcrops.

Vibration control of beams using constrained layer damping with functionally graded viscoelastic cores: theory and experiments

NASA Astrophysics Data System (ADS)

El-Sabbagh, A.; Baz, A.

2006-03-01

Conventionally, the viscoelastic cores of Constrained Layer Damping (CLD) treatments are made of materials that have uniform shear modulus. Under such conditions, it is well-recognized that these treatments are only effective near their edges where the shear strains attain their highest values. In order to enhance the damping characteristics of the CLD treatments, we propose to manufacture the cores from Functionally Graded ViscoElastic Materials (FGVEM) that have optimally selected gradient of the shear modulus over the length of the treatments. With such optimized distribution of the shear modulus, the shear strain can be enhanced, and the energy dissipation can be maximized. The theory governing the vibration of beams treated with CLD, that has functionally graded viscoelastic cores, is presented using the finite element method (FEM). The predictions of the FEM are validated experimentally for plain beams, beams treated conventional CLD, and beams with CLD/FGVEM of different configurations. The obtained results indicate a close agreement between theory and experiments. Furthermore, the obtained results demonstrate the effectiveness of the new class of CLD with functionally graded cores in enhancing the energy dissipation over the conventional CLD over a broad frequency band. Extension of the proposed one-dimensional beam/CLD/FGVEM system to more complex structures is a natural extension to the present study.

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

NASA Astrophysics Data System (ADS)

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

2002-06-01

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

Modelling carotid artery adaptations to dynamic alterations in pressure and flow over the cardiac cycle

PubMed Central

Cardamone, L.; Valentín, A.; Eberth, J. F.; Humphrey, J. D.

2010-01-01

Motivated by recent clinical and laboratory findings of important effects of pulsatile pressure and flow on arterial adaptations, we employ and extend an established constrained mixture framework of growth (change in mass) and remodelling (change in structure) to include such dynamical effects. New descriptors of cell and tissue behavior (constitutive relations) are postulated and refined based on new experimental data from a transverse aortic arch banding model in the mouse that increases pulsatile pressure and flow in one carotid artery. In particular, it is shown that there was a need to refine constitutive relations for the active stress generated by smooth muscle, to include both stress- and stress rate-mediated control of the turnover of cells and matrix and to account for a cyclic stress-mediated loss of elastic fibre integrity and decrease in collagen stiffness in order to capture the reported evolution, over 8 weeks, of luminal radius, wall thickness, axial force and in vivo axial stretch of the hypertensive mouse carotid artery. We submit, therefore, that complex aspects of adaptation by elastic arteries can be predicted by constrained mixture models wherein individual constituents are produced or removed at individual rates and to individual extents depending on changes in both stress and stress rate from normal values. PMID:20484365

Flutter suppression of plates using passive constrained viscoelastic layers

NASA Astrophysics Data System (ADS)

Cunha-Filho, A. G.; de Lima, A. M. G.; Donadon, M. V.; Leão, L. S.

2016-10-01

Flutter in aeronautical panels is a self-excited aeroelastic phenomenon which occurs during supersonic flights due to dynamic instability of inertia, elastic and aerodynamic forces of the system. In the flutter condition, when the critical aerodynamic pressure is reached, the vibration amplitudes of the panel become dynamically unstable and increase exponentially with time, significantly affecting the fatigue life of the existing aeronautical components. Thus, in this paper, the interest is to investigate the possibility reducing the effects of the supersonic aeroelastic instability of rectangular plates by applying passive constrained viscoelastic layers. The rationale for such study is the fact that as the addition of viscoelastic materials provides decreased vibration amplitudes it becomes important to quantify the suppression of plate flutter coalescence modes that can be obtained. Moreover, despite the fact that much research on the suppression of panel flutter has been carried out by using passive, semi-active and active control techniques, few works have been proposed to deal with the problem of predicting the flutter boundary of aeroviscoelastic systems, since they must conveniently account for the frequency- and temperature-dependent behavior of the viscoelastic material. After the presentation of the theoretical foundations of the methodology, the description of a numerical study on the flutter analysis of a three-layer sandwich plate is addressed.

Carbonate system parameters of an algal-dominated reef along West Maui

NASA Astrophysics Data System (ADS)

Prouty, Nancy G.; Yates, Kimberly K.; Smiley, Nathan; Gallagher, Chris; Cheriton, Olivia; Storlazzi, Curt D.

2018-04-01

Constraining coral reef metabolism and carbon chemistry dynamics are fundamental for understanding and predicting reef vulnerability to rising coastal CO2 concentrations and decreasing seawater pH. However, few studies exist along reefs occupying densely inhabited shorelines with known input from land-based sources of pollution. The shallow coral reefs off Kahekili, West Maui, are exposed to nutrient-enriched, low-pH submarine groundwater discharge (SGD) and are particularly vulnerable to the compounding stressors from land-based sources of pollution and lower seawater pH. To constrain the carbonate chemistry system, nutrients and carbonate chemistry were measured along the Kahekili reef flat every 4 h over a 6-day sampling period in March 2016. Abiotic process - primarily SGD fluxes - controlled the carbonate chemistry adjacent to the primary SGD vent site, with nutrient-laden freshwater decreasing pH levels and favoring undersaturated aragonite saturation (Ωarag) conditions. In contrast, diurnal variability in the carbonate chemistry at other sites along the reef flat was driven by reef community metabolism. Superimposed on the diurnal signal was a transition during the second sampling period to a surplus of total alkalinity (TA) and dissolved inorganic carbon (DIC) compared to ocean endmember TA and DIC measurements. A shift from positive net community production and positive net community calcification to negative net community production and negative net community calcification was identified. This transition occurred during a period of increased SGD-driven nutrient loading, lower wave height, and reduced current speeds. This detailed study of carbon chemistry dynamics highlights the need to incorporate local effects of nearshore oceanographic processes into predictions of coral reef vulnerability and resilience.

Redesigning Escherichia coli Metabolism for Anaerobic Production of Isobutanol▿†

PubMed Central

Trinh, Cong T.; Li, Johnny; Blanch, Harvey W.; Clark, Douglas S.

2011-01-01

Fermentation enables the production of reduced metabolites, such as the biofuels ethanol and butanol, from fermentable sugars. This work demonstrates a general approach for designing and constructing a production host that uses a heterologous pathway as an obligately fermentative pathway to produce reduced metabolites, specifically, the biofuel isobutanol. Elementary mode analysis was applied to design an Escherichia coli strain optimized for isobutanol production under strictly anaerobic conditions. The central metabolism of E. coli was decomposed into 38,219 functional, unique, and elementary modes (EMs). The model predictions revealed that during anaerobic growth E. coli cannot produce isobutanol as the sole fermentative product. By deleting 7 chromosomal genes, the total 38,219 EMs were constrained to 12 EMs, 6 of which can produce high yields of isobutanol in a range from 0.29 to 0.41 g isobutanol/g glucose under anaerobic conditions. The remaining 6 EMs rely primarily on the pyruvate dehydrogenase enzyme complex (PDHC) and are typically inhibited under anaerobic conditions. The redesigned E. coli strain was constrained to employ the anaerobic isobutanol pathways through deletion of 7 chromosomal genes, addition of 2 heterologous genes, and overexpression of 5 genes. Here we present the design, construction, and characterization of an isobutanol-producing E. coli strain to illustrate the approach. The model predictions are evaluated in relation to experimental data and strategies proposed to improve anaerobic isobutanol production. We also show that the endogenous alcohol/aldehyde dehydrogenase AdhE is the key enzyme responsible for the production of isobutanol and ethanol under anaerobic conditions. The glycolytic flux can be controlled to regulate the ratio of isobutanol to ethanol production. PMID:21642415

The robust model predictive control based on mixed H2/H∞ approach with separated performance formulations and its ISpS analysis

NASA Astrophysics Data System (ADS)

Li, Dewei; Li, Jiwei; Xi, Yugeng; Gao, Furong

2017-12-01

In practical applications, systems are always influenced by parameter uncertainties and external disturbance. Both the H2 performance and the H∞ performance are important for the real applications. For a constrained system, the previous designs of mixed H2/H∞ robust model predictive control (RMPC) optimise one performance with the other performance requirement as a constraint. But the two performances cannot be optimised at the same time. In this paper, an improved design of mixed H2/H∞ RMPC for polytopic uncertain systems with external disturbances is proposed to optimise them simultaneously. In the proposed design, the original uncertain system is decomposed into two subsystems by the additive character of linear systems. Two different Lyapunov functions are used to separately formulate the two performance indices for the two subsystems. Then, the proposed RMPC is designed to optimise both the two performances by the weighting method with the satisfaction of the H∞ performance requirement. Meanwhile, to make the design more practical, a simplified design is also developed. The recursive feasible conditions of the proposed RMPC are discussed and the closed-loop input state practical stable is proven. The numerical examples reflect the enlarged feasible region and the improved performance of the proposed design.

Does Nudging Squelch the Extremes in Regional Climate Modeling?

EPA Science Inventory

An important question in regional climate downscaling is whether to constrain (nudge) the interior of the limited-area domain toward the larger-scale driving fields. Prior research has demonstrated that interior nudging can increase the skill of regional climate predictions origin...

Stall Recovery Guidance Algorithms Based on Constrained Control Approaches

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje; Kaneshige, John; Acosta, Diana

2016-01-01

Aircraft loss-of-control, in particular approach to stall or fully developed stall, is a major factor contributing to aircraft safety risks, which emphasizes the need to develop algorithms that are capable of assisting the pilots to identify the problem and providing guidance to recover the aircraft. In this paper we present several stall recovery guidance algorithms, which are implemented in the background without interfering with flight control system and altering the pilot's actions. They are using input and state constrained control methods to generate guidance signals, which are provided to the pilot in the form of visual cues. It is the pilot's decision to follow these signals. The algorithms are validated in the pilot-in-the loop medium fidelity simulation experiment.

Boundary control for a constrained two-link rigid-flexible manipulator with prescribed performance

NASA Astrophysics Data System (ADS)

Cao, Fangfei; Liu, Jinkun

2018-05-01

In this paper, we consider a boundary control problem for a constrained two-link rigid-flexible manipulator. The nonlinear system is described by hybrid ordinary differential equation-partial differential equation (ODE-PDE) dynamic model. Based on the coupled ODE-PDE model, boundary control is proposed to regulate the joint positions and eliminate the elastic vibration simultaneously. With the help of prescribed performance functions, the tracking error can converge to an arbitrarily small residual set and the convergence rate is no less than a certain pre-specified value. Asymptotic stability of the closed-loop system is rigorously proved by the LaSalle's Invariance Principle extended to infinite-dimensional system. Numerical simulations are provided to demonstrate the effectiveness of the proposed controller.

Directional control of lamellipodia extension by constraining cell shape and orienting cell tractional forces

NASA Technical Reports Server (NTRS)

Parker, Kevin Kit; Brock, Amy Lepre; Brangwynne, Cliff; Mannix, Robert J.; Wang, Ning; Ostuni, Emanuele; Geisse, Nicholas A.; Adams, Josephine C.; Whitesides, George M.; Ingber, Donald E.

2002-01-01

Directed cell migration is critical for tissue morphogenesis and wound healing, but the mechanism of directional control is poorly understood. Here we show that the direction in which cells extend their leading edge can be controlled by constraining cell shape using micrometer-sized extracellular matrix (ECM) islands. When cultured on square ECM islands in the presence of motility factors, cells preferentially extended lamellipodia, filopodia, and microspikes from their corners. Square cells reoriented their stress fibers and focal adhesions so that tractional forces were concentrated in these corner regions. When cell tension was dissipated, lamellipodia extension ceased. Mechanical interactions between cells and ECM that modulate cytoskeletal tension may therefore play a key role in the control of directional cell motility.

Figure of Merit Characteristics Compared to Engineering Parameters

NASA Technical Reports Server (NTRS)

Rickman, D.L.; Schrader, C.M.

2010-01-01

A workshop held in 2005 defined a large number of parameters of interest for users of lunar simulants. The need for formal requirements and standards in the manufacture and use of simulants necessitates certain features of measurements. They must be definable, measureable, useful, and primary rather than derived. There are also certain features that must be avoided. Analysis of the total parameter list led to the realization that almost all of the parameters could be tightly constrained, though not predicted, if only four properties were measured: Particle composition, particle size distribution, particle shape distribution, and bulk density. These four are collectively referred to as figures of merit (FoMs). An evaluation of how each of the parameters identified in 2005 is controlled by the four FoMs is given.

MPR

PubMed Central

Killeen, Peter R.; Sitomer, Matthew T.

2008-01-01

Mathematical Principles of Reinforcement (MPR) is a theory of reinforcement schedules. This paper reviews the origin of the principles constituting MPR: arousal, association and constraint. Incentives invigorate responses, in particular those preceding and predicting the incentive. The process that generates an associative bond between stimuli, responses and incentives is called coupling. The combination of arousal and coupling constitutes reinforcement. Models of coupling play a central role in the evolution of the theory. The time required to respond constrains the maximum response rates, and generates a hyperbolic relation between rate of responding and rate of reinforcement. Models of control by ratio schedules are developed to illustrate the interaction of the principles. Correlations among parameters are incorporated into the structure of the models, and assumptions that were made in the original theory are refined in light of current data. PMID:12729968

Reactor Simulator Testing Overview

NASA Technical Reports Server (NTRS)

Schoenfeld, Michael P.

2013-01-01

OBJECTIVE: Integrated testing of the TDU components TESTING SUMMARY: a) Verify the operation of the core simulator, the instrumentation and control system, and the ground support gas and vacuum test equipment. b) Thermal test heat regeneration design aspect of a cold trap purification filter. c) Pump performance test at pump voltages up to 150 V (targeted mass flow rate of 1.75 kg/s was not obtained in the RxSim at the originally constrained voltage of 120 V). TESTING HIGHLIGHTS: a) Gas and vacuum ground support test equipment performed effectively for NaK fill, loop pressurization, and NaK drain operations. b) Instrumentation and control system effectively controlled loop temperature and flow rates or pump voltage to targeted settings. c) Cold trap design was able to obtain the targeted cold temperature of 480 K. An outlet temperature of 636 K was obtained which was lower than the predicted 750 K but 156 K higher than the cold temperature indicating the design provided some heat regeneration. d) ALIP produce a maximum flow rate of 1.53 kg/s at 800 K when operated at 150 V and 53 Hz.

Effects of life-history requirements on the distribution of a threatened reptile.

PubMed

Thompson, Denise M; Ligon, Day B; Patton, Jason C; Papeş, Monica

2017-04-01

Survival and reproduction are the two primary life-history traits essential for species' persistence; however, the environmental conditions that support each of these traits may not be the same. Despite this, reproductive requirements are seldom considered when estimating species' potential distributions. We sought to examine potentially limiting environmental factors influencing the distribution of an oviparous reptile of conservation concern with respect to the species' survival and reproduction and to assess the implications of the species' predicted climatic constraints on current conservation practices. We used ecological niche modeling to predict the probability of environmental suitability for the alligator snapping turtle (Macrochelys temminckii). We built an annual climate model to examine survival and a nesting climate model to examine reproduction. We combined incubation temperature requirements, products of modeled soil temperature data, and our estimated distributions to determine whether embryonic development constrained the northern distribution of the species. Low annual precipitation constrained the western distribution of alligator snapping turtles, whereas the northern distribution was constrained by thermal requirements during embryonic development. Only a portion of the geographic range predicted to have a high probability of suitability for alligator snapping turtle survival was estimated to be capable of supporting successful embryonic development. Historic occurrence records suggest adult alligator snapping turtles can survive in regions with colder climes than those associated with consistent and successful production of offspring. Estimated egg-incubation requirements indicated that current reintroductions at the northern edge of the species' range are within reproductively viable environmental conditions. Our results highlight the importance of considering survival and reproduction when estimating species' ecological niches, implicating conservation plans, and benefits of incorporating physiological data when evaluating species' distributions. © 2016 Society for Conservation Biology.

Constraining the Sensitivity of Amazonian Rainfall with Observations of Surface Temperature

NASA Astrophysics Data System (ADS)

Dolman, A. J.; von Randow, C.; de Oliveira, G. S.; Martins, G.; Nobre, C. A.

2016-12-01

Earth System models generally do a poor job in predicting Amazonian rainfall, necessitating the need to look for observational constraints on their predictability. We use observed surface temperature and precipitation of the Amazon and a set of 21 CMIP5 models to derive an observational constraint of the sensitivity of rainfall to surface temperature (dP/dT). From first principles such a relation between the surface temperature of the earth and the amount of precipitation through the surface energy balance should exist, particularly in the tropics. When de-trended anomalies in surface temperature and precipitation from a set of datasets are plotted, a clear linear relation between surface temperature and precipitation appears. CMIP5 models show a similar relation with relatively cool models having a larger sensitivity, producing more rainfall. Using the ensemble of models and the observed surface temperature we were able to derive an emerging constraint, reducing the dPdt sensitivity of the CMIP5 model from -0.75 mm day-1 0C-1 (+/- 0.54 SD) to -0.77 mm day-1 0C-1 with a reduced uncertainty of about a factor 5. dPdT from the observation is -0.89 mm day-1 0C-1 . We applied the method to wet and dry season separately noticing that in the wet season we shifted the mean and reduced uncertainty, while in the dry season we very much reduced uncertainty only. The method can be applied to other model simulations such as specific deforestation scenarios to constrain the sensitivity of rainfall to surface temperature. We discuss the implications of the constrained sensitivity for future Amazonian predictions.

Optimal Guaranteed Cost Sliding Mode Control for Constrained-Input Nonlinear Systems With Matched and Unmatched Disturbances.

PubMed

Zhang, Huaguang; Qu, Qiuxia; Xiao, Geyang; Cui, Yang

2018-06-01

Based on integral sliding mode and approximate dynamic programming (ADP) theory, a novel optimal guaranteed cost sliding mode control is designed for constrained-input nonlinear systems with matched and unmatched disturbances. When the system moves on the sliding surface, the optimal guaranteed cost control problem of sliding mode dynamics is transformed into the optimal control problem of a reformulated auxiliary system with a modified cost function. The ADP algorithm based on single critic neural network (NN) is applied to obtain the approximate optimal control law for the auxiliary system. Lyapunov techniques are used to demonstrate the convergence of the NN weight errors. In addition, the derived approximate optimal control is verified to guarantee the sliding mode dynamics system to be stable in the sense of uniform ultimate boundedness. Some simulation results are presented to verify the feasibility of the proposed control scheme.

The electrochemistry of carbon steel in simulated concrete pore water in boom clay repository environments

NASA Astrophysics Data System (ADS)

MacDonald, D. D.; Saleh, A.; Lee, S. K.; Azizi, O.; Rosas-Camacho, O.; Al-Marzooqi, A.; Taylor, M.

2011-04-01

The prediction of corrosion damage of canisters to experimentally inaccessible times is vitally important in assessing various concepts for the disposal of High Level Nuclear Waste. Such prediction can only be made using deterministic models, whose predictions are constrained by the time-invariant natural laws. In this paper, we describe the measurement of experimental electrochemical data that will allow the prediction of damage to the carbon steel overpack of the super container in Belgium's proposed Boom Clay repository by using the Point Defect Model (PDM). PDM parameter values are obtained by optimizing the model on experimental, wide-band electrochemical impedance spectroscopy data.

ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.

PubMed

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J

2014-07-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.

The making of the minibody: an engineered beta-protein for the display of conformationally constrained peptides.

PubMed

Tramontano, A; Bianchi, E; Venturini, S; Martin, F; Pessi, A; Sollazzo, M

1994-03-01

Conformationally constraining selectable peptides onto a suitable scaffold that enables their conformation to be predicted or readily determined by experimental techniques would considerably boost the drug discovery process by reducing the gap between the discovery of a peptide lead and the design of a peptidomimetic with a more desirable pharmacological profile. With this in mind, we designed the minibody, a 61-residue beta-protein aimed at retaining some desirable features of immunoglobulin variable domains, such as tolerance to sequence variability in selected regions of the protein and predictability of the main chain conformation of the same regions, based on the 'canonical structures' model. To test the ability of the minibody scaffold to support functional sites we also designed a metal binding version of the protein by suitably choosing the sequences of its loops. The minibody was produced both by chemical synthesis and expression in E. coli and characterized by size exclusion chromatography, UV CD (circular dichroism) spectroscopy and metal binding activity. All our data supported the model, but a more detailed structural characterization of the molecule was impaired by its low solubility. We were able to overcome this problem both by further mutagenesis of the framework and by addition of a solubilizing motif. The minibody is being used to select constrained human IL-6 peptidic ligands from a library displayed on the surface of the f1 bacteriophage.

Constraining the interaction between dark sectors with future HI intensity mapping observations

NASA Astrophysics Data System (ADS)

Xu, Xiaodong; Ma, Yin-Zhe; Weltman, Amanda

2018-04-01

We study a model of interacting dark matter and dark energy, in which the two components are coupled. We calculate the predictions for the 21-cm intensity mapping power spectra, and forecast the detectability with future single-dish intensity mapping surveys (BINGO, FAST and SKA-I). Since dark energy is turned on at z ˜1 , which falls into the sensitivity range of these radio surveys, the HI intensity mapping technique is an efficient tool to constrain the interaction. By comparing with current constraints on dark sector interactions, we find that future radio surveys will produce tight and reliable constraints on the coupling parameters.

Structural and parameteric uncertainty quantification in cloud microphysics parameterization schemes

NASA Astrophysics Data System (ADS)

van Lier-Walqui, M.; Morrison, H.; Kumjian, M. R.; Prat, O. P.; Martinkus, C.

2017-12-01

Atmospheric model parameterization schemes employ approximations to represent the effects of unresolved processes. These approximations are a source of error in forecasts, caused in part by considerable uncertainty about the optimal value of parameters within each scheme -- parameteric uncertainty. Furthermore, there is uncertainty regarding the best choice of the overarching structure of the parameterization scheme -- structrual uncertainty. Parameter estimation can constrain the first, but may struggle with the second because structural choices are typically discrete. We address this problem in the context of cloud microphysics parameterization schemes by creating a flexible framework wherein structural and parametric uncertainties can be simultaneously constrained. Our scheme makes no assuptions about drop size distribution shape or the functional form of parametrized process rate terms. Instead, these uncertainties are constrained by observations using a Markov Chain Monte Carlo sampler within a Bayesian inference framework. Our scheme, the Bayesian Observationally-constrained Statistical-physical Scheme (BOSS), has flexibility to predict various sets of prognostic drop size distribution moments as well as varying complexity of process rate formulations. We compare idealized probabilistic forecasts from versions of BOSS with varying levels of structural complexity. This work has applications in ensemble forecasts with model physics uncertainty, data assimilation, and cloud microphysics process studies.

The highest-frequency kHz QPOs in neutron star low mass X-ray binaries

NASA Astrophysics Data System (ADS)

van Doesburgh, Marieke; van der Klis, Michiel; Morsink, Sharon M.

2018-05-01

We investigate the detections with RXTE of the highest-frequency kHz QPOs previously reported in six neutron star (NS) low mass X-ray binaries. We find that the highest-frequency kHz QPO detected in 4U 0614+09 has a 1267 Hz 3σ confidence lower limit on its centroid frequency. This is the highest such limit reported to date, and of direct physical interest as it can be used to constrain QPO models and the supranuclear density equation of state (EoS). We compare our measured frequencies to maximum orbital frequencies predicted in full GR using models of rotating neutron stars with a number of different modern EoS and show that these can accommodate the observed QPO frequencies. Orbital motion constrained by NS and ISCO radii is therefore a viable explanation of these QPOs. In the most constraining case of 4U 0614+09 we find the NS mass must be M<2.1 M⊙. From our measured QPO frequencies we can constrain the NS radii for five of the six sources we studied to narrow ranges (±0.1-0.7 km) different for each source and each EoS.

Parameter and prediction uncertainty in an optimized terrestrial carbon cycle model: Effects of constraining variables and data record length

NASA Astrophysics Data System (ADS)

Ricciuto, Daniel M.; King, Anthony W.; Dragoni, D.; Post, Wilfred M.

2011-03-01

Many parameters in terrestrial biogeochemical models are inherently uncertain, leading to uncertainty in predictions of key carbon cycle variables. At observation sites, this uncertainty can be quantified by applying model-data fusion techniques to estimate model parameters using eddy covariance observations and associated biometric data sets as constraints. Uncertainty is reduced as data records become longer and different types of observations are added. We estimate parametric and associated predictive uncertainty at the Morgan Monroe State Forest in Indiana, USA. Parameters in the Local Terrestrial Ecosystem Carbon (LoTEC) are estimated using both synthetic and actual constraints. These model parameters and uncertainties are then used to make predictions of carbon flux for up to 20 years. We find a strong dependence of both parametric and prediction uncertainty on the length of the data record used in the model-data fusion. In this model framework, this dependence is strongly reduced as the data record length increases beyond 5 years. If synthetic initial biomass pool constraints with realistic uncertainties are included in the model-data fusion, prediction uncertainty is reduced by more than 25% when constraining flux records are less than 3 years. If synthetic annual aboveground woody biomass increment constraints are also included, uncertainty is similarly reduced by an additional 25%. When actual observed eddy covariance data are used as constraints, there is still a strong dependence of parameter and prediction uncertainty on data record length, but the results are harder to interpret because of the inability of LoTEC to reproduce observed interannual variations and the confounding effects of model structural error.

Free vibrations of a plate with varying number of supports

NASA Technical Reports Server (NTRS)

Drake, J.; Kang, C. K.; Dowell, E. H.

1973-01-01

This experimental investigation tested the accuracy of an analysis which predicts the natural frequencies of vibration of a plate constrained by an arbitrary number of point supports along the edges, and also determined the number of such supports which approximates an infinite number.

The Lore of the Hair

NASA Astrophysics Data System (ADS)

Yunes, Nicolas; Yagi, Kent; Stein, Leo

2016-03-01

Stars can be hairy beasts, especially in theories that go beyond Einstein's. In the latter, a scalar field can be sourced and anchored to a neutron star, and if the later is in a binary system, the scalar field will emit dipole radiation. This radiation removes energy from the binary, forcing the orbit to adiabatically decay much more rapidly than due to the emission of gravitational waves as predicted in General Relativity. The detailed radio observation of binary pulsars has constrained the orbital decay of compact binaries stringently, so much so that theories that predict neutron stars with scalar hair are believed to be essentially ruled out. In this talk I will explain why this ``lore'' is actually incorrect, providing a counter-example in which scalar hair is sourced by neutron stars, yet dipole radiation is absent. I will then describe what binary systems need to be observed to constrain such theories with future astrophysical observations. I acknowledge support from NSF CAREER Grant PHY-1250636.

Climate change in fish: effects of respiratory constraints on optimal life history and behaviour.

PubMed

Holt, Rebecca E; Jørgensen, Christian

2015-02-01

The difference between maximum metabolic rate and standard metabolic rate is referred to as aerobic scope, and because it constrains performance it is suggested to constitute a key limiting process prescribing how fish may cope with or adapt to climate warming. We use an evolutionary bioenergetics model for Atlantic cod (Gadus morhua) to predict optimal life histories and behaviours at different temperatures. The model assumes common trade-offs and predicts that optimal temperatures for growth and fitness lie below that for aerobic scope; aerobic scope is thus a poor predictor of fitness at high temperatures. Initially, warming expands aerobic scope, allowing for faster growth and increased reproduction. Beyond the optimal temperature for fitness, increased metabolic requirements intensify foraging and reduce survival; oxygen budgeting conflicts thus constrain successful completion of the life cycle. The model illustrates how physiological adaptations are part of a suite of traits that have coevolved. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

Lexical mediation of phonotactic frequency effects on spoken word recognition: A Granger causality analysis of MRI-constrained MEG/EEG data.

PubMed

Gow, David W; Olson, Bruna B

2015-07-01

Phonotactic frequency effects play a crucial role in a number of debates over language processing and representation. It is unclear however, whether these effects reflect prelexical sensitivity to phonotactic frequency, or lexical "gang effects" in speech perception. In this paper, we use Granger causality analysis of MR-constrained MEG/EEG data to understand how phonotactic frequency influences neural processing dynamics during auditory lexical decision. Effective connectivity analysis showed weaker feedforward influence from brain regions involved in acoustic-phonetic processing (superior temporal gyrus) to lexical areas (supramarginal gyrus) for high phonotactic frequency words, but stronger top-down lexical influence for the same items. Low entropy nonwords (nonwords judged to closely resemble real words) showed a similar pattern of interactions between brain regions involved in lexical and acoustic-phonetic processing. These results contradict the predictions of a feedforward model of phonotactic frequency facilitation, but support the predictions of a lexically mediated account.

Lexical mediation of phonotactic frequency effects on spoken word recognition: A Granger causality analysis of MRI-constrained MEG/EEG data

PubMed Central

Gow, David W.; Olson, Bruna B.

2015-01-01

Phonotactic frequency effects play a crucial role in a number of debates over language processing and representation. It is unclear however, whether these effects reflect prelexical sensitivity to phonotactic frequency, or lexical “gang effects” in speech perception. In this paper, we use Granger causality analysis of MR-constrained MEG/EEG data to understand how phonotactic frequency influences neural processing dynamics during auditory lexical decision. Effective connectivity analysis showed weaker feedforward influence from brain regions involved in acoustic-phonetic processing (superior temporal gyrus) to lexical areas (supramarginal gyrus) for high phonotactic frequency words, but stronger top-down lexical influence for the same items. Low entropy nonwords (nonwords judged to closely resemble real words) showed a similar pattern of interactions between brain regions involved in lexical and acoustic-phonetic processing. These results contradict the predictions of a feedforward model of phonotactic frequency facilitation, but support the predictions of a lexically mediated account. PMID:25883413

Economic considerations for social distancing and behavioral based policies during an epidemic

PubMed Central

Fenichel, Eli P.

2013-01-01

Public policies intended to induce behavioral change, specifically incentives to reduce interpersonal contacts or to “social distance,” increasingly play a prominent role in public disease response strategies as governments plan for and respond to major epidemics. I compare social distancing incentives and outcomes under decentralized, full control social planner, and constrained social planner, without health class specific control, decision making scenarios. Constrained social planner decision making, based on non-health class specific controls, can in some instances make society worse off than decentralized decision making (i.e. no intervention). The oft neglected behavior of recovered and immune individuals is important for welfare and health outcomes. PMID:23419635

Processing Complex Sounds Passing through the Rostral Brainstem: The New Early Filter Model

PubMed Central

Marsh, John E.; Campbell, Tom A.

2016-01-01

The rostral brainstem receives both “bottom-up” input from the ascending auditory system and “top-down” descending corticofugal connections. Speech information passing through the inferior colliculus of elderly listeners reflects the periodicity envelope of a speech syllable. This information arguably also reflects a composite of temporal-fine-structure (TFS) information from the higher frequency vowel harmonics of that repeated syllable. The amplitude of those higher frequency harmonics, bearing even higher frequency TFS information, correlates positively with the word recognition ability of elderly listeners under reverberatory conditions. Also relevant is that working memory capacity (WMC), which is subject to age-related decline, constrains the processing of sounds at the level of the brainstem. Turning to the effects of a visually presented sensory or memory load on auditory processes, there is a load-dependent reduction of that processing, as manifest in the auditory brainstem responses (ABR) evoked by to-be-ignored clicks. Wave V decreases in amplitude with increases in the visually presented memory load. A visually presented sensory load also produces a load-dependent reduction of a slightly different sort: The sensory load of visually presented information limits the disruptive effects of background sound upon working memory performance. A new early filter model is thus advanced whereby systems within the frontal lobe (affected by sensory or memory load) cholinergically influence top-down corticofugal connections. Those corticofugal connections constrain the processing of complex sounds such as speech at the level of the brainstem. Selective attention thereby limits the distracting effects of background sound entering the higher auditory system via the inferior colliculus. Processing TFS in the brainstem relates to perception of speech under adverse conditions. Attentional selectivity is crucial when the signal heard is degraded or masked: e.g., speech in noise, speech in reverberatory environments. The assumptions of a new early filter model are consistent with these findings: A subcortical early filter, with a predictive selectivity based on acoustical (linguistic) context and foreknowledge, is under cholinergic top-down control. A prefrontal capacity limitation constrains this top-down control as is guided by the cholinergic processing of contextual information in working memory. PMID:27242396

Processing Complex Sounds Passing through the Rostral Brainstem: The New Early Filter Model.

PubMed

Marsh, John E; Campbell, Tom A

2016-01-01

The rostral brainstem receives both "bottom-up" input from the ascending auditory system and "top-down" descending corticofugal connections. Speech information passing through the inferior colliculus of elderly listeners reflects the periodicity envelope of a speech syllable. This information arguably also reflects a composite of temporal-fine-structure (TFS) information from the higher frequency vowel harmonics of that repeated syllable. The amplitude of those higher frequency harmonics, bearing even higher frequency TFS information, correlates positively with the word recognition ability of elderly listeners under reverberatory conditions. Also relevant is that working memory capacity (WMC), which is subject to age-related decline, constrains the processing of sounds at the level of the brainstem. Turning to the effects of a visually presented sensory or memory load on auditory processes, there is a load-dependent reduction of that processing, as manifest in the auditory brainstem responses (ABR) evoked by to-be-ignored clicks. Wave V decreases in amplitude with increases in the visually presented memory load. A visually presented sensory load also produces a load-dependent reduction of a slightly different sort: The sensory load of visually presented information limits the disruptive effects of background sound upon working memory performance. A new early filter model is thus advanced whereby systems within the frontal lobe (affected by sensory or memory load) cholinergically influence top-down corticofugal connections. Those corticofugal connections constrain the processing of complex sounds such as speech at the level of the brainstem. Selective attention thereby limits the distracting effects of background sound entering the higher auditory system via the inferior colliculus. Processing TFS in the brainstem relates to perception of speech under adverse conditions. Attentional selectivity is crucial when the signal heard is degraded or masked: e.g., speech in noise, speech in reverberatory environments. The assumptions of a new early filter model are consistent with these findings: A subcortical early filter, with a predictive selectivity based on acoustical (linguistic) context and foreknowledge, is under cholinergic top-down control. A prefrontal capacity limitation constrains this top-down control as is guided by the cholinergic processing of contextual information in working memory.

A greedy algorithm for species selection in dimension reduction of combustion chemistry

NASA Astrophysics Data System (ADS)

Hiremath, Varun; Ren, Zhuyin; Pope, Stephen B.

2010-09-01

Computational calculations of combustion problems involving large numbers of species and reactions with a detailed description of the chemistry can be very expensive. Numerous dimension reduction techniques have been developed in the past to reduce the computational cost. In this paper, we consider the rate controlled constrained-equilibrium (RCCE) dimension reduction method, in which a set of constrained species is specified. For a given number of constrained species, the 'optimal' set of constrained species is that which minimizes the dimension reduction error. The direct determination of the optimal set is computationally infeasible, and instead we present a greedy algorithm which aims at determining a 'good' set of constrained species; that is, one leading to near-minimal dimension reduction error. The partially-stirred reactor (PaSR) involving methane premixed combustion with chemistry described by the GRI-Mech 1.2 mechanism containing 31 species is used to test the algorithm. Results on dimension reduction errors for different sets of constrained species are presented to assess the effectiveness of the greedy algorithm. It is shown that the first four constrained species selected using the proposed greedy algorithm produce lower dimension reduction error than constraints on the major species: CH4, O2, CO2 and H2O. It is also shown that the first ten constrained species selected using the proposed greedy algorithm produce a non-increasing dimension reduction error with every additional constrained species; and produce the lowest dimension reduction error in many cases tested over a wide range of equivalence ratios, pressures and initial temperatures.

Evaluation of tropical Pacific observing systems using NCEP and GFDL ocean data assimilation systems

NASA Astrophysics Data System (ADS)

Xue, Yan; Wen, Caihong; Yang, Xiaosong; Behringer, David; Kumar, Arun; Vecchi, Gabriel; Rosati, Anthony; Gudgel, Rich

2017-08-01

The TAO/TRITON array is the cornerstone of the tropical Pacific and ENSO observing system. Motivated by the recent rapid decline of the TAO/TRITON array, the potential utility of TAO/TRITON was assessed for ENSO monitoring and prediction. The analysis focused on the period when observations from Argo floats were also available. We coordinated observing system experiments (OSEs) using the global ocean data assimilation system (GODAS) from the National Centers for Environmental Prediction and the ensemble coupled data assimilation (ECDA) from the Geophysical Fluid Dynamics Laboratory for the period 2004-2011. Four OSE simulations were conducted with inclusion of different subsets of in situ profiles: all profiles (XBT, moorings, Argo), all except the moorings, all except the Argo and no profiles. For evaluation of the OSE simulations, we examined the mean bias, standard deviation difference, root-mean-square difference (RMSD) and anomaly correlation against observations and objective analyses. Without assimilation of in situ observations, both GODAS and ECDA had large mean biases and RMSD in all variables. Assimilation of all in situ data significantly reduced mean biases and RMSD in all variables except zonal current at the equator. For GODAS, the mooring data is critical in constraining temperature in the eastern and northwestern tropical Pacific, while for ECDA both the mooring and Argo data is needed in constraining temperature in the western tropical Pacific. The Argo data is critical in constraining temperature in off-equatorial regions for both GODAS and ECDA. For constraining salinity, sea surface height and surface current analysis, the influence of Argo data was more pronounced. In addition, the salinity data from the TRITON buoys played an important role in constraining salinity in the western Pacific. GODAS was more sensitive to withholding Argo data in off-equatorial regions than ECDA because it relied on local observations to correct model biases and there were few XBT profiles in those regions. The results suggest that multiple ocean data assimilation systems should be used to assess sensitivity of ocean analyses to changes in the distribution of ocean observations to get more robust results that can guide the design of future tropical Pacific observing systems.

A Novel Approach for Adaptive Signal Processing

NASA Technical Reports Server (NTRS)

Chen, Ya-Chin; Juang, Jer-Nan

1998-01-01

Adaptive linear predictors have been used extensively in practice in a wide variety of forms. In the main, their theoretical development is based upon the assumption of stationarity of the signals involved, particularly with respect to the second order statistics. On this basis, the well-known normal equations can be formulated. If high- order statistical stationarity is assumed, then the equivalent normal equations involve high-order signal moments. In either case, the cross moments (second or higher) are needed. This renders the adaptive prediction procedure non-blind. A novel procedure for blind adaptive prediction has been proposed and considerable implementation has been made in our contributions in the past year. The approach is based upon a suitable interpretation of blind equalization methods that satisfy the constant modulus property and offers significant deviations from the standard prediction methods. These blind adaptive algorithms are derived by formulating Lagrange equivalents from mechanisms of constrained optimization. In this report, other new update algorithms are derived from the fundamental concepts of advanced system identification to carry out the proposed blind adaptive prediction. The results of the work can be extended to a number of control-related problems, such as disturbance identification. The basic principles are outlined in this report and differences from other existing methods are discussed. The applications implemented are speech processing, such as coding and synthesis. Simulations are included to verify the novel modelling method.

Prediction and Measurement of the Vibration and Acoustic Radiation of Panels Subjected to Acoustic Loading

NASA Technical Reports Server (NTRS)

Turner, Travis L.; Rizzi, Stephen A.

1995-01-01

Interior noise and sonic fatigue are important issues in the development and design of advanced subsonic and supersonic aircraft. Conventional aircraft typically employ passive treatments, such as constrained layer damping and acoustic absorption materials, to reduce the structural response and resulting acoustic levels in the aircraft interior. These techniques require significant addition of mass and only attenuate relatively high frequency noise transmitted through the fuselage. Although structural acoustic coupling is in general very important in the study of aircraft fuselage interior noise, analysis of noise transmission through a panel supported in an infinite rigid baffle (separating two semi-infinite acoustic domains) can be useful in evaluating the effects of active/adaptive materials, complex loading, etc. Recent work has been aimed at developing adaptive and/or active methods of controlling the structural acoustic response of panels to reduce the transmitted noise1. A finite element formulation was recently developed to study the dynamic response of shape memory alloy (SMA) hybrid composite panels (conventional composite panel with embedded SMA fibers) subject to combined acoustic and thermal loads2. Further analysis has been performed to predict the far-field acoustic radiation using the finite element dynamic panel response prediction3. The purpose of the present work is to validate the panel vibration and acoustic radiation prediction methods with baseline experimental results obtained from an isotropic panel, without the effect of SMA.

A multidimensional stability model for predicting shallow landslide size and shape across landscapes.

PubMed

Milledge, David G; Bellugi, Dino; McKean, Jim A; Densmore, Alexander L; Dietrich, William E

2014-11-01

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size-frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data.

A multidimensional stability model for predicting shallow landslide size and shape across landscapes

PubMed Central

Milledge, David G; Bellugi, Dino; McKean, Jim A; Densmore, Alexander L; Dietrich, William E

2014-01-01

The size of a shallow landslide is a fundamental control on both its hazard and geomorphic importance. Existing models are either unable to predict landslide size or are computationally intensive such that they cannot practically be applied across landscapes. We derive a model appropriate for natural slopes that is capable of predicting shallow landslide size but simple enough to be applied over entire watersheds. It accounts for lateral resistance by representing the forces acting on each margin of potential landslides using earth pressure theory and by representing root reinforcement as an exponential function of soil depth. We test our model's ability to predict failure of an observed landslide where the relevant parameters are well constrained by field data. The model predicts failure for the observed scar geometry and finds that larger or smaller conformal shapes are more stable. Numerical experiments demonstrate that friction on the boundaries of a potential landslide increases considerably the magnitude of lateral reinforcement, relative to that due to root cohesion alone. We find that there is a critical depth in both cohesive and cohesionless soils, resulting in a minimum size for failure, which is consistent with observed size-frequency distributions. Furthermore, the differential resistance on the boundaries of a potential landslide is responsible for a critical landslide shape which is longer than it is wide, consistent with observed aspect ratios. Finally, our results show that minimum size increases as approximately the square of failure surface depth, consistent with observed landslide depth-area data. PMID:26213663

Technologies for Developing Predictive Atomistic and Coarse-Grained Force Fields for Ionic Liquid Property Prediction

DTIC Science & Technology

2008-07-29

studied are set to zero and a constrained MM minimization is performed. It is critical that all other force field parameters (for bonds, angles, charges...identifying the symmetry of the problem and tailoring the parameterization accordingly may be critical . For Phase I, the above described procedure was...tasks and the evaluation of their properties. The tremendous number of possible ionic liquids that are within reach makes it critical that a reliable

STICK-SLIP-SEPARATION Analysis and Non-Linear Stiffness and Damping Characterization of Friction Contacts Having Variable Normal Load

NASA Astrophysics Data System (ADS)

Yang, B. D.; Chu, M. L.; Menq, C. H.

1998-03-01

Mechanical systems in which moving components are mutually constrained through contacts often lead to complex contact kinematics involving tangential and normal relative motions. A friction contact model is proposed to characterize this type of contact kinematics that imposes both friction non-linearity and intermittent separation non-linearity on the system. The stick-slip friction phenomenon is analyzed by establishing analytical criteria that predict the transition between stick, slip, and separation of the interface. The established analytical transition criteria are particularly important to the proposed friction contact model for the transition conditions of the contact kinematics are complicated by the effect of normal load variation and possible interface separation. With these transition criteria, the induced friction force on the contact plane and the variable normal load perpendicular to the contact plane, can be predicted for any given cyclic relative motions at the contact interface and hysteresis loops can be produced so as to characterize the equivalent damping and stiffness of the friction contact. These-non-linear damping and stiffness methods along with the harmonic balance method are then used to predict the resonant response of a frictionally constrained two-degree-of-freedom oscillator. The predicted results are compared with those of the time integration method and the damping effect, the resonant frequency shift, and the jump phenomenon are examined.

Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

NASA Astrophysics Data System (ADS)

Spivey, Benjamin James

2011-07-01

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

Model Wind Turbines Tested at Full-Scale Similarity

NASA Astrophysics Data System (ADS)

Miller, M. A.; Kiefer, J.; Westergaard, C.; Hultmark, M.

2016-09-01

The enormous length scales associated with modern wind turbines complicate any efforts to predict their mechanical loads and performance. Both experiments and numerical simulations are constrained by the large Reynolds numbers governing the full- scale aerodynamics. The limited fundamental understanding of Reynolds number effects in combination with the lack of empirical data affects our ability to predict, model, and design improved turbines and wind farms. A new experimental approach is presented, which utilizes a highly pressurized wind tunnel (up to 220 bar). It allows exact matching of the Reynolds numbers (no matter how it is defined), tip speed ratios, and Mach numbers on a geometrically similar, small-scale model. The design of a measurement and instrumentation stack to control the turbine and measure the loads in the pressurized environment is discussed. Results are then presented in the form of power coefficients as a function of Reynolds number and Tip Speed Ratio. Due to gearbox power loss, a preliminary study has also been completed to find the gearbox efficiency and the resulting correction has been applied to the data set.

Tiltrotor noise reduction through flight trajectory management and aircraft configuration control

NASA Astrophysics Data System (ADS)

Gervais, Marc

A tiltrotor can hover, takeoff and land vertically as well as cruise at high speeds and fly long distances. Because of these unique capabilities, tiltrotors are envisioned as an aircraft that could provide a solution to the issue of airport gridlock by operating on stub runways, helipads, or from smaller regional airports. However, during an approach-to-land a tiltrotor is susceptible to radiating strong impulsive noise, in particular, Blade-Vortex Interaction noise (BVI), a phenomenon highly dependent on the vehicle's performance-state. A mathematical model was developed to predict the quasi-static performance characteristics of a tiltrotor during a converting approach in the longitudinal plane. Additionally, a neural network was designed to model the acoustic results from a flight test of the XV-15 tiltrotor as a function of the aircraft's performance parameters. The performance model was linked to the neural network to yield a combined performance/acoustic model that is capable of predicting tiltrotor noise emitted during a decelerating approach. The model was then used to study noise trends associated with different combinations of airspeed, nacelle tilt, and flight path angle. It showed that BVI noise is the dominant noise source during a descent and that its strength increases with steeper descent angles. Strong BVI noise was observed at very steep flight path angles, suggesting that the tiltrotor's high downwash prevents the wake from being pushed above the rotor, even at such steep descent angles. The model was used to study the effects of various aircraft configuration and flight trajectory parameters on the rotor inflow, which adequately captured the measured BVI noise trends. Flight path management effectively constrained the rotor inflow during a converting approach and thus limited the strength of BVI noise. The maximum deceleration was also constrained by controlling the nacelle tilt-rate during conversion. By applying these constraints, low BVI noise approaches that take into account the first-order effects of deceleration on the acoustics were systematically designed and compared to a baseline approach profile. The low-noise approaches yielded substantial noise reduction benefits on a hemisphere surrounding the aircraft and on a ground plane below the aircraft's trajectory.

Effectiveness of conservation easements in agricultural regions.

PubMed

Braza, Mark

2017-08-01

Conservation easements are a standard technique for preventing habitat loss, particularly in agricultural regions with extensive cropland cultivation, yet little is known about their effectiveness. I developed a spatial econometric approach to propensity-score matching and used the approach to estimate the amount of habitat loss prevented by a grassland conservation easement program of the U.S. federal government. I used a spatial autoregressive probit model to predict tract enrollment in the easement program as of 2001 based on tract agricultural suitability, habitat quality, and spatial interactions among neighboring tracts. Using the predicted values from the model, I matched enrolled tracts with similar unenrolled tracts to form a treatment group and a control group. To measure the program's impact on subsequent grassland loss, I estimated cropland cultivation rates for both groups in 2014 with a second spatial probit model. Between 2001 and 2014, approximately 14.9% of control tracts were cultivated and 0.3% of treated tracts were cultivated. Therefore, approximately 14.6% of the protected land would have been cultivated in the absence of the program. My results demonstrate that conservation easements can significantly reduce habitat loss in agricultural regions; however, the enrollment of tracts with low cropland suitability may constrain the amount of habitat loss they prevent. My results also show that spatial econometric models can improve the validity of control groups and thereby strengthen causal inferences about program effectiveness in situations when spatial interactions influence conservation decisions. © 2017 Society for Conservation Biology.

Trajectory Design Strategies for the NGST L2 Libration Point Mission

NASA Technical Reports Server (NTRS)

Folta, David; Cooley, Steven; Howell, Kathleen; Bauer, Frank H.

2001-01-01

The Origins' Next Generation Space Telescope (NGST) trajectory design is addressed in light of improved methods for attaining constrained orbit parameters and their control at the exterior collinear libration point, L2. The use of a dynamical systems approach, state-space equations for initial libration orbit control, and optimization to achieve constrained orbit parameters are emphasized. The NGST trajectory design encompasses a direct transfer and orbit maintenance under a constant acceleration. A dynamical systems approach can be used to provide a biased orbit and stationkeeping maintenance method that incorporates the constraint of a single axis correction scheme.

Geomorphically based predictive mapping of soil thickness in upland watersheds

NASA Astrophysics Data System (ADS)

Pelletier, Jon D.; Rasmussen, Craig

2009-09-01

The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ˜0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.

Linear and Logarithmic Speed-Accuracy Trade-Offs in Reciprocal Aiming Result from Task-Specific Parameterization of an Invariant Underlying Dynamics

ERIC Educational Resources Information Center

Bongers, Raoul M.; Fernandez, Laure; Bootsma, Reinoud J.

2009-01-01

The authors examined the origins of linear and logarithmic speed-accuracy trade-offs from a dynamic systems perspective on motor control. In each experiment, participants performed 2 reciprocal aiming tasks: (a) a velocity-constrained task in which movement time was imposed and accuracy had to be maximized, and (b) a distance-constrained task in…

Development of an eddy-resolving reanalysis using the 1/12° global HYbrid Coordinate Ocean Model and the Navy Coupled Ocean Data Assimilation Scheme

NASA Astrophysics Data System (ADS)

Allard, Richard; Metzger, E. Joseph; Broome, Robert; Franklin, Deborah; Smedstad, Ole Martin; Wallcraft, Alan

2013-04-01

Multiple international agencies have performed atmospheric reanalyses using static dynamical models and assimilation schemes while ingesting all available quality controlled observational data. Some are clearly aimed at climate time scales while others focus on the more recent time period in which assimilated satellite data are used to constrain the system. Typically these are performed at horizontal and vertical resolutions that are coarser than the existing operational atmospheric prediction system. Multiple agencies have also performed ocean reanalyses using some of the atmospheric forcing products described above. However, only a few are eddy-permitting and none are capable of resolving oceanic mesoscale features (eddies and current meanders) across the entire globe. To fill this void, the Naval Research Laboratory is performing an eddy-resolving 1993-2010 ocean reanalysis using the 1/12° global HYbrid Coordinate Ocean Model (HYCOM) that employs the Navy Coupled Ocean Data Assimilation (NCODA) scheme. A 1/12° global HYCOM/NCODA prediction system has been running in real-time at the Naval Oceanographic Office (NAVOCEANO) since 22 December 2006. It has undergone operational testing and will become an operational product by early 2013. It is capable of nowcasting and forecasting the oceanic "weather" which includes the 3D ocean temperature, salinity and current structure, the surface mixed layer, and the location of mesoscale features such as eddies, meandering currents and fronts. The system has a mid-latitude resolution of ~7 km and employs 32 hybrid vertical coordinate surfaces. Compared to traditional isopycnal coordinate models, the hybrid vertical coordinate extends the geographic range of applicability toward shallow coastal seas and the unstratified parts of the world ocean. HYCOM contains a built-in thermodynamic ice model, where ice grows and melts due to heat flux and sea surface temperature (SST) changes, but it does not contain advanced rheological physics. The ice edge is constrained by satellite ice concentration. Once per day, NCODA performs a 3D ocean analysis using all available observational data and the 1-day HYCOM forecast as the first guess in a sequential incremental update cycle. Observational data include surface observations from satellites, including sea surface height (SSH) anomalies, SST, and sea ice concentrations, plus in-situ SST observations from ships and buoys as well as temperature and salinity profiles from XBTs, CTDs and Argo profiling floats. Surface information is projected downward using synthetic profiles from the Modular Ocean Data Assimilation System (MODAS) at those locations with a predefined SSH anomaly. Unlike previous reanalyses, this ocean reanalysis will be integrated at the same horizontal and vertical resolution as the operational system running at NAVOCEANO. The system is forced with atmospheric output from the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) and the observations listed above. The reanalysis began in 1993 because of the advent of satellite altimeter data that will constrain the oceanic mesoscale. Significant effort has been put into obtaining and quality controlling all input observational data, with special emphasis on the profile data. The computational resources are obtained through the High Performance Computing Modernization Office.

Adjoint-Based Sensitivity and Uncertainty Analysis for Density and Composition: A User’s Guide

DOE PAGES

Favorite, Jeffrey A.; Perko, Zoltan; Kiedrowski, Brian C.; ...

2017-03-01

The ability to perform sensitivity analyses using adjoint-based first-order sensitivity theory has existed for decades. This paper provides guidance on how adjoint sensitivity methods can be used to predict the effect of material density and composition uncertainties in critical experiments, including when these uncertain parameters are correlated or constrained. Two widely used Monte Carlo codes, MCNP6 (Ref. 2) and SCALE 6.2 (Ref. 3), are both capable of computing isotopic density sensitivities in continuous energy and angle. Additionally, Perkó et al. have shown how individual isotope density sensitivities, easily computed using adjoint methods, can be combined to compute constrained first-order sensitivitiesmore » that may be used in the uncertainty analysis. This paper provides details on how the codes are used to compute first-order sensitivities and how the sensitivities are used in an uncertainty analysis. Constrained first-order sensitivities are computed in a simple example problem.« less

Global circulation as the main source of cloud activity on Titan

USGS Publications Warehouse

Rodriguez, S.; Le, Mouelic S.; Rannou, P.; Tobie, G.; Baines, K.H.; Barnes, J.W.; Griffith, C.A.; Hirtzig, M.; Pitman, K.M.; Sotin, Christophe; Brown, R.H.; Buratti, B.J.; Clark, R.N.; Nicholson, P.D.

2009-01-01

Clouds on Titan result from the condensation of methane and ethane and, as on other planets, are primarily structured by circulation of the atmosphere. At present, cloud activity mainly occurs in the southern (summer) hemisphere, arising near the pole and at mid-latitudes from cumulus updrafts triggered by surface heating and/or local methane sources, and at the north (winter) pole, resulting from the subsidence and condensation of ethane-rich air into the colder troposphere. General circulation models predict that this distribution should change with the seasons on a 15-year timescale, and that clouds should develop under certain circumstances at temperate latitudes (40??) in the winter hemisphere. The models, however, have hitherto been poorly constrained and their long-term predictions have not yet been observationally verified. Here we report that the global spatial cloud coverage on Titan is in general agreement with the models, confirming that cloud activity is mainly controlled by the global circulation. The non-detection of clouds at latitude 40??N and the persistence of the southern clouds while the southern summer is ending are, however, both contrary to predictions. This suggests that Titans equator-to-pole thermal contrast is overestimated in the models and that its atmosphere responds to the seasonal forcing with a greater inertia than expected. ?? 2009 Macmillan Publishers Limited. All rights reserved.

Digestive capacity predicts diet diversity in Neotropical frugivorous bats.

PubMed

Saldaña-Vázquez, Romeo A; Ruiz-Sanchez, Eduardo; Herrera-Alsina, Leonel; Schondube, Jorge E

2015-09-01

1. Predicting the diet diversity of animals is important to basic and applied ecology. Knowledge of diet diversity in animals helps us understand niche partitioning, functional diversity and ecosystem services such as pollination, pest control and seed dispersal. 2. There is a negative relationship between the length of the digestive tract and diet diversity in animals; however, the role of digestive physiology in determining diet diversity has been ignored. This is especially important in vertebrates with powered flight because, unlike non-flying vertebrates, they have limitations that may constrain gut size. 3. Here, we evaluate the relationship between digestive capacity and diet diversity in Carollinae and Stenodermatinae frugivorous bats. These bats disperse the seeds of plants that are key to Neotropical forest regeneration. 4. Our results show that digestive capacity is a good predictor of diet diversity in Carollinae and Stenodermatinae frugivorous bats (R(2) = 0·77). 5. Surprisingly, the most phylogenetically closely related species were not similar in their digestive capacity or diet diversity. The lack of a phylogenetic signal for the traits evaluated implies differences in digestive physiology and diet in closely related species. 6. Our results highlight the predictive usefulness of digestive physiology for understanding the feeding ecology of animals. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.

Making Predictions about Chemical Reactivity: Assumptions and Heuristics

ERIC Educational Resources Information Center

Maeyer, Jenine; Talanquer, Vicente

2013-01-01

Diverse implicit cognitive elements seem to support but also constrain reasoning in different domains. Many of these cognitive constraints can be thought of as either implicit assumptions about the nature of things or reasoning heuristics for decision-making. In this study we applied this framework to investigate college students' understanding of…

Prediction of cheatgrass field germination potential using wet thermal accumulation

Treesearch

Bruce A. Roundy; Stuart P. Hardegree; Jeane C. Chambers; Alison Whittaker

2007-01-01

Invasion and dominance of weedy species is facilitated or constrained by environmental and ecological factors that affect resource availability during critical life stages. We compared the relative effects of season, annual weather, site, and disturbance on potential cheatgrass (Bromus tectorum L.) germination in big sagebrush (Artemisia...

Improving SWAT model prediction using an upgraded denitrification scheme and constrained auto calibration

USDA-ARS?s Scientific Manuscript database

The reliability of common calibration practices for process based water quality models has recently been questioned. A so-called “adequately calibrated model” may contain input errors not readily identifiable by model users, or may not realistically represent intra-watershed responses. These short...

ODE Constrained Mixture Modelling: A Method for Unraveling Subpopulation Structures and Dynamics

PubMed Central

Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J.

2014-01-01

Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity. PMID:24992156

Predictions of vertical uplift caused by changing polar ice volumes on a viscoelastic earth

NASA Technical Reports Server (NTRS)

Wahr, John; Dazhong, Han; Trupin, Andrew

1995-01-01

Measurements of crustal uplift from bedrock around the edges of Antarctica or Greenland could help constrain the mass balance of those ice caps. Present-day changes in ice could cause vertical displacement rates of several mm/yr around Antarctica and up to 10-15 mm/yr around Greenland. Horizontal displacement rates are likely to be about 1/3 the vertical rates. The viscoelastic response of the earth to past changes in ice could cause uplift rates that are several times larger. By measuring both gravity and vertical displacements, it is possible to remove the viscoelastic effects, so that the observations can be used to constrain present-day thickness changes.

Robust fuzzy control subject to state variance and passivity constraints for perturbed nonlinear systems with multiplicative noises.

PubMed

Chang, Wen-Jer; Huang, Bo-Jyun

2014-11-01

The multi-constrained robust fuzzy control problem is investigated in this paper for perturbed continuous-time nonlinear stochastic systems. The nonlinear system considered in this paper is represented by a Takagi-Sugeno fuzzy model with perturbations and state multiplicative noises. The multiple performance constraints considered in this paper include stability, passivity and individual state variance constraints. The Lyapunov stability theory is employed to derive sufficient conditions to achieve the above performance constraints. By solving these sufficient conditions, the contribution of this paper is to develop a parallel distributed compensation based robust fuzzy control approach to satisfy multiple performance constraints for perturbed nonlinear systems with multiplicative noises. At last, a numerical example for the control of perturbed inverted pendulum system is provided to illustrate the applicability and effectiveness of the proposed multi-constrained robust fuzzy control method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

PI controller design of a wind turbine: evaluation of the pole-placement method and tuning using constrained optimization

NASA Astrophysics Data System (ADS)

Mirzaei, Mahmood; Tibaldi, Carlo; Hansen, Morten H.

2016-09-01

PI/PID controllers are the most common wind turbine controllers. Normally a first tuning is obtained using methods such as pole-placement or Ziegler-Nichols and then extensive aeroelastic simulations are used to obtain the best tuning in terms of regulation of the outputs and reduction of the loads. In the traditional tuning approaches, the properties of different open loop and closed loop transfer functions of the system are not normally considered. In this paper, an assessment of the pole-placement tuning method is presented based on robustness measures. Then a constrained optimization setup is suggested to automatically tune the wind turbine controller subject to robustness constraints. The properties of the system such as the maximum sensitivity and complementary sensitivity functions (Ms and Mt ), along with some of the responses of the system, are used to investigate the controller performance and formulate the optimization problem. The cost function is the integral absolute error (IAE) of the rotational speed from a disturbance modeled as a step in wind speed. Linearized model of the DTU 10-MW reference wind turbine is obtained using HAWCStab2. Thereafter, the model is reduced with model order reduction. The trade-off curves are given to assess the tunings of the poles- placement method and a constrained optimization problem is solved to find the best tuning.

Predicting Great Lakes fish yields: tools and constraints

USGS Publications Warehouse

Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

1987-01-01

Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

Kinetics of heavy metal adsorption and desorption in soil: Developing a unified model based on chemical speciation

NASA Astrophysics Data System (ADS)

Peng, Lanfang; Liu, Paiyu; Feng, Xionghan; Wang, Zimeng; Cheng, Tao; Liang, Yuzhen; Lin, Zhang; Shi, Zhenqing

2018-03-01

Predicting the kinetics of heavy metal adsorption and desorption in soil requires consideration of multiple heterogeneous soil binding sites and variations of reaction chemistry conditions. Although chemical speciation models have been developed for predicting the equilibrium of metal adsorption on soil organic matter (SOM) and important mineral phases (e.g. Fe and Al (hydr)oxides), there is still a lack of modeling tools for predicting the kinetics of metal adsorption and desorption reactions in soil. In this study, we developed a unified model for the kinetics of heavy metal adsorption and desorption in soil based on the equilibrium models WHAM 7 and CD-MUSIC, which specifically consider metal kinetic reactions with multiple binding sites of SOM and soil minerals simultaneously. For each specific binding site, metal adsorption and desorption rate coefficients were constrained by the local equilibrium partition coefficients predicted by WHAM 7 or CD-MUSIC, and, for each metal, the desorption rate coefficients of various binding sites were constrained by their metal binding constants with those sites. The model had only one fitting parameter for each soil binding phase, and all other parameters were derived from WHAM 7 and CD-MUSIC. A stirred-flow method was used to study the kinetics of Cd, Cu, Ni, Pb, and Zn adsorption and desorption in multiple soils under various pH and metal concentrations, and the model successfully reproduced most of the kinetic data. We quantitatively elucidated the significance of different soil components and important soil binding sites during the adsorption and desorption kinetic processes. Our model has provided a theoretical framework to predict metal adsorption and desorption kinetics, which can be further used to predict the dynamic behavior of heavy metals in soil under various natural conditions by coupling other important soil processes.

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks

PubMed Central

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S.

2017-01-01

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a=(u,v) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages. PMID:28771201

Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks.

PubMed

Zhu, Junxing; Zhang, Jiawei; Wu, Quanyuan; Jia, Yan; Zhou, Bin; Wei, Xiaokai; Yu, Philip S

2017-08-03

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a = ( u , v ) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.

Optimal Power Flow for Distribution Systems under Uncertain Forecasts: Preprint

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

Dall'Anese, Emiliano; Baker, Kyri; Summers, Tyler

2016-12-01

The paper focuses on distribution systems featuring renewable energy sources and energy storage devices, and develops an optimal power flow (OPF) approach to optimize the system operation in spite of forecasting errors. The proposed method builds on a chance-constrained multi-period AC OPF formulation, where probabilistic constraints are utilized to enforce voltage regulation with a prescribed probability. To enable a computationally affordable solution approach, a convex reformulation of the OPF task is obtained by resorting to i) pertinent linear approximations of the power flow equations, and ii) convex approximations of the chance constraints. Particularly, the approximate chance constraints provide conservative boundsmore » that hold for arbitrary distributions of the forecasting errors. An adaptive optimization strategy is then obtained by embedding the proposed OPF task into a model predictive control framework.« less

Hyperpolarizability and Operational Magic Wavelength in an Optical Lattice Clock

NASA Astrophysics Data System (ADS)

Brown, R. C.; Phillips, N. B.; Beloy, K.; McGrew, W. F.; Schioppo, M.; Fasano, R. J.; Milani, G.; Zhang, X.; Hinkley, N.; Leopardi, H.; Yoon, T. H.; Nicolodi, D.; Fortier, T. M.; Ludlow, A. D.

2017-12-01

Optical clocks benefit from tight atomic confinement enabling extended interrogation times as well as Doppler- and recoil-free operation. However, these benefits come at the cost of frequency shifts that, if not properly controlled, may degrade clock accuracy. Numerous theoretical studies have predicted optical lattice clock frequency shifts that scale nonlinearly with trap depth. To experimentally observe and constrain these shifts in an 171Yb optical lattice clock, we construct a lattice enhancement cavity that exaggerates the light shifts. We observe an atomic temperature that is proportional to the optical trap depth, fundamentally altering the scaling of trap-induced light shifts and simplifying their parametrization. We identify an "operational" magic wavelength where frequency shifts are insensitive to changes in trap depth. These measurements and scaling analysis constitute an essential systematic characterization for clock operation at the 10-18 level and beyond.

Exploring constrained quantum control landscapes

NASA Astrophysics Data System (ADS)

Moore, Katharine W.; Rabitz, Herschel

2012-10-01

The broad success of optimally controlling quantum systems with external fields has been attributed to the favorable topology of the underlying control landscape, where the landscape is the physical observable as a function of the controls. The control landscape can be shown to contain no suboptimal trapping extrema upon satisfaction of reasonable physical assumptions, but this topological analysis does not hold when significant constraints are placed on the control resources. This work employs simulations to explore the topology and features of the control landscape for pure-state population transfer with a constrained class of control fields. The fields are parameterized in terms of a set of uniformly spaced spectral frequencies, with the associated phases acting as the controls. This restricted family of fields provides a simple illustration for assessing the impact of constraints upon seeking optimal control. Optimization results reveal that the minimum number of phase controls necessary to assure a high yield in the target state has a special dependence on the number of accessible energy levels in the quantum system, revealed from an analysis of the first- and second-order variation of the yield with respect to the controls. When an insufficient number of controls and/or a weak control fluence are employed, trapping extrema and saddle points are observed on the landscape. When the control resources are sufficiently flexible, solutions producing the globally maximal yield are found to form connected "level sets" of continuously variable control fields that preserve the yield. These optimal yield level sets are found to shrink to isolated points on the top of the landscape as the control field fluence is decreased, and further reduction of the fluence turns these points into suboptimal trapping extrema on the landscape. Although constrained control fields can come in many forms beyond the cases explored here, the behavior found in this paper is illustrative of the impacts that constraints can introduce.

Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

PubMed

Heydari, Ali; Balakrishnan, Sivasubramanya N

2013-01-01

To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.

Constrains on the South Atlantic Anomaly from Réunion Island

NASA Astrophysics Data System (ADS)

Béguin, A.; de Groot, L. V.

2017-12-01

The South Atlantic Anomaly (SAA) is a region where the geomagnetic field intensity is about half as strong as would be expected from the current geomagnetic dipole moment that arises from geomagnetic field models. Those field models predict a westward movement of the SAA and predicts its origin East of Africa around 1500 AD. The onset and evolution of the SAA, however, are poorly constrained due to a lack of full-vector paleomagnetic data from Africa and the Indian Ocean for the past centuries. Here we present a full-vector paleosecular variation (PSV) curve for Réunion Island (21°S, 55°E) located East the African continent, in the region that currently shows the fastest increase in geomagnetic field strength in contrast to the average global decay. We sampled 27 sites covering the last 700 years, and subjected them to a directional and multi-method paleointensity study. The obtained directional records reveal shallower inclinations and less variation in the declination compared to current geomagnetic field model predictions. Scrutinizing the IZZI-Thellier, Multispecimen, and calibrated pseudo-Thellier results produces a coherent paleointensity record. The predicted intensity trend from the geomagnetic field models generally agrees with the trend in our data, however, the high paleointensities are higher than the models predict, and the low paleointensities are lower than the models. This illustrates the inevitable smoothing inherent to geomagnetic field modelling. We will discuss the constraints on the onset of the SAA that arise from the new full-vector PSV curve for Réunion that we present and the implications for the past and future evolution of this geomagnetic phenomenon.

Predicting structures in the Zone of Avoidance

NASA Astrophysics Data System (ADS)

Sorce, Jenny G.; Colless, Matthew; Kraan-Korteweg, Renée C.; Gottlöber, Stefan

2017-11-01

The Zone of Avoidance (ZOA), whose emptiness is an artefact of our Galaxy dust, has been challenging observers as well as theorists for many years. Multiple attempts have been made on the observational side to map this region in order to better understand the local flows. On the theoretical side, however, this region is often simply statistically populated with structures but no real attempt has been made to confront theoretical and observed matter distributions. This paper takes a step forward using constrained realizations (CRs) of the local Universe shown to be perfect substitutes of local Universe-like simulations for smoothed high-density peak studies. Far from generating completely `random' structures in the ZOA, the reconstruction technique arranges matter according to the surrounding environment of this region. More precisely, the mean distributions of structures in a series of constrained and random realizations (RRs) differ: while densities annihilate each other when averaging over 200 RRs, structures persist when summing 200 CRs. The probability distribution function of ZOA grid cells to be highly overdense is a Gaussian with a 15 per cent mean in the random case, while that of the constrained case exhibits large tails. This implies that areas with the largest probabilities host most likely a structure. Comparisons between these predictions and observations, like those of the Puppis 3 cluster, show a remarkable agreement and allow us to assert the presence of the, recently highlighted by observations, Vela supercluster at about 180 h-1 Mpc, right behind the thickest dust layers of our Galaxy.

Alpha Oscillations during Incidental Encoding Predict Subsequent Memory for New "Foil" Information.

PubMed

Vogelsang, David A; Gruber, Matthias; Bergström, Zara M; Ranganath, Charan; Simons, Jon S

2018-05-01

People can employ adaptive strategies to increase the likelihood that previously encoded information will be successfully retrieved. One such strategy is to constrain retrieval toward relevant information by reimplementing the neurocognitive processes that were engaged during encoding. Using EEG, we examined the temporal dynamics with which constraining retrieval toward semantic versus nonsemantic information affects the processing of new "foil" information encountered during a memory test. Time-frequency analysis of EEG data acquired during an initial study phase revealed that semantic compared with nonsemantic processing was associated with alpha decreases in a left frontal electrode cluster from around 600 msec after stimulus onset. Successful encoding of semantic versus nonsemantic foils during a subsequent memory test was related to decreases in alpha oscillatory activity in the same left frontal electrode cluster, which emerged relatively late in the trial at around 1000-1600 msec after stimulus onset. Across participants, left frontal alpha power elicited by semantic processing during the study phase correlated significantly with left frontal alpha power associated with semantic foil encoding during the memory test. Furthermore, larger left frontal alpha power decreases elicited by semantic foil encoding during the memory test predicted better subsequent semantic foil recognition in an additional surprise foil memory test, although this effect did not reach significance. These findings indicate that constraining retrieval toward semantic information involves reimplementing semantic encoding operations that are mediated by alpha oscillations and that such reimplementation occurs at a late stage of memory retrieval, perhaps reflecting additional monitoring processes.

Integrative application of active controls (IAAC) technology to an advanced subsonic transport project. Initial act configuration design study

NASA Technical Reports Server (NTRS)

1980-01-01

The performance and economic benefits of a constrained application of Active Controls Technology (ACT) are identified, and the approach to airplane design is established for subsequent steps leading to the development of a less constrained final ACT configuration. The active controls configurations are measured against a conventional baseline configuration, a state-of-the-art transport, to determine whether the performance and economic changes resulting from ACT merit proceeding with the project. The technology established by the conventional baseline configuration was held constant except for the addition of ACT. The wing, with the same planform, was moved forward on the initial ACT configuration to move the loading range aft relative to the wing mean aerodynamic chord. Wing trailing-edge surfaces and surface controls also were reconfigured for load alleviation and structural stabilization.

A predictive parameter estimation approach for the thermodynamically constrained averaging theory applied to diffusion in porous media

NASA Astrophysics Data System (ADS)

Valdes-Parada, F. J.; Ostvar, S.; Wood, B. D.; Miller, C. T.

2017-12-01

Modeling of hierarchical systems such as porous media can be performed by different approaches that bridge microscale physics to the macroscale. Among the several alternatives available in the literature, the thermodynamically constrained averaging theory (TCAT) has emerged as a robust modeling approach that provides macroscale models that are consistent across scales. For specific closure relation forms, TCAT models are expressed in terms of parameters that depend upon the physical system under study. These parameters are usually obtained from inverse modeling based upon either experimental data or direct numerical simulation at the pore scale. Other upscaling approaches, such as the method of volume averaging, involve an a priori scheme for parameter estimation for certain microscale and transport conditions. In this work, we show how such a predictive scheme can be implemented in TCAT by studying the simple problem of single-phase passive diffusion in rigid and homogeneous porous media. The components of the effective diffusivity tensor are predicted for several porous media by solving ancillary boundary-value problems in periodic unit cells. The results are validated through a comparison with data from direct numerical simulation. This extension of TCAT constitutes a useful advance for certain classes of problems amenable to this estimation approach.

Multi-Scale Three-Dimensional Variational Data Assimilation System for Coastal Ocean Prediction

NASA Technical Reports Server (NTRS)

Li, Zhijin; Chao, Yi; Li, P. Peggy

2012-01-01

A multi-scale three-dimensional variational data assimilation system (MS-3DVAR) has been formulated and the associated software system has been developed for improving high-resolution coastal ocean prediction. This system helps improve coastal ocean prediction skill, and has been used in support of operational coastal ocean forecasting systems and field experiments. The system has been developed to improve the capability of data assimilation for assimilating, simultaneously and effectively, sparse vertical profiles and high-resolution remote sensing surface measurements into coastal ocean models, as well as constraining model biases. In this system, the cost function is decomposed into two separate units for the large- and small-scale components, respectively. As such, data assimilation is implemented sequentially from large to small scales, the background error covariance is constructed to be scale-dependent, and a scale-dependent dynamic balance is incorporated. This scheme then allows effective constraining large scales and model bias through assimilating sparse vertical profiles, and small scales through assimilating high-resolution surface measurements. This MS-3DVAR enhances the capability of the traditional 3DVAR for assimilating highly heterogeneously distributed observations, such as along-track satellite altimetry data, and particularly maximizing the extraction of information from limited numbers of vertical profile observations.

H-, He-like recombination spectra - II. l-changing collisions for He Rydberg states

NASA Astrophysics Data System (ADS)

Guzmán, F.; Badnell, N. R.; Williams, R. J. R.; van Hoof, P. A. M.; Chatzikos, M.; Ferland, G. J.

2017-01-01

Cosmological models can be constrained by determining primordial abundances. Accurate predictions of the He I spectrum are needed to determine the primordial helium abundance to a precision of <1 per cent in order to constrain big bang nucleosynthesis models. Theoretical line emissivities at least this accurate are needed if this precision is to be achieved. In the first paper of this series, which focused on H I, we showed that differences in l-changing collisional rate coefficients predicted by three different theories can translate into 10 per cent changes in predictions for H I spectra. Here, we consider the more complicated case of He atoms, where low-l subshells are not energy degenerate. A criterion for deciding when the energy separation between l subshells is small enough to apply energy-degenerate collisional theories is given. Moreover, for certain conditions, the Bethe approximation originally proposed by Pengelly & Seaton is not sufficiently accurate. We introduce a simple modification of this theory which leads to rate coefficients which agree well with those obtained from pure quantal calculations using the approach of Vrinceanu et al. We show that the l-changing rate coefficients from the different theoretical approaches lead to differences of ˜10 per cent in He I emissivities in simulations of H II regions using spectral code CLOUDY.

An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances.

PubMed

Fairbank, Michael; Li, Shuhui; Fu, Xingang; Alonso, Eduardo; Wunsch, Donald

2014-01-01

We present a recurrent neural-network (RNN) controller designed to solve the tracking problem for control systems. We demonstrate that a major difficulty in training any RNN is the problem of exploding gradients, and we propose a solution to this in the case of tracking problems, by introducing a stabilization matrix and by using carefully constrained context units. This solution allows us to achieve consistently lower training errors, and hence allows us to more easily introduce adaptive capabilities. The resulting RNN is one that has been trained off-line to be rapidly adaptive to changing plant conditions and changing tracking targets. The case study we use is a renewable-energy generator application; that of producing an efficient controller for a three-phase grid-connected converter. The controller we produce can cope with the random variation of system parameters and fluctuating grid voltages. It produces tracking control with almost instantaneous response to changing reference states, and virtually zero oscillation. This compares very favorably to the classical proportional integrator (PI) controllers, which we show produce a much slower response and settling time. In addition, the RNN we propose exhibits better learning stability and convergence properties, and can exhibit faster adaptation, than has been achieved with adaptive critic designs. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Simulink Library of cryogenic components to automatically generate control schemes for large Cryorefrigerators

NASA Astrophysics Data System (ADS)

Bonne, François; Alamir, Mazen; Hoa, Christine; Bonnay, Patrick; Bon-Mardion, Michel; Monteiro, Lionel

2015-12-01

In this article, we present a new Simulink library of cryogenics components (such as valve, phase separator, mixer, heat exchanger...) to assemble to generate model-based control schemes. Every component is described by its algebraic or differential equation and can be assembled with others to build the dynamical model of a complete refrigerator or the model of a subpart of it. The obtained model can be used to automatically design advanced model based control scheme. It also can be used to design a model based PI controller. Advanced control schemes aim to replace classical user experience designed approaches usually based on many independent PI controllers. This is particularly useful in the case where cryoplants are submitted to large pulsed thermal loads, expected to take place in future fusion reactors such as those expected in the cryogenic cooling systems of the International Thermonuclear Experimental Reactor (ITER) or the Japan Torus-60 Super Advanced Fusion Experiment (JT- 60SA). The paper gives the example of the generation of the dynamical model of the 400W@1.8K refrigerator and shows how to build a Constrained Model Predictive Control for it. Based on the scheme, experimental results will be given. This work is being supported by the French national research agency (ANR) through the ANR-13-SEED-0005 CRYOGREEN program.

An English language interface for constrained domains

NASA Technical Reports Server (NTRS)

Page, Brenda J.

1989-01-01

The Multi-Satellite Operations Control Center (MSOCC) Jargon Interpreter (MJI) demonstrates an English language interface for a constrained domain. A constrained domain is defined as one with a small and well delineated set of actions and objects. The set of actions chosen for the MJI is from the domain of MSOCC Applications Executive (MAE) Systems Test and Operations Language (STOL) directives and contains directives for signing a cathode ray tube (CRT) on or off, calling up or clearing a display page, starting or stopping a procedure, and controlling history recording. The set of objects chosen consists of CRTs, display pages, STOL procedures, and history files. Translation from English sentences to STOL directives is done in two phases. In the first phase, an augmented transition net (ATN) parser and dictionary are used for determining grammatically correct parsings of input sentences. In the second phase, grammatically typed sentences are submitted to a forward-chaining rule-based system for interpretation and translation into equivalent MAE STOL directives. Tests of the MJI show that it is able to translate individual clearly stated sentences into the subset of directives selected for the prototype. This approach to an English language interface may be used for similarly constrained situations by modifying the MJI's dictionary and rules to reflect the change of domain.

Constrained growth flips the direction of optimal phenological responses among annual plants.

PubMed

Lindh, Magnus; Johansson, Jacob; Bolmgren, Kjell; Lundström, Niklas L P; Brännström, Åke; Jonzén, Niclas

2016-03-01

Phenological changes among plants due to climate change are well documented, but often hard to interpret. In order to assess the adaptive value of observed changes, we study how annual plants with and without growth constraints should optimize their flowering time when productivity and season length changes. We consider growth constraints that depend on the plant's vegetative mass: self-shading, costs for nonphotosynthetic structural tissue and sibling competition. We derive the optimal flowering time from a dynamic energy allocation model using optimal control theory. We prove that an immediate switch (bang-bang control) from vegetative to reproductive growth is optimal with constrained growth and constant mortality. Increasing mean productivity, while keeping season length constant and growth unconstrained, delayed the optimal flowering time. When growth was constrained and productivity was relatively high, the optimal flowering time advanced instead. When the growth season was extended equally at both ends, the optimal flowering time was advanced under constrained growth and delayed under unconstrained growth. Our results suggests that growth constraints are key factors to consider when interpreting phenological flowering responses. It can help to explain phenological patterns along productivity gradients, and links empirical observations made on calendar scales with life-history theory. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

CONSTRAINING SOLAR FLARE DIFFERENTIAL EMISSION MEASURES WITH EVE AND RHESSI

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

Caspi, Amir; McTiernan, James M.; Warren, Harry P.

2014-06-20

Deriving a well-constrained differential emission measure (DEM) distribution for solar flares has historically been difficult, primarily because no single instrument is sensitive to the full range of coronal temperatures observed in flares, from ≲2 to ≳50 MK. We present a new technique, combining extreme ultraviolet (EUV) spectra from the EUV Variability Experiment (EVE) onboard the Solar Dynamics Observatory with X-ray spectra from the Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI), to derive, for the first time, a self-consistent, well-constrained DEM for jointly observed solar flares. EVE is sensitive to ∼2-25 MK thermal plasma emission, and RHESSI to ≳10 MK; together, the twomore » instruments cover the full range of flare coronal plasma temperatures. We have validated the new technique on artificial test data, and apply it to two X-class flares from solar cycle 24 to determine the flare DEM and its temporal evolution; the constraints on the thermal emission derived from the EVE data also constrain the low energy cutoff of the non-thermal electrons, a crucial parameter for flare energetics. The DEM analysis can also be used to predict the soft X-ray flux in the poorly observed ∼0.4-5 nm range, with important applications for geospace science.« less

Predicting Energy Consumption for Potential Effective Use in Hybrid Vehicle Powertrain Management Using Driver Prediction

NASA Astrophysics Data System (ADS)

Magnuson, Brian

A proof-of-concept software-in-the-loop study is performed to assess the accuracy of predicted net and charge-gaining energy consumption for potential effective use in optimizing powertrain management of hybrid vehicles. With promising results of improving fuel efficiency of a thermostatic control strategy for a series, plug-ing, hybrid-electric vehicle by 8.24%, the route and speed prediction machine learning algorithms are redesigned and implemented for real- world testing in a stand-alone C++ code-base to ingest map data, learn and predict driver habits, and store driver data for fast startup and shutdown of the controller or computer used to execute the compiled algorithm. Speed prediction is performed using a multi-layer, multi-input, multi- output neural network using feed-forward prediction and gradient descent through back- propagation training. Route prediction utilizes a Hidden Markov Model with a recurrent forward algorithm for prediction and multi-dimensional hash maps to store state and state distribution constraining associations between atomic road segments and end destinations. Predicted energy is calculated using the predicted time-series speed and elevation profile over the predicted route and the road-load equation. Testing of the code-base is performed over a known road network spanning 24x35 blocks on the south hill of Spokane, Washington. A large set of training routes are traversed once to add randomness to the route prediction algorithm, and a subset of the training routes, testing routes, are traversed to assess the accuracy of the net and charge-gaining predicted energy consumption. Each test route is traveled a random number of times with varying speed conditions from traffic and pedestrians to add randomness to speed prediction. Prediction data is stored and analyzed in a post process Matlab script. The aggregated results and analysis of all traversals of all test routes reflect the performance of the Driver Prediction algorithm. The error of average energy gained through charge-gaining events is 31.3% and the error of average net energy consumed is 27.3%. The average delta and average standard deviation of the delta of predicted energy gained through charge-gaining events is 0.639 and 0.601 Wh respectively for individual time-series calculations. Similarly, the average delta and average standard deviation of the delta of the predicted net energy consumed is 0.567 and 0.580 Wh respectively for individual time-series calculations. The average delta and standard deviation of the delta of the predicted speed is 1.60 and 1.15 respectively also for the individual time-series measurements. The percentage of accuracy of route prediction is 91%. Overall, test routes are traversed 151 times for a total test distance of 276.4 km.

Disentangling climatic versus biotic drivers of tree range constraints: Broad scale tradeoffs between climate and competion rarely explain local range boundaries

NASA Astrophysics Data System (ADS)

Anderegg, L. D. L.; Hillerislambers, J.

2016-12-01

Accurate prediction of climatically-driven range shifts requires knowledge of the dominant forces constraining species ranges, because climatically controlled range boundaries will likely behave differently from biotically controlled range boundaries in a changing climate. Yet the roles of climatic constraints (due to species physiological tolerance) versus biotic constraints (caused by species interactions) on geographic ranges are largely unknown, infusing large uncertainty into projections of future range shifts. Plant species ranges across strong climatic gradients such as elevation gradients are often assumed to represent a tradeoff between climatic constraints on the harsh side of the range and biotic constraints (often competitive constraints) on the climatically benign side. To test this assumption, we collected tree cores from across the elevational range of the three dominant tree species inhabiting each of three climatically disparate mountain slopes and assessed climatic versus competitive constraints on growth at each species' range margins. Across all species and mountains, we found evidence for a tradeoff between climatic and competitve growth constraints. We also found that some individual species did show an apparent trade-off between a climatic constraint at one range margin and a competitive constraint at the other. However, even these simple elevation gradients resulted in complex interactions between temperature, moisture, and competitive constraints such that a climate-competition tradeoff did not explain range constraints for many species. Our results suggest that tree species can be constrained by a simple trade-off between climate and competition, but that the intricacies of real world climate gradients complicate the application of this theory even in apparently harsh environments, such as near high elevation tree line.

Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

NASA Astrophysics Data System (ADS)

Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

2008-12-01

The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously calculated such that measurements from on-board sensors would lead to maximal reduction in the forecast error after data assimilation. The MPC controller also reduces the consumption of system resources such as energy expended in sampling and wireless communication. The MPC-based control approach can be generalized to accept data from remote sensing satellites. This will enable in-situ sensors to be regulated using forecasts generated by assimilating local high resolution in-situ measurements with wide-area observations from remote sensing satellites.

Interactions of timing and prediction error learning.

PubMed

Kirkpatrick, Kimberly

2014-01-01

Timing and prediction error learning have historically been treated as independent processes, but growing evidence has indicated that they are not orthogonal. Timing emerges at the earliest time point when conditioned responses are observed, and temporal variables modulate prediction error learning in both simple conditioning and cue competition paradigms. In addition, prediction errors, through changes in reward magnitude or value alter timing of behavior. Thus, there appears to be a bi-directional interaction between timing and prediction error learning. Modern theories have attempted to integrate the two processes with mixed success. A neurocomputational approach to theory development is espoused, which draws on neurobiological evidence to guide and constrain computational model development. Heuristics for future model development are presented with the goal of sparking new approaches to theory development in the timing and prediction error fields. Copyright © 2013 Elsevier B.V. All rights reserved.

Precision Departure Release Capability (PDRC) Final Report

NASA Technical Reports Server (NTRS)

Engelland, Shawn A.; Capps, Richard; Day, Kevin Brian; Kistler, Matthew Stephen; Gaither, Frank; Juro, Greg

2013-01-01

After takeoff, aircraft must merge into en route (Center) airspace traffic flows that may be subject to constraints that create localized demand/capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool, based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas/Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents research results from the PDRC research activity. Companion papers present the Concept of Operations and a Technology Description.

Precision Departure Release Capability (PDRC) Technology Description

NASA Technical Reports Server (NTRS)

Engelland, Shawn A.; Capps, Richard; Day, Kevin; Robinson, Corissia; Null, Jody R.

2013-01-01

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center TMC to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System (NextGen) plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that uses this technology to improve tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept helps reduce uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station (NTX) in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents the Technology Description. Companion papers include the Final Report and a Concept of Operations.

Precision Departure Release Capability (PDRC): NASA to FAA Research Transition

NASA Technical Reports Server (NTRS)

Engelland, Shawn; Davis, Thomas J.

2013-01-01

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demand-capacity imbalances. When demand exceeds capacity, Traffic Management Coordinators (TMCs) and Frontline Managers (FLMs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release time is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that improves tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions and departure runway assignments to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept reduces uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs and FLMs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station in Dallas-Fort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations.

Precision Departure Release Capability (PDRC) Concept of Operations

NASA Technical Reports Server (NTRS)

Engelland, Shawn; Capps, Richard A.; Day, Kevin Brian

2013-01-01

After takeoff, aircraft must merge into en route (Center) airspace traffic flows which may be subject to constraints that create localized demandcapacity imbalances. When demand exceeds capacity Traffic Management Coordinators (TMCs) often use tactical departure scheduling to manage the flow of departures into the constrained Center traffic flow. Tactical departure scheduling usually involves use of a Call for Release (CFR) procedure wherein the Tower must call the Center TMC to coordinate a release time prior to allowing the flight to depart. In present-day operations release times are computed by the Center Traffic Management Advisor (TMA) decision support tool based upon manual estimates of aircraft ready time verbally communicated from the Tower to the Center. The TMA-computed release is verbally communicated from the Center back to the Tower where it is relayed to the Local controller as a release window that is typically three minutes wide. The Local controller will manage the departure to meet the coordinated release time window. Manual ready time prediction and verbal release time coordination are labor intensive and prone to inaccuracy. Also, use of release time windows adds uncertainty to the tactical departure process. Analysis of more than one million flights from January 2011 indicates that a significant number of tactically scheduled aircraft missed their en route slot due to ready time prediction uncertainty. Uncertainty in ready time estimates may result in missed opportunities to merge into constrained en route flows and lead to lost throughput. Next Generation Air Transportation System (NextGen) plans call for development of Tower automation systems capable of computing surface trajectory-based ready time estimates. NASA has developed the Precision Departure Release Capability (PDRC) concept that uses this technology to improve tactical departure scheduling by automatically communicating surface trajectory-based ready time predictions to the Center scheduling tool. The PDRC concept also incorporates earlier NASA and FAA research into automation-assisted CFR coordination. The PDRC concept helps reduce uncertainty by automatically communicating coordinated release times with seconds-level precision enabling TMCs to work with target times rather than windows. NASA has developed a PDRC prototype system that integrates the Center's TMA system with a research prototype Tower decision support tool. A two-phase field evaluation was conducted at NASA's North Texas Research Station (NTX) in DallasFort Worth. The field evaluation validated the PDRC concept and demonstrated reduced release time uncertainty while being used for tactical departure scheduling of more than 230 operational flights over 29 weeks of operations. This paper presents the Concept of Operations. Companion papers include the Final Report and a Technology Description. ? SUBJECT:

Hybrid Stochastic Search Technique based Suboptimal AGC Regulator Design for Power System using Constrained Feedback Control Strategy

NASA Astrophysics Data System (ADS)

Ibraheem, Omveer, Hasan, N.

2010-10-01

A new hybrid stochastic search technique is proposed to design of suboptimal AGC regulator for a two area interconnected non reheat thermal power system incorporating DC link in parallel with AC tie-line. In this technique, we are proposing the hybrid form of Genetic Algorithm (GA) and simulated annealing (SA) based regulator. GASA has been successfully applied to constrained feedback control problems where other PI based techniques have often failed. The main idea in this scheme is to seek a feasible PI based suboptimal solution at each sampling time. The feasible solution decreases the cost function rather than minimizing the cost function.

Quorum sensing control of Type VI secretion factors restricts the proliferation of quorum-sensing mutants

PubMed Central

Majerczyk, Charlotte; Schneider, Emily; Greenberg, E Peter

2016-01-01

Burkholderia thailandensis uses acyl-homoserine lactone-mediated quorum sensing systems to regulate hundreds of genes. Here we show that cell-cell contact-dependent type VI secretion (T6S) toxin-immunity systems are among those activated by quorum sensing in B. thailandensis. We also demonstrate that T6S is required to constrain proliferation of quorum sensing mutants in colony cocultures of a BtaR1 quorum-sensing signal receptor mutant and its parent. However, the BtaR1 mutant is not constrained by and outcompetes its parent in broth coculture, presumably because no cell contact occurs and there is a metabolic cost associated with quorum sensing gene activation. The increased fitness of the wild type over the BtaR1 mutant during agar surface growth is dependent on an intact T6SS-1 apparatus. Thus, quorum sensing activates B. thailandensis T6SS-1 growth inhibition and this control serves to police and constrain quorum-sensing mutants. This work defines a novel role for T6SSs in intraspecies mutant control. DOI: http://dx.doi.org/10.7554/eLife.14712.001 PMID:27183270

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

PubMed

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 source, available under an MIT license, and can be installed using the Julia package manager from the JuPOETs GitHub repository.

Can we go From Tomographically Determined Seismic Velocities to Composition? Amplitude Resolution Issues in Local Earthquake Tomography

NASA Astrophysics Data System (ADS)

Wagner, L.

2007-12-01

There have been a number of recent papers (i.e. Lee (2003), James et al. (2004), Hacker and Abers (2004), Schutt and Lesher (2006)) which calculate predicted velocities for xenolith compositions at mantle pressures and temperatures. It is tempting, therefore, to attempt to go the other way ... to use tomographically determined absolute velocities to constrain mantle composition. However, in order to do this, it is vital that one is able to accurately constrain not only the polarity of the determined velocity deviations (i.e. fast vs slow) but also how much faster, how much slower relative to the starting model, if absolute velocities are to be so closely analyzed. While much attention has been given to issues concerning spatial resolution in seismic tomography (i.e. what areas are fast, what areas are slow), little attention has been directed at the issue of amplitude resolution (how fast, how slow). Velocity deviation amplitudes in seismic tomography are heavily influenced by the amount of regularization used and the number of iterations performed. Determining these two parameters is a difficult and little discussed problem. I explore the effect of these two parameters on the amplitudes obtained from the tomographic inversion of the Chile Argentina Geophysical Experiment (CHARGE) dataset, and attempt to determine a reasonable solution space for the low Vp, high Vs, low Vp/Vs anomaly found above the flat slab in central Chile. I then compare this solution space to the range in experimentally determined velocities for peridotite end-members to evaluate our ability to constrain composition using tomographically determined seismic velocities. I find that in general, it will be difficult to constrain the compositions of normal mantle peridotites using tomographically determined velocities, but that in the unusual case of the anomaly above the flat slab, the observed velocity structure still has an anomalously high S wave velocity and low Vp/Vs ratio that is most consistent with enstatite, but inconsistent with the predicted velocities of known mantle xenoliths.

Systems design study of the Pioneer Venus spacecraft. Appendices to volume 1, section 7 (part 2 of 3). [procedures for predicting aeroheating environment of Venus entry probes

NASA Technical Reports Server (NTRS)

1973-01-01

The procedures for predicting the aeroheating environment of Venus entry probes are outlined. After some consideration, a number of assumptions were adopted in order to make the prediction techniques tractable. Among these assumptions are thermochemical equilibrium, uncoupled radiative and convective processes, and uncoupled ablation products effects. The single strip method of integral relations, appropriately constrained, is shown to provide adequate inviscid results as a basis for heating calculations on blunt configurations. Techniques for prediction of the laminar, transitional, and turbulent convective environment are outlined and shown to agree with data. The prediction of radiative heating in C, N, and O gas mixtures is discussed and a practical scheme adopted. A comparison with LRC calculations is made.

Zones of life in the subsurface of hydrothermal vents: A synthesis

NASA Astrophysics Data System (ADS)

Larson, B. I.; Houghton, J.; Meile, C. D.

2011-12-01

Subsurface microbial communities in Mid-ocean Ridge (MOR) hydrothermal systems host a wide array of unique metabolic strategies, but the spatial distribution of biogeochemical transformations is poorly constrained. Here we present an approach that reexamines chemical measurements from diffuse fluids with models of convective transport to delineate likely reaction zones. Chemical data have been compiled from bare basalt surfaces at a wide array of mid-ocean ridge systems, including 9°N, East Pacific Rise, Axial Seamount, Juan de Fuca, and Lucky Strike, Mid-Atlantic Ridge. Co-sampled end-member fluid from Ty (EPR) was used to constrain reaction path models that define diffuse fluid compositions as a function of temperature. The degree of mixing between hot vent fluid (350 deg. C) and seawater (2 deg. C) governs fluid temperature, Fe-oxide mineral precipitation is suppressed, and aqueous redox reactions are prevented from equilibrating, consistent with sluggish kinetics. Quartz and pyrite are predicted to precipitate, consistent with field observations. Most reported samples of diffuse fluids from EPR and Axial Seamount fall along the same predicted mixing line only when pyrite precipitation is suppressed, but Lucky Strike fluids do not follow the same trend. The predicted fluid composition as a function of temperature is then used to calculate the free energy available to autotrophic microorganisms for a variety of catabolic strategies in the subsurface. Finally, the relationships between temperature and free energy is combined with modeled temperature fields (Lowell et al., 2007 Geochem. Geophys., Geosys.) over a 500 m x 500 m region extending downward from the seafloor and outward from the high temperature focused hydrothermal flow to define areas that are energetically most favorable for a given metabolic process as well as below the upper temperature limit for life (~120 deg. C). In this way, we can expand the relevance of geochemical model predictions of bioenergetics by predicting functionally-defined 'Zones of Life' and placing them spatially within the boundary of the 120 deg. C isotherm, estimating the extent of subsurface biosphere beneath mid-ocean ridge hydrothermal systems. Preliminary results indicate that methanogenesis yields the most energy per kg of vent fluid, consistent with the elevated CH4(aq) seen at all three sites, but may be constrained by temperatures too hot for microbial life while available energy from the oxidation of Fe(II) peaks near regions of the crust that are more hospitable.

Controlling High-Resolution LROC NAC Polar Mosaics to LOLA Track Data

NASA Astrophysics Data System (ADS)

Archinal, B.; Lee, E.; Weller, L.; Richie, J.; Edmundson, K.; Laura, J.; Robinson, M.; Speyerer, E.; Boyd, A.; Bowman-Cisneros, E.; Wagner, R.; Nefian, A.

2016-11-01

We describe our progress on completing 1 m resolution geodetically controlled LROC NAC illumination mosaics of both lunar poles out to 85 degrees latitude, constrained using matching to LOLA track data.

Digital robust control law synthesis using constrained optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivekananda

1989-01-01

Development of digital robust control laws for active control of high performance flexible aircraft and large space structures is a research area of significant practical importance. The flexible system is typically modeled by a large order state space system of equations in order to accurately represent the dynamics. The active control law must satisy multiple conflicting design requirements and maintain certain stability margins, yet should be simple enough to be implementable on an onboard digital computer. Described here is an application of a generic digital control law synthesis procedure for such a system, using optimal control theory and constrained optimization technique. A linear quadratic Gaussian type cost function is minimized by updating the free parameters of the digital control law, while trying to satisfy a set of constraints on the design loads, responses and stability margins. Analytical expressions for the gradients of the cost function and the constraints with respect to the control law design variables are used to facilitate rapid numerical convergence. These gradients can be used for sensitivity study and may be integrated into a simultaneous structure and control optimization scheme.

Postglacial Rebound and Current Ice Loss Estimates from Space Geodesy: The New ICE-6G (VM5a) Global Model

NASA Astrophysics Data System (ADS)

Peltier, W. R.; Argus, D.; Drummond, R.; Moore, A. W.

2012-12-01

We compare, on a global basis, estimates of site velocity against predictions of the newly constructed postglacial rebound model ICE-6G (VM5a). This model is fit to observations of North American postglacial rebound thereby demonstrating that the ice sheet at last glacial maximum must have been, relative to ICE-5G,thinner in southern Manitoba, thinner near Yellowknife (northwest Territories), thicker in eastern and southern Quebec, and thicker along the British Columbia-Alberta border. The GPS based estimates of site velocity that we employ are more accurate than were previously available because they are based on GPS estimates of position as a function of time determined by incorporating satellite phase center variations [Desai et al. 2011]. These GPS estimates are constraining postglacial rebound in North America and Europe more tightly than ever before. In particular, given the high density of GPS sites in North America, and the fact that the velocity of the mass center (CM) of Earth is also more tightly constrained, the new model much more strongly constrains both the lateral extent of the proglacial forebulge and the rate at which this peripheral bulge (that was emplaced peripheral to the late Pleistocence Laurentia ice sheet) is presently collapsing. This fact proves to be important to the more accurate inference of the current rate of ice loss from both Greenland and Alaska based upon the time dependent gravity observations being provided by the GRACE satellite system. In West Antarctica we have also been able to significantly revise the previously prevalent ICE-5G deglaciation history so as to enable its predictions to be optimally consistent with GPS site velocities determined by connecting campaign WAGN measurements to those provided by observations from the permanent ANET sites. Ellsworth Land (south of the Antarctic peninsula), is observed to be rising at 6 ±3 mm/yr according to our latest analyses; the Ellsworth mountains themselves are observed to be rising at 5 ±4 mm/yr; Palmer Land is observed to be rising at 3 ±3 mm/yr. The predictions of the ICE-5G (VM2) model and those of the postglacial rebound component of the model of Simons, Ivins, and James [2010] had predicted uplift to be significantly faster than observed in this region, as previously documented in Argus et al [2011]. From a global perspective the new ICE-6G (VM5a) model is also a further significant improvement on the previous ICE-5G (VM2) model in that the degree two and order one components of its predicted time dependence of geoid height are tightly constrained by the recent inferences of Roy and Peltier [2011] of the post-GRACE-launch values of the speed and direction of true polar wander and the non-tidal acceleration of the lod. .

Management filters and species traits: Weed community assembly in long-term organic and conventional systems

USDA-ARS?s Scientific Manuscript database

Community assembly theory provides a useful framework to assess the response of weed communities to agricultural management systems and to improve the predictive power of weed science. Under this framework, weed community assembly is constrained by abiotic and biotic "filters" that act on species tr...

Constrained range expansion and climate change assessments

Treesearch

Yohay Carmel; Curtis H. Flather

2006-01-01

Modeling the future distribution of keystone species has proved to be an important approach to assessing the potential ecological consequences of climate change (Loehle and LeBlanc 1996; Hansen et al. 2001). Predictions of range shifts are typically based on empirical models derived from simple correlative relationships between climatic characteristics of occupied and...

Reducing the Uncertainties in Direct Aerosol Radiative Forcing

NASA Technical Reports Server (NTRS)

Kahn, Ralph A.

2011-01-01

Airborne particles, which include desert and soil dust, wildfire smoke, sea salt, volcanic ash, black carbon, natural and anthropogenic sulfate, nitrate, and organic aerosol, affect Earth's climate, in part by reflecting and absorbing sunlight. This paper reviews current status, and evaluates future prospects for reducing the uncertainty aerosols contribute to the energy budget of Earth, which at present represents a leading factor limiting the quality of climate predictions. Information from satellites is critical for this work, because they provide frequent, global coverage of the diverse and variable atmospheric aerosol load. Both aerosol amount and type must be determined. Satellites are very close to measuring aerosol amount at the level-of-accuracy needed, but aerosol type, especially how bright the airborne particles are, cannot be constrained adequately by current techniques. However, satellite instruments can map out aerosol air mass type, which is a qualitative classification rather than a quantitative measurement, and targeted suborbital measurements can provide the required particle property detail. So combining satellite and suborbital measurements, and then using this combination to constrain climate models, will produce a major advance in climate prediction.

Defensive traits exhibit an evolutionary trade-off and drive diversification in ants.

PubMed

Blanchard, Benjamin D; Moreau, Corrie S

2017-02-01

Evolutionary biologists have long predicted that evolutionary trade-offs among traits should constrain morphological divergence and species diversification. However, this prediction has yet to be tested in a broad evolutionary context in many diverse clades, including ants. Here, we reconstruct an expanded ant phylogeny representing 82% of ant genera, compile a new family-wide trait database, and conduct various trait-based analyses to show that defensive traits in ants do exhibit an evolutionary trade-off. In particular, the use of a functional sting negatively correlates with a suite of other defensive traits including spines, large eye size, and large colony size. Furthermore, we find that several of the defensive traits that trade off with a sting are also positively correlated with each other and drive increased diversification, further suggesting that these traits form a defensive suite. Our results support the hypothesis that trade-offs in defensive traits significantly constrain trait evolution and influence species diversification in ants. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Effective theory of flavor for Minimal Mirror Twin Higgs

NASA Astrophysics Data System (ADS)

Barbieri, Riccardo; Hall, Lawrence J.; Harigaya, Keisuke

2017-10-01

We consider two copies of the Standard Model, interchanged by an exact parity symmetry, P. The observed fermion mass hierarchy is described by suppression factors ɛ^{n_i} for charged fermion i, as can arise in Froggatt-Nielsen and extra-dimensional theories of flavor. The corresponding flavor factors in the mirror sector are ɛ^' {n}_i} , so that spontaneous breaking of the parity P arises from a single parameter ɛ'/ɛ, yielding a tightly constrained version of Minimal Mirror Twin Higgs, introduced in our previous paper. Models are studied for simple values of n i , including in particular one with SU(5)-compatibility, that describe the observed fermion mass hierarchy. The entire mirror quark and charged lepton spectrum is broadly predicted in terms of ɛ'/ɛ, as are the mirror QCD scale and the decoupling temperature between the two sectors. Helium-, hydrogen- and neutron-like mirror dark matter candidates are constrained by self-scattering and relic ionization. In each case, the allowed parameter space can be fully probed by proposed direct detection experiments. Correlated predictions are made as well for the Higgs signal strength and the amount of dark radiation.

Physics of Inference

NASA Astrophysics Data System (ADS)

Toroczkai, Zoltan

Jaynes's maximum entropy method provides a family of principled models that allow the prediction of a system's properties as constrained by empirical data (observables). However, their use is often hindered by the degeneracy problem characterized by spontaneous symmetry breaking, where predictions fail. Here we show that degeneracy appears when the corresponding density of states function is not log-concave, which is typically the consequence of nonlinear relationships between the constraining observables. We illustrate this phenomenon on several examples, including from complex networks, combinatorics and classical spin systems (e.g., Blume-Emery-Griffiths lattice-spin models). Exploiting these nonlinear relationships we then propose a solution to the degeneracy problem for a large class of systems via transformations that render the density of states function log-concave. The effectiveness of the method is demonstrated on real-world network data. Finally, we discuss the implications of these findings on the relationship between the geometrical properties of the density of states function and phase transitions in spin systems. Supported in part by Grant No. FA9550-12-1-0405 from AFOSR/DARPA and by Grant No. HDTRA 1-09-1-0039 from DTRA.

Algorithmic pie-crusting of the medial collateral ligament guided by sensing technology affects the use of constrained inserts during total knee arthroplasty.

PubMed

Amundsen, Spencer; Lee, Yuo-Yu; González Della Valle, Alejandro

2017-06-01

Intra-operative sensing technology is an alternative to standard techniques in total knee arthroplasty (TKA) for determining balance by providing quantitative analysis of loads and point of contact throughout a range of motion. We used intra-operative sensing (VERASENSE-OrthoSensor, Inc.) to examine pie-crusting release of the medial collateral ligament in knees with varus deformity (study group) in comparison to a control group where balance was obtained using a classic release technique and assessed using laminar spreaders, spacer blocks, manual stress, and a ruler. The surgery was performed by a single surgeon utilizing measured resection and posterior-stabilized, cemented implants. Seventy-five study TKAs were matched 1:3 with 225 control TKAs. Outcome variables included the use of a constrained insert, functional- and knee-specific Knee Society score (KSS) at six weeks, four months, and one year post-operatively. Outcomes were analyzed in a multivariate model controlling for age, sex, BMI, and severity of deformity. The use of a constrained insert was significantly lower in the study group (5.3 vs. 13.8%; p = 0.049). The use of increased constraint was not significant between groups with increasing deformity. There was no difference in functional KSS and knee-specific KSS between groups at any follow-up interval. An algorithmic pie-crusting technique guided by intra-operative sensing is associated with decreased use of constrained inserts in TKA patients with a pre-operative varus deformity. This may cause a positive shift in value and cost savings.

Constrained ℋ∞ control for low bandwidth active suspensions

NASA Astrophysics Data System (ADS)

Wasiwitono, Unggul; Sutantra, I. Nyoman

2017-08-01

Low Bandwidth Active Suspension (LBAS) is shown to be more competitive to High Bandwidth Active Suspension (HBAS) when energy and cost aspects are taken into account. In this paper, the constrained ℋ∞ control scheme is applied for LBAS system. The ℋ∞ performance is used to measure ride comfort while the concept of reachable set in a state-space ellipsoid defined by a quadratic storage function is used to capture the time domain constraint that representing the requirements for road holding, suspension deflection limitation and actuator saturation. Then, the control problem is derived in the framework of Linear Matrix Inequality (LMI) optimization. The simulation is conducted considering the road disturbance as a stationary random process. The achievable performance of LBAS is analyzed for different values of bandwidth and damping ratio.

Feasibility Assessment of a Fine-Grained Access Control Model on Resource Constrained Sensors.

PubMed

Uriarte Itzazelaia, Mikel; Astorga, Jasone; Jacob, Eduardo; Huarte, Maider; Romaña, Pedro

2018-02-13

Upcoming smart scenarios enabled by the Internet of Things (IoT) envision smart objects that provide services that can adapt to user behavior or be managed to achieve greater productivity. In such environments, smart things are inexpensive and, therefore, constrained devices. However, they are also critical components because of the importance of the information that they provide. Given this, strong security is a requirement, but not all security mechanisms in general and access control models in particular are feasible. In this paper, we present the feasibility assessment of an access control model that utilizes a hybrid architecture and a policy language that provides dynamic fine-grained policy enforcement in the sensors, which requires an efficient message exchange protocol called Hidra. This experimental performance assessment includes a prototype implementation, a performance evaluation model, the measurements and related discussions, which demonstrate the feasibility and adequacy of the analyzed access control model.

Feasibility Assessment of a Fine-Grained Access Control Model on Resource Constrained Sensors

PubMed Central

Huarte, Maider; Romaña, Pedro

2018-01-01

Upcoming smart scenarios enabled by the Internet of Things (IoT) envision smart objects that provide services that can adapt to user behavior or be managed to achieve greater productivity. In such environments, smart things are inexpensive and, therefore, constrained devices. However, they are also critical components because of the importance of the information that they provide. Given this, strong security is a requirement, but not all security mechanisms in general and access control models in particular are feasible. In this paper, we present the feasibility assessment of an access control model that utilizes a hybrid architecture and a policy language that provides dynamic fine-grained policy enforcement in the sensors, which requires an efficient message exchange protocol called Hidra. This experimental performance assessment includes a prototype implementation, a performance evaluation model, the measurements and related discussions, which demonstrate the feasibility and adequacy of the analyzed access control model. PMID:29438338

Kin competition and the evolution of cooperation

PubMed Central

Platt, Thomas G.; Bever, James D.

2017-01-01

Kin and multilevel selection theories predict that genetic structure is required for the evolution of cooperation. However, local competition among relatives can limit cooperative benefits, antagonizing the evolution of cooperation. We show that several ecological factors determine the extent to which kin competition constrains cooperative benefits. In addition, we argue that cooperative acts that expand local carrying capacity are less constrained by kin competition than other cooperative traits, and are therefore more likely to evolve. These arguments are particularly relevant to microbial cooperation, which often involves the production of public goods that promote population expansion. The challenge now is to understand how an organism’s ecology influences how much cooperative groups contribute to future generations and thereby the evolution of cooperation. PMID:19409651

Monitoring is not enough: on the need for a model-based approach to migratory bird management

USGS Publications Warehouse

Nichols, J.D.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry

2000-01-01

Informed management requires information about system state and about effects of potential management actions on system state. Population monitoring can provide the needed information about system state, as well as information that can be used to investigate effects of management actions. Three methods for investigating effects of management on bird populations are (1) retrospective analysis, (2) formal experimentation and constrained-design studies, and (3) adaptive management. Retrospective analyses provide weak inferences, regardless of the quality of the monitoring data. The active use of monitoring data in experimental or constrained-design studies or in adaptive management is recommended. Under both approaches, learning occurs via the comparison of estimates from the monitoring program with predictions from competing management models.

Toward Process-resolving Synthesis and Prediction of Arctic Climate Change Using the Regional Arctic System Model

NASA Astrophysics Data System (ADS)

Maslowski, W.

2017-12-01

The Regional Arctic System Model (RASM) has been developed to better understand the operation of Arctic System at process scale and to improve prediction of its change at a spectrum of time scales. RASM is a pan-Arctic, fully coupled ice-ocean-atmosphere-land model with marine biogeochemistry extension to the ocean and sea ice models. The main goal of our research is to advance a system-level understanding of critical processes and feedbacks in the Arctic and their links with the Earth System. The secondary, an equally important objective, is to identify model needs for new or additional observations to better understand such processes and to help constrain models. Finally, RASM has been used to produce sea ice forecasts for September 2016 and 2017, in contribution to the Sea Ice Outlook of the Sea Ice Prediction Network. Future RASM forecasts, are likely to include increased resolution for model components and ecosystem predictions. Such research is in direct support of the US environmental assessment and prediction needs, including those of the U.S. Navy, Department of Defense, and the recent IARPC Arctic Research Plan 2017-2021. In addition to an overview of RASM technical details, selected model results are presented from a hierarchy of climate models together with available observations in the region to better understand potential oceanic contributions to polar amplification. RASM simulations are analyzed to evaluate model skill in representing seasonal climatology as well as interannual and multi-decadal climate variability and predictions. Selected physical processes and resulting feedbacks are discussed to emphasize the need for fully coupled climate model simulations, high model resolution and sensitivity of simulated sea ice states to scale dependent model parameterizations controlling ice dynamics, thermodynamics and coupling with the atmosphere and ocean.

Population Dynamics and Flight Phenology Model of Codling Moth Differ between Commercial and Abandoned Apple Orchard Ecosystems.

PubMed

Joshi, Neelendra K; Rajotte, Edwin G; Naithani, Kusum J; Krawczyk, Greg; Hull, Larry A

2016-01-01

Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM), Cydia pomonella (L.) (Lepidoptera: Tortricidae), which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight, and egg-hatch) allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator) that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth) models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e., PETE model). In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology.

Population Dynamics and Flight Phenology Model of Codling Moth Differ between Commercial and Abandoned Apple Orchard Ecosystems

PubMed Central

Joshi, Neelendra K.; Rajotte, Edwin G.; Naithani, Kusum J.; Krawczyk, Greg; Hull, Larry A.

2016-01-01

Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM), Cydia pomonella (L.) (Lepidoptera: Tortricidae), which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight, and egg-hatch) allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator) that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth) models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e., PETE model). In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology. PMID:27713702

Digital robust active control law synthesis for large order systems using constrained optimization

NASA Technical Reports Server (NTRS)

Mukhopadhyay, Vivek

1987-01-01

This paper presents a direct digital control law synthesis procedure for a large order, sampled data, linear feedback system using constrained optimization techniques to meet multiple design requirements. A linear quadratic Gaussian type cost function is minimized while satisfying a set of constraints on the design loads and responses. General expressions for gradients of the cost function and constraints, with respect to the digital control law design variables are derived analytically and computed by solving a set of discrete Liapunov equations. The designer can choose the structure of the control law and the design variables, hence a stable classical control law as well as an estimator-based full or reduced order control law can be used as an initial starting point. Selected design responses can be treated as constraints instead of lumping them into the cost function. This feature can be used to modify a control law, to meet individual root mean square response limitations as well as minimum single value restrictions. Low order, robust digital control laws were synthesized for gust load alleviation of a flexible remotely piloted drone aircraft.

Management of groundwater in-situ bioremediation system using reactive transport modelling under parametric uncertainty: field scale application

NASA Astrophysics Data System (ADS)

Verardo, E.; Atteia, O.; Rouvreau, L.

2015-12-01

In-situ bioremediation is a commonly used remediation technology to clean up the subsurface of petroleum-contaminated sites. Forecasting remedial performance (in terms of flux and mass reduction) is a challenge due to uncertainties associated with source properties and the uncertainties associated with contribution and efficiency of concentration reducing mechanisms. In this study, predictive uncertainty analysis of bio-remediation system efficiency is carried out with the null-space Monte Carlo (NSMC) method which combines the calibration solution-space parameters with the ensemble of null-space parameters, creating sets of calibration-constrained parameters for input to follow-on remedial efficiency. The first step in the NSMC methodology for uncertainty analysis is model calibration. The model calibration was conducted by matching simulated BTEX concentration to a total of 48 observations from historical data before implementation of treatment. Two different bio-remediation designs were then implemented in the calibrated model. The first consists in pumping/injection wells and the second in permeable barrier coupled with infiltration across slotted piping. The NSMC method was used to calculate 1000 calibration-constrained parameter sets for the two different models. Several variants of the method were implemented to investigate their effect on the efficiency of the NSMC method. The first variant implementation of the NSMC is based on a single calibrated model. In the second variant, models were calibrated from different initial parameter sets. NSMC calibration-constrained parameter sets were sampled from these different calibrated models. We demonstrate that in context of nonlinear model, second variant avoids to underestimate parameter uncertainty which may lead to a poor quantification of predictive uncertainty. Application of the proposed approach to manage bioremediation of groundwater in a real site shows that it is effective to provide support in management of the in-situ bioremediation systems. Moreover, this study demonstrates that the NSMC method provides a computationally efficient and practical methodology of utilizing model predictive uncertainty methods in environmental management.

Analyses of deep mammalian sequence alignments and constraint predictions for 1% of the human genome

PubMed Central

Margulies, Elliott H.; Cooper, Gregory M.; Asimenos, George; Thomas, Daryl J.; Dewey, Colin N.; Siepel, Adam; Birney, Ewan; Keefe, Damian; Schwartz, Ariel S.; Hou, Minmei; Taylor, James; Nikolaev, Sergey; Montoya-Burgos, Juan I.; Löytynoja, Ari; Whelan, Simon; Pardi, Fabio; Massingham, Tim; Brown, James B.; Bickel, Peter; Holmes, Ian; Mullikin, James C.; Ureta-Vidal, Abel; Paten, Benedict; Stone, Eric A.; Rosenbloom, Kate R.; Kent, W. James; Bouffard, Gerard G.; Guan, Xiaobin; Hansen, Nancy F.; Idol, Jacquelyn R.; Maduro, Valerie V.B.; Maskeri, Baishali; McDowell, Jennifer C.; Park, Morgan; Thomas, Pamela J.; Young, Alice C.; Blakesley, Robert W.; Muzny, Donna M.; Sodergren, Erica; Wheeler, David A.; Worley, Kim C.; Jiang, Huaiyang; Weinstock, George M.; Gibbs, Richard A.; Graves, Tina; Fulton, Robert; Mardis, Elaine R.; Wilson, Richard K.; Clamp, Michele; Cuff, James; Gnerre, Sante; Jaffe, David B.; Chang, Jean L.; Lindblad-Toh, Kerstin; Lander, Eric S.; Hinrichs, Angie; Trumbower, Heather; Clawson, Hiram; Zweig, Ann; Kuhn, Robert M.; Barber, Galt; Harte, Rachel; Karolchik, Donna; Field, Matthew A.; Moore, Richard A.; Matthewson, Carrie A.; Schein, Jacqueline E.; Marra, Marco A.; Antonarakis, Stylianos E.; Batzoglou, Serafim; Goldman, Nick; Hardison, Ross; Haussler, David; Miller, Webb; Pachter, Lior; Green, Eric D.; Sidow, Arend

2007-01-01

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization. PMID:17567995

Integrated Control Using the SOFFT Control Structure

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1996-01-01

The need for integrated/constrained control systems has become clearer as advanced aircraft introduced new coupled subsystems such as new propulsion subsystems with thrust vectoring and new aerodynamic designs. In this study, we develop an integrated control design methodology which accomodates constraints among subsystem variables while using the Stochastic Optimal Feedforward/Feedback Control Technique (SOFFT) thus maintaining all the advantages of the SOFFT approach. The Integrated SOFFT Control methodology uses a centralized feedforward control and a constrained feedback control law. The control thus takes advantage of the known coupling among the subsystems while maintaining the identity of subsystems for validation purposes and the simplicity of the feedback law to understand the system response in complicated nonlinear scenarios. The Variable-Gain Output Feedback Control methodology (including constant gain output feedback) is extended to accommodate equality constraints. A gain computation algorithm is developed. The designer can set the cross-gains between two variables or subsystems to zero or another value and optimize the remaining gains subject to the constraint. An integrated control law is designed for a modified F-15 SMTD aircraft model with coupled airframe and propulsion subsystems using the Integrated SOFFT Control methodology to produce a set of desired flying qualities.

Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints.

PubMed

Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai

2015-07-01

The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.

H2, fixed architecture, control design for large scale systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Mercadal, Mathieu

1990-01-01

The H2, fixed architecture, control problem is a classic linear quadratic Gaussian (LQG) problem whose solution is constrained to be a linear time invariant compensator with a decentralized processing structure. The compensator can be made of p independent subcontrollers, each of which has a fixed order and connects selected sensors to selected actuators. The H2, fixed architecture, control problem allows the design of simplified feedback systems needed to control large scale systems. Its solution becomes more complicated, however, as more constraints are introduced. This work derives the necessary conditions for optimality for the problem and studies their properties. It is found that the filter and control problems couple when the architecture constraints are introduced, and that the different subcontrollers must be coordinated in order to achieve global system performance. The problem requires the simultaneous solution of highly coupled matrix equations. The use of homotopy is investigated as a numerical tool, and its convergence properties studied. It is found that the general constrained problem may have multiple stabilizing solutions, and that these solutions may be local minima or saddle points for the quadratic cost. The nature of the solution is not invariant when the parameters of the system are changed. Bifurcations occur, and a solution may continuously transform into a nonstabilizing compensator. Using a modified homotopy procedure, fixed architecture compensators are derived for models of large flexible structures to help understand the properties of the constrained solutions and compare them to the corresponding unconstrained ones.

Self-control, future orientation, smoking, and the impact of Dutch tobacco control measures.

PubMed

Daly, Michael; Delaney, Liam; Baumeister, Roy F

2015-06-01

The pronounced discrepancy between smokers' intentions to quit and their smoking behavior has led researchers to suggest that many smokers are time inconsistent, have self-control problems, and may benefit from external efforts to constrain their consumption. This study aims to test whether self-control and future orientation predict smoking levels and to identify if these traits modify how cigarette consumption responds to the introduction of tobacco control measures. A sample of Dutch adults (N = 1585) completed a measure of self-control and the Consideration of Future Consequences Scale (CFCS) in 2001 and indicated their tobacco consumption each year from 2001 to 2007. In 2004, a workplace smoking ban and substantial tax increase on tobacco was introduced in the Netherlands. To identify the potential impact of these tobacco control measures we examined whether participants smoked or were heavy smokers (20 + cigarettes per day) each year from 2001 to 2007. Participants with high self-control and CFCS scores showed lower rates of smoking across the seven year period of the study. The 2004 smoking restrictions were linked with a subsequent decline in heavy smoking. This decline was moderated by self-control levels. Those with low self-control showed a large reduction in heavy smoking whereas those with high self-control did not. The effects were, however, temporary: many people with low self-control resumed heavy smoking 2-3 years after the introduction of the tobacco restrictions. The immediate costs which national tobacco control measures impose on smokers may assist smokers with poor self-control in reducing their cigarette consumption.

Mechanistic variables can enhance predictive models of endotherm distributions: the American pika under current, past, and future climates.

PubMed

Mathewson, Paul D; Moyer-Horner, Lucas; Beever, Erik A; Briscoe, Natalie J; Kearney, Michael; Yahn, Jeremiah M; Porter, Warren P

2017-03-01

How climate constrains species' distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8-19% less habitat loss in response to annual temperature increases of ~3-5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans. © 2016 John Wiley & Sons Ltd.

Mechanistic variables can enhance predictive models of endotherm distributions: The American pika under current, past, and future climates

USGS Publications Warehouse

Mathewson, Paul; Moyer-Horner, Lucas; Beever, Erik; Briscoe, Natalie; Kearney, Michael T.; Yahn, Jeremiah; Porter, Warren P.

2017-01-01

How climate constrains species’ distributions through time and space is an important question in the context of conservation planning for climate change. Despite increasing awareness of the need to incorporate mechanism into species distribution models (SDMs), mechanistic modeling of endotherm distributions remains limited in this literature. Using the American pika (Ochotona princeps) as an example, we present a framework whereby mechanism can be incorporated into endotherm SDMs. Pika distribution has repeatedly been found to be constrained by warm temperatures, so we used Niche Mapper, a mechanistic heat-balance model, to convert macroclimate data to pika-specific surface activity time in summer across the western United States. We then explored the difference between using a macroclimate predictor (summer temperature) and using a mechanistic predictor (predicted surface activity time) in SDMs. Both approaches accurately predicted pika presences in current and past climate regimes. However, the activity models predicted 8–19% less habitat loss in response to annual temperature increases of ~3–5 °C predicted in the region by 2070, suggesting that pikas may be able to buffer some climate change effects through behavioral thermoregulation that can be captured by mechanistic modeling. Incorporating mechanism added value to the modeling by providing increased confidence in areas where different modeling approaches agreed and providing a range of outcomes in areas of disagreement. It also provided a more proximate variable relating animal distribution to climate, allowing investigations into how unique habitat characteristics and intraspecific phenotypic variation may allow pikas to exist in areas outside those predicted by generic SDMs. Only a small number of easily obtainable data are required to parameterize this mechanistic model for any endotherm, and its use can improve SDM predictions by explicitly modeling a widely applicable direct physiological effect: climate-imposed restrictions on activity. This more complete understanding is necessary to inform climate adaptation actions, management strategies, and conservation plans.

Potential New Lidar Observations for Cloud Studies

NASA Technical Reports Server (NTRS)

Winker, Dave; Hu, Yong; Narir, Amin; Cai, Xia

2015-01-01

The response of clouds to global warming represents a major uncertainty in estimating climate sensitivity. These uncertainties have been tracked to shallow marine clouds in the tropics and subtropics. CALIOP observations have already been used extensively to evaluate model predictions of shallow cloud fraction and top height (Leahy et al. 2013; Nam et al 2012). Tools are needed to probe the lowest levels of the troposphere. The large footprint of satellite lidars gives large multiple scattering from clouds which presents new possibilities for cloud retrievals to constrain model predictions.

Prediction during language processing is a piece of cake--but only for skilled producers.

PubMed

Mani, Nivedita; Huettig, Falk

2012-08-01

Are there individual differences in children's prediction of upcoming linguistic input and what do these differences reflect? Using a variant of the preferential looking paradigm (Golinkoff, Hirsh-Pasek, Cauley, & Gordon, 1987), we found that, upon hearing a sentence like, "The boy eats a big cake," 2-year-olds fixate edible objects in a visual scene (a cake) soon after they hear the semantically constraining verb eats and prior to hearing the word cake. Importantly, children's prediction skills were significantly correlated with their productive vocabulary size-skilled producers (i.e., children with large production vocabularies) showed evidence of predicting upcoming linguistic input, while low producers did not. Furthermore, we found that children's prediction ability is tied specifically to their production skills and not to their comprehension skills. Prediction is really a piece of cake, but only for skilled producers.

River networks as ecological corridors: A coherent ecohydrological perspective

NASA Astrophysics Data System (ADS)

Rinaldo, Andrea; Gatto, Marino; Rodriguez-Iturbe, Ignacio

2018-02-01

This paper draws together several lines of argument to suggest that an ecohydrological framework, i.e. laboratory, field and theoretical approaches focused on hydrologic controls on biota, has contributed substantially to our understanding of the function of river networks as ecological corridors. Such function proves relevant to: the spatial ecology of species; population dynamics and biological invasions; the spread of waterborne disease. As examples, we describe metacommunity predictions of fish diversity patterns in the Mississippi-Missouri basin, geomorphic controls imposed by the fluvial landscape on elevational gradients of species' richness, the zebra mussel invasion of the same Mississippi-Missouri river system, and the spread of proliferative kidney disease in salmonid fish. We conclude that spatial descriptions of ecological processes in the fluvial landscape, constrained by their specific hydrologic and ecological dynamics and by the ecosystem matrix for interactions, i.e. the directional dispersal embedded in fluvial and host/pathogen mobility networks, have already produced a remarkably broad range of significant results. Notable scientific and practical perspectives are thus open, in the authors' view, to future developments in ecohydrologic research.

Geometrical and Mechanical Properties Control Actin Filament Organization

PubMed Central

Ennomani, Hajer; Théry, Manuel; Nedelec, Francois; Blanchoin, Laurent

2015-01-01

The different actin structures governing eukaryotic cell shape and movement are not only determined by the properties of the actin filaments and associated proteins, but also by geometrical constraints. We recently demonstrated that limiting nucleation to specific regions was sufficient to obtain actin networks with different organization. To further investigate how spatially constrained actin nucleation determines the emergent actin organization, we performed detailed simulations of the actin filament system using Cytosim. We first calibrated the steric interaction between filaments, by matching, in simulations and experiments, the bundled actin organization observed with a rectangular bar of nucleating factor. We then studied the overall organization of actin filaments generated by more complex pattern geometries used experimentally. We found that the fraction of parallel versus antiparallel bundles is determined by the mechanical properties of actin filament or bundles and the efficiency of nucleation. Thus nucleation geometry, actin filaments local interactions, bundle rigidity, and nucleation efficiency are the key parameters controlling the emergent actin architecture. We finally simulated more complex nucleation patterns and performed the corresponding experiments to confirm the predictive capabilities of the model. PMID:26016478

A Four-parameter Budyko Equation for Mean Annual Water Balance

NASA Astrophysics Data System (ADS)

Tang, Y.; Wang, D.

2016-12-01

In this study, a four-parameter Budyko equation for long-term water balance at watershed scale is derived based on the proportionality relationships of the two-stage partitioning of precipitation. The four-parameter Budyko equation provides a practical solution to balance model simplicity and representation of dominated hydrologic processes. Under the four-parameter Budyko framework, the key hydrologic processes related to the lower bound of Budyko curve are determined, that is, the lower bound is corresponding to the situation when surface runoff and initial evaporation not competing with base flow generation are zero. The derived model is applied to 166 MOPEX watersheds in United States, and the dominant controlling factors on each parameter are determined. Then, four statistical models are proposed to predict the four model parameters based on the dominant controlling factors, e.g., saturated hydraulic conductivity, fraction of sand, time period between two storms, watershed slope, and Normalized Difference Vegetation Index. This study shows a potential application of the four-parameter Budyko equation to constrain land-surface parameterizations in ungauged watersheds or general circulation models.

A cost-constrained model of strategic service quality emphasis in nursing homes.

PubMed

Davis, M A; Provan, K G

1996-02-01

This study employed structural equation modeling to test the relationship between three aspects of the environmental context of nursing homes; Medicaid dependence, ownership status, and market demand, and two basic strategic orientations: low cost and differentiation based on service quality emphasis. Hypotheses were proposed and tested against data collected from a sample of nursing homes operating in a single state. Because of the overwhelming importance of cost control in the nursing home industry, a cost constrained strategy perspective was supported. Specifically, while the three contextual variables had no direct effect on service quality emphasis, the entire model was supported when cost control orientation was introduced as a mediating variable.

Explicit reference governor for linear systems

NASA Astrophysics Data System (ADS)

Garone, Emanuele; Nicotra, Marco; Ntogramatzidis, Lorenzo

2018-06-01

The explicit reference governor is a constrained control scheme that was originally introduced for generic nonlinear systems. This paper presents two explicit reference governor strategies that are specifically tailored for the constrained control of linear time-invariant systems subject to linear constraints. Both strategies are based on the idea of maintaining the system states within an invariant set which is entirely contained in the constraints. This invariant set can be constructed by exploiting either the Lyapunov inequality or modal decomposition. To improve the performance, we show that the two strategies can be combined by choosing at each time instant the least restrictive set. Numerical simulations illustrate that the proposed scheme achieves performances that are comparable to optimisation-based reference governors.

Comprehensive, Process-based Identification of Hydrologic Models using Satellite and In-situ Water Storage Data: A Multi-objective calibration Approach

NASA Astrophysics Data System (ADS)

Abdo Yassin, Fuad; Wheater, Howard; Razavi, Saman; Sapriza, Gonzalo; Davison, Bruce; Pietroniro, Alain

2015-04-01

The credible identification of vertical and horizontal hydrological components and their associated parameters is very challenging (if not impossible) by only constraining the model to streamflow data, especially in regions where the vertical processes significantly dominate the horizontal processes. The prairie areas of the Saskatchewan River basin, a major water system in Canada, demonstrate such behavior, where the hydrologic connectivity and vertical fluxes are mainly controlled by the amount of surface and sub-surface water storages. In this study, we develop a framework for distributed hydrologic model identification and calibration that jointly constrains the model response (i.e., streamflows) as well as a set of model state variables (i.e., water storages) to observations. This framework is set up in the form of multi-objective optimization, where multiple performance criteria are defined and used to simultaneously evaluate the fidelity of the model to streamflow observations and observed (estimated) changes of water storage in the gridded landscape over daily and monthly time scales. The time series of estimated changes in total water storage (including soil, canopy, snow and pond storages) used in this study were derived from an experimental study enhanced by the information obtained from the GRACE satellite. We test this framework on the calibration of a Land Surface Scheme-Hydrology model, called MESH (Modélisation Environmentale Communautaire - Surface and Hydrology), for the Saskatchewan River basin. Pareto Archived Dynamically Dimensioned Search (PA-DDS) is used as the multi-objective optimization engine. The significance of using the developed framework is demonstrated in comparison with the results obtained through a conventional calibration approach to streamflow observations. The approach of incorporating water storage data into the model identification process can more potentially constrain the posterior parameter space, more comprehensively evaluate the model fidelity, and yield more credible predictions.

Seasonally-resolved trace element concentrations in stalagmites from a shallow cave in New Mexico

NASA Astrophysics Data System (ADS)

Sekhon, N.; Banner, J.; Miller, N. R.; Carlson, P. E.; Breecker, D.

2017-12-01

High-resolution (sub-annual/seasonal) paleoclimate records extending beyond the instrumental period are required to test climate models and better understand how climate warming/cooling and wetting/drying are manifested seasonally. This is particularly the case for areas such as the southwest United States where precipitation and temperature seasonality dictate the regional climate. Study of a 20thcentury stalagmite (Carlson et al., in prep) documented (1) seasonal variation in trace element compositions of a stalagmite from a shallow, well-ventilated cave and (2) demonstrated the seasonal variation in stalagmite Mg to be in agreement with predicted temperature-dependent fractionation between water and calcite. The seasonal nature of variability was constrained by monitoring the cave on a monthly basis (Casteel and Banner, 2015; Carlson et al., in prep). Here we expand on using stalagmites from shallow, well-ventilated caves as archives of seasonally-resolved climate recorders by studying trace element variations in two coeval modern stalagmites (SBFC-1 and SBFC-2) cored from Sitting Bull Falls, southern New Mexico. Seasonal cycles will be confirmed by analyzing Mg, Ba, and Sr in in-situ calcite precipitated on artificial substrates as available (July, Sept., and Nov. 2017). The chronology is constrained by semi-automated peak counting and 14C bomb-peak. In addition, principal component analyses of trace element data identify two primary underlying modes of trace element variability for soil-derived elements (Cu, Zn, and Fe) and bedrock-derived elements (Mg, Sr, and Ba). We hypothesize that the soil-derived elements are transported by seasonal infiltration of organic colloids and the bedrock-derived elements are ­­controlled by variability in cave air temperature, drip water, and calcite growth rate. The two modes of variability will be calibrated against instrumental data over the 20th century. When complete, these new seasonally resolved proxy records will constrain the pattern and mechanism of the regional climate in southwest United States with a focus on drought indicators.

Thermal and energetic constraints on ectotherm abundance: A global test using lizards

USGS Publications Warehouse

Buckley, L.B.; Rodda, G.H.; Jetz, W.

2008-01-01

Population densities of birds and mammals have been shown to decrease with body mass at approximately the same rate as metabolic rates increase, indicating that energetic needs constrain endotherm population densities. In ectotherms, the exponential increase of metabolic rate with body temperature suggests that environmental temperature may additionally constrain population densities. Here we test simple bioenergetic models for an ecologically important group of ectothermic vertebrates by examining 483 lizard populations. We find that lizard population densities decrease as a power law of body mass with a slope approximately inverse to the slope of the relationship between metabolic rates and body mass. Energy availability should limit population densities. As predicted, environmental productivity has a positive effect on lizard density, strengthening the relationship between lizard density and body mass. In contrast, the effect of environmental temperature is at most weak due to behavioral thermoregulation, thermal evolution, or the temperature dependence of ectotherm performance. Our results provide initial insights into how energy needs and availability differentially constrain ectotherm and endotherm density across broad spatial scales. ?? 2008 by the Ecological Society of America.

Thermal and energetic constraints on ectotherm abundance: a global test using lizards.

PubMed

Buckley, Lauren B; Rodda, Gordon H; Jetz, Walter

2008-01-01

Population densities of birds and mammals have been shown to decrease with body mass at approximately the same rate as metabolic rates increase, indicating that energetic needs constrain endotherm population densities. In ectotherms, the exponential increase of metabolic rate with body temperature suggests that environmental temperature may additionally constrain population densities. Here we test simple bioenergetic models for an ecologically important group of ectothermic vertebrates by examining 483 lizard populations. We find that lizard population densities decrease as a power law of body mass with a slope approximately inverse to the slope of the relationship between metabolic rates and body mass. Energy availability should limit population densities. As predicted, environmental productivity has a positive effect on lizard density, strengthening the relationship between lizard density and body mass. In contrast, the effect of environmental temperature is at most weak due to behavioral thermoregulation, thermal evolution, or the temperature dependence of ectotherm performance. Our results provide initial insights into how energy needs and availability differentially constrain ectotherm and endotherm density across broad spatial scales.

Longitudinal train dynamics model for a rail transit simulation system

DOE PAGES

Wang, Jinghui; Rakha, Hesham A.

2018-01-01

The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The calibration and validation work is based on data collected from the Portland light rail train fleet. The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The validity of the model is assessed by comparing instantaneous model predictions against field observations, and also evaluated in the domains of acceleration/deceleration versus speed and acceleration/deceleration versus distance. A test is conducted to investigate the adequacy of themore » model in simulation implementation. The results demonstrate that the proposed model can adequately capture instantaneous train dynamics, and provides good performance in the simulation test. Thus, the model provides a simple theoretical foundation for microscopic simulators and will significantly support the planning, management and control of railway transportation systems.« less

Longitudinal train dynamics model for a rail transit simulation system

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

Wang, Jinghui; Rakha, Hesham A.

The paper develops a longitudinal train dynamics model in support of microscopic railway transportation simulation. The model can be calibrated without any mechanical data making it ideal for implementation in transportation simulators. The calibration and validation work is based on data collected from the Portland light rail train fleet. The calibration procedure is mathematically formulated as a constrained non-linear optimization problem. The validity of the model is assessed by comparing instantaneous model predictions against field observations, and also evaluated in the domains of acceleration/deceleration versus speed and acceleration/deceleration versus distance. A test is conducted to investigate the adequacy of themore » model in simulation implementation. The results demonstrate that the proposed model can adequately capture instantaneous train dynamics, and provides good performance in the simulation test. Thus, the model provides a simple theoretical foundation for microscopic simulators and will significantly support the planning, management and control of railway transportation systems.« less

Measurement and analysis of critical crack tip processes during fatigue crack growth

NASA Technical Reports Server (NTRS)

Davidson, D. L.; Hudak, S. J.; Dexter, R. J.

1985-01-01

The mechanics of fatigue crack growth under constant-amplitudes and variable-amplitude loading were examined. Critical loading histories involving relatively simple overload and overload/underload cycles were studied to provide a basic understanding of the underlying physical processes controlling crack growth. The material used for this study was 7091-T7E69, a powder metallurgy aluminum alloy. Local crack-tip parameters were measured at various times before, during, and after the overloads, these include crack-tip opening loads and displacements, and crack-tip strain fields. The latter were useed, in combination with the materials cyclic and monotonic stress-strain properties, to compute crack-tip residual stresses. The experimental results are also compared with analytical predictions obtained using the FAST-2 computer code. The sensitivity of the analytical model to constant-amplitude fatigue crack growth rate properties and to through-thickness constrain are studied.

Vesiculation of basaltic magma during eruption

USGS Publications Warehouse

Mangan, Margaret T.; Cashman, Katharine V.; Newman, Sally

1993-01-01

Vesicle size distributions in vent lavas from the Pu'u'O'o-Kupaianaha eruption of Kilauea volcano are used to estimate nucleation and growth rates of H2O-rich gas bubbles in basaltic magma nearing the earth's surface (≤120 m depth). By using well-constrained estimates for the depth of volatile exsolution and magma ascent rate, nucleation rates of 35.9 events ⋅ cm-3 ⋅ s-1 and growth rates of 3.2 x 10-4cm/s are determined directly from size-distribution data. The results are consistent with diffusion-controlled growth as predicted by a parabolic growth law. This empirical approach is not subject to the limitations inherent in classical nucleation and growth theory and provides the first direct measurement of vesiculation kinetics in natural settings. In addition, perturbations in the measured size distributions are used to examine bubble escape, accumulation, and coalescence prior to the eruption of magma.

Optimizing an Actuator Array for the Control of Multi-Frequency Noise in Aircraft Interiors

NASA Technical Reports Server (NTRS)

Palumbo, D. L.; Padula, S. L.

1997-01-01

Techniques developed for selecting an optimized actuator array for interior noise reduction at a single frequency are extended to the multi-frequency case. Transfer functions for 64 actuators were obtained at 5 frequencies from ground testing the rear section of a fully trimmed DC-9 fuselage. A single loudspeaker facing the left side of the aircraft was the primary source. A combinatorial search procedure (tabu search) was employed to find optimum actuator subsets of from 2 to 16 actuators. Noise reduction predictions derived from the transfer functions were used as a basis for evaluating actuator subsets during optimization. Results indicate that it is necessary to constrain actuator forces during optimization. Unconstrained optimizations selected actuators which require unrealistically large forces. Two methods of constraint are evaluated. It is shown that a fast, but approximate, method yields results equivalent to an accurate, but computationally expensive, method.

A method to stabilize linear systems using eigenvalue gradient information

NASA Technical Reports Server (NTRS)

Wieseman, C. D.

1985-01-01

Formal optimization methods and eigenvalue gradient information are used to develop a stabilizing control law for a closed loop linear system that is initially unstable. The method was originally formulated by using direct, constrained optimization methods with the constraints being the real parts of the eigenvalues. However, because of problems in trying to achieve stabilizing control laws, the problem was reformulated to be solved differently. The method described uses the Davidon-Fletcher-Powell minimization technique to solve an indirect, constrained minimization problem in which the performance index is the Kreisselmeier-Steinhauser function of the real parts of all the eigenvalues. The method is applied successfully to solve two different problems: the determination of a fourth-order control law stabilizes a single-input single-output active flutter suppression system and the determination of a second-order control law for a multi-input multi-output lateral-directional flight control system. Various sets of design variables and initial starting points were chosen to show the robustness of the method.

Status Report on Speech Research. A Report on the Status and Progress of Studies on the Nature of Speech, Instrumentation for Its Investigation, and Practical Applications.

DTIC Science & Technology

1984-08-01

6, 391-395. Abbs, J. H., & Gracco, V. L. (in press). Control of complex motor gestures 0 and orofacial muscle responses to load perturbations of the...E2, and E, are on the same world line where %,! E. is causally constrained by E2 and E. is causally constrained by El. You take pains to note that the

Assessment of the interactions between economic growth and industrial wastewater discharges using co-integration analysis: a case study for China's Hunan Province.

PubMed

Xiao, Qiang; Gao, Yang; Hu, Dan; Tan, Hong; Wang, Tianxiang

2011-07-01

We have investigated the interactions between economic growth and industrial wastewater discharge from 1978 to 2007 in China's Hunan Province using co-integration theory and an error-correction model. Two main economic growth indicators and four representative industrial wastewater pollutants were selected to demonstrate the interaction mechanism. We found a long-term equilibrium relationship between economic growth and the discharge of industrial pollutants in wastewater between 1978 and 2007 in Hunan Province. The error-correction mechanism prevented the variable expansion for long-term relationship at quantity and scale, and the size of the error-correction parameters reflected short-term adjustments that deviate from the long-term equilibrium. When economic growth changes within a short term, the discharge of pollutants will constrain growth because the values of the parameters in the short-term equation are smaller than those in the long-term co-integrated regression equation, indicating that a remarkable long-term influence of economic growth on the discharge of industrial wastewater pollutants and that increasing pollutant discharge constrained economic growth. Economic growth is the main driving factor that affects the discharge of industrial wastewater pollutants in Hunan Province. On the other hand, the discharge constrains economic growth by producing external pressure on growth, although this feedback mechanism has a lag effect. Economic growth plays an important role in explaining the predicted decomposition of the variance in the discharge of industrial wastewater pollutants, but this discharge contributes less to predictions of the variations in economic growth.

Assessment of the Interactions between Economic Growth and Industrial Wastewater Discharges Using Co-integration Analysis: A Case Study for China’s Hunan Province

PubMed Central

Xiao, Qiang; Gao, Yang; Hu, Dan; Tan, Hong; Wang, Tianxiang

2011-01-01

We have investigated the interactions between economic growth and industrial wastewater discharge from 1978 to 2007 in China’s Hunan Province using co-integration theory and an error-correction model. Two main economic growth indicators and four representative industrial wastewater pollutants were selected to demonstrate the interaction mechanism. We found a long-term equilibrium relationship between economic growth and the discharge of industrial pollutants in wastewater between 1978 and 2007 in Hunan Province. The error-correction mechanism prevented the variable expansion for long-term relationship at quantity and scale, and the size of the error-correction parameters reflected short-term adjustments that deviate from the long-term equilibrium. When economic growth changes within a short term, the discharge of pollutants will constrain growth because the values of the parameters in the short-term equation are smaller than those in the long-term co-integrated regression equation, indicating that a remarkable long-term influence of economic growth on the discharge of industrial wastewater pollutants and that increasing pollutant discharge constrained economic growth. Economic growth is the main driving factor that affects the discharge of industrial wastewater pollutants in Hunan Province. On the other hand, the discharge constrains economic growth by producing external pressure on growth, although this feedback mechanism has a lag effect. Economic growth plays an important role in explaining the predicted decomposition of the variance in the discharge of industrial wastewater pollutants, but this discharge contributes less to predictions of the variations in economic growth. PMID:21845167

Relationships between digestive efficiency and metabolomic profiles of serum and intestinal contents in chickens.

PubMed

Beauclercq, Stéphane; Nadal-Desbarats, Lydie; Hennequet-Antier, Christelle; Gabriel, Irène; Tesseraud, Sophie; Calenge, Fanny; Le Bihan-Duval, Elisabeth; Mignon-Grasteau, Sandrine

2018-04-27

The increasing cost of conventional feedstuffs has bolstered interest in genetic selection for digestive efficiency (DE), a component of feed efficiency, assessed by apparent metabolisable energy corrected to zero nitrogen retention (AMEn). However, its measurement is time-consuming and constraining, and its relationship with metabolic efficiency poorly understood. To simplify selection for this trait, we searched for indirect metabolic biomarkers through an analysis of the serum metabolome using nuclear magnetic resonance ( 1 H NMR). A partial least squares (PLS) model including six amino acids and two derivatives from butyrate predicted 59% of AMEn variability. Moreover, to increase our knowledge of the molecular mechanisms controlling DE, we investigated 1 H NMR metabolomes of ileal, caecal, and serum contents by fitting canonical sparse PLS. This analysis revealed strong associations between metabolites and DE. Models based on the ileal, caecal, and serum metabolome respectively explained 77%, 78%, and 74% of the variability of AMEn and its constitutive components (utilisation of starch, lipids, and nitrogen). In our conditions, the metabolites presenting the strongest associations with AMEn were proline in the serum, fumarate in the ileum and glucose in caeca. This study shows that serum metabolomics offers new opportunities to predict chicken DE.

Constraining slip rates and spacings for active normal faults

NASA Astrophysics Data System (ADS)

Cowie, Patience A.; Roberts, Gerald P.

2001-12-01

Numerous observations of extensional provinces indicate that neighbouring faults commonly slip at different rates and, moreover, may be active over different time intervals. These published observations include variations in slip rate measured along-strike of a fault array or fault zone, as well as significant across-strike differences in the timing and rates of movement on faults that have a similar orientation with respect to the regional stress field. Here we review published examples from the western USA, the North Sea, and central Greece, and present new data from the Italian Apennines that support the idea that such variations are systematic and thus to some extent predictable. The basis for the prediction is that: (1) the way in which a fault grows is fundamentally controlled by the ratio of maximum displacement to length, and (2) the regional strain rate must remain approximately constant through time. We show how data on fault lengths and displacements can be used to model the observed patterns of long-term slip rate where measured values are sparse. Specifically, we estimate the magnitude of spatial variation in slip rate along-strike and relate it to the across-strike spacing between active faults.

Evaluating an image-fusion algorithm with synthetic-image-generation tools

NASA Astrophysics Data System (ADS)

Gross, Harry N.; Schott, John R.

1996-06-01

An algorithm that combines spectral mixing and nonlinear optimization is used to fuse multiresolution images. Image fusion merges images of different spatial and spectral resolutions to create a high spatial resolution multispectral combination. High spectral resolution allows identification of materials in the scene, while high spatial resolution locates those materials. In this algorithm, conventional spectral mixing estimates the percentage of each material (called endmembers) within each low resolution pixel. Three spectral mixing models are compared; unconstrained, partially constrained, and fully constrained. In the partially constrained application, the endmember fractions are required to sum to one. In the fully constrained application, all fractions are additionally required to lie between zero and one. While negative fractions seem inappropriate, they can arise from random spectral realizations of the materials. In the second part of the algorithm, the low resolution fractions are used as inputs to a constrained nonlinear optimization that calculates the endmember fractions for the high resolution pixels. The constraints mirror the low resolution constraints and maintain consistency with the low resolution fraction results. The algorithm can use one or more higher resolution sharpening images to locate the endmembers to high spatial accuracy. The algorithm was evaluated with synthetic image generation (SIG) tools. A SIG developed image can be used to control the various error sources that are likely to impair the algorithm performance. These error sources include atmospheric effects, mismodeled spectral endmembers, and variability in topography and illumination. By controlling the introduction of these errors, the robustness of the algorithm can be studied and improved upon. The motivation for this research is to take advantage of the next generation of multi/hyperspectral sensors. Although the hyperspectral images will be of modest to low resolution, fusing them with high resolution sharpening images will produce a higher spatial resolution land cover or material map.

Ethical Considerations in the Practical Application of the Unisa Socio-Critical Model of Student Success

ERIC Educational Resources Information Center

Fynn, Angelo

2016-01-01

The prediction and classification of student performance has always been a central concern within higher education institutions. It is therefore natural for higher education institutions to harvest and analyse student data to inform decisions on education provision in resource constrained South African environments. One of the drivers for the use…

The Postindustrial University: Fiscal Crisis and the Changing Structure of Academic Labour.

ERIC Educational Resources Information Center

Barrow, Clyde W.

This paper, in reflecting on socioeconomic trends that will affect higher education in the 1990s, argues for a "postindustrial" university model. The paper predicts that the current fiscal crisis in American higher education will persist throughout the 1990s as a result of: (1) slowly rising state appropriations, (2) market constrains on…

Predictors of Numeracy Performance in National Testing Programs: Insights from the Longitudinal Study of Australian Children

ERIC Educational Resources Information Center

Carmichael, Colin; MacDonald, Amy; McFarland-Piazza, Laura

2014-01-01

This article is based on an exploratory study that examines factors which predict children's performance on the numeracy component of the Australian National Assessment Program--Literacy and Numeracy (NAPLAN). Utilizing an ecological theoretical model, this study examines child, home and school variables which may enable or constrain NAPLAN…

Enhancing model prediction reliability through improved soil representation and constrained model auto calibration - A paired waterhsed study

USDA-ARS?s Scientific Manuscript database

Process based and distributed watershed models possess a large number of parameters that are not directly measured in field and need to be calibrated through matching modeled in-stream fluxes with monitored data. Recently, there have been waves of concern about the reliability of this common practic...

The added value of remote sensing products in constraining hydrological models

NASA Astrophysics Data System (ADS)

Nijzink, Remko C.; Almeida, Susana; Pechlivanidis, Ilias; Capell, René; Gustafsson, David; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; Sleziak, Patrik; Parajka, Juraj; Savenije, Hubert; Hrachowitz, Markus

2017-04-01

The calibration of a hydrological model still depends on the availability of streamflow data, even though more additional sources of information (i.e. remote sensed data products) have become more widely available. In this research, the model parameters of four different conceptual hydrological models (HYPE, HYMOD, TUW, FLEX) were constrained with remotely sensed products. The models were applied over 27 catchments across Europe to cover a wide range of climates, vegetation and landscapes. The fluxes and states of the models were correlated with the relevant products (e.g. MOD10A snow with modelled snow states), after which new a-posteriori parameter distributions were determined based on a weighting procedure using conditional probabilities. Briefly, each parameter was weighted with the coefficient of determination of the relevant regression between modelled states/fluxes and products. In this way, final feasible parameter sets were derived without the use of discharge time series. Initial results show that improvements in model performance, with regard to streamflow simulations, are obtained when the models are constrained with a set of remotely sensed products simultaneously. In addition, we present a more extensive analysis to assess a model's ability to reproduce a set of hydrological signatures, such as rising limb density or peak distribution. Eventually, this research will enhance our understanding and recommendations in the use of remotely sensed products for constraining conceptual hydrological modelling and improving predictive capability, especially for data sparse regions.

Design of a minimally constraining, passively supported gait training exoskeleton: ALEX II.

PubMed

Winfree, Kyle N; Stegall, Paul; Agrawal, Sunil K

2011-01-01

This paper discusses the design of a new, minimally constraining, passively supported gait training exoskeleton known as ALEX II. This device builds on the success and extends the features of the ALEX I device developed at the University of Delaware. Both ALEX (Active Leg EXoskeleton) devices have been designed to supply a controllable torque to a subject's hip and knee joint. The current control strategy makes use of an assist-as-needed algorithm. Following a brief review of previous work motivating this redesign, we discuss the key mechanical features of the new ALEX device. A short investigation was conducted to evaluate the effectiveness of the control strategy and impact of the exoskeleton on the gait of six healthy subjects. This paper concludes with a comparison between the subjects' gait both in and out of the exoskeleton. © 2011 IEEE

Morphoelastic control of gastro-intestinal organogenesis: Theoretical predictions and numerical insights

NASA Astrophysics Data System (ADS)

Balbi, V.; Kuhl, E.; Ciarletta, P.

2015-05-01

With nine meters in length, the gastrointestinal tract is not only our longest, but also our structurally most diverse organ. During embryonic development, it evolves as a bilayered tube with an inner endodermal lining and an outer mesodermal layer. Its inner surface displays a wide variety of morphological patterns, which are closely correlated to digestive function. However, the evolution of these intestinal patterns remains poorly understood. Here we show that geometric and mechanical factors can explain intestinal pattern formation. Using the nonlinear field theories of mechanics, we model surface morphogenesis as the instability problem of constrained differential growth. To allow for internal and external expansion, we model the gastrointestinal tract with homogeneous Neumann boundary conditions. To establish estimates for the folding pattern at the onset of folding, we perform a linear stability analysis supplemented by the perturbation theory. To predict pattern evolution in the post-buckling regime, we perform a series of nonlinear finite element simulations. Our model explains why longitudinal folds emerge in the esophagus with a thick and stiff outer layer, whereas circumferential folds emerge in the jejunum with a thinner and softer outer layer. In intermediate regions like the feline esophagus, longitudinal and circumferential folds emerge simultaneously. Our model could serve as a valuable tool to explain and predict alterations in esophageal morphology as a result of developmental disorders or certain digestive pathologies including food allergies.

Wavelength Dependent Luminosity Functions for Super Star Clusters

NASA Astrophysics Data System (ADS)

Garmany, Catharine

1997-07-01

Starburst galaxies, considered to exhibit enhanced star formation on a galaxy-wide scale, have now been found with HST to contain very intense knots of star formation, referred to as ``super star clusters'', or SSCs. A steepening of the luminosity function with increasing wavelength for young burst populations, such as SSCs, has recently been predicted by Hogg & Phinney {1997}. This prediction, not previously addressed in the literature, is straightforward to test with multi- wavelength photometry. Using the colors of the SSCs in a galaxy in combination with the difference in slopes of the luminosity functions derived from different wavelength bands and applying population synthesis models, we can also constrain the high mass stellar initial mass function {IMF}. Recent work has suggested that the slope of the IMF is roughly constant in a variety of local environments, from galactic OB associations to the closest analog of a super star cluster, R136 in the LMC. This investigation will allow us to compare the IMFs in the extreme environments of SSCs in starburst galaxies to IMFs found locally in the Galaxy, LMC, and SMC. Archival imaging data in both the UV and optical bands is available for about 10 young starburst systems. These data will allow us to test the predictions of Hogg & Phinney, as well as constrain the IMF for environments not found in the nearby universe.

Male mate choice influences female promiscuity in Soay sheep

PubMed Central

Preston, B.T.; Stevenson, I.R.; Pemberton, J.M.; Coltman, D.W.; Wilson, K.

2005-01-01

In most animal species, males are predicted to compete for reproductive opportunities, while females are expected to choose between potential mates. However, when males’ rate of reproduction is constrained, or females vary widely in ‘quality’, male mate choice is also predicted to occur. Such conditions exist in the promiscuous mating system of feral Soay sheep on St Kilda, Scotland, where a highly synchronized mating season, intense sperm competition and limitations on sperm production constrain males’ potential reproductive rate, and females vary substantially in their ability to produce successful offspring. We show that, consistent with predictions, competitive rams focus their mating activity and siring success towards heavier females with higher inclusive fitness. To our knowledge, this is the first time that male mate choice has been identified and shown to lead to assortative patterns of parentage in a natural mammalian system, and occurs despite fierce male–male competition for mates. An additional consequence of assortative mating in this population is that lighter females experience a series of unstable consorts with less adept rams, and hence are mated by a greater number of males during their oestrus. We have thus also identified a novel male-driven mechanism that generates variation in female promiscuity, which suggests that the high levels of female promiscuity in this system are not part of an adaptive female tactic to intensify post-copulatory competition between males. PMID:15734690

Male mate choice influences female promiscuity in Soay sheep.

PubMed

Preston, B T; Stevenson, I R; Pemberton, J M; Coltman, D W; Wilson, K

2005-02-22

In most animal species, males are predicted to compete for reproductive opportunities, while females are expected to choose between potential mates. However, when males' rate of reproduction is constrained, or females vary widely in 'quality', male mate choice is also predicted to occur. Such conditions exist in the promiscuous mating system of feral Soay sheep on St Kilda, Scotland, where a highly synchronized mating season, intense sperm competition and limitations on sperm production constrain males' potential reproductive rate, and females vary substantially in their ability to produce successful offspring. We show that, consistent with predictions, competitive rams focus their mating activity and siring success towards heavier females with higher inclusive fitness. To our knowledge, this is the first time that male mate choice has been identified and shown to lead to assortative patterns of parentage in a natural mammalian system, and occurs despite fierce male-male competition for mates. An additional consequence of assortative mating in this population is that lighter females experience a series of unstable consorts with less adept rams, and hence are mated by a greater number of males during their oestrus. We have thus also identified a novel male-driven mechanism that generates variation in female promiscuity, which suggests that the high levels of female promiscuity in this system are not part of an adaptive female tactic to intensify post-copulatory competition between males.

Constraining hot plasma in a non-flaring solar active region with FOXSI hard X-ray observations

NASA Astrophysics Data System (ADS)

Ishikawa, Shin-nosuke; Glesener, Lindsay; Christe, Steven; Ishibashi, Kazunori; Brooks, David H.; Williams, David R.; Shimojo, Masumi; Sako, Nobuharu; Krucker, Säm

2014-12-01

We present new constraints on the high-temperature emission measure of a non-flaring solar active region using observations from the recently flown Focusing Optics X-ray Solar Imager (FOXSI) sounding rocket payload. FOXSI has performed the first focused hard X-ray (HXR) observation of the Sun in its first successful flight on 2012 November 2. Focusing optics, combined with small strip detectors, enable high-sensitivity observations with respect to previous indirect imagers. This capability, along with the sensitivity of the HXR regime to high-temperature emission, offers the potential to better characterize high-temperature plasma in the corona as predicted by nanoflare heating models. We present a joint analysis of the differential emission measure (DEM) of active region 11602 using coordinated observations by FOXSI, Hinode/XRT, and Hinode/EIS. The Hinode-derived DEM predicts significant emission measure between 1 MK and 3 MK, with a peak in the DEM predicted at 2.0-2.5 MK. The combined XRT and EIS DEM also shows emission from a smaller population of plasma above 8 MK. This is contradicted by FOXSI observations that significantly constrain emission above 8 MK. This suggests that the Hinode DEM analysis has larger uncertainties at higher temperatures and that > 8 MK plasma above an emission measure of 3 × 1044 cm-3 is excluded in this active region.

Marine fish may be biochemically constrained from inhabiting the deepest ocean depths

PubMed Central

Yancey, Paul H.; Gerringer, Mackenzie E.; Drazen, Jeffrey C.; Rowden, Ashley A.; Jamieson, Alan

2014-01-01

No fish have been found in the deepest 25% of the ocean (8,400–11,000 m). This apparent absence has been attributed to hydrostatic pressure, although direct evidence is wanting because of the lack of deepest-living species to study. The common osmolyte trimethylamine N-oxide (TMAO) stabilizes proteins against pressure and increases with depth, going from 40 to 261 mmol/kg in teleost fishes from 0 to 4,850 m. TMAO accumulation with depth results in increasing internal osmolality (typically 350 mOsmol/kg in shallow species compared with seawater's 1,100 mOsmol/kg). Preliminary extrapolation of osmolalities of predicted isosmotic state at 8,000–8,500 m may indicate a possible physiological limit, as greater depths would require reversal of osmotic gradients and, thus, osmoregulatory systems. We tested this prediction by capturing five of the second-deepest known fish, the hadal snailfish (Notoliparis kermadecensis; Liparidae), from 7,000 m in the Kermadec Trench. We found their muscles to have a TMAO content of 386 ± 18 mmol/kg and osmolality of 991 ± 22 mOsmol/kg. These data fit previous extrapolations and, combined with new osmolalities from bathyal and abyssal fishes, predict isosmotic state at 8,200 m. This is previously unidentified evidence that biochemistry could constrain the depth of a large, complex taxonomic group. PMID:24591588

Where does the carbon go? A model–data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites

PubMed Central

De Kauwe, Martin G; Medlyn, Belinda E; Zaehle, Sönke; Walker, Anthony P; Dietze, Michael C; Wang, Ying-Ping; Luo, Yiqi; Jain, Atul K; El-Masri, Bassil; Hickler, Thomas; Wårlind, David; Weng, Ensheng; Parton, William J; Thornton, Peter E; Wang, Shusen; Prentice, I Colin; Asao, Shinichi; Smith, Benjamin; McCarthy, Heather R; Iversen, Colleen M; Hanson, Paul J; Warren, Jeffrey M; Oren, Ram; Norby, Richard J

2014-01-01

Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets. PMID:24844873

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

NASA Astrophysics Data System (ADS)

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 application of costly treatments. This model will incorporate information from remote sensing, in-situ weather sources, soil measurements, crop models, and tacit farmer knowledge of the relative productivity of the selected control regions of the farm to provide incremental advice throughout the growing season on water and chemical treatments. Genetic and meta-heuristic algorithms will be used to solve the constrained optimization problem that possesses complex constraints and a non-linear objective function. *

Numerical Estimation of Balanced and Falling States for Constrained Legged Systems

NASA Astrophysics Data System (ADS)

Mummolo, Carlotta; Mangialardi, Luigi; Kim, Joo H.

2017-08-01

Instability and risk of fall during standing and walking are common challenges for biped robots. While existing criteria from state-space dynamical systems approach or ground reference points are useful in some applications, complete system models and constraints have not been taken into account for prediction and indication of fall for general legged robots. In this study, a general numerical framework that estimates the balanced and falling states of legged systems is introduced. The overall approach is based on the integration of joint-space and Cartesian-space dynamics of a legged system model. The full-body constrained joint-space dynamics includes the contact forces and moments term due to current foot (or feet) support and another term due to altered contact configuration. According to the refined notions of balanced, falling, and fallen, the system parameters, physical constraints, and initial/final/boundary conditions for balancing are incorporated into constrained nonlinear optimization problems to solve for the velocity extrema (representing the maximum perturbation allowed to maintain balance without changing contacts) in the Cartesian space at each center-of-mass (COM) position within its workspace. The iterative algorithm constructs the stability boundary as a COM state-space partition between balanced and falling states. Inclusion in the resulting six-dimensional manifold is a necessary condition for a state of the given system to be balanced under the given contact configuration, while exclusion is a sufficient condition for falling. The framework is used to analyze the balance stability of example systems with various degrees of complexities. The manifold for a 1-degree-of-freedom (DOF) legged system is consistent with the experimental and simulation results in the existing studies for specific controller designs. The results for a 2-DOF system demonstrate the dependency of the COM state-space partition upon joint-space configuration (elbow-up vs. elbow-down). For both 1- and 2-DOF systems, the results are validated in simulation environments. Finally, the manifold for a biped walking robot is constructed and illustrated against its single-support walking trajectories. The manifold identified by the proposed framework for any given legged system can be evaluated beforehand as a system property and serves as a map for either a specified state or a specific controller's performance.

Simulation of Constrained Musculoskeletal Systems in Task Space.

PubMed

Stanev, Dimitar; Moustakas, Konstantinos

2018-02-01

This paper proposes an operational task space formalization of constrained musculoskeletal systems, motivated by its promising results in the field of robotics. The change of representation requires different algorithms for solving the inverse and forward dynamics simulation in the task space domain. We propose an extension to the direct marker control and an adaptation of the computed muscle control algorithms for solving the inverse kinematics and muscle redundancy problems, respectively. Experimental evaluation demonstrates that this framework is not only successful in dealing with the inverse dynamics problem, but also provides an intuitive way of studying and designing simulations, facilitating assessment prior to any experimental data collection. The incorporation of constraints in the derivation unveils an important extension of this framework toward addressing systems that use absolute coordinates and topologies that contain closed kinematic chains. Task space projection reveals a more intuitive encoding of the motion planning problem, allows for better correspondence between observed and estimated variables, provides the means to effectively study the role of kinematic redundancy, and most importantly, offers an abstract point of view and control, which can be advantageous toward further integration with high level models of the precommand level. Task-based approaches could be adopted in the design of simulation related to the study of constrained musculoskeletal systems.

Studies of Sound Absorption by and Transmission Through Layers of Elastic Noise Control Foams: Finite Element Modeling and Effects of Anisotropy

NASA Astrophysics Data System (ADS)

Kang, Yeon June

In this thesis an elastic-absorption finite element model of isotropic elastic porous noise control materials is first presented as a means of investigating the effects of finite dimension and edge constraints on the sound absorption by, and transmission through, layers of acoustical foams. Methods for coupling foam finite elements with conventional acoustic and structural finite elements are also described. The foam finite element model based on the Biot theory allows for the simultaneous propagation of the three types of waves known to exist in an elastic porous material. Various sets of boundary conditions appropriate for modeling open, membrane-sealed and panel-bonded foam surfaces are formulated and described. Good agreement was achieved when finite element predictions were compared with previously established analytical results for the plane wave absorption coefficient and transmission loss in the case of wave propagation both in foam-filled waveguides and through foam-lined double panel structures of infinite lateral extent. The primary effect of the edge constraints of a foam layer was found to be an acoustical stiffening of the foam. Constraining the ends of the facing panels in foam-lined double panel systems was also found to increase the sound transmission loss significantly in the low frequency range. In addition, a theoretical multi-dimensional model for wave propagation in anisotropic elastic porous materials was developed to study the effect of anisotropy on the sound transmission of foam-lined noise control treatments. The predictions of the theoretical anisotropic model have been compared with experimental measurements for the random incidence sound transmission through double panel structure lined with polyimide foam. The predictions were made by using the measured and estimated macroscopic physical parameters of polyimide foam samples which were known to be anisotropic. It has been found that the macroscopic physical parameters in the direction normal to the face of foam layer play the principal role in determining the acoustical behavior of polyimide foam layers, although more satisfactory agreement between experimental measurements and theoretical predictions of transmission loss is obtained when the anisotropic properties are allowed in the model.

Controls on Lava Flow Morphology and Propagation: Using Laboratory Analogue Experiments

NASA Astrophysics Data System (ADS)

Peters, S.; Clarke, A. B.

2017-12-01

The morphology of lava flows is controlled by eruption rate, composition, cooling rate, and topography [Fink and Griffiths, 1990; Gregg and Fink, 2000, 2006]. Lava flows are used to understand how volcanoes, volcanic fields, and igneous provinces formed and evolved [Gregg and Fink., 1996; Sheth, 2006]. This is particularly important for other planets where compositional data is limited and historical context is nonexistent. Numerical modeling of lava flows remains challenging, but has been aided by laboratory analog experiments [Gregg and Keszrthelyi, 2004; Soule and Cashman, 2004]. Experiments using polyethylene glycol (PEG) 600 wax have been performed to understand lava flow emplacement [Fink and Griffiths, 1990, 1992; Gregg and Fink, 2000]. These experiments established psi (hereafter denoted by Ψ), a dimensionless parameter that relates crust formation and advection timescales of a viscous gravity current. Four primary flow morphologies corresponding to discreet Ψ ranges were observed. Gregg and Fink [2000] also investigated flows on slopes and found that steeper slopes increase the effective effusion rate producing predicted morphologies at lower Ψ values. Additional work is needed to constrain the Ψ parameter space, evaluate the predictive capability of Ψ, and determine if the preserved flow morphology can be used to indicate the initial flow conditions. We performed 514 experiments to address the following controls on lava flow morphology: slope (n = 282), unsteadiness/pulsations (n = 58), slope & unsteadiness/pulsations (n = 174), distal processes, and emplacement vs. post-emplacement morphologies. Our slope experiments reveal a similar trend to Gregg and Fink [2000] with the caveat that very high and very low local & source eruption rates can reduce the apparent predictive capability of Ψ. Predicted Ψ morphologies were often produced halfway through the eruption. Our pulse experiments are expected to produce morphologies unique to each eruption rate and promote tube formation and compound flows. Post-emplacement morphologies are modified by a variety of factors (e.g. solidification, deflation), which may not preserve the initial morphology produced during an eruption. Relating this morphology to the eruption conditions is pertinent to understanding the evolution of planetary surfaces.

Clinical prediction and the idea of a population.

PubMed

Armstrong, David

2017-04-01

Using an analysis of the British Medical Journal over the past 170 years, this article describes how changes in the idea of a population have informed new technologies of medical prediction. These approaches have largely replaced older ideas of clinical prognosis based on understanding the natural histories of the underlying pathologies. The 19 th -century idea of a population, which provided a denominator for medical events such as births and deaths, was constrained in its predictive power by its method of enumerating individual bodies. During the 20 th century, populations were increasingly constructed through inferential techniques based on patient groups and samples seen to possess variable characteristics. The emergence of these new virtual populations created the conditions for the emergence of predictive algorithms that are used to foretell our medical futures.

Mission Data System Java Edition Version 7

NASA Technical Reports Server (NTRS)

Reinholtz, William K.; Wagner, David A.

2013-01-01

The Mission Data System framework defines closed-loop control system abstractions from State Analysis including interfaces for state variables, goals, estimators, and controllers that can be adapted to implement a goal-oriented control system. The framework further provides an execution environment that includes a goal scheduler, execution engine, and fault monitor that support the expression of goal network activity plans. Using these frameworks, adapters can build a goal-oriented control system where activity coordination is verified before execution begins (plan time), and continually during execution. Plan failures including violations of safety constraints expressed in the plan can be handled through automatic re-planning. This version optimizes a number of key interfaces and features to minimize dependencies, performance overhead, and improve reliability. Fault diagnosis and real-time projection capabilities are incorporated. This version enhances earlier versions primarily through optimizations and quality improvements that raise the technology readiness level. Goals explicitly constrain system states over explicit time intervals to eliminate ambiguity about intent, as compared to command-oriented control that only implies persistent intent until another command is sent. A goal network scheduling and verification process ensures that all goals in the plan are achievable before starting execution. Goal failures at runtime can be detected (including predicted failures) and handled by adapted response logic. Responses can include plan repairs (try an alternate tactic to achieve the same goal), goal shedding, ignoring the fault, cancelling the plan, or safing the system.

Diffusion-controlled garnet growth in siliceous dolomites of the Adamello contact aureole, N-Italy

NASA Astrophysics Data System (ADS)

Muller, T.; Fiebich, E.; Foster, C. T.

2012-12-01

Texture forming processes are controlled by many factors, such as material transport through polycrystalline materials, surface kinetics, fluid flow, and many others. In metamorphic rocks, texture forming processes typically involve local reactions linked to net mass transfer which allows constraining the actual reaction path in more detail. In this study, we present geochemical data combined with textural modeling to constrain the conditions and reaction mechanism during contact metamorphic garnet growth in siliceous dolomites in the southern Adamello Massif, Italy. The metamorphic garnet porphyroblasts are poikiloblastic and idiomorphic in shape with a typical grain size ranging between 0.6-1 cm in diameter sitting in a matrix of calcite+diopside+anorthite+wollastonite. Inclusions in the grossular-rich garnets are almost uniquely diopside. On the hand specimen, garnets are surrounded by visible rims of about 0.6 mm indicating a diffusion-limited reaction mechanism to be responsible for the garnet formation. In the course of this study samples have been characterized by polarization microscopy, element x-ray maps using EMPA, cathodulominescence images and stable isotope analyses of carbon and oxygen of matrix carbonates. In addition, pseudosections have been calculated using the software package PerpleX (Connolly, 2005) based on the bulk chemistry of collected samples. Results indicate that the visible margin consists of a small rim (< 1 mm) purely consisting of recrystallized calcite adjacent to the garnet edge. The major part of the observed halo, however, is characterized by the absence of anorthite and wollastonite. The observed texture of garnet porphyroblasts growing and simultaneously forming an anorthite and wollastonite free margin can successfully be reproduced using the SEG program (Foster, 1993), which assumes diffusive mass transport. Therefore the model constrains the diffusive fluxes of Ca, Mg, Al and Si by mass balance and the local Gibbs-Duhem equations on the reaction site. Assuming that the pore fluid is not saturated in CO2, which is justified for the assumption of fluid-infiltration during contact metamorphism, the model predicts the wollastonite halo to be about the same size as the anorthite halo. Interestingly, the model also predicts the small diopside-free calcite margin surrounding the garnet interface, which is also observed in the thin section of the natural sample. Taken together, we interpret the garnet growth to be the consequence of the breakdown of anorthite + wollastonite + calcite at water-rich (XCO2 < 0.2) conditions around 600 °C. Preliminary modeling results suggest that the effective relative diffusion coefficients for Si, Mg and Al are not equal producing the diopside-free calcite rim surrounding the garnet edge. Connolly, J.A.D., 2005, Computation of phase equilibria by linear programming: A tool for geodynamic modeling and its application to subduction zone decarbonation. EPSL, 236 : p. 524-541. Foster, C.T., 1993, SEG93: A program to model metamorphic textures: Geological Society of America Abstracts with Programs, v. 25, no. 6, p. A264.

Constraining geostatistical models with hydrological data to improve prediction realism

NASA Astrophysics Data System (ADS)

Demyanov, V.; Rojas, T.; Christie, M.; Arnold, D.

2012-04-01

Geostatistical models reproduce spatial correlation based on the available on site data and more general concepts about the modelled patters, e.g. training images. One of the problem of modelling natural systems with geostatistics is in maintaining realism spatial features and so they agree with the physical processes in nature. Tuning the model parameters to the data may lead to geostatistical realisations with unrealistic spatial patterns, which would still honour the data. Such model would result in poor predictions, even though although fit the available data well. Conditioning the model to a wider range of relevant data provide a remedy that avoid producing unrealistic features in spatial models. For instance, there are vast amounts of information about the geometries of river channels that can be used in describing fluvial environment. Relations between the geometrical channel characteristics (width, depth, wave length, amplitude, etc.) are complex and non-parametric and are exhibit a great deal of uncertainty, which is important to propagate rigorously into the predictive model. These relations can be described within a Bayesian approach as multi-dimensional prior probability distributions. We propose a way to constrain multi-point statistics models with intelligent priors obtained from analysing a vast collection of contemporary river patterns based on previously published works. We applied machine learning techniques, namely neural networks and support vector machines, to extract multivariate non-parametric relations between geometrical characteristics of fluvial channels from the available data. An example demonstrates how ensuring geological realism helps to deliver more reliable prediction of a subsurface oil reservoir in a fluvial depositional environment.

Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

PubMed

Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

2016-05-01

Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

The role of ecosystem memory in predicting inter-annual variations of the tropical carbon balance.

NASA Astrophysics Data System (ADS)

Bloom, A. A.; Liu, J.; Bowman, K. W.; Konings, A. G.; Saatchi, S.; Worden, J. R.; Worden, H. M.; Jiang, Z.; Parazoo, N.; Williams, M. D.; Schimel, D.

2017-12-01

Understanding the trajectory of the tropical carbon balance remains challenging, in part due to large uncertainties in the integrated response of carbon cycle processes to climate variability. Satellite observations atmospheric CO2 from GOSAT and OCO-2, together with ancillary satellite measurements, provide crucial constraints on continental-scale terrestrial carbon fluxes. However, an integrated understanding of both climate forcings and legacy effects (or "ecosystem memory") on the terrestrial carbon balance is ultimately needed to reduce uncertainty on its future trajectory. Here we use the CARbon DAta-MOdel fraMework (CARDAMOM) diagnostic model-data fusion approach - constrained by an array of C cycle satellite surface observations, including MODIS leaf area, biomass, GOSAT solar-induced fluorescence, as well as "top-down" atmospheric inversion estimates of CO2 and CO surface fluxes from the NASA Carbon Monitoring System Flux (CMS-Flux) - to constrain and predict spatially-explicit tropical carbon state variables during 2010-2015. We find that the combined assimilation of land surface and atmospheric datasets places key constraints on the temperature sensitivity and first order carbon-water feedbacks throughout the tropics and combustion factors within biomass burning regions. By varying the duration of the assimilation period, we find that the prediction skill on inter-annual net biospheric exchange is primarily limited by record length rather than model structure and process representation. We show that across all tropical biomes, quantitative knowledge of memory effects - which account for 30-50% of interannual variations across the tropics - is critical for understanding and ultimately predicting the inter-annual tropical carbon balance.

Training Signaling Pathway Maps to Biochemical Data with Constrained Fuzzy Logic: Quantitative Analysis of Liver Cell Responses to Inflammatory Stimuli

PubMed Central

Morris, Melody K.; Saez-Rodriguez, Julio; Clarke, David C.; Sorger, Peter K.; Lauffenburger, Douglas A.

2011-01-01

Predictive understanding of cell signaling network operation based on general prior knowledge but consistent with empirical data in a specific environmental context is a current challenge in computational biology. Recent work has demonstrated that Boolean logic can be used to create context-specific network models by training proteomic pathway maps to dedicated biochemical data; however, the Boolean formalism is restricted to characterizing protein species as either fully active or inactive. To advance beyond this limitation, we propose a novel form of fuzzy logic sufficiently flexible to model quantitative data but also sufficiently simple to efficiently construct models by training pathway maps on dedicated experimental measurements. Our new approach, termed constrained fuzzy logic (cFL), converts a prior knowledge network (obtained from literature or interactome databases) into a computable model that describes graded values of protein activation across multiple pathways. We train a cFL-converted network to experimental data describing hepatocytic protein activation by inflammatory cytokines and demonstrate the application of the resultant trained models for three important purposes: (a) generating experimentally testable biological hypotheses concerning pathway crosstalk, (b) establishing capability for quantitative prediction of protein activity, and (c) prediction and understanding of the cytokine release phenotypic response. Our methodology systematically and quantitatively trains a protein pathway map summarizing curated literature to context-specific biochemical data. This process generates a computable model yielding successful prediction of new test data and offering biological insight into complex datasets that are difficult to fully analyze by intuition alone. PMID:21408212

Control of serpentinisation rate by reaction-induced cracking

NASA Astrophysics Data System (ADS)

Malvoisin, Benjamin; Brantut, Nicolas; Kaczmarek, Mary-Alix

2017-10-01

Serpentinisation of mantle rocks requires the generation and maintenance of transport pathways for water. The solid volume increase during serpentinisation can lead to stress build-up and trigger cracking, which ease fluid penetration into the rock. The quantitative effect of this reaction-induced cracking mechanism on reactive surface generation is poorly constrained, thus hampering our ability to predict serpentinisation rate in geological environments. Here we use a combined approach with numerical modelling and observations in natural samples to provide estimates of serpentinisation rate at mid-ocean ridges. We develop a micromechanical model to quantify the propagation of serpentinisation-induced cracks in olivine. The maximum crystallisation pressure deduced from thermodynamic calculations reaches several hundreds of megapascals but does not necessary lead to crack propagation if the olivine grain is subjected to high compressive stresses. The micromechanical model is then coupled to a simple geometrical model to predict reactive surface area formation during grain splitting, and thus bulk reaction rate. Our model reproduces quantitatively experimental kinetic data and the typical mesh texture formed during serpentinisation. We also compare the model results with olivine grain size distribution data obtained on natural serpentinised peridotites from the Marum ophiolite and the Papuan ultramafic belt (Papua New Guinea). The natural serpentinised peridotites show an increase of the number of olivine grains for a decrease of the mean grain size by one order of magnitude as reaction progresses from 5 to 40%. These results are in agreement with our model predictions, suggesting that reaction-induced cracking controls the serpentinisation rate. We use our model to estimate that, at mid-ocean ridges, serpentinisation occurs up to 12 km depth and reaction-induced cracking reduces the characteristic time of serpentinisation by one order of magnitude, down to values comprised between 10 and 1000 yr. The increase of effective pressure with depth also prevents cracking, which positions the peak in serpentinisation rate at shallower depths, 4 km above previous predictions.

Maximal oxygen uptake is proportional to muscle fiber oxidative capacity, from chronic heart failure patients to professional cyclists.

PubMed

van der Zwaard, Stephan; de Ruiter, C Jo; Noordhof, Dionne A; Sterrenburg, Renske; Bloemers, Frank W; de Koning, Jos J; Jaspers, Richard T; van der Laarse, Willem J

2016-09-01

V̇o2 max during whole body exercise is presumably constrained by oxygen delivery to mitochondria rather than by mitochondria's ability to consume oxygen. Humans and animals have been reported to exploit only 60-80% of their mitochondrial oxidative capacity at maximal oxygen uptake (V̇o2 max). However, ex vivo quantification of mitochondrial overcapacity is complicated by isolation or permeabilization procedures. An alternative method for estimating mitochondrial oxidative capacity is via enzyme histochemical quantification of succinate dehydrogenase (SDH) activity. We determined to what extent V̇o2 max attained during cycling exercise differs from mitochondrial oxidative capacity predicted from SDH activity of vastus lateralis muscle in chronic heart failure patients, healthy controls, and cyclists. V̇o2 max was assessed in 20 healthy subjects and 28 cyclists, and SDH activity was determined from biopsy cryosections of vastus lateralis using quantitative histochemistry. Similar data from our laboratory of 14 chronic heart failure patients and 6 controls were included. Mitochondrial oxidative capacity was predicted from SDH activity using estimated skeletal muscle mass and the relationship between ex vivo fiber V̇o2 max and SDH activity of isolated single muscle fibers and myocardial trabecula under hyperoxic conditions. Mitochondrial oxidative capacity predicted from SDH activity was related (r(2) = 0.89, P < 0.001) to V̇o2 max measured during cycling in subjects with V̇o2 max ranging from 9.8 to 79.0 ml·kg(-1)·min(-1) V̇o2 max measured during cycling was on average 90 ± 14% of mitochondrial oxidative capacity. We conclude that human V̇o2 max is related to mitochondrial oxidative capacity predicted from skeletal muscle SDH activity. Mitochondrial oxidative capacity is likely marginally limited by oxygen supply to mitochondria. Copyright © 2016 the American Physiological Society.

Influence of stochastic geometric imperfections on the load-carrying behaviour of thin-walled structures using constrained random fields

NASA Astrophysics Data System (ADS)

Lauterbach, S.; Fina, M.; Wagner, W.

2018-04-01

Since structural engineering requires highly developed and optimized structures, the thickness dependency is one of the most controversially debated topics. This paper deals with stability analysis of lightweight thin structures combined with arbitrary geometrical imperfections. Generally known design guidelines only consider imperfections for simple shapes and loading, whereas for complex structures the lower-bound design philosophy still holds. Herein, uncertainties are considered with an empirical knockdown factor representing a lower bound of existing measurements. To fully understand and predict expected bearable loads, numerical investigations are essential, including geometrical imperfections. These are implemented into a stand-alone program code with a stochastic approach to compute random fields as geometric imperfections that are applied to nodes of the finite element mesh of selected structural examples. The stochastic approach uses the Karhunen-Loève expansion for the random field discretization. For this approach, the so-called correlation length l_c controls the random field in a powerful way. This parameter has a major influence on the buckling shape, and also on the stability load. First, the impact of the correlation length is studied for simple structures. Second, since most structures for engineering devices are more complex and combined structures, these are intensively discussed with the focus on constrained random fields for e.g. flange-web-intersections. Specific constraints for those random fields are pointed out with regard to the finite element model. Further, geometrical imperfections vanish where the structure is supported.

The power of data mining in diagnosis of childhood pneumonia.

PubMed

Naydenova, Elina; Tsanas, Athanasios; Howie, Stephen; Casals-Pascual, Climent; De Vos, Maarten

2016-07-01

Childhood pneumonia is the leading cause of death of children under the age of 5 years globally. Diagnostic information on the presence of infection, severity and aetiology (bacterial versus viral) is crucial for appropriate treatment. However, the derivation of such information requires advanced equipment (such as X-rays) and clinical expertise to correctly assess observational clinical signs (such as chest indrawing); both of these are often unavailable in resource-constrained settings. In this study, these challenges were addressed through the development of a suite of data mining tools, facilitating automated diagnosis through quantifiable features. Findings were validated on a large dataset comprising 780 children diagnosed with pneumonia and 801 age-matched healthy controls. Pneumonia was identified via four quantifiable vital signs (98.2% sensitivity and 97.6% specificity). Moreover, it was shown that severity can be determined through a combination of three vital signs and two lung sounds (72.4% sensitivity and 82.2% specificity); addition of a conventional biomarker (C-reactive protein) further improved severity predictions (89.1% sensitivity and 81.3% specificity). Finally, we demonstrated that aetiology can be determined using three vital signs and a newly proposed biomarker (lipocalin-2) (81.8% sensitivity and 90.6% specificity). These results suggest that a suite of carefully designed machine learning tools can be used to support multi-faceted diagnosis of childhood pneumonia in resource-constrained settings, compensating for the shortage of expensive equipment and highly trained clinicians. © 2016 The Authors.

Thermodynamics of one-dimensional SU(4) and SU(6) fermions with attractive interactions

NASA Astrophysics Data System (ADS)

Hoffman, M. D.; Loheac, A. C.; Porter, W. J.; Drut, J. E.

2017-03-01

Motivated by advances in the manipulation and detection of ultracold atoms with multiple internal degrees of freedom, we present a finite-temperature lattice Monte Carlo calculation of the density and pressure equations of state, as well as Tan's contact, of attractively interacting SU(4)- and SU(6)-symmetric fermion systems in one spatial dimension. We also furnish a nonperturbative proof of a universal relation whereby quantities computable in the SU(2) case completely determine the virial coefficients of the SU(Nf) case. These one-dimensional systems are appealing because they can be experimentally realized in highly constrained traps and because of the dominant role played by correlations. The latter are typically nonperturbative and are crucial for understanding ground states and quantum phase transitions. While quantum fluctuations are typically overpowered by thermal ones in one and two dimensions at any finite temperature, we find that quantum effects do leave their imprint in thermodynamic quantities. Our calculations show that the additional degrees of freedom, relative to the SU(2) case, provide a dramatic enhancement of the density and pressure (in units of their noninteracting counterparts) in a wide region around vanishing β μ , where β is the inverse temperature and μ the chemical potential. As shown recently in experiments, the thermodynamics we explore here can be measured in a controlled and precise fashion in highly constrained traps and optical lattices. Our results are a prediction for such experiments in one dimension with atoms of high nuclear spin.

Source-Constrained Recall: Front-End and Back-End Control of Retrieval Quality

ERIC Educational Resources Information Center

Halamish, Vered; Goldsmith, Morris; Jacoby, Larry L.

2012-01-01

Research on the strategic regulation of memory accuracy has focused primarily on monitoring and control processes used to edit out incorrect information after it is retrieved (back-end control). Recent studies, however, suggest that rememberers also enhance accuracy by preventing the retrieval of incorrect information in the first place (front-end…

Maximizing the information learned from finite data selects a simple model

NASA Astrophysics Data System (ADS)

Mattingly, Henry H.; Transtrum, Mark K.; Abbott, Michael C.; Machta, Benjamin B.

2018-02-01

We use the language of uninformative Bayesian prior choice to study the selection of appropriately simple effective models. We advocate for the prior which maximizes the mutual information between parameters and predictions, learning as much as possible from limited data. When many parameters are poorly constrained by the available data, we find that this prior puts weight only on boundaries of the parameter space. Thus, it selects a lower-dimensional effective theory in a principled way, ignoring irrelevant parameter directions. In the limit where there are sufficient data to tightly constrain any number of parameters, this reduces to the Jeffreys prior. However, we argue that this limit is pathological when applied to the hyperribbon parameter manifolds generic in science, because it leads to dramatic dependence on effects invisible to experiment.

NO(x) Concentrations in the Upper Troposphere as a Result of Lightning

NASA Technical Reports Server (NTRS)

Penner, Joyce E.

1998-01-01

Upper tropospheric NO(x) controls, in part, the distribution of ozone in this greenhouse-sensitive region of the atmosphere. Many factors control NO(x) in this region. As a result it is difficult to assess uncertainties in anthropogenic perturbations to NO from aircraft, for example, without understanding the role of the other major NO(x) sources in the upper troposphere. These include in situ sources (lightning, aircraft), convection from the surface (biomass burning, fossil fuels, soils), stratospheric intrusions, and photochemical recycling from HNO3. This work examines the separate contribution to upper tropospheric "primary" NO(x) from each source category and uses two different chemical transport models (CTMS) to represent a range of possible atmospheric transport. Because aircraft emissions are tied to particular pressure altitudes, it is important to understand whether those emissions are placed in the model stratosphere or troposphere and to assess whether the models can adequately differentiate stratospheric air from tropospheric air. We examine these issues by defining a point-by-point "tracer tropopause" in order to differentiate stratosphere from troposphere in terms of NO(x) perturbations. Both models predict similar zonal average peak enhancements of primary NO(x) due to aircraft (approx. = 10-20 parts per trillion by volume (pptv) in both January and July); however, the placement of this peak is primarily in a region of large stratospheric influence in one model and centered near the level evaluated as the tracer tropopause in the second. Below the tracer tropopause, both models show negligible NO(x) derived directly from the stratospheric source. Also, they predict a typically low background of 1 - 20 pptv NO(x) when tropospheric HNO3 is constrained to be 100 pptv of HNO3. The two models calculate large differences in the total background NO(x) (defined as the source of NO(x) from lightning + stratosphere + surface + HNO3) when using identical loss frequencies for NO(x). This difference is primarily due to differing treatments of vertical transport. An improved diagnosis of this transport that is relevant to NO(x) requires either measurements of a surface-based tracer with a substantially shorter lifetime than Rn-222 or diagnosis and mapping of tracer correlations with different source signatures. Because of differences in transport by the two models we cannot constrain the source of NO(x) from lightning through comparison of average model concentrations with observations of NO(x).

Stochastic control system parameter identifiability

NASA Technical Reports Server (NTRS)

Lee, C. H.; Herget, C. J.

1975-01-01

The parameter identification problem of general discrete time, nonlinear, multiple input/multiple output dynamic systems with Gaussian white distributed measurement errors is considered. The knowledge of the system parameterization was assumed to be known. Concepts of local parameter identifiability and local constrained maximum likelihood parameter identifiability were established. A set of sufficient conditions for the existence of a region of parameter identifiability was derived. A computation procedure employing interval arithmetic was provided for finding the regions of parameter identifiability. If the vector of the true parameters is locally constrained maximum likelihood (CML) identifiable, then with probability one, the vector of true parameters is a unique maximal point of the maximum likelihood function in the region of parameter identifiability and the constrained maximum likelihood estimation sequence will converge to the vector of true parameters.

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

Ovchinnikov, Mikhail; Ackerman, Andrew; Avramov, Alex

Large-eddy simulations of mixed-phase Arctic clouds by 11 different models are analyzed with the goal of improving understanding and model representation of processes controlling the evolution of these clouds. In a case based on observations from the Indirect and Semi-Direct Aerosol Campaign (ISDAC), it is found that ice number concentration, Ni, exerts significant influence on the cloud structure. Increasing Ni leads to a substantial reduction in liquid water path (LWP) and potential cloud dissipation, in agreement with earlier studies. By comparing simulations with the same microphysics coupled to different dynamical cores as well as the same dynamics coupled to differentmore » microphysics schemes, it is found that the ice water path (IWP) is mainly controlled by ice microphysics, while the inter-model differences in LWP are largely driven by physics and numerics of the dynamical cores. In contrast to previous intercomparisons, all models here use the same ice particle properties (i.e., mass-size, mass-fall speed, and mass-capacitance relationships) and a common radiation parameterization. The constrained setup exposes the importance of ice particle size distributions (PSD) in influencing cloud evolution. A clear separation in LWP and IWP predicted by models with bin and bulk microphysical treatments is documented and attributed primarily to the assumed shape of ice PSD used in bulk schemes. Compared to the bin schemes that explicitly predict the PSD, schemes assuming exponential ice PSD underestimate ice growth by vapor deposition and overestimate mass-weighted fall speed leading to an underprediction of IWP by a factor of two in the considered case.« less

Robust model predictive control for multi-step short range spacecraft rendezvous

NASA Astrophysics Data System (ADS)

Zhu, Shuyi; Sun, Ran; Wang, Jiaolong; Wang, Jihe; Shao, Xiaowei

2018-07-01

This work presents a robust model predictive control (MPC) approach for the multi-step short range spacecraft rendezvous problem. During the specific short range phase concerned, the chaser is supposed to be initially outside the line-of-sight (LOS) cone. Therefore, the rendezvous process naturally includes two steps: the first step is to transfer the chaser into the LOS cone and the second step is to transfer the chaser into the aimed region with its motion confined within the LOS cone. A novel MPC framework named after Mixed MPC (M-MPC) is proposed, which is the combination of the Variable-Horizon MPC (VH-MPC) framework and the Fixed-Instant MPC (FI-MPC) framework. The M-MPC framework enables the optimization for the two steps to be implemented jointly rather than to be separated factitiously, and its computation workload is acceptable for the usually low-power processors onboard spacecraft. Then considering that disturbances including modeling error, sensor noise and thrust uncertainty may induce undesired constraint violations, a robust technique is developed and it is attached to the above M-MPC framework to form a robust M-MPC approach. The robust technique is based on the chance-constrained idea, which ensures that constraints can be satisfied with a prescribed probability. It improves the robust technique proposed by Gavilan et al., because it eliminates the unnecessary conservativeness by explicitly incorporating known statistical properties of the navigation uncertainty. The efficacy of the robust M-MPC approach is shown in a simulation study.

Hybrid Active/Passive Control of Sound Radiation from Panels with Constrained Layer Damping and Model Predictive Feedback Control

NASA Technical Reports Server (NTRS)

Cabell, Randolph H.; Gibbs, Gary P.

2000-01-01

There has been considerable interest over the past several years in applying feedback control methods to problems of structural acoustics. One problem of particular interest is the control of sound radiation from aircraft panels excited on one side by a turbulent boundary layer (TBL). TBL excitation appears as many uncorrelated sources acting on the panel, which makes it difficult to find a single reference signal that is coherent with the excitation. Feedback methods have no need for a reference signal, and are thus suited to this problem. Some important considerations for the structural acoustics problem include the fact that the required controller bandwidth can easily extend to several hundred Hertz, so a digital controller would have to operate at a few kilohertz. In addition, aircraft panel structures have a reasonably high modal density over this frequency range. A model based controller must therefore handle the modally dense system, or have some way to reduce the bandwidth of the problem. Further complicating the problem is the fact that the stiffness and dynamic properties of an aircraft panel can vary considerably during flight due to altitude changes resulting in significant resonant frequency shifts. These considerations make the tradeoff between robustness to changes in the system being controlled and controller performance especially important. Recent papers concerning the design and implementation of robust controllers for structural acoustic problems highlight the need to consider both performance and robustness when designing the controller. While robust control methods such as H1 can be used to balance performance and robustness, their implementation is not easy and requires assumptions about the types of uncertainties in the plant being controlled. Achieving a useful controller design may require many tradeoff studies of different types of parametric uncertainties in the system. Another approach to achieving robustness to plant changes is to make the controller adaptive. For example, a mathematical model of the plant could be periodically updated as the plant changes, and the feedback gains recomputed from the updated model. To be practical, this approach requires a simple plant model that can be updated quickly with reasonable computational requirements. A recent paper by the authors discussed one way to simplify a feedback controller, by reducing the number of actuators and sensors needed for good performance. The work was done on a tensioned aircraft-style panel excited on one side by TBL flow in a low speed wind tunnel. Actuation was provided by a piezoelectric (PZT) actuator mounted on the center of the panel. For sensing, the responses of four accelerometers, positioned to approximate the response of the first radiation mode of the panel, were summed and fed back through the controller. This single input-single output topology was found to have nearly the same noise reduction performance as a controller with fifteen accelerometers and three PZT patches. This paper extends the previous results by looking at how constrained layer damping (CLD) on a panel can be used to enhance the performance of the feedback controller thus providing a more robust and efficient hybrid active/passive system. The eventual goal is to use the CLD to reduce sound radiation at high frequencies, then implement a very simple, reduced order, low sample rate adaptive controller to attenuate sound radiation at low frequencies. Additionally this added damping smoothes phase transitions over the bandwidth which promotes robustness to natural frequency shifts. Experiments were conducted in a transmission loss facility on a clamped-clamped aluminum panel driven on one side by a loudspeaker. A generalized predictive control (GPC) algorithm, which is suited to online adaptation of its parameters, was used in single input-single output and multiple input-single output configurations. Because this was a preliminary look at the potential constrained layer damping for adaptive control, static feedback control with no online adaptation was used. Two configurations of CLD in addition to a bare panel configuration were studied. For each CLD configuration, two sensor arrangements for the feedback controller were compared. The first arrangement used fifteen accelerometers on the panel to estimate the responses of the first six radiation modes of the panel. The second sensor arrangement was simpler, using the summed responses of only four accelerometers to approximate the response of the first radiation mode of the panel. In all cases a PZT patch was mounted at the center of the panel for control input. The performance of the controller was quantified using the responses of the fifteen accelerometers on the panel to estimate radiated sound power. The paper begins with a brief discussion of the GPC algorithm and the experimental setup. The experimental results are discussed next, comparing the CLD and sensor configurations, followed by discussion and conclusions.

Predictions penetrate perception: Converging insights from brain, behaviour and disorder

PubMed Central

O’Callaghan, Claire; Kveraga, Kestutis; Shine, James M; Adams, Reginald B.; Bar, Moshe

2018-01-01

It is argued that during ongoing visual perception, the brain is generating top-down predictions to facilitate, guide and constrain the processing of incoming sensory input. Here we demonstrate that these predictions are drawn from a diverse range of cognitive processes, in order to generate the richest and most informative prediction signals. This is consistent with a central role for cognitive penetrability in visual perception. We review behavioural and mechanistic evidence that indicate a wide spectrum of domains—including object recognition, contextual associations, cognitive biases and affective state—that can directly influence visual perception. We combine these insights from the healthy brain with novel observations from neuropsychiatric disorders involving visual hallucinations, which highlight the consequences of imbalance between top-down signals and incoming sensory information. Together, these lines of evidence converge to indicate that predictive penetration, be it cognitive, social or emotional, should be considered a fundamental framework that supports visual perception. PMID:27222169

A distance constrained synaptic plasticity model of C. elegans neuronal network

NASA Astrophysics Data System (ADS)

Badhwar, Rahul; Bagler, Ganesh

2017-03-01

Brain research has been driven by enquiry for principles of brain structure organization and its control mechanisms. The neuronal wiring map of C. elegans, the only complete connectome available till date, presents an incredible opportunity to learn basic governing principles that drive structure and function of its neuronal architecture. Despite its apparently simple nervous system, C. elegans is known to possess complex functions. The nervous system forms an important underlying framework which specifies phenotypic features associated to sensation, movement, conditioning and memory. In this study, with the help of graph theoretical models, we investigated the C. elegans neuronal network to identify network features that are critical for its control. The 'driver neurons' are associated with important biological functions such as reproduction, signalling processes and anatomical structural development. We created 1D and 2D network models of C. elegans neuronal system to probe the role of features that confer controllability and small world nature. The simple 1D ring model is critically poised for the number of feed forward motifs, neuronal clustering and characteristic path-length in response to synaptic rewiring, indicating optimal rewiring. Using empirically observed distance constraint in the neuronal network as a guiding principle, we created a distance constrained synaptic plasticity model that simultaneously explains small world nature, saturation of feed forward motifs as well as observed number of driver neurons. The distance constrained model suggests optimum long distance synaptic connections as a key feature specifying control of the network.

Hydrogen and Oxygen Isotope Ratios in Body Water and Hair: Modeling Isotope Dynamics in Nonhuman Primates

PubMed Central

O’Grady, Shannon P.; Valenzuela, Luciano O.; Remien, Christopher H.; Enright, Lindsey E.; Jorgensen, Matthew J.; Kaplan, Jay R.; Wagner, Janice D.; Cerling, Thure E.; Ehleringer, James R.

2012-01-01

The stable isotopic composition of drinking water, diet, and atmospheric oxygen influence the isotopic composition of body water (2H/1H, 18O/16O expressed as δ2H and δ18O). In turn, body water influences the isotopic composition of organic matter in tissues, such as hair and teeth, which are often used to reconstruct historical dietary and movement patterns of animals and humans. Here, we used a nonhuman primate system (Macaca fascicularis) to test the robustness of two different mechanistic stable isotope models: a model to predict the δ2H and δ18O values of body water and a second model to predict the δ2H and δ18O values of hair. In contrast to previous human-based studies, use of nonhuman primates fed controlled diets allowed us to further constrain model parameter values and evaluate model predictions. Both models reliably predicted the δ2H and δ18O values of body water and of hair. Moreover, the isotope data allowed us to better quantify values for two critical variables in the models: the δ2H and δ18O values of gut water and the 18O isotope fractionation associated with a carbonyl oxygen-water interaction in the gut (αow). Our modeling efforts indicated that better predictions for body water and hair isotope values were achieved by making the isotopic composition of gut water approached that of body water. Additionally, the value of αow was 1.0164, in close agreement with the only other previously measured observation (microbial spore cell walls), suggesting robustness of this fractionation factor across different biological systems. PMID:22553163

Hydrogen and oxygen isotope ratios in body water and hair: modeling isotope dynamics in nonhuman primates.

PubMed

O'Grady, Shannon P; Valenzuela, Luciano O; Remien, Christopher H; Enright, Lindsey E; Jorgensen, Matthew J; Kaplan, Jay R; Wagner, Janice D; Cerling, Thure E; Ehleringer, James R

2012-07-01

The stable isotopic composition of drinking water, diet, and atmospheric oxygen influence the isotopic composition of body water ((2)H/(1)H, (18)O/(16)O expressed as δ(2) H and δ(18)O). In turn, body water influences the isotopic composition of organic matter in tissues, such as hair and teeth, which are often used to reconstruct historical dietary and movement patterns of animals and humans. Here, we used a nonhuman primate system (Macaca fascicularis) to test the robustness of two different mechanistic stable isotope models: a model to predict the δ(2)H and δ(18)O values of body water and a second model to predict the δ(2)H and δ(18)O values of hair. In contrast to previous human-based studies, use of nonhuman primates fed controlled diets allowed us to further constrain model parameter values and evaluate model predictions. Both models reliably predicted the δ(2)H and δ(18)O values of body water and of hair. Moreover, the isotope data allowed us to better quantify values for two critical variables in the models: the δ(2)H and δ(18)O values of gut water and the (18)O isotope fractionation associated with a carbonyl oxygen-water interaction in the gut (α(ow)). Our modeling efforts indicated that better predictions for body water and hair isotope values were achieved by making the isotopic composition of gut water approached that of body water. Additionally, the value of α(ow) was 1.0164, in close agreement with the only other previously measured observation (microbial spore cell walls), suggesting robustness of this fractionation factor across different biological systems. © 2012 Wiley Periodicals, Inc.

Advance in prediction of soil slope instabilities

NASA Astrophysics Data System (ADS)

Sigarán-Loría, C.; Hack, R.; Nieuwenhuis, J. D.

2012-04-01

Six generic soils (clays and sands) were systematically modeled with plane-strain finite elements (FE) at varying heights and inclinations. A dataset was generated in order to develop predictive relations of soil slope instabilities, in terms of co-seismic displacements (u), under strong motions with a linear multiple regression. For simplicity, the seismic loads are monochromatic artificial sinusoidal functions at four frequencies: 1, 2, 4, and 6 Hz, and the slope failure criterion used corresponds to near 10% Cartesian shear strains along a continuous region comparable to a slip surface. The generated dataset comprises variables from the slope geometry and site conditions: height, H, inclination, i, shear wave velocity from the upper 30 m, vs30, site period, Ts; as well as the input strong motion: yield acceleration, ay (equal to peak ground acceleration, PGA in this research), frequency, f; and in some cases moment magnitude, M, and Arias intensity, Ia, assumed from empirical correlations. Different datasets or scenarios were created: "Magnitude-independent", "Magnitude-dependent", and "Soil-dependent", and the data was statistically explored and analyzed with varying mathematical forms. Qualitative relations show that the permanent deformations are highly related to the soil class for the clay slopes, but not for the sand slopes. Furthermore, the slope height does not constrain the variability in the co-seismic displacements. The input frequency decreases the variability of the co-seismic displacements for the "Magnitude-dependent" and "Soil-dependent" datasets. The empirical models were developed with two and three predictors. For the sands it was not possible because they could not satisfy the constrains from the statistical method. For the clays, the best models with the smallest errors coincided with the simple general form of multiple regression with three predictors (e.g. near 0.16 and 0.21 standard error, S.E. and 0.75 and 0.55 R2 for the "M-independent" and "M-dependent" datasets correspondingly). From the models with two predictors, a 2nd-order polynom gave the best performance but with a not-significant parameter. The best models with both predictors significant have slightly larger error and smaller R2, e.g. 0.15 S.E., 44% R2 with ay and i. The predictive models obtained with the three scenarios from the clay slopes provide well-constrained predictions but low R2, suggesting the predictors are "not complete", most likely in relation to the simplicity used in the strong motion characterization. Nevertheless, the findings from this work demonstrate the potential from analytical methods in developing more precise predictions as well as the importance on treating different different ground types.

Using eddy covariance of CO2, 13CO2 and CH4, continuous soil respiration measurements, and PhenoCams to constrain a process-based biogeochemical model for carbon market-funded wetland restoration

NASA Astrophysics Data System (ADS)

Oikawa, P. Y.; Baldocchi, D. D.; Knox, S. H.; Sturtevant, C. S.; Verfaillie, J. G.; Dronova, I.; Jenerette, D.; Poindexter, C.; Huang, Y. W.

2015-12-01

We use multiple data streams in a model-data fusion approach to reduce uncertainty in predicting CO2 and CH4 exchange in drained and flooded peatlands. Drained peatlands in the Sacramento-San Joaquin River Delta, California are a strong source of CO2 to the atmosphere and flooded peatlands or wetlands are a strong CO2 sink. However, wetlands are also large sources of CH4 that can offset the greenhouse gas mitigation potential of wetland restoration. Reducing uncertainty in model predictions of annual CO2 and CH4 budgets is critical for including wetland restoration in Cap-and-Trade programs. We have developed and parameterized the Peatland Ecosystem Photosynthesis, Respiration, and Methane Transport model (PEPRMT) in a drained agricultural peatland and a restored wetland. Both ecosystem respiration (Reco) and CH4 production are a function of 2 soil carbon (C) pools (i.e. recently-fixed C and soil organic C), temperature, and water table height. Photosynthesis is predicted using a light use efficiency model. To estimate parameters we use a Markov Chain Monte Carlo approach with an adaptive Metropolis-Hastings algorithm. Multiple data streams are used to constrain model parameters including eddy covariance of CO2, 13CO2 and CH4, continuous soil respiration measurements and digital photography. Digital photography is used to estimate leaf area index, an important input variable for the photosynthesis model. Soil respiration and 13CO2 fluxes allow partitioning of eddy covariance data between Reco and photosynthesis. Partitioned fluxes of CO2 with associated uncertainty are used to parametrize the Reco and photosynthesis models within PEPRMT. Overall, PEPRMT model performance is high. For example, we observe high data-model agreement between modeled and observed partitioned Reco (r2 = 0.68; slope = 1; RMSE = 0.59 g C-CO2 m-2 d-1). Model validation demonstrated the model's ability to accurately predict annual budgets of CO2 and CH4 in a wetland system (within 14% and 1% of observed annual budgets of CO2 and CH4, respectively). The use of multiple data streams is critical for constraining parameters and reducing uncertainty in model predictions, thereby providing accurate simulation of greenhouse gas exchange in a wetland restoration project with implications for C market-funded wetland restoration worldwide.

Parameter estimation uncertainty: Comparing apples and apples?

NASA Astrophysics Data System (ADS)

Hart, D.; Yoon, H.; McKenna, S. A.

2012-12-01

Given a highly parameterized ground water model in which the conceptual model of the heterogeneity is stochastic, an ensemble of inverse calibrations from multiple starting points (MSP) provides an ensemble of calibrated parameters and follow-on transport predictions. However, the multiple calibrations are computationally expensive. Parameter estimation uncertainty can also be modeled by decomposing the parameterization into a solution space and a null space. From a single calibration (single starting point) a single set of parameters defining the solution space can be extracted. The solution space is held constant while Monte Carlo sampling of the parameter set covering the null space creates an ensemble of the null space parameter set. A recently developed null-space Monte Carlo (NSMC) method combines the calibration solution space parameters with the ensemble of null space parameters, creating sets of calibration-constrained parameters for input to the follow-on transport predictions. Here, we examine the consistency between probabilistic ensembles of parameter estimates and predictions using the MSP calibration and the NSMC approaches. A highly parameterized model of the Culebra dolomite previously developed for the WIPP project in New Mexico is used as the test case. A total of 100 estimated fields are retained from the MSP approach and the ensemble of results defining the model fit to the data, the reproduction of the variogram model and prediction of an advective travel time are compared to the same results obtained using NSMC. We demonstrate that the NSMC fields based on a single calibration model can be significantly constrained by the calibrated solution space and the resulting distribution of advective travel times is biased toward the travel time from the single calibrated field. To overcome this, newly proposed strategies to employ a multiple calibration-constrained NSMC approach (M-NSMC) are evaluated. Comparison of the M-NSMC and MSP methods suggests that M-NSMC can provide a computationally efficient and practical solution for predictive uncertainty analysis in highly nonlinear and complex subsurface flow and transport models. This material is based upon work supported as part of the Center for Frontiers of Subsurface Energy Security, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences under Award Number DE-SC0001114. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Low power interface IC's for electrostatic energy harvesting applications

NASA Astrophysics Data System (ADS)

Kempitiya, Asantha

The application of wireless distributed micro-sensor systems ranges from equipment diagnostic and control to real time structural and biomedical monitoring. A major obstacle in developing autonomous micro-sensor networks is the need for local electric power supply, since using a battery is often not a viable solution. This void has sparked significant interest in micro-scale power generators based on electrostatic, piezoelectric and electromagnetic energy conversion that can scavenge ambient energy from the environment. In comparison to existing energy harvesting techniques, electrostatic-based power generation is attractive as it can be integrated using mainstream silicon technologies while providing higher power densities through miniaturization. However the power output of reported electrostatic micro-generators to date does not meet the communication and computation requirements of wireless sensor nodes. The objective of this thesis is to investigate novel CMOS-based energy harvesting circuit (EHC) architectures to increase the level of harvested mechanical energy in electrostatic converters. The electronic circuits that facilitate mechanical to electrical energy conversion employing variable capacitors can either have synchronous or asynchronous architectures. The later does not require synchronization of electrical events with mechanical motion, which eliminates difficulties in gate clocking and the power consumption associated with complex control circuitry. However, the implementation of the EHC with the converter can be detrimental to system performance when done without concurrent optimization of both elements, an aspect mainly overlooked in the literature. System level analysis is performed to show that there is an optimum value for either the storage capacitor or cycle number for maximum scavenging of ambient energy. The analysis also shows that maximum power is extracted when the system approaches synchronous operation. However, there is a region of interest where the storage capacitor can be optimized to produce almost 70% of the ideal power taken as the power harvested with synchronous converters when neglecting the power consumption associated with synchronizing control circuitry. Theoretical predictions are confirmed by measurements on an asynchronous EHC implemented with a macro-scale electrostatic converter prototype. Based on the preceding analysis, the design of a novel ultra low power electrostatic integrated energy harvesting circuit is proposed for efficient harvesting of mechanical energy. The fundamental challenges of designing reliable low power sensing circuits for charge constrained electrostatic energy harvesters with capacity to self power its controller and driver stages are addressed. Experimental results are presented for a controller design implemented in AMI 0.7muM high voltage CMOS process using a macro-scale electrostatic converter prototype. The EHC produces 1.126muW for a power investment of 417nW with combined conduction and controller losses of 450nW which is a 20-30% improvement compared to prior art on electrostatic EHCs operating under charge constrain. Inherently dual plate variable capacitors harvest energy only during half of the mechanical cycle with the other half unutilized for energy conversion. To harvest mechanical energy over the complete mechanical vibration cycle, a low power energy harvesting circuit (EHC) that performs charge constrained synchronous energy conversion on a tri-plate variable capacitor for maximizing energy conversion is proposed. The tri-plate macro electrostatic generator with capacitor variation of 405pF to 1.15nF and 405pF to 1.07nF on two complementary adjacent capacitors is fabricated and used in the characterization of the designed EHC. The integrated circuit fabricated in AMI 0.7muM high voltage CMOS process, produces a total output power of 497nW to a 10muF reservoir capacitor from a 98Hz vibration signal. In summary, the thesis lays out the theoretical and experimental foundation for overcoming the main challenges associated with the design of charge constrained synchronous EHC's, making electrostatic converters a possible candidate for powering emerging communication transceivers and portable electronics.

Use of Contextual Information and Prediction by Struggling Adult Readers: Evidence from Reading Times and Event-Related Potentials

ERIC Educational Resources Information Center

Ng, Shukhan; Payne, Brennan R.; Steen, Allison A.; Stine-Morrow, Elizabeth A. L.; Federmeier, Kara D.

2017-01-01

We employed self-paced reading and event-related potential measures to investigate how adults of varying literacy levels use sentence context information when reading. Community-dwelling participants read strongly and weakly constraining sentences that ended with expected or unexpected target words. Skilled readers showed N400s that were graded by…

Use of Contextual Information and Prediction by Struggling Adult Readers: Evidence from Reading Times and Event-Related Potentials.

ERIC Educational Resources Information Center

Ng, Shukhan; Payne, Brennan R.; Steen, Allison A.; Stine-Morrow, Elizabeth A. L.; Federmeier, Kara D.

2017-01-01

We employed self-paced reading and event-related potential measures to investigate how adults of varying literacy levels use sentence context information when reading. Community-dwelling participants read strongly and weakly constraining sentences that ended with expected or unex- pected target words. Skilled readers showed N400s that were graded…

Estimating tree crown widths for the primary Acadian species in Maine

Treesearch

Matthew B. Russell; Aaron R. Weiskittel

2012-01-01

In this analysis, data for seven conifer and eight hardwood species were gathered from across the state of Maine for estimating tree crown widths. Maximum and largest crown width equations were developed using tree diameter at breast height as the primary predicting variable. Quantile regression techniques were used to estimate the maximum crown width and a constrained...

Slow climate velocities of mountain streams portend their role as refugia for cold-water biodiversity

Treesearch

Daniel J. Isaak; Michael K. Young; Charlie Luce; Steven W. Hostetler; Seth J. Wenger; Erin E. Peterson; Jay M. Ver Hoef; Matthew C. Groce; Dona L. Horan; David E. Nagel

2016-01-01

The imminent demise of montane species is a recurrent theme in the climate change literature, particularly for aquatic species that are constrained to networks and elevational rather than latitudinal retreat as temperatures increase. Predictions of widespread species losses, however, have yet to be fulfilled despite decades of climate change, suggesting that trends are...

Snapshots of Children's Changing Biases during Language Development: Differential Weighting of Perceptual and Linguistic Factors Predicts Noun Age of Acquisition

ERIC Educational Resources Information Center

Ramey, Christopher H.; Chrysikou, Evangelia G.; Reilly, Jamie

2013-01-01

Word learning is a lifelong activity constrained by cognitive biases that people possess at particular points in development. Age of acquisition (AoA) is a psycholinguistic variable that may prove useful toward gauging the relative weighting of different phonological, semantic, and morphological factors at different phases of language acquisition…

Data-Constrained Projections of Methane Fluxes in a Northern Minnesota Peatland in Response to Elevated CO2 and Warming

Treesearch

Shuang Ma; Jiang Jiang; Yuanyuan Huang; Zheng Shi; Rachel M. Wilson; Daniel Ricciuto; Stephen D. Sebestyen; Paul J. Hanson; Yiqi Luo

2017-01-01

Large uncertainties exist in predicting responses of wetland methane (CH4) fluxes to future climate change. However, sources of the uncertainty have not been clearly identified despite the fact that methane production and emission processes have been extensively explored. In this study, we took advantage of manual CH4 flux...

Effective theory of flavor for Minimal Mirror Twin Higgs

DOE PAGES

Barbieri, Riccardo; Hall, Lawrence J.; Harigaya, Keisuke

2017-10-03

We consider two copies of the Standard Model, interchanged by an exact parity symmetry, P. The observed fermion mass hierarchy is described by suppression factors ϵ more » $$n_i$$ for charged fermion i, as can arise in Froggatt-Nielsen and extra-dimensional theories of flavor. The corresponding flavor factors in the mirror sector are ϵ' $$n_i$$, so that spontaneous breaking of the parity P arises from a single parameter ϵ'/ϵ, yielding a tightly constrained version of Minimal Mirror Twin Higgs, introduced in our previous paper. Models are studied for simple values of n i, including in particular one with SU(5)-compatibility, that describe the observed fermion mass hierarchy. The entire mirror quark and charged lepton spectrum is broadly predicted in terms of ϵ'/ϵ, as are the mirror QCD scale and the decoupling temperature between the two sectors. Helium-, hydrogen- and neutron-like mirror dark matter candidates are constrained by self-scattering and relic ionization. Lastly, in each case, the allowed parameter space can be fully probed by proposed direct detection experiments. Correlated predictions are made as well for the Higgs signal strength and the amount of dark radiation.« less

An enhanced beam model for constrained layer damping and a parameter study of damping contribution

NASA Astrophysics Data System (ADS)

Xie, Zhengchao; Shepard, W. Steve, Jr.

2009-01-01

An enhanced analytical model is presented based on an extension of previous models for constrained layer damping (CLD) in beam-like structures. Most existing CLD models are based on the assumption that shear deformation in the core layer is the only source of damping in the structure. However, previous research has shown that other types of deformation in the core layer, such as deformations from longitudinal extension and transverse compression, can also be important. In the enhanced analytical model developed here, shear, extension, and compression deformations are all included. This model can be used to predict the natural frequencies and modal loss factors. The numerical study shows that compared to other models, this enhanced model is accurate in predicting the dynamic characteristics. As a result, the model can be accepted as a general computation model. With all three types of damping included and the formulation used here, it is possible to study the impact of the structure's geometry and boundary conditions on the relative contribution of each type of damping. To that end, the relative contributions in the frequency domain for a few sample cases are presented.

USING ForeCAT DEFLECTIONS AND ROTATIONS TO CONSTRAIN THE EARLY EVOLUTION OF CMEs

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

Kay, C.; Opher, M.; Colaninno, R. C.

2016-08-10

To accurately predict the space weather effects of the impacts of coronal mass ejection (CME) at Earth one must know if and when a CME will impact Earth and the CME parameters upon impact. In 2015 Kay et al. presented Forecasting a CME’s Altered Trajectory (ForeCAT), a model for CME deflections based on the magnetic forces from the background solar magnetic field. Knowing the deflection and rotation of a CME enables prediction of Earth impacts and the orientation of the CME upon impact. We first reconstruct the positions of the 2010 April 8 and the 2012 July 12 CMEs frommore » the observations. The first of these CMEs exhibits significant deflection and rotation (34° deflection and 58° rotation), while the second shows almost no deflection or rotation (<3° each). Using ForeCAT, we explore a range of initial parameters, such as the CME’s location and size, and find parameters that can successfully reproduce the behavior for each CME. Additionally, since the deflection depends strongly on the behavior of a CME in the low corona, we are able to constrain the expansion and propagation of these CMEs in the low corona.« less