The influence of coping strategies on subsequent well-being in older patients with cancer: A comparison with 2 control groups.

PubMed

Baitar, Abdelbari; Buntinx, Frank; De Burghgraeve, Tine; Deckx, Laura; Schrijvers, Dirk; Wildiers, Hans; van den Akker, Marjan

2018-03-01

To evaluate dispositional coping strategies as predictors for changes in well-being after 1 year in older patients with cancer (OCP) and 2 control groups. OCP were compared with 2 control groups: middle-aged patients with cancer (MCP) (aging effect) and older patients without cancer (ONC) (cancer effect). Patients were interviewed shortly after a cancer diagnosis and 1 year later. Dispositional coping was measured with the Short Utrecht Coping List. For well-being, we considered psychological well-being (depression, loneliness, distress) and physical health (fatigue, ADL, IADL). Logistic regression analyses were performed to study baseline coping as predictor for subsequent well-being while controlling for important baseline covariates. A total of 1245 patients were included in the analysis at baseline: 263 OCP, 590 ONC, and 392 MCP. Overall, active tackling was employed most often. With the exception of palliative reacting, OCP utilized each coping strategy less frequently than MCP. At 1-year follow-up, 833 patients (66.9%) were interviewed. Active coping strategies (active tackling and seeking social support) predicted subsequent well-being only in MCP. Avoidance coping strategies did not predict well-being in any of the patient groups. Palliative reacting predicted distress in OCP; depression and dependency for ADL in MCP. Coping strategies influence subsequent well-being in patients with cancer, but the impact is different in the age groups. Palliative reacting was the only coping strategy that predicted well-being (ie, distress) in OCP and is therefore, especially in this population, a target for coping skill interventions. Copyright © 2017 John Wiley & Sons, Ltd.

Perturbed cooperative-state feedback strategy for model predictive networked control of interconnected systems.

PubMed

Tran, Tri; Ha, Q P

2018-01-01

A perturbed cooperative-state feedback (PSF) strategy is presented for the control of interconnected systems in this paper. The subsystems of an interconnected system can exchange data via the communication network that has multiple connection topologies. The PSF strategy can resolve both issues, the sensor data losses and the communication network breaks, thanks to the two components of the control including a cooperative-state feedback and a perturbation variable, e.g., u i =K ij x j +w i . The PSF is implemented in a decentralized model predictive control scheme with a stability constraint and a non-monotonic storage function (ΔV(x(k))≥0), derived from the dissipative systems theory. Numerical simulation for the automatic generation control problem in power systems is studied to illustrate the effectiveness of the presented PSF strategy. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Control Strategy of Active Power Filter Based on Modular Multilevel Converter

NASA Astrophysics Data System (ADS)

Xie, Xifeng

2018-03-01

To improve the capacity, pressure resistance and the equivalent switching frequency of active power filter (APF), a control strategy of APF based on Modular Multilevel Converter (MMC) is presented. In this Control Strategy, the indirect current control method is used to achieve active current and reactive current decoupling control; Voltage Balance Control Strategy is to stabilize sub-module capacitor voltage, the predictive current control method is used to Track and control of harmonic currents. As a result, the harmonic current is restrained, and power quality is improved. Finally, the simulation model of active power filter controller based on MMC is established in Matlab/Simulink, the simulation proves that the proposed strategy is feasible and correct.

Low-income minority fathers' control strategies and children's regulatory skills

PubMed Central

Malin, Jenessa L.; Cabrera, Natasha J.; Karberg, Elizabeth; Aldoney, Daniela; Rowe, Meredith

2015-01-01

The current study explored the bidirectional association of children's individual characteristics, fathers' control strategies at 24-months and children's regulatory skills at pre-kindergarten (pre-K). Using a sample of low-income minority families with 2-year-olds from the Early Head Start Evaluation Research Program (n = 71) we assessed the association between child gender and vocabulary skills, fathers' control strategies at 24-months (e.g., regulatory behavior and regulatory language), and children's sustained attention and emotion regulation at pre-kindergarten. There were three main findings. First, fathers' overwhelmingly use commands (e.g., do that) to promote compliance in their 24-month old children. Second, children's vocabulary skills predict fathers' regulatory behaviors during a father-child interaction, whereas children's gender predicts fathers' regulatory language during an interaction. Third, controlling for maternal supportiveness, fathers' regulatory behaviors at 24-months predict children's sustained attention at pre-kindergarten whereas fathers' regulatory language at 24-months predicts children's emotion regulation at pre-kindergarten. Our findings highlight the importance of examining paternal contributions to children's regulatory skills. PMID:25798496

Low-income, minority fathers' control strategies and their children's regulatory skills.

PubMed

Malin, Jenessa L; Cabrera, Natasha J; Karberg, Elizabeth; Aldoney, Daniela; Rowe, Meredith L

2014-01-01

The current study explored the bidirectional association of children's individual characteristics, fathers' control strategies at 24 months, and children's regulatory skills at prekindergarten (pre-K). Using a sample of low-income, minority families with 2-year-olds from the Early Head Start Research and Evaluation Project (n = 71), we assessed the association between child gender and vocabulary skills, fathers' control strategies at 24 months (e.g., regulatory behavior and regulatory language), and children's sustained attention and emotion regulation at prekindergarten. There were three main findings. First, fathers overwhelmingly used commands (e.g., "Do that.") to promote compliance in their 24-month-old children. Second, children's vocabulary skills predicted fathers' regulatory behaviors during a father-child interaction whereas children's gender predicted fathers' regulatory language during an interaction. Third, controlling for maternal supportiveness, fathers' regulatory behaviors at 24 months predicted children's sustained attention at pre-K whereas fathers' regulatory language at 24 months predicted children's emotion regulation at pre-K. Our findings highlight the importance of examining paternal contributions to children's regulatory skills. © 2014 Michigan Association for Infant Mental Health.

Cascade generalized predictive control strategy for boiler drum level.

PubMed

Xu, Min; Li, Shaoyuan; Cai, Wenjian

2005-07-01

This paper proposes a cascade model predictive control scheme for boiler drum level control. By employing generalized predictive control structures for both inner and outer loops, measured and unmeasured disturbances can be effectively rejected, and drum level at constant load is maintained. In addition, nonminimum phase characteristic and system constraints in both loops can be handled effectively by generalized predictive control algorithms. Simulation results are provided to show that cascade generalized predictive control results in better performance than that of well tuned cascade proportional integral differential controllers. The algorithm has also been implemented to control a 75-MW boiler plant, and the results show an improvement over conventional control schemes.

How Personality Affects Vulnerability among Israelis and Palestinians following the 2009 Gaza Conflict

PubMed Central

Canetti, Daphna; Kimhi, Shaul; Hanoun, Rasmiyah; Rocha, Gabriel A.; Galea, Sandro; Morgan, Charles A.

2016-01-01

Can the onset of PTSD symptoms and depression be predicted by personality factors and thought control strategies? A logical explanation for the different mental health outcomes of individuals exposed to trauma would seem to be personality factors and thought control strategies. Trauma exposure is necessary but not sufficient for the development of PTSD. To this end, we assess the role of personality traits and coping styles in PTSD vulnerability among Israeli and Palestinian students amid conflict. We also determine whether gender and exposure level to trauma impact the likelihood of the onset of PTSD symptoms. Five questionnaires assess previous trauma, PTSD symptoms, demographics, personality factors and thought control strategies, which are analyzed using path analysis. Findings show that the importance of personality factors and thought control strategies in predicting vulnerability increases in the face of political violence: the higher stress, the more important the roles of personality and thought control strategies. Thought control strategies associated with introverted and less emotionally stable personality-types correlate positively with higher levels of PTSD symptoms and depression, particularly among Palestinians. By extension, because mental health is key to reducing violence in the region, PTSD reduction in conflict zones warrants rethinking. PMID:27391240

How Personality Affects Vulnerability among Israelis and Palestinians following the 2009 Gaza Conflict.

PubMed

Canetti, Daphna; Kimhi, Shaul; Hanoun, Rasmiyah; Rocha, Gabriel A; Galea, Sandro; Morgan, Charles A

2016-01-01

Can the onset of PTSD symptoms and depression be predicted by personality factors and thought control strategies? A logical explanation for the different mental health outcomes of individuals exposed to trauma would seem to be personality factors and thought control strategies. Trauma exposure is necessary but not sufficient for the development of PTSD. To this end, we assess the role of personality traits and coping styles in PTSD vulnerability among Israeli and Palestinian students amid conflict. We also determine whether gender and exposure level to trauma impact the likelihood of the onset of PTSD symptoms. Five questionnaires assess previous trauma, PTSD symptoms, demographics, personality factors and thought control strategies, which are analyzed using path analysis. Findings show that the importance of personality factors and thought control strategies in predicting vulnerability increases in the face of political violence: the higher stress, the more important the roles of personality and thought control strategies. Thought control strategies associated with introverted and less emotionally stable personality-types correlate positively with higher levels of PTSD symptoms and depression, particularly among Palestinians. By extension, because mental health is key to reducing violence in the region, PTSD reduction in conflict zones warrants rethinking.

Prediction, Control and the Challenge to Complexity

ERIC Educational Resources Information Center

Radford, Mike

2008-01-01

The dominant discourse in research, management and teaching is one that may loosely be characterised as that of prediction and control. The objective of research is to identify causal correlations within policy, management, teaching strategies and educational outcomes that are sufficiently robust as to be able to predict outcomes and make…

Predictive Effects of Good Self-Control and Poor Regulation on Alcohol-Related Outcomes: Do Protective Behavioral Strategies Mediate?

PubMed Central

Pearson, Matthew R.; Kite, Benjamin A.; Henson, James M.

2016-01-01

In the present study, we examined whether use of protective behavioral strategies mediated the relationship between self-control constructs and alcohol-related outcomes. According to the two-mode model of self-control, good self-control (planfulness; measured with Future Time Perspective, Problem Solving, and Self-Reinforcement) and poor regulation (impulsivity; measured with Present Time Perspective, Poor Delay of Gratification, Distractibility) are theorized to be relatively independent constructs rather than opposite ends of a single continuum. The analytic sample consisted of 278 college student drinkers (68% women) who responded to a battery of surveys at a single time point. Using a structural equation model based on the two-mode model of self-control, we found that good self-control predicted increased use of three types of protective behavioral strategies (Manner of Drinking, Limiting/Stopping Drinking, and Serious Harm Reduction). Poor regulation was unrelated to use of protective behavioral strategies, but had direct effects on alcohol use and alcohol problems. Further, protective behavioral strategies mediated the relationship between good self-control and alcohol use. The clinical implications of these findings are discussed. PMID:22663345

Assessing Strategies Against Gambiense Sleeping Sickness Through Mathematical Modeling

PubMed Central

Rock, Kat S; Ndeffo-Mbah, Martial L; Castaño, Soledad; Palmer, Cody; Pandey, Abhishek; Atkins, Katherine E; Ndung’u, Joseph M; Hollingsworth, T Déirdre; Galvani, Alison; Bever, Caitlin; Chitnis, Nakul; Keeling, Matt J

2018-01-01

Abstract Background Control of gambiense sleeping sickness relies predominantly on passive and active screening of people, followed by treatment. Methods Mathematical modeling explores the potential of 3 complementary interventions in high- and low-transmission settings. Results Intervention strategies that included vector control are predicted to halt transmission most quickly. Targeted active screening, with better and more focused coverage, and enhanced passive surveillance, with improved access to diagnosis and treatment, are both estimated to avert many new infections but, when used alone, are unlikely to halt transmission before 2030 in high-risk settings. Conclusions There was general model consensus in the ranking of the 3 complementary interventions studied, although with discrepancies between the quantitative predictions due to differing epidemiological assumptions within the models. While these predictions provide generic insights into improving control, the most effective strategy in any situation depends on the specific epidemiology in the region and the associated costs. PMID:29860287

Intrusive thoughts in obsessive-compulsive disorder and eating disorder patients: a differential analysis.

PubMed

García-Soriano, Gemma; Roncero, Maria; Perpiñá, Conxa; Belloch, Amparo

2014-05-01

The present study aims to compare the unwanted intrusions experienced by obsessive-compulsive (OCD) and eating disorder (ED) patients, their appraisals, and their control strategies and analyse which variables predict the intrusions' disruption and emotional disturbance in each group. Seventy-nine OCD and 177 ED patients completed two equivalent self-reports designed to assess OCD-related and ED-related intrusions, their dysfunctional appraisals, and associated control strategies. OCD and ED patients experienced intrusions with comparable frequency and emotional disturbance, but OCD patients experienced greater disruption. Differences appeared between groups on some appraisals and control strategies. Intolerance to uncertainty (OCD group) and thought importance (ED group) predicted their respective emotional disturbance and disruption. Additionally, control importance (OCD group) and thought-action fusion moral (OCD and ED groups) predicted their emotional disturbance. OCD and ED share the presence of intrusions; however, different variables explain why they are disruptive and emotionally disturbing. Cognitive intrusions require further investigation as a transdiagnostic variable. Copyright © 2014 John Wiley & Sons, Ltd and Eating Disorders Association.

Nonlinear Model Predictive Control with Constraint Satisfactions for a Quadcopter

NASA Astrophysics Data System (ADS)

Wang, Ye; Ramirez-Jaime, Andres; Xu, Feng; Puig, Vicenç

2017-01-01

This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the effectiveness of the proposed strategy.

Coping with examinations: exploring relationships between students' coping strategies, implicit theories of ability, and perceived control.

PubMed

Doron, Julie; Stephan, Yannick; Boiché, Julie; Le Scanff, Christine

2009-09-01

Relatively little is known about the contribution of students' beliefs regarding the nature of academic ability (i.e. their implicit theories) on strategies used to deal with examinations. This study applied Dweck's socio-cognitive model of achievement motivation to better understand how students cope with examinations. It was expected that students' implicit theories of academic ability would be related to their use of particular coping strategies to deal with exam-related stress. Additionally, it was predicted that perceived control over exams acts as a mediator between implicit theories of ability and coping. Four hundred and ten undergraduate students (263 males, 147 females), aged from 17 to 26 years old (M=19.73, SD=1.46) were volunteers for the present study. Students completed measures of coping, implicit theories of academic ability, and perception of control over academic examinations during regular classes in the first term of the university year. Multiple regression analyses revealed that incremental beliefs of ability significantly and positively predicted active coping, planning, venting of emotions, seeking social support for emotional and instrumental reasons, whereas entity beliefs positively predicted behavioural disengagement and negatively predicted active coping and acceptance. In addition, analyses revealed that entity beliefs of ability were related to coping strategies through students' perception of control over academic examinations. These results confirm that exam-related coping varies as a function of students' beliefs about the nature of academic ability and their perceptions of control when approaching examinations.

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Robust model predictive control for satellite formation keeping with eccentricity/inclination vector separation

NASA Astrophysics Data System (ADS)

Lim, Yeerang; Jung, Youeyun; Bang, Hyochoong

2018-05-01

This study presents model predictive formation control based on an eccentricity/inclination vector separation strategy. Alternative collision avoidance can be accomplished by using eccentricity/inclination vectors and adding a simple goal function term for optimization process. Real-time control is also achievable with model predictive controller based on convex formulation. Constraint-tightening approach is address as well improve robustness of the controller, and simulation results are presented to verify performance enhancement for the proposed approach.

Finite Control Set Model Predictive Control for Multiple Distributed Generators Microgrids

NASA Astrophysics Data System (ADS)

Babqi, Abdulrahman Jamal

This dissertation proposes two control strategies for AC microgrids that consist of multiple distributed generators (DGs). The control strategies are valid for both grid-connected and islanded modes of operation. In general, microgrid can operate as a stand-alone system (i.e., islanded mode) or while it is connected to the utility grid (i.e., grid connected mode). To enhance the performance of a micrgorid, a sophisticated control scheme should be employed. The control strategies of microgrids can be divided into primary and secondary controls. The primary control regulates the output active and reactive powers of each DG in grid-connected mode as well as the output voltage and frequency of each DG in islanded mode. The secondary control is responsible for regulating the microgrid voltage and frequency in the islanded mode. Moreover, it provides power sharing schemes among the DGs. In other words, the secondary control specifies the set points (i.e. reference values) for the primary controllers. In this dissertation, Finite Control Set Model Predictive Control (FCS-MPC) was proposed for controlling microgrids. FCS-MPC was used as the primary controller to regulate the output power of each DG (in the grid-connected mode) or the voltage of the point of DG coupling (in the islanded mode of operation). In the grid-connected mode, Direct Power Model Predictive Control (DPMPC) was implemented to manage the power flow between each DG and the utility grid. In the islanded mode, Voltage Model Predictive Control (VMPC), as the primary control, and droop control, as the secondary control, were employed to control the output voltage of each DG and system frequency. The controller was equipped with a supplementary current limiting technique in order to limit the output current of each DG in abnormal incidents. The control approach also enabled smooth transition between the two modes. The performance of the control strategy was investigated and verified using PSCAD/EMTDC software platform. This dissertation also proposes a control and power sharing strategy for small-scale microgrids in both grid-connected and islanded modes based on centralized FCS-MPC. In grid-connected mode, the controller was capable of managing the output power of each DG and enabling flexible power regulation between the microgrid and the utility grid. In islanded mode, the controller regulated the microgrid voltage and frequency, and provided a precise power sharing scheme among the DGs. In addition, the power sharing can be adjusted flexibly by changing the sharing ratio. The proposed control also enabled plug-and-play operation. Moreover, a smooth transition between the two modes of operation was achieved without any disturbance in the system. Case studies were carried out in order to validate the proposed control strategy with the PSCAD/EMTDA software package.

Paraphrasing and Prediction with Self-Explanation as Generative Strategies for Learning Science Principles in a Simulation

ERIC Educational Resources Information Center

Morrison, Jennifer R.; Bol, Linda; Ross, Steven M.; Watson, Ginger S.

2015-01-01

This study examined the incorporation of generative strategies for the guided discovery of physics principles in a simulation. Participants who either paraphrased or predicted and self-explained guided discovery assignments exhibited improved performance on an achievement test as compared to a control group. Calibration accuracy (the…

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.

Performance and robustness of hybrid model predictive control for controllable dampers in building models

NASA Astrophysics Data System (ADS)

Johnson, Erik A.; Elhaddad, Wael M.; Wojtkiewicz, Steven F.

2016-04-01

A variety of strategies have been developed over the past few decades to determine controllable damping device forces to mitigate the response of structures and mechanical systems to natural hazards and other excitations. These "smart" damping devices produce forces through passive means but have properties that can be controlled in real time, based on sensor measurements of response across the structure, to dramatically reduce structural motion by exploiting more than the local "information" that is available to purely passive devices. A common strategy is to design optimal damping forces using active control approaches and then try to reproduce those forces with the smart damper. However, these design forces, for some structures and performance objectives, may achieve high performance by selectively adding energy, which cannot be replicated by a controllable damping device, causing the smart damper performance to fall far short of what an active system would provide. The authors have recently demonstrated that a model predictive control strategy using hybrid system models, which utilize both continuous and binary states (the latter to capture the switching behavior between dissipative and non-dissipative forces), can provide reductions in structural response on the order of 50% relative to the conventional clipped-optimal design strategy. This paper explores the robustness of this newly proposed control strategy through evaluating controllable damper performance when the structure model differs from the nominal one used to design the damping strategy. Results from the application to a two-degree-of-freedom structure model confirms the robustness of the proposed strategy.

Towards a Semantically-Enabled Control Strategy for Building Simulations: Integration of Semantic Technologies and Model Predictive Control

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

Delgoshaei, Parastoo; Austin, Mark A.; Pertzborn, Amanda J.

State-of-the-art building simulation control methods incorporate physical constraints into their mathematical models, but omit implicit constraints associated with policies of operation and dependency relationships among rules representing those constraints. To overcome these shortcomings, there is a recent trend in enabling the control strategies with inference-based rule checking capabilities. One solution is to exploit semantic web technologies in building simulation control. Such approaches provide the tools for semantic modeling of domains, and the ability to deduce new information based on the models through use of Description Logic (DL). In a step toward enabling this capability, this paper presents a cross-disciplinary data-drivenmore » control strategy for building energy management simulation that integrates semantic modeling and formal rule checking mechanisms into a Model Predictive Control (MPC) formulation. The results show that MPC provides superior levels of performance when initial conditions and inputs are derived from inference-based rules.« less

Robust shrinking ellipsoid model predictive control for linear parameter varying system

PubMed Central

Yan, Yan

2017-01-01

In this paper, a new off-line model predictive control strategy is presented for a kind of linear parameter varying system with polytopic uncertainty. A nest of shrinking ellipsoids is constructed by solving linear matrix inequality. By splitting the objective function into two parts, the proposed strategy moves most computations off-line. The on-line computation is only calculating the current control to assure the system shrinking into the smaller ellipsoid. With the proposed formulation, the stability of the closed system is proved, followed with two numerical examples to demonstrate the proposed method’s effectiveness in the end. PMID:28575028

Model predictive control for spacecraft rendezvous in elliptical orbit

NASA Astrophysics Data System (ADS)

Li, Peng; Zhu, Zheng H.

2018-05-01

This paper studies the control of spacecraft rendezvous with attitude stable or spinning targets in an elliptical orbit. The linearized Tschauner-Hempel equation is used to describe the motion of spacecraft and the problem is formulated by model predictive control. The control objective is to maximize control accuracy and smoothness simultaneously to avoid unexpected change or overshoot of trajectory for safe rendezvous. It is achieved by minimizing the weighted summations of control errors and increments. The effects of two sets of horizons (control and predictive horizons) in the model predictive control are examined in terms of fuel consumption, rendezvous time and computational effort. The numerical results show the proposed control strategy is effective.

Predictability, Force and (Anti-)Resonance in Complex Object Control.

PubMed

Maurice, Pauline; Hogan, Neville; Sternad, Dagmar

2018-04-18

Manipulation of complex objects as in tool use is ubiquitous and has given humans an evolutionary advantage. This study examined the strategies humans choose when manipulating an object with underactuated internal dynamics, such as a cup of coffee. The object's dynamics renders the temporal evolution complex, possibly even chaotic, and difficult to predict. A cart-and-pendulum model, loosely mimicking coffee sloshing in a cup, was implemented in a virtual environment with a haptic interface. Participants rhythmically manipulated the virtual cup containing a rolling ball; they could choose the oscillation frequency, while the amplitude was prescribed. Three hypotheses were tested: 1) humans decrease interaction forces between hand and object; 2) humans increase the predictability of the object dynamics; 3) humans exploit the resonances of the coupled object-hand system. Analysis revealed that humans chose either a high-frequency strategy with anti-phase cup-and-ball movements or a low-frequency strategy with in-phase cup-and-ball movements. Counter Hypothesis 1, they did not decrease interaction force; instead, they increased the predictability of the interaction dynamics, quantified by mutual information, supporting Hypothesis 2. To address Hypothesis 3, frequency analysis of the coupled hand-object system revealed two resonance frequencies separated by an anti-resonance frequency. The low-frequency strategy exploited one resonance, while the high-frequency strategy afforded more choice, consistent with the frequency response of the coupled system; both strategies avoided the anti-resonance. Hence, humans did not prioritize interaction force, but rather strategies that rendered interactions predictable. These findings highlight that physical interactions with complex objects pose control challenges not present in unconstrained movements.

Improved LTVMPC design for steering control of autonomous vehicle

NASA Astrophysics Data System (ADS)

Velhal, Shridhar; Thomas, Susy

2017-01-01

An improved linear time varying model predictive control for steering control of autonomous vehicle running on slippery road is presented. Control strategy is designed such that the vehicle will follow the predefined trajectory with highest possible entry speed. In linear time varying model predictive control, nonlinear vehicle model is successively linearized at each sampling instant. This linear time varying model is used to design MPC which will predict the future horizon. By incorporating predicted input horizon in each successive linearization the effectiveness of controller has been improved. The tracking performance using steering with front wheel and braking at four wheels are presented to illustrate the effectiveness of the proposed method.

Cognitive strategies regulate fictive, but not reward prediction error signals in a sequential investment task.

PubMed

Gu, Xiaosi; Kirk, Ulrich; Lohrenz, Terry M; Montague, P Read

2014-08-01

Computational models of reward processing suggest that foregone or fictive outcomes serve as important information sources for learning and augment those generated by experienced rewards (e.g. reward prediction errors). An outstanding question is how these learning signals interact with top-down cognitive influences, such as cognitive reappraisal strategies. Using a sequential investment task and functional magnetic resonance imaging, we show that the reappraisal strategy selectively attenuates the influence of fictive, but not reward prediction error signals on investment behavior; such behavioral effect is accompanied by changes in neural activity and connectivity in the anterior insular cortex, a brain region thought to integrate subjective feelings with high-order cognition. Furthermore, individuals differ in the extent to which their behaviors are driven by fictive errors versus reward prediction errors, and the reappraisal strategy interacts with such individual differences; a finding also accompanied by distinct underlying neural mechanisms. These findings suggest that the variable interaction of cognitive strategies with two important classes of computational learning signals (fictive, reward prediction error) represent one contributing substrate for the variable capacity of individuals to control their behavior based on foregone rewards. These findings also expose important possibilities for understanding the lack of control in addiction based on possibly foregone rewarding outcomes. Copyright © 2013 The Authors. Human Brain Mapping Published by Wiley Periodicals, Inc.

Coping with stress in adolescents with type 1 diabetes and their mothers.

PubMed

Pisula, Ewa; Czaplinska, C

2010-11-04

Coping with stress plays a vital role in the adjustment of adolescents with diabetes. The majority of studies in this area leave out the control group, limiting their power to make inferences about specificity vs. similarity of coping strategies used by these adolescents. The aims of this study were: (1) To compare coping strategies in adolescents with diabetes and healthy adolescents; (2) To compare coping strategies in girls and boys with diabetes; (3) To determine whether there is a relationship between adolescents' coping strategies and their mothers' coping styles. Adolescents (12-17 years old) with Type 1 diabetes (n = 51) were compared with a control group of healthy secondary school students (n = 56) by means of a self-reported questionnaire measuring coping strategies (Adolescence Coping Checklist). Mothers of these adolescents (n = 107) completed the Coping Inventory for Stressful Situations, measuring 3 coping styles. Diabetic adolescents used the 'seek professional help' strategy more often than their healthy peers. The girls with diabetes reported using the 'investing in close friends' strategy more often than boys, while in the control group girls were also more likely to use "seeking social support", "seeking spiritual support", and "relaxing diversions" strategies. Mothers' emotion-oriented coping style predicted focus-oriented coping in adolescents with diabetes. In the non-diabetic group, mothers' task-oriented coping predicted seeking professional help, while mothers' avoidance-oriented coping predicted seeking spiritual support. The results demonstrated that: (1) the only differences in terms of coping strategies in adolescents with diabetes and healthy adolescents were found in seeking professional help; (2) gender differences in coping with stress were significantly smaller in adolescents with diabetes than in healthy adolescents, (3) mothers' coping styles were predictors of coping strategies in adolescents, albeit there were differences in that respect between adolescents with diabetes and healthy adolescents.

Learning Strategies and Reading Literacy among Chinese and Finnish Adolescents: Evidence of Suppression

ERIC Educational Resources Information Center

Cai, Yuyang; Zhu, Xinhua

2017-01-01

Many arguments have been advanced in the context of the predictive correlation between learning strategies and reading achievement. There is insufficient understanding, however, of the subtle ways in which different types of learning strategies (i.e. memorisation, elaboration and control strategies) function in facilitating students' reading…

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

NASA Astrophysics Data System (ADS)

Velarde, P.; Valverde, L.; Maestre, J. M.; Ocampo-Martinez, C.; Bordons, C.

2017-03-01

In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.

Finite element based model predictive control for active vibration suppression of a one-link flexible manipulator.

PubMed

Dubay, Rickey; Hassan, Marwan; Li, Chunying; Charest, Meaghan

2014-09-01

This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Predicting fifth-grade students' understanding of ecological science concepts with motivational and cognitive variables

NASA Astrophysics Data System (ADS)

Alao, Solomon

The need to identify factors that contribute to students' understanding of ecological concepts has been widely expressed in recent literature. The purpose of this study was to investigate the relationship between fifth grade students' prior knowledge, learning strategies, interest, and learning goals and their conceptual understanding of ecological science concepts. Subject were 72 students from three fifth grade classrooms located in a metropolitan area of the eastern United States. Students completed the goal commitment, interest, and strategy use questionnaire (GISQ), and a knowledge test designed to assess their prior knowledge and conceptual understanding of ecological science concepts. The learning goals scale assessed intentions to try to learn and understand ecological concepts. The interest scale assessed the feeling and value-related valences that students ascribed to science and ecological science concepts. The strategy use scale assessed the use of two cognitive strategies (monitoring and elaboration). The knowledge test assessed students' understanding of ecological concepts (the relationship between living organisms and their environment). Scores on all measures were examined for gender differences; no significant gender differences were observed. The motivational and cognitive variables contributed to students' understanding of ecological concepts. After accounting for interest, learning goals, and strategy use, prior knowledge accounted for 28% of the total variance in conceptual understanding. After accounting for prior knowledge, interest, learning goals, and strategy use explained 7%, 6%, and 4% of the total variance in conceptual understanding, respectively. More importantly, these variables were interrelated to each other and to conceptual understanding. After controlling for prior knowledge, learning goals, and strategy use, interest did not predict the variance in conceptual understanding. After controlling for prior knowledge, interest, and strategy use, learning goals did not predict the variance in conceptual understanding. And, after controlling for prior knowledge, interest, and learning goals, strategy use did not predict the variance in conceptual understanding. Results of this study indicated that prior knowledge, interest, learning goals, and strategy use should be included in theoretical models design to explain and to predict fifth grade students' understanding of ecological concepts. Results of this study further suggested that curriculum developers and science teachers need to take fifth grade students' prior knowledge of ecological concepts, interest in science and ecological concepts; intentions to learn and understand ecological concepts, and use of cognitive strategies into account when designing instructional contexts to support these students' understanding of ecological concepts.

Multiplexed Predictive Control of a Large Commercial Turbofan Engine

NASA Technical Reports Server (NTRS)

Richter, hanz; Singaraju, Anil; Litt, Jonathan S.

2008-01-01

Model predictive control is a strategy well-suited to handle the highly complex, nonlinear, uncertain, and constrained dynamics involved in aircraft engine control problems. However, it has thus far been infeasible to implement model predictive control in engine control applications, because of the combination of model complexity and the time allotted for the control update calculation. In this paper, a multiplexed implementation is proposed that dramatically reduces the computational burden of the quadratic programming optimization that must be solved online as part of the model-predictive-control algorithm. Actuator updates are calculated sequentially and cyclically in a multiplexed implementation, as opposed to the simultaneous optimization taking place in conventional model predictive control. Theoretical aspects are discussed based on a nominal model, and actual computational savings are demonstrated using a realistic commercial engine model.

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.

Should different marketing communication strategies be used to promote healthy eating among male and female adolescents?

PubMed

Chan, Kara; Ng, Yu-Leung; Prendergast, Gerard

2014-01-01

A study was conducted to examine how interpersonal norms, media norms, attitudes, perceived behavioral control, perceived barriers, and self-efficacy had an influence on healthy eating intention among adolescents. A probability sample of 544 adolescents aged 12 to 18 was conducted. Results indicated that girls had a more favorable attitude and intention toward healthy eating than boys. Healthy eating intention among boys was predicted by attitude, perceived behavioral control, perceived barriers, and self-efficacy, and among girls was predicted by perceived behavioral control and self-efficacy. Different marketing strategies to promote healthy eating among adolescent boys and girls should be adopted.

Optimal combinations of control strategies and cost-effective analysis for visceral leishmaniasis disease transmission.

PubMed

Biswas, Santanu; Subramanian, Abhishek; ELMojtaba, Ibrahim M; Chattopadhyay, Joydev; Sarkar, Ram Rup

2017-01-01

Visceral leishmaniasis (VL) is a deadly neglected tropical disease that poses a serious problem in various countries all over the world. Implementation of various intervention strategies fail in controlling the spread of this disease due to issues of parasite drug resistance and resistance of sandfly vectors to insecticide sprays. Due to this, policy makers need to develop novel strategies or resort to a combination of multiple intervention strategies to control the spread of the disease. To address this issue, we propose an extensive SIR-type model for anthroponotic visceral leishmaniasis transmission with seasonal fluctuations modeled in the form of periodic sandfly biting rate. Fitting the model for real data reported in South Sudan, we estimate the model parameters and compare the model predictions with known VL cases. Using optimal control theory, we study the effects of popular control strategies namely, drug-based treatment of symptomatic and PKDL-infected individuals, insecticide treated bednets and spray of insecticides on the dynamics of infected human and vector populations. We propose that the strategies remain ineffective in curbing the disease individually, as opposed to the use of optimal combinations of the mentioned strategies. Testing the model for different optimal combinations while considering periodic seasonal fluctuations, we find that the optimal combination of treatment of individuals and insecticide sprays perform well in controlling the disease for the time period of intervention introduced. Performing a cost-effective analysis we identify that the same strategy also proves to be efficacious and cost-effective. Finally, we suggest that our model would be helpful for policy makers to predict the best intervention strategies for specific time periods and their appropriate implementation for elimination of visceral leishmaniasis.

A comparison between two simulation models for spread of foot-and-mouth disease.

PubMed

Halasa, Tariq; Boklund, Anette; Stockmarr, Anders; Enøe, Claes; Christiansen, Lasse E

2014-01-01

Two widely used simulation models of foot-and-mouth disease (FMD) were used in order to compare the models' predictions in term of disease spread, consequence, and the ranking of the applied control strategies, and to discuss the effect of the way disease spread is modeled on the predicted outcomes of each model. The DTU-DADS (version 0.100), and ISP (version 2.001.11) were used to simulate a hypothetical spread of FMD in Denmark. Actual herd type, movements, and location data in the period 1st October 2006 and 30th September 2007 was used. The models simulated the spread of FMD using 3 different control scenarios: 1) A basic scenario representing EU and Danish control strategies, 2) pre-emptive depopulation of susceptible herds within a 500 meters radius around the detected herds, and 3) suppressive vaccination of susceptible herds within a 1,000 meters radius around the detected herds. Depopulation and vaccination started 14 days following the detection of the first infected herd. Five thousand index herds were selected randomly, of which there were 1,000 cattle herds located in high density cattle areas and 1,000 in low density cattle areas, 1,000 swine herds located in high density swine areas and 1,000 in low density swine areas, and 1,000 sheep herds. Generally, DTU-DADS predicted larger, longer duration and costlier epidemics than ISP, except when epidemics started in cattle herds located in high density cattle areas. ISP supported suppressive vaccination rather than pre-emptive depopulation, while DTU-DADS was indifferent to the alternative control strategies. Nonetheless, the absolute differences between control strategies were small making the choice of control strategy during an outbreak to be most likely based on practical reasons.

A Comparison between Two Simulation Models for Spread of Foot-and-Mouth Disease

PubMed Central

Halasa, Tariq; Boklund, Anette; Stockmarr, Anders; Enøe, Claes; Christiansen, Lasse E.

2014-01-01

Two widely used simulation models of foot-and-mouth disease (FMD) were used in order to compare the models’ predictions in term of disease spread, consequence, and the ranking of the applied control strategies, and to discuss the effect of the way disease spread is modeled on the predicted outcomes of each model. The DTU-DADS (version 0.100), and ISP (version 2.001.11) were used to simulate a hypothetical spread of FMD in Denmark. Actual herd type, movements, and location data in the period 1st October 2006 and 30th September 2007 was used. The models simulated the spread of FMD using 3 different control scenarios: 1) A basic scenario representing EU and Danish control strategies, 2) pre-emptive depopulation of susceptible herds within a 500 meters radius around the detected herds, and 3) suppressive vaccination of susceptible herds within a 1,000 meters radius around the detected herds. Depopulation and vaccination started 14 days following the detection of the first infected herd. Five thousand index herds were selected randomly, of which there were 1,000 cattle herds located in high density cattle areas and 1,000 in low density cattle areas, 1,000 swine herds located in high density swine areas and 1,000 in low density swine areas, and 1,000 sheep herds. Generally, DTU-DADS predicted larger, longer duration and costlier epidemics than ISP, except when epidemics started in cattle herds located in high density cattle areas. ISP supported suppressive vaccination rather than pre-emptive depopulation, while DTU-DADS was indifferent to the alternative control strategies. Nonetheless, the absolute differences between control strategies were small making the choice of control strategy during an outbreak to be most likely based on practical reasons. PMID:24667525

Predicting tree mortality following gypsy moth defoliation

Treesearch

D.E. Fosbroke; R.R. Hicks; K.W. Gottschalk

1991-01-01

Appropriate application of gypsy moth control strategies requires an accurate prediction of the distribution and intensity of tree mortality prior to defoliation. This prior information is necessary to better target investments in control activities where they are needed. This poster lays the groundwork for developing hazard-rating systems for forests of the...

Optimal Battery Utilization Over Lifetime for Parallel Hybrid Electric Vehicle to Maximize Fuel Economy

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

Patil, Chinmaya; Naghshtabrizi, Payam; Verma, Rajeev

This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of batterymore » aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.« less

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

Scenario-based, closed-loop model predictive control with application to emergency vehicle scheduling

NASA Astrophysics Data System (ADS)

Goodwin, Graham. C.; Medioli, Adrian. M.

2013-08-01

Model predictive control has been a major success story in process control. More recently, the methodology has been used in other contexts, including automotive engine control, power electronics and telecommunications. Most applications focus on set-point tracking and use single-sequence optimisation. Here we consider an alternative class of problems motivated by the scheduling of emergency vehicles. Here disturbances are the dominant feature. We develop a novel closed-loop model predictive control strategy aimed at this class of problems. We motivate, and illustrate, the ideas via the problem of fluid deployment of ambulance resources.

Metering Best Practices Applied in the National Renewable Energy Laboratory's Research Support Facility: A Primer to the 2011 Measured and Modeled Energy Consumption Datasets

DOE Data Explorer

Sheppy, Michael; Beach, A.; Pless, Shanti

2016-08-09

Modern buildings are complex energy systems that must be controlled for energy efficiency. The Research Support Facility (RSF) at the National Renewable Energy Laboratory (NREL) has hundreds of controllers -- computers that communicate with the building's various control systems -- to control the building based on tens of thousands of variables and sensor points. These control strategies were designed for the RSF's systems to efficiently support research activities. Many events that affect energy use cannot be reliably predicted, but certain decisions (such as control strategies) must be made ahead of time. NREL researchers modeled the RSF systems to predict how they might perform. They then monitor these systems to understand how they are actually performing and reacting to the dynamic conditions of weather, occupancy, and maintenance.

The kinetics and location of intra-host HIV evolution to evade cellular immunity are predictable

NASA Astrophysics Data System (ADS)

Barton, John; Goonetilleke, Nilu; Butler, Thomas; Walker, Bruce; McMichael, Andrew; Chakraborty, Arup

Human immunodeficiency virus (HIV) evolves within infected persons to escape targeting and clearance by the host immune system, thereby preventing effective immune control of infection. Knowledge of the timing and pathways of escape that result in loss of control of the virus could aid in the design of effective strategies to overcome the challenge of viral diversification and immune escape. We combined methods from statistical physics and evolutionary dynamics to predict the course of in vivo viral sequence evolution in response to T cell-mediated immune pressure in a cohort of 17 persons with acute HIV infection. Our predictions agree well with both the location of documented escape mutations and the clinically observed time to escape. We also find that that the mutational pathways to escape depend on the viral sequence background due to epistatic interactions. The ability to predict escape pathways, and the duration over which control is maintained by specific immune responses prior to escape, could be exploited for the rational design of immunotherapeutic strategies that may enable long-term control of HIV infection.

Periodic-Zone Model Predictive Control for Diurnal Closed-Loop Operation of an Artificial Pancreas

PubMed Central

Gondhalekar, Ravi; Dassau, Eyal; Zisser, Howard C.; Doyle, Francis J.

2013-01-01

Background The objective of this research is an artificial pancreas (AP) that performs automatic regulation of blood glucose levels in people with type 1 diabetes mellitus. This article describes a control strategy that performs algorithmic insulin dosing for maintaining safe blood glucose levels over prolonged, overnight periods of time and furthermore was designed with outpatient, multiday deployment in mind. Of particular concern is the prevention of nocturnal hypoglycemia, because during sleep, subjects cannot monitor themselves and may not respond to alarms. An AP intended for prolonged and unsupervised outpatient deployment must strategically reduce the risk of hypoglycemia during times of sleep, without requiring user interaction. Methods A diurnal insulin delivery strategy based on predictive control methods is proposed. The so-called “periodic-zone model predictive control” (PZMPC) strategy employs periodically time-dependent blood glucose output target zones and furthermore enforces periodically time-dependent insulin input constraints to modulate its behavior based on the time of day. Results The proposed strategy was evaluated through an extensive simulation-based study and a preliminary clinical trial. Results indicate that the proposed method delivers insulin more conservatively during nighttime than during daytime while maintaining safe blood glucose levels at all times. In clinical trials, the proposed strategy delivered 77% of the amount of insulin delivered by a time-invariant control strategy; specifically, it delivered on average 1.23 U below, compared with 0.31 U above, the nominal basal rate overnight while maintaining comparable, and safe, blood glucose values. Conclusions The proposed PZMPC algorithm strategically prevents nocturnal hypoglycemia and is considered a significant step toward deploying APs into outpatient environments for extended periods of time in full closed-loop operation. PMID:24351171

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

Mine planning and emission control strategies using geostatistics

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

Martino, F.; Kim, Y.C.

1983-03-01

This paper reviews the past four years' research efforts performed jointly by the University of Arizona and the Homer City Owners in which geostatistics were applied to solve various problems associated with coal characterization, mine planning, and development of emission control strategies. Because geostatistics is the only technique which can quantify the degree of confidence associated with a given estimate (or prediction), it played an important role throughout the research efforts. Through geostatistics, it was learned that there is an urgent need for closely spaced sample information, if short-term coal quality predictions are to be made for mine planning purposes.

Data quality assurance and control in cognitive research: Lessons learned from the PREDICT-HD study.

PubMed

Westervelt, Holly James; Bernier, Rachel A; Faust, Melanie; Gover, Mary; Bockholt, H Jeremy; Zschiegner, Roland; Long, Jeffrey D; Paulsen, Jane S

2017-09-01

We discuss the strategies employed in data quality control and quality assurance for the cognitive core of Neurobiological Predictors of Huntington's Disease (PREDICT-HD), a long-term observational study of over 1,000 participants with prodromal Huntington disease. In particular, we provide details regarding the training and continual evaluation of cognitive examiners, methods for error corrections, and strategies to minimize errors in the data. We present five important lessons learned to help other researchers avoid certain assumptions that could potentially lead to inaccuracies in their cognitive data. Copyright © 2017 John Wiley & Sons, Ltd.

Predicting the Impact of Intervention Strategies for Sleeping Sickness in Two High-Endemicity Health Zones of the Democratic Republic of Congo.

PubMed

Rock, Kat S; Torr, Steve J; Lumbala, Crispin; Keeling, Matt J

2017-01-01

Two goals have been set for Gambian human African trypanosomiasis (HAT), the first is to achieve elimination as a public health problem in 90% of foci by 2020, and the second is to achieve zero transmission globally by 2030. It remains unclear if certain HAT hotspots could achieve elimination as a public health problem by 2020 and, of greater concern, it appears that current interventions to control HAT in these areas may not be sufficient to achieve zero transmission by 2030. A mathematical model of disease dynamics was used to assess the potential impact of changing the intervention strategy in two high-endemicity health zones of Kwilu province, Democratic Republic of Congo. Six key strategies and twelve variations were considered which covered a range of recruitment strategies for screening and vector control. It was found that effectiveness of HAT screening could be improved by increasing effort to recruit high-risk groups for screening. Furthermore, seven proposed strategies which included vector control were predicted to be sufficient to achieve an incidence of less than 1 reported case per 10,000 people by 2020 in the study region. All vector control strategies simulated reduced transmission enough to meet the 2030 goal, even if vector control was only moderately effective (60% tsetse population reduction). At this level of control the full elimination threshold was expected to be met within six years following the start of the change in strategy and over 6000 additional cases would be averted between 2017 and 2030 compared to current screening alone. It is recommended that a two-pronged strategy including both enhanced active screening and tsetse control is implemented in this region and in other persistent HAT foci to ensure the success of the control programme and meet the 2030 elimination goal for HAT.

Predicting the Impact of Intervention Strategies for Sleeping Sickness in Two High-Endemicity Health Zones of the Democratic Republic of Congo

PubMed Central

Torr, Steve J.; Lumbala, Crispin; Keeling, Matt J.

2017-01-01

Two goals have been set for Gambian human African trypanosomiasis (HAT), the first is to achieve elimination as a public health problem in 90% of foci by 2020, and the second is to achieve zero transmission globally by 2030. It remains unclear if certain HAT hotspots could achieve elimination as a public health problem by 2020 and, of greater concern, it appears that current interventions to control HAT in these areas may not be sufficient to achieve zero transmission by 2030. A mathematical model of disease dynamics was used to assess the potential impact of changing the intervention strategy in two high-endemicity health zones of Kwilu province, Democratic Republic of Congo. Six key strategies and twelve variations were considered which covered a range of recruitment strategies for screening and vector control. It was found that effectiveness of HAT screening could be improved by increasing effort to recruit high-risk groups for screening. Furthermore, seven proposed strategies which included vector control were predicted to be sufficient to achieve an incidence of less than 1 reported case per 10,000 people by 2020 in the study region. All vector control strategies simulated reduced transmission enough to meet the 2030 goal, even if vector control was only moderately effective (60% tsetse population reduction). At this level of control the full elimination threshold was expected to be met within six years following the start of the change in strategy and over 6000 additional cases would be averted between 2017 and 2030 compared to current screening alone. It is recommended that a two-pronged strategy including both enhanced active screening and tsetse control is implemented in this region and in other persistent HAT foci to ensure the success of the control programme and meet the 2030 elimination goal for HAT. PMID:28056016

Counteracting Obstacles with Optimistic Predictions

ERIC Educational Resources Information Center

Zhang, Ying; Fishbach, Ayelet

2010-01-01

This research tested for counteractive optimism: a self-control strategy of generating optimistic predictions of future goal attainment in order to overcome anticipated obstacles in goal pursuit. In support of the counteractive optimism model, participants in 5 studies predicted better performance, more time invested in goal activities, and lower…

Coping strategies and self-stigma among adolescents discharged from psychiatric hospitalization: a 6-month follow-up study.

PubMed

Moses, Tally

2015-03-01

The effects of mental illness stigma on adolescents receiving psychiatric treatment may largely be determined by their coping strategies. Yet, little is known about adolescents' use of stigma-coping strategies, or how helpful these are for addressing stigma-related stress. This study explores how adolescents discharged from psychiatric hospitalization anticipate coping with a hypothetical social stigma event related to hospitalization. We examine how well anticipated coping strategies predict adolescents' self-stigma ratings following 6 months. To evaluate the direction of causality, the reverse order of effects, the influence of self-stigma on coping strategies, is also assessed. A voluntary sample of 80 adolescents participated in two face-to-face interviews that assessed coping and self-stigma. Anticipated (baseline) and actual (follow-up) coping strategies were measured with a modified Response to Stress Questionnaire (primary and secondary control engagement coping, disengagement) and two stigma-specific strategies developed for this study (disconfirming stereotypes and aggression/confrontation). Relationships between anticipated coping strategies and self-stigma were assessed with ordinary least squares (OLS) regression; multivariate general linear modeling (GLM) and structural equation modeling (SEM) explored the reverse associations. Youth reporting higher self-stigma ratings at follow-up anticipated using more disengagement and effort to disconfirm stereotypes and less secondary control engagement coping at baseline. Anticipated use of secondary control engagement coping was uniquely significant in predicting participants' self-stigma when controlling for baseline self-stigma. At the same time, higher baseline self-stigma ratings predicted less adaptive coping (disengagement and effort to disconfirm stereotypes) at follow-up. The results point to the particular importance of secondary control engagement coping for helping to mitigate the impact of peer prejudice or discrimination on self-stigma among youth receiving psychiatric services. At the same time, higher initial levels of self-stigma likely drive less adaptive coping with peer stigma. These bidirectional influences point to a vicious cycle between internalizing negative stereotypes and coping in ways that perpetuate negative outcomes. © The Author(s) 2014.

Constructing the effect of alternative intervention strategies on historic epidemics.

PubMed

Cook, A R; Gibson, G J; Gottwald, T R; Gilligan, C A

2008-10-06

Data from historical epidemics provide a vital and sometimes under-used resource from which to devise strategies for future control of disease. Previous methods for retrospective analysis of epidemics, in which alternative interventions are compared, do not make full use of the information; by using only partial information on the historical trajectory, augmentation of control may lead to predictions of a paradoxical increase in disease. Here we introduce a novel statistical approach that takes full account of the available information in constructing the effect of alternative intervention strategies in historic epidemics. The key to the method lies in identifying a suitable mapping between the historic and notional outbreaks, under alternative control strategies. We do this by using the Sellke construction as a latent process linking epidemics. We illustrate the application of the method with two examples. First, using temporal data for the common human cold, we show the improvement under the new method in the precision of predictions for different control strategies. Second, we show the generality of the method for retrospective analysis of epidemics by applying it to a spatially extended arboreal epidemic in which we demonstrate the relative effectiveness of host culling strategies that differ in frequency and spatial extent. Some of the inferential and philosophical issues that arise are discussed along with the scope of potential application of the new method.

Coping with stress in adolescents with Type 1 diabetes and their mothers

PubMed Central

2010-01-01

Objectives Coping with stress plays a vital role in the adjustment of adolescents with diabetes. The majority of studies in this area leave out the control group, limiting their power to make inferences about specificity vs. similarity of coping strategies used by these adolescents. The aims of this study were: (1) To compare coping strategies in adolescents with diabetes and healthy adolescents; (2) To compare coping strategies in girls and boys with diabetes; (3) To determine whether there is a relationship between adolescents' coping strategies and their mothers' coping styles. Material and methods Adolescents (12-17 years old) with Type 1 diabetes (n = 51) were compared with a control group of healthy secondary school students (n = 56) by means of a self-reported questionnaire measuring coping strategies (Adolescence Coping Checklist). Mothers of these adolescents (n = 107) completed the Coping Inventory for Stressful Situations, measuring 3 coping styles. Results Diabetic adolescents used the 'seek professional help' strategy more often than their healthy peers. The girls with diabetes reported using the 'investing in close friends' strategy more often than boys, while in the control group girls were also more likely to use 'seeking social support', 'seeking spiritual support', and 'relaxing diversions' strategies. Mothers' emotion-oriented coping style predicted focus-oriented coping in adolescents with diabetes. In the non-diabetic group, mothers' task-oriented coping predicted seeking professional help, while mothers' avoidance-oriented coping predicted seeking spiritual support. Conclusions The results demonstrated that: (1) the only differences in terms of coping strategies in adolescents with diabetes and healthy adolescents were found in seeking professional help; (2) gender differences in coping with stress were significantly smaller in adolescents with diabetes than in healthy adolescents, (3) mothers' coping styles were predictors of coping strategies in adolescents, albeit there were differences in that respect between adolescents with diabetes and healthy adolescents. PMID:21147637

The role of strategic attention deployment in development of self-regulation: predicting preschoolers' delay of gratification from mother-toddler interactions.

PubMed

Sethi, A; Mischel, W; Aber, J L; Shoda, Y; Rodriguez, M L

2000-11-01

Toddlers' use of effective attention deployment strategies to cope with separation from the mother and with maternal behavior predicted the use of effective delay-of-gratification strategies at age 5, even though the contexts, measures, and manifest behaviors were different. Toddlers who used distraction strategies during a brief separation from the mother were able, at age 5, to delay immediate gratification longer for more valued rewards. Toddlers who explored at a distance from a controlling mother when she tried to engage the child also delayed longer and used more effective delay strategies at age 5, compared with toddlers who did not distance themselves. Toddlers whose mothers were not controlling showed the opposite pattern: Those who did not distance themselves from the mother's bids had longer preschool delay times and more effective strategies. Strategic attention deployment was shown to be an enduring self-regulatory skill visible in early development across domains, measures, and over time.

Disease prevention versus data privacy: using landcover maps to inform spatial epidemic models.

PubMed

Tildesley, Michael J; Ryan, Sadie J

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock.

Disease Prevention versus Data Privacy: Using Landcover Maps to Inform Spatial Epidemic Models

PubMed Central

Tildesley, Michael J.; Ryan, Sadie J.

2012-01-01

The availability of epidemiological data in the early stages of an outbreak of an infectious disease is vital for modelers to make accurate predictions regarding the likely spread of disease and preferred intervention strategies. However, in some countries, the necessary demographic data are only available at an aggregate scale. We investigated the ability of models of livestock infectious diseases to predict epidemic spread and obtain optimal control policies in the event of imperfect, aggregated data. Taking a geographic information approach, we used land cover data to predict UK farm locations and investigated the influence of using these synthetic location data sets upon epidemiological predictions in the event of an outbreak of foot-and-mouth disease. When broadly classified land cover data were used to create synthetic farm locations, model predictions deviated significantly from those simulated on true data. However, when more resolved subclass land use data were used, moderate to highly accurate predictions of epidemic size, duration and optimal vaccination and ring culling strategies were obtained. This suggests that a geographic information approach may be useful where individual farm-level data are not available, to allow predictive analyses to be carried out regarding the likely spread of disease. This method can also be used for contingency planning in collaboration with policy makers to determine preferred control strategies in the event of a future outbreak of infectious disease in livestock. PMID:23133352

Structure-based feeding strategies: A key component of child nutrition.

PubMed

Taylor, Maija B; Emley, Elizabeth; Pratt, Mercedes; Musher-Eizenman, Dara R

2017-07-01

This study examined the relationship between structure, autonomy promotion, and control feeding strategies and parent-reported child diet. Participants (N = 497) were parents of children ages 2.5 to 7.5 recruited from Amazon Mechanical Turk. This sample was a Caucasian (79%), educated sample (61% college graduates) with most reports from mothers (76%). Online survey including measures of parent feeding strategies and child dietary intake. Use of structure-based feeding strategies explained 21% of the variance in child consumption of added sugar, 12% of the variance in child intake of added sugar from sugar-sweetened beverages, and 16% of the variance in child consumption of fruits and vegetables. Higher unhealthy food availability and permissive feeding uniquely predicted higher child added sugar intake and child consumption of added sugar from sugar-sweetened beverages. Greater healthy food availability uniquely predicted higher child fruit and vegetable intake. and Future Directions: In Caucasian educated families, structure-based feeding strategies appear to be a relatively stronger correlate of parent-reported child intake of added sugar and fruits and vegetables as compared to autonomy promotion and control feeding strategies. Longitudinal research may be needed in order to reveal the relationships between autonomy promotion and control feeding strategies with child diet. If future studies have similar findings to this study's results, researchers may want to focus more heavily on investigating the impact of teaching parents stimulus-control techniques and feeding-related assertiveness skills on child dietary intake. Copyright © 2017 Elsevier Ltd. All rights reserved.

Personal contextual characteristics and cognitions: predicting child abuse potential and disciplinary style.

PubMed

Rodriguez, Christina M

2010-02-01

According to Social Information Processing theory, parents' cognitive processes influence their decisions to engage in physical maltreatment, although cognitions occur in the context of other aspects of the parents' life. The present study investigated whether cognitive processes (external locus of control, inappropriate developmental expectations) predicted child abuse potential and overreactive disciplinary style beyond personal contextual factors characteristic of the parent (hostility, stress, and coping). 363 parents were recruited online. Results highlight the relative importance of the contextual characteristics (particularly stress, avoidant coping, and irritability) relative to cognitive processes in predicting abuse potential and overreactive discipline strategies, although an external locus of control also significantly contributed. Findings do not support that parents' developmental expectations uniquely predict elevated abuse risk. Results indicate stressed parents who utilize avoidance coping strategies are more likely to use overreactive discipline and report increased abuse potential. Findings are discussed with regard to implications for prevention/intervention efforts.

Does believing in "use it or lose it" relate to self-rated memory control, strategy use, and recall?

PubMed

Hertzog, Christopher; McGuire, Christy L; Horhota, Michelle; Jopp, Daniela

2010-01-01

After an oral free recall task, participants were interviewed about their memory. Despite reporting similar levels of perceived personal control over memory, older and young adults differed in the means in which they believed memory could be controlled. Older adults cited health and wellness practices and exercising memory, consistent with a "use it or lose it" belief system, more often than young adults who were more likely to mention metacognition and flexible strategy use as means of memory control. Young adults reported using more effective relational strategies during study for a free recall test. Use of relational strategies predicted recall in both age groups, but did not materially affect age differences in performance. Metacognitive beliefs, including implicit theories about aging and memory decline, memory self-concept, and perceived control over memory functioning, did not systematically correlate with strategy use or recall.

Predictive control strategy of a gas turbine for improvement of combined cycle power plant dynamic performance and efficiency.

PubMed

Mohamed, Omar; Wang, Jihong; Khalil, Ashraf; Limhabrash, Marwan

2016-01-01

This paper presents a novel strategy for implementing model predictive control (MPC) to a large gas turbine power plant as a part of our research progress in order to improve plant thermal efficiency and load-frequency control performance. A generalized state space model for a large gas turbine covering the whole steady operational range is designed according to subspace identification method with closed loop data as input to the identification algorithm. Then the model is used in developing a MPC and integrated into the plant existing control strategy. The strategy principle is based on feeding the reference signals of the pilot valve, natural gas valve, and the compressor pressure ratio controller with the optimized decisions given by the MPC instead of direct application of the control signals. If the set points for the compressor controller and turbine valves are sent in a timely manner, there will be more kinetic energy in the plant to release faster responses on the output and the overall system efficiency is improved. Simulation results have illustrated the feasibility of the proposed application that has achieved significant improvement in the frequency variations and load following capability which are also translated to be improvements in the overall combined cycle thermal efficiency of around 1.1 % compared to the existing one.

Mechanical effort predicts the selection of ankle over hip strategies in nonstepping postural responses

PubMed Central

Jonkers, Ilse; De Schutter, Joris; De Groote, Friedl

2016-01-01

Experimental studies have shown that a continuum of ankle and hip strategies is used to restore posture following an external perturbation. Postural responses can be modeled by feedback control with feedback gains that optimize a specific objective. On the one hand, feedback gains that minimize effort have been used to predict muscle activity during perturbed standing. On the other hand, hip and ankle strategies have been predicted by minimizing postural instability and deviation from upright posture. It remains unclear, however, whether and how effort minimization influences the selection of a specific postural response. We hypothesize that the relative importance of minimizing mechanical work vs. postural instability influences the strategy used to restore upright posture. This hypothesis was investigated based on experiments and predictive simulations of the postural response following a backward support surface translation. Peak hip flexion angle was significantly correlated with three experimentally determined measures of effort, i.e., mechanical work, mean muscle activity and metabolic energy. Furthermore, a continuum of ankle and hip strategies was predicted in simulation when changing the relative importance of minimizing mechanical work and postural instability, with increased weighting of mechanical work resulting in an ankle strategy. In conclusion, the combination of experimental measurements and predictive simulations of the postural response to a backward support surface translation showed that the trade-off between effort and postural instability minimization can explain the selection of a specific postural response in the continuum of potential ankle and hip strategies. PMID:27489362

Multi-model predictive control based on LMI: from the adaptation of the state-space model to the analytic description of the control law

NASA Astrophysics Data System (ADS)

Falugi, P.; Olaru, S.; Dumur, D.

2010-08-01

This article proposes an explicit robust predictive control solution based on linear matrix inequalities (LMIs). The considered predictive control strategy uses different local descriptions of the system dynamics and uncertainties and thus allows the handling of less conservative input constraints. The computed control law guarantees constraint satisfaction and asymptotic stability. The technique is effective for a class of nonlinear systems embedded into polytopic models. A detailed discussion of the procedures which adapt the partition of the state space is presented. For the practical implementation the construction of suitable (explicit) descriptions of the control law are described upon concrete algorithms.

Enhanced pid vs model predictive control applied to bldc motor

NASA Astrophysics Data System (ADS)

Gaya, M. S.; Muhammad, Auwal; Aliyu Abdulkadir, Rabiu; Salim, S. N. S.; Madugu, I. S.; Tijjani, Aminu; Aminu Yusuf, Lukman; Dauda Umar, Ibrahim; Khairi, M. T. M.

2018-01-01

BrushLess Direct Current (BLDC) motor is a multivariable and highly complex nonlinear system. Variation of internal parameter values with environment or reference signal increases the difficulty in controlling the BLDC effectively. Advanced control strategies (like model predictive control) often have to be integrated to satisfy the control desires. Enhancing or proper tuning of a conventional algorithm results in achieving the desired performance. This paper presents a performance comparison of Enhanced PID and Model Predictive Control (MPC) applied to brushless direct current motor. The simulation results demonstrated that the PSO-PID is slightly better than the PID and MPC in tracking the trajectory of the reference signal. The proposed scheme could be useful algorithms for the system.

Predictive validity of the classroom strategies scale-observer form on statewide testing scores: an initial investigation.

PubMed

Reddy, Linda A; Fabiano, Gregory A; Dudek, Christopher M; Hsu, Louis

2013-12-01

The present study examined the validity of a teacher observation measure, the Classroom Strategies Scale--Observer Form (CSS), as a predictor of student performance on statewide tests of mathematics and English language arts. The CSS is a teacher practice observational measure that assesses evidence-based instructional and behavioral management practices in elementary school. A series of two-level hierarchical generalized linear models were fitted to data of a sample of 662 third- through fifth-grade students to assess whether CSS Part 2 Instructional Strategy and Behavioral Management Strategy scale discrepancy scores (i.e., ∑ |recommended frequency--frequency ratings|) predicted statewide mathematics and English language arts proficiency scores when percentage of minority students in schools was controlled. Results indicated that the Instructional Strategy scale discrepancy scores significantly predicted mathematics and English language arts proficiency scores: Relatively larger discrepancies on observer ratings of what teachers did versus what should have been done were associated with lower proficiency scores. Results offer initial evidence of the predictive validity of the CSS Part 2 Instructional Strategy discrepancy scores on student academic outcomes. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Within Your Control? When Problem Solving May Be Most Helpful.

PubMed

Sarfan, Laurel D; Gooch, Peter; Clerkin, Elise M

2017-08-01

Emotion regulation strategies have been conceptualized as adaptive or maladaptive, but recent evidence suggests emotion regulation outcomes may be context-dependent. The present study tested whether the adaptiveness of a putatively adaptive emotion regulation strategy-problem solving-varied across contexts of high and low controllability. The present study also tested rumination, suggested to be one of the most putatively maladaptive strategies, which was expected to be associated with negative outcomes regardless of context. Participants completed an in vivo speech task, in which they were randomly assigned to a controllable ( n = 65) or an uncontrollable ( n = 63) condition. Using moderation analyses, we tested whether controllability interacted with emotion regulation use to predict negative affect, avoidance, and perception of performance. Partially consistent with hypotheses, problem solving was associated with certain positive outcomes (i.e., reduced behavioral avoidance) in the controllable (vs. uncontrollable) condition. Consistent with predictions, rumination was associated with negative outcomes (i.e., desired avoidance, negative affect, negative perception of performance) in both conditions. Overall, findings partially support contextual models of emotion regulation, insofar as the data suggest that the effects of problem solving may be more adaptive in controllable contexts for certain outcomes, whereas rumination may be maladaptive regardless of context.

State feedback control design for Boolean networks.

PubMed

Liu, Rongjie; Qian, Chunjiang; Liu, Shuqian; Jin, Yu-Fang

2016-08-26

Driving Boolean networks to desired states is of paramount significance toward our ultimate goal of controlling the progression of biological pathways and regulatory networks. Despite recent computational development of controllability of general complex networks and structural controllability of Boolean networks, there is still a lack of bridging the mathematical condition on controllability to real boolean operations in a network. Further, no realtime control strategy has been proposed to drive a Boolean network. In this study, we applied semi-tensor product to represent boolean functions in a network and explored controllability of a boolean network based on the transition matrix and time transition diagram. We determined the necessary and sufficient condition for a controllable Boolean network and mapped this requirement in transition matrix to real boolean functions and structure property of a network. An efficient tool is offered to assess controllability of an arbitrary Boolean network and to determine all reachable and non-reachable states. We found six simplest forms of controllable 2-node Boolean networks and explored the consistency of transition matrices while extending these six forms to controllable networks with more nodes. Importantly, we proposed the first state feedback control strategy to drive the network based on the status of all nodes in the network. Finally, we applied our reachability condition to the major switch of P53 pathway to predict the progression of the pathway and validate the prediction with published experimental results. This control strategy allowed us to apply realtime control to drive Boolean networks, which could not be achieved by the current control strategy for Boolean networks. Our results enabled a more comprehensive understanding of the evolution of Boolean networks and might be extended to output feedback control design.

Category and design fluency in mild cognitive impairment: Performance, strategy use, and neural correlates.

PubMed

Peter, Jessica; Kaiser, Jannis; Landerer, Verena; Köstering, Lena; Kaller, Christoph P; Heimbach, Bernhard; Hüll, Michael; Bormann, Tobias; Klöppel, Stefan

2016-12-01

The exploration and retrieval of words during category fluency involves different strategies to improve or maintain performance. Deficits in that task, which are common in patients with amnestic mild cognitive impairment (aMCI), mirror either impaired semantic memory or dysfunctional executive control mechanisms. Relating category fluency to tasks that place greater demands on either semantic knowledge or executive functions might help to determine the underlying cognitive process. The aims of this study were to compare performance and strategy use of 20 patients with aMCI to 30 healthy elderly controls (HC) and to identify the dominant component (either executive or semantic) for better task performance in category fluency. Thus, the relationship between category fluency, design fluency and naming was examined. As fluency tasks have been associated with the superior frontal gyrus (SFG), the inferior frontal gyrus (IFG), and the temporal pole, we further explored the relationship between gray matter volume in these areas and both performance and strategy use. Patients with aMCI showed significantly lower performance and significantly less strategy use during fluency tasks compared to HC. However, both groups equally improved their performance when repeatedly confronted with the same task. In aMCI, performance during category fluency was significantly predicted by design fluency performance, while in HC, it was significantly predicted by naming performance. In HC, volume of the SFG significantly predicted both category and design fluency performance, and strategy use during design fluency. In aMCI, the SFG and the IFG predicted performance during both category and design fluency. The IFG significantly predicted strategy use during category fluency in both groups. The reduced category fluency performance in aMCI seems to be primarily due to dysfunctional executive control mechanisms rather than impaired semantic knowledge. This finding is directly relevant to patients in the different stages of Alzheimer's disease as it links the known semantic fluency deficit in this population to executive functions. Although patients with aMCI are impaired in both performance and strategy use compared to HC, they are able to increase performance over time. However, only HC were able to significantly improve the utilization of fluency strategies in both category and design fluency over time. HC seem to rely more heavily on the SFG during fluency tasks, while in patients with aMCI additional frontal brain areas are involved, possibly reflecting compensational processes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction based active ramp metering control strategy with mobility and safety assessment

NASA Astrophysics Data System (ADS)

Fang, Jie; Tu, Lili

2018-04-01

Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

Predictive Multiple Model Switching Control with the Self-Organizing Map

NASA Technical Reports Server (NTRS)

Motter, Mark A.

2000-01-01

A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

Predictive Management of Asian Carps in the Upper Mississippi River System

USGS Publications Warehouse

Vondracek, Bruce C.; Carlson, Andrew K.

2014-01-01

Prolific non-native organisms pose serious threats to ecosystems and economies worldwide. Nonnative bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix), collectively referred to as Asian carps, continue to colonize aquatic ecosystems throughout the central United States. These species are r-selected, exhibiting iteroparous spawning, rapid growth, broad environmental tolerance, high density, and long-distance movement. Hydrological, thermal, and physicochemical conditions are favorable for establishment beyond the current range, rendering containment and control imperative. Ecological approaches to confine Asian carp populations and prevent colonization characterize contemporary management in the United States. Foraging and reproduction of Asian carps govern habitat selection and movement, providing valuable insight for predictive control. Current management approaches are progressive and often anticipatory but deficient in human dimensions. We define predictive management of Asian carps as synthesis of ecology and human dimensions at regional and local scales to develop strategies for containment and control. We illustrate predictive management in the Upper Mississippi River System and suggest resource managers integrate predictive models, containment paradigms, and human dimensions to design effective, socially acceptable management strategies. Through continued research, university-agency collaboration, and public engagement, predictive management of Asian carps is an auspicious paradigm for preventing and alleviating consequences of colonization in the United States.

Analyses of the most influential factors for vibration monitoring of planetary power transmissions in pellet mills by adaptive neuro-fuzzy technique

NASA Astrophysics Data System (ADS)

Milovančević, Miloš; Nikolić, Vlastimir; Anđelković, Boban

2017-01-01

Vibration-based structural health monitoring is widely recognized as an attractive strategy for early damage detection in civil structures. Vibration monitoring and prediction is important for any system since it can save many unpredictable behaviors of the system. If the vibration monitoring is properly managed, that can ensure economic and safe operations. Potentials for further improvement of vibration monitoring lie in the improvement of current control strategies. One of the options is the introduction of model predictive control. Multistep ahead predictive models of vibration are a starting point for creating a successful model predictive strategy. For the purpose of this article, predictive models of are created for vibration monitoring of planetary power transmissions in pellet mills. The models were developed using the novel method based on ANFIS (adaptive neuro fuzzy inference system). The aim of this study is to investigate the potential of ANFIS for selecting the most relevant variables for predictive models of vibration monitoring of pellet mills power transmission. The vibration data are collected by PIC (Programmable Interface Controller) microcontrollers. The goal of the predictive vibration monitoring of planetary power transmissions in pellet mills is to indicate deterioration in the vibration of the power transmissions before the actual failure occurs. The ANFIS process for variable selection was implemented in order to detect the predominant variables affecting the prediction of vibration monitoring. It was also used to select the minimal input subset of variables from the initial set of input variables - current and lagged variables (up to 11 steps) of vibration. The obtained results could be used for simplification of predictive methods so as to avoid multiple input variables. It was preferable to used models with less inputs because of overfitting between training and testing data. While the obtained results are promising, further work is required in order to get results that could be directly applied in practice.

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

NASA Astrophysics Data System (ADS)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

Weight-control behaviors and subsequent weight change among adolescents and young adult females123

PubMed Central

Haines, Jess; Rosner, Bernard; Willett, Walter C

2010-01-01

Background: Little is known about the effectiveness of behavioral strategies to prevent long-term weight gain among adolescents and young adults. Objective: The objective was to assess the relation of dietary and physical activity weight-control strategies, alone and together, with subsequent weight change. Design: This was a prospective study of 4456 female adolescents and young adults aged 14–22 y in the ongoing Growing Up Today Study. Weight-control behaviors, including dietary approaches and physical activity, were self-reported in 2001 and were used to predict weight change from 2001 to 2005. Results: In 2001–2002, 23.7% of female adolescents and young adults were trying to maintain their weight and another 54.4% were trying to lose weight. Approximately 25% used each of the following weight-control strategies: not eating snacks, following low-calorie or low-fat diets, and limiting portion sizes. In addition, 47.7% reported exercising at least occasionally for weight control. During 4 y of follow-up, participants gained an average of 3.3 kg. None of the dietary approaches to weight control predicted less weight change; however, females who exercised ≥5 d/wk gained significantly less weight than did their peers (−0.9 kg; 95% CI: −1.4, −0.4). The most successful strategy for weight-gain prevention among the females was to limit portion sizes (−1.9 kg; 95% CI: −2.6, −1.1) combined with frequent exercise. Conclusions: Our results suggest that physical activity is a necessary strategy for long-term weight control among adolescents and young adult females. Combining dietary weight-control approaches with physical activity is the most effective method for reducing weight gain. PMID:19889827

Using the integrative model of behavioral prediction to identify promising message strategies to promote healthy sleep behavior among college students.

PubMed

Robbins, Rebecca; Niederdeppe, Jeff

2015-01-01

This research used the Integrative Model of Behavioral Prediction (IMBP) to examine cognitive predictors of intentions to engage in healthy sleep behavior among a population of college students. In doing so, we identify promising message strategies to increase healthy sleep behavior during college. In Phase 1, members of a small sample of undergraduates (n = 31) were asked to describe their beliefs about expected outcomes, norms, and perceived behavioral control associated with sleep on an open-ended questionnaire. We analyzed these qualitative responses to create a closed-ended survey about sleep-related attitudes, perceived norms, control beliefs, behavioral intentions, and behavior. In Phase 2, a larger sample of undergraduate students (n = 365) completed the survey. Attitudes and perceived behavioral control were the strongest predictors of both intentions to engage in sleep behavior and self-reported sleep behavior. Control beliefs associated with time management and stress also had substantial room to change, suggesting their potential as message strategies to better promote healthy sleep behavior in college. We conclude with a broader discussion of the study's implications for message design and intervention.

Dynamic performance analysis of permanent magnet contactor with a flux-weakening control strategy

NASA Astrophysics Data System (ADS)

Wang, Xianbing; Lin, Heyun; Fang, Shuhua; Jin, Ping; Wang, Junhua; Ho, S. L.

2011-04-01

A new flux-weakening control strategy for permanent magnet contactors is proposed. By matching the dynamic attraction force and the antiforce, the terminal velocity and collision energy of the movable iron in the closing process are significantly reduced. The movable iron displacement is estimated by detecting the closing voltage and current with the proposed control. A dynamic mathematical model is also established under four kinds of excitation scenarios. The attraction force and flux linkage are predicted by finite element method and the dynamics of the closing process is simulated using the 4th-order Runge-Kutta algorithm. Experiments are carried out on a 250A prototype with an intelligent control unit to verify the proposed control strategy.

Image quality prediction - An aid to the Viking lander imaging investigation on Mars

NASA Technical Reports Server (NTRS)

Huck, F. O.; Wall, S. D.

1976-01-01

Image quality criteria and image quality predictions are formulated for the multispectral panoramic cameras carried by the Viking Mars landers. Image quality predictions are based on expected camera performance, Mars surface radiance, and lighting and viewing geometry (fields of view, Mars lander shadows, solar day-night alternation), and are needed in diagnosis of camera performance, in arriving at a preflight imaging strategy, and revision of that strategy should the need arise. Landing considerations, camera control instructions, camera control logic, aspects of the imaging process (spectral response, spatial response, sensitivity), and likely problems are discussed. Major concerns include: degradation of camera response by isotope radiation, uncertainties in lighting and viewing geometry and in landing site local topography, contamination of camera window by dust abrasion, and initial errors in assigning camera dynamic ranges (gains and offsets).

Mitigating Future Avian Malaria Threats to Hawaiian Forest Birds from Climate Change.

PubMed

Liao, Wei; Atkinson, Carter T; LaPointe, Dennis A; Samuel, Michael D

2017-01-01

Avian malaria, transmitted by Culex quinquefasciatus mosquitoes in the Hawaiian Islands, has been a primary contributor to population range limitations, declines, and extinctions for many endemic Hawaiian honeycreepers. Avian malaria is strongly influenced by climate; therefore, predicted future changes are expected to expand transmission into higher elevations and intensify and lengthen existing transmission periods at lower elevations, leading to further population declines and potential extinction of highly susceptible honeycreepers in mid- and high-elevation forests. Based on future climate changes and resulting malaria risk, we evaluated the viability of alternative conservation strategies to preserve endemic Hawaiian birds at mid and high elevations through the 21st century. We linked an epidemiological model with three alternative climatic projections from the Coupled Model Intercomparison Project to predict future malaria risk and bird population dynamics for the coming century. Based on climate change predictions, proposed strategies included mosquito population suppression using modified males, release of genetically modified refractory mosquitoes, competition from other introduced mosquitoes that are not competent vectors, evolved malaria-tolerance in native honeycreepers, feral pig control to reduce mosquito larval habitats, and predator control to improve bird demographics. Transmission rates of malaria are predicted to be higher than currently observed and are likely to have larger impacts in high-elevation forests where current low rates of transmission create a refuge for highly-susceptible birds. As a result, several current and proposed conservation strategies will be insufficient to maintain existing forest bird populations. We concluded that mitigating malaria transmission at high elevations should be a primary conservation goal. Conservation strategies that maintain highly susceptible species like Iiwi (Drepanis coccinea) will likely benefit other threatened and endangered Hawai'i species, especially in high-elevation forests. Our results showed that mosquito control strategies offer potential long-term benefits to high elevation Hawaiian honeycreepers. However, combined strategies will likely be needed to preserve endemic birds at mid elevations. Given the delay required to research, develop, evaluate, and improve several of these currently untested conservation strategies we suggest that planning should begin expeditiously.

Mitigating future avian malaria threats to Hawaiian forest birds from climate change

USGS Publications Warehouse

Liao, Wei; Atkinson, Carter T.; LaPointe, Dennis; Samuel, Michael D.

2017-01-01

Avian malaria, transmitted by Culex quinquefasciatus mosquitoes in the Hawaiian Islands, has been a primary contributor to population range limitations, declines, and extinctions for many endemic Hawaiian honeycreepers. Avian malaria is strongly influenced by climate; therefore, predicted future changes are expected to expand transmission into higher elevations and intensify and lengthen existing transmission periods at lower elevations, leading to further population declines and potential extinction of highly susceptible honeycreepers in mid- and high-elevation forests. Based on future climate changes and resulting malaria risk, we evaluated the viability of alternative conservation strategies to preserve endemic Hawaiian birds at mid and high elevations through the 21st century. We linked an epidemiological model with three alternative climatic projections from the Coupled Model Intercomparison Project to predict future malaria risk and bird population dynamics for the coming century. Based on climate change predictions, proposed strategies included mosquito population suppression using modified males, release of genetically modified refractory mosquitoes, competition from other introduced mosquitoes that are not competent vectors, evolved malaria-tolerance in native honeycreepers, feral pig control to reduce mosquito larval habitats, and predator control to improve bird demographics. Transmission rates of malaria are predicted to be higher than currently observed and are likely to have larger impacts in high-elevation forests where current low rates of transmission create a refuge for highly-susceptible birds. As a result, several current and proposed conservation strategies will be insufficient to maintain existing forest bird populations. We concluded that mitigating malaria transmission at high elevations should be a primary conservation goal. Conservation strategies that maintain highly susceptible species like Iiwi (Drepanis coccinea) will likely benefit other threatened and endangered Hawai’i species, especially in high-elevation forests. Our results showed that mosquito control strategies offer potential long-term benefits to high elevation Hawaiian honeycreepers. However, combined strategies will likely be needed to preserve endemic birds at mid elevations. Given the delay required to research, develop, evaluate, and improve several of these currently untested conservation strategies we suggest that planning should begin expeditiously.

Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation

NASA Astrophysics Data System (ADS)

Li, Guang

2017-01-01

This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.

Data analytics and optimization of an ice-based energy storage system for commercial buildings

DOE PAGES

Luo, Na; Hong, Tianzhen; Li, Hui; ...

2017-07-25

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential whenmore » the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.« less

Data analytics and optimization of an ice-based energy storage system for commercial buildings

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

Luo, Na; Hong, Tianzhen; Li, Hui

Ice-based thermal energy storage (TES) systems can shift peak cooling demand and reduce operational energy costs (with time-of-use rates) in commercial buildings. The accurate prediction of the cooling load, and the optimal control strategy for managing the charging and discharging of a TES system, are two critical elements to improving system performance and achieving energy cost savings. This study utilizes data-driven analytics and modeling to holistically understand the operation of an ice–based TES system in a shopping mall, calculating the system’s performance using actual measured data from installed meters and sensors. Results show that there is significant savings potential whenmore » the current operating strategy is improved by appropriately scheduling the operation of each piece of equipment of the TES system, as well as by determining the amount of charging and discharging for each day. A novel optimal control strategy, determined by an optimization algorithm of Sequential Quadratic Programming, was developed to minimize the TES system’s operating costs. Three heuristic strategies were also investigated for comparison with our proposed strategy, and the results demonstrate the superiority of our method to the heuristic strategies in terms of total energy cost savings. Specifically, the optimal strategy yields energy costs of up to 11.3% per day and 9.3% per month compared with current operational strategies. A one-day-ahead hourly load prediction was also developed using machine learning algorithms, which facilitates the adoption of the developed data analytics and optimization of the control strategy in a real TES system operation.« less

Drug Resistance and Substance Use Among Male and Female Adolescents in Alternative Secondary Schools in Guanajuato, Mexico

PubMed Central

Kulis, Stephen; Marsiglia, Flavio F.; Ayers, Stephanie L.; Booth, Jaime; Nuño-Gutiérrez, Bertha L.

2012-01-01

Objective: Research is limited on the strategies that Mexican adolescents use to resist use of alcohol, cigarettes, and other drugs. Cultural norms and gender socialization patterns concerning the acceptability of use of various substances by women and men influence Mexican youths in their responses to offers of substances. This study explored the drug-resistance strategies used by youth in the central Mexican state of Guanajuato, how their use predicted patterns of substance use, and how these associations differed by gender. Method: The analysis used cross-sectional survey data from 702 (60% male) students enrolled in eight alternative secondary education school sites in 2007. Participants reported the drug-resistance behaviors they used to deal with offers of alcohol, cigarettes, and marijuana. Past-12-month use of the four drug-resistance strategies employed most often by U.S. youth—refuse, explain, avoid, and leave (R.E.A.L.)—and any other strategies were measured. Composite measures of lifetime and recent use of alcohol, cigarettes, and marijuana were predicted in multivariate ordinary least squares regression analyses. Models were tested with and without controls for the frequency that respondents were offered substances and introduced gender interaction effects. Results: Controlling for substance use offers, more frequent use of a wide repertoire of R.E.A.L. strategies predicted less consumption of alcohol and cigarettes, and using non-R.E.A.L. strategies predicted less marijuana consumption. All of these relationships were either stronger for males than for females or significant for males only. Conclusions: Gender differences exist in the impact of R.E.A.L. strategies on substance use among youth in Mexico. Despite a narrowing gender gap in substance use in Mexico, large exposure to and susceptibility of substance use remains. Developing effective prevention programs in Mexico based on teaching appropriate drug-resistance strategies and enhancing communication skills could aid in reducing substance use among Mexican adolescents. PMID:22152668

Identifying Stride-To-Stride Control Strategies in Human Treadmill Walking

PubMed Central

Dingwell, Jonathan B.; Cusumano, Joseph P.

2015-01-01

Variability is ubiquitous in human movement, arising from internal and external noise, inherent biological redundancy, and from the neurophysiological control actions that help regulate movement fluctuations. Increased walking variability can lead to increased energetic cost and/or increased fall risk. Conversely, biological noise may be beneficial, even necessary, to enhance motor performance. Indeed, encouraging more variability actually facilitates greater improvements in some forms of locomotor rehabilitation. Thus, it is critical to identify the fundamental principles humans use to regulate stride-to-stride fluctuations in walking. This study sought to determine how humans regulate stride-to-stride fluctuations in stepping movements during treadmill walking. We developed computational models based on pre-defined goal functions to compare if subjects, from each stride to the next, tried to maintain the same speed as the treadmill, or instead stay in the same position on the treadmill. Both strategies predicted average behaviors empirically indistinguishable from each other and from that of humans. These strategies, however, predicted very different stride-to-stride fluctuation dynamics. Comparisons to experimental data showed that human stepping movements were generally well-predicted by the speed-control model, but not by the position-control model. Human subjects also exhibited no indications they corrected deviations in absolute position only intermittently: i.e., closer to the boundaries of the treadmill. Thus, humans clearly do not adopt a control strategy whose primary goal is to maintain some constant absolute position on the treadmill. Instead, humans appear to regulate their stepping movements in a way most consistent with a strategy whose primary goal is to try to maintain the same speed as the treadmill at each consecutive stride. These findings have important implications both for understanding how biological systems regulate walking in general and for being able to harness these mechanisms to develop more effective rehabilitation interventions to improve locomotor performance. PMID:25910253

Locus of Control & Motivation Strategies for Learning Questionnaire: Predictors of Student Success on the ATI Comprehensive Predictor Exam & NCLEX-RN Examination

ERIC Educational Resources Information Center

Carpenter, Jane H.

2011-01-01

The two purposes of this study were to determine whether locus of control (LOC) was predictive of how a student would perform on the ATI Comprehensive Predictor Exam and the NCLEX-RN, and if the Motivated Strategies for Learning Questionnaire (MSLQ) provided information that would help determine predictors of success on these two exams. The study…

State dependent model predictive control for orbital rendezvous using pulse-width pulse-frequency modulated thrusters

NASA Astrophysics Data System (ADS)

Li, Peng; Zhu, Zheng H.; Meguid, S. A.

2016-07-01

This paper studies the pulse-width pulse-frequency modulation based trajectory planning for orbital rendezvous and proximity maneuvering near a non-cooperative spacecraft in an elliptical orbit. The problem is formulated by converting the continuous control input, output from the state dependent model predictive control, into a sequence of pulses of constant magnitude by controlling firing frequency and duration of constant-magnitude thrusters. The state dependent model predictive control is derived by minimizing the control error of states and control roughness of control input for a safe, smooth and fuel efficient approaching trajectory. The resulting nonlinear programming problem is converted into a series of quadratic programming problem and solved by numerical iteration using the receding horizon strategy. The numerical results show that the proposed state dependent model predictive control with the pulse-width pulse-frequency modulation is able to effectively generate optimized trajectories using equivalent control pulses for the proximity maneuvering with less energy consumption.

Control and Optimization of Electric Ship Propulsion Systems with Hybrid Energy Storage

NASA Astrophysics Data System (ADS)

Hou, Jun

Electric ships experience large propulsion-load fluctuations on their drive shaft due to encountered waves and the rotational motion of the propeller, affecting the reliability of the shipboard power network and causing wear and tear. This dissertation explores new solutions to address these fluctuations by integrating a hybrid energy storage system (HESS) and developing energy management strategies (EMS). Advanced electric propulsion drive concepts are developed to improve energy efficiency, performance and system reliability by integrating HESS, developing advanced control solutions and system integration strategies, and creating tools (including models and testbed) for design and optimization of hybrid electric drive systems. A ship dynamics model which captures the underlying physical behavior of the electric ship propulsion system is developed to support control development and system optimization. To evaluate the effectiveness of the proposed control approaches, a state-of-the-art testbed has been constructed which includes a system controller, Li-Ion battery and ultra-capacitor (UC) modules, a high-speed flywheel, electric motors with their power electronic drives, DC/DC converters, and rectifiers. The feasibility and effectiveness of HESS are investigated and analyzed. Two different HESS configurations, namely battery/UC (B/UC) and battery/flywheel (B/FW), are studied and analyzed to provide insights into the advantages and limitations of each configuration. Battery usage, loss analysis, and sensitivity to battery aging are also analyzed for each configuration. In order to enable real-time application and achieve desired performance, a model predictive control (MPC) approach is developed, where a state of charge (SOC) reference of flywheel for B/FW or UC for B/UC is used to address the limitations imposed by short predictive horizons, because the benefits of flywheel and UC working around high-efficiency range are ignored by short predictive horizons. Given the multi-frequency characteristics of load fluctuations, a filter-based control strategy is developed to illustrate the importance of the coordination within the HESS. Without proper control strategies, the HESS solution could be worse than a single energy storage system solution. The proposed HESS, when introduced into an existing shipboard electrical propulsion system, will interact with the power generation systems. A model-based analysis is performed to evaluate the interactions of the multiple power sources when a hybrid energy storage system is introduced. The study has revealed undesirable interactions when the controls are not coordinated properly, and leads to the conclusion that a proper EMS is needed. Knowledge of the propulsion-load torque is essential for the proposed system-level EMS, but this load torque is immeasurable in most marine applications. To address this issue, a model-based approach is developed so that load torque estimation and prediction can be incorporated into the MPC. In order to evaluate the effectiveness of the proposed approach, an input observer with linear prediction is developed as an alternative approach to obtain the load estimation and prediction. Comparative studies are performed to illustrate the importance of load torque estimation and prediction, and demonstrate the effectiveness of the proposed approach in terms of improved efficiency, enhanced reliability, and reduced wear and tear. Finally, the real-time MPC algorithm has been implemented on a physical testbed. Three different efforts have been made to enable real-time implementation: a specially tailored problem formulation, an efficient optimization algorithm and a multi-core hardware implementation. Compared to the filter-based strategy, the proposed real-time MPC achieves superior performance, in terms of the enhanced system reliability, improved HESS efficiency, and extended battery life.

Planner-Based Control of Advanced Life Support Systems

NASA Technical Reports Server (NTRS)

Muscettola, Nicola; Kortenkamp, David; Fry, Chuck; Bell, Scott

2005-01-01

The paper describes an approach to the integration of qualitative and quantitative modeling techniques for advanced life support (ALS) systems. Developing reliable control strategies that scale up to fully integrated life support systems requires augmenting quantitative models and control algorithms with the abstractions provided by qualitative, symbolic models and their associated high-level control strategies. This will allow for effective management of the combinatorics due to the integration of a large number of ALS subsystems. By focusing control actions at different levels of detail and reactivity we can use faster: simpler responses at the lowest level and predictive but complex responses at the higher levels of abstraction. In particular, methods from model-based planning and scheduling can provide effective resource management over long time periods. We describe reference implementation of an advanced control system using the IDEA control architecture developed at NASA Ames Research Center. IDEA uses planning/scheduling as the sole reasoning method for predictive and reactive closed loop control. We describe preliminary experiments in planner-based control of ALS carried out on an integrated ALS simulation developed at NASA Johnson Space Center.

Predictive displays for a process-control schematic interface.

PubMed

Yin, Shanqing; Wickens, Christopher D; Helander, Martin; Laberge, Jason C

2015-02-01

Our objective was to examine the extent to which increasing precision of predictive (rate of change) information in process control will improve performance on a simulated process-control task. Predictive displays have been found to be useful in process control (as well as aviation and maritime industries). However, authors of prior research have not examined the extent to which predictive value is increased by increasing predictor resolution, nor has such research tied potential improvements to changes in process control strategy. Fifty nonprofessional participants each controlled a simulated chemical mixture process (honey mixer simulation) that simulated the operations found in process control. Participants in each of five groups controlled with either no predictor or a predictor ranging in the resolution of prediction of the process. Increasing detail resolution generally increased the benefit of prediction over the control condition although not monotonically so. The best overall performance, combining quality and predictive ability, was obtained by the display of intermediate resolution. The two displays with the lowest resolution were clearly inferior. Predictors with higher resolution are of value but may trade off enhanced sensitivity to variable change (lower-resolution discrete state predictor) with smoother control action (higher-resolution continuous predictors). The research provides guidelines to the process-control industry regarding displays that can most improve operator performance.

Impact of Disease Severity, Illness Beliefs, and Coping Strategies on Outcomes in Psoriatic Arthritis.

PubMed

Howells, Laura; Chisholm, Anna; Cotterill, Sarah; Chinoy, Hector; Warren, Richard B; Bundy, Christine

2018-02-01

Little is known about how people with psoriatic arthritis (PsA) cope with and manage their condition, but data show that psychological problems are underrecognized and undertreated. The Common Sense Self-Regulatory Model (CS-SRM) suggests illness beliefs, mediated by coping, may influence health outcomes. The study aimed to investigate the roles of disease severity, illness beliefs, and coping strategies in predicting depression, anxiety, and quality of life (QoL) in people with PsA. Additionally, we aimed to assess the role of depression and anxiety in predicting QoL. We conducted a cross-sectional observational study, where adults with PsA (n = 179) completed validated measures of predictor (illness beliefs, coping strategies, disease severity) and outcome variables (depression, anxiety, QoL) using an online survey distributed via social media. The participants were a community sample of 179 adults with PsA, ages 20 to 72 years (77.1% female). After controlling for disease severity, hierarchical multiple regression models indicated that more negative beliefs about consequences and behavioral disengagement as a coping method predicted levels of depression, and self-blame predicted anxiety. Beliefs about consequences and the presence of depression predicted quality of life scores after controlling for disease severity. This study offers support for the use of the CS-SRM in explaining variation on psychological outcomes in individuals with PsA. The illness beliefs and coping strategies identified as predictors in this article are potential targets for interventions addressing PsA-related distress and QoL. © 2017, American College of Rheumatology.

Predicting long-term growth in students' mathematics achievement: the unique contributions of motivation and cognitive strategies.

PubMed

Murayama, Kou; Pekrun, Reinhard; Lichtenfeld, Stephanie; Vom Hofe, Rudolf

2013-01-01

This research examined how motivation (perceived control, intrinsic motivation, and extrinsic motivation), cognitive learning strategies (deep and surface strategies), and intelligence jointly predict long-term growth in students' mathematics achievement over 5 years. Using longitudinal data from six annual waves (Grades 5 through 10; Mage  = 11.7 years at baseline; N = 3,530), latent growth curve modeling was employed to analyze growth in achievement. Results showed that the initial level of achievement was strongly related to intelligence, with motivation and cognitive strategies explaining additional variance. In contrast, intelligence had no relation with the growth of achievement over years, whereas motivation and learning strategies were predictors of growth. These findings highlight the importance of motivation and learning strategies in facilitating adolescents' development of mathematical competencies. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Subjective well-being in times of social change: congruence of control strategies and perceived control.

PubMed

Grümer, Sebastian; Silbereisen, Rainer K; Heckhausen, Jutta

2013-01-01

This paper investigates the association between perceptions of broader changes in the social-ecological context and individuals' subjective well-being (SWB). Macro-level societal changes such as globalization or demographic change give rise to new demands for individual functioning at work and/or in the family. Such new demands associated with social change are stressful and likely to be related to lower levels of SWB. Being active agents, individuals attempt to deal with social change and its increasing demands to protect their SWB. The present study investigates which kinds of control strategies are most effective in protecting one's SWB. Specifically, we predicted that control strategies of goal engagement will be most effective under conditions of perceived high control, and control strategies of goal disengagement will be most effective under conditions of perceived low control. In a large sample of 2537 German adults, work- and family-related demands associated with social change were found to be negatively linked to SWB. Moreover and in line with the motivational theory of lifespan development, control strategies of goal engagement and disengagement were beneficial for SWB to the extent that they matched the perceived control of the demands associated with social change.

McJobs and Pieces of Flair: Linking McDonaldization to Alienating Work

ERIC Educational Resources Information Center

Treiber, Linda Ann

2013-01-01

This article offers strategies for teaching about rationality, bureaucracy, and social change using George Ritzer's "The McDonaldization of Society" and its ideas about efficiency, predictability, calculability, and control. Student learning is facilitated using a series of strategies: making the familiar strange, explaining…

Zooming in on children's behavior during delay of gratification: Disentangling impulsigenic and volitional processes underlying self-regulation.

PubMed

Neuenschwander, Regula; Blair, Clancy

2017-02-01

When delaying gratification, both motivational and regulatory processes are likely to be at play; however, the relative contributions of motivational and regulatory influences on delay behavior are unclear. By examining behavioral responses during a delay task, this study sought to examine the motivational (anticipatory behavior) and regulatory mechanisms (executive function and self-control strategies) underlying children's self-regulation. The participants, 65 5- to 9-year-old children (M age =7.19years, SD=0.89), were video-recorded during a delay procedure and later coded for anticipatory behaviors (e.g., gazing intensely at the tablet) and self-control strategies. Children also completed two executive function (EF) tasks. We found that anticipatory behavior was curvilinearly related to delay time. Children showing either very low or very high levels of anticipatory behavior were not able to wait the entire time. Furthermore, our results indicated that anticipatory behavior interacted with EF to predict delay time. Specifically, anticipatory behavior was negatively related to delay time only if EF abilities were low. Finally, self-control strategies also interacted with EF to predict children's ability to delay. Spontaneous engagement in self-control strategies such as fidgeting and engagement in alternative activities were beneficial for children with low EF but were unrelated to delay time for children with high EF. Results indicate the value of examining motivational and regulatory influences on delay behavior. Lapses in self-regulation may be due to the combination of powerful impulsigenic (i.e., anticipatory behavior) and weak volitional processes (i.e., EF, self-control strategies). Copyright © 2016. Published by Elsevier Inc.

Towards energy efficient operation of Heating, Ventilation and Air Conditioning systems via advanced supervisory control design

NASA Astrophysics Data System (ADS)

Oswiecinska, A.; Hibbs, J.; Zajic, I.; Burnham, K. J.

2015-11-01

This paper presents conceptual control solution for reliable and energy efficient operation of heating, ventilation and air conditioning (HVAC) systems used in large volume building applications, e.g. warehouse facilities or exhibition centres. Advanced two-level scalable control solution, designed to extend capabilities of the existing low-level control strategies via remote internet connection, is presented. The high-level, supervisory controller is based on Model Predictive Control (MPC) architecture, which is the state-of-the-art for indoor climate control systems. The innovative approach benefits from using passive heating and cooling control strategies for reducing the HVAC system operational costs, while ensuring that required environmental conditions are met.

Predicting adolescent posttraumatic stress in the aftermath of war: differential effects of coping strategies across trauma reminder, loss reminder, and family conflict domains.

PubMed

Howell, Kathryn H; Kaplow, Julie B; Layne, Christopher M; Benson, Molly A; Compas, Bruce E; Katalinski, Ranka; Pasalic, Hafiza; Bosankic, Nina; Pynoos, Robert

2015-01-01

The vast majority of youth who lived through the Bosnian war were exposed to multiple traumatic events, including interpersonal violence, community destruction, and the loss of a loved one. This study examined factors that predict post-war psychological adjustment, specifically posttraumatic stress, in Bosnian adolescents. Regression analyses evaluated theorized differential relations between three types of post-war stressors - exposure to trauma reminders, loss reminders, and intrafamilial conflict - specific coping strategies, and posttraumatic stress symptom dimensions. We examined 555 Bosnian adolescents, aged 15-19 years, to predict their long-term posttraumatic stress reactions in the aftermath of war. Findings indicated that post-war exposure to trauma reminders, loss reminders, and family conflict, as well as engagement and disengagement coping strategies, predicted posttraumatic stress symptoms. Secondary control engagement coping responses to all three types of post-war stressors were inversely associated with posttraumatic stress symptoms, whereas primary control engagement coping responses to family conflict were inversely associated with hyperarousal symptoms. Disengagement responses to trauma reminders and family conflict were positively associated with re-experiencing symptoms. These findings shed light on ways in which trauma reminders, loss reminders, and family conflict may intersect with coping responses to influence adolescent postwar adjustment.

COARSE PM EMISSIONS MODEL DEVELOPMENT AND INVENTORY VALIDATION

EPA Science Inventory

The proposed research will contribute to our understanding of the sources and controlling variables of coarse PM. This greater understanding, along with an increase in our ability to predict these emissions, will enable more efficient pollution control strategy development. Ad...

Optimal charge control strategies for stationary photovoltaic battery systems

NASA Astrophysics Data System (ADS)

Li, Jiahao; Danzer, Michael A.

2014-07-01

Battery systems coupled to photovoltaic (PV) modules for example fulfill one major function: they locally decouple PV generation and consumption of electrical power leading to two major effects. First, they reduce the grid load, especially at peak times and therewith reduce the necessity of a network expansion. And second, they increase the self-consumption in households and therewith help to reduce energy expenses. For the management of PV batteries charge control strategies need to be developed to reach the goals of both the distribution system operators and the local power producer. In this work optimal control strategies regarding various optimization goals are developed on the basis of the predicted household loads and PV generation profiles using the method of dynamic programming. The resulting charge curves are compared and essential differences discussed. Finally, a multi-objective optimization shows that charge control strategies can be derived that take all optimization goals into account.

Wheel slip control with torque blending using linear and nonlinear model predictive control

NASA Astrophysics Data System (ADS)

Basrah, M. Sofian; Siampis, Efstathios; Velenis, Efstathios; Cao, Dongpu; Longo, Stefano

2017-11-01

Modern hybrid electric vehicles employ electric braking to recuperate energy during deceleration. However, currently anti-lock braking system (ABS) functionality is delivered solely by friction brakes. Hence regenerative braking is typically deactivated at a low deceleration threshold in case high slip develops at the wheels and ABS activation is required. If blending of friction and electric braking can be achieved during ABS events, there would be no need to impose conservative thresholds for deactivation of regenerative braking and the recuperation capacity of the vehicle would increase significantly. In addition, electric actuators are typically significantly faster responding and would deliver better control of wheel slip than friction brakes. In this work we present a control strategy for ABS on a fully electric vehicle with each wheel independently driven by an electric machine and friction brake independently applied at each wheel. In particular we develop linear and nonlinear model predictive control strategies for optimal performance and enforcement of critical control and state constraints. The capability for real-time implementation of these controllers is assessed and their performance is validated in high fidelity simulation.

Distinct discrimination learning strategies and their relation with spatial memory and attentional control in 4- to 14-year-olds.

PubMed

Schmittmann, Verena D; van der Maas, Han L J; Raijmakers, Maartje E J

2012-04-01

Behavioral, psychophysiological, and neuropsychological studies have revealed large developmental differences in various learning paradigms where learning from positive and negative feedback is essential. The differences are possibly due to the use of distinct strategies that may be related to spatial working memory and attentional control. In this study, strategies in performing a discrimination learning task were distinguished in a cross-sectional sample of 302 children from 4 to 14 years of age. The trial-by-trial accuracy data were analyzed with mathematical learning models. The best-fitting model revealed three learning strategies: hypothesis testing, slow abrupt learning, and nonlearning. The proportion of hypothesis-testing children increased with age. Nonlearners were present only in the youngest age group. Feature preferences for the irrelevant dimension had a detrimental effect on performance in the youngest age group. The executive functions spatial working memory and attentional control significantly predicted posterior learning strategy probabilities after controlling for age. Copyright © 2011 Elsevier Inc. All rights reserved.

Engineering bacterial translation initiation - Do we have all the tools we need?

PubMed

Vigar, Justin R J; Wieden, Hans-Joachim

2017-11-01

Reliable tools that allow precise and predictable control over gene expression are critical for the success of nearly all bioengineering applications. Translation initiation is the most regulated phase during protein biosynthesis, and is therefore a promising target for exerting control over gene expression. At the translational level, the copy number of a protein can be fine-tuned by altering the interaction between the translation initiation region of an mRNA and the ribosome. These interactions can be controlled by modulating the mRNA structure using numerous approaches, including small molecule ligands, RNAs, or RNA-binding proteins. A variety of naturally occurring regulatory elements have been repurposed, facilitating advances in synthetic gene regulation strategies. The pursuit of a comprehensive understanding of mechanisms governing translation initiation provides the framework for future engineering efforts. Here we outline state-of-the-art strategies used to predictably control translation initiation in bacteria. We also discuss current limitations in the field and future goals. Due to its function as the rate-determining step, initiation is the ideal point to exert effective translation regulation. Several engineering tools are currently available to rationally design the initiation characteristics of synthetic mRNAs. However, improvements are required to increase the predictability, effectiveness, and portability of these tools. Predictable and reliable control over translation initiation will allow greater predictability when designing, constructing, and testing genetic circuits. The ability to build more complex circuits predictably will advance synthetic biology and contribute to our fundamental understanding of the underlying principles of these processes. "This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptive MPC based on MIMO ARX-Laguerre model.

PubMed

Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

2017-03-01

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The effectiveness of research-based physics learning module with predict-observe-explain strategies to improve the student’s competence

NASA Astrophysics Data System (ADS)

Usmeldi

2018-05-01

The preliminary study shows that many students are difficult to master the concept of physics. There are still many students who have not mastery learning physics. Teachers and students still use textbooks. Students rarely do experiments in the laboratory. One model of learning that can improve students’ competence is a research-based learning with Predict- Observe-Explain (POE) strategies. To implement this learning, research-based physics learning modules with POE strategy are used. The research aims to find out the effectiveness of implementation of research-based physics learning modules with POE strategy to improving the students’ competence. The research used a quasi-experimental with pretest-posttest group control design. Data were collected using observation sheets, achievement test, skill assessment sheets, questionnaire of attitude and student responses to learning implementation. The results of research showed that research-based physics learning modules with POE strategy was effective to improve the students’ competence, in the case of (1) mastery learning of physics has been achieved by majority of students, (2) improving the students competency of experimental class including high category, (3) there is a significant difference between the average score of students’ competence of experimental class and the control class, (4) the average score of the students competency of experimental class is higher than the control class, (5) the average score of the students’ responses to the learning implementation is very good category, this means that most students can implement research-based learning with POE strategies.

On the self-serving function of social anxiety: shyness as a self-handicapping strategy.

PubMed

Snyder, C R; Smith, T W; Augelli, R W; Ingram, R E

1985-04-01

We tested the hypothesis that socially anxious or shy individuals use their anxiety symptoms as a strategy to control attributions made about their performances in social-evaluative settings (i.e., self-handicapping strategies). Specifically, we predicted that trait-socially anxious or shy persons would report more symptoms of social anxiety in an evaluative setting in which anxiety or shyness could serve as an excuse for poor performance than would individuals in (a) an evaluative setting in which shyness was precluded as an excuse or (b) a nonevaluative setting. Furthermore, we predicted that this self-protective pattern of symptom reporting would not occur for individuals who were not trait-socially anxious because these persons would not commonly use such symptoms as a self-handicapping strategy. Results supported these predictions for male subjects, but not for female subjects. Sex differences in the strategic use of shyness are discussed in relation to other research on sex differences in the etiology and correlates of social anxiety.

Application of model predictive control for optimal operation of wind turbines

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Cao, Pei; Tang, J.

2017-04-01

For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.

Unique contributions of emotion regulation and executive functions in predicting the quality of parent-child interaction behaviors.

PubMed

Shaffer, Anne; Obradović, Jelena

2017-03-01

Parenting is a cognitive, emotional, and behavioral endeavor, yet limited research investigates parents' executive functions and emotion regulation as predictors of how parents interact with their children. The current study is a multimethod investigation of parental self-regulation in relation to the quality of parenting behavior and parent-child interactions in a diverse sample of parents and kindergarten-age children. Using path analyses, we tested how parent executive functions (inhibitory control) and lack of emotion regulation strategies uniquely relate to both sensitive/responsive behaviors and positive/collaborative behaviors during observed interaction tasks. In our analyses, we accounted for parent education, financial stress, and social support as socioeconomic factors that likely relate to parent executive function and emotion regulation skills. In a diverse sample of primary caregivers (N = 102), we found that direct assessment of parent inhibitory control was positively associated with sensitive/responsive behaviors, whereas parent self-reported difficulties in using emotion regulation strategies were associated with lower levels of positive and collaborative dyadic behaviors. Parent education and financial stress predicted inhibitory control, and social support predicted emotion regulation difficulties; parent education was also a significant predictor of sensitive/responsive behaviors. Greater inhibitory control skills and fewer difficulties identifying effective emotion regulation strategies were not significantly related in our final path model. We discuss our findings in the context of current and emerging parenting interventions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Variable Demographic Rates in an Invasive Plant Species: Differences Among Populations and Management Implications

USDA-ARS?s Scientific Manuscript database

Population managers are frequently faced with the challenge of selecting the most effective management strategy from a set of available strategies. In the case of classical weed biological control, this requires predicting a priori which of a group of candidate biocontrol agent species has the great...

Cognitive Learning Strategy as a Partial Effect on Major Field Test in Business Results

ERIC Educational Resources Information Center

Strang, Kenneth David

2014-01-01

An experiment was developed to determine if cognitive learning strategies improved standardized university business exam results. Previous studies revealed that factors such as prior ability, age, gender, and culture predicted a student's Major Field Test in Business (MFTB) score better than course content. The experiment control consisted of…

Controlling Viscous Fingering Using Time-Dependent Strategies

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

Stone, Howard; Zheng, Zhong; Kim, Hyoungsoo

Control and stabilization of viscous fingering of immiscible fluids impacts a wide variety of pressure-driven multiphase flows. Here, we report theoretical and experimental results on time-dependent control strategy by manipulating the gap thickness b(t) in a lifting Hele-Shaw cell in the power-law form b(t) = b 1t 1/7. Experimental results show good quantitative agreement with the predictions of linear stability analysis. Furthermore, by choosing the value of a single time-independent control parameter we can either totally suppress the viscous fingering instability or maintain a series of non-splitting viscous fingers during the fluid displacement process. Besides the gap thickness of amore » Hele-Shaw cell, in principle, time-dependent control strategies can also be placed on the injection rate, viscosity of the displaced fluid, and interfacial tensions between the two fluids.« less

Controlling Viscous Fingering Using Time-Dependent Strategies

DOE PAGES

Stone, Howard; Zheng, Zhong; Kim, Hyoungsoo

2015-10-20

Control and stabilization of viscous fingering of immiscible fluids impacts a wide variety of pressure-driven multiphase flows. Here, we report theoretical and experimental results on time-dependent control strategy by manipulating the gap thickness b(t) in a lifting Hele-Shaw cell in the power-law form b(t) = b 1t 1/7. Experimental results show good quantitative agreement with the predictions of linear stability analysis. Furthermore, by choosing the value of a single time-independent control parameter we can either totally suppress the viscous fingering instability or maintain a series of non-splitting viscous fingers during the fluid displacement process. Besides the gap thickness of amore » Hele-Shaw cell, in principle, time-dependent control strategies can also be placed on the injection rate, viscosity of the displaced fluid, and interfacial tensions between the two fluids.« less

Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

PubMed Central

Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

2015-01-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 hours to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. PMID:21546146

Regional differences in brain volume predict the acquisition of skill in a complex real-time strategy videogame.

PubMed

Basak, Chandramallika; Voss, Michelle W; Erickson, Kirk I; Boot, Walter R; Kramer, Arthur F

2011-08-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also be useful in predicting the acquisition of skill in complex tasks, such as strategy-based video games. Twenty older adults were trained for over 20 h to play Rise of Nations, a complex real-time strategy game. These adults showed substantial improvements over the training period in game performance. MRI scans obtained prior to training revealed that the volume of a number of brain regions, which have been previously associated with subsets of the trained skills, predicted a substantial amount of variance in learning on the complex game. Thus, regional differences in brain volume can predict learning in complex tasks that entail the use of a variety of perceptual, cognitive and motor processes. Copyright © 2011 Elsevier Inc. All rights reserved.

Assessing assessment: Can the expected effects of the St. Marys River sea lamprey control strategy be detected?

USGS Publications Warehouse

Adams, Jean V.; Bergstedt, Roger A.; Christie, Gavin C.; Cuddy, Douglas W.; Fodale, Michael F.; Heinrich, John W.; Jones, Michael L.; McDonald, Rodney B.; Mullett, Katherine M.; Young, Robert J.

2003-01-01

In 1997 the Great Lakes Fishery Commission approved a 5-year (1998 to 2002) control strategy to reduce sea lamprey (Petromyzon marinus) production in the St. Marys River, the primary source of parasitic sea lampreys in northern Lake Huron. An assessment plan was developed to measure the success of the control strategy and decide on subsequent control efforts. The expected effects of the St. Marys River control strategy are described, the assessments in place to measure these effects are outlined, and the ability of these assessments to detect the expected effects are quantified. Several expected changes were predicted to be detectable: abundance of parasitic-phase sea lampreys and annual mortality of lake trout (Salvelinus namaycush) by 2001, abundance of spawning-phase sea lampreys by 2002, and relative return rates of lake trout and sea lamprey wounding rates on lake trout by 2005. Designing an effective assessment program to quantify the consequences of fishery management actions is a critical, but often overlooked ingredient of sound fisheries management.

The relationship between high residential density in student dormitories and anxiety, binge eating and Internet addiction: a study of Chinese college students.

PubMed

Tao, Zhuoli; Wu, Gao; Wang, Zeyuan

2016-01-01

Although various studies have indicated that high residential density may affect health and psychological outcomes, to our knowledge, there have been no studies regarding the predictive nature of crowded living conditions on binge eating and the use of the Internet as coping strategies. A total of 1048 Chinese college students (540 males and 508 females) were randomly selected and asked to complete a battery of questionnaires that included the Zung's Self-Rating Anxiety Scale, the Internet Addiction Test, and Rosenbaum's Self-Control Scale. Binge eating behaviors and compensatory behaviors were also reported, and variables about residential density were measured. Among female participants, binge eating scores were significantly predicted by anxiety caused by high-density living conditions (P = 0.008), and similarly, the frequency of compensatory behaviors was significantly predicted by anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.003). Furthermore, the Internet Addiction Test scores were significantly predicted by the anxiety caused by high -density living conditions (P = 0.000) and self-control (P = 0.000). Among male participants, not only were the binge eating scores significantly predicted by the anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.000), but the frequency of compensatory behaviors was also significantly predicted by the anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.01). Furthermore, Internet Addiction Test scores were significantly predicted by anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.000). It was further found that for both genders, subjective factors such as self-control, and the anxiety caused by high-density living conditions had a stronger impact on Internet addiction than objective factors, such as the size of the student's dormitory room. Moreover, self-control was found to act as a moderator in the relationship between anxiety and Internet addiction among male participants. Binge eating and Internet use could be considered coping strategies for Chinese college students facing high residential density in their dormitories.

How Home Gets to School: Parental Control Strategies Predict Children's School Readiness

ERIC Educational Resources Information Center

Walker, Aimee Kleisner; MacPhee, David

2011-01-01

At-risk families' control style (autonomy support and coercive control) was examined in relation to children's school readiness; children's social skills and mastery motivation were hypothesized mediating variables. In two different, low-income samples from diverse ethnic backgrounds, one preschool sample recruited from Head Start (N = 199) and a…

A new model predictive control algorithm by reducing the computing time of cost function minimization for NPC inverter in three-phase power grids.

PubMed

Taheri, Asghar; Zhalebaghi, Mohammad Hadi

2017-11-01

This paper presents a new control strategy based on finite-control-set model-predictive control (FCS-MPC) for Neutral-point-clamped (NPC) three-level converters. Containing some advantages like fast dynamic response, easy inclusion of constraints and simple control loop, makes the FCS-MPC method attractive to use as a switching strategy for converters. However, the large amount of required calculations is a problem in the widespread of this method. In this way, to resolve this problem this paper presents a modified method that effectively reduces the computation load compare with conventional FCS-MPC method and at the same time does not affect on control performance. The proposed method can be used for exchanging power between electrical grid and DC resources by providing active and reactive power compensations. Experiments on three-level converter for three Power Factor Correction (PFC), inductive and capacitive compensation modes verify the good and comparable performance. The results have been simulated using MATLAB/SIMULINK software. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Predictability and Robustness in the Manipulation of Dynamically Complex Objects

PubMed Central

Hasson, Christopher J.

2017-01-01

Manipulation of complex objects and tools is a hallmark of many activities of daily living, but how the human neuromotor control system interacts with such objects is not well understood. Even the seemingly simple task of transporting a cup of coffee without spilling creates complex interaction forces that humans need to compensate for. Predicting the behavior of an underactuated object with nonlinear fluid dynamics based on an internal model appears daunting. Hence, this research tests the hypothesis that humans learn strategies that make interactions predictable and robust to inaccuracies in neural representations of object dynamics. The task of moving a cup of coffee is modeled with a cart-and-pendulum system that is rendered in a virtual environment, where subjects interact with a virtual cup with a rolling ball inside using a robotic manipulandum. To gain insight into human control strategies, we operationalize predictability and robustness to permit quantitative theory-based assessment. Predictability is quantified by the mutual information between the applied force and the object dynamics; robustness is quantified by the energy margin away from failure. Three studies are reviewed that show how with practice subjects develop movement strategies that are predictable and robust. Alternative criteria, common for free movement, such as maximization of smoothness and minimization of force, do not account for the observed data. As manual dexterity is compromised in many individuals with neurological disorders, the experimental paradigm and its analyses are a promising platform to gain insights into neurological diseases, such as dystonia and multiple sclerosis, as well as healthy aging. PMID:28035560

A Stitch in Time: Strategic Self-Control in High School and College Students.

PubMed

Duckworth, Angela L; White, Rachel E; Matteucci, Alyssa J; Shearer, Annie; Gross, James J

2016-04-01

A growing body of research indicates that self-control is critical to academic success. Surprisingly little is known, however, about the diverse strategies students use to implement self-control or how well these strategies work. To address these issues, we conducted a naturalistic investigation of self-control strategies (Study 1) and two field experiments (Studies 2 and 3). In Study 1, high school students described the strategies they use to manage interpersonal conflicts, get academic work done, eat healthfully, and manage other everyday self-control challenges. The majority of strategies in these self-nominated incidents as well as in three hypothetical academic scenarios (e.g., studying instead of texting friends) were reliably classified using the process model of self-control. As predicted by the process model, students rated strategies deployed early in the impulse-generation process (situation selection, situation modification) as being dramatically more effective than strategies deployed later (attentional deployment, cognitive change, response modulation). In Study 2, high school students randomly assigned to implement situation modification were more likely to meet their academic goals during the following week than students assigned either to implement response modulation or no strategy at all. In Study 3, college students randomly assigned to implement situation modification were also more successful in meeting their academic goals, and this effect was partially mediated by decreased feelings of temptation throughout the week. Collectively, these findings suggest that students might benefit from learning to initiate self-control when their impulses are still nascent.

A Stitch in Time: Strategic Self-Control in High School and College Students

PubMed Central

Duckworth, Angela L.; White, Rachel E.; Matteucci, Alyssa J.; Shearer, Annie; Gross, James J.

2015-01-01

A growing body of research indicates that self-control is critical to academic success. Surprisingly little is known, however, about the diverse strategies students use to implement self-control or how well these strategies work. To address these issues, we conducted a naturalistic investigation of self-control strategies (Study 1) and two field experiments (Studies 2 and 3). In Study 1, high school students described the strategies they use to manage interpersonal conflicts, get academic work done, eat healthfully, and manage other everyday self-control challenges. The majority of strategies in these self-nominated incidents as well as in three hypothetical academic scenarios (e.g., studying instead of texting friends) were reliably classified using the process model of self-control. As predicted by the process model, students rated strategies deployed early in the impulse-generation process (situation selection, situation modification) as being dramatically more effective than strategies deployed later (attentional deployment, cognitive change, response modulation). In Study 2, high school students randomly assigned to implement situation modification were more likely to meet their academic goals during the following week than students assigned either to implement response modulation or no strategy at all. In Study 3, college students randomly assigned to implement situation modification were also more successful in meeting their academic goals, and this effect was partially mediated by decreased feelings of temptation throughout the week. Collectively, these findings suggest that students might benefit from learning to initiate self-control when their impulses are still nascent. PMID:27158155

Validity of the MicroDYN Approach: Complex Problem Solving Predicts School Grades beyond Working Memory Capacity

ERIC Educational Resources Information Center

Schweizer, Fabian; Wustenberg, Sascha; Greiff, Samuel

2013-01-01

This study examines the validity of the complex problem solving (CPS) test MicroDYN by investigating a) the relation between its dimensions--rule identification (exploration strategy), rule knowledge (acquired knowledge), rule application (control performance)--and working memory capacity (WMC), and b) whether CPS predicts school grades in…

Tenacious self-reliance in health maintenance may jeopardize late life survival.

PubMed

Hamm, Jeremy M; Chipperfield, Judith G; Perry, Raymond P; Parker, Patti C; Heckhausen, Jutta

2017-11-01

Although an active pursuit of health goals is typically adaptive, there may be circumstances in very late life when it is not. Our 10-year study of community-dwelling individuals (n = 220, 79-98 years-old) examined whether investing substantial effort into personal health (high selective primary control) in the absence of help-seeking strategies (low compensatory primary control) jeopardized survival for very old adults who varied in functional independence (low, high). Cox proportional hazard models showed selective primary control (SPC) predicted 10-year mortality risk for only those with low compensatory primary control (CPC) and high initial functional independence. For these individuals, each standard deviation increase in SPC predicted a 101% higher risk of death. Results are consistent with the lines-of-defense model (Heckhausen et al., 2013) and suggest that, for very old adults with little previous need for help-seeking strategies, tenacious self-reliance (high SPC, low CPC) may have life-shortening consequences. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Real-Time Charging Strategies for an Electric Vehicle Aggregator to Provide Ancillary Services

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

Wenzel, George; Negrete-Pincetic, Matias; Olivares, Daniel E.

Real-time charging strategies, in the context of vehicle to grid (V2G) technology, are needed to enable the use of electric vehicle (EV) fleets batteries to provide ancillary services (AS). Here, we develop tools to manage charging and discharging in a fleet to track an Automatic Generation Control (AGC) signal when aggregated. We also propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing Model Predictive Control (MPC). Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.

Real-Time Charging Strategies for an Electric Vehicle Aggregator to Provide Ancillary Services

DOE PAGES

Wenzel, George; Negrete-Pincetic, Matias; Olivares, Daniel E.; ...

2017-03-13

Real-time charging strategies, in the context of vehicle to grid (V2G) technology, are needed to enable the use of electric vehicle (EV) fleets batteries to provide ancillary services (AS). Here, we develop tools to manage charging and discharging in a fleet to track an Automatic Generation Control (AGC) signal when aggregated. We also propose a real-time controller that considers bidirectional charging efficiency and extend it to study the effect of looking ahead when implementing Model Predictive Control (MPC). Simulations show that the controller improves tracking error as compared with benchmark scheduling algorithms, as well as regulation capacity and battery cycling.

The physicochemical process of bacterial attachment to abiotic surfaces: Challenges for mechanistic studies, predictability and the development of control strategies.

PubMed

Wang, Yi; Lee, Sui Mae; Dykes, Gary

2015-01-01

Bacterial attachment to abiotic surfaces can be explained as a physicochemical process. Mechanisms of the process have been widely studied but are not yet well understood due to their complexity. Physicochemical processes can be influenced by various interactions and factors in attachment systems, including, but not limited to, hydrophobic interactions, electrostatic interactions and substratum surface roughness. Mechanistic models and control strategies for bacterial attachment to abiotic surfaces have been established based on the current understanding of the attachment process and the interactions involved. Due to a lack of process control and standardization in the methodologies used to study the mechanisms of bacterial attachment, however, various challenges are apparent in the development of models and control strategies. In this review, the physicochemical mechanisms, interactions and factors affecting the process of bacterial attachment to abiotic surfaces are described. Mechanistic models established based on these parameters are discussed in terms of their limitations. Currently employed methods to study these parameters and bacterial attachment are critically compared. The roles of these parameters in the development of control strategies for bacterial attachment are reviewed, and the challenges that arise in developing mechanistic models and control strategies are assessed.

Strategies for Controlling Non-Transmissible Infection Outbreaks Using a Large Human Movement Data Set

PubMed Central

Hancock, Penelope A.; Rehman, Yasmin; Hall, Ian M.; Edeghere, Obaghe; Danon, Leon; House, Thomas A.; Keeling, Matthew J.

2014-01-01

Prediction and control of the spread of infectious disease in human populations benefits greatly from our growing capacity to quantify human movement behavior. Here we develop a mathematical model for non-transmissible infections contracted from a localized environmental source, informed by a detailed description of movement patterns of the population of Great Britain. The model is applied to outbreaks of Legionnaires' disease, a potentially life-threatening form of pneumonia caused by the bacteria Legionella pneumophilia. We use case-report data from three recent outbreaks that have occurred in Great Britain where the source has already been identified by public health agencies. We first demonstrate that the amount of individual-level heterogeneity incorporated in the movement data greatly influences our ability to predict the source location. The most accurate predictions were obtained using reported travel histories to describe movements of infected individuals, but using detailed simulation models to estimate movement patterns offers an effective fast alternative. Secondly, once the source is identified, we show that our model can be used to accurately determine the population likely to have been exposed to the pathogen, and hence predict the residential locations of infected individuals. The results give rise to an effective control strategy that can be implemented rapidly in response to an outbreak. PMID:25211122

A review of 'green' strategies to prevent or mitigate microbiologically influenced corrosion.

PubMed

Little, Brenda; Lee, Jason; Ray, Richard

2007-01-01

Two approaches to control microbiologically influenced corrosion (MIC) have been developed that do not require the use of biocides. These strategies include the following: i) use of biofilms to inhibit or prevent corrosion, and ii) manipulation (removal or addition) of an electron acceptor, (e.g. oxygen, sulphate or nitrate) to influence the microbial population. In both approaches the composition of the microbial community is affected by small perturbations in the environment (e.g. temperature, nutrient concentration and flow) and the response of microorganisms cannot be predicted with certainty. The following sections will review the literature on the effectiveness of these environmentally friendly, "green," strategies for controlling MIC.

Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

USGS Publications Warehouse

Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

1997-01-01

One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

An intelligent system with EMG-based joint angle estimation for telemanipulation.

PubMed

Suryanarayanan, S; Reddy, N P; Gupta, V

1996-01-01

Bio-control of telemanipulators is being researched as an alternate control strategy. This study investigates the use of surface EMG from the biceps to predict joint angle during flexion of the arm that can be used to control an anthropomorphic telemanipulator. An intelligent system based on neural networks and fuzzy logic has been developed to use the processed surface EMG signal and predict the joint angle. The system has been tested on various angles of flexion-extension of the arm and at several speeds of flexion-extension. Preliminary results show the RMS error between the predicted angle and the actual angle to be less than 3% during training and less than 15% during testing. The technique of direct bio-control using EMG has the potential as an interface for telemanipulation applications.

Life satisfaction and its correlates in older women with osteoarthritis.

PubMed

Tak, Sunghee H; Laffrey, Shirley C

2003-01-01

To identify the relationships among functional disability, chronic daily stress, coping strategies, beliefs about personal control, social support, and life satisfaction in older women with osteoarthritis. A descriptive, correlational design was used. The study participants were 107 women aged 60 years or older. Study participants completed six survey questionnaires and a demographic form. Bivariate correlational analyses showed that older women with poorer functional ability experienced greater chronic daily stress, reported more frequent use of emotion-focused coping strategies, and had a higher chance health locus of control. A hierarchic regression analysis revealed that the perceived social support and internal health locus of control significantly contributed to the prediction of life satisfaction after demographic, illness-related, and stress-related variables were controlled. Stress management strategies matched to the participants' style of coping process can increase their sense of control over their health and enhance their social networks and activities.

Analysis and Control of Pulse-Width Modulated AC to DC Voltage Source Converters.

NASA Astrophysics Data System (ADS)

Wu, Rusong

The pulse width modulated AC to DC voltage source converter is comprehensively analyzed in the thesis. A general mathematical model of the converter is first established, which is discontinuous, time-variant and non-linear. The following three techniques are used to obtain closed form solutions: Fourier analysis, transformation of reference frame and small signal linearization. Three models, namely, a steady-state DC model, a low frequency small signal AC model and a high frequency model, are consequently developed. Finally, three solution sets, namely, the steady-state solution, various dynamic transfer functions and the high frequency harmonic components, are obtained from the three models. Two control strategies, the Phase and Amplitude Control (PAC) and a new proposed strategy, Predicted Current Control with a Fixed Switching Frequency (PCFF), are investigated. Based on the transfer functions derived from the above mentioned analysis, regulators for a closed-loop control are designed. A prototype circuit is built to experimentally verify the theoretical predictions. The analysis and experimental results show that both strategies produce nearly sinusoidal line current with unity power factor on the utility side in both rectifying and regenerating operations and concurrently provide a regulated DC output voltage on the load side. However the proposed PCFF control has a faster and improved dynamic response over the PAC control. Moreover it is also easier to be implemented. Therefore, the PCFF control is preferable to the PAC control. As an example of application, a configuration of variable DC supply under PCFF control is proposed. The quasi-optimal dynamic response obtained shows that the PWM AC to DC converter lays the foundation for building a four-quadrant, fast-dynamic system, and the PCFF control is an effective strategy for improving dynamic performances not only as applied to the AC to DC converter, but also as applied to the DC to DC chopper or other circuits.

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.

Gambling with Rose-Tinted Glasses on: Use of Emotion-Regulation Strategies Correlates with Dysfunctional Cognitions in Gambling Disorder Patients

PubMed Central

Navas, Juan F.; Verdejo-García, Antonio; LÓpez-GÓmez, Marta; Maldonado, Antonio; Perales, José C.

2016-01-01

Background and aims Existing research shows that gambling disorder patients (GDPs) process gambling outcomes abnormally when compared against healthy controls (HCs). These anomalies present the form of exaggerated or distorted beliefs regarding the expected utility of outcomes and one’s ability to predict or control gains and losses, as well as retrospective reinterpretations of what caused them. This study explores the possibility that the emotional regulation strategies GDPs use to cope with aversive events are linked to these cognitions. Methods 41 GDPs and 45 HCs, matched in sociodemographic variables, were assessed in gambling severity, emotion-regulation strategies (cognitive emotion-regulation questionnaire, CERQ), and gambling-related cognitions (gambling-related cognitions scale, GRCS). Results GDPs showed higher scores in all gambling-related cognition dimensions. Regarding emotion regulation, GDPs were observed to use self-blame and catastrophizing, but also positive refocusing, more often than controls. Additionally, in GDPs, putatively adaptive CERQ strategies shared a significant portion of variance with South Oaks gambling screen severity and GRCS beliefs. Shared variability was mostly attributable to the roles of refocusing on planning and putting into perspective at positively predicting severity and the interpretative bias (GDPs propensity to reframe losses in a more benign way), respectively. Discussion and conclusions Results show links between emotion-regulation strategies and problematic gambling-related behaviors and cognitions. The pattern of those links supports the idea that GDPs use emotion-regulation strategies, customarily regarded as adaptive, to cope with negative emotions, so that the motivational and cognitive processing of gambling outcomes becomes less effective in shaping gambling-related behavior. PMID:27363462

Cell Fate Reprogramming by Control of Intracellular Network Dynamics

PubMed Central

Zañudo, Jorge G. T.; Albert, Réka

2015-01-01

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell’s fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our method’s potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. PMID:25849586

Prediction-based sampled-data H∞ controller design for attitude stabilisation of a rigid spacecraft with disturbances

NASA Astrophysics Data System (ADS)

Zhu, Baolong; Zhang, Zhiping; Zhou, Ding; Ma, Jie; Li, Shunli

2017-08-01

This paper investigates the H∞ control problem of the attitude stabilisation of a rigid spacecraft with external disturbances using prediction-based sampled-data control strategy. Aiming to achieve a 'virtual' closed-loop system, a type of parameterised sampled-data controller is designed by introducing a prediction mechanism. The resultant closed-loop system is equivalent to a hybrid system featured by a continuous-time and an impulsive differential system. By using a time-varying Lyapunov functional, a generalised bounded real lemma (GBRL) is first established for a kind of impulsive differential system. Based on this GBRL and Lyapunov functional approach, a sufficient condition is derived to guarantee the closed-loop system to be asymptotically stable and to achieve a prescribed H∞ performance. In addition, the controller parameter tuning is cast into a convex optimisation problem. Simulation and comparative results are provided to illustrate the effectiveness of the developed control scheme.

Estimation of Danger and Endorsement of Self-Protection Strategies: A Study of Locus of Control.

ERIC Educational Resources Information Center

Heath, Linda; And Others

Contradictory predictions concerning control over negative events exist in Walster's self-protective attribution theory which maintains that on-lookers in negative situations are apt to seek control by convincing themselves that such a situation couldn't happen to them, while Shaver's defensive attribution theory suggests that in a comparable…

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.

Thought control strategies in adolescents: links with OCD symptoms and meta-cognitive beliefs.

PubMed

Wilson, Charlotte; Hall, Martin

2012-07-01

The perceived control of intrusive thoughts is important in our understanding of a variety of psychological disorders, but particularly in Obsessive Compulsive Disorder (OCD). Little research has explored thought control strategies in younger populations, despite the frequent onset of OCD in childhood. This study examined thought control strategies and meta-cognitive beliefs in relation to Obsessive Compulsive (OC) interference scores in an adolescent sample. A non-referred sample of 151 adolescents aged 13-16 completed the Thought Control Questionnaire, the Meta-Cognitions Questionnaire - Adolescent version, and the Leyton Obsessional Inventory - Child Version. Adolescents reported using distraction and worry as thought control strategies as much as adults, but social control and reappraisal less frequently, with adolescent males also reporting less use of punishment as a strategy. The strategies of worry and punishment, and positive beliefs about worry, uncontrollability and danger beliefs (UCD) and superstition punishment and responsibility beliefs (SPR) predicted OC interference scores. Furthermore, these meta-cognitive beliefs mediated the relationships between punishment and worry and OC interference scores. Given the similarities between our results and those from research exploring these variables in adults, it is proposed that cognitive behavioural models of OCD that have been developed in adult populations may be relevant to adolescents, but that meta-cognitive beliefs about superstition, punishment and responsibility may be important in adolescence.

Development of a Low-Lift Chiller Controller and Simplified Precooling Control Algorithm - Final Report

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

Gayeski, N.; Armstrong, Peter; Alvira, M.

2011-11-30

KGS Buildings LLC (KGS) and Pacific Northwest National Laboratory (PNNL) have developed a simplified control algorithm and prototype low-lift chiller controller suitable for model-predictive control in a demonstration project of low-lift cooling. Low-lift cooling is a highly efficient cooling strategy conceived to enable low or net-zero energy buildings. A low-lift cooling system consists of a high efficiency low-lift chiller, radiant cooling, thermal storage, and model-predictive control to pre-cool thermal storage overnight on an optimal cooling rate trajectory. We call the properly integrated and controlled combination of these elements a low-lift cooling system (LLCS). This document is the final report formore » that project.« less

Striatal dysfunction during reversal learning in unmedicated schizophrenia patients☆

PubMed Central

Schlagenhauf, Florian; Huys, Quentin J.M.; Deserno, Lorenz; Rapp, Michael A.; Beck, Anne; Heinze, Hans-Joachim; Dolan, Ray; Heinz, Andreas

2014-01-01

Subjects with schizophrenia are impaired at reinforcement-driven reversal learning from as early as their first episode. The neurobiological basis of this deficit is unknown. We obtained behavioral and fMRI data in 24 unmedicated, primarily first episode, schizophrenia patients and 24 age-, IQ- and gender-matched healthy controls during a reversal learning task. We supplemented our fMRI analysis, focusing on learning from prediction errors, with detailed computational modeling to probe task solving strategy including an ability to deploy an internal goal directed model of the task. Patients displayed reduced functional activation in the ventral striatum (VS) elicited by prediction errors. However, modeling task performance revealed that a subgroup did not adjust their behavior according to an accurate internal model of the task structure, and these were also the more severely psychotic patients. In patients who could adapt their behavior, as well as in controls, task solving was best described by cognitive strategies according to a Hidden Markov Model. When we compared patients and controls who acted according to this strategy, patients still displayed a significant reduction in VS activation elicited by informative errors that precede salient changes of behavior (reversals). Thus, our study shows that VS dysfunction in schizophrenia patients during reward-related reversal learning remains a core deficit even when controlling for task solving strategies. This result highlights VS dysfunction is tightly linked to a reward-related reversal learning deficit in early, unmedicated schizophrenia patients. PMID:24291614

Illness perception, coping and adherence to treatment among patients with chronic kidney disease.

PubMed

Vélez-Vélez, Esperanza; Bosch, Ricardo J

2016-04-01

To analyse the predictive value of illness representations on treatment adherence and coping strategies in a group of patients on haemodialysis. Understanding the cognitive and emotional factors that influence adherence behaviour and coping strategies and determining their relationship to sociodemographic factors remain a challenge; meeting this challenge would encourage comprehensive patient care, thereby improving their quality of life Cross-sectional study with predictive means in a sample of 135 patients on haemodialysis. Data collection occurred from September 2010-January 2012 and tools included the following: sociodemographic data, Illness Perception Questionnaire-Revised, the Cuestionario de Afrontamiento del Estrés and the Morisky-Green test to study adherence to treatment. Being a woman, having a greater knowledge of the disease and having a poorer sense of personal control affected adherence to treatment on controlling for each factor. 'Identity', 'personal control' and 'adherence' were associated with a proactive coping strategy, whereas 'evolution' and 'gender' were related independently to avoidance coping strategies; those who believed that their illness had a chronic course were more likely to cope by avoiding the problem and this tendency was stronger among women. This study provides evidence supporting the role of gender, knowledge about the disease and sense of personal control in adherence to therapeutic regimens of patients in chronic haemodialysis. The identification and characterization of patients' perception of chronic illness may represent a useful framework to influence disease outcomes such as adherence. © 2015 John Wiley & Sons Ltd.

A Simple Microsoft Excel Method to Predict Antibiotic Outbreaks and Underutilization.

PubMed

Miglis, Cristina; Rhodes, Nathaniel J; Avedissian, Sean N; Zembower, Teresa R; Postelnick, Michael; Wunderink, Richard G; Sutton, Sarah H; Scheetz, Marc H

2017-07-01

Benchmarking strategies are needed to promote the appropriate use of antibiotics. We have adapted a simple regressive method in Microsoft Excel that is easily implementable and creates predictive indices. This method trends consumption over time and can identify periods of over- and underuse at the hospital level. Infect Control Hosp Epidemiol 2017;38:860-862.

Single session real-time fMRI neurofeedback has a lasting impact on cognitive behavioral therapy strategies.

PubMed

MacDuffie, Katherine E; MacInnes, Jeff; Dickerson, Kathryn C; Eddington, Kari M; Strauman, Timothy J; Adcock, R Alison

2018-01-01

To benefit from cognitive behavioral therapy (CBT), individuals must not only learn new skills but also strategically implement them outside of session. Here, we tested a novel technique for personalizing CBT skills and facilitating their generalization to daily life. We hypothesized that showing participants the impact of specific CBT strategies on their own brain function using real-time functional magnetic imaging (rt-fMRI) neurofeedback would increase their metacognitive awareness, help them identify effective strategies, and motivate real-world use. In a within-subjects design, participants who had completed a clinical trial of a standardized course of CBT created a personal repertoire of negative autobiographical stimuli and mood regulation strategies. From each participant's repertoire, a set of experimental and control strategies were identified; only experimental strategies were practiced in the scanner. During the rt-fMRI neurofeedback session, participants used negative stimuli and strategies from their repertoire to manipulate activation in the anterior cingulate cortex, a region implicated in emotional distress. The primary outcome measures were changes in participant ratings of strategy difficulty, efficacy, and frequency of use. As predicted, ratings for unscanned control strategies were stable across observations, whereas ratings for experimental strategies changed after neurofeedback. At follow-up one month after the session, efficacy and frequency ratings for scanned strategies were predicted by neurofeedback during the rt-fMRI session. These results suggest that rt-fMRI neurofeedback created a salient and durable learning experience for patients, extending beyond the scan session to guide and motivate CBT skill use weeks later. This metacognitive approach to neurofeedback offers a promising model for increasing clinical benefits from cognitive behavioral therapy by personalizing skills and facilitating generalization.

Evaluation of control strategies using an oxidation ditch benchmark.

PubMed

Abusam, A; Keesman, K J; Spanjers, H; van, Straten G; Meinema, K

2002-01-01

This paper presents validation and implementation results of a benchmark developed for a specific full-scale oxidation ditch wastewater treatment plant. A benchmark is a standard simulation procedure that can be used as a tool in evaluating various control strategies proposed for wastewater treatment plants. It is based on model and performance criteria development. Testing of this benchmark, by comparing benchmark predictions to real measurements of the electrical energy consumptions and amounts of disposed sludge for a specific oxidation ditch WWTP, has shown that it can (reasonably) be used for evaluating the performance of this WWTP. Subsequently, the validated benchmark was then used in evaluating some basic and advanced control strategies. Some of the interesting results obtained are the following: (i) influent flow splitting ratio, between the first and the fourth aerated compartments of the ditch, has no significant effect on the TN concentrations in the effluent, and (ii) for evaluation of long-term control strategies, future benchmarks need to be able to assess settlers' performance.

Strategies for memory-based decision making: Modeling behavioral and neural signatures within a cognitive architecture.

PubMed

Fechner, Hanna B; Pachur, Thorsten; Schooler, Lael J; Mehlhorn, Katja; Battal, Ceren; Volz, Kirsten G; Borst, Jelmer P

2016-12-01

How do people use memories to make inferences about real-world objects? We tested three strategies based on predicted patterns of response times and blood-oxygen-level-dependent (BOLD) responses: one strategy that relies solely on recognition memory, a second that retrieves additional knowledge, and a third, lexicographic (i.e., sequential) strategy, that considers knowledge conditionally on the evidence obtained from recognition memory. We implemented the strategies as computational models within the Adaptive Control of Thought-Rational (ACT-R) cognitive architecture, which allowed us to derive behavioral and neural predictions that we then compared to the results of a functional magnetic resonance imaging (fMRI) study in which participants inferred which of two cities is larger. Overall, versions of the lexicographic strategy, according to which knowledge about many but not all alternatives is searched, provided the best account of the joint patterns of response times and BOLD responses. These results provide insights into the interplay between recognition and additional knowledge in memory, hinting at an adaptive use of these two sources of information in decision making. The results highlight the usefulness of implementing models of decision making within a cognitive architecture to derive predictions on the behavioral and neural level. Copyright © 2016 Elsevier B.V. All rights reserved.

Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer.

PubMed

Ouari, Kamel; Rekioua, Toufik; Ouhrouche, Mohand

2014-01-01

In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

PubMed Central

Ferrand, Claude; Audiffren, Michel

2018-01-01

Background Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. Results A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging. PMID:29850247

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis.

PubMed

André, Nathalie; Ferrand, Claude; Albinet, Cédric; Audiffren, Michel

2018-01-01

Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging.

Stoichiometric Network Analysis of Cyanobacterial Acclimation to Photosynthesis-Associated Stresses Identifies Heterotrophic Niches

DOE PAGES

Beck, Ashley; Bernstein, Hans; Carlson, Ross

2017-06-19

Metabolic acclimation to photosynthesis-associated stresses was examined in the thermophilic cyanobacterium Thermosynechococcus elongatus BP-1 using integrated computational and photobioreactor analyses. A genome-enabled metabolic model, complete with measured biomass composition, was analyzed using ecological resource allocation theory to predict and interpret metabolic acclimation to irradiance, O 2, and nutrient stresses. Reduced growth efficiency, shifts in photosystem utilization, changes in photorespiration strategies, and differing byproduct secretion patterns were predicted to occur along culturing stress gradients. These predictions were compared with photobioreactor physiological data and previously published transcriptomic data and found to be highly consistent with observations, providing a systems-based rationale for themore » culture phenotypes. The analysis also indicated that cyanobacterial stress acclimation strategies created niches for heterotrophic organisms and that heterotrophic activity could enhance cyanobacterial stress tolerance by removing inhibitory metabolic byproducts. This study provides mechanistic insight into stress acclimation strategies in photoautotrophs and establishes a framework for predicting, designing, and engineering both axenic and photoautotrophic-heterotrophic systems as a function of controllable parameters.« less

Network congestion control algorithm based on Actor-Critic reinforcement learning model

NASA Astrophysics Data System (ADS)

Xu, Tao; Gong, Lina; Zhang, Wei; Li, Xuhong; Wang, Xia; Pan, Wenwen

2018-04-01

Aiming at the network congestion control problem, a congestion control algorithm based on Actor-Critic reinforcement learning model is designed. Through the genetic algorithm in the congestion control strategy, the network congestion problems can be better found and prevented. According to Actor-Critic reinforcement learning, the simulation experiment of network congestion control algorithm is designed. The simulation experiments verify that the AQM controller can predict the dynamic characteristics of the network system. Moreover, the learning strategy is adopted to optimize the network performance, and the dropping probability of packets is adaptively adjusted so as to improve the network performance and avoid congestion. Based on the above finding, it is concluded that the network congestion control algorithm based on Actor-Critic reinforcement learning model can effectively avoid the occurrence of TCP network congestion.

MPC Design for Rapid Pump-Attenuation and Expedited Hyperglycemia Response to Treat T1DM with an Artificial Pancreas

PubMed Central

Gondhalekar, Ravi; Dassau, Eyal; Doyle, Francis J.

2016-01-01

The design of a Model Predictive Control (MPC) strategy for the closed-loop operation of an Artificial Pancreas (AP) for treating Type 1 Diabetes Mellitus (T1DM) is considered in this paper. The contribution of this paper is to propose two changes to the usual structure of the MPC problems typically considered for control of an AP. The first proposed change is to replace the symmetric, quadratic input cost function with an asymmetric, quadratic function, allowing negative control inputs to be penalized less than positive ones. This facilitates rapid pump-suspensions in response to predicted hypoglycemia, while simultaneously permitting the design of a conservative response to hyperglycemia. The second proposed change is to penalize the velocity of the predicted glucose level, where this velocity penalty is based on a cost function that is again asymmetric, but additionally state-dependent. This facilitates the accelerated response to acute, persistent hyperglycemic events, e.g., as induced by unannounced meals. The novel functionality is demonstrated by numerical examples, and the efficacy of the proposed MPC strategy verified using the University of Padova/Virginia metabolic simulator. PMID:28479660

To Switch or Not to Switch: Role of Cognitive Control in Working Memory Training in Older Adults.

PubMed

Basak, Chandramallika; O'Connell, Margaret A

2016-01-01

It is currently not known what are the best working memory training strategies to offset the age-related declines in fluid cognitive abilities. In this randomized clinical double-blind trial, older adults were randomly assigned to one of two types of working memory training - one group was trained on a predictable memory updating task (PT) and another group was trained on a novel, unpredictable memory updating task (UT). Unpredictable memory updating, compared to predictable, requires greater demands on cognitive control (Basak and Verhaeghen, 2011a). Therefore, the current study allowed us to evaluate the role of cognitive control in working memory training. All participants were assessed on a set of near and far transfer tasks at three different testing sessions - before training, immediately after the training, and 1.5 months after completing the training. Additionally, individual learning rates for a comparison working memory task (performed by both groups) and the trained task were computed. Training on unpredictable memory updating, compared to predictable, significantly enhanced performance on a measure of episodic memory, immediately after the training. Moreover, individuals with faster learning rates showed greater gains in this episodic memory task and another new working memory task; this effect was specific to UT. We propose that the unpredictable memory updating training, compared to predictable memory updating training, may a better strategy to improve selective cognitive abilities in older adults, and future studies could further investigate the role of cognitive control in working memory training.

Evaluating vaccination strategies to control foot-and-mouth disease: a model comparison study.

PubMed

Roche, S E; Garner, M G; Sanson, R L; Cook, C; Birch, C; Backer, J A; Dube, C; Patyk, K A; Stevenson, M A; Yu, Z D; Rawdon, T G; Gauntlett, F

2015-04-01

Simulation models can offer valuable insights into the effectiveness of different control strategies and act as important decision support tools when comparing and evaluating outbreak scenarios and control strategies. An international modelling study was performed to compare a range of vaccination strategies in the control of foot-and-mouth disease (FMD). Modelling groups from five countries (Australia, New Zealand, USA, UK, The Netherlands) participated in the study. Vaccination is increasingly being recognized as a potentially important tool in the control of FMD, although there is considerable uncertainty as to how and when it should be used. We sought to compare model outputs and assess the effectiveness of different vaccination strategies in the control of FMD. Using a standardized outbreak scenario based on data from an FMD exercise in the UK in 2010, the study showed general agreement between respective models in terms of the effectiveness of vaccination. Under the scenario assumptions, all models demonstrated that vaccination with 'stamping-out' of infected premises led to a significant reduction in predicted epidemic size and duration compared to the 'stamping-out' strategy alone. For all models there were advantages in vaccinating cattle-only rather than all species, using 3-km vaccination rings immediately around infected premises, and starting vaccination earlier in the control programme. This study has shown that certain vaccination strategies are robust even to substantial differences in model configurations. This result should increase end-user confidence in conclusions drawn from model outputs. These results can be used to support and develop effective policies for FMD control.

Landfill gas control at military installations. Final report

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

Shafer, R.A.; Renta-Babb, A.; Bandy, J.T.

1984-01-01

This report provides information useful to Army personnel responsible for recognizing and solving potential problems from gas generated by landfills. Information is provided on recognizing and gauging the magnitude of landfill gas problems; selecting appropriate gas control strategies, procedures, and equipment; use of computer modeling to predict gas production and migration and the success of gas control devices; and safety considerations.

Feedback control of an electrorheological long-stroke vibration damper

NASA Astrophysics Data System (ADS)

Sims, Neil D.; Stanway, Roger; Johnson, Andrew R.; Peel, David J.; Bullough, William A.

1999-06-01

It is widely acknowledged that the inherent non-linearity of smart fluid dampers is inhibiting the development of effective control regimes, and mass-production devices. In an earlier publication, an innovative solution to this problem was presented -- using a simple feedback control strategy to linearize the response. The study used a quasi-steady model of a long-stroke Electrorheological damper, and showed how proportional feedback control could linearize the simulated response. However, this initial research did not consider the dynamics of the damper's behavior, and so the development of a more advanced model has been necessary. In this article, the authors present an extension to this earlier study, using a model of the damper's response that is capable of accurately predicting the dynamic response of the damper. To introduce the topic, the electrorheological long-stroke damper test rig is described, and an overview of the earlier study is given. The advanced model is then derived, and its predictions are compared to experimental data from the test rig. This model is then incorporated into the feedback control simulations, and it is shown how the control strategy is still able to linearize the response in simulations.

Synthesizing epidemiological and economic optima for control of immunizing infections.

PubMed

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

2011-08-23

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

Application of indoor noise prediction in the real world

NASA Astrophysics Data System (ADS)

Lewis, David N.

2002-11-01

Predicting indoor noise in industrial workrooms is an important part of the process of designing industrial plants. Predicted levels are used in the design process to determine compliance with occupational-noise regulations, and to estimate levels inside the walls in order to predict community noise radiated from the building. Once predicted levels are known, noise-control strategies can be developed. In this paper an overview of over 20 years of experience is given with the use of various prediction approaches to manage noise in Unilever plants. This work has applied empirical and ray-tracing approaches separately, and in combination, to design various packaging and production plants and other facilities. The advantages of prediction methods in general, and of the various approaches in particular, will be discussed. A case-study application of prediction methods to the optimization of noise-control measures in a food-packaging plant will be presented. Plans to acquire a simplified prediction model for use as a company noise-screening tool will be discussed.

Regional Differences in Brain Volume Predict the Acquisition of Skill in a Complex Real-Time Strategy Videogame

ERIC Educational Resources Information Center

Basak, Chandramallika; Voss, Michelle W.; Erickson, Kirk I.; Boot, Walter R.; Kramer, Arthur F.

2011-01-01

Previous studies have found that differences in brain volume among older adults predict performance in laboratory tasks of executive control, memory, and motor learning. In the present study we asked whether regional differences in brain volume as assessed by the application of a voxel-based morphometry technique on high resolution MRI would also…

Development of a Model for Human Operator Learning in Continuous Estimation and Control Tasks.

DTIC Science & Technology

1983-12-01

and (3) a " precognitive mode" in 𔄁 17 which the pilot is able to take full advantage of any predictability "" inherent in the external inputs and can...allow application of a partial feedforward strategy; and (3) a " precognitive " mode in which full advantage is taken of any predictability of the

Predicting energy savings attributed to daylighting

NASA Astrophysics Data System (ADS)

Robbins, C. L.

1982-08-01

A method is described for estimating a building's energy savings attributed to daylighting by predicting the percentage of the year that the electric lighting system is not in use. This depends on the particular control strategy chosen, a standard work year, and the amount of light (as a daylight factor) reaching on daylight and sunlight availability for selected cities in the United States.

Optimization and real-time control for laser treatment of heterogeneous soft tissues.

PubMed

Feng, Yusheng; Fuentes, David; Hawkins, Andrea; Bass, Jon M; Rylander, Marissa Nichole

2009-01-01

Predicting the outcome of thermotherapies in cancer treatment requires an accurate characterization of the bioheat transfer processes in soft tissues. Due to the biological and structural complexity of tumor (soft tissue) composition and vasculature, it is often very difficult to obtain reliable tissue properties that is one of the key factors for the accurate treatment outcome prediction. Efficient algorithms employing in vivo thermal measurements to determine heterogeneous thermal tissues properties in conjunction with a detailed sensitivity analysis can produce essential information for model development and optimal control. The goals of this paper are to present a general formulation of the bioheat transfer equation for heterogeneous soft tissues, review models and algorithms developed for cell damage, heat shock proteins, and soft tissues with nanoparticle inclusion, and demonstrate an overall computational strategy for developing a laser treatment framework with the ability to perform real-time robust calibrations and optimal control. This computational strategy can be applied to other thermotherapies using the heat source such as radio frequency or high intensity focused ultrasound.

Designing a Minimal Intervention Strategy to Control Taenia solium.

PubMed

Lightowlers, Marshall W; Donadeu, Meritxell

2017-06-01

Neurocysticercosis is an important cause of epilepsy in many developing countries. The disease is a zoonosis caused by the cestode parasite Taenia solium. Many potential intervention strategies are available, however none has been able to be implemented and sustained. Here we predict the impact of some T. solium interventions that could be applied to prevent transmission through pigs, the parasite's natural animal intermediate host. These include minimal intervention strategies that are predicted to be effective and likely to be feasible. Logical models are presented which reflect changes in the risk that age cohorts of animals have for their potential to transmit T. solium. Interventions that include a combined application of vaccination, plus chemotherapy in young animals, are the most effective. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Assessment of semi-active friction dampers

NASA Astrophysics Data System (ADS)

dos Santos, Marcelo Braga; Coelho, Humberto Tronconi; Lepore Neto, Francisco Paulo; Mafhoud, Jarir

2017-09-01

The use of friction dampers has been widely proposed for a variety of mechanical systems for which applying viscoelastic materials, fluid based dampers or other viscous dampers is impossible. An important example is the application of friction dampers in aircraft engines to reduce the blades' vibration amplitudes. In most cases, friction dampers have been studied in a passive manner, but significant improvements can be achieved by controlling the normal force in the contact region. The aim of this paper is to present and study five control strategies for friction dampers based on three different hysteresis cycles by using the Harmonic Balance Method (HBM), a numerical and experimental analysis. The first control strategy uses the friction force as a resistance when the system is deviating from its equilibrium position. The second control strategy maximizes the energy removal in each harmonic oscillation cycle by calculating the optimal normal force based on the last displacement peak. The third control strategy combines the first strategy with the homogenous modulation of the friction force. Finally, the last two strategies attempt to predict the system's movement based on its velocity and acceleration and our knowledge of its physical properties. Numerical and experimental studies are performed with these five strategies, which define the performance metrics. The experimental testing rig is fully identified and its parameters are used for numerical simulations. The obtained results show the satisfactory performance of the friction damper and selected strategy and the suitable agreement between the numerical and experimental results.

Multivariable model predictive control design of reactive distillation column for Dimethyl Ether production

NASA Astrophysics Data System (ADS)

Wahid, A.; Putra, I. G. E. P.

2018-03-01

Dimethyl ether (DME) as an alternative clean energy has attracted a growing attention in the recent years. DME production via reactive distillation has potential for capital cost and energy requirement savings. However, combination of reaction and distillation on a single column makes reactive distillation process a very complex multivariable system with high non-linearity of process and strong interaction between process variables. This study investigates a multivariable model predictive control (MPC) based on two-point temperature control strategy for the DME reactive distillation column to maintain the purities of both product streams. The process model is estimated by a first order plus dead time model. The DME and water purity is maintained by controlling a stage temperature in rectifying and stripping section, respectively. The result shows that the model predictive controller performed faster responses compared to conventional PI controller that are showed by the smaller ISE values. In addition, the MPC controller is able to handle the loop interactions well.

Preliminary analysis of the PreFlexMS molten salt once-through steam generator dynamics and control strategy

NASA Astrophysics Data System (ADS)

Trabucchi, Stefano; Casella, Francesco; Maioli, Tommaso; Elsido, Cristina; Franzini, Davide; Ramond, Mathieu

2017-06-01

Concentrated Solar Power plants (CSP) coupled with thermal storage have the potential to guarantee both flexible and continuous energy production, thus being competitive with conventional fossil fuel and hydro power plants, in terms of dispatchability and provision of ancillary services. Hence, the plant equipment and control design have to be focused on flexible operation on one hand, and on plant safety concerning the molten salt freezing on the other hand. The PreFlexMS European project aims to introduce a molten salt Once-Through Steam Generator (OTSG) within a Rankine cycle based power unit, a technology that has greater flexibility potential if compared to steam drum boilers, currently used in CSP plants. The dynamic modelling and simulation from the early design stages is, thus, of paramount importance, to assess the plant dynamic behavior and controllability, and to predict the achievable closed-loop dynamic performance, potentially saving money and time during the detailed design, construction and commissioning phases. The present paper reports the main results of the analysis carried out during the first part of the project, regarding the system analysis and control design. In particular, two different control systems have been studied and tested with the plant dynamic model: a decentralized control strategy based on PI controllers and a Linear Model Predictive Control (LMPC).

Study on SOC wavelet analysis for LiFePO4 battery

NASA Astrophysics Data System (ADS)

Liu, Xuepeng; Zhao, Dongmei

2017-08-01

Improving the prediction accuracy of SOC can reduce the complexity of the conservative and control strategy of the strategy such as the scheduling, optimization and planning of LiFePO4 battery system. Based on the analysis of the relationship between the SOC historical data and the external stress factors, the SOC Estimation-Correction Prediction Model based on wavelet analysis is established. Using wavelet neural network prediction model is of high precision to achieve forecast link, external stress measured data is used to update parameters estimation in the model, implement correction link, makes the forecast model can adapt to the LiFePO4 battery under rated condition of charge and discharge the operating point of the variable operation area. The test results show that the method can obtain higher precision prediction model when the input and output of LiFePO4 battery are changed frequently.

Predicting Baseline for Analysis of Electricity Pricing

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

Kim, T.; Lee, D.; Choi, J.

2016-05-03

To understand the impact of new pricing structure on residential electricity demands, we need a baseline model that captures every factor other than the new price. The standard baseline is a randomized control group, however, a good control group is hard to design. This motivates us to devlop data-driven approaches. We explored many techniques and designed a strategy, named LTAP, that could predict the hourly usage years ahead. The key challenge in this process is that the daily cycle of electricity demand peaks a few hours after the temperature reaching its peak. Existing methods rely on the lagged variables ofmore » recent past usages to enforce this daily cycle. These methods have trouble making predictions years ahead. LTAP avoids this trouble by assuming the daily usage profile is determined by temperature and other factors. In a comparison against a well-designed control group, LTAP is found to produce accurate predictions.« less

Feedforward hysteresis compensation in trajectory control of piezoelectrically-driven nanostagers

NASA Astrophysics Data System (ADS)

Bashash, Saeid; Jalili, Nader

2006-03-01

Complex structural nonlinearities of piezoelectric materials drastically degrade their performance in variety of micro- and nano-positioning applications. From the precision positioning and control perspective, the multi-path time-history dependent hysteresis phenomenon is the most concerned nonlinearity in piezoelectric actuators to be analyzed. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligent properties of hysteresis with the effects of non-local memories are discussed. Through performing a set of experiments on a piezoelectrically-driven nanostager with high resolution capacitive position sensor, it is shown that for the precise prediction of hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the system everpresent nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect if memory units are sufficiently chosen for the inverse model.

Optimal control analysis of Ebola disease with control strategies of quarantine and vaccination.

PubMed

Ahmad, Muhammad Dure; Usman, Muhammad; Khan, Adnan; Imran, Mudassar

2016-07-13

The 2014 Ebola epidemic is the largest in history, affecting multiple countries in West Africa. Some isolated cases were also observed in other regions of the world. In this paper, we introduce a deterministic SEIR type model with additional hospitalization, quarantine and vaccination components in order to understand the disease dynamics. Optimal control strategies, both in the case of hospitalization (with and without quarantine) and vaccination are used to predict the possible future outcome in terms of resource utilization for disease control and the effectiveness of vaccination on sick populations. Further, with the help of uncertainty and sensitivity analysis we also have identified the most sensitive parameters which effectively contribute to change the disease dynamics. We have performed mathematical analysis with numerical simulations and optimal control strategies on Ebola virus models. We used dynamical system tools with numerical simulations and optimal control strategies on our Ebola virus models. The original model, which allowed transmission of Ebola virus via human contact, was extended to include imperfect vaccination and quarantine. After the qualitative analysis of all three forms of Ebola model, numerical techniques, using MATLAB as a platform, were formulated and analyzed in detail. Our simulation results support the claims made in the qualitative section. Our model incorporates an important component of individuals with high risk level with exposure to disease, such as front line health care workers, family members of EVD patients and Individuals involved in burial of deceased EVD patients, rather than the general population in the affected areas. Our analysis suggests that in order for R 0 (i.e., the basic reproduction number) to be less than one, which is the basic requirement for the disease elimination, the transmission rate of isolated individuals should be less than one-fourth of that for non-isolated ones. Our analysis also predicts, we need high levels of medication and hospitalization at the beginning of an epidemic. Further, optimal control analysis of the model suggests the control strategies that may be adopted by public health authorities in order to reduce the impact of epidemics like Ebola.

Output-Feedback Model Predictive Control of a Pasteurization Pilot Plant based on an LPV model

NASA Astrophysics Data System (ADS)

Karimi Pour, Fatemeh; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-01-01

This paper presents a model predictive control (MPC) of a pasteurization pilot plant based on an LPV model. Since not all the states are measured, an observer is also designed, which allows implementing an output-feedback MPC scheme. However, the model of the plant is not completely observable when augmented with the disturbance models. In order to solve this problem, the following strategies are used: (i) the whole system is decoupled into two subsystems, (ii) an inner state-feedback controller is implemented into the MPC control scheme. A real-time example based on the pasteurization pilot plant is simulated as a case study for testing the behavior of the approaches.

Temperature control in a solar collector field using Filtered Dynamic Matrix Control.

PubMed

Lima, Daniel Martins; Normey-Rico, Julio Elias; Santos, Tito Luís Maia

2016-05-01

This paper presents the output temperature control of a solar collector field of a desalinization plant using the Filtered Dynamic Matrix Control (FDMC). The FDMC is a modified controller based on the Dynamic Matrix Control (DMC), a predictive control strategy widely used in industry. In the FDMC, a filter is used in the prediction error, which allows the modification of the robustness and disturbance rejection characteristics of the original algorithm. The implementation and tuning of the FDMC are simple and maintain the advantages of DMC. Several simulation results using a validated model of the solar plant are presented considering different scenarios. The results are also compared to nonlinear control techniques, showing that FDMC, if properly tuned, can yield similar results to more complex control algorithms. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

PubMed

Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

2017-10-12

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

Left behind or moving forward? Effects of possible selves and strategies to attain them among rural Chinese children.

PubMed

Bi, Chongzeng; Oyserman, Daphna

2015-10-01

Are possible selves and strategies to attain them universally helpful even among children with few resources? We test this question in rural China. Rural Chinese children are commonly "left behind" (LB) by parents seizing economic opportunities by migrating, hoping the family will "move forward" and their children will attain their predestined better future. Media, teachers, and peers negatively represent LB children as unruly and undisciplined, with negative fates, making LB a negative stereotype that includes the idea of destiny or fate. Indeed, making the idea of LB salient increases children's fatalism (Study 1 n = 144, Study 2 n = 124). However, having strategies to attain possible future selves predicts better in-class behavior, fewer depressive symptoms, and better exam performance even a year later and controlling for prior performance (Study 3 n = 176, Study 4 n = 145). Possible selves have mixed effects, not always predicting better grades and undermining LB children's self-control. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Development of a model to simulate infection dynamics of Mycobacterium bovis in cattle herds in the United States

PubMed Central

Smith, Rebecca L.; Schukken, Ynte H.; Lu, Zhao; Mitchell, Rebecca M.; Grohn, Yrjo T.

2013-01-01

Objective To develop a mathematical model to simulate infection dynamics of Mycobacterium bovis in cattle herds in the United States and predict efficacy of the current national control strategy for tuberculosis in cattle. Design Stochastic simulation model. Sample Theoretical cattle herds in the United States. Procedures A model of within-herd M bovis transmission dynamics following introduction of 1 latently infected cow was developed. Frequency- and density-dependent transmission modes and 3 tuberculin-test based culling strategies (no test-based culling, constant (annual) testing with test-based culling, and the current strategy of slaughterhouse detection-based testing and culling) were investigated. Results were evaluated for 3 herd sizes over a 10-year period and validated via simulation of known outbreaks of M bovis infection. Results On the basis of 1,000 simulations (1000 herds each) at replacement rates typical for dairy cattle (0.33/y), median time to detection of M bovis infection in medium-sized herds (276 adult cattle) via slaughterhouse surveillance was 27 months after introduction, and 58% of these herds would spontaneously clear the infection prior to that time. Sixty-two percent of medium-sized herds without intervention and 99% of those managed with constant test-based culling were predicted to clear infection < 10 years after introduction. The model predicted observed outbreaks best for frequency-dependent transmission, and probability of clearance was most sensitive to replacement rate. Conclusions and Clinical Relevance Although modeling indicated the current national control strategy was sufficient for elimination of M bovis infection from dairy herds after detection, slaughterhouse surveillance was not sufficient to detect M bovis infection in all herds and resulted in subjectively delayed detection, compared with the constant testing method. Further research is required to economically optimize this strategy. PMID:23865885

Active model-based balancing strategy for self-reconfigurable batteries

NASA Astrophysics Data System (ADS)

Bouchhima, Nejmeddine; Schnierle, Marc; Schulte, Sascha; Birke, Kai Peter

2016-08-01

This paper describes a novel balancing strategy for self-reconfigurable batteries where the discharge and charge rates of each cell can be controlled. While much effort has been focused on improving the hardware architecture of self-reconfigurable batteries, energy equalization algorithms have not been systematically optimized in terms of maximizing the efficiency of the balancing system. Our approach includes aspects of such optimization theory. We develop a balancing strategy for optimal control of the discharge rate of battery cells. We first formulate the cell balancing as a nonlinear optimal control problem, which is modeled afterward as a network program. Using dynamic programming techniques and MATLAB's vectorization feature, we solve the optimal control problem by generating the optimal battery operation policy for a given drive cycle. The simulation results show that the proposed strategy efficiently balances the cells over the life of the battery, an obvious advantage that is absent in the other conventional approaches. Our algorithm is shown to be robust when tested against different influencing parameters varying over wide spectrum on different drive cycles. Furthermore, due to the little computation time and the proved low sensitivity to the inaccurate power predictions, our strategy can be integrated in a real-time system.

Reasoning, learning, and creativity: frontal lobe function and human decision-making.

PubMed

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control--that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior.

Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation.

PubMed

Ławryńczuk, Maciej

2017-03-01

This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Robust predictive control with optimal load tracking for critical applications. Final report

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

Tse, J.; Bentsman, J.; Miller, N.

1994-09-01

This report derives a multi-input multi-output (MIMO) version of a two-degree-of-freedom receding-horizon control law based on mixed H{sub 2}/H{infinity} minimization. First, the integrand in the frequency domain representation of the MIMO performance criterion is decomposed into disturbance and reference spectra. Then the controller is derived which minimizes the peak of the disturbance spectrum and the integral of the reference spectrum on the unit circle. The resulting two-degree-of-freedom MIMO control strategy, referred to as the minimax predictive multivariable control (MPC), is shown to have worst-case-disturbance-rejection and robust-stability properties superior to those of purely H{sub 2}-optimal controllers, such as Generalized Predictive Controlmore » (GPC), for identical horizons. An attractive feature of the receding horizon structure of MPC is that it can, in ways similar to GPC, directly incorporate input constraints and pre-programmed reference inputs, which are nontrivial tasks in the standard H{infinity} design.« less

The happy personality: a meta-analysis of 137 personality traits and subjective well-being.

PubMed

DeNeve, K M; Cooper, H

1998-09-01

This meta-analysis used 9 literature search strategies to examine 137 distinct personality constructs as correlates of subjective well-being (SWB). Personality was found to be equally predictive of life satisfaction, happiness, and positive affect, but significantly less predictive of negative affect. The traits most closely associated with SWB were repressive-defensiveness, trust, emotional stability, locus of control-chance, desire for control, hardiness, positive affectivity, private collective self-esteem, and tension. When personality traits were grouped according to the Big Five factors, Neuroticism was the strongest predictor of life satisfaction, happiness, and negative affect. Positive affect was predicted equally well by Extraversion and Agreeableness. The relative importance of personality for predicting SWB, how personality might influence SWB, and limitations of the present review are discussed.

Viking navigation

NASA Technical Reports Server (NTRS)

Oneil, W. J.; Rudd, R. P.; Farless, D. L.; Hildebrand, C. E.; Mitchell, R. T.; Rourke, K. H.; Euler, E. A.

1979-01-01

A comprehensive description of the navigation of the Viking spacecraft throughout their flight from Earth launch to Mars landing is given. The flight path design, actual inflight control, and postflight reconstruction are discussed in detail. The preflight analyses upon which the operational strategies and performance predictions were based are discussed. The inflight results are then discussed and compared with the preflight predictions and, finally, the results of any postflight analyses are presented.

Using the Theory of Planned Behavior to predict implementation of harm reduction strategies among MDMA/ecstasy users.

PubMed

Davis, Alan K; Rosenberg, Harold

2016-06-01

This prospective study was designed to test whether the variables proposed by the Theory of Planned Behavior (TPB) were associated with baseline intention to implement and subsequent use of 2 MDMA/ecstasy-specific harm reduction interventions: preloading/postloading and pill testing/pill checking. Using targeted Facebook advertisements, an international sample of 391 recreational ecstasy users were recruited to complete questionnaires assessing their ecstasy consumption history, and their attitudes, subjective norms, perceived behavioral control, habit strength (past strategy use), and intention to use these two strategies. Attitudes, subjective norms, and perceived behavioral control were significantly associated with baseline intention to preload/postload and pill test/pill check. Out of the 391 baseline participants, 100 completed the two-month follow-up assessment. Baseline habit strength and frequency of ecstasy consumption during the three months prior to baseline were the only significant predictors of how often participants used the preloading/postloading strategy during the follow-up. Baseline intention to pill test/pill check was the only significant predictor of how often participants used this strategy during the follow-up. These findings provide partial support for TPB variables as both correlates of baseline intention to implement and predictors of subsequent use of these two strategies. Future investigations could assess whether factors related to ecstasy consumption (e.g., subjective level of intoxication, craving, negative consequences following consumption), and environmental factors (e.g., accessibility and availability of harm reduction resources) improve the prediction of how often ecstasy users employ these and other harm reduction strategies. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Adaptive two-degree-of-freedom PI for speed control of permanent magnet synchronous motor based on fractional order GPC.

PubMed

Qiao, Wenjun; Tang, Xiaoqi; Zheng, Shiqi; Xie, Yuanlong; Song, Bao

2016-09-01

In this paper, an adaptive two-degree-of-freedom (2Dof) proportional-integral (PI) controller is proposed for the speed control of permanent magnet synchronous motor (PMSM). Firstly, an enhanced just-in-time learning technique consisting of two novel searching engines is presented to identify the model of the speed control system in a real-time manner. Secondly, a general formula is given to predict the future speed reference which is unavailable at the interval of two bus-communication cycles. Thirdly, the fractional order generalized predictive control (FOGPC) is introduced to improve the control performance of the servo drive system. Based on the identified model parameters and predicted speed reference, the optimal control law of FOGPC is derived. Finally, the designed 2Dof PI controller is auto-tuned by matching with the optimal control law. Simulations and real-time experimental results on the servo drive system of PMSM are provided to illustrate the effectiveness of the proposed strategy. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Goal setting frequency and the use of behavioral strategies related to diet and physical activity.

PubMed

Nothwehr, Faryle; Yang, Jingzhen

2007-08-01

Goal setting is an effective way to focus attention on behavior change. Theoretically, frequency of goal setting may indicate the level of commitment to diet and physical activity behavior change. Yet, little is known about the association between goal setting frequency and use of specific diet or physical activity-related strategies. This study examines whether changes in goal setting frequency predict changes in use of behavioral strategies over time, controlling for baseline strategy use, demographics and whether a person was trying to lose weight. Data are from a baseline and 1-year follow-up survey of adults in rural Iowa (n = 385). Overall, goal setting frequency was positively associated with use of the strategies measured, at baseline and overtime. Frequent goal setting that is focused specifically on diet or physical activity was more predictive of using dietary or physical activity strategies, respectively, than goal setting focused on weight loss overall. The study provides empirical support for what has been assumed theoretically, that is, frequent goal setting for weight management is an indicator of use of specific behavioral strategies. Significant challenges remain in regard to maintenance of this activity and attainment of weight loss goals.

Supraspinal Control Predicts Locomotor Function and Forecasts Responsiveness to Training after Spinal Cord Injury

PubMed Central

Field-Fote, Edelle C.; Yang, Jaynie F.; Basso, D. Michele; Gorassini, Monica A.

2017-01-01

Abstract Restoration of walking ability is an area of great interest in the rehabilitation of persons with spinal cord injury. Because many cortical, subcortical, and spinal neural centers contribute to locomotor function, it is important that intervention strategies be designed to target neural elements at all levels of the neuraxis that are important for walking ability. While to date most strategies have focused on activation of spinal circuits, more recent studies are investigating the value of engaging supraspinal circuits. Despite the apparent potential of pharmacological, biological, and genetic approaches, as yet none has proved more effective than physical therapeutic rehabilitation strategies. By making optimal use of the potential of the nervous system to respond to training, strategies can be developed that meet the unique needs of each person. To complement the development of optimal training interventions, it is valuable to have the ability to predict future walking function based on early clinical presentation, and to forecast responsiveness to training. A number of clinical prediction rules and association models based on common clinical measures have been developed with the intent, respectively, to predict future walking function based on early clinical presentation, and to delineate characteristics associated with responsiveness to training. Further, a number of variables that are correlated with walking function have been identified. Not surprisingly, most of these prediction rules, association models, and correlated variables incorporate measures of volitional lower extremity strength, illustrating the important influence of supraspinal centers in the production of walking behavior in humans. PMID:27673569

Development of a strategy and computational application to select candidate protein analogues with reduced HLA binding and immunogenicity.

PubMed

Dhanda, Sandeep Kumar; Grifoni, Alba; Pham, John; Vaughan, Kerrie; Sidney, John; Peters, Bjoern; Sette, Alessandro

2018-01-01

Unwanted immune responses against protein therapeutics can reduce efficacy or lead to adverse reactions. T-cell responses are key in the development of such responses, and are directed against immunodominant regions within the protein sequence, often associated with binding to several allelic variants of HLA class II molecules (promiscuous binders). Herein, we report a novel computational strategy to predict 'de-immunized' peptides, based on previous studies of erythropoietin protein immunogenicity. This algorithm (or method) first predicts promiscuous binding regions within the target protein sequence and then identifies residue substitutions predicted to reduce HLA binding. Further, this method anticipates the effect of any given substitution on flanking peptides, thereby circumventing the creation of nascent HLA-binding regions. As a proof-of-principle, the algorithm was applied to Vatreptacog α, an engineered Factor VII molecule associated with unintended immunogenicity. The algorithm correctly predicted the two immunogenic peptides containing the engineered residues. As a further validation, we selected and evaluated the immunogenicity of seven substitutions predicted to simultaneously reduce HLA binding for both peptides, five control substitutions with no predicted reduction in HLA-binding capacity, and additional flanking region controls. In vitro immunogenicity was detected in 21·4% of the cultures of peptides predicted to have reduced HLA binding and 11·4% of the flanking regions, compared with 46% for the cultures of the peptides predicted to be immunogenic. This method has been implemented as an interactive application, freely available online at http://tools.iedb.org/deimmunization/. © 2017 John Wiley & Sons Ltd.

Neuroanatomy of the vmPFC and dlPFC predicts individual differences in cognitive regulation during dietary self-control across regulation strategies.

PubMed

Schmidt, Liane; Tusche, Anita; Manoharan, Nicolas; Hutcherson, Cendri; Hare, Todd; Plassmann, Hilke

2018-06-04

Making healthy food choices is challenging for many people. Individuals differ greatly in their ability to follow health goals in the face of temptation, but it is unclear what underlies such differences. Using voxel-based morphometry (VBM), we investigated in healthy humans (i.e., men and women) links between structural variation in gray matter volume and individuals' level of success in shifting toward healthier food choices. We combined MRI and choice data into a joint dataset by pooling across three independent studies that employed a task prompting participants to explicitly focus on the healthiness of food items before making their food choices. Within this dataset, we found that individual differences in gray matter volume in the ventromedial prefrontal cortex (vmPFC) and dorsolateral prefrontal cortex (dlPFC) predicted regulatory success. We extended and confirmed these initial findings by predicting regulatory success out of sample and across tasks in a second dataset requiring participants to apply a different regulation strategy that entailed distancing from cravings for unhealthy, appetitive foods. Our findings suggest that neuroanatomical markers in the vmPFC and dlPFC generalized to different forms of dietary regulation strategies across participant groups. They provide novel evidence that structural differences in neuroanatomy of two key regions for valuation and its control, the vmPFC and dlPFC, predict an individual's ability to exert control in dietary choices. SIGNIFICANCE STATEMENT Dieting involves regulating food choices in order to eat healthier foods and fewer unhealthy foods. People differ dramatically in their ability to achieve or maintain this regulation, but it is unclear why. Here, we show that individuals with more gray matter volume in the dorsolateral and ventromedial prefrontal cortex are better at exercising dietary self-control. This relationship was observed across four different studies examining two different forms of dietary self-regulation, suggesting that neuroanatomical differences in the vmPFC and dlPFC may represent a general marker for self-control abilities. These results identify candidate neuroanatomical markers for dieting success and failure, and suggest potential targets for therapies aimed at preventing or treating obesity and related eating disorders. Copyright © 2018 the authors.

Planning schistosomiasis control: investigation of alternative sampling strategies for Schistosoma mansoni to target mass drug administration of praziquantel in East Africa.

PubMed

Sturrock, Hugh J W; Gething, Pete W; Ashton, Ruth A; Kolaczinski, Jan H; Kabatereine, Narcis B; Brooker, Simon

2011-09-01

In schistosomiasis control, there is a need to geographically target treatment to populations at high risk of morbidity. This paper evaluates alternative sampling strategies for surveys of Schistosoma mansoni to target mass drug administration in Kenya and Ethiopia. Two main designs are considered: lot quality assurance sampling (LQAS) of children from all schools; and a geostatistical design that samples a subset of schools and uses semi-variogram analysis and spatial interpolation to predict prevalence in the remaining unsurveyed schools. Computerized simulations are used to investigate the performance of sampling strategies in correctly classifying schools according to treatment needs and their cost-effectiveness in identifying high prevalence schools. LQAS performs better than geostatistical sampling in correctly classifying schools, but at a cost with a higher cost per high prevalence school correctly classified. It is suggested that the optimal surveying strategy for S. mansoni needs to take into account the goals of the control programme and the financial and drug resources available.

[Parental Monitoring and its Relation to Behaviour Problems and Risk Behaviour in an Adolescent School Sample].

PubMed

Trick, Sarah; Jantzer, Vanessa; Haffner, Johann; Parzer, Peter; Resch, Franz

2016-10-01

Parental Monitoring and its Relation to Behaviour Problems and Risk Behaviour in an Adolescent School Sample Numerous research studies emphasize parental monitoring as a protective factor for adolescent problem behaviour. The purpose of the study presented was to use Stattin and Kerr's (2000) monitoring subscales for the first time in a German-speaking area and to explore the relations to behaviour problems in an adolescent school sample. The two active monitoring strategies "parental control" and "parental solicitation" as well as "parental knowledge" and "child disclosure" relating to behaviour problems and risk behaviour were examined. A sample of 494 pupils, grades 5, 7 and 9, of German secondary schools and their parents answered questions on "parental knowledge", "control", "solicitation" and "child disclosure". Adolescents also answered the German version of the Strengths and Difficulties Questionnaire (SDQ) and items about risk behaviour like frequency of violence, delinquency, substance abuse, self-injuring behaviour and school absenteeism. Behaviour problems in terms of the SDQ could be predicted sufficiently by "parental knowledge", but for the prediction of risk behaviour, the active parental monitoring strategies were of importance, too. More "parental knowledge", more "control" and less "solicitation" could predict less risk behaviour. Results confirm "parental knowledge" as a general protective factor for problem behaviour. However, they show the importance of "parental control" for adolescent risk behaviour.

Disrupted latent inhibition in individuals at ultra high-risk for developing psychosis.

PubMed

Kraus, Michael; Rapisarda, Attilio; Lam, Max; Thong, Jamie Y J; Lee, Jimmy; Subramaniam, Mythily; Collinson, Simon L; Chong, Siow Ann; Keefe, Richard S E

2016-12-01

The addition of off-the-shelf cognitive measures to established prodromal criteria has resulted in limited improvement in the prediction of conversion to psychosis. Tests that assess cognitive processes central to schizophrenia might better identify those at highest risk. The latent inhibition paradigm assesses a subject's tendency to ignore irrelevant stimuli, a process integral to healthy perceptual and cognitive function that has been hypothesized to be a key deficit underlying the development of schizophrenia. In this study, 142 young people at ultra high-risk for developing psychosis and 105 controls were tested on a within-subject latent inhibition paradigm. Additionally, we later inquired about the strategy that each subject employed to complete the test, and further investigated the relationship between reported strategy and the extent of latent inhibition exhibited. Unlike controls, ultra high-risk subjects did not demonstrate a significant latent inhibition effect. This difference between groups became greater when controlling for strategy. The lack of latent inhibition effect in our ultra high-risk sample suggests that individuals at ultra high-risk for psychosis are impaired in their allocation of attentional resources based on past predictive value of repeated stimuli. This fundamental deficit in the allocation of attention may contribute to the broader array of cognitive impairments and clinical symptoms displayed by individuals at ultra high-risk for psychosis.

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.

Method of operating an oil shale kiln

DOEpatents

Reeves, Adam A.

1978-05-23

Continuously determining the bulk density of raw and retorted oil shale, the specific gravity of the raw oil shale and the richness of the raw oil shale provides accurate means to control process variables of the retorting of oil shale, predicting oil production, determining mining strategy, and aids in controlling shale placement in the kiln for the retorting.

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

DOE PAGES

Li, Mingjie; Zhou, Ping; Wang, Hong; ...

2017-09-19

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

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

Li, Mingjie; Zhou, Ping; Wang, Hong

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

The self-serving function of hypochondriacal complaints: physical symptoms as self-handicapping strategies.

PubMed

Smith, T W; Snyder, C R; Perkins, S C

1983-04-01

The present experiment tested the hypothesis that hypochondriacal individuals commonly use reports of physical illness and symptoms as a strategy to control attributions made about their performances in evaluative settings (i.e., self-handicapping strategies). Specifically, it was predicted that hypochondriacal individuals would report more recent physical illness and complaints and more current physical symptoms in an evaluative setting in which poor health could serve as an alternative explanation for poor performance than would either individuals in an evaluative setting in which poor health was precluded as an excuse or individuals in a nonevaluative setting. As predicted, results supported this self-protective pattern of complaints in a hypochondriacal sample but not in a nonhypochondriacal group. The self-protective role of hypochondriacal behavior is discussed in relation to other theory and research on the nature and treatment of hypochondriasis.

How Can Onchocerciasis Elimination in Africa Be Accelerated? Modeling the Impact of Increased Ivermectin Treatment Frequency and Complementary Vector Control.

PubMed

Verver, Suzanne; Walker, Martin; Kim, Young Eun; Fobi, Grace; Tekle, Afework H; Zouré, Honorat G M; Wanji, Samuel; Boakye, Daniel A; Kuesel, Annette C; de Vlas, Sake J; Boussinesq, Michel; Basáñez, Maria-Gloria; Stolk, Wilma A

2018-06-01

Great strides have been made toward onchocerciasis elimination by mass drug administration (MDA) of ivermectin. Focusing on MDA-eligible areas, we investigated where the elimination goal can be achieved by 2025 by continuation of current practice (annual MDA with ivermectin) and where intensification or additional vector control is required. We did not consider areas hypoendemic for onchocerciasis with loiasis coendemicity where MDA is contraindicated. We used 2 previously published mathematical models, ONCHOSIM and EPIONCHO, to simulate future trends in microfilarial prevalence for 80 different settings (defined by precontrol endemicity and past MDA frequency and coverage) under different future treatment scenarios (annual, biannual, or quarterly MDA with different treatment coverage through 2025, with or without vector control strategies), assessing for each strategy whether it eventually leads to elimination. Areas with 40%-50% precontrol microfilarial prevalence and ≥10 years of annual MDA may achieve elimination with a further 7 years of annual MDA, if not achieved already, according to both models. For most areas with 70%-80% precontrol prevalence, ONCHOSIM predicts that either annual or biannual MDA is sufficient to achieve elimination by 2025, whereas EPIONCHO predicts that elimination will not be achieved even with complementary vector control. Whether elimination will be reached by 2025 depends on precontrol endemicity, control history, and strategies chosen from now until 2025. Biannual or quarterly MDA will accelerate progress toward elimination but cannot guarantee it by 2025 in high-endemicity areas. Long-term concomitant MDA and vector control for high-endemicity areas might be useful.

Quality of life, psychological characteristics, and adjustment in parents of children with Attention-Deficit/Hyperactivity Disorder.

PubMed

Cappe, Emilie; Bolduc, Mélanie; Rougé, Marie-Caroline; Saiag, Marie-Claude; Delorme, Richard

2017-05-01

This study investigated quality of life and adjustment mechanisms in parents of children with Attention-Deficit/Hyperactivity Disorder (ADHD). Ninety parents of children with ADHD completed a sociodemographic questionnaire and self-assessment scales to measure their perceived stress, social support, sense of control, coping strategies and quality of life. ADHD in children negatively affected parents' quality of life, especially their psychological well-being and personal fulfillment. Family and couple relationships, as well as daily life activities, were also affected. The severity of the disorder, perceiving the situation as a threat or a loss, feeling guilty and holding on to irrational beliefs were related to emotion-focused coping strategies and to a poorer quality of life. Furthermore, hyperactivity index and stress ratings relative to perceiving the situation as a threat or a loss, and adopting emotion-focused coping strategies, predicted poorer quality of life. In contrast, perceiving the situation as challenging was related to a greater sense of control and personal fulfillment. Moreover, perceiving the situation as challenging and adopting problem-focused coping strategies predicted better quality of life. The findings highlight the negative effects of ADHD on parent psychological adjustment and underline the need to recommend training programs that improve parenting skills, parents' perceptions concerning their child's behavior disorder and parental functioning.

Investigation of High School Students' Online Science Information Searching Performance: The Role of Implicit and Explicit Strategies

NASA Astrophysics Data System (ADS)

Tsai, Meng-Jung; Hsu, Chung-Yuan; Tsai, Chin-Chung

2012-04-01

Due to a growing trend of exploring scientific knowledge on the Web, a number of studies have been conducted to highlight examination of students' online searching strategies. The investigation of online searching generally employs methods including a survey, interview, screen-capturing, or transactional logs. The present study firstly intended to utilize a survey, the Online Information Searching Strategies Inventory (OISSI), to examine users' searching strategies in terms of control, orientation, trial and error, problem solving, purposeful thinking, selecting main ideas, and evaluation, which is defined as implicit strategies. Second, this study conducted screen-capturing to investigate the students' searching behaviors regarding the number of keywords, the quantity and depth of Web page exploration, and time attributes, which is defined as explicit strategies. Ultimately, this study explored the role that these two types of strategies played in predicting the students' online science information searching outcomes. A total of 103 Grade 10 students were recruited from a high school in northern Taiwan. Through Pearson correlation and multiple regression analyses, the results showed that the students' explicit strategies, particularly the time attributes proposed in the present study, were more successful than their implicit strategies in predicting their outcomes of searching science information. The participants who spent more time on detailed reading (explicit strategies) and had better skills of evaluating Web information (implicit strategies) tended to have superior searching performance.

Impact of stakeholders influence, geographic level and risk perception on strategic decisions in simulated foot and mouth disease epizootics in France.

PubMed

Marsot, Maud; Rautureau, Séverine; Dufour, Barbara; Durand, Benoit

2014-01-01

Comparison of control strategies against animal infectious diseases allows determining optimal strategies according to their epidemiological and/or economic impacts. However, in real life, the choice of a control strategy does not always obey a pure economic or epidemiological rationality. The objective of this study was to analyze the choice of a foot and mouth disease (FMD) control strategy as a decision-making process in which the decision-maker is influenced by several stakeholders (government, agro-food industries, public opinion). For each of these, an indicator of epizootic impact was quantified to compare seven control strategies. We then determined how, in France, the optimal control strategy varied according to the relative weights of stakeholders and to the perception of risk by the decision-maker (risk-neutral/risk-averse). When the scope of decision was national, whatever their perception of risk and the stakeholders' weights, decision-makers chose a strategy based on vaccination. This consensus concealed marked differences between regions, which were connected with the regional breeding characteristics. Vaccination-based strategies were predominant in regions with dense cattle and swine populations, and in regions with a dense population of small ruminants, combined with a medium density of cattle and swine. These differences between regions suggested that control strategies could be usefully adapted to local breeding conditions. We then analyzed the feasibility of adaptive decision-making processes depending on the date and place where the epizootic starts, or on the evolution of the epizootic over time. The initial conditions always explained at least half of the variance of impacts, the remaining variance being attributed to the variability of epizootics evolution. However, the first weeks of this evolution explained a large part of the impacts variability. Although the predictive value of the initial conditions for determining the optimal strategy was weak, adaptive strategies changing dynamically according to the evolution of the epizootic appeared feasible.

Smart EV Energy Management System to Support Grid Services

NASA Astrophysics Data System (ADS)

Wang, Bin

Under smart grid scenarios, the advanced sensing and metering technologies have been applied to the legacy power grid to improve the system observability and the real-time situational awareness. Meanwhile, there is increasing amount of distributed energy resources (DERs), such as renewable generations, electric vehicles (EVs) and battery energy storage system (BESS), etc., being integrated into the power system. However, the integration of EVs, which can be modeled as controllable mobile energy devices, brings both challenges and opportunities to the grid planning and energy management, due to the intermittency of renewable generation, uncertainties of EV driver behaviors, etc. This dissertation aims to solve the real-time EV energy management problem in order to improve the overall grid efficiency, reliability and economics, using online and predictive optimization strategies. Most of the previous research on EV energy management strategies and algorithms are based on simplified models with unrealistic assumptions that the EV charging behaviors are perfectly known or following known distributions, such as the arriving time, leaving time and energy consumption values, etc. These approaches fail to obtain the optimal solutions in real-time because of the system uncertainties. Moreover, there is lack of data-driven strategy that performs online and predictive scheduling for EV charging behaviors under microgrid scenarios. Therefore, we develop an online predictive EV scheduling framework, considering uncertainties of renewable generation, building load and EV driver behaviors, etc., based on real-world data. A kernel-based estimator is developed to predict the charging session parameters in real-time with improved estimation accuracy. The efficacy of various optimization strategies that are supported by this framework, including valley-filling, cost reduction, event-based control, etc., has been demonstrated. In addition, the existing simulation-based approaches do not consider a variety of practical concerns of implementing such a smart EV energy management system, including the driver preferences, communication protocols, data models, and customized integration of existing standards to provide grid services. Therefore, this dissertation also solves these issues by designing and implementing a scalable system architecture to capture the user preferences, enable multi-layer communication and control, and finally improve the system reliability and interoperability.

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking

PubMed Central

Janssen, Christian P.; Brumby, Duncan P.

2015-01-01

We investigate how good people are at multitasking by comparing behavior to a prediction of the optimal strategy for dividing attention between two concurrent tasks. In our experiment, 24 participants had to interleave entering digits on a keyboard with controlling a randomly moving cursor with a joystick. The difficulty of the tracking task was systematically varied as a within-subjects factor. Participants were also exposed to different explicit reward functions that varied the relative importance of the tracking task relative to the typing task (between-subjects). Results demonstrate that these changes in task characteristics and monetary incentives, together with individual differences in typing ability, influenced how participants choose to interleave tasks. This change in strategy then affected their performance on each task. A computational cognitive model was used to predict performance for a wide set of alternative strategies for how participants might have possibly interleaved tasks. This allowed for predictions of optimal performance to be derived, given the constraints placed on performance by the task and cognition. A comparison of human behavior with the predicted optimal strategy shows that participants behaved near optimally. Our findings have implications for the design and evaluation of technology for multitasking situations, as consideration should be given to the characteristics of the task, but also to how different users might use technology depending on their individual characteristics and their priorities. PMID:26161851

Preserving privacy whilst maintaining robust epidemiological predictions.

PubMed

Werkman, Marleen; Tildesley, Michael J; Brooks-Pollock, Ellen; Keeling, Matt J

2016-12-01

Mathematical models are invaluable tools for quantifying potential epidemics and devising optimal control strategies in case of an outbreak. State-of-the-art models increasingly require detailed individual farm-based and sensitive data, which may not be available due to either lack of capacity for data collection or privacy concerns. However, in many situations, aggregated data are available for use. In this study, we systematically investigate the accuracy of predictions made by mathematical models initialised with varying data aggregations, using the UK 2001 Foot-and-Mouth Disease Epidemic as a case study. We consider the scenario when the only data available are aggregated into spatial grid cells, and develop a metapopulation model where individual farms in a single subpopulation are assumed to behave uniformly and transmit randomly. We also adapt this standard metapopulation model to capture heterogeneity in farm size and composition, using farm census data. Our results show that homogeneous models based on aggregated data overestimate final epidemic size but can perform well for predicting spatial spread. Recognising heterogeneity in farm sizes improves predictions of the final epidemic size, identifying risk areas, determining the likelihood of epidemic take-off and identifying the optimal control strategy. In conclusion, in cases where individual farm-based data are not available, models can still generate meaningful predictions, although care must be taken in their interpretation and use. Copyright © 2016. Published by Elsevier B.V.

The adaptive nature of eye movements in linguistic tasks: how payoff and architecture shape speed-accuracy trade-offs.

PubMed

Lewis, Richard L; Shvartsman, Michael; Singh, Satinder

2013-07-01

We explore the idea that eye-movement strategies in reading are precisely adapted to the joint constraints of task structure, task payoff, and processing architecture. We present a model of saccadic control that separates a parametric control policy space from a parametric machine architecture, the latter based on a small set of assumptions derived from research on eye movements in reading (Engbert, Nuthmann, Richter, & Kliegl, 2005; Reichle, Warren, & McConnell, 2009). The eye-control model is embedded in a decision architecture (a machine and policy space) that is capable of performing a simple linguistic task integrating information across saccades. Model predictions are derived by jointly optimizing the control of eye movements and task decisions under payoffs that quantitatively express different desired speed-accuracy trade-offs. The model yields distinct eye-movement predictions for the same task under different payoffs, including single-fixation durations, frequency effects, accuracy effects, and list position effects, and their modulation by task payoff. The predictions are compared to-and found to accord with-eye-movement data obtained from human participants performing the same task under the same payoffs, but they are found not to accord as well when the assumptions concerning payoff optimization and processing architecture are varied. These results extend work on rational analysis of oculomotor control and adaptation of reading strategy (Bicknell & Levy, ; McConkie, Rayner, & Wilson, 1973; Norris, 2009; Wotschack, 2009) by providing evidence for adaptation at low levels of saccadic control that is shaped by quantitatively varying task demands and the dynamics of processing architecture. Copyright © 2013 Cognitive Science Society, Inc.

When to throw the switch: The adaptiveness of modifying emotion regulation strategies based on affective and physiological feedback.

PubMed

Birk, Jeffrey L; Bonanno, George A

2016-08-01

Particular emotion regulation (ER) strategies are beneficial in certain contexts, but little is known about the adaptiveness of switching strategies after implementing an initial strategy. Research and theory on regulatory flexibility suggest that people switch strategies dynamically and that internal states provide feedback indicating when switches are appropriate. Frequent switching may predict positive outcomes among people who respond to this feedback. We investigated whether internal feedback (particularly corrugator activity, heart rate, or subjective negative intensity) guides people to switch to an optimal (i.e., distraction) but not nonoptimal (i.e., reappraisal) strategy for regulating strong emotion. We also tested whether switching frequency and responsiveness to internal feedback (RIF) together predict well-being. While attempting to regulate emotion elicited by unpleasant pictures, participants could switch to an optimal (Study 1; reappraisal-to-distraction order; N = 90) or nonoptimal (Study 2; distraction-to-reappraisal order; N = 95) strategy for high-arousal emotion. A RIF score for each emotion measure indexed the relative strength of emotion during the initial phase for trials on which participants later switched strategies. As hypothesized, negative intensity, corrugator activity, and the magnitude of heart rate deceleration during this early phase were higher on switch than maintain trials in Study 1 only. Critically, in Study 1 only, greater switching frequency predicted higher and lower life satisfaction for participants with high and low corrugator RIF, respectively, even after controlling for reappraisal success. Individual differences in RIF may contribute to subjective well-being provided that the direction of strategy switching aligns well with regulatory preferences for high emotion. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Parent-child attachment: meta-analysis of associations with parenting behaviors in middle childhood and adolescence.

PubMed

Koehn, Amanda J; Kerns, Kathryn A

2018-08-01

Maternal sensitivity predicts mother-child attachment in young children, but no meta-analysis has investigated the link between parenting and parent-child attachment in older children. This study examined the relationship between parent-child attachment and multiple components of parenting in children 5-18 years of age. A series of meta-analyses showed that parents of children with more secure attachment are more responsive, more supportive of the child's autonomy, use more behavioral control strategies, and use less harsh control strategies. Parents of children with more avoidant attachment were less responsive and used less behavioral control strategies. Ambivalent attachment was not significantly related to any of the parenting behaviors, and there were not enough studies to reliably test the relationship between disorganized attachment and parenting. There were few significant moderators. The findings inform new areas for future research, as well as family interventions for at-risk youth.

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.

BIOMATERIAL STRATEGIES FOR IMMUNOMODULATION

PubMed Central

Hotaling, Nathan A.; Tang, Li; Irvine, Darrell J.; Babensee, Julia E.

2016-01-01

Strategies to enhance, suppress, or qualitatively shape the immune response are of importance for diverse biomedical applications, such as the development of new vaccines, treatments for autoimmune diseases and allergies, strategies for regenerative medicine, and immunotherapies for cancer. However, the intricate cellular and molecular signals regulating the immune system are major hurdles to predictably manipulating the immune response and developing safe and effective therapies. To meet this challenge, biomaterials are being developed that control how, where, and when immune cells are stimulated in vivo, and that can finely control their differentiation in vitro. We review recent advances in the field of biomaterials for immunomodulation, focusing particularly on designing biomaterials to provide controlled immunostimulation, targeting drugs and vaccines to lymphoid organs, and serving as scaffolds to organize immune cells and emulate lymphoid tissues. These ongoing efforts highlight the many ways in which biomaterials can be brought to bear to engineer the immune system. PMID:26421896

Material Stream Strategy for Lithium and Inorganics (U)

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

Safarik, Douglas Joseph; Dunn, Paul Stanton; Korzekwa, Deniece Rochelle

Design Agency Responsibilities: Manufacturing Support to meet Stockpile Stewardship goals for maintaining the nuclear stockpile through experimental and predictive modeling capability. Development and maintenance of Manufacturing Science expertise to assess material specifications and performance boundaries, and their relationship to processing parameters. Production Engineering Evaluations with competence in design requirements, material specifications, and manufacturing controls. Maintenance and enhancement of Aging Science expertise to support Stockpile Stewardship predictive science capability.

Rapid improvements in emotion regulation predict intensive treatment outcome for patients with bulimia nervosa and purging disorder.

PubMed

MacDonald, Danielle E; Trottier, Kathryn; Olmsted, Marion P

2017-10-01

Rapid and substantial behavior change (RSBC) early in cognitive behavior therapy (CBT) for eating disorders is the strongest known predictor of treatment outcome. Rapid change in other clinically relevant variables may also be important. This study examined whether rapid change in emotion regulation predicted treatment outcomes, beyond the effects of RSBC. Participants were diagnosed with bulimia nervosa or purging disorder (N = 104) and completed ≥6 weeks of CBT-based intensive treatment. Hierarchical regression models were used to test whether rapid change in emotion regulation variables predicted posttreatment outcomes, defined in three ways: (a) binge/purge abstinence; (b) cognitive eating disorder psychopathology; and (c) depression symptoms. Baseline psychopathology and emotion regulation difficulties and RSBC were controlled for. After controlling for baseline variables and RSBC, rapid improvement in access to emotion regulation strategies made significant unique contributions to the prediction of posttreatment binge/purge abstinence, cognitive psychopathology of eating disorders, and depression symptoms. Individuals with eating disorders who rapidly improve their belief that they can effectively modulate negative emotions are more likely to achieve a variety of good treatment outcomes. This supports the formal inclusion of emotion regulation skills early in CBT, and encouraging patient beliefs that these strategies are helpful. © 2017 Wiley Periodicals, Inc.

Web malware spread modelling and optimal control strategies

NASA Astrophysics Data System (ADS)

Liu, Wanping; Zhong, Shouming

2017-02-01

The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.

Web malware spread modelling and optimal control strategies.

PubMed

Liu, Wanping; Zhong, Shouming

2017-02-10

The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice.

A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation

PubMed Central

Chen, Qing; Zhang, Jinxiu; Hu, Ze

2017-01-01

This article investigates the dynamic topology control problem of satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites’ relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT) strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime. PMID:28241474

A Topology Control Strategy with Reliability Assurance for Satellite Cluster Networks in Earth Observation.

PubMed

Chen, Qing; Zhang, Jinxiu; Hu, Ze

2017-02-23

This article investigates the dynamic topology control problemof satellite cluster networks (SCNs) in Earth observation (EO) missions by applying a novel metric of stability for inter-satellite links (ISLs). The properties of the periodicity and predictability of satellites' relative position are involved in the link cost metric which is to give a selection criterion for choosing the most reliable data routing paths. Also, a cooperative work model with reliability is proposed for the situation of emergency EO missions. Based on the link cost metric and the proposed reliability model, a reliability assurance topology control algorithm and its corresponding dynamic topology control (RAT) strategy are established to maximize the stability of data transmission in the SCNs. The SCNs scenario is tested through some numeric simulations of the topology stability of average topology lifetime and average packet loss rate. Simulation results show that the proposed reliable strategy applied in SCNs significantly improves the data transmission performance and prolongs the average topology lifetime.

Web malware spread modelling and optimal control strategies

PubMed Central

Liu, Wanping; Zhong, Shouming

2017-01-01

The popularity of the Web improves the growth of web threats. Formulating mathematical models for accurate prediction of malicious propagation over networks is of great importance. The aim of this paper is to understand the propagation mechanisms of web malware and the impact of human intervention on the spread of malicious hyperlinks. Considering the characteristics of web malware, a new differential epidemic model which extends the traditional SIR model by adding another delitescent compartment is proposed to address the spreading behavior of malicious links over networks. The spreading threshold of the model system is calculated, and the dynamics of the model is theoretically analyzed. Moreover, the optimal control theory is employed to study malware immunization strategies, aiming to keep the total economic loss of security investment and infection loss as low as possible. The existence and uniqueness of the results concerning the optimality system are confirmed. Finally, numerical simulations show that the spread of malware links can be controlled effectively with proper control strategy of specific parameter choice. PMID:28186203

The role of strategies in motor learning

PubMed Central

Taylor, Jordan A.; Ivry, Richard B.

2015-01-01

There has been renewed interest in the role of strategies in sensorimotor learning. The combination of new behavioral methods and computational methods has begun to unravel the interaction between processes related to strategic control and processes related to motor adaptation. These processes may operate on very different error signals. Strategy learning is sensitive to goal-based performance error. In contrast, adaptation is sensitive to prediction errors between the desired and actual consequences of a planned movement. The former guides what the desired movement should be, whereas the latter guides how to implement the desired movement. Whereas traditional approaches have favored serial models in which an initial strategy-based phase gives way to more automatized forms of control, it now seems that strategic and adaptive processes operate with considerable independence throughout learning, although the relative weight given the two processes will shift with changes in performance. As such, skill acquisition involves the synergistic engagement of strategic and adaptive processes. PMID:22329960

Creativity of Biology Students in Online Learning: Case Study of Universitas Terbuka, Indonesia

NASA Astrophysics Data System (ADS)

Diki, Diki

This is a study about the effect of students' attitudes of creativity toward their learning achievement and persistence in an online learning program. The study also investigated if there was an effect of indirect effect of attitudes of creativity toward learning achievement and persistence through learning strategies. There are three learning strategies, which are deep-learning, strategic-learning, and surface-learning. The participants were students of the department of biology and the department of biology teacher training in Universitas Terbuka (UT -- Indonesia Open University), a distance learning university in Indonesia. The researcher sent the questionnaire through email to students who lived throughout Indonesia. There were 102 students participated in the survey. The instruments were rCAB test for value and attitudes toward creativity (Runco, 2012) and approaches and Study Skills Inventory for Students (ASSIST) test (Speth, 2013). There were four research questions (RQ) in this study. The first was if there was a relationship between attitudes of creativity and persistence. The researcher used independent samples t test technique for RQ 1. The second was if there is a relationship between attitudes of creativity and learning outcome. The researcher used multiple regressions for RQ2. The third was if there was an indirect relationship between attitudes of creativity and persistence through learning strategy. The fourth question was if there is an indirect relationship between attitudes of creativity and learning outcome through learning strategy. The researcher used multiple regression for RQ3 and path analysis for RQ 4. Controlling variables were age, income, departments, gender, high school GPA, and daily online activities. The result showed that fun, and being unconventional negatively predicted learning outcomes while high school GPA positively predicted learning outcome. Age and high school GPA negatively predicted persistence while being unconventional positively predicted persistence. Two variables of deep-learning strategy predicted learning outcome. There were indirect relationships between attitudes of creativity and learning outcomes through deep-learning strategy.

Strategies for control of sudden oak death in Humboldt County-informed guidance based on a parameterized epidemiological model

Treesearch

João A. N. Filipe; Richard C. Cobb; David M. Rizzo; Ross K. Meentemeyer; Christopher A. Gilligan

2010-01-01

Landscape- to regional-scale models of plant epidemics are direly needed to predict largescale impacts of disease and assess practicable options for control. While landscape heterogeneity is recognized as a major driver of disease dynamics, epidemiological models are rarely applied to realistic landscape conditions due to computational and data limitations. Here we...

Action Control, Motivated Strategies, and Integrative Motivation as Predictors of Language Learning Affect and the Intention to Continue Learning French

ERIC Educational Resources Information Center

MacIntyre, Peter D.; Blackie, Rebecca A.

2012-01-01

The present study examines the relative ability of variables from three motivational frameworks to predict four non-linguistic outcomes of language learning. The study examines Action Control Theory with its measures of (1) hesitation, (2) volatility and (3) rumination. The study also examined Pintrich's expectancy-value model that uses measures…

Field Test of Wake Steering at an Offshore Wind Farm

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

Fleming, Paul; Annoni, Jennifer; Shah, Jigar J.

In this paper, a field test of wake steering control is presented. The field test is the result of a collaboration between the National Renewable Energy Laboratory (NREL) and Envision Energy, a smart energy management company and turbine manufacturer. In the campaign, an array of turbines within an operating commercial offshore wind farm in China have the normal yaw controller modified to implement wake steering according to a yaw control strategy. The strategy was designed using NREL wind farm models, including a computational fluid dynamics model, SOWFA, for understanding wake dynamics and an engineering model, FLORIS, for yaw control optimization.more » Results indicate that, within the certainty afforded by the data, the wake-steering controller was successful in increasing power capture, by amounts similar to those predicted from the models.« less

Field Test of Wake Steering at an Offshore Wind Farm

DOE PAGES

Fleming, Paul; Annoni, Jennifer; Shah, Jigar J.; ...

2017-02-06

In this paper, a field test of wake steering control is presented. The field test is the result of a collaboration between the National Renewable Energy Laboratory (NREL) and Envision Energy, a smart energy management company and turbine manufacturer. In the campaign, an array of turbines within an operating commercial offshore wind farm in China have the normal yaw controller modified to implement wake steering according to a yaw control strategy. The strategy was designed using NREL wind farm models, including a computational fluid dynamics model, SOWFA, for understanding wake dynamics and an engineering model, FLORIS, for yaw control optimization.more » Results indicate that, within the certainty afforded by the data, the wake-steering controller was successful in increasing power capture, by amounts similar to those predicted from the models.« less

The relation of locus-of-control orientation and task structure to problem-solving performance of sixth-grade student pairs

NASA Astrophysics Data System (ADS)

Main, June Dewey; Budd Rowe, Mary

This study investigated the relationship of locus-of-control orientations and task structure to the science problem-solving performance of 100 same-sex, sixth-grade student pairs. Pairs performed a four-variable problem-solving task, racing cylinders down a ramp in a series of trials to determine the 3 fastest of 18 different cylinders. The task was completed in one of two treatment conditions: the structured condition with moderate cuing and the unstructured condition with minimal cuing. Pairs completed an after-task assessment, predicting the results of proposed cylinder races, to measure the ability to understand and apply task concepts. Overall conclusions were: (1) There was no relationship between locus-of-control orientation and effectiveness of problem-solving strategy; (2) internality was significantly related to higher accuracy on task solutions and on after-task predictions; (3) there was no significant relationship between task structure and effectiveness of problem-solving strategy; (4) solutions to the task were more accurate in the unstructured task condition; (5) internality related to more accurate solutions in the unstructured task condition.

Intelligence rules of hysteresis in the feedforward trajectory control of piezoelectrically-driven nanostagers

NASA Astrophysics Data System (ADS)

Bashash, Saeid; Jalili, Nader

2007-02-01

Piezoelectrically-driven nanostagers have limited performance in a variety of feedforward and feedback positioning applications because of their nonlinear hysteretic response to input voltage. The hysteresis phenomenon is well known for its complex and multi-path behavior. To realize the underlying physics of this phenomenon and to develop an efficient compensation strategy, the intelligence properties of hysteresis with the effects of non-local memories are discussed here. Through performing a set of experiments on a piezoelectrically-driven nanostager with a high resolution capacitive position sensor, it is shown that for the precise prediction of the hysteresis path, certain memory units are required to store the previous hysteresis trajectory data. Based on the experimental observations, a constitutive memory-based mathematical modeling framework is developed and trained for the precise prediction of the hysteresis path for arbitrarily assigned input profiles. Using the inverse hysteresis model, a feedforward control strategy is then developed and implemented on the nanostager to compensate for the ever-present nonlinearity. Experimental results demonstrate that the controller remarkably eliminates the nonlinear effect, if memory units are sufficiently chosen for the inverse model.

Energy efficiency technologies in cement and steel industry

NASA Astrophysics Data System (ADS)

Zanoli, Silvia Maria; Cocchioni, Francesco; Pepe, Crescenzo

2018-02-01

In this paper, Advanced Process Control strategies aimed at energy efficiency achievement and improvement in cement and steel industry are proposed. A flexible and smart control structure constituted by several functional modules and blocks has been developed. The designed control strategy is based on Model Predictive Control techniques, formulated on linear models. Two industrial control solutions have been developed, oriented to energy efficiency and process control improvement in cement industry clinker rotary kilns (clinker production phase) and in steel industry billets reheating furnaces. Tailored customization procedures for the design of ad hoc control systems have been executed, based on the specific needs and specifications of the analysed processes. The installation of the developed controllers on cement and steel plants produced significant benefits in terms of process control which resulted in working closer to the imposed operating limits. With respect to the previous control systems, based on local controllers and/or operators manual conduction, more profitable configurations of the crucial process variables have been provided.

Optimization of Control Strategies for Non-Domiciliated Triatoma dimidiata, Chagas Disease Vector in the Yucatán Peninsula, Mexico

PubMed Central

Barbu, Corentin; Dumonteil, Eric; Gourbière, Sébastien

2009-01-01

Background Chagas disease is the most important vector-borne disease in Latin America. Regional initiatives based on residual insecticide spraying have successfully controlled domiciliated vectors in many regions. Non-domiciliated vectors remain responsible for a significant transmission risk, and their control is now a key challenge for disease control. Methodology/Principal Findings A mathematical model was developed to predict the temporal variations in abundance of non-domiciliated vectors inside houses. Demographic parameters were estimated by fitting the model to two years of field data from the Yucatan peninsula, Mexico. The predictive value of the model was tested on an independent data set before simulations examined the efficacy of control strategies based on residual insecticide spraying, insect screens, and bednets. The model accurately fitted and predicted field data in the absence and presence of insecticide spraying. Pyrethroid spraying was found effective when 50 mg/m2 were applied yearly within a two-month period matching the immigration season. The >80% reduction in bug abundance was not improved by larger doses or more frequent interventions, and it decreased drastically for different timing and lower frequencies of intervention. Alternatively, the use of insect screens consistently reduced bug abundance proportionally to the reduction of the vector immigration rate. Conclusion/Significance Control of non-domiciliated vectors can hardly be achieved by insecticide spraying, because it would require yearly application and an accurate understanding of the temporal pattern of immigration. Insect screens appear to offer an effective and sustainable alternative, which may be part of multi-disease interventions for the integrated control of neglected vector-borne diseases. PMID:19365542

Employee stress management: An examination of adaptive and maladaptive coping strategies on employee health.

PubMed

Holton, M Kim; Barry, Adam E; Chaney, J Don

2015-01-01

Employees commonly report feeling stressed at work. Examine how employees cope with work and personal stress, whether their coping strategies are adaptive (protective to health) or maladaptive (detrimental to health), and if the manner in which employees cope with stress influences perceived stress management. In this cross-sectional study, a random sample of 2,500 full-time university non-student employees (i.e. faculty, salaried professionals, and hourly non-professionals) were surveyed on health related behaviors including stress and coping. Approximately 1,277 completed the survey (51% ). Hierarchical logistic regression was used to assess the ability of adaptive and maladaptive coping strategies to predict self-reported stress management, while controlling for multiple demographic variables. Over half of employees surveyed reported effective stress management. Most frequently used adaptive coping strategies were communication with friend/family member and exercise, while most frequently used maladaptive coping strategies were drinking alcohol and eating more than usual. Both adaptive and maladaptive coping strategies made significant (p < 0.05) contributions to predicting employee's perceived stress management. Only adaptive coping strategies (B = 0.265) predicted whether someone would self-identify as effectively managing stress. Use of maladaptive coping strategies decreased likelihood of self-reporting effective stress management. Actual coping strategies employed may influence employees' perceived stress management. Adaptive coping strategies may be more influential than maladaptive coping strategies on perceived stress management. Results illustrate themes for effective workplace stress management programs. Stress management programs focused on increasing use of adaptive coping may have a greater impact on employee stress management than those focused on decreasing use of maladaptive coping. Coping is not only a reaction to stressful experiences but also a consequence of coping resources. Thereby increasing the availability of resources in the workplace to facilitate the use of adaptive coping strategies is necessary for successful stress management and, ultimately, healthier employees.

The moderating effect of gender on the relationship between coping and suicide risk in a Portuguese community sample of adults.

PubMed

Campos, Rui C; Holden, Ronald R; Costa, Fátima; Oliveira, Ana Rita; Abreu, Marta; Fresca, Natália

2017-02-01

Background and aims(s): The study evaluated the contribution of coping strategies, based on the Toulousiane conceptualization of coping, to the prediction of suicide risk and tested the moderating effect of gender, controlling for depressive symptoms. A two-time data collection design was used. A community sample of 195 adults (91 men and 104 women) ranging in age from 19 to 65 years and living in several Portuguese regions, mostly in Alentejo, participated in this research. Gender, depressive symptoms, control, and withdrawal and conversion significantly predicted suicide risk and gender interacted with control, withdrawal and conversion, and social distraction in the prediction of suicide risk. Coping predicted suicide risk only for women. Results have important implications for assessment and intervention with suicide at-risk individuals. In particular,the evaluation and development of coping skills is indicated as a goal for therapists having suicide at-risk women as clients.

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Cell fate reprogramming by control of intracellular network dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Albert, Reka

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

Effects of walking speed on the step-by-step control of step width.

PubMed

Stimpson, Katy H; Heitkamp, Lauren N; Horne, Joscelyn S; Dean, Jesse C

2018-02-08

Young, healthy adults walking at typical preferred speeds use step-by-step adjustments of step width to appropriately redirect their center of mass motion and ensure mediolateral stability. However, it is presently unclear whether this control strategy is retained when walking at the slower speeds preferred by many clinical populations. We investigated whether the typical stabilization strategy is influenced by walking speed. Twelve young, neurologically intact participants walked on a treadmill at a range of prescribed speeds (0.2-1.2 m/s). The mediolateral stabilization strategy was quantified as the proportion of step width variance predicted by the mechanical state of the pelvis throughout a step (calculated as R 2 magnitude from a multiple linear regression). Our ability to accurately predict the upcoming step width increased over the course of a step. The strength of the relationship between step width and pelvis mechanics at the start of a step was reduced at slower speeds. However, these speed-dependent differences largely disappeared by the end of a step, other than at the slowest walking speed (0.2 m/s). These results suggest that mechanics-dependent adjustments in step width are a consistent component of healthy gait across speeds and contexts. However, slower walking speeds may ease this control by allowing mediolateral repositioning of the swing leg to occur later in a step, thus encouraging slower walking among clinical populations with limited sensorimotor control. Published by Elsevier Ltd.

A distributed model predictive control scheme for leader-follower multi-agent systems

NASA Astrophysics Data System (ADS)

Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco

2018-02-01

In this paper, we present a novel receding horizon control scheme for solving the formation problem of leader-follower configurations. The algorithm is based on set-theoretic ideas and is tuned for agents described by linear time-invariant (LTI) systems subject to input and state constraints. The novelty of the proposed framework relies on the capability to jointly use sequences of one-step controllable sets and polyhedral piecewise state-space partitions in order to online apply the 'better' control action in a distributed receding horizon fashion. Moreover, we prove that the design of both robust positively invariant sets and one-step-ahead controllable regions is achieved in a distributed sense. Simulations and numerical comparisons with respect to centralised and local-based strategies are finally performed on a group of mobile robots to demonstrate the effectiveness of the proposed control strategy.

Nonlinear model predictive control applied to the separation of praziquantel in simulated moving bed chromatography.

PubMed

Andrade Neto, A S; Secchi, A R; Souza, M B; Barreto, A G

2016-10-28

An adaptive nonlinear model predictive control of a simulated moving bed unit for the enantioseparation of praziquantel is presented. A first principle model was applied at the proposed purity control scheme. The main concern about this kind of model in a control framework is in regard to the computational effort to solve it; however, a fast enough solution was achieved. In order to evaluate the controller's performance, several cases were simulated, including external pumps and switching valve malfunctions. The problem of plant-model mismatch was also investigated, and for that reason a parameter estimation step was introduced in the control strategy. In every studied scenario, the controller was able to maintain the purity levels at their set points, which were set to 99% and 98.6% for extract and raffinate, respectively. Additionally, fast responses and smooth actuation were achieved. Copyright © 2016 Elsevier B.V. All rights reserved.

Active Redesign of a Medicaid Care Management Strategy for Greater Return on Investment: Predicting Impactability.

PubMed

DuBard, C Annette; Jackson, Carlos T

2018-04-01

Care management of high-cost/high-needs patients is an increasingly common strategy to reduce health care costs. A variety of targeting methodologies have emerged to identify patients with high historical or predicted health care utilization, but the more pertinent question for program planners is how to identify those who are most likely to benefit from care management intervention. This paper describes the evolution of complex care management targeting strategies in Community Care of North Carolina's (CCNC) work with the statewide non-dual Medicaid population, culminating in the development of an "Impactability Score" that uses administrative data to predict achievable savings. It describes CCNC's pragmatic approach for estimating intervention effects in a historical cohort of 23,455 individuals, using a control population of 14,839 to determine expected spending at an individual level, against which actual spending could be compared. The actual-to-expected spending difference was then used as the dependent variable in a multivariate model to determine the predictive contribution of a multitude of demographic, clinical, and utilization characteristics. The coefficients from this model yielded the information required to build predictive models for prospective use. Model variables related to medication adherence and historical utilization unexplained by disease burden proved to be more important predictors of impactability than any given diagnosis or event, disease profile, or overall costs of care. Comparison of this approach to alternative targeting strategies (emergency department super-utilizers, inpatient super-utilizers, or patients with highest Hierarchical Condition Category risk scores) suggests a 2- to 3-fold higher return on investment using impactability-based targeting.

From self-assessment to frustration, a small step toward autonomy in robotic navigation

PubMed Central

Jauffret, Adrien; Cuperlier, Nicolas; Tarroux, Philippe; Gaussier, Philippe

2013-01-01

Autonomy and self-improvement capabilities are still challenging in the fields of robotics and machine learning. Allowing a robot to autonomously navigate in wide and unknown environments not only requires a repertoire of robust strategies to cope with miscellaneous situations, but also needs mechanisms of self-assessment for guiding learning and for monitoring strategies. Monitoring strategies requires feedbacks on the behavior's quality, from a given fitness system in order to take correct decisions. In this work, we focus on how a second-order controller can be used to (1) manage behaviors according to the situation and (2) seek for human interactions to improve skills. Following an incremental and constructivist approach, we present a generic neural architecture, based on an on-line novelty detection algorithm that may be able to self-evaluate any sensory-motor strategies. This architecture learns contingencies between sensations and actions, giving the expected sensation from the previous perception. Prediction error, coming from surprising events, provides a measure of the quality of the underlying sensory-motor contingencies. We show how a simple second-order controller (emotional system) based on the prediction progress allows the system to regulate its behavior to solve complex navigation tasks and also succeeds in asking for help if it detects dead-lock situations. We propose that this model could be a key structure toward self-assessment and autonomy. We made several experiments that can account for such properties for two different strategies (road following and place cells based navigation) in different situations. PMID:24115931

Anticipating the next meal using meal behavioral profiles: a hybrid model-based stochastic predictive control algorithm for T1DM.

PubMed

Hughes, C S; Patek, S D; Breton, M; Kovatchev, B P

2011-05-01

Automatic control of Type 1 Diabetes Mellitus (T1DM) with subcutaneous (SC) measurement of glucose concentration and subcutaneous (SC) insulin infusion is of great interest within the diabetes technology research community. The main challenge with the so-called "SC-SC" route to control is sensing and actuation delay, which tends to either destabilize the system or inhibit the aggressiveness of the controller in responding to meals and exercise. Model predictive control (MPC) is one strategy for mitigating delay, where optimal insulin infusions can be given in anticipation of future meal disturbances. Unfortunately, exact prior knowledge of meals can only be assured in a clinical environment and uncertainty about when and if meals will arrive could lead to catastrophic outcomes. As a follow-on to our recent paper in the IFAC symposium on Biological and Medical Systems (MCBMS 2009), we develop a control law that can anticipate meals given a probabilistic description of the patient's eating behavior in the form of a random meal (behavioral) profile. Preclinical in silico trials using the oral glucose meal model of Dalla Man et al. show that the control strategy provides a convenient means of accounting for uncertain prior knowledge of meals without compromising patient safety, even in the event that anticipated meals are skipped. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

IMPROVE AND APPLY CHEMICAL MECHANISMS FOR DEVELOPING OZONE CONTROL STRATEGIES

EPA Science Inventory

Air quality models that realistically describe the formation of ozone, air toxics, and other pollutants are needed by EPA and state agencies to predict current and future concentrations of these pollutants and develop ways to decrease their concentrations below harmful levels. ...

Watershed Management Tool for Selection and Spacial Allocation of Non-Point Source Pollution Control Practices

EPA Science Inventory

Distributed-parameter watershed models are often utilized for evaluating the effectiveness of sediment and nutrient abatement strategies through the traditional {calibrate→ validate→ predict} approach. The applicability of the method is limited due to modeling approximations. In ...

A multi-species model to assess the effect of refugia on worm control and anthelmintic resistance in sheep grazing systems.

PubMed

Dobson, R J; Barnes, E H; Tyrrell, K L; Hosking, B C; Larsen, J W A; Besier, R B; Love, S; Rolfe, P F; Bailey, J N

2011-06-01

Develop a computer simulation model that uses daily meteorological data and farm management practices to predict populations of Trichostrongylus colubriformis, Haemonchus contortus and Teladorsagia (Ostertagia) circumcincta and the evolution of anthelmintic resistance within a sheep flock. Use the model to explore if increased refugia, provided by leaving some adult sheep untreated, would delay development of anthelmintic resistance without compromising nematode control. Compare model predictions with field observations from a breeding flock in Armidale, NSW. Simulate the impact of leaving 1-10% of adult sheep untreated in diverse sheep-grazing systems. Predicted populations of Tr. colubriformis and T. circumcincta were less than those observed in the field, attributed to nutritional stress experienced by the sheep during drought and not accounted for by the model. Observed variation in faecal egg counts explained by the model (R(2) ) for these species was 40-50%. The H. contortus populations and R(2) were both low. Leaving some sheep untreated worked best in situations where animals were already grazing or were moved onto pastures with low populations of infective larvae. In those cases, anthelmintic resistance was delayed and nematode control was maintained when 1-4% of adult stock remained untreated. In general, the model predicted that leaving more than 4% of adults untreated did not sufficiently delay the development of anthelmintic resistance to justify the increased production risk from such a strategy. The choice of a drug rotation strategy had an equal or larger effect on nematode control, and selection for resistance, than leaving 1-10% of adults untreated. © 2011 The Authors. Australian Veterinary Journal © 2011 Australian Veterinary Association.

Cognitive niches: an ecological model of strategy selection.

PubMed

Marewski, Julian N; Schooler, Lael J

2011-07-01

How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each strategy a cognitive niche, that is, a limited number of situations in which the strategy can be applied, simplifying strategy selection. To illustrate our proposal, we consider selection in the context of 2 theories: the simple heuristics framework and the ACT-R (adaptive control of thought-rational) architecture of cognition. From the heuristics framework, we adopt the thesis that people make decisions by selecting from a repertoire of simple decision strategies that exploit regularities in the environment and draw on cognitive capacities, such as memory and time perception. ACT-R provides a quantitative theory of how these capacities adapt to the environment. In 14 simulations and 10 experiments, we consider the choice between strategies that operate on the accessibility of memories and those that depend on elaborate knowledge about the world. Based on Internet statistics, our model quantitatively predicts people's familiarity with and knowledge of real-world objects, the distributional characteristics of the associated speed of memory retrieval, and the cognitive niches of classic decision strategies, including those of the fluency, recognition, integration, lexicographic, and sequential-sampling heuristics. In doing so, the model specifies when people will be able to apply different strategies and how accurate, fast, and effortless people's decisions will be.

Internal health locus of control predicts willingness to track health behaviors online and with smartphone applications.

PubMed

Bennett, Brooke L; Goldstein, Carly M; Gathright, Emily C; Hughes, Joel W; Latner, Janet D

2017-12-01

Given rising technology use across all demographic groups, digital interventions offer a potential strategy for increasing access to health information and care. Research is lacking on identifying individual differences that impact willingness to use digital interventions, which may affect patient engagement. Health locus of control, the amount of control an individual believes they have over their own health, may predict willingness to use mobile health (mHealth) applications ('apps') and online trackers. A cross-sectional study (n = 276) was conducted to assess college students' health locus of control beliefs and willingness to use health apps and online trackers. Internal and powerful other health locus of control beliefs predicted willingness to use health apps and online trackers while chance health locus of control beliefs did not. Individuals with internal and powerful other health locus of control beliefs are more willing than those with chance health locus of control beliefs to utilize a form of technology to monitor or change health behaviors. Health locus of control is an easy-to-assess patient characteristic providers can measure to identify which patients are more likely to utilize mHealth apps and online trackers.

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure.

PubMed

Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

2008-11-07

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges.

Understanding climate: A strategy for climate modeling and predictability research, 1985-1995

NASA Technical Reports Server (NTRS)

Thiele, O. (Editor); Schiffer, R. A. (Editor)

1985-01-01

The emphasis of the NASA strategy for climate modeling and predictability research is on the utilization of space technology to understand the processes which control the Earth's climate system and it's sensitivity to natural and man-induced changes and to assess the possibilities for climate prediction on time scales of from about two weeks to several decades. Because the climate is a complex multi-phenomena system, which interacts on a wide range of space and time scales, the diversity of scientific problems addressed requires a hierarchy of models along with the application of modern empirical and statistical techniques which exploit the extensive current and potential future global data sets afforded by space observations. Observing system simulation experiments, exploiting these models and data, will also provide the foundation for the future climate space observing system, e.g., Earth observing system (EOS), 1985; Tropical Rainfall Measuring Mission (TRMM) North, et al. NASA, 1984.

Quantitative analysis and predictive engineering of self-rolling of nanomembranes under anisotropic mismatch strain

NASA Astrophysics Data System (ADS)

Chen, Cheng; Song, Pengfei; Meng, Fanchao; Li, Xiao; Liu, Xinyu; Song, Jun

2017-12-01

The present work presents a quantitative modeling framework for investigating the self-rolling of nanomembranes under different lattice mismatch strain anisotropy. The effect of transverse mismatch strain on the roll-up direction and curvature has been systematically studied employing both analytical modeling and numerical simulations. The bidirectional nature of the self-rolling of nanomembranes and the critical role of transverse strain in affecting the rolling behaviors have been demonstrated. Two fabrication strategies, i.e., third-layer deposition and corner geometry engineering, have been proposed to predictively manipulate the bidirectional rolling competition of strained nanomembranes, so as to achieve controlled, unidirectional roll-up. In particular for the strategy of corner engineering, microfabrication experiments have been performed to showcase its practical application and effectiveness. Our study offers new mechanistic knowledge towards understanding and predictive engineering of self-rolling of nanomembranes with improved roll-up yield.

A model predictive current control of flux-switching permanent magnet machines for torque ripple minimization

NASA Astrophysics Data System (ADS)

Huang, Wentao; Hua, Wei; Yu, Feng

2017-05-01

Due to high airgap flux density generated by magnets and the special double salient structure, the cogging torque of the flux-switching permanent magnet (FSPM) machine is considerable, which limits the further applications. Based on the model predictive current control (MPCC) and the compensation control theory, a compensating-current MPCC (CC-MPCC) scheme is proposed and implemented to counteract the dominated components in cogging torque of an existing three-phase 12/10 FSPM prototyped machine, and thus to alleviate the influence of the cogging torque and improve the smoothness of electromagnetic torque as well as speed, where a comprehensive cost function is designed to evaluate the switching states. The simulated results indicate that the proposed CC-MPCC scheme can suppress the torque ripple significantly and offer satisfactory dynamic performances by comparisons with the conventional MPCC strategy. Finally, experimental results validate both the theoretical and simulated predictions.

Aperiodic Robust Model Predictive Control for Constrained Continuous-Time Nonlinear Systems: An Event-Triggered Approach.

PubMed

Liu, Changxin; Gao, Jian; Li, Huiping; Xu, Demin

2018-05-01

The event-triggered control is a promising solution to cyber-physical systems, such as networked control systems, multiagent systems, and large-scale intelligent systems. In this paper, we propose an event-triggered model predictive control (MPC) scheme for constrained continuous-time nonlinear systems with bounded disturbances. First, a time-varying tightened state constraint is computed to achieve robust constraint satisfaction, and an event-triggered scheduling strategy is designed in the framework of dual-mode MPC. Second, the sufficient conditions for ensuring feasibility and closed-loop robust stability are developed, respectively. We show that robust stability can be ensured and communication load can be reduced with the proposed MPC algorithm. Finally, numerical simulations and comparison studies are performed to verify the theoretical results.

Reflections on the Anopheles gambiae genome sequence, transgenic mosquitoes and the prospect for controlling malaria and other vector borne diseases.

PubMed

Tabachnick, Walter J

2003-09-01

The completion of the Anopheles gambiae Giles genome sequencing project is a milestone toward developing more effective strategies in reducing the impact of malaria and other vector borne diseases. The successes in developing transgenic approaches using mosquitoes have provided another essential new tool for further progress in basic vector genetics and the goal of disease control. The use of transgenic approaches to develop refractory mosquitoes is also possible. The ability to use genome sequence to identify genes, and transgenic approaches to construct refractory mosquitoes, has provided the opportunity that with the future development of an appropriate genetic drive system, refractory transgenes can be released into vector populations leading to nontransmitting mosquitoes. An. gambiae populations incapable of transmitting malaria. This compelling strategy will be very difficult to achieve and will require a broad substantial research program for success. The fundamental information that is required on genome structure, gene function and environmental effects on genetic expression are largely unknown. The ability to predict gene effects on phenotype is rudimentary, particularly in natural populations. As a result, the release of a refractory transgene into natural mosquito populations is imprecise and there is little ability to predict unintended consequences. The new genetic tools at hand provide opportunities to address an array of important issues, many of which can have immediate impact on the effectiveness of a host of strategies to control vector borne disease. Transgenic release approaches represent only one strategy that should be pursued. A balanced research program is required.

To suppress, or not to suppress? That is repression: controlling intrusive thoughts in addictive behaviour.

PubMed

Moss, Antony C; Erskine, James A K; Albery, Ian P; Allen, James Richard; Georgiou, George J

2015-05-01

Research to understand how individuals cope with intrusive negative or threatening thoughts suggests a variety of different cognitive strategies aimed at thought control. In this review, two of these strategies--thought suppression and repressive coping--are discussed in the context of addictive behaviour. Thought suppression involves conscious, volitional attempts to expel a thought from awareness, whereas repressive coping, which involves the avoidance of thoughts without the corresponding conscious intention, appears to be a far more automated process. Whilst there has been an emerging body of research exploring the role of thought suppression in addictive behaviour, there remains a dearth of research which has considered the role of repressive coping in the development of, and recovery from, addiction. Based on a review of the literature, and a discussion of the supposed mechanisms which underpin these strategies for exercising mental control, a conceptual model is proposed which posits a potential common mechanism. This model makes a number of predictions which require exploration in future research to fully understand the cognitive strategies utilised by individuals to control intrusive thoughts related to their addictive behaviour. Copyright © 2015 Elsevier Ltd. All rights reserved.

How physiological and physical processes contribute to the phenology of cyanobacterial blooms in large shallow lakes: A new Euler-Lagrangian coupled model.

PubMed

Feng, Tao; Wang, Chao; Wang, Peifang; Qian, Jin; Wang, Xun

2018-09-01

Cyanobacterial blooms have emerged as one of the most severe ecological problems affecting large and shallow freshwater lakes. To improve our understanding of the factors that influence, and could be used to predict, surface blooms, this study developed a novel Euler-Lagrangian coupled approach combining the Eulerian model with agent-based modelling (ABM). The approach was subsequently verified based on monitoring datasets and MODIS data in a large shallow lake (Lake Taihu, China). The Eulerian model solves the Eulerian variables and physiological parameters, whereas ABM generates the complete life cycle and transport processes of cyanobacterial colonies. This model ensemble performed well in fitting historical data and predicting the dynamics of cyanobacterial biomass, bloom distribution, and area. Based on the calculated physical and physiological characteristics of surface blooms, principal component analysis (PCA) captured the major processes influencing surface bloom formation at different stages (two bloom clusters). Early bloom outbreaks were influenced by physical processes (horizontal transport and vertical turbulence-induced mixing), whereas buoyancy-controlling strategies were essential for mature bloom outbreaks. Canonical correlation analysis (CCA) revealed the combined actions of multiple environment variables on different bloom clusters. The effects of buoyancy-controlling strategies (ISP), vertical turbulence-induced mixing velocity of colony (VMT) and horizontal drift velocity of colony (HDT) were quantitatively compared using scenario simulations in the coupled model. VMT accounted for 52.9% of bloom formations and maintained blooms over long periods, thus demonstrating the importance of wind-induced turbulence in shallow lakes. In comparison, HDT and buoyancy controlling strategies influenced blooms at different stages. In conclusion, the approach developed here presents a promising tool for understanding the processes of onshore/offshore algal blooms formation and subsequent predicting. Copyright © 2018 Elsevier Ltd. All rights reserved.

A Hybrid Model for Predicting the Prevalence of Schistosomiasis in Humans of Qianjiang City, China

PubMed Central

Wang, Ying; Lu, Zhouqin; Tian, Lihong; Tan, Li; Shi, Yun; Nie, Shaofa; Liu, Li

2014-01-01

Backgrounds/Objective Schistosomiasis is still a major public health problem in China, despite the fact that the government has implemented a series of strategies to prevent and control the spread of the parasitic disease. Advanced warning and reliable forecasting can help policymakers to adjust and implement strategies more effectively, which will lead to the control and elimination of schistosomiasis. Our aim is to explore the application of a hybrid forecasting model to track the trends of the prevalence of schistosomiasis in humans, which provides a methodological basis for predicting and detecting schistosomiasis infection in endemic areas. Methods A hybrid approach combining the autoregressive integrated moving average (ARIMA) model and the nonlinear autoregressive neural network (NARNN) model to forecast the prevalence of schistosomiasis in the future four years. Forecasting performance was compared between the hybrid ARIMA-NARNN model, and the single ARIMA or the single NARNN model. Results The modelling mean square error (MSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the ARIMA-NARNN model was 0.1869×10−4, 0.0029, 0.0419 with a corresponding testing error of 0.9375×10−4, 0.0081, 0.9064, respectively. These error values generated with the hybrid model were all lower than those obtained from the single ARIMA or NARNN model. The forecasting values were 0.75%, 0.80%, 0.76% and 0.77% in the future four years, which demonstrated a no-downward trend. Conclusion The hybrid model has high quality prediction accuracy in the prevalence of schistosomiasis, which provides a methodological basis for future schistosomiasis monitoring and control strategies in the study area. It is worth attempting to utilize the hybrid detection scheme in other schistosomiasis-endemic areas including other infectious diseases. PMID:25119882

A Discrete-Time Average Model Based Predictive Control for Quasi-Z-Source Inverter

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

Liu, Yushan; Abu-Rub, Haitham; Xue, Yaosuo

A discrete-time average model-based predictive control (DTA-MPC) is proposed for a quasi-Z-source inverter (qZSI). As a single-stage inverter topology, the qZSI regulates the dc-link voltage and the ac output voltage through the shoot-through (ST) duty cycle and the modulation index. Several feedback strategies have been dedicated to produce these two control variables, among which the most popular are the proportional–integral (PI)-based control and the conventional model-predictive control (MPC). However, in the former, there are tradeoffs between fast response and stability; the latter is robust, but at the cost of high calculation burden and variable switching frequency. Moreover, they require anmore » elaborated design or fine tuning of controller parameters. The proposed DTA-MPC predicts future behaviors of the ST duty cycle and modulation signals, based on the established discrete-time average model of the quasi-Z-source (qZS) inductor current, the qZS capacitor voltage, and load currents. The prediction actions are applied to the qZSI modulator in the next sampling instant, without the need of other controller parameters’ design. A constant switching frequency and significantly reduced computations are achieved with high performance. Transient responses and steady-state accuracy of the qZSI system under the proposed DTA-MPC are investigated and compared with the PI-based control and the conventional MPC. Simulation and experimental results verify the effectiveness of the proposed approach for the qZSI.« less

A Discrete-Time Average Model Based Predictive Control for Quasi-Z-Source Inverter

DOE PAGES

Liu, Yushan; Abu-Rub, Haitham; Xue, Yaosuo; ...

2017-12-25

A discrete-time average model-based predictive control (DTA-MPC) is proposed for a quasi-Z-source inverter (qZSI). As a single-stage inverter topology, the qZSI regulates the dc-link voltage and the ac output voltage through the shoot-through (ST) duty cycle and the modulation index. Several feedback strategies have been dedicated to produce these two control variables, among which the most popular are the proportional–integral (PI)-based control and the conventional model-predictive control (MPC). However, in the former, there are tradeoffs between fast response and stability; the latter is robust, but at the cost of high calculation burden and variable switching frequency. Moreover, they require anmore » elaborated design or fine tuning of controller parameters. The proposed DTA-MPC predicts future behaviors of the ST duty cycle and modulation signals, based on the established discrete-time average model of the quasi-Z-source (qZS) inductor current, the qZS capacitor voltage, and load currents. The prediction actions are applied to the qZSI modulator in the next sampling instant, without the need of other controller parameters’ design. A constant switching frequency and significantly reduced computations are achieved with high performance. Transient responses and steady-state accuracy of the qZSI system under the proposed DTA-MPC are investigated and compared with the PI-based control and the conventional MPC. Simulation and experimental results verify the effectiveness of the proposed approach for the qZSI.« less

On-Line Control of Glucose Concentration in High-Yielding Mammalian Cell Cultures Enabled Through Oxygen Transfer Rate Measurements.

PubMed

Goldrick, Stephen; Lee, Kenneth; Spencer, Christopher; Holmes, William; Kuiper, Marcel; Turner, Richard; Farid, Suzanne S

2018-04-01

Glucose control is vital to ensure consistent growth and protein production in mammalian cell cultures. The typical fed-batch glucose control strategy involving bolus glucose additions based on infrequent off-line daily samples results in cells experiencing significant glucose concentration fluctuations that can influence product quality and growth. This study proposes an on-line method to control and manipulate glucose utilizing readily available process measurements. The method generates a correlation between the cumulative oxygen transfer rate and the cumulative glucose consumed. This correlation generates an on-line prediction of glucose that has been successfully incorporated into a control algorithm manipulating the glucose feed-rate. This advanced process control (APC) strategy enables the glucose concentration to be maintained at an adjustable set-point and has been found to significantly reduce the deviation in glucose concentration in comparison to conventional operation. This method has been validated to produce various therapeutic proteins across cell lines with different glucose consumption demands and is successfully demonstrated on micro (15 mL), laboratory (7 L), and pilot (50 L) scale systems. This novel APC strategy is simple to implement and offers the potential to significantly enhance the glucose control strategy for scales spanning micro-scale systems through to full scale industrial bioreactors. © 2018 The Authors. Biotechnology Journal Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Using Machine Learning to Predict Swine Movements within a Regional Program to Improve Control of Infectious Diseases in the US.

PubMed

Valdes-Donoso, Pablo; VanderWaal, Kimberly; Jarvis, Lovell S; Wayne, Spencer R; Perez, Andres M

2017-01-01

Between-farm animal movement is one of the most important factors influencing the spread of infectious diseases in food animals, including in the US swine industry. Understanding the structural network of contacts in a food animal industry is prerequisite to planning for efficient production strategies and for effective disease control measures. Unfortunately, data regarding between-farm animal movements in the US are not systematically collected and thus, such information is often unavailable. In this paper, we develop a procedure to replicate the structure of a network, making use of partial data available, and subsequently use the model developed to predict animal movements among sites in 34 Minnesota counties. First, we summarized two networks of swine producing facilities in Minnesota, then we used a machine learning technique referred to as random forest, an ensemble of independent classification trees, to estimate the probability of pig movements between farms and/or markets sites located in two counties in Minnesota. The model was calibrated and tested by comparing predicted data and observed data in those two counties for which data were available. Finally, the model was used to predict animal movements in sites located across 34 Minnesota counties. Variables that were important in predicting pig movements included between-site distance, ownership, and production type of the sending and receiving farms and/or markets. Using a weighted-kernel approach to describe spatial variation in the centrality measures of the predicted network, we showed that the south-central region of the study area exhibited high aggregation of predicted pig movements. Our results show an overlap with the distribution of outbreaks of porcine reproductive and respiratory syndrome, which is believed to be transmitted, at least in part, though animal movements. While the correspondence of movements and disease is not a causal test, it suggests that the predicted network may approximate actual movements. Accordingly, the predictions provided here might help to design and implement control strategies in the region. Additionally, the methodology here may be used to estimate contact networks for other livestock systems when only incomplete information regarding animal movements is available.

Adaptive fuzzy predictive sliding control of uncertain nonlinear systems with bound-known input delay.

PubMed

Khazaee, Mostafa; Markazi, Amir H D; Omidi, Ehsan

2015-11-01

In this paper, a new Adaptive Fuzzy Predictive Sliding Mode Control (AFP-SMC) is presented for nonlinear systems with uncertain dynamics and unknown input delay. The control unit consists of a fuzzy inference system to approximate the ideal linearization control, together with a switching strategy to compensate for the estimation errors. Also, an adaptive fuzzy predictor is used to estimate the future values of the system states to compensate for the time delay. The adaptation laws are used to tune the controller and predictor parameters, which guarantee the stability based on a Lyapunov-Krasovskii functional. To evaluate the method effectiveness, the simulation and experiment on an overhead crane system are presented. According to the obtained results, AFP-SMC can effectively control the uncertain nonlinear systems, subject to input delays of known bound. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Effects of external loads on balance control during upright stance: experimental results and model-based predictions.

PubMed

Qu, Xingda; Nussbaum, Maury A

2009-01-01

The purpose of this study was to identify the effects of external loads on balance control during upright stance, and to examine the ability of a new balance control model to predict these effects. External loads were applied to 12 young, healthy participants, and effects on balance control were characterized by center-of-pressure (COP) based measures. Several loading conditions were studied, involving combinations of load mass (10% and 20% of individual body mass) and height (at or 15% of stature above the whole-body COM). A balance control model based on an optimal control strategy was used to predict COP time series. It was assumed that a given individual would adopt the same neural optimal control mechanisms, identified in a no-load condition, under diverse external loading conditions. With the application of external loads, COP mean velocity in the anterior-posterior direction and RMS distance in the medial-lateral direction increased 8.1% and 10.4%, respectively. Predicted COP mean velocity and RMS distance in the anterior-posterior direction also increased with external loading, by 11.1% and 2.9%, respectively. Both experimental COP data and model-based predictions provided the same general conclusion, that application of larger external loads and loads more superior to the whole body center of mass lead to less effective postural control and perhaps a greater risk of loss of balance or falls. Thus, it can be concluded that the assumption about consistency in control mechanisms was partially supported, and it is the mechanical changes induced by external loads that primarily affect balance control.

[Transmission dynamic model for echinococcosis granulosus: establishment and application].

PubMed

Yang, Shi-Jie; Wu, Wei-Ping

2009-06-01

A dynamic model of disease can be used to quantitatively describe the pattern and characteristics of disease transmission, predict the disease status and evaluate the efficacy of control strategy. This review summarizes the basic transmission dynamic models of echinococcosis granulosus and their application.

Got the "Kids Who Blurt Out" Blues?

ERIC Educational Resources Information Center

Charney, Ruth Sidney

1998-01-01

Strategies for curbing disruptions in the classroom include setting expectations, naming and defining behaviors students must learn, modeling appropriate and alternative behavior, setting up routines showing that self-control is important, settling on predictable consequences for blurting out, having children start over if communication breaks…

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

Development and implementation of a dynamic TES dispatch control component in a PV-CSP techno-economic performance modelling tool

NASA Astrophysics Data System (ADS)

Hansson, Linus; Guédez, Rafael; Larchet, Kevin; Laumert, Bjorn

2017-06-01

The dispatchability offered by thermal energy storage (TES) in concentrated solar power (CSP) and solar hybrid plants based on such technology presents the most important difference compared to power generation based only on photovoltaics (PV). This has also been one reason for recent hybridization efforts of the two technologies and the creation of Power Purchase Agreement (PPA) payment schemes based on offering higher payment multiples during daily hours of higher (peak or priority) demand. Recent studies involving plant-level thermal energy storage control strategies are however to a large extent based on pre-determined approaches, thereby not taking into account the actual dynamics of thermal energy storage system operation. In this study, the implementation of a dynamic dispatch strategy in the form of a TRNSYS controller for hybrid PV-CSP plants in the power-plant modelling tool DYESOPT is presented. In doing this it was attempted to gauge the benefits of incorporating a day-ahead approach to dispatch control compared to a fully pre-determined approach determining hourly dispatch only once prior to annual simulation. By implementing a dynamic strategy, it was found possible to enhance technical and economic performance for CSP-only plants designed for peaking operation and featuring low values of the solar multiple. This was achieved by enhancing dispatch control, primarily by taking storage levels at the beginning of every simulation day into account. The sequential prediction of the TES level could therefore be improved, notably for evaluated plants without integrated PV, for which the predicted storage levels deviated less than when PV was present in the design. While also featuring dispatch performance gains, optimal plant configurations for hybrid PV-CSP was found to present a trade-off in economic performance in the form of an increase in break-even electricity price when using the dynamic strategy which was offset to some extent by a reduction in upfront investment cost. An increase in turbine starts for the implemented strategy however highlights that this is where further improvements can be made.

An assigned responsibility system for robotic teleoperation control.

PubMed

Small, Nicolas; Lee, Kevin; Mann, Graham

2018-01-01

This paper proposes an architecture that explores a gap in the spectrum of existing strategies for robot control mode switching in adjustable autonomy. In situations where the environment is reasonably known and/or predictable, pre-planning these control changes could relieve robot operators of the additional task of deciding when and how to switch. Such a strategy provides a clear division of labour between the automation and the human operator(s) before the job even begins, allowing for individual responsibilities to be known ahead of time, limiting confusion and allowing rest breaks to be planned. Assigned Responsibility is a new form of adjustable autonomy-based teleoperation that allows the selective inclusion of automated control elements at key stages of a robot operation plan's execution. Progression through these stages is controlled by automatic goal accomplishment tracking. An implementation is evaluated through engineering tests and a usability study, demonstrating the viability of this approach and offering insight into its potential applications.

H∞ control for switched fuzzy systems via dynamic output feedback: Hybrid and switched approaches

NASA Astrophysics Data System (ADS)

Xiang, Weiming; Xiao, Jian; Iqbal, Muhammad Naveed

2013-06-01

Fuzzy T-S model has been proven to be a practical and effective way to deal with the analysis and synthesis problems for complex nonlinear systems. As for switched nonlinear system, describing its subsystems as fuzzy T-S models, namely switched fuzzy system, naturally is an alternative method to conventional control approaches. In this paper, the H∞ control problem for a class of switched fuzzy systems is addressed. Hybrid and switched design approaches are proposed with different availability of switching signal information at switching instant. The hybrid control strategy includes two parts: fuzzy controllers for subsystems and state updating controller at switching instant, and the switched control strategy contains the controllers for subsystems. It is demonstrated that the conservativeness is reduced by introducing the state updating behavior but its cost is an online prediction of switching signal. Numerical examples are given to illustrate the effectiveness of proposed approaches and compare the conservativeness of two approaches.

Output-feedback control of combined sewer networks through receding horizon control with moving horizon estimation

NASA Astrophysics Data System (ADS)

Joseph-Duran, Bernat; Ocampo-Martinez, Carlos; Cembrano, Gabriela

2015-10-01

An output-feedback control strategy for pollution mitigation in combined sewer networks is presented. The proposed strategy provides means to apply model-based predictive control to large-scale sewer networks, in-spite of the lack of measurements at most of the network sewers. In previous works, the authors presented a hybrid linear control-oriented model for sewer networks together with the formulation of Optimal Control Problems (OCP) and State Estimation Problems (SEP). By iteratively solving these problems, preliminary Receding Horizon Control with Moving Horizon Estimation (RHC/MHE) results, based on flow measurements, were also obtained. In this work, the RHC/MHE algorithm has been extended to take into account both flow and water level measurements and the resulting control loop has been extensively simulated to assess the system performance according different measurement availability scenarios and rain events. All simulations have been carried out using a detailed physically based model of a real case-study network as virtual reality.

Perceived Control and Social Activity in Midlife and Older Age: A Reciprocal Association? Findings From the German Ageing Survey.

PubMed

Curtis, Rachel G; Huxhold, Oliver; Windsor, Tim D

2018-06-14

Perceived control may promote social activity in older adults because individuals with greater perceived control have greater confidence in their ability to achieve outcomes and are more likely to choose difficult activities, show persistence, and employ strategies to overcome challenges. Cross-sectional research has linked perceived control with social activity in life span and older adult samples but provides little insight into the direction of influence. We examined reciprocal associations between perceived control and social activity in order to establish temporal sequencing, which is one prerequisite for determining potential causation. Participants were 14,126 midlife and older adults from the German Ageing Survey. Using cross-lagged autoregressive modeling with age as the time metric (40-87 years), we examined reciprocal 3-year lagged associations between perceived control and social activity, while controlling for concurrent associations. Perceived control significantly predicted social activity 3 years later. Reciprocally, social activity significantly predicted perceived control 3 years later. The influence of perceived control on social activity was greater than the influence of social activity on perceived control. The finding that perceived control significantly predicts future social activity has potential implications for developing interventions aimed at promoting social activity in midlife and older adults.

The Gaze-Cueing Effect in the United States and Japan: Influence of Cultural Differences in Cognitive Strategies on Control of Attention

PubMed Central

Takao, Saki; Yamani, Yusuke; Ariga, Atsunori

2018-01-01

The direction of gaze automatically and exogenously guides visual spatial attention, a phenomenon termed as the gaze-cueing effect. Although this effect arises when the duration of stimulus onset asynchrony (SOA) between a non-predictive gaze cue and the target is relatively long, no empirical research has examined the factors underlying this extended cueing effect. Two experiments compared the gaze-cueing effect at longer SOAs (700 ms) in Japanese and American participants. Cross-cultural studies on cognition suggest that Westerners tend to use a context-independent analytical strategy to process visual environments, whereas Asians use a context-dependent holistic approach. We hypothesized that Japanese participants would not demonstrate the gaze-cueing effect at longer SOAs because they are more sensitive to contextual information, such as the knowledge that the direction of a gaze is not predictive. Furthermore, we hypothesized that American participants would demonstrate the gaze-cueing effect at the long SOAs because they tend to follow gaze direction whether it is predictive or not. In Experiment 1, American participants demonstrated the gaze-cueing effect at the long SOA, indicating that their attention was driven by the central non-predictive gaze direction regardless of the SOAs. In Experiment 2, Japanese participants demonstrated no gaze-cueing effect at the long SOA, suggesting that the Japanese participants exercised voluntary control of their attention, which inhibited the gaze-cueing effect with the long SOA. Our findings suggest that the control of visual spatial attention elicited by social stimuli systematically differs between American and Japanese individuals. PMID:29379457

The Gaze-Cueing Effect in the United States and Japan: Influence of Cultural Differences in Cognitive Strategies on Control of Attention.

PubMed

Takao, Saki; Yamani, Yusuke; Ariga, Atsunori

2017-01-01

The direction of gaze automatically and exogenously guides visual spatial attention, a phenomenon termed as the gaze-cueing effect . Although this effect arises when the duration of stimulus onset asynchrony (SOA) between a non-predictive gaze cue and the target is relatively long, no empirical research has examined the factors underlying this extended cueing effect. Two experiments compared the gaze-cueing effect at longer SOAs (700 ms) in Japanese and American participants. Cross-cultural studies on cognition suggest that Westerners tend to use a context-independent analytical strategy to process visual environments, whereas Asians use a context-dependent holistic approach. We hypothesized that Japanese participants would not demonstrate the gaze-cueing effect at longer SOAs because they are more sensitive to contextual information, such as the knowledge that the direction of a gaze is not predictive. Furthermore, we hypothesized that American participants would demonstrate the gaze-cueing effect at the long SOAs because they tend to follow gaze direction whether it is predictive or not. In Experiment 1, American participants demonstrated the gaze-cueing effect at the long SOA, indicating that their attention was driven by the central non-predictive gaze direction regardless of the SOAs. In Experiment 2, Japanese participants demonstrated no gaze-cueing effect at the long SOA, suggesting that the Japanese participants exercised voluntary control of their attention, which inhibited the gaze-cueing effect with the long SOA. Our findings suggest that the control of visual spatial attention elicited by social stimuli systematically differs between American and Japanese individuals.

Parasite control in the age of drug resistance and changing agricultural practices.

PubMed

Molento, Marcelo Beltrão

2009-08-07

The benefits of using antiparasitic drugs in farm animals are unquestionable. However, despite anthelmintic use as the predominant control strategy, extreme parasite infection cases are appearing in sheep and goat production; these impact productivity and have show mortality rates reaching pre-drug use levels. This was a predictable situation resulting from the loss of efficacy by all available products, particularly when some products were used as the sole intervention. The concepts of agroecology and holistic agriculture, which advocate the use of integrated management strategies, such as target selected treatment, herbal medicine, and the application of other parasite control alternatives, are not completely new, but are undergoing a resurgence because of their more sustainable appeal. The objective of this review article is to examine the problem of parasite control in the face of parasite drug resistance and to outline some strategies that may be used in parasite control programmes. Before they are accepted and recommended by the WAAVP, agroecological methods such as those listed above and described in detail herein should be validated based on scientific evidence of their efficacy for parasite control and should be tested for both host and environmental safety.

Simulated effect of pig-population density on epidemic size and choice of control strategy for classical swine fever epidemics in The Netherlands.

PubMed

Mangen, M-J J; Nielen, M; Burrell, A M

2002-12-18

We examined the importance of pig-population density in the area of an outbreak of classical swine fever (CSF) for the spread of the infection and the choice of control measures. A spatial, stochastic, dynamic epidemiological simulation model linked to a sector-level market-and-trade model for The Netherlands were used. Outbreaks in sparsely and densely populated areas were compared under four different control strategies and with two alternative trade assumptions. The obligatory control strategy required by current EU legislation was predicted to be enough to eradicate an epidemic starting in an area with sparse pig population. By contrast, additional control measures would be necessary if the outbreak began in an area with high pig density. The economic consequences of using preventive slaughter rather than emergency vaccination as an additional control measure depended strongly on the reactions of trading partners. Reducing the number of animal movements significantly reduced the size and length of epidemics in areas with high pig density. The phenomenon of carrier piglets was included in the model with realistic probabilities of infection by this route, but it made a negligible contribution to the spread of the infection.

Method for Phenotypic Detection of Extended-Spectrum Beta-Lactamases in Enterobacter Species in the Routine Clinical Setting ▿

PubMed Central

Stuart, James Cohen; Diederen, Bram; al Naiemi, Nashwan; Fluit, Ad; Arents, Niek; Thijsen, Steven; Vlaminckx, Bart; Mouton, Johan W.; Leverstein-van Hall, Maurine

2011-01-01

In 271 Enterobacter blood culture isolates from 12 hospitals, extended-spectrum beta-lactamase (ESBL) prevalence varied between 0% and 30% per hospital. High prevalence was associated with dissemination, indicating the potential relevance of infection control measures. Screening with cefepime or Vitek 2, followed by a cefepime/cefepime-clavulanate Etest, was an accurate strategy for ESBL detection in Enterobacter isolates (positive predictive value, 100%; negative predictive value, 99%). PMID:21562100

Predictive Coding Strategies for Invariant Object Recognition and Volitional Motion Control in Neuromorphic Agents

DTIC Science & Technology

2015-09-02

human behavior. In this project, we hypothesized that visual memory of past motion trajectories may be used for selecting future behavior. In other...34Decoding sequence of actions using fMRI ", Society for Neuroscience Annual Meeting, San Diego, CA, USA, Nov 9-13 2013 (only abstract) 3. Hansol Choi, Dae...Shik Kim, "Planning as inference in a Hierarchical Predictive Memory ", Proceedings of International Conference on Neural Information Processing

Effects of an intervention in active strategies for text comprehension and recall.

PubMed

Elosúa, M Rosa; García-Madruga, Juan A; Gutiérrez, Francisco; Luque, Juan Luis; Gárate, Milagros

2002-11-01

The aim of this study was to investigate the effects of an intervention program to promote active text-processing strategies (main-idea identification and summarization) at two developmental levels (12- and 16-year-olds). The independent variables were training condition (experimental and control) and school level (7th and 10th grades). Several measures were taken as dependent variables: reading span, reading time, construction of macrostructure, and structural recall. The hypothesis claimed that training would increase comprehension and recall significantly. Furthermore, as a result of the training program, a reduction in developmental differences in the experimental groups at posttest was also expected. Results supported the predictions, showing a significant improvement in the experimental groups' reading comprehension and recall. These results are discussed in terms of the importance of active and self-controlled strategies for text comprehension and recall.

Simulating the Historical Process To Create Laboratory Exercises That Teach Research Methods.

ERIC Educational Resources Information Center

Alcock, James

1994-01-01

Explains how controlling student access to data can be used as a strategy enabling students to take the role of a research geologist. Students develop models based on limited data and conduct field tests by comparing their predictions with the additional data. (DDR)

A Simple Approach To Assessing Copper Pitting Corrosion Tendenices and Developing Control Strategies

EPA Science Inventory

The objective of this research was to assess the effectiveness of a simple pipe loop system and protocol to predict localized corrosion, and to assess treatment alternatives for a drinking water that has been associated with customer complaints of pinhole leaks.

Health Care Psychology: Prospects for the Well-Being of Children.

ERIC Educational Resources Information Center

Wright, Logan

1979-01-01

Health care psychology is distinguished from traditional child psychology in that it emphasizes clinical application and is concerned with primary mental health care. Diagnosis, classification, prediction, and treatment and control strategies in the field offer definite solutions to problems such as tracheotomy addiction, encopresis, psychogenic…

Comparative Investigation on Tool Wear during End Milling of AISI H13 Steel with Different Tool Path Strategies

NASA Astrophysics Data System (ADS)

Adesta, Erry Yulian T.; Riza, Muhammad; Avicena

2018-03-01

Tool wear prediction plays a significant role in machining industry for proper planning and control machining parameters and optimization of cutting conditions. This paper aims to investigate the effect of tool path strategies that are contour-in and zigzag tool path strategies applied on tool wear during pocket milling process. The experiments were carried out on CNC vertical machining centre by involving PVD coated carbide inserts. Cutting speed, feed rate and depth of cut were set to vary. In an experiment with three factors at three levels, Response Surface Method (RSM) design of experiment with a standard called Central Composite Design (CCD) was employed. Results obtained indicate that tool wear increases significantly at higher range of feed per tooth compared to cutting speed and depth of cut. This result of this experimental work is then proven statistically by developing empirical model. The prediction model for the response variable of tool wear for contour-in strategy developed in this research shows a good agreement with experimental work.

Optimal Control of Distributed Energy Resources using Model Predictive Control

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

Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.

2012-07-22

In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizingmore » costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.« less

PSO-MISMO modeling strategy for multistep-ahead time series prediction.

PubMed

Bao, Yukun; Xiong, Tao; Hu, Zhongyi

2014-05-01

Multistep-ahead time series prediction is one of the most challenging research topics in the field of time series modeling and prediction, and is continually under research. Recently, the multiple-input several multiple-outputs (MISMO) modeling strategy has been proposed as a promising alternative for multistep-ahead time series prediction, exhibiting advantages compared with the two currently dominating strategies, the iterated and the direct strategies. Built on the established MISMO strategy, this paper proposes a particle swarm optimization (PSO)-based MISMO modeling strategy, which is capable of determining the number of sub-models in a self-adaptive mode, with varying prediction horizons. Rather than deriving crisp divides with equal-size s prediction horizons from the established MISMO, the proposed PSO-MISMO strategy, implemented with neural networks, employs a heuristic to create flexible divides with varying sizes of prediction horizons and to generate corresponding sub-models, providing considerable flexibility in model construction, which has been validated with simulated and real datasets.

Efficient Strategies for Predictive Cell-Level Control of Lithium-Ion Batteries

NASA Astrophysics Data System (ADS)

Xavier, Marcelo A.

This dissertation introduces a set of state-space based model predictive control (MPC) algorithms tailored to a non-zero feedthrough term to account for the ohmic resistance that is inherent to the battery dynamics. MPC is herein applied to the problem of regulating cell-level measures of performance for lithium-ion batteries; the control methodologies are used first to compute a fast charging profile that respects input, output, and state constraints, i.e., input current, terminal voltage, and state of charge for an equivalent circuit model of the battery cell, and extended later to a linearized physics-based reduced-order model. The novelty of this work can summarized as follows: (1) the MPC variants are employed to a physics based reduce-order model in order to make use of the available set of internal electrochemical variables and mitigate internal mechanisms of cell degradation. (e.g., lithium plating); (2) we developed a dual-mode MPC closed-loop paradigm that suits the battery control problem with the objective of reducing computational effort by solving simpler optimization routines and guaranteeing stability; and finally (3) we developed a completely new approach of the use of a predictive control strategy where MPC is employed as a "smart sensor" for power estimation. Results are presented that show the comparative performance of the MPC algorithms for both EMC and PBROM These results highlight that dual-mode MPC can deliver optimal input current profiles by using a shorter horizon while still guaranteeing stability. Additionally, rigorous mathematical developments are presented for the development of the MPC algorithms. The use of MPC as a "smart sensor" presents it self as an appealing method for power estimation, since MPC permits a fully dynamic input profile that is able to achieve performance right at the proper constraint boundaries. Therefore, MPC is expected to produce accurate power limits for each computed sample time when compared to the Bisection method [1] which assumes constant input values over the prediction interval.

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

Path-following in model predictive rollover prevention using front steering and braking

NASA Astrophysics Data System (ADS)

Ghazali, Mohammad; Durali, Mohammad; Salarieh, Hassan

2017-01-01

In this paper vehicle path-following in the presence of rollover risk is investigated. Vehicles with high centre of mass are prone to roll instability. Untripped rollover risk is increased in high centre of gravity vehicles and high-friction road condition. Researches introduce strategies to handle the short-duration rollover condition. In these researches, however, trajectory tracking is affected and not thoroughly investigated. This paper puts stress on tracking error from rollover prevention. A lower level model predictive front steering controller is adopted to deal with rollover and tracking error as a priority sequence. A brake control is included in lower level controller which directly obeys an upper level controller (ULC) command. The ULC manages vehicle speed regarding primarily tracking error. Simulation results show that the proposed control framework maintains roll stability while tracking error is confined to predefined error limit.

Multistep-Ahead Air Passengers Traffic Prediction with Hybrid ARIMA-SVMs Models

PubMed Central

Ming, Wei; Xiong, Tao

2014-01-01

The hybrid ARIMA-SVMs prediction models have been established recently, which take advantage of the unique strength of ARIMA and SVMs models in linear and nonlinear modeling, respectively. Built upon this hybrid ARIMA-SVMs models alike, this study goes further to extend them into the case of multistep-ahead prediction for air passengers traffic with the two most commonly used multistep-ahead prediction strategies, that is, iterated strategy and direct strategy. Additionally, the effectiveness of data preprocessing approaches, such as deseasonalization and detrending, is investigated and proofed along with the two strategies. Real data sets including four selected airlines' monthly series were collected to justify the effectiveness of the proposed approach. Empirical results demonstrate that the direct strategy performs better than iterative one in long term prediction case while iterative one performs better in the case of short term prediction. Furthermore, both deseasonalization and detrending can significantly improve the prediction accuracy for both strategies, indicating the necessity of data preprocessing. As such, this study contributes as a full reference to the planners from air transportation industries on how to tackle multistep-ahead prediction tasks in the implementation of either prediction strategy. PMID:24723814

Controlling in situ crystallization of pharmaceutical particles within the spray dryer.

PubMed

Woo, Meng Wai; Lee, May Ginn; Shakiba, Soroush; Mansouri, Shahnaz

2017-11-01

Simultaneous solidification and in situ crystallization (or partial crystallization) of droplets within the drying chamber are commonly encountered in the spray drying of pharmaceuticals. The crystallinity developed will determine the functionality of the powder and its stability during storage. This review discusses strategies that can be used to control the in situ crystallization process. Areas covered: The premise of the strategies discussed focuses on the manipulation of the droplet drying rate relative to the timescale of crystallization. This can be undertaken by the control of the spray drying operation, by the use of volatile materials and by the inclusion of additives. Several predictive approaches for in situ crystallization control and new spray dryer configuration strategies are further discussed. Expert opinion: Most reports, hitherto, have focused on the crystallinity of the spray dried material or the development of crystallinity during storage. More mechanistic understanding of the in situ crystallization process during spray drying is required to guide product formulation trials. The key challenge will be in adapting the mechanistic approach to the myriad possible formulations in the pharmaceutical industry.

Perceived control over personal goals in Russian and American college students.

PubMed

Savina, Elena

2013-01-01

This study investigated cultural variations in perceived control over personal goals in Russian and American college students. Several appraisal dimensions of personal goals were studied including goals' importance, their attainability, and sources of control over goal attainment, such as self, others, luck, and fate. The association between assimilative (tenacious goal pursuit) and accommodative (flexible goal adjustment) control strategies and perceived attainability of goals was also examined. The results indicated that both Russian and American students gave higher priority to work- and education-related goals and lower priority to the familial goal. In both samples, the familial goal was the most influenced and health was the least influenced by luck/chance and fate. Overall, American students were more optimistic about the perceived probability to attain their goals, which may be affected by a cultural tendency for self-enhancement and positive outlook. Russian students had a stronger belief in control by luck/chance and fate over personal goals, which coincides with a less agentic orientation of Russian culture. Regardless of culture and goal content, goal importance was associated with greater perceived success in goal attainment. However, control strategies (assimilative and accommodative) as well as internal control differentially predicted perceived attainability of goals depending on the goals' content. For both Russians and Americans, perceived attainability of education-related goals was associated with assimilative strategies and internal control; leisure was associated with accommodative strategies and health-related goals were associated with internal control. Characteristics of cultural contexts accountable for crosscultural differences in perceived control over personal goals are discussed.

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.

Computational Prediction of the Global Functional Genomic Landscape: Applications, Methods and Challenges

PubMed Central

Zhou, Weiqiang; Sherwood, Ben; Ji, Hongkai

2017-01-01

Technological advances have led to an explosive growth of high-throughput functional genomic data. Exploiting the correlation among different data types, it is possible to predict one functional genomic data type from other data types. Prediction tools are valuable in understanding the relationship among different functional genomic signals. They also provide a cost-efficient solution to inferring the unknown functional genomic profiles when experimental data are unavailable due to resource or technological constraints. The predicted data may be used for generating hypotheses, prioritizing targets, interpreting disease variants, facilitating data integration, quality control, and many other purposes. This article reviews various applications of prediction methods in functional genomics, discusses analytical challenges, and highlights some common and effective strategies used to develop prediction methods for functional genomic data. PMID:28076869

Control and prediction for blackouts caused by frequency collapse in smart grids.

PubMed

Wang, Chengwei; Grebogi, Celso; Baptista, Murilo S

2016-09-01

The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers, and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids and another one for smart grids. The control strategies show the efficient function of the fast-response energy storage systems in preventing and predicting blackouts in smart grids. This work provides innovative ideas which help us to build up a robuster and more economic smart power system.

Control and prediction for blackouts caused by frequency collapse in smart grids

NASA Astrophysics Data System (ADS)

Wang, Chengwei; Grebogi, Celso; Baptista, Murilo S.

2016-09-01

The electric power system is one of the cornerstones of modern society. One of its most serious malfunctions is the blackout, a catastrophic event that may disrupt a substantial portion of the system, playing havoc to human life and causing great economic losses. Thus, understanding the mechanisms leading to blackouts and creating a reliable and resilient power grid has been a major issue, attracting the attention of scientists, engineers, and stakeholders. In this paper, we study the blackout problem in power grids by considering a practical phase-oscillator model. This model allows one to simultaneously consider different types of power sources (e.g., traditional AC power plants and renewable power sources connected by DC/AC inverters) and different types of loads (e.g., consumers connected to distribution networks and consumers directly connected to power plants). We propose two new control strategies based on our model, one for traditional power grids and another one for smart grids. The control strategies show the efficient function of the fast-response energy storage systems in preventing and predicting blackouts in smart grids. This work provides innovative ideas which help us to build up a robuster and more economic smart power system.

An integrated control strategy for the composite braking system of an electric vehicle with independently driven axles

NASA Astrophysics Data System (ADS)

Sun, Fengchun; Liu, Wei; He, Hongwen; Guo, Hongqiang

2016-08-01

For an electric vehicle with independently driven axles, an integrated braking control strategy was proposed to coordinate the regenerative braking and the hydraulic braking. The integrated strategy includes three modes, namely the hybrid composite mode, the parallel composite mode and the pure hydraulic mode. For the hybrid composite mode and the parallel composite mode, the coefficients of distributing the braking force between the hydraulic braking and the two motors' regenerative braking were optimised offline, and the response surfaces related to the driving state parameters were established. Meanwhile, the six-sigma method was applied to deal with the uncertainty problems for reliability. Additionally, the pure hydraulic mode is activated to ensure the braking safety and stability when the predictive failure of the response surfaces occurs. Experimental results under given braking conditions showed that the braking requirements could be well met with high braking stability and energy regeneration rate, and the reliability of the braking strategy was guaranteed on general braking conditions.

Hippocampal mGluR5 predicts an occurrence of helplessness behavior after repetitive exposure to uncontrollable stress.

PubMed

Yim, Yeong Shin; Lee, Jinu; Kim, Gun-Tae; Song, Teresa; Kim, Chul Hoon; Kim, Dong Goo

2012-06-21

An individual's behavior is generally based on genetic blueprint and previous experiences. A coping strategy, affected by personal interpretation of past events, can be determined by behavioral controllability of stress. In this study, we examined the relationship between the hippocampal mGluR5 expression and coping strategies to stress. Rats were exposed to stress via inescapable and unpredictable footshocks on PNDs 14 and 90. Coping strategies to stress were also measured. Hippocampal mGluR5 was found to be linked to the behavioral coping strategy, as it increased in rats that showed helplessness behavior (HL (+) group) and decreased in those that did not (HL (-) group). Also, the HL (+) group showed a lack of adaptation in a novel environment but the HL (-) group did not. The results suggest that mGluR5 has a pivotal role in the controllability-based coping strategy. Hippocampal mGluR5 could be a target molecule in the manipulation of neuropsychiatric conditions for which maladaptation is a part of behavioral consequences. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

An Examination of Incentive Strategies to Increase Participation in Outcomes Research for an Adolescent Inpatient Unit.

PubMed

Ha, Carolyn; Madan, Alok; Long, Tessa A; Sharp, Carla

2016-05-01

Tracking adolescent outcomes after inpatient hospitalization is important in informing clinical care for this age group, as inpatient care is one of the most expensive treatment modalities. This study examined 4 incentive strategies used to maintain adolescent participation in follow-up research (at 6, 12, and 18 mo) after their discharge from the hospital (N=267). A generalized estimation equation approach was taken to investigate whether different incentive strategies predicted adolescent completion of the follow-up assessments at each time point. Findings demonstrate that implementation of social worker contact significantly differed from other incentive strategies in increasing adolescent completion of follow-up assessments (Z=2.51, P=0.012) over the 3 time points, even when controlling for age and sex. Although these findings ultimately need to be confirmed through a randomized controlled study of incentive strategies, they provide preliminary support for the notion that relational incentives, such as maintaining contact with a member of the clinical team at the hospital, may be particularly important in promoting adolescent participation in outcomes research.

Cost-benefit analysis of foot and mouth disease control in Ethiopia.

PubMed

Jemberu, Wudu T; Mourits, Monique; Rushton, Jonathan; Hogeveen, Henk

2016-09-15

Foot and mouth disease (FMD) occurs endemically in Ethiopia. Quantitative insights on its national economic impact and on the costs and benefits of control options are, however, lacking to support decision making in its control. The objectives of this study were, therefore, to estimate the annual costs of FMD in cattle production systems of Ethiopia, and to conduct an ex ante cost-benefit analysis of potential control alternatives. The annual costs of FMD were assessed based on production losses, export losses and control costs. The total annual costs of FMD under the current status quo of no official control program were estimated at 1354 (90% CR: 864-2042) million birr. The major cost (94%) was due to production losses. The costs and benefits of three potential control strategies: 1) ring vaccination (reactive vaccination around outbreak area supported by animal movement restrictions, 2) targeted vaccination (annual preventive vaccination in high risk areas plus ring vaccination in the rest of the country), and 3) preventive mass vaccination (annual preventive vaccination of the whole national cattle population) were compared with the baseline scenario of no official control program. Experts were elicited to estimate the influence of each of the control strategies on outbreak incidence and number of cases per outbreak. Based on these estimates, the incidence of the disease was simulated stochastically for 10 years. Preventive mass vaccination was epidemiologically the most efficient control strategy by reducing the national outbreak incidence below 5% with a median time interval of 3 years, followed by targeted vaccination strategy with a corresponding median time interval of 5 years. On average, all evaluated control strategies resulted in positive net present values. The ranges in the net present values were, however, very wide, including negative values. The targeted vaccination strategy was the most economic strategy with a median benefit cost ratio of 4.29 (90%CR: 0.29-9.63). It was also the least risky strategy with 11% chance of a benefit cost ratio of less than one. The study indicates that FMD has a high economic impact in Ethiopia. Its control is predicted to be economically profitable even without a full consideration of gains from export. The targeted vaccination strategy is shown to provide the largest economic return with a relatively low risk of loss. More studies to generate data, especially on production impact of the disease and effectiveness of control measures are needed to improve the rigor of future analysis. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting Language Proficiency Based on the Use of Multimedia Interfaces for Transcription Tasks.

ERIC Educational Resources Information Center

Crosby, Martha E.; And Others

1996-01-01

Describes a controlled experiment conducted to determine the differences between native and nonnative speakers' strategies for transcribing dialogs, from the simple to the complex. Results confirmed that there were significant differences among three categories of the users' interactions with a computerized transcription system. (seven references)…

Prediction of a peptidome for the western tarnished plant bug Lygus hesperus

USDA-ARS?s Scientific Manuscript database

Many strategies for controlling insect pests require an understanding of their hormonal signaling agents, peptides being the largest and most diverse single class of these molecules. Lygus hesperus is a pest species of particular concern; it responsible for millions of dollars of damage to cotton, ...

Prediction errors in wildland fire situation analyses.

Treesearch

Geoffrey H. Donovan; Peter Noordijk

2005-01-01

Wildfires consume budgets and put the heat on fire managers to justify and control suppression costs. To determine the appropriate suppression strategy, land managers must conduct a wildland fire situation analysis (WFSA) when:A wildland fire is expected to or does escape initial attack,A wildland fire managed for resource benefits...

Flight Mechanics/Estimation Theory Symposium, 1991

NASA Technical Reports Server (NTRS)

Stengle, Thomas (Editor)

1991-01-01

Twenty-six papers and abstracts are presented. A wide range of issues related to orbit attitude prediction, orbit determination, and orbit control are examined including attitude sensor calibration, attitude dynamics, and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

COMPUTATIONAL CHEMISTRY METHOD FOR PREDICTING VAPOR PRESSURES AND ACTIVITY COEFFICIENTS OF POLAR ORGANIC OXYGENATES IN PM2.5

EPA Science Inventory

Parameterizations of interactions of polar multifunctional organic oxygenates in PM2.5 must be included in aerosol chemistry models for evaluating control strategies for reducing ambient concentrations of PM2.5 compounds. Vapor pressures and activity coefficients of these compo...

Women and Transgression in the Halls of Academe

ERIC Educational Resources Information Center

Davies, Bronwyn

2006-01-01

The controlling strategies of neo-liberalism, designed to constitute academics as economic units supporting the designs of government, are contrasted here with the creative and transgressive elements of a more Deleuzian approach to writing that opens things up, that brings thought to life, that makes the familiar, predictable order tremble. The…

FlexStem: improving predictions of RNA secondary structures with pseudoknots by reducing the search space.

PubMed

Chen, Xiang; He, Si-Min; Bu, Dongbo; Zhang, Fa; Wang, Zhiyong; Chen, Runsheng; Gao, Wen

2008-09-15

RNA secondary structures with pseudoknots are often predicted by minimizing free energy, which is proved to be NP-hard. Due to kinetic reasons the real RNA secondary structure often has local instead of global minimum free energy. This implies that we may improve the performance of RNA secondary structure prediction by taking kinetics into account and minimize free energy in a local area. we propose a novel algorithm named FlexStem to predict RNA secondary structures with pseudoknots. Still based on MFE criterion, FlexStem adopts comprehensive energy models that allow complex pseudoknots. Unlike classical thermodynamic methods, our approach aims to simulate the RNA folding process by successive addition of maximal stems, reducing the search space while maintaining or even improving the prediction accuracy. This reduced space is constructed by our maximal stem strategy and stem-adding rule induced from elaborate statistical experiments on real RNA secondary structures. The strategy and the rule also reflect the folding characteristic of RNA from a new angle and help compensate for the deficiency of merely relying on MFE in RNA structure prediction. We validate FlexStem by applying it to tRNAs, 5SrRNAs and a large number of pseudoknotted structures and compare it with the well-known algorithms such as RNAfold, PKNOTS, PknotsRG, HotKnots and ILM according to their overall sensitivities and specificities, as well as positive and negative controls on pseudoknots. The results show that FlexStem significantly increases the prediction accuracy through its local search strategy. Software is available at http://pfind.ict.ac.cn/FlexStem/. Supplementary data are available at Bioinformatics online.

Induced changes in island fox (Urocyon littoralis) activity do not mitigate the extinction threat posed by a novel predator.

PubMed

Hudgens, Brian R; Garcelon, David K

2011-03-01

Prey response to novel predators influences the impacts on prey populations of introduced predators, bio-control efforts, and predator range expansion. Predicting the impacts of novel predators on native prey requires an understanding of both predator avoidance strategies and their potential to reduce predation risk. We examine the response of island foxes (Urocyon littoralis) to invasion by golden eagles (Aquila chrysaetos). Foxes reduced daytime activity and increased night time activity relative to eagle-naïve foxes. Individual foxes reverted toward diurnal tendencies following eagle removal efforts. We quantified the potential population impact of reduced diurnality by modeling island fox population dynamics. Our model predicted an annual population decline similar to what was observed following golden eagle invasion and predicted that the observed 11% reduction in daytime activity would not reduce predation risk sufficiently to reduce extinction risk. The limited effect of this behaviorally plastic predator avoidance strategy highlights the importance of linking behavioral change to population dynamics for predicting the impact of novel predators on resident prey populations.

Identification of the feedforward component in manual control with predictable target signals.

PubMed

Drop, Frank M; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus M; Mulder, Max

2013-12-01

In the manual control of a dynamic system, the human controller (HC) often follows a visible and predictable reference path. Compared with a purely feedback control strategy, performance can be improved by making use of this knowledge of the reference. The operator could effectively introduce feedforward control in conjunction with a feedback path to compensate for errors, as hypothesized in literature. However, feedforward behavior has never been identified from experimental data, nor have the hypothesized models been validated. This paper investigates human control behavior in pursuit tracking of a predictable reference signal while being perturbed by a quasi-random multisine disturbance signal. An experiment was done in which the relative strength of the target and disturbance signals were systematically varied. The anticipated changes in control behavior were studied by means of an ARX model analysis and by fitting three parametric HC models: two different feedback models and a combined feedforward and feedback model. The ARX analysis shows that the experiment participants employed control action on both the error and the target signal. The control action on the target was similar to the inverse of the system dynamics. Model fits show that this behavior can be modeled best by the combined feedforward and feedback model.

When high working memory capacity is and is not beneficial for predicting nonlinear processes.

PubMed

Fischer, Helen; Holt, Daniel V

2017-04-01

Predicting the development of dynamic processes is vital in many areas of life. Previous findings are inconclusive as to whether higher working memory capacity (WMC) is always associated with using more accurate prediction strategies, or whether higher WMC can also be associated with using overly complex strategies that do not improve accuracy. In this study, participants predicted a range of systematically varied nonlinear processes based on exponential functions where prediction accuracy could or could not be enhanced using well-calibrated rules. Results indicate that higher WMC participants seem to rely more on well-calibrated strategies, leading to more accurate predictions for processes with highly nonlinear trajectories in the prediction region. Predictions of lower WMC participants, in contrast, point toward an increased use of simple exemplar-based prediction strategies, which perform just as well as more complex strategies when the prediction region is approximately linear. These results imply that with respect to predicting dynamic processes, working memory capacity limits are not generally a strength or a weakness, but that this depends on the process to be predicted.

Neuro-fuzzy control of structures using acceleration feedback

NASA Astrophysics Data System (ADS)

Schurter, Kyle C.; Roschke, Paul N.

2001-08-01

This paper described a new approach for the reduction of environmentally induced vibration in constructed facilities by way of a neuro-fuzzy technique. The new control technique is presented and tested in a numerical study that involves two types of building models. The energy of each building is dissipated through magnetorheological (MR) dampers whose damping properties are continuously updated by a fuzzy controller. This semi-active control scheme relies on the development of a correlation between the accelerations of the building (controller input) and the voltage applied to the MR damper (controller output). This correlation forms the basis for the development of an intelligent neuro-fuzzy control strategy. To establish a context for assessing the effectiveness of the semi-active control scheme, responses to earthquake excitation are compared with passive strategies that have similar authority for control. According to numerical simulation, MR dampers are less effective control mechanisms than passive dampers with respect to a single degree of freedom (DOF) building model. On the other hand, MR dampers are predicted to be superior when used with multiple DOF structures for reduction of lateral acceleration.

The impact of social cognitive and personality factors on teachers' reported inclusive behaviour.

PubMed

Wilson, Claire; Woolfson, Lisa Marks; Durkin, Kevin; Elliott, Mark A

2016-09-01

Inclusive education of children with intellectual disabilities (ID) is intended to maximize their educational experience within the mainstream school setting. While policy mandates inclusion, it is classroom teachers' behaviours that determine its success. This study provided a novel application of the theory of planned behaviour (TPB) in this setting. It examined the effect of TPB variables and personality on reported inclusive teaching behaviours for learners with ID. The sample comprised 145 primary school teachers (85% female) from mainstream schools across Scotland. Participants completed a TPB questionnaire assessing attitudes (instrumental and affective), subjective norms (injunctive and descriptive norms), perceptions of control (self-efficacy and controllability), and behavioural intentions towards using inclusive strategies. The Big Five Personality Index, measuring extraversion, conscientiousness, openness, neuroticism, and agreeableness, was also completed. Teaching practices were reported 2 weeks later. Instrumental attitudes, descriptive norm, self-efficacy, and neuroticism predicted teachers' intentions to use inclusive strategies. Further, conscientiousness had indirect effects on intentions through TPB variables. These intentions, however, did not predict reported behaviour expected by TPB. Instead, self-efficacy was the only significant predictor of reported behaviour. This study demonstrates the application of TPB to an educational setting and contributes to the understanding of teachers' reported use of inclusive strategies for children with ID. © 2016 The British Psychological Society.

Prediction and measurement of human pilot dynamic characteristics

NASA Technical Reports Server (NTRS)

Hess, Ronald A.; Reedy, James T.

1988-01-01

An analytical and experimental study of human pilot control strategies in a manned rotorcraft simulation is described. The task simulated involves a low-speed, constant-altitude maneuvering task in which a head-down display is utilized to allow the pilot to track a moving hover point. The efficacy of the display law driving an 'acceleration symbol' is determined and the manner in which the prediction and measurement of pilot/vehicle dynamics can be made part of man/machine system evaluations is demonstrated.

Process evaluation of the project P.A.T.H.S. (secondary 2 program): findings based on the co-walker scheme.

PubMed

Shek, Daniel T L; Tam, Suet-yan

2009-01-01

To understand the implementation quality of the Tier 1 Program (Secondary 2 Curriculum) of the P.A.T.H.S. Project, process evaluation was carried out by co-walkers through classroom observation of 195 units in 131 schools. Results showed that the overall level of program adherence was generally high with an average of 84.55%, and different factors of the implementation process were evaluated as positive. Quality of program implementation and achievement of program objectives were predicted by students' participation and involvement, strategies to enhance students' motivation, opportunity for reflection, time management, and class preparation. Success in program implementation was predicted by students' participation and involvement, classroom control, interactive delivery method, strategies to enhance students' motivation, opportunity for reflection, and lesson preparation.

Enhanced polyhydroxyalkanoate production from organic wastes via process control.

PubMed

Vargas, Alejandro; Montaño, Liliana; Amaya, Rodolfo

2014-03-01

This work explores the use of a model-based control scheme to enhance the productivity of polyhroxyalkanoate (PHA) production in a mixed culture two-stage system fed with synthetic wastewater. The controller supplies pulses of substrate while regulating the dissolved oxygen (DO) concentration and uses the data to fit a dynamic mathematical model, which in turn is used to predict the time until the next pulse addition. Experiments in a bench scale system first determined the optimal DO set-point and initial substrate concentration. Then the proposed feedback control strategy was compared with a simpler empiric algorithm. The results show that a substrate conversion rate of 1.370±0.598mgPHA/mgCOD/d was achieved. The proposed strategy can also indicate when to stop the accumulation of PHA upon saturation, which occurred with a PHA content of 71.0±7.2wt.%. Copyright © 2014 Elsevier Ltd. All rights reserved.

Biosensor commercialization strategy - a theoretical approach.

PubMed

Lin, Chin-Tsai; Wang, Su-Man

2005-01-01

Biosensors are analytical devices, which use biological interactions to provide either qualitative or quantitative results. They are extensively employed in many fields such as clinical diagnosis and biomedicine, military applications, anti-terrorism, farm, garden and veterinary analysis, process control, fermentation control and analysis, pharmaceutical and drug analysis, food and drink production and analysis, pollution control and monitoring, microbiology, bacterial and viral analysis, mining, and industrial and toxic gases. The biosensor market has significantly increased and will be mushrooming in the next decade. The total biosensor market is estimated to be 10.8 billion dollars by 2007. The emerging biosensor market presents both opportunities and obstacles to start-up biosensor entrepreneurs. The major challenge and threat for these entrepreneurs is how to predict the biosensor market and how to convert promising biosensor technology into commercialized biosensors. By adopting a simple commercialization strategy framework, we identify two key elements of biosensor commercialization strategy: excludability and complementary asset. We further divide biosensor commercialization environments into four distinct sub-environments: the Attacker's Advantage, Reputation-Based Idea Trading, Greenfield Competition and Ideas Factories. This paper explains how the interaction between these two key elements shapes biosensor commercialization strategy and biosensor industry dynamics. This paper also discusses alternative commercialization strategies for each specific commercialization environment and how to choose from these alternatives. The analysis of this study further provides a good reference for start-up biosensor entrepreneurs to formulate effective biosensor commercialization strategy.

Intelligent automated control of life support systems using proportional representations.

PubMed

Wu, Annie S; Garibay, Ivan I

2004-06-01

Effective automatic control of Advanced Life Support Systems (ALSS) is a crucial component of space exploration. An ALSS is a coupled dynamical system which can be extremely sensitive and difficult to predict. As a result, such systems can be difficult to control using deliberative and deterministic methods. We investigate the performance of two machine learning algorithms, a genetic algorithm (GA) and a stochastic hill-climber (SH), on the problem of learning how to control an ALSS, and compare the impact of two different types of problem representations on the performance of both algorithms. We perform experiments on three ALSS optimization problems using five strategies with multiple variations of a proportional representation for a total of 120 experiments. Results indicate that although a proportional representation can effectively boost GA performance, it does not necessarily have the same effect on other algorithms such as SH. Results also support previous conclusions that multivector control strategies are an effective method for control of coupled dynamical systems.

Self-Regulation and Recall: Growth Curve Modeling of Intervention Outcomes for Older Adults

PubMed Central

West, Robin L.; Hastings, Erin C.

2013-01-01

Memory training has often been supported as a potential means to improve performance for older adults. Less often studied are the characteristics of trainees that benefit most from training. Using a self-regulatory perspective, the current project examined a latent growth curve model to predict training-related gains for middle-aged and older adult trainees from individual differences (e.g., education), information processing skills (strategy use) and self-regulatory factors such as self-efficacy, control, and active engagement in training. For name recall, a model including strategy usage and strategy change as predictors of memory gain, along with self-efficacy and self-efficacy change, showed comparable fit to a more parsimonious model including only self-efficacy variables as predictors. The best fit to the text recall data was a model focusing on self-efficacy change as the main predictor of memory change, and that model showed significantly better fit than a model also including strategy usage variables as predictors. In these models, overall performance was significantly predicted by age and memory self-efficacy, and subsequent training-related gains in performance were best predicted directly by change in self-efficacy (text recall), or indirectly through the impact of active engagement and self-efficacy on gains (name recall). These results underscore the benefits of targeting self-regulatory factors in intervention programs designed to improve memory skills. PMID:21604891

Self-regulation and recall: growth curve modeling of intervention outcomes for older adults.

PubMed

West, Robin L; Hastings, Erin C

2011-12-01

Memory training has often been supported as a potential means to improve performance for older adults. Less often studied are the characteristics of trainees that benefit most from training. Using a self-regulatory perspective, the current project examined a latent growth curve model to predict training-related gains for middle-aged and older adult trainees from individual differences (e.g., education), information processing skills (strategy use) and self-regulatory factors such as self-efficacy, control, and active engagement in training. For name recall, a model including strategy usage and strategy change as predictors of memory gain, along with self-efficacy and self-efficacy change, showed comparable fit to a more parsimonious model including only self-efficacy variables as predictors. The best fit to the text recall data was a model focusing on self-efficacy change as the main predictor of memory change, and that model showed significantly better fit than a model also including strategy usage variables as predictors. In these models, overall performance was significantly predicted by age and memory self-efficacy, and subsequent training-related gains in performance were best predicted directly by change in self-efficacy (text recall), or indirectly through the impact of active engagement and self-efficacy on gains (name recall). These results underscore the benefits of targeting self-regulatory factors in intervention programs designed to improve memory skills.

Low speed hybrid generalized predictive control of a gasoline-propelled car.

PubMed

Romero, M; de Madrid, A P; Mañoso, C; Milanés, V

2015-07-01

Low-speed driving in traffic jams causes significant pollution and wasted time for commuters. Additionally, from the passengers׳ standpoint, this is an uncomfortable, stressful and tedious scene that is suitable to be automated. The highly nonlinear dynamics of car engines at low-speed turn its automation in a complex problem that still remains as unsolved. Considering the hybrid nature of the vehicle longitudinal control at low-speed, constantly switching between throttle and brake pedal actions, hybrid control is a good candidate to solve this problem. This work presents the analytical formulation of a hybrid predictive controller for automated low-speed driving. It takes advantage of valuable characteristics supplied by predictive control strategies both for compensating un-modeled dynamics and for keeping passengers security and comfort analytically by means of the treatment of constraints. The proposed controller was implemented in a gas-propelled vehicle to experimentally validate the adopted solution. To this end, different scenarios were analyzed varying road layouts and vehicle speeds within a private test track. The production vehicle is a commercial Citroën C3 Pluriel which has been modified to automatically act over its throttle and brake pedals. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Variable memory strategy use in children's adaptive intratask learning behavior: developmental changes and working memory influences in free recall.

PubMed

Lehmann, Martin; Hasselhorn, Marcus

2007-01-01

Variability in strategy use within single trials in free recall was analyzed longitudinally from second to fourth grades (ages 8-10 years). To control for practice effects another sample of fourth graders was included (age 10 years). Video analyses revealed that children employed different strategies when preparing for free recall. A gradual shift from labeling to cumulative rehearsal was present both with increasing age and across different list positions. Whereas cumulative rehearsal was frequent at early list positions, labeling was dominant at later list portions. Working memory capacity predicted the extent of cumulative rehearsal usage, which became more efficient with increasing age. Results are discussed in the context of the adaptive strategy choice model.

Effective and ineffective coping strategies in a low-autonomy work environment.

PubMed

Britt, Thomas W; Crane, Monique; Hodson, Stephanie E; Adler, Amy B

2016-04-01

The authors examined the effectiveness of different coping strategies in buffering the negative effects of uncontrollable stressors and predicting mental health symptoms in a low-autonomy work environment using a longitudinal design. Soldiers in training indicated the extent to which they engaged in various coping strategies to deal with stressors related to the training environment at 4 different points in time. Factor analyses of soldiers in 2 different countries (i.e., United States and Australia) yielded 5 coping dimensions: active coping, acceptance of demands, seeking social support, humor, and denial/self-criticism. Among U.S. soldiers in basic training, acceptance of demands and denial/self-criticism interacted with the magnitude of basic-training stressors to predict mental health symptoms (depression and anxiety) at 3 different points during training while controlling for symptoms at the immediate prior time period. Acceptance buffered soldiers from the negative effects of the stressors, whereas denial/self-criticism exacerbated the effects of the stressors. The results of LGC models also indicated that the slopes of acceptance and active coping were negatively related to the slope of mental health symptoms across training, whereas the slope for denial/self-criticism was positively related to the slope of symptoms. Active coping was less predictive of functioning in the face of stressors and in the prediction of symptoms over time. The results demonstrated that in a low-autonomy occupational setting, acceptance coping was more effective in facilitating good mental health outcomes compared with other coping strategies considered important in prior research (e.g., active coping). (c) 2016 APA, all rights reserved).

Advances, challenges, and directions in shrimp disease control: the guidelines from an ecological perspective.

PubMed

Xiong, Jinbo; Dai, Wenfang; Li, Chenghua

2016-08-01

High-density aquaculture has led to increasing occurrences of diseases in shrimp. Thus, it is imperative to establish effective and quantitative strategies for preventing and predicting these diseases. Water quality indices and investigations of specific pathogen abundance provide only a qualitative evaluation of the risk of shrimp disease and can be inaccurate. To address these shortcomings, we introduced intestinal indicative assemblages as independent variables with which to quantitatively predict incidences of shrimp disease. Given the ignorance regarding the niches differences in the shrimp intestine throughout its developmental stages, the use of probiotics in aquaculture has had limited success. Therefore, we propose the exploration of effective probiotic bacteria from shrimp intestinal flora and the establishment of therapeutic strategies dependent on shrimp age. Following ecological selection principles, we hypothesize that the larval stage provides the best opportunity to establish a desired gut microbiota through preemptive colonization of the treated rearing water with known probiotics. To employ this strategy, however, substantial barriers must be overcome.

Mindfulness as a strategy for coping with cue-elicited cravings for alcohol: an experimental examination.

PubMed

Murphy, Cara M; MacKillop, James

2014-04-01

Mindfulness has been identified as a promising strategy for managing cravings for alcohol and other drugs, but little controlled experimental research has directly studied whether this approach is effective. The current study systematically examined the effects of an acute mindfulness manipulation on craving for alcohol during prolonged exposure to alcohol cues. Heavy drinkers (N = 84, 50% male) underwent a prolonged alcohol cue exposure paradigm in a simulated bar environment and received either a mindfulness-based strategy, a distraction (DST)-based strategy (active control), or no strategy (passive control) to cope with alcohol cravings and discomfort associated with craving. No baseline differences were present between conditions. Manipulation checks revealed that participants in the 2 active conditions reported using the recommended strategies. Across groups, the initial exposure to alcohol cues was associated with significant increases in craving, urge distress, and heart rate. Mixed analyses of variance on these indices following the experimental manipulation revealed significant differences based on condition over the course of the bar laboratory protocol. The DST strategy was significantly more effective at acutely reducing craving and urge distress than the other 2 conditions, which did not significantly differ from each other. Contrary to our prediction, these findings suggest that an acute DSTstrategy is beneficial for coping with alcohol cravings. The potential importance of protracted mindfulness training to detect significant effects on in vivo craving, additional implications, and methodological considerations are discussed. Copyright © 2013 by the Research Society on Alcoholism.

Systematic review of management strategies to control chronic wasting disease in wild deer populations in North America.

PubMed

Uehlinger, F D; Johnston, A C; Bollinger, T K; Waldner, C L

2016-08-22

Chronic wasting disease (CWD) is a contagious, fatal prion disease affecting cervids in a growing number of regions across North America. Projected deer population declines and concern about potential spread of CWD to other species warrant strategies to manage this disease. Control efforts to date have been largely unsuccessful, resulting in continuing spread and increasing prevalence. This systematic review summarizes peer-reviewed published reports describing field-applicable CWD control strategies in wild deer populations in North America using systematic review methods. Ten databases were searched for peer-reviewed literature. Following deduplication, relevance screening, full-text appraisal, subject matter expert review and qualitative data extraction, nine references were included describing four distinct management strategies. Six of the nine studies used predictive modeling to evaluate control strategies. All six demonstrated one or more interventions to be effective but results were dependant on parameters and assumptions used in the model. Three found preferential removal of CWD infected deer to be effective in reducing CWD prevalence; one model evaluated a test and slaughter strategy, the other selective removal of infected deer by predators and the third evaluated increased harvest of the sex with highest prevalence (males). Three models evaluated non-selective harvest of deer. There were only three reports that examined primary data collected as part of observational studies. Two of these studies supported the effectiveness of intensive non-selective culling; the third study did not find a difference between areas that were subjected to culling and those that were not. Seven of the nine studies were conducted in the United States. This review highlights the paucity of evaluated, field-applicable control strategies for CWD in wild deer populations. Knowledge gaps in the complex epidemiology of CWD and the intricacies inherent to prion diseases currently pose significant challenges to effective control of this disease in wild deer in North America.

A Novel Topology Link-Controlling Approach for Active Defense of a Node in a Network.

PubMed

Li, Jun; Hu, HanPing; Ke, Qiao; Xiong, Naixue

2017-03-09

With the rapid development of virtual machine technology and cloud computing, distributed denial of service (DDoS) attacks, or some peak traffic, poses a great threat to the security of the network. In this paper, a novel topology link control technique and mitigation attacks in real-time environments is proposed. Firstly, a non-invasive method of deploying virtual sensors in the nodes is built, which uses the resource manager of each monitored node as a sensor. Secondly, a general topology-controlling approach of resisting the tolerant invasion is proposed. In the proposed approach, a prediction model is constructed by using copula functions for predicting the peak of a resource through another resource. The result of prediction determines whether or not to initiate the active defense. Finally, a minority game with incomplete strategy is employed to suppress attack flows and improve the permeability of the normal flows. The simulation results show that the proposed approach is very effective in protecting nodes.

A Novel Topology Link-Controlling Approach for Active Defense of Nodes in Networks

PubMed Central

Li, Jun; Hu, HanPing; Ke, Qiao; Xiong, Naixue

2017-01-01

With the rapid development of virtual machine technology and cloud computing, distributed denial of service (DDoS) attacks, or some peak traffic, poses a great threat to the security of the network. In this paper, a novel topology link control technique and mitigation attacks in real-time environments is proposed. Firstly, a non-invasive method of deploying virtual sensors in the nodes is built, which uses the resource manager of each monitored node as a sensor. Secondly, a general topology-controlling approach of resisting the tolerant invasion is proposed. In the proposed approach, a prediction model is constructed by using copula functions for predicting the peak of a resource through another resource. The result of prediction determines whether or not to initiate the active defense. Finally, a minority game with incomplete strategy is employed to suppress attack flows and improve the permeability of the normal flows. The simulation results show that the proposed approach is very effective in protecting nodes. PMID:28282962

Adaptive support ventilation may deliver unwanted respiratory rate-tidal volume combinations in patients with acute lung injury ventilated according to an open lung concept.

PubMed

Dongelmans, Dave A; Paulus, Frederique; Veelo, Denise P; Binnekade, Jan M; Vroom, Margreeth B; Schultz, Marcus J

2011-05-01

With adaptive support ventilation, respiratory rate and tidal volume (V(T)) are a function of the Otis least work of breathing formula. We hypothesized that adaptive support ventilation in an open lung ventilator strategy would deliver higher V(T)s to patients with acute lung injury. Patients with acute lung injury were ventilated according to a local guideline advising the use of lower V(T) (6-8 ml/kg predicted body weight), high concentrations of positive end-expiratory pressure, and recruitment maneuvers. Ventilation parameters were recorded when the ventilator was switched to adaptive support ventilation, and after recruitment maneuvers. If V(T) increased more than 8 ml/kg predicted body weight, airway pressure was limited to correct for the rise of V(T). Ten patients with a mean (±SD) Pao(2)/Fio(2) of 171 ± 86 mmHg were included. After a switch from pressure-controlled ventilation to adaptive support ventilation, respiratory rate declined (from 31 ± 5 to 21 ± 6 breaths/min; difference = 10 breaths/min, 95% CI 3-17 breaths/min, P = 0.008) and V(T) increased (from 6.5 ± 0.8 to 9.0 ± 1.6 ml/kg predicted body weight; difference = 2.5 ml, 95% CI 0.4-4.6 ml/kg predicted body weight, P = 0.02). Pressure limitation corrected for the rise of V(T), but minute ventilation declined, forcing the user to switch back to pressure-controlled ventilation. Adaptive support ventilation, compared with pressure-controlled ventilation in an open lung strategy setting, delivers a lower respiratory rate-higher V(T) combination. Pressure limitation does correct for the rise of V(T), but leads to a decline in minute ventilation.

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed Central

Rees, Mark; Rose, Karen E

2002-01-01

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed. PMID:12137582

Evolution of flowering strategies in Oenothera glazioviana: an integral projection model approach.

PubMed

Rees, Mark; Rose, Karen E

2002-07-22

The timing of reproduction is a key determinant of fitness. Here, we develop parameterized integral projection models of size-related flowering for the monocarpic perennial Oenothera glazioviana and use these to predict the evolutionarily stable strategy (ESS) for flowering. For the most part there is excellent agreement between the model predictions and the results of quantitative field studies. However, the model predicts a much steeper relationship between plant size and the probability of flowering than observed in the field, indicating selection for a 'threshold size' flowering function. Elasticity and sensitivity analysis of population growth rate lambda and net reproductive rate R(0) are used to identify the critical traits that determine fitness and control the ESS for flowering. Using the fitted model we calculate the fitness landscape for invading genotypes and show that this is characterized by a ridge of approximately equal fitness. The implications of these results for the maintenance of genetic variation are discussed.

Environmental controls, oceanography and population dynamics of pathogens and harmful algal blooms: connecting sources to human exposure

PubMed Central

Dyble, Julianne; Bienfang, Paul; Dusek, Eva; Hitchcock, Gary; Holland, Fred; Laws, Ed; Lerczak, James; McGillicuddy, Dennis J; Minnett, Peter; Moore, Stephanie K; O'Kelly, Charles; Solo-Gabriele, Helena; Wang, John D

2008-01-01

Coupled physical-biological models are capable of linking the complex interactions between environmental factors and physical hydrodynamics to simulate the growth, toxicity and transport of infectious pathogens and harmful algal blooms (HABs). Such simulations can be used to assess and predict the impact of pathogens and HABs on human health. Given the widespread and increasing reliance of coastal communities on aquatic systems for drinking water, seafood and recreation, such predictions are critical for making informed resource management decisions. Here we identify three challenges to making this connection between pathogens/HABs and human health: predicting concentrations and toxicity; identifying the spatial and temporal scales of population and ecosystem interactions; and applying the understanding of population dynamics of pathogens/HABs to management strategies. We elaborate on the need to meet each of these challenges, describe how modeling approaches can be used and discuss strategies for moving forward in addressing these challenges. PMID:19025676

Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

NASA Astrophysics Data System (ADS)

Chen, Xin; Liu, Li; Zhou, Sida; Yue, Zhenjiang

2016-09-01

Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.

Modeling temperature variations in a pilot plant thermophilic anaerobic digester.

PubMed

Valle-Guadarrama, Salvador; Espinosa-Solares, Teodoro; López-Cruz, Irineo L; Domaschko, Max

2011-05-01

A model that predicts temperature changes in a pilot plant thermophilic anaerobic digester was developed based on fundamental thermodynamic laws. The methodology utilized two simulation strategies. In the first, model equations were solved through a searching routine based on a minimal square optimization criterion, from which the overall heat transfer coefficient values, for both biodigester and heat exchanger, were determined. In the second, the simulation was performed with variable values of these overall coefficients. The prediction with both strategies allowed reproducing experimental data within 5% of the temperature span permitted in the equipment by the system control, which validated the model. The temperature variation was affected by the heterogeneity of the feeding and extraction processes, by the heterogeneity of the digestate recirculation through the heating system and by the lack of a perfect mixing inside the biodigester tank. The use of variable overall heat transfer coefficients improved the temperature change prediction and reduced the effect of a non-ideal performance of the pilot plant modeled.

Prediction and prevention of the next pandemic zoonosis

PubMed Central

Morse, Stephen S; Mazet, Jonna A K; Woolhouse, Mark; Parrish, Colin R; Carroll, Dennis; Karesh, William B; Zambrana-Torrelio, Carlos; Lipkin, W Ian; Daszak, Peter

2013-01-01

Most pandemics—eg, HIV/AIDS, severe acute respiratory syndrome, pandemic influenza—originate in animals, are caused by viruses, and are driven to emerge by ecological, behavioural, or socioeconomic changes. Despite their substantial effects on global public health and growing understanding of the process by which they emerge, no pandemic has been predicted before infecting human beings. We review what is known about the pathogens that emerge, the hosts that they originate in, and the factors that drive their emergence. We discuss challenges to their control and new efforts to predict pandemics, target surveillance to the most crucial interfaces, and identify prevention strategies. New mathematical modelling, diagnostic, communications, and informatics technologies can identify and report hitherto unknown microbes in other species, and thus new risk assessment approaches are needed to identify microbes most likely to cause human disease. We lay out a series of research and surveillance opportunities and goals that could help to overcome these challenges and move the global pandemic strategy from response to pre-emption. PMID:23200504

Predicting short-term positive affect in individuals with social anxiety disorder: The role of selected personality traits and emotion regulation strategies.

PubMed

Weisman, Jaclyn S; Rodebaugh, Thomas L; Lim, Michelle H; Fernandez, Katya C

2015-08-01

Recently, research has provided support for a moderate, inverse relationship between social anxiety and dispositional positive affect. However, the dynamics of this relationship remain poorly understood. The present study evaluates whether certain personality traits and emotion regulation variables predict short-term positive affect for individuals with social anxiety disorder and healthy controls. Positive affect as measured by two self-report instruments was assessed before and after two tasks in which the participant conversed with either a friend or a romantic partner. Tests of models examining the hypothesized prospective predictors revealed that the paths did not differ significantly across diagnostic group and both groups showed the hypothesized patterns of endorsement for the emotion regulation variables. Further, a variable reflecting difficulty redirecting oneself when distressed prospectively predicted one measure of positive affect. Additional research is needed to explore further the role of emotion regulation strategies on positive emotions for individuals higher in social anxiety. Copyright © 2015 Elsevier Ltd. All rights reserved.

Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

NASA Astrophysics Data System (ADS)

Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

2010-09-01

The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the other hand, buildings are affected by particularly local weather conditions at the building site. To overcome this discrepancy, we make use of local measurements to statistically adapt the COSMO-7 model output to the meteorological conditions at the building. For this, we have developed a general correction algorithm that exploits systematic properties of the COSMO-7 prediction error and explicitly estimates the degree of temporal autocorrelation using online recursive estimation. The resulting corrected predictions are improved especially for the first few hours being the most crucial for the predictive controller and, ultimately for the reduction of primary energy consumption using predictive control. The use of numerical weather forecasts in predictive building automation is one example in a wide field of weather dependent advanced energy saving technologies. Our work particularly highlights the need for the development of specifically tailored weather forecast products by (statistical) postprocessing in order to meet the requirements of specific applications.

Task-Specific Response Strategy Selection on the Basis of Recent Training Experience

PubMed Central

Fulvio, Jacqueline M.; Green, C. Shawn; Schrater, Paul R.

2014-01-01

The goal of training is to produce learning for a range of activities that are typically more general than the training task itself. Despite a century of research, predicting the scope of learning from the content of training has proven extremely difficult, with the same task producing narrowly focused learning strategies in some cases and broadly scoped learning strategies in others. Here we test the hypothesis that human subjects will prefer a decision strategy that maximizes performance and reduces uncertainty given the demands of the training task and that the strategy chosen will then predict the extent to which learning is transferable. To test this hypothesis, we trained subjects on a moving dot extrapolation task that makes distinct predictions for two types of learning strategy: a narrow model-free strategy that learns an input-output mapping for training stimuli, and a general model-based strategy that utilizes humans' default predictive model for a class of trajectories. When the number of distinct training trajectories is low, we predict better performance for the mapping strategy, but as the number increases, a predictive model is increasingly favored. Consonant with predictions, subject extrapolations for test trajectories were consistent with using a mapping strategy when trained on a small number of training trajectories and a predictive model when trained on a larger number. The general framework developed here can thus be useful both in interpreting previous patterns of task-specific versus task-general learning, as well as in building future training paradigms with certain desired outcomes. PMID:24391490

Application of Multivariable Model Predictive Advanced Control for a 2×310T/H CFB Boiler Unit

NASA Astrophysics Data System (ADS)

Weijie, Zhao; Zongllao, Dai; Rong, Gou; Wengan, Gong

When a CFB boiler is in automatic control, there are strong interactions between various process variables and inverse response characteristics of bed temperature control target. Conventional Pill control strategy cannot deliver satisfactory control demand. Kalman wave filter technology is used to establish a non-linear combustion model, based on the CFB combustion characteristics of bed fuel inventory, heating values, bed lime inventory and consumption. CFB advanced combustion control utilizes multivariable model predictive control technology to optimize primary and secondary air flow, bed temperature, air flow, fuel flow and heat flux. In addition to providing advanced combustion control to 2×310t/h CFB+1×100MW extraction condensing turbine generator unit, the control also provides load allocation optimization and advanced control for main steam pressure, combustion and temperature. After the successful implementation, under 10% load change, main steam pressure varied less than ±0.07MPa, temperature less than ±1°C, bed temperature less than ±4°C, and air flow (O2) less than ±0.4%.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms.

PubMed

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants' strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research.

Individual strategy ratings improve the control for task difficulty effects in arithmetic problem solving paradigms

PubMed Central

Tschentscher, Nadja; Hauk, Olaf

2015-01-01

Mental arithmetic is a powerful paradigm to study problem solving using neuroimaging methods. However, the evaluation of task complexity varies significantly across neuroimaging studies. Most studies have parameterized task complexity by objective features such as the number size. Only a few studies used subjective rating procedures. In fMRI, we provided evidence that strategy self-reports control better for task complexity across arithmetic conditions than objective features (Tschentscher and Hauk, 2014). Here, we analyzed the relative predictive value of self-reported strategies and objective features for performance in addition and multiplication tasks, by using a paradigm designed for neuroimaging research. We found a superiority of strategy ratings as predictor of performance above objective features. In a Principal Component Analysis on reaction times, the first component explained over 90 percent of variance and factor loadings reflected percentages of self-reported strategies well. In multiple regression analyses on reaction times, self-reported strategies performed equally well or better than objective features, depending on the operation type. A Receiver Operating Characteristic (ROC) analysis confirmed this result. Reaction times classified task complexity better when defined by individual ratings. This suggests that participants’ strategy ratings are reliable predictors of arithmetic complexity and should be taken into account in neuroimaging research. PMID:26321997

A model of yeast glycolysis based on a consistent kinetic characterisation of all its enzymes

PubMed Central

Smallbone, Kieran; Messiha, Hanan L.; Carroll, Kathleen M.; Winder, Catherine L.; Malys, Naglis; Dunn, Warwick B.; Murabito, Ettore; Swainston, Neil; Dada, Joseph O.; Khan, Farid; Pir, Pınar; Simeonidis, Evangelos; Spasić, Irena; Wishart, Jill; Weichart, Dieter; Hayes, Neil W.; Jameson, Daniel; Broomhead, David S.; Oliver, Stephen G.; Gaskell, Simon J.; McCarthy, John E.G.; Paton, Norman W.; Westerhoff, Hans V.; Kell, Douglas B.; Mendes, Pedro

2013-01-01

We present an experimental and computational pipeline for the generation of kinetic models of metabolism, and demonstrate its application to glycolysis in Saccharomyces cerevisiae. Starting from an approximate mathematical model, we employ a “cycle of knowledge” strategy, identifying the steps with most control over flux. Kinetic parameters of the individual isoenzymes within these steps are measured experimentally under a standardised set of conditions. Experimental strategies are applied to establish a set of in vivo concentrations for isoenzymes and metabolites. The data are integrated into a mathematical model that is used to predict a new set of metabolite concentrations and reevaluate the control properties of the system. This bottom-up modelling study reveals that control over the metabolic network most directly involved in yeast glycolysis is more widely distributed than previously thought. PMID:23831062

Active and passive stabilization of body pitch in insect flight

PubMed Central

Ristroph, Leif; Ristroph, Gunnar; Morozova, Svetlana; Bergou, Attila J.; Chang, Song; Guckenheimer, John; Wang, Z. Jane; Cohen, Itai

2013-01-01

Flying insects have evolved sophisticated sensory–motor systems, and here we argue that such systems are used to keep upright against intrinsic flight instabilities. We describe a theory that predicts the instability growth rate in body pitch from flapping-wing aerodynamics and reveals two ways of achieving balanced flight: active control with sufficiently rapid reactions and passive stabilization with high body drag. By glueing magnets to fruit flies and perturbing their flight using magnetic impulses, we show that these insects employ active control that is indeed fast relative to the instability. Moreover, we find that fruit flies with their control sensors disabled can keep upright if high-drag fibres are also attached to their bodies, an observation consistent with our prediction for the passive stability condition. Finally, we extend this framework to unify the control strategies used by hovering animals and also furnish criteria for achieving pitch stability in flapping-wing robots. PMID:23697713

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.

Drug Resistance Strategies of Early Adolescents in Mexico: Gender Differences in the Influence of Drug Offers and Relationship to the Offeror

PubMed Central

Booth, Jaime Michelle; Bercerra, David

2016-01-01

To address increases in substance use among Mexican adolescents, particularly females, US prevention programs are being adapted to the Mexican cultural context. Understanding how responses to substance offers by Mexican adolescents are shaped by gender and relationships to those making offers is an important step in the adaptation process. Using data from Guadalajara, Mexico middle schools (N=431), this pilot study tested for gender differences in the use of several drug resistance strategies commonly taught in US substance abuse prevention interventions. Results indicated that the drug resistance strategies of Mexican early adolescents differ by gender, type of substance offered, and the youth’s relationship to the offeror. Contrary to previous research on older Mexican adolescents, in this sample females received more substance offers from age peers than males did, and employed a wider repertoire of drug resistance strategies, including active strategies such as direct refusals. Gender differences in use of the strategies persisted after controlling for number of offers received. There were gender differences in the conditional effects of greater exposure to offers. A larger volume of alcohol and cigarette offers predicted females’ use of direct strategies more strongly than for males, but less strongly than males for marijuana offers. Females’ use of drug resistance strategies was more strongly associated with offers from family adults, siblings and cousins, while males’ use of strategies was predicted more strongly by offers from non-family adults. Interpretations and prevention implications are discussed in light of changing gender norms in Mexico and gendered patterns of substance use. PMID:26886157

Effective Teaching Strategies for Predicting Reading Growth in English Language Learners

ERIC Educational Resources Information Center

Melgarejo, Melina

2017-01-01

The goal of the present study was to examine how effective use of teaching strategies predict reading growth among a sample of English Language Learners. The study specifically examined whether the types of teaching strategies that predict growth in decoding skills also predict growth in comprehension skills. The sample consisted of students in…

Predicting Future-Year Ozone Concentrations: Integrated Observational-Modeling Approach for Probabilistic Evaluation of the Efficacy of Emission Control strategies

EPA Science Inventory

Regional-scale air quality models are being used to demonstrate attainment of the ozone air quality standard. In current regulatory applications, a regional-scale air quality model is applied for a base year and a future year with reduced emissions using the same meteorological ...

Dredging Operations Technical Support Program. Management Strategy for Disposal of Dredged Material: Contaminant Testing and Controls.

DTIC Science & Technology

1985-08-01

laboratory test using a rainfall simulator has been developed ( Westerdahl and Skogerboe 1981) and is being used to predict surface runoff water quality...Marine Protection, Research, and Sanctuaries Act of 1972)," US Army Engineer Waterways Experiment Station, Vicksburg, Miss. Westerdahl , H. E., and

DYNAMIC EVALUATION OF REGIONAL AIR QUALITY MODELS: ASSESSING CHANGES TO O 3 STEMMING FROM CHANGES IN EMISSIONS AND METEOROLOGY

EPA Science Inventory

Regional-scale air quality models are used to estimate the response of air pollutants to potential emission control strategies as part of the decision-making process. Traditionally, the model predicted pollutant concentrations are evaluated for the “base case” to assess a model’s...

Unscented predictive variable structure filter for satellite attitude estimation with model errors when using low precision sensors

NASA Astrophysics Data System (ADS)

Cao, Lu; Li, Hengnian

2016-10-01

For the satellite attitude estimation problem, the serious model errors always exist and hider the estimation performance of the Attitude Determination and Control System (ACDS), especially for a small satellite with low precision sensors. To deal with this problem, a new algorithm for the attitude estimation, referred to as the unscented predictive variable structure filter (UPVSF) is presented. This strategy is proposed based on the variable structure control concept and unscented transform (UT) sampling method. It can be implemented in real time with an ability to estimate the model errors on-line, in order to improve the state estimation precision. In addition, the model errors in this filter are not restricted only to the Gaussian noises; therefore, it has the advantages to deal with the various kinds of model errors or noises. It is anticipated that the UT sampling strategy can further enhance the robustness and accuracy of the novel UPVSF. Numerical simulations show that the proposed UPVSF is more effective and robustness in dealing with the model errors and low precision sensors compared with the traditional unscented Kalman filter (UKF).

Prediction, Assessment of the Rift Valley Fever Activity in East and Southern Africa 2006–2008 and Possible Vector Control Strategies

PubMed Central

Anyamba, Assaf; Linthicum, Kenneth J.; Small, Jennifer; Britch, Seth C.; Pak, Edwin; de La Rocque, Stephane; Formenty, Pierre; Hightower, Allen W.; Breiman, Robert F.; Chretien, Jean-Paul; Tucker, Compton J.; Schnabel, David; Sang, Rosemary; Haagsma, Karl; Latham, Mark; Lewandowski, Henry B.; Magdi, Salih Osman; Mohamed, Mohamed Ally; Nguku, Patrick M.; Reynes, Jean-Marc; Swanepoel, Robert

2010-01-01

Historical outbreaks of Rift Valley fever (RVF) since the early 1950s have been associated with cyclical patterns of the El Niño/Southern Oscillation (ENSO) phenomenon, which results in elevated and widespread rainfall over the RVF endemic areas of Africa. Using satellite measurements of global and regional elevated sea surface temperatures, elevated rainfall, and satellite derived-normalized difference vegetation index data, we predicted with lead times of 2–4 months areas where outbreaks of RVF in humans and animals were expected and occurred in the Horn of Africa, Sudan, and Southern Africa at different time periods from September 2006 to March 2008. Predictions were confirmed by entomological field investigations of virus activity and by reported cases of RVF in human and livestock populations. This represents the first series of prospective predictions of RVF outbreaks and provides a baseline for improved early warning, control, response planning, and mitigation into the future. PMID:20682905

An attribution theory perspective on emotional labour in nurse-patient encounters: a nested cross-sectional study in paediatric settings.

PubMed

Golfenshtein, Nadya; Drach-Zahavy, Anat

2015-05-01

To understand the role of patients' attributions under the attribution theory framework (locus, controllability, stability) in nurses' performance of surface or deep acting, as they unfold in interactions with different patients. Regulation of emotions at work, or emotional labour, has been conceptualized in terms of two main strategies: surface acting and deep acting. Most prior research tested for between-subject variation in the search for the factors evoking these strategies in nurses, assuming them to be trait-like characteristics. Only scant research has examined how nurses modify their emotional labour strategies in different patient-nurse encounters. A nested cross-sectional design (patients within nurses). Data were collected during 2011-2012 through validated questionnaires from the nursing staff (N = 41) of two paediatric hospital wards and their randomly selected patients (N = 239). Questionnaires were administered to nurses multiple times after encounters with different patients. Analyses were conducted using mixed effects models. In accordance with attribution theory, different combinations of locus, controllability and stability attributions were related to the choice of surface or deep acting. Nurses' perceptions of patients' controllability were associated positively with surface acting and negatively with deep acting. Interaction terms of stability and locus and of controllability and stability, were distinctively associated with deep and surface acting. Findings innovatively introduce the attribution process as an explanatory perspective to nurses' emotional labour and highlight its situational nature, providing a potential tool for emotional labour strategy prediction. Raising nurses' awareness of how they perceive patients may increase control of the strategies employed. © 2015 John Wiley & Sons Ltd.

The role of meteorological conditions and pollution control strategies in reducing air pollution in Beijing during APEC 2014 and Victory Parade 2015

NASA Astrophysics Data System (ADS)

Liang, Pengfei; Zhu, Tong; Fang, Yanhua; Li, Yingruo; Han, Yiqun; Wu, Yusheng; Hu, Min; Wang, Junxia

2017-11-01

To control severe air pollution in China, comprehensive pollution control strategies have been implemented throughout the country in recent years. To evaluate the effectiveness of these strategies, the influence of meteorological conditions on levels of air pollution needs to be determined. Using the intensive air pollution control strategies implemented during the Asia-Pacific Economic Cooperation Forum in 2014 (APEC 2014) and the 2015 China Victory Day Parade (Victory Parade 2015) as examples, we estimated the role of meteorological conditions and pollution control strategies in reducing air pollution levels in Beijing. Atmospheric particulate matter of aerodynamic diameter ≤ 2.5 µm (PM2.5) samples were collected and gaseous pollutants (SO2, NO, NOx, and O3) were measured online at a site in Peking University (PKU). To determine the influence of meteorological conditions on the levels of air pollution, we first compared the air pollutant concentrations during days with stable meteorological conditions. However, there were few days with stable meteorological conditions during the Victory Parade. As such, we were unable to estimate the level of emission reduction efforts during this period. Finally, a generalized linear regression model (GLM) based only on meteorological parameters was built to predict air pollutant concentrations, which could explain more than 70 % of the variation in air pollutant concentration levels, after incorporating the nonlinear relationships between certain meteorological parameters and the concentrations of air pollutants. Evaluation of the GLM performance revealed that the GLM, even based only on meteorological parameters, could be satisfactory to estimate the contribution of meteorological conditions in reducing air pollution and, hence, the contribution of control strategies in reducing air pollution. Using the GLM, we found that the meteorological conditions and pollution control strategies contributed 30 and 28 % to the reduction of the PM2.5 concentration during APEC and 38 and 25 % during the Victory Parade, respectively, based on the assumption that the concentrations of air pollutants are only determined by meteorological conditions and emission intensities. We also estimated the contribution of meteorological conditions and control strategies in reducing the concentrations of gaseous pollutants and PM2.5 components with the GLMs, revealing the effective control of anthropogenic emissions.

A standardized model for predicting flap failure using indocyanine green dye

NASA Astrophysics Data System (ADS)

Zimmermann, Terence M.; Moore, Lindsay S.; Warram, Jason M.; Greene, Benjamin J.; Nakhmani, Arie; Korb, Melissa L.; Rosenthal, Eben L.

2016-03-01

Techniques that provide a non-invasive method for evaluation of intraoperative skin flap perfusion are currently available but underutilized. We hypothesize that intraoperative vascular imaging can be used to reliably assess skin flap perfusion and elucidate areas of future necrosis by means of a standardized critical perfusion threshold. Five animal groups (negative controls, n=4; positive controls, n=5; chemotherapy group, n=5; radiation group, n=5; chemoradiation group, n=5) underwent pre-flap treatments two weeks prior to undergoing random pattern dorsal fasciocutaneous flaps with a length to width ratio of 2:1 (3 x 1.5 cm). Flap perfusion was assessed via laser-assisted indocyanine green dye angiography and compared to standard clinical assessment for predictive accuracy of flap necrosis. For estimating flap-failure, clinical prediction achieved a sensitivity of 79.3% and a specificity of 90.5%. When average flap perfusion was more than three standard deviations below the average flap perfusion for the negative control group at the time of the flap procedure (144.3+/-17.05 absolute perfusion units), laser-assisted indocyanine green dye angiography achieved a sensitivity of 81.1% and a specificity of 97.3%. When absolute perfusion units were seven standard deviations below the average flap perfusion for the negative control group, specificity of necrosis prediction was 100%. Quantitative absolute perfusion units can improve specificity for intraoperative prediction of viable tissue. Using this strategy, a positive predictive threshold of flap failure can be standardized for clinical use.

The Role of Coping Change in Borderline Personality Disorder: A Process-Outcome Analysis on Dialectical-Behaviour Skills Training.

PubMed

Kramer, Ueli

2017-03-01

Difficulty in emotion regulation is a hallmark feature of patients with borderline personality disorder (BPD). Skills training concepts based on dialectical-behaviour therapy (DBT) are common and effective treatment options for specifically addressing lacking skills in emotion regulation. However, so far it is unclear which aspects of coping change over the course of DBT skills training and if these coping strategies predict symptom change. The present process-outcome analysis, based on a randomized controlled study, aims at investigating these questions, by referring to a general conception of coping and by using an observer-rated approach to assess coping strategies directly in the therapy sessions. In total, n = 31 patients with BPD underwent two individual clinical interview assessments (pre- and post-study intervention; half of the patients underwent DBT skills training, half were in a wait-list control). All individual assessment sessions were transcribed and analysed using the Coping Action Pattern Rating Scale. Outcome was assessed pre- and post-intervention using the Outcome Questionnaire-45.2 and the Borderline Symptom List 23. The results showed increase in overall coping functioning in patients who underwent the DBT skills training, compared with the controls, and specific increases in relatedness coping where the stress is appraised as challenge, along with specific decreases in autonomy coping where the stress is appraised as threat. These changes predicted changes in general distress and borderline symptomatology. The results are interpreted within a general framework aiming at understanding the psychological effects of treatments for BPD, in particular effects related to coping. Effective emotion regulation strategies may therefore be important candidates as potential change mechanisms in treatments for BPD. Copyright © 2016 John Wiley & Sons, Ltd. It seems important for clinicians to assess the quality of coping strategies as they occur within the session facing a patient with borderline personality disorder. Clinicians may foster the emergence of support-seeking and self-reliance coping strategies in order to increase the effectiveness of therapy. Clinicians may monitor closely the patient's use of ineffective emotion regulation strategies, in particular opposition and submission, with the aim of reducing them early in therapy. Copyright © 2016 John Wiley & Sons, Ltd.

Formulation strategies for optimizing the morphology of polymeric bulk heterojunction organic solar cells: a brief review

NASA Astrophysics Data System (ADS)

Vongsaysy, Uyxing; Bassani, Dario M.; Servant, Laurent; Pavageau, Bertrand; Wantz, Guillaume; Aziz, Hany

2014-01-01

Polymeric bulk heterojunction (BHJ) organic solar cells represent one of the most promising technologies for renewable energy with a low fabrication cost. Control over BHJ morphology is one of the key factors in obtaining high-efficiency devices. This review focuses on formulation strategies for optimizing the BHJ morphology. We address how solvent choice and the introduction of processing additives affect the morphology. We also review a number of recent studies concerning prediction methods that utilize the Hansen solubility parameters to develop efficient solvent systems.

Chronic wasting disease—Status, science, and management support by the U.S. Geological Survey

USGS Publications Warehouse

Carlson, Christina M.; Hopkins, M. Camille; Nguyen, Natalie T.; Richards, Bryan J.; Walsh, Daniel P.; Walter, W. David

2018-03-01

The U.S. Geological Survey (USGS) investigates chronic wasting disease (CWD) at multiple science centers and cooperative research units across the Nation and supports the management of CWD through science-based strategies. CWD research conducted by USGS scientists has three strategies: (1) to understand the biology, ecology, and causes and distribution of CWD; (2) to assess and predict the spread and persistence of CWD in wildlife and the environment; and (3) to develop tools for early detection, diagnosis, surveillance, and control of CWD.

Control strategy to limit duty cycle impact of earthquakes on the LIGO gravitational-wave detectors

NASA Astrophysics Data System (ADS)

Biscans, S.; Warner, J.; Mittleman, R.; Buchanan, C.; Coughlin, M.; Evans, M.; Gabbard, H.; Harms, J.; Lantz, B.; Mukund, N.; Pele, A.; Pezerat, C.; Picart, P.; Radkins, H.; Shaffer, T.

2018-03-01

Advanced gravitational-wave detectors such as the laser interferometer gravitational-wave observatories (LIGO) require an unprecedented level of isolation from the ground. When in operation, they measure motion of less than 10‑19 m. Strong teleseismic events like earthquakes disrupt the proper functioning of the detectors, and result in a loss of data. An earthquake early-warning system, as well as a prediction model, have been developed to understand the impact of earthquakes on LIGO. This paper describes a control strategy to use this early-warning system to reduce the LIGO downtime by  ∼30%. It also presents a plan to implement this new earthquake configuration in the LIGO automation system.

Protection induced by a commercial bivalent vaccine against Foot-and-Mouth Disease 2010 field virus from Ecuador.

PubMed

Duque, Hernando; Naranjo, Jose; Carrillo, Consuelo; Burbano, Alexandra; Vargas, Javier; Pauszek, Lisa; Olesen, Ian; Sanchez-Vazquez, Manuel J; Cosivi, Ottorino; Allende, Rossana M

2016-07-29

Foot-and-Mouth Disease serotype O circulated endemically in Ecuador for many years, with an upsurge occurring in 2009. This manuscript describes retrospectively in vitro and in vivo laboratory studies to predict the field effectiveness of a commercial FMD vaccine to protect against the field strain, and explains the key actions and epidemiological strategies followed by the country to control the disease. The results established that the use of a good quality oil vaccine, manufactured with strains that were isolated long ago: O1 Campos Br/58 and A24 Cruzeiro Br/55; combined with the correct epidemiological strategies, are useful to control field strains when used in periodic biannual vaccination campaigns. Published by Elsevier Ltd.

Evaluation of emission control strategies to reduce ozone pollution in the Paso del Norte region using a photochemical air quality modeling system

NASA Astrophysics Data System (ADS)

Valenzuela, Victor Hugo

Air pollution emissions control strategies to reduce ozone precursor pollutants are analyzed by applying a photochemical modeling system. Simulations of air quality conditions during an ozone episode which occurred in June, 2006 are undertaken by increasing or reducing area source emissions in Ciudad Juarez, Chihuahua, Mexico. Two air pollutants are primary drivers in the formation of tropospheric ozone. Oxides of nitrogen (NOx) and volatile organic compounds (VOC) undergo multiple chemical reactions under favorable meteorological conditions to form ozone, which is a secondary pollutant that irritates respiratory systems in sensitive individuals especially the elderly and young children. The U.S. Environmental Protection Agency established National Ambient Air Quality Standards (NAAQS) to limit ambient air pollutants such as ozone by establishing an 8-hour average concentration of 0.075 ppm as the threshold at which a violation of the standard occurs. Ozone forms primarily due reactions in the troposphere of NOx and VOC emissions generated primarily by anthropogenic sources in urban regions. Data from emissions inventories indicate area sources account for ˜15 of NOx and ˜45% of regional VOC emissions. Area sources include gasoline stations, automotive paint bodyshops and nonroad mobile sources. Multiplicity of air pollution emissions sources provides an opportunity to investigate and potentially implement air quality improvement strategies to reduce emissions which contribute to elevated ozone concentrations. A baseline modeling scenario was established using the CAMx photochemical air quality model from which a series of sensitivity analyses for evaluating air quality control strategies were conducted. Modifications to area source emissions were made by varying NOx and / or VOC emissions in the areas of particular interest. Model performance was assessed for each sensitivity analysis. Normalized bias (NB) and normalized error (NE) were used to identify variability of the PREDICTED to OBSERVED ozone concentrations of both BASELINE model and simulations with modified emissions assessed by the sensitivity analysis. All simulations were found to vary within acceptable ranges of these two criteria variables. Simulation results indicate ozone formation in the PdN region is VOC-limited. Under VOC-limited conditions, modifications to NOx emissions do not produce a marked increase or decrease in ozone concentrations. Modifications to VOC emissions generated the highest variability in ozone concentrations. Increasing VOC emissions by 75% produced results which minimized model bias and error when comparing PREDICTED and OBSERVED ozone concentrations. Increasing VOC emissions by 75% either alone or in combination with a 75% increase in NOx emissions generated PREDICTED ozone concentrations very near to OBSERVED ozone. By evaluating the changes in ambient ozone concentrations through photochemical modeling, air quality planners may identify the most efficient or effective VOC emissions control strategies for area sources. Among the strategies to achieve emissions reductions are installation of gasoline vapor recovery systems, replacing high-pressure low-volume surface coating paint spray guns with high-volume low-pressure spray paint guns, requiring emissions control booths for surface coating operations as well as undertaking solvent management practices, requiring the sale of low VOC paint solvents in the surface-coating industry, and requiring low-VOC solvents in the dry cleaning industry. Other strategies to reduce VOC emissions include initiating Eco-Driving strategies to reduce fuel consumption from mobile sources and minimize vehicle idling at the international ports of entry by reducing bridge wait times. This dissertation depicts a tool for evaluating impacts of emissions on regional air quality by addressing the highly unresolved fugitive emissions in the Paso del Norte region. It provides a protocol for decision makers to assess the effects of various emission control strategies in the region. Impacts of specific source categories such as the international ports of entry, gasoline stations, paint body shops, truck stops, and military installations on the regional air quality can be easily and systematically addressed in a timely manner in the future.

Prediction and control of neural responses to pulsatile electrical stimulation

NASA Astrophysics Data System (ADS)

Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

2012-04-01

This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

Performance predictions affect attentional processes of event-based prospective memory.

PubMed

Rummel, Jan; Kuhlmann, Beatrice G; Touron, Dayna R

2013-09-01

To investigate whether making performance predictions affects prospective memory (PM) processing, we asked one group of participants to predict their performance in a PM task embedded in an ongoing task and compared their performance with a control group that made no predictions. A third group gave not only PM predictions but also ongoing-task predictions. Exclusive PM predictions resulted in slower ongoing-task responding both in a nonfocal (Experiment 1) and in a focal (Experiment 2) PM task. Only in the nonfocal task was the additional slowing accompanied by improved PM performance. Even in the nonfocal task, however, was the correlation between ongoing-task speed and PM performance reduced after predictions, suggesting that the slowing was not completely functional for PM. Prediction-induced changes could be avoided by asking participants to additionally predict their performance in the ongoing task. In sum, the present findings substantiate a role of metamemory for attention-allocation strategies of PM. Copyright © 2013 Elsevier Inc. All rights reserved.

TOPEX/POSEIDON orbit maintenance maneuver design

NASA Technical Reports Server (NTRS)

Bhat, R. S.; Frauenholz, R. B.; Cannell, Patrick E.

1990-01-01

The Ocean Topography Experiment (TOPEX/POSEIDON) mission orbit requirements are outlined, as well as its control and maneuver spacing requirements including longitude and time targeting. A ground-track prediction model dealing with geopotential, luni-solar gravity, and atmospheric-drag perturbations is considered. Targeting with all modeled perturbations is discussed, and such ground-track prediction errors as initial semimajor axis, orbit-determination, maneuver-execution, and atmospheric-density modeling errors are assessed. A longitude targeting strategy for two extreme situations is investigated employing all modeled perturbations and prediction errors. It is concluded that atmospheric-drag modeling errors are the prevailing ground-track prediction error source early in the mission during high solar flux, and that low solar-flux levels expected late in the experiment stipulate smaller maneuver magnitudes.

Flexibility to contingency changes distinguishes habitual and goal-directed strategies in humans

PubMed Central

Keramati, Mehdi

2017-01-01

Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, a balance that has been characterized in terms of a trade-off between a slower, prospective goal-directed model-based (MB) strategy and a fast, retrospective habitual model-free (MF) strategy. Theory predicts that flexibility to changes in both reward values and transition contingencies can determine the relative influence of the two systems in reinforcement learning, but few studies have manipulated the latter. Therefore, we developed a novel two-level contingency change task in which transition contingencies between states change every few trials; MB and MF control predict different responses following these contingency changes, allowing their relative influence to be inferred. Additionally, we manipulated the rate of contingency changes in order to determine whether contingency change volatility would play a role in shifting subjects between a MB and MF strategy. We found that human subjects employed a hybrid MB/MF strategy on the task, corroborating the parallel contribution of MB and MF systems in reinforcement learning. Further, subjects did not remain at one level of MB/MF behaviour but rather displayed a shift towards more MB behavior over the first two blocks that was not attributable to the rate of contingency changes but rather to the extent of training. We demonstrate that flexibility to contingency changes can distinguish MB and MF strategies, with human subjects utilizing a hybrid strategy that shifts towards more MB behavior over blocks, consequently corresponding to a higher payoff. PMID:28957319

Flexibility to contingency changes distinguishes habitual and goal-directed strategies in humans.

PubMed

Lee, Julie J; Keramati, Mehdi

2017-09-01

Decision-making in the real world presents the challenge of requiring flexible yet prompt behavior, a balance that has been characterized in terms of a trade-off between a slower, prospective goal-directed model-based (MB) strategy and a fast, retrospective habitual model-free (MF) strategy. Theory predicts that flexibility to changes in both reward values and transition contingencies can determine the relative influence of the two systems in reinforcement learning, but few studies have manipulated the latter. Therefore, we developed a novel two-level contingency change task in which transition contingencies between states change every few trials; MB and MF control predict different responses following these contingency changes, allowing their relative influence to be inferred. Additionally, we manipulated the rate of contingency changes in order to determine whether contingency change volatility would play a role in shifting subjects between a MB and MF strategy. We found that human subjects employed a hybrid MB/MF strategy on the task, corroborating the parallel contribution of MB and MF systems in reinforcement learning. Further, subjects did not remain at one level of MB/MF behaviour but rather displayed a shift towards more MB behavior over the first two blocks that was not attributable to the rate of contingency changes but rather to the extent of training. We demonstrate that flexibility to contingency changes can distinguish MB and MF strategies, with human subjects utilizing a hybrid strategy that shifts towards more MB behavior over blocks, consequently corresponding to a higher payoff.

[Research on optimal modeling strategy for licorice extraction process based on near-infrared spectroscopy technology].

PubMed

Wang, Hai-Xia; Suo, Tong-Chuan; Yu, He-Shui; Li, Zheng

2016-10-01

The manufacture of traditional Chinese medicine (TCM) products is always accompanied by processing complex raw materials and real-time monitoring of the manufacturing process. In this study, we investigated different modeling strategies for the extraction process of licorice. Near-infrared spectra associate with the extraction time was used to detemine the states of the extraction processes. Three modeling approaches, i.e., principal component analysis (PCA), partial least squares regression (PLSR) and parallel factor analysis-PLSR (PARAFAC-PLSR), were adopted for the prediction of the real-time status of the process. The overall results indicated that PCA, PLSR and PARAFAC-PLSR can effectively detect the errors in the extraction procedure and predict the process trajectories, which has important significance for the monitoring and controlling of the extraction processes. Copyright© by the Chinese Pharmaceutical Association.

Evaluation of classifier topologies for the real-time classification of simultaneous limb motions.

PubMed

Ortiz-Catalan, Max; Branemark, Rickard; Hakansson, Bo

2013-01-01

The prediction of motion intent through the decoding of myoelectric signals has the potential to improve the functionally of limb prostheses. Considerable research on individual motion classifiers has been done to exploit this idea. A drawback with the individual prediction approach, however, is its limitation to serial control, which is slow, cumbersome, and unnatural. In this work, different classifier topologies suitable for the decoding of mixed classes, and thus capable of predicting simultaneous motions, were investigated in real-time. These topologies resulted in higher offline accuracies than previously achieved, but more importantly, positive indications of their suitability for real-time systems were found. Furthermore, in order to facilitate further development, benchmarking, and cooperation, the algorithms and data generated in this study are freely available as part of BioPatRec, an open source framework for the development of advanced prosthetic control strategies.

1999 Flight Mechanics Symposium

NASA Technical Reports Server (NTRS)

Lynch, John P. (Editor)

1999-01-01

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium held on May 18-20, 1999. Sponsored by the Guidance, Navigation and Control Center of Goddard Space Flight Center, this symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Development and Implementation of a Hardware In-the-Loop Test Bed for Unmanned Aerial Vehicle Control Algorithms

NASA Technical Reports Server (NTRS)

Nyangweso, Emmanuel; Bole, Brian

2014-01-01

Successful prediction and management of battery life using prognostic algorithms through ground and flight tests is important for performance evaluation of electrical systems. This paper details the design of test beds suitable for replicating loading profiles that would be encountered in deployed electrical systems. The test bed data will be used to develop and validate prognostic algorithms for predicting battery discharge time and battery failure time. Online battery prognostic algorithms will enable health management strategies. The platform used for algorithm demonstration is the EDGE 540T electric unmanned aerial vehicle (UAV). The fully designed test beds developed and detailed in this paper can be used to conduct battery life tests by controlling current and recording voltage and temperature to develop a model that makes a prediction of end-of-charge and end-of-life of the system based on rapid state of health (SOH) assessment.

Assessment of an alternative postdeployment reintegration strategy with soldiers returning from Iraq.

PubMed

Sipos, Maurice L; Foran, Heather M; Wood, Michael D; Wright, Kathleen M; Barnhart, Vincent J; Riviere, Lyndon A; Adler, Amy B

2014-05-01

The present study examined behavioral health outcomes, risk behaviors, aggression, alcohol misuse, marital satisfaction, and attitudes toward reintegration associated with an alternative, front-loaded reintegration strategy compared with a more standardized reintegration process in soldiers returning from combat deployments. The type of reintegration strategy used did not predict differences in posttraumatic stress disorder (PTSD) symptoms, alcohol misuse, aggression, and marital satisfaction, although slightly higher reports of risk behaviors were found in the unit using the standard reintegration approach even after controlling for demographic covariates and combat exposure. These findings may help guide leadership when making decisions regarding reintegration approaches in the future. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Molecular inspired models for prediction and control of directional FSO/RF wireless networks

NASA Astrophysics Data System (ADS)

Llorca, Jaime; Milner, Stuart D.; Davis, Christopher C.

2010-08-01

Directional wireless networks using FSO and RF transmissions provide wireless backbone support for mobile communications in dynamic environments. The heterogeneous and dynamic nature of such networks challenges their robustness and requires self-organization mechanisms to assure end-to-end broadband connectivity. We developed a framework based on the definition of a potential energy function to characterize robustness in communication networks and the study of first and second order variations of the potential energy to provide prediction and control strategies for network performance optimization. In this paper, we present non-convex molecular potentials such as the Morse Potential, used to describe the potential energy of bonds within molecules, for the characterization of communication links in the presence of physical constraints such as the power available at the network nodes. The inclusion of the Morse Potential translates into adaptive control strategies where forces on network nodes drive the release, retention or reconfiguration of communication links for network performance optimization. Simulation results show the effectiveness of our self-organized control mechanism, where the physical topology reorganizes to maximize the number of source to destination communicating pairs. Molecular Normal Mode Analysis (NMA) techniques for assessing network performance degradation in dynamic networks are also presented. Preliminary results show correlation between peaks in the eigenvalues of the Hessian of the network potential and network degradation.

Examining the relationships between span of control and manager job and unit performance outcomes.

PubMed

Wong, Carol A; Elliott-Miller, Pat; Laschinger, Heather; Cuddihy, Michael; Meyer, Raquel M; Keatings, Margaret; Burnett, Camille; Szudy, Natalie

2015-03-01

Our aim was to examine the combination of frontline manager (FLM) personal characteristics and span of control (SOC) on their job and unit performance outcomes. Healthcare downsizing and reform have contributed to larger spans for FLMs in Canadian hospitals and increased concerns about manager workload. Despite a heightened awareness of SOC issues among decision makers, there is limited empirical evidence related to the effects of SOC on outcomes. A non-experimental predictive survey design was used to examine FLM SOC in 14 Canadian academic hospitals. Managers (n = 121) completed an online survey of work characteristics and The Ottawa Hospital (TOH) SOC tool. Unit turnover data were collected from organisational databases. The combination of SOC and core self-evaluation significantly predicted role overload, work control and job satisfaction, but only SOC predicted unit adverse outcomes and neither significantly predicted unit turnover. The findings contribute to an understanding of connections between the combination of SOC and core self-evaluation and manager job and unit performance outcomes. Organisational strategies to create manageable FLM SOC are essential to ensure exemplary job and unit outcomes. Core self-evaluation is a personality characteristic that may enhance manager performance in the face of high spans of control. © 2013 John Wiley & Sons Ltd.

The Role of Metacognitive Reading Strategies, Metacognitive Study and Learning Strategies, and Behavioral Study and Learning Strategies in Predicting Academic Success in Students With and Without a History of Reading Difficulties.

PubMed

Chevalier, Thérèse M; Parrila, Rauno; Ritchie, Krista C; Deacon, S Hélène

2017-01-01

We examined the self-reported use of reading, study, and learning strategies in university students with a history of reading difficulties (HRD; n = 77) and with no history of reading difficulties (NRD; n = 295). We examined both between-groups differences in strategy use and strategy use as a predictive measure of academic success. Participants completed online questionnaires regarding reading history and strategy use. GPA and frequency of use of academic support services were also obtained for all students. University students with HRD reported a different profile of strategy use than their NRD peers, and self-reported strategy use was differentially predictive of GPA for students with HRD and NRD. For students with HRD, the use of metacognitive reading strategies and the use of study aids predicted academic success. Implications for university student services providers are discussed. © Hammill Institute on Disabilities 2015.

Obstacle avoidance handling and mixed integer predictive control for space robots

NASA Astrophysics Data System (ADS)

Zong, Lijun; Luo, Jianjun; Wang, Mingming; Yuan, Jianping

2018-04-01

This paper presents a novel obstacle avoidance constraint and a mixed integer predictive control (MIPC) method for space robots avoiding obstacles and satisfying physical limits during performing tasks. Firstly, a novel kind of obstacle avoidance constraint of space robots, which needs the assumption that the manipulator links and the obstacles can be represented by convex bodies, is proposed by limiting the relative velocity between two closest points which are on the manipulator and the obstacle, respectively. Furthermore, the logical variables are introduced into the obstacle avoidance constraint, which have realized the constraint form is automatically changed to satisfy different obstacle avoidance requirements in different distance intervals between the space robot and the obstacle. Afterwards, the obstacle avoidance constraint and other system physical limits, such as joint angle ranges, the amplitude boundaries of joint velocities and joint torques, are described as inequality constraints of a quadratic programming (QP) problem by using the model predictive control (MPC) method. To guarantee the feasibility of the obtained multi-constraint QP problem, the constraints are treated as soft constraints and assigned levels of priority based on the propositional logic theory, which can realize that the constraints with lower priorities are always firstly violated to recover the feasibility of the QP problem. Since the logical variables have been introduced, the optimization problem including obstacle avoidance and system physical limits as prioritized inequality constraints is termed as MIPC method of space robots, and its computational complexity as well as possible strategies for reducing calculation amount are analyzed. Simulations of the space robot unfolding its manipulator and tracking the end-effector's desired trajectories with the existence of obstacles and physical limits are presented to demonstrate the effectiveness of the proposed obstacle avoidance strategy and MIPC control method of space robots.

Cognitive control predicts use of model-based reinforcement learning.

PubMed

Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D

2015-02-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior.

The role of meta-cognitions and thought control techniques in predisposition to auditory and visual hallucinations.

PubMed

García-Montes, José M; Cangas, Adolfo; Pérez-Alvarez, M; Fidalgo, Angel M; Gutiérrez, Olga

2006-09-01

This study examines the relationship between a predisposition to hallucinations and meta-cognitive variables and thought-control techniques, controlling for the possible effect of anxiety. In order to do so, we start out with the hypothesis that anxiety does not, in itself, explain the association between meta-cognitions and a predisposition to auditory and visual hallucinations. A within-participants correlational design was employed. Four psychometric tests relating to predisposition to hallucinations, anxiety, meta-cognitions and thought-control techniques were administered to 150 participants. It was found that, after controlling for participants' anxiety levels, the 'loss of cognitive confidence' factor predicted the score on the scale of predisposition to both auditory and visual hallucinations. Thought-control strategies based on worry were also found to be predictive of a greater predisposition to hallucinations, regardless of whether or not participants' anxiety level was controlled. Meta-cognitive variables of cognitive confidence and thought control through worry are positively associated with a predisposition to hallucinations. The correlational nature of the design does not allow inferences about causal relationships.

Predictive Control of the Blood Glucose Level in Type I Diabetic Patient Using Delay Differential Equation Wang Model.

PubMed

Esna-Ashari, Mojgan; Zekri, Maryam; Askari, Masood; Khalili, Noushin

2017-01-01

Because of increasing risk of diabetes, the measurement along with control of blood sugar has been of great importance in recent decades. In type I diabetes, because of the lack of insulin secretion, the cells cannot absorb glucose leading to low level of glucose. To control blood glucose (BG), the insulin must be injected to the body. This paper proposes a method for BG level regulation in type I diabetes. The control strategy is based on nonlinear model predictive control. The aim of the proposed controller optimized with genetics algorithms is to measure BG level each time and predict it for the next time interval. This merit causes a less amount of control effort, which is the rate of insulin delivered to the patient body. Consequently, this method can decrease the risk of hypoglycemia, a lethal phenomenon in regulating BG level in diabetes caused by a low BG level. Two delay differential equation models, namely Wang model and Enhanced Wang model, are applied as controller model and plant, respectively. The simulation results exhibit an acceptable performance of the proposed controller in meal disturbance rejection and robustness against parameter changes. As a result, if the nutrition of the person decreases instantly, the hypoglycemia will not happen. Furthermore, comparing this method with other works, it was shown that the new method outperforms previous studies.

Predictive Control of the Blood Glucose Level in Type I Diabetic Patient Using Delay Differential Equation Wang Model

PubMed Central

Esna-Ashari, Mojgan; Zekri, Maryam; Askari, Masood; Khalili, Noushin

2017-01-01

Because of increasing risk of diabetes, the measurement along with control of blood sugar has been of great importance in recent decades. In type I diabetes, because of the lack of insulin secretion, the cells cannot absorb glucose leading to low level of glucose. To control blood glucose (BG), the insulin must be injected to the body. This paper proposes a method for BG level regulation in type I diabetes. The control strategy is based on nonlinear model predictive control. The aim of the proposed controller optimized with genetics algorithms is to measure BG level each time and predict it for the next time interval. This merit causes a less amount of control effort, which is the rate of insulin delivered to the patient body. Consequently, this method can decrease the risk of hypoglycemia, a lethal phenomenon in regulating BG level in diabetes caused by a low BG level. Two delay differential equation models, namely Wang model and Enhanced Wang model, are applied as controller model and plant, respectively. The simulation results exhibit an acceptable performance of the proposed controller in meal disturbance rejection and robustness against parameter changes. As a result, if the nutrition of the person decreases instantly, the hypoglycemia will not happen. Furthermore, comparing this method with other works, it was shown that the new method outperforms previous studies. PMID:28487828

Model-Based Battery Management Systems: From Theory to Practice

NASA Astrophysics Data System (ADS)

Pathak, Manan

Lithium-ion batteries are now extensively being used as the primary storage source. Capacity and power fade, and slow recharging times are key issues that restrict its use in many applications. Battery management systems are critical to address these issues, along with ensuring its safety. This dissertation focuses on exploring various control strategies using detailed physics-based electrochemical models developed previously for lithium-ion batteries, which could be used in advanced battery management systems. Optimal charging profiles for minimizing capacity fade based on SEI-layer formation are derived and the benefits of using such control strategies are shown by experimentally testing them on a 16 Ah NMC-based pouch cell. This dissertation also explores different time-discretization strategies for non-linear models, which gives an improved order of convergence for optimal control problems. Lastly, this dissertation also explores a physics-based model for predicting the linear impedance of a battery, and develops a freeware that is extremely robust and computationally fast. Such a code could be used for estimating transport, kinetic and material properties of the battery based on the linear impedance spectra.

Risk assessment and management of brucellosis in the southern greater Yellowstone area (I): A citizen-science based risk model for bovine brucellosis transmission from elk to cattle.

PubMed

Kauffman, Mandy; Peck, Dannele; Scurlock, Brandon; Logan, Jim; Robinson, Timothy; Cook, Walt; Boroff, Kari; Schumaker, Brant

2016-09-15

Livestock producers and state wildlife agencies have used multiple management strategies to control bovine brucellosis in the Greater Yellowstone Area (GYA). However, spillover from elk to domestic bison and cattle herds continues to occur. Although knowledge is increasing about the location and behavior of elk in the SGYA, predicting spatiotemporal overlap between elk and cattle requires locations of livestock operations and observations of elk contact by producers. We queried all producers in a three-county area using a questionnaire designed to determine location of cattle and whether producers saw elk comingle with their animals. This information was used to parameterize a spatially-explicit risk model to estimate the number of elk expected to overlap with cattle during the brucellosis transmission risk period. Elk-cattle overlap was predicted in areas further from roads and forest boundaries in areas with wolf activity, with higher slopes, lower hunter densities, and where the cost-distance to feedgrounds was very low or very high. The model was used to estimate the expected number of years until a cattle reactor will be detected, under alternative management strategies. The model predicted cattle cases every 4.28 years in the highest risk herd unit, a higher prediction than the one case in 26 years we have observed. This difference likely indicates that ongoing management strategies are at least somewhat effective in preventing potential elk-cattle brucellosis transmission in these areas. Using this model, we can infer the expected effectiveness of various management strategies for reducing the risk of brucellosis spillover from elk to cattle. Copyright © 2016 Elsevier B.V. All rights reserved.

Adult age differences in subjective and objective measures of strategy use on a sequentially cued prediction task

PubMed Central

Seaman, Kendra L.; Howard, Darlene V.; Howard, James H.

2015-01-01

Differences in strategy use are thought to underlie age-related performance deficits on many learning and decision-making tasks. Recently, age-related differences in learning to make predictions were reported on the Triplets Prediction Task (TPT; Seaman, Howard & Howard, 2013). Notably, deficits appeared early in training and continued with experience. To assess if age differences were due to early strategy use, neural networks were used to objectively assess the strategies implemented by participants during Session 1. Then the relationship between these strategies and performance was examined. Results revealed that older adults were more likely to implement a disadvantageous strategy early in learning, and this led to poorer task performance. Importantly the relationship between age and task performance was partially mediated by early strategy use, suggesting that early strategy selection played a role in the lower quality of predictions in older adults. PMID:24673615

Personality differences in the susceptibility to stress-eating: The influence of emotional control and impulsivity.

PubMed

Van Blyderveen, Sherry; Lafrance, Adele; Emond, Michael; Kosmerly, Stacey; O'Connor, Megan; Chang, Felicia

2016-12-01

Stress has been associated with deviations from typical eating patterns, with respect to both food choice and overall caloric intake. Both increases and decreases in dietary intake have been previously noted in response to stress. The purpose of the present study was to determine whether the affect regulation strategies of emotional control and impulsivity predict susceptibility to eating in response to stress. Specifically, it was anticipated that emotional suppression would predict decreases in caloric intake, whereas impulsivity would predict increases in caloric intake, in response to a stressor. Participants were randomly assigned to view either a video designed to elicit stress or a control video. Food was provided during the video and the amount and type of food consumed was measured. Participants' nutritional intake was greater in the stress condition than in the control condition. One aspect of affect regulation, impulsivity, moderated this relationship, with a tendency for greater impulsivity to be associated with greater caloric intake in the stress condition. The degree of negative affect that participants experienced in the stress condition predicted food choice and overall caloric intake. Both emotional control and impulsivity moderated the relationship between negative affect and both food choice and caloric intake in the stress condition. The present study highlights the importance of considering the personality attributes of both impulsivity and emotional suppression in understanding stress eating. Copyright © 2016. Published by Elsevier Ltd.

Spatial pattern formation facilitates eradication of infectious diseases

PubMed Central

Eisinger, Dirk; Thulke, Hans-Hermann

2008-01-01

Control of animal-born diseases is a major challenge faced by applied ecologists and public health managers. To improve cost-effectiveness, the effort required to control such pathogens needs to be predicted as accurately as possible. In this context, we reviewed the anti-rabies vaccination schemes applied around the world during the past 25 years. We contrasted predictions from classic approaches based on theoretical population ecology (which governs rabies control to date) with a newly developed individual-based model. Our spatially explicit approach allowed for the reproduction of pattern formation emerging from a pathogen's spread through its host population. We suggest that a much lower management effort could eliminate the disease than that currently in operation. This is supported by empirical evidence from historic field data. Adapting control measures to the new prediction would save one-third of resources in future control programmes. The reason for the lower prediction is the spatial structure formed by spreading infections in spatially arranged host populations. It is not the result of technical differences between models. Synthesis and applications. For diseases predominantly transmitted by neighbourhood interaction, our findings suggest that the emergence of spatial structures facilitates eradication. This may have substantial implications for the cost-effectiveness of existing disease management schemes, and suggests that when planning management strategies consideration must be given to methods that reflect the spatial nature of the pathogen–host system. PMID:18784795

Evaluation of peripheral binocular visual field in patients with glaucoma: a pilot study.

PubMed

Ana, Banc; Cristina, Stan; Dorin, Chiselita

2016-01-01

The objective of this study was to evaluate the peripheral binocular visual field (PBVF) in patients with glaucoma using the threshold strategy of Humphrey Field Analyzer. We conducted a case-control pilot study in which we enrolled 59 patients with glaucoma and 20 controls. All participants were evaluated using a custom PBVF test and central 24 degrees monocular visual field tests for each eye using the threshold strategy. The central binocular visual field (CBVF) was predicted from the monocular tests using the most sensitive point at each field location. The glaucoma patients were grouped according to Hodapp classification and age. The PBVF was compared to controls and the relationship between the PBVF and CBVF was tested. The areas of frame-induced artefacts were determined (over 50 degrees in each temporal field, 24 degrees superiorly and 45 degrees inferiorly) and excluded from interpretation. The patients presented a statistically significant generalized decrease of the peripheral retinal sensitivity compared to controls for Hodapp initial stage--groups aged 50-59 (t = 11.93 > 2.06; p < 0.05) and 60-69 (t = 7.55 > 2.06; p < 0.05). For the initial Hodapp stage there was no significant relationship between PBVF and CBVF (r = 0.39). For the moderate and advanced Hodapp stages, the interpretation of data was done separately for each patient. This pilot study suggests that glaucoma patients present a decrease of PBVF compared to controls and CBVF cannot predict the PBVF in glaucoma.

Beliefs about emotion: implications for avoidance-based emotion regulation and psychological health.

PubMed

De Castella, Krista; Platow, Michael J; Tamir, Maya; Gross, James J

2018-06-01

People's beliefs about their ability to control their emotions predict a range of important psychological outcomes. It is not clear, however, whether these beliefs are playing a causal role, and if so, why this might be. In the current research, we tested whether avoidance-based emotion regulation explains the link between beliefs and psychological outcomes. In Study 1 (N = 112), a perceived lack of control over emotions predicted poorer psychological health outcomes (increased self-reported avoidance, lower well-being, and higher levels of clinical symptoms), and avoidance strategies indirectly explained these links between emotion beliefs and psychological health. In Study 2 (N = 101), we experimentally manipulated participants' emotion beliefs by leading participants to believe that they struggled (low regulatory self-efficacy) or did not struggle (high regulatory self-efficacy) with controlling their emotions. Participants in the low regulatory self-efficacy condition reported increased intentions to engage in avoidance strategies over the next month and were more likely to avoid seeking psychological help. When asked if they would participate in follow-up studies, these participants were also more likely to display avoidance-based emotion regulation. These findings provide initial evidence for the causal role of emotion beliefs in avoidance-based emotion regulation, and document their impact on psychological health-related outcomes.

Prediction of Isoelectric Point of Manganese and Cobalt Lamellar Oxides: Application to Controlled Synthesis of Mixed Oxides.

PubMed

Tang, Céline; Giaume, Domitille; Guerlou-Demourgues, Liliane; Lefèvre, Grégory; Barboux, Philippe

2018-05-30

To design novel layered materials, bottom-up strategy is very promising. It consists of (1) synthesizing various layered oxides, (2) exfoliating them, then (3) restacking them in a controlled way. The last step is based on electrostatic interactions between different layered oxides and is difficult to control. The aim of this study is to facilitate this step by predicting the isoelectric point (IEP) of exfoliated materials. The Multisite Complexation model (MUSIC) was used for this objective and was shown to be able to predict IEP from the mean oxidation state of the metal in the (hydr)oxides, as the main parameter. Moreover, the effect of exfoliation on IEP has also been calculated. Starting from platelets with a high basal surface area over total surface area, we show that the exfoliation process has no impact on calculated IEP value, as verified with experiments. Moreover, the restacked materials containing different monometallic (hydr)oxide layers also have an IEP consistent with values calculated with the model. This study proves that MUSIC model is a useful tool to predict IEP of various complex metal oxides and hydroxides.

Texting while driving: psychosocial influences on young people's texting intentions and behaviour.

PubMed

Nemme, Heidi E; White, Katherine M

2010-07-01

Despite the dangers and illegality, there is a continued prevalence of texting while driving amongst young Australian drivers. The present study tested an extended theory of planned behaviour (TPB) to predict young drivers' (17-24 years) intentions to [1] send and [2] read text messages while driving. Participants (n=169 university students) completed measures of attitudes, subjective norm, perceived behavioural control, intentions, and the additional social influence measures of group norm and moral norm. One week later, participants reported on the number of texts sent and read while driving in the previous week. Attitude predicted intentions to both send and read texts while driving, and subjective norm and perceived behavioural control determined sending, but not reading, intentions. Further, intention, but not perceptions of control, predicted both texting behaviours 1 week later. In addition, both group norm and moral norm added predictive ability to the model. These findings provide support for the TPB in understanding students' decisions to text while driving as well as the inclusion of additional normative influences within this context, suggesting that a multi-strategy approach is likely to be useful in attempts to reduce the incidence of these risky driving behaviours. Copyright 2010 Elsevier Ltd. All rights reserved.

Near infrared spectroscopy based monitoring of extraction processes of raw material with the help of dynamic predictive modeling

NASA Astrophysics Data System (ADS)

Wang, Haixia; Suo, Tongchuan; Wu, Xiaolin; Zhang, Yue; Wang, Chunhua; Yu, Heshui; Li, Zheng

2018-03-01

The control of batch-to-batch quality variations remains a challenging task for pharmaceutical industries, e.g., traditional Chinese medicine (TCM) manufacturing. One difficult problem is to produce pharmaceutical products with consistent quality from raw material of large quality variations. In this paper, an integrated methodology combining the near infrared spectroscopy (NIRS) and dynamic predictive modeling is developed for the monitoring and control of the batch extraction process of licorice. With the spectra data in hand, the initial state of the process is firstly estimated with a state-space model to construct a process monitoring strategy for the early detection of variations induced by the initial process inputs such as raw materials. Secondly, the quality property of the end product is predicted at the mid-course during the extraction process with a partial least squares (PLS) model. The batch-end-time (BET) is then adjusted accordingly to minimize the quality variations. In conclusion, our study shows that with the help of the dynamic predictive modeling, NIRS can offer the past and future information of the process, which enables more accurate monitoring and control of process performance and product quality.

Mariner 9 navigation

NASA Technical Reports Server (NTRS)

Neil, W. J.; Jordan, J. F.; Zielenbach, J. W.; Wong, S. K.; Mitchell, R. T.; Webb, W. A.; Koskela, P. E.

1973-01-01

A final, comprehensive description of the navigation of Mariner 9-the first U.S. spacecraft to orbit another planet is provided. The Mariner 9 navigation function included not only precision flight path control but also pointing of the spacecraft's scientific instruments mounted on a two degree of freedom scan platform. To the extent appropriate, each section describes the perflight analyses on which the operational strategies and performance predictions were based. Inflight results are then discussed and compared with the preflight predictions. Postflight analyses, which were primarily concerned with developing a thorough understanding of unexpected in-flight results, are also presented.

Prediction and measurement of human pilot dynamic characteristics in a manned rotorcraft simulation

NASA Technical Reports Server (NTRS)

Hess, Ronald A.; Reedy, James T.

1988-01-01

An analytical and experimental study of the human pilot control strategies in a manned rotorcraft simulation is described. The task simulated involves a low-speed, constant-altitude maneuvering task in which a head-down display is utilized to allow the pilot to track a moving hover point. The efficacy of the display law driving an acceleration symbol is determined and the manner in which the prediction and measurement of pilot/vehicle dynamics can be made part of man/machine system evaluations is demonstrated.

Multi-criteria evaluation of wastewater treatment plant control strategies under uncertainty.

PubMed

Flores-Alsina, Xavier; Rodríguez-Roda, Ignasi; Sin, Gürkan; Gernaey, Krist V

2008-11-01

The evaluation of activated sludge control strategies in wastewater treatment plants (WWTP) via mathematical modelling is a complex activity because several objectives; e.g. economic, environmental, technical and legal; must be taken into account at the same time, i.e. the evaluation of the alternatives is a multi-criteria problem. Activated sludge models are not well characterized and some of the parameters can present uncertainty, e.g. the influent fractions arriving to the facility and the effect of either temperature or toxic compounds on the kinetic parameters, having a strong influence in the model predictions used during the evaluation of the alternatives and affecting the resulting rank of preferences. Using a simplified version of the IWA Benchmark Simulation Model No. 2 as a case study, this article shows the variations in the decision making when the uncertainty in activated sludge model (ASM) parameters is either included or not during the evaluation of WWTP control strategies. This paper comprises two main sections. Firstly, there is the evaluation of six WWTP control strategies using multi-criteria decision analysis setting the ASM parameters at their default value. In the following section, the uncertainty is introduced, i.e. input uncertainty, which is characterized by probability distribution functions based on the available process knowledge. Next, Monte Carlo simulations are run to propagate input through the model and affect the different outcomes. Thus (i) the variation in the overall degree of satisfaction of the control objectives for the generated WWTP control strategies is quantified, (ii) the contributions of environmental, legal, technical and economic objectives to the existing variance are identified and finally (iii) the influence of the relative importance of the control objectives during the selection of alternatives is analyzed. The results show that the control strategies with an external carbon source reduce the output uncertainty in the criteria used to quantify the degree of satisfaction of environmental, technical and legal objectives, but increasing the economical costs and their variability as a trade-off. Also, it is shown how a preliminary selected alternative with cascade ammonium controller becomes less desirable when input uncertainty is included, having simpler alternatives more chance of success.

The Pitch Imagery Arrow Task: Effects of Musical Training, Vividness, and Mental Control

PubMed Central

Gelding, Rebecca W.; Thompson, William Forde; Johnson, Blake W.

2015-01-01

Musical imagery is a relatively unexplored area, partly because of deficiencies in existing experimental paradigms, which are often difficult, unreliable, or do not provide objective measures of performance. Here we describe a novel protocol, the Pitch Imagery Arrow Task (PIAT), which induces and trains pitch imagery in both musicians and non-musicians. Given a tonal context and an initial pitch sequence, arrows are displayed to elicit a scale-step sequence of imagined pitches, and participants indicate whether the final imagined tone matches an audible probe. It is a staircase design that accommodates individual differences in musical experience and imagery ability. This new protocol was used to investigate the roles that musical expertise, self-reported auditory vividness and mental control play in imagery performance. Performance on the task was significantly better for participants who employed a musical imagery strategy compared to participants who used an alternative cognitive strategy and positively correlated with scores on the Control subscale from the Bucknell Auditory Imagery Scale (BAIS). Multiple regression analysis revealed that Imagery performance accuracy was best predicted by a combination of strategy use and scores on the Vividness subscale of BAIS. These results confirm that competent performance on the PIAT requires active musical imagery and is very difficult to achieve using alternative cognitive strategies. Auditory vividness and mental control were more important than musical experience in the ability to perform manipulation of pitch imagery. PMID:25807078

Job demands-control-social support model and coping strategies: predicting burnout and wellbeing in a group of Italian nurses.

PubMed

Pisanti, R

2012-01-01

Nursing is generally considered to be a stressful profession. The purpose of the present study was to test the core hypotheses of the job demands-control-social support model (JDCS) of Karasek & Theorell (1990). In order to refine and extend the JDCS model, we also analyzed the direct and interactive role of three coping strategies: task- oriented, emotion-oriented, and avoidance-oriented coping. Questionnaire data from 1383 nurses (77%female) were collected. Controlling for demographic variables and non-linearity of the associations between job characteristics and outcomes (job satisfaction; burnout dimensions, psychological distress, and somatic complaints), hierarchical regression analyses indicated that job control and social support combined additively (p < 0.001) with job demands to explain the wellbeing outcomes (explained variance between 6% and 28%). Coping strategies accounted for additional variance (p < 0.001; explained variance between 4% and 15%) in all outcomes except in job satisfaction. Support was found for main effects of coping. Coping strategies did not moderate the impact of job characteristics on burnout and wellbeing. Emotion-oriented coping emerged as the most important predictor and was consistently associated with higher burnout levels and lower wellbeing levels. The results demonstrated the need to include the role of individual variables in the JDCS model. The limitations of the study, and theoretical and practical implications are discussed.

Optimization-based power management of hybrid power systems with applications in advanced hybrid electric vehicles and wind farms with battery storage

NASA Astrophysics Data System (ADS)

Borhan, Hoseinali

Modern hybrid electric vehicles and many stationary renewable power generation systems combine multiple power generating and energy storage devices to achieve an overall system-level efficiency and flexibility which is higher than their individual components. The power or energy management control, "brain" of these "hybrid" systems, determines adaptively and based on the power demand the power split between multiple subsystems and plays a critical role in overall system-level efficiency. This dissertation proposes that a receding horizon optimal control (aka Model Predictive Control) approach can be a natural and systematic framework for formulating this type of power management controls. More importantly the dissertation develops new results based on the classical theory of optimal control that allow solving the resulting optimal control problem in real-time, in spite of the complexities that arise due to several system nonlinearities and constraints. The dissertation focus is on two classes of hybrid systems: hybrid electric vehicles in the first part and wind farms with battery storage in the second part. The first part of the dissertation proposes and fully develops a real-time optimization-based power management strategy for hybrid electric vehicles. Current industry practice uses rule-based control techniques with "else-then-if" logic and look-up maps and tables in the power management of production hybrid vehicles. These algorithms are not guaranteed to result in the best possible fuel economy and there exists a gap between their performance and a minimum possible fuel economy benchmark. Furthermore, considerable time and effort are spent calibrating the control system in the vehicle development phase, and there is little flexibility in real-time handling of constraints and re-optimization of the system operation in the event of changing operating conditions and varying parameters. In addition, a proliferation of different powertrain configurations may result in the need for repeated control system redesign. To address these shortcomings, we formulate the power management problem as a nonlinear and constrained optimal control problem. Solution of this optimal control problem in real-time on chronometric- and memory-constrained automotive microcontrollers is quite challenging; this computational complexity is due to the highly nonlinear dynamics of the powertrain subsystems, mixed-integer switching modes of their operation, and time-varying and nonlinear hard constraints that system variables should satisfy. The main contribution of the first part of the dissertation is that it establishes methods for systematic and step-by step improvements in fuel economy while maintaining the algorithmic computational requirements in a real-time implementable framework. More specifically a linear time-varying model predictive control approach is employed first which uses sequential quadratic programming to find sub-optimal solutions to the power management problem. Next the objective function is further refined and broken into a short and a long horizon segments; the latter approximated as a function of the state using the connection between the Pontryagin minimum principle and Hamilton-Jacobi-Bellman equations. The power management problem is then solved using a nonlinear MPC framework with a dynamic programming solver and the fuel economy is further improved. Typical simplifying academic assumptions are minimal throughout this work, thanks to close collaboration with research scientists at Ford research labs and their stringent requirement that the proposed solutions be tested on high-fidelity production models. Simulation results on a high-fidelity model of a hybrid electric vehicle over multiple standard driving cycles reveal the potential for substantial fuel economy gains. To address the control calibration challenges, we also present a novel and fast calibration technique utilizing parallel computing techniques. ^ The second part of this dissertation presents an optimization-based control strategy for the power management of a wind farm with battery storage. The strategy seeks to minimize the error between the power delivered by the wind farm with battery storage and the power demand from an operator. In addition, the strategy attempts to maximize battery life. The control strategy has two main stages. The first stage produces a family of control solutions that minimize the power error subject to the battery constraints over an optimization horizon. These solutions are parameterized by a given value for the state of charge at the end of the optimization horizon. The second stage screens the family of control solutions to select one attaining an optimal balance between power error and battery life. The battery life model used in this stage is a weighted Amp-hour (Ah) throughput model. The control strategy is modular, allowing for more sophisticated optimization models in the first stage, or more elaborate battery life models in the second stage. The strategy is implemented in real-time in the framework of Model Predictive Control (MPC).

Modeling in the quality by design environment: Regulatory requirements and recommendations for design space and control strategy appointment.

PubMed

Djuris, Jelena; Djuric, Zorica

2017-11-30

Mathematical models can be used as an integral part of the quality by design (QbD) concept throughout the product lifecycle for variety of purposes, including appointment of the design space and control strategy, continual improvement and risk assessment. Examples of different mathematical modeling techniques (mechanistic, empirical and hybrid) in the pharmaceutical development and process monitoring or control are provided in the presented review. In the QbD context, mathematical models are predominantly used to support design space and/or control strategies. Considering their impact to the final product quality, models can be divided into the following categories: high, medium and low impact models. Although there are regulatory guidelines on the topic of modeling applications, review of QbD-based submission containing modeling elements revealed concerns regarding the scale-dependency of design spaces and verification of models predictions at commercial scale of manufacturing, especially regarding real-time release (RTR) models. Authors provide critical overview on the good modeling practices and introduce concepts of multiple-unit, adaptive and dynamic design space, multivariate specifications and methods for process uncertainty analysis. RTR specification with mathematical model and different approaches to multivariate statistical process control supporting process analytical technologies are also presented. Copyright © 2017 Elsevier B.V. All rights reserved.

Interventions for the prediction and management of chronic postsurgical pain after total knee replacement: systematic review of randomised controlled trials

PubMed Central

Beswick, Andrew D; Wylde, Vikki; Gooberman-Hill, Rachael

2015-01-01

Objectives Total knee replacement can be a successful operation for pain relief. However, 10–34% of patients experience chronic postsurgical pain. Our aim was to synthesise evidence on the effectiveness of applying predictive models to guide preventive treatment, and for interventions in the management of chronic pain after total knee replacement. Setting We conducted a systematic review of randomised controlled trials using appropriate search strategies in the Cochrane Library, MEDLINE and EMBASE from inception to October 2014. No language restrictions were applied. Participants Adult patients receiving total knee replacement. Interventions Predictive models to guide treatment for prevention of chronic pain. Interventions for management of chronic pain. Primary and secondary outcome measures Reporting of specific outcomes was not an eligibility criterion but we sought outcomes relating to pain severity. Results No studies evaluated the effectiveness of predictive models in guiding treatment and improving outcomes after total knee replacement. One study evaluated an intervention for the management of chronic pain. The trial evaluated the use of a botulinum toxin A injection with antinociceptive and anticholinergic activity in 49 patients with chronic postsurgical pain after knee replacement. A single injection provided meaningful pain relief for about 40 days and the authors acknowledged the need for a large trial with repeated injections. No trials of multidisciplinary interventions or individualised treatments were identified. Conclusions Our systematic review highlights a lack of evidence about the effectiveness of prediction and management strategies for chronic postsurgical pain after total knee replacement. As a large number of people are affected by chronic pain after total knee replacement, development of an evidence base about care for these patients should be a research priority. PMID:25967998

Modeling Dynamics of Culex pipiens Complex Populations and Assessing Abatement Strategies for West Nile Virus

PubMed Central

Pawelek, Kasia A.; Hager, Elizabeth J.; Hunt, Gregg J.

2014-01-01

The primary mosquito species associated with underground stormwater systems in the United States are the Culex pipiens complex species. This group represents important vectors of West Nile virus (WNV) throughout regions of the continental U.S. In this study, we designed a mathematical model and compared it with surveillance data for the Cx. pipiens complex collected in Beaufort County, South Carolina. Based on the best fit of the model to the data, we estimated parameters associated with the effectiveness of public health insecticide (adulticide) treatments (primarily pyrethrin products) as well as the birth, maturation, and death rates of immature and adult Cx. pipiens complex mosquitoes. We used these estimates for modeling the spread of WNV to obtain more reliable disease outbreak predictions and performed numerical simulations to test various mosquito abatement strategies. We demonstrated that insecticide treatments produced significant reductions in the Cx. pipiens complex populations. However, abatement efforts were effective for approximately one day and the vector mosquitoes rebounded until the next treatment. These results suggest that frequent insecticide applications are necessary to control these mosquitoes. We derived the basic reproductive number (ℜ0) to predict the conditions under which disease outbreaks are likely to occur and to evaluate mosquito abatement strategies. We concluded that enhancing the mosquito death rate results in lower values of ℜ0, and if ℜ0<1, then an epidemic will not occur. Our modeling results provide insights about control strategies of the vector populations and, consequently, a potential decrease in the risk of a WNV outbreak. PMID:25268229

The insertion of human dynamics models in the flight control loops of V/STOL research aircraft. Appendix 2: The optimal control model of a pilot in V/STOL aircraft control loops

NASA Technical Reports Server (NTRS)

Zipf, Mark E.

1989-01-01

An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.

Added Value of Avian Influenza (H5) Day-Old Chick Vaccination for Disease Control in Egypt.

PubMed

Peyre, Marisa; Choisy, Marc; Sobhy, Heba; Kilany, Walid H; Gély, Marie; Tripodi, Astrid; Dauphin, Gwenaëlle; Saad, Mona; Roger, François; Lubroth, Juan; Jobre, Yilma

2016-05-01

The immunity profile against H5N1 highly pathogenic avian influenza (HPAI) in the commercial poultry value chain network in Egypt was modeled with the use of different vaccination scenarios. The model estimated the vaccination coverage, the protective seroconversion level, and the duration of immunity for each node of the network and vaccination scenario. Partial budget analysis was used to compare the benefit-cost of the different vaccination scenarios. The model predicted that targeting day-old chick avian influenza (AI) vaccination in industrial and large hatcheries would increase immunity levels in the overall poultry population in Egypt and especially in small commercial poultry farms (from <30% to >60%). This strategy was shown to be more efficient than the current strategy of using inactivated vaccines. Improving HPAI control in the commercial poultry sector in Egypt would have a positive impact to improve disease control.

Flight Mechanics Symposium 1997

NASA Technical Reports Server (NTRS)

Walls, Donna M. (Editor)

1997-01-01

This conference publication includes papers and abstracts presented at the Flight Mechanics Symposium. This symposium featured technical papers on a wide range of issues related to orbit-attitude prediction, determination, and control; attitude sensor calibration; attitude determination error analysis; attitude dynamics; and orbit decay and maneuver strategy. Government, industry, and the academic community participated in the preparation and presentation of these papers.

Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency

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

Ramachandran, Thiagarajan; Kundu, Soumya; Chen, Yan

This paper develops and utilizes an optimization based framework to investigate the maximal energy efficiency potentially attainable by HVAC system operation in a non-predictive context. Performance is evaluated relative to the existing state of the art set point reset strategies. The expected efficiency increase driven by operation constraints relaxations is evaluated.

Towards a framework for selection of supervisory control for commercial buildings: HVAC system energy efficiency

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

Ramachandran, Thiagarajan; Kundu, Soumya; Chen, Yan

This paper develops and utilizes an optimization based framework to investigate the maximal energy efficiency potentially attainable by HVAC system operation in a non-predictive context. Performance is evaluated relative to the existing state of the art set-point reset strategies. The expected efficiency increase driven by operation constraints relaxations is evaluated.

Visual Compensatory Tracking Performance after Exposure to Flashblinding Pulses. I. Comparison of Human and Rhesus Monkey Subjects

DTIC Science & Technology

1981-04-01

If different Irom Report) 18. SUPPLEMENTARY NOTES 19. KEY WOROS rContlnuo nrn rever.se ., vde it nee.ssary and rdenrlfy hv brock number) Flashbl...control strategy plays a minor or secondary role in predicting the effects of an insult to the system would be more acceptable. CONCLUSIONS Humans and

Coping with Discrimination: The Subjective Well-Being of South Asian American Women

ERIC Educational Resources Information Center

Liang, Christopher T. H.; Nathwani, Anisha; Ahmad, Sarah; Prince, Jessica K.

2010-01-01

The relationship between coping strategies used by South Asian American women and subjective well-being (SWB) was studied. Second-generation women were found to use more support compared with 1st-generation women. Problem-solving coping was inversely related to age. Avoidance coping was found to predict SWB when controlling for age and…

Prediction, Assessment of the Rift Valley fever Activity in East and Southern Africa 2006 - 2008 and Possible Vector Control Strategies

USDA-ARS?s Scientific Manuscript database

Historical outbreaks of Rift Valley fever (RVF) since the early 1950s have been associated with cyclical patterns of the El Nino/Southern Oscillation (ENSO) phenomenon which results in elevated and widespread rainfall over the RVF endemic areas of Africa. Using satellite measurements of global and ...

Non-fragile observer-based output feedback control for polytopic uncertain system under distributed model predictive control approach

NASA Astrophysics Data System (ADS)

Zhu, Kaiqun; Song, Yan; Zhang, Sunjie; Zhong, Zhaozhun

2017-07-01

In this paper, a non-fragile observer-based output feedback control problem for the polytopic uncertain system under distributed model predictive control (MPC) approach is discussed. By decomposing the global system into some subsystems, the computation complexity is reduced, so it follows that the online designing time can be saved.Moreover, an observer-based output feedback control algorithm is proposed in the framework of distributed MPC to deal with the difficulties in obtaining the states measurements. In this way, the presented observer-based output-feedback MPC strategy is more flexible and applicable in practice than the traditional state-feedback one. What is more, the non-fragility of the controller has been taken into consideration in favour of increasing the robustness of the polytopic uncertain system. After that, a sufficient stability criterion is presented by using Lyapunov-like functional approach, meanwhile, the corresponding control law and the upper bound of the quadratic cost function are derived by solving an optimisation subject to convex constraints. Finally, some simulation examples are employed to show the effectiveness of the method.

Strategic modulation of cognitive control.

PubMed

Lungu, Ovidiu V; Liu, Tao; Waechter, Tobias; Willingham, Daniel T; Ashe, James

2007-08-01

The neural substrate of cognitive control is thought to comprise an evaluative component located in the anterior cingulate cortex (ACC) and an executive component in the prefrontal cortex (PFC). The control mechanism itself is mainly local, triggered by response conflict (monitored by the ACC) and involving the allocation of executive resources (recruited by the PFC) in a trial-to-trial fashion. However, another way to achieve control would be to use a strategic mechanism based on long-term prediction of upcoming events and on a chronic response strategy that ignores local features of the task. In the current study, we showed that such a strategic control mechanism was based on a functional dissociation or complementary relationship between the ACC and the PFC. When information in the environment was available to make predictions about upcoming stimuli, local task features (e.g., response conflict) were no longer used as a control signal. We suggest that having separate control mechanisms based on local or global task features allows humans to be persistent in pursuing their goals, yet flexible enough to adapt to changes in the environment.

Alcohol self-control behaviors of adolescents.

PubMed

Glassman, Tavis; Werch, Chudley Chad; Jobli, Edessa

2007-03-01

The aims of the present study were to: (1) factor analyze a 13-item adolescent alcohol self-control behavior scale, (2) examine associations between frequency of self-control behavior use and alcohol consumption, and (3) to determine which self-control behaviors best predict alcohol use and consequences. A confidential standardized survey was used to collect data on participant's 30-day frequency, quantity, and heavy use of alcohol; alcohol-related consequences; and alcohol self-control behaviors. A principal component factor analysis produced the following three components: Healthy Alternatives (alpha=.81), Self-regulation (alpha=.72), and Assertive Communication (alpha=.73). MANOVAs indicated strong associations between frequency of use of the three types of self-control behaviors and alcohol consumption (p values< or =.001). Logistic regression analysis revealed that Self-regulation behaviors were the best predictor for all alcohol use measures and consequences (p values< or =.001). Self-control behaviors differ in their ability to predict alcohol use and consequences. Self-regulation strategies emerged as the most consistent predictor of alcohol use patterns and consequences among adolescents, followed by Healthy Alternatives.

RRCRank: a fusion method using rank strategy for residue-residue contact prediction.

PubMed

Jing, Xiaoyang; Dong, Qiwen; Lu, Ruqian

2017-09-02

In structural biology area, protein residue-residue contacts play a crucial role in protein structure prediction. Some researchers have found that the predicted residue-residue contacts could effectively constrain the conformational search space, which is significant for de novo protein structure prediction. In the last few decades, related researchers have developed various methods to predict residue-residue contacts, especially, significant performance has been achieved by using fusion methods in recent years. In this work, a novel fusion method based on rank strategy has been proposed to predict contacts. Unlike the traditional regression or classification strategies, the contact prediction task is regarded as a ranking task. First, two kinds of features are extracted from correlated mutations methods and ensemble machine-learning classifiers, and then the proposed method uses the learning-to-rank algorithm to predict contact probability of each residue pair. First, we perform two benchmark tests for the proposed fusion method (RRCRank) on CASP11 dataset and CASP12 dataset respectively. The test results show that the RRCRank method outperforms other well-developed methods, especially for medium and short range contacts. Second, in order to verify the superiority of ranking strategy, we predict contacts by using the traditional regression and classification strategies based on the same features as ranking strategy. Compared with these two traditional strategies, the proposed ranking strategy shows better performance for three contact types, in particular for long range contacts. Third, the proposed RRCRank has been compared with several state-of-the-art methods in CASP11 and CASP12. The results show that the RRCRank could achieve comparable prediction precisions and is better than three methods in most assessment metrics. The learning-to-rank algorithm is introduced to develop a novel rank-based method for the residue-residue contact prediction of proteins, which achieves state-of-the-art performance based on the extensive assessment.

Impact of edge removal on the centrality betweenness of the best spreaders

NASA Astrophysics Data System (ADS)

Chung, N. N.; Chew, L. Y.; Zhou, J.; Lai, C. H.

2012-06-01

The control of epidemic spreading is essential to avoid potential fatal consequences and also, to lessen the unforeseen socio-economic impact. The need for effective control is exemplified during the severe acute respiratory syndrome (SARS) epidemy in 2003, which has inflicted nearly a thousand deaths as well as bankruptcies of airlines and related businesses. In this article, we examine the efficacy of control strategies on the propagation of infectious diseases based on removing connections within real-world airline networks with the associated economic and social costs taken into account through defining appropriate quantitative measures. We uncover the surprising results that removing less busy connections can be far more effective in hindering the spread of the disease than removing the more popular connections. Since disconnecting the less popular routes tends to incur less socio-economic cost, our finding suggests the possibility of trading minimal reduction in connectivity of an important hub with efficiencies in epidemic control. In particular, we demonstrate the performance of various local epidemic control strategies, and show how our approach can predict their cost effectiveness through the spreading control characteristics.

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

Simpson, L.; Britt, J.; Birkmire, R.

ITN Energy Systems, Inc., and Global Solar Energy, Inc., assisted by NREL's PV Manufacturing R&D program, have continued to advance CIGS production technology by developing trajectory-oriented predictive/control models, fault-tolerance control, control platform development, in-situ sensors, and process improvements. Modeling activities included developing physics-based and empirical models for CIGS and sputter-deposition processing, implementing model-based control, and applying predictive models to the construction of new evaporation sources and for control. Model-based control is enabled by implementing reduced or empirical models into a control platform. Reliability improvement activities include implementing preventive maintenance schedules; detecting failed sensors/equipment and reconfiguring to tinue processing; and systematicmore » development of fault prevention and reconfiguration strategies for the full range of CIGS PV production deposition processes. In-situ sensor development activities have resulted in improved control and indicated the potential for enhanced process status monitoring and control of the deposition processes. Substantial process improvements have been made, including significant improvement in CIGS uniformity, thickness control, efficiency, yield, and throughput. In large measure, these gains have been driven by process optimization, which in turn have been enabled by control and reliability improvements due to this PV Manufacturing R&D program.« less

Evaluation of plant-wide WWTP control strategies including the effects of filamentous bulking sludge.

PubMed

Flores-Alsina, Xavier; Comas, Joaquim; Rodríguez Roda, Ignasi; Poch, Manel; Gernaey, Krist V; Jeppsson, Ulf

2009-01-01

The main objective of this paper is to evaluate the effect of filamentous bulking sludge on the predicted performance of simulated plant-wide WWTP control strategies. First, as a reference case, several control strategies are implemented, simulated and evaluated using the IWA Benchmark Simulation Model No. 2 (BSM2). In a second series of simulations the parameters of the secondary settler model in the BSM2 are automatically changed on the basis of an on-line calculated risk of filamentous bulking, in order to mimic the effect of growth of filamentous bacteria in the plant. The results are presented using multivariate analysis. Including the effects of filamentous bulking in the simulation model gives a-more realistic-deterioration of the plant performance during periods when the conditions for development of filamentous bulking sludge are favourable: compared to the reference case where bulking effects are not considered. Thus, there is a decrease of the overall settling velocity, an accumulation of the total suspended solids (TSS) in the middle layers of the settler with a consequent reduction of their degree of compaction in the bottom. As a consequence there is a lower TSS concentration in both return and waste flow, less biomass in the bioreactors and a reduction of the TSS removal efficiency. The control alternatives using a TSS controller substantially increase the food to microorganisms (F/M) ratio in the bioreactor, thereby reducing both risk and effects of bulking sludge. The effects of ammonium (NH(4)(+)), nitrate (NO(3)(-)) and reject water control strategies are rather poor when it comes to handling solids separation problems.

Rational adaptation under task and processing constraints: implications for testing theories of cognition and action.

PubMed

Howes, Andrew; Lewis, Richard L; Vera, Alonso

2009-10-01

The authors assume that individuals adapt rationally to a utility function given constraints imposed by their cognitive architecture and the local task environment. This assumption underlies a new approach to modeling and understanding cognition-cognitively bounded rational analysis-that sharpens the predictive acuity of general, integrated theories of cognition and action. Such theories provide the necessary computational means to explain the flexible nature of human behavior but in doing so introduce extreme degrees of freedom in accounting for data. The new approach narrows the space of predicted behaviors through analysis of the payoff achieved by alternative strategies, rather than through fitting strategies and theoretical parameters to data. It extends and complements established approaches, including computational cognitive architectures, rational analysis, optimal motor control, bounded rationality, and signal detection theory. The authors illustrate the approach with a reanalysis of an existing account of psychological refractory period (PRP) dual-task performance and the development and analysis of a new theory of ordered dual-task responses. These analyses yield several novel results, including a new understanding of the role of strategic variation in existing accounts of PRP and the first predictive, quantitative account showing how the details of ordered dual-task phenomena emerge from the rational control of a cognitive system subject to the combined constraints of internal variance, motor interference, and a response selection bottleneck.

Impaired sequential and partially compensated probabilistic skill learning in Parkinson's disease.

PubMed

Kemény, Ferenc; Demeter, Gyula; Racsmány, Mihály; Valálik, István; Lukács, Ágnes

2018-06-08

The striatal dopaminergic dysfunction in Parkinson's disease (PD) has been associated with deficits in skill learning in numerous studies, but some of the findings remain controversial. Our aim was to explore the generality of the learning deficit using two widely reported skill learning tasks in the same group of Parkinson's patients. Thirty-four patients with PD (mean age: 62.83 years, SD: 7.67) were compared to age-matched healthy adults. Two tasks were employed: the Serial Reaction Time Task (SRT), testing the learning of motor sequences, and the Weather Prediction (WP) task, testing non-sequential probabilistic category learning. On the SRT task, patients with PD showed no significant evidence for sequence learning. These results support and also extend previous findings, suggesting that motor skill learning is vulnerable in PD. On the WP task, the PD group showed the same amount of learning as controls, but they exploited qualitatively different strategies in predicting the target categories. While controls typically combined probabilities from multiple predicting cues, patients with PD instead focused on individual cues. We also found moderate to high correlations between the different measures of skill learning. These findings support our hypothesis that skill learning is generally impaired in PD, and can in some cases be compensated by relying on alternative learning strategies. © 2018 The Authors. Journal of Neuropsychology published by John Wiley & Sons Ltd on behalf of British Psychological Society.

Mind-sets matter: a meta-analytic review of implicit theories and self-regulation.

PubMed

Burnette, Jeni L; O'Boyle, Ernest H; VanEpps, Eric M; Pollack, Jeffrey M; Finkel, Eli J

2013-05-01

This review builds on self-control theory (Carver & Scheier, 1998) to develop a theoretical framework for investigating associations of implicit theories with self-regulation. This framework conceptualizes self-regulation in terms of 3 crucial processes: goal setting, goal operating, and goal monitoring. In this meta-analysis, we included articles that reported a quantifiable assessment of implicit theories and at least 1 self-regulatory process or outcome. With a random effects approach used, meta-analytic results (total unique N = 28,217; k = 113) across diverse achievement domains (68% academic) and populations (age range = 5-42; 10 different nationalities; 58% from United States; 44% female) demonstrated that implicit theories predict distinct self-regulatory processes, which, in turn, predict goal achievement. Incremental theories, which, in contrast to entity theories, are characterized by the belief that human attributes are malleable rather than fixed, significantly predicted goal setting (performance goals, r = -.151; learning goals, r = .187), goal operating (helpless-oriented strategies, r = -.238; mastery-oriented strategies, r = .227), and goal monitoring (negative emotions, r = -.233; expectations, r = .157). The effects for goal setting and goal operating were stronger in the presence (vs. absence) of ego threats such as failure feedback. Discussion emphasizes how the present theoretical analysis merges an implicit theory perspective with self-control theory to advance scholarship and unlock major new directions for basic and applied research.

Further validation of artificial neural network-based emissions simulation models for conventional and hybrid electric vehicles.

PubMed

Tóth-Nagy, Csaba; Conley, John J; Jarrett, Ronald P; Clark, Nigel N

2006-07-01

With the advent of hybrid electric vehicles, computer-based vehicle simulation becomes more useful to the engineer and designer trying to optimize the complex combination of control strategy, power plant, drive train, vehicle, and driving conditions. With the desire to incorporate emissions as a design criterion, researchers at West Virginia University have developed artificial neural network (ANN) models for predicting emissions from heavy-duty vehicles. The ANN models were trained on engine and exhaust emissions data collected from transient dynamometer tests of heavy-duty diesel engines then used to predict emissions based on engine speed and torque data from simulated operation of a tractor truck and hybrid electric bus. Simulated vehicle operation was performed with the ADVISOR software package. Predicted emissions (carbon dioxide [CO2] and oxides of nitrogen [NO(x)]) were then compared with actual emissions data collected from chassis dynamometer tests of similar vehicles. This paper expands on previous research to include different driving cycles for the hybrid electric bus and varying weights of the conventional truck. Results showed that different hybrid control strategies had a significant effect on engine behavior (and, thus, emissions) and may affect emissions during different driving cycles. The ANN models underpredicted emissions of CO2 and NO(x) in the case of a class-8 truck but were more accurate as the truck weight increased.

A Blueprint for a Synthetic Genetic Feedback Controller to Reprogram Cell Fate.

PubMed

Del Vecchio, Domitilla; Abdallah, Hussein; Qian, Yili; Collins, James J

2017-01-25

To artificially reprogram cell fate, experimentalists manipulate the gene regulatory networks (GRNs) that maintain a cell's phenotype. In practice, reprogramming is often performed by constant overexpression of specific transcription factors (TFs). This process can be unreliable and inefficient. Here, we address this problem by introducing a new approach to reprogramming based on mathematical analysis. We demonstrate that reprogramming GRNs using constant overexpression may not succeed in general. Instead, we propose an alternative reprogramming strategy: a synthetic genetic feedback controller that dynamically steers the concentration of a GRN's key TFs to any desired value. The controller works by adjusting TF expression based on the discrepancy between desired and actual TF concentrations. Theory predicts that this reprogramming strategy is guaranteed to succeed, and its performance is independent of the GRN's structure and parameters, provided that feedback gain is sufficiently high. As a case study, we apply the controller to a model of induced pluripotency in stem cells. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Quality of life of French Canadian parents raising a child with autism spectrum disorder and effects of psychosocial factors.

PubMed

Cappe, Émilie; Poirier, Nathalie; Sankey, Carol; Belzil, Andréa; Dionne, Carmen

2018-04-01

This study aimed to investigate the quality of life of parents of a child with autism spectrum disorder in Quebec. Seventy-seven participants completed a questionnaire with socio-biographic information and five self-assessed scales, to measure perceived stress, social support and control, coping strategies, and quality of life. Perception of their child's autonomy level, of the severity of the disorder, of the family's income, as well as changes in their professional or familial organization influenced parents' quality of life. Perceiving their situation as a threat predicted poor quality of life, whereas satisfaction of social support predicted good quality of life. In addition, parents who used problem solving and support-seeking coping strategies had a better relationship with their child, whereas those who used more emotion-centered coping strategies struggled. Lastly, parents who felt they had the power to contribute to their child's development were more satisfied and less disturbed. Beyond the parents' actual situation, our results underscore the importance of paying attention to their own perception of the situation in order to provide them with appropriate support.

Computer-aided rational design of the phosphotransferase system for enhanced glucose uptake in Escherichia coli

PubMed Central

Nishio, Yousuke; Usuda, Yoshihiro; Matsui, Kazuhiko; Kurata, Hiroyuki

2008-01-01

The phosphotransferase system (PTS) is the sugar transportation machinery that is widely distributed in prokaryotes and is critical for enhanced production of useful metabolites. To increase the glucose uptake rate, we propose a rational strategy for designing the molecular architecture of the Escherichia coli glucose PTS by using a computer-aided design (CAD) system and verified the simulated results with biological experiments. CAD supports construction of a biochemical map, mathematical modeling, simulation, and system analysis. Assuming that the PTS aims at controlling the glucose uptake rate, the PTS was decomposed into hierarchical modules, functional and flux modules, and the effect of changes in gene expression on the glucose uptake rate was simulated to make a rational strategy of how the gene regulatory network is engineered. Such design and analysis predicted that the mlc knockout mutant with ptsI gene overexpression would greatly increase the specific glucose uptake rate. By using biological experiments, we validated the prediction and the presented strategy, thereby enhancing the specific glucose uptake rate. PMID:18197177

Self-focus, other-focus, and interpersonal needs as correlates of loneliness.

PubMed

Green, V A; Wildermuth, N L

1993-12-01

Residential college students (44 men, 51 women) participated in a questionnaire study to clarify the relationship between loneliness, self- or other-focus, and interpersonal needs. Contrary to predictions, loneliness was unrelated to self-focus, other-focus, or the ability to elicit disclosure from others. However, sex differences were found on interpersonal needs. Specifically, loneliness in men was predicted by a lack of expressed inclusion and a desire for control from others, while loneliness in women was predicted by a lack of expressed affection. These findings suggest that lonely men and women may benefit from different intervention strategies. Outcome studies are needed to ensure that such interventions actually reduce loneliness.

Predicting Effects of Psychological Inflexibility/Experiential Avoidance and Stress Coping Strategies for Internet Addiction, Significant Depression, and Suicidality in College Students: A Prospective Study.

PubMed

Chou, Wei-Po; Yen, Cheng-Fang; Liu, Tai-Ling

2018-04-18

The aims of this study were to evaluate the predicting effects of psychological inflexibility/experiential avoidance (PI/EA) and stress coping strategies for Internet addiction, significant depression and suicidality among college students during the follow-up period of one year. A total of 500 college students participated in this study. The level of PI/EA and stress coping strategies were evaluated initially. One year later, 324 participants were invited to complete the Chen Internet Addiction Scale, Beck Depression Inventory-II and the questionnaire for suicidality to evaluate depression symptoms and internet addiction and suicidality. The predicting effects of PI/EA and stress coping strategies were examined by using logistic regression analysis controlling for the effects of gender and age. The results indicated that PI/EA at the initial assessment increased the risk of Internet addiction (OR = 1.087, 95% CI: 1.042–1.135), significant depression (OR = 1.125, 95% CI: 1.081–1.170), and suicidality (OR = 1.099, 95% CI: 1.053–1.147) at the follow-up assessment. Less effective coping at the initial assessment also increased the risk of Internet addiction (OR = 1.074, 95% CI: 1.011–1.140), significant depression (OR = 1.091, 95% CI: 1.037–1.147), and suicidality (OR = 1.074, 95% CI: 1.014–1.138) at the follow-up assessment. Problem focused and emotion-focus coping at the initial assessment was not significantly associated with the risks of Internet addiction, significant depression, and suicidality at the follow-up assessment. College students who have high PI/EA or are accustomed to using less effective stress coping strategies should be the target of prevention programs for IA (internet addiction), depression, and suicidality.

The role of free-play physical activity in healthy blood glucose maintenance in children with type 1 diabetes mellitus.

PubMed

Marrone, Sonia; Plume, Jessica White; Kerr, Patrick; Pignol, Anna; Vogeltanz-Holm, Nancy; Holm, Jeffrey; Larsen, Margo Adams

2009-01-01

Medical management for children with type 1 diabetes mellitus, including insulin administration to control high blood glucose levels (BGL), is crucial. However, a child-controlled behavioural strategy, like physical activity, to maintain target BGL may be warranted. To demonstrate, pre- and post-activity BGL were collected for 73 children aged 8- to 14-years attending a diabetes camp. Change in BGL across one session of a free-play swimming activity was analysed. Average BGL was significantly reduced from 197.18 mg/dl to 177.78 mg/dl across one 45 min session, and male gender predicted larger reductions. With safety precautions and within the context of appropriate medical management, free-play activity could be used as a strategy for maintaining target BGL.

Spatial Map of Synthesized Criteria for the Redundancy Resolution of Human Arm Movements.

PubMed

Li, Zhi; Milutinovic, Dejan; Rosen, Jacob

2015-11-01

The kinematic redundancy of the human arm enables the elbow position to rotate about the axis going through the shoulder and wrist, which results in infinite possible arm postures when the arm reaches to a target in a 3-D workspace. To infer the control strategy the human motor system uses to resolve redundancy in reaching movements, this paper compares five redundancy resolution criteria and evaluates their arm posture prediction performance using data on healthy human motion. Two synthesized criteria are developed to provide better real-time arm posture prediction than the five individual criteria. Of these two, the criterion synthesized using an exponential method predicts the arm posture more accurately than that using a least squares approach, and therefore is preferable for inferring the contributions of the individual criteria to motor control during reaching movements. As a methodology contribution, this paper proposes a framework to compare and evaluate redundancy resolution criteria for arm motion control. A cluster analysis which associates criterion contributions with regions of the workspace provides a guideline for designing a real-time motion control system applicable to upper-limb exoskeletons for stroke rehabilitation.

Rational Design and Tuning of Functional RNA Switch to Control an Allosteric Intermolecular Interaction.

PubMed

Endoh, Tamaki; Sugimoto, Naoki

2015-08-04

Conformational transitions of biomolecules in response to specific stimuli control many biological processes. In natural functional RNA switches, often called riboswitches, a particular RNA structure that has a suppressive or facilitative effect on gene expression transitions to an alternative structure with the opposite effect upon binding of a specific metabolite to the aptamer region. Stability of RNA secondary structure (-ΔG°) can be predicted based on thermodynamic parameters and is easily tuned by changes in nucleobases. We envisioned that tuning of a functional RNA switch that causes an allosteric interaction between an RNA and a peptide would be possible based on a predicted switching energy (ΔΔG°) that corresponds to the energy difference between the RNA secondary structure before (-ΔG°before) and after (-ΔG°after) the RNA conformational transition. We first selected functional RNA switches responsive to neomycin with predicted ΔΔG° values ranging from 5.6 to 12.2 kcal mol(-1). We then demonstrated a simple strategy to rationally convert the functional RNA switch to switches responsive to natural metabolites thiamine pyrophosphate, S-adenosyl methionine, and adenine based on the predicted ΔΔG° values. The ΔΔG° values of the designed RNA switches proportionally correlated with interaction energy (ΔG°interaction) between the RNA and peptide, and we were able to tune the sensitivity of the RNA switches for the trigger molecule. The strategy demonstrated here will be generally applicable for construction of functional RNA switches and biosensors in which mechanisms are based on conformational transition of nucleic acids.

High-throughput prediction of tablet weight and trimethoprim content of compound sulfamethoxazole tablets for controlling the uniformity of dosage units by NIR.

PubMed

Dong, Yanhong; Li, Juan; Zhong, Xiaoxiao; Cao, Liya; Luo, Yang; Fan, Qi

2016-04-15

This paper establishes a novel method to simultaneously predict the tablet weight (TW) and trimethoprim (TMP) content of compound sulfamethoxazole tablets (SMZCO) by near infrared (NIR) spectroscopy with partial least squares (PLS) regression for controlling the uniformity of dosage units (UODU). The NIR spectra for 257 samples were measured using the optimized parameter values and pretreated using the optimized chemometric techniques. After the outliers were ignored, two PLS models for predicting TW and TMP content were respectively established by using the selected spectral sub-ranges and the reference values. The TW model reaches the correlation coefficient of calibration (R(c)) 0.9543 and the TMP content model has the R(c) 0.9205. The experimental results indicate that this strategy expands the NIR application in controlling UODU, especially in the high-throughput and rapid analysis of TWs and contents of the compound pharmaceutical tablets, and may be an important complement to the common NIR on-line analytical method for pharmaceutical tablets. Copyright © 2016 Elsevier B.V. All rights reserved.

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

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

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-01-07

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

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

Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming

2013-04-03

Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive controlmore » (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.« less

Kinetically Controlled Lifetimes in Redox-Responsive Transient Supramolecular Hydrogels.

PubMed

Wojciechowski, Jonathan P; Martin, Adam D; Thordarson, Pall

2018-02-28

It remains challenging to program soft materials to show dynamic, tunable time-dependent properties. In this work, we report a strategy to design transient supramolecular hydrogels based on kinetic control of competing reactions. Specifically, the pH-triggered self-assembly of a redox-active supramolecular gelator, N,N'-dibenzoyl-l-cystine (DBC) in the presence of a reducing agent, which acts to disassemble the system. The lifetimes of the transient hydrogels can be tuned simply by pH or reducing agent concentration. We find through kinetic analysis that gel formation hinders the ability of the reducing agent and enables longer transient hydrogel lifetimes than would be predicted. The transient hydrogels undergo clean cycles, with no kinetically trapped aggregates observed. As a result, multiple transient hydrogel cycles are demonstrated and can be predicted. This work contributes to our understanding of designing transient assemblies with tunable temporal control.

Identity processes and coping strategies in college students: short-term longitudinal dynamics and the role of personality.

PubMed

Luyckx, Koen; Klimstra, Theo A; Duriez, Bart; Schwartz, Seth J; Vanhalst, Janne

2012-09-01

Coping strategies and identity processes are hypothesized to influence one another over time. This three-wave longitudinal study (N = 458; 84.9% women) examined, for the first time, how and to what extent identity processes (i.e., commitment making, identification with commitment, exploration in breadth, exploration in depth, and ruminative exploration) and coping strategies (i.e., problem solving, social support seeking, and avoidance) predicted one another over time. Cross-lagged analyses indicated that processes of identity exploration seemed especially to be intertwined with different coping strategies over time, suggesting that identity exploration may resemble problem-solving behavior on the pathway to an achieved identity. Commitment processes were found to be influenced by certain coping strategies, although identification with commitment also negatively influenced avoidance coping. These temporal sequences remained significant when controlling for baseline levels of Big Five personality traits. Hence, evidence was obtained for reciprocal pathways indicating that coping strategies and identity processes reinforce one another over time in college students.

Near-Nash targeting strategies for heterogeneous teams of autonomous combat vehicles

NASA Astrophysics Data System (ADS)

Galati, David G.; Simaan, Marwan A.

2008-04-01

Military strategists are currently seeking methodologies to control large numbers of autonomous assets. Automated planners based upon the Nash equilibrium concept in non-zero sum games are one option. Because such planners inherently consider possible adversarial actions, assets are able to adapt to, and to some extent predict, potential enemy actions. However, these planners must function properly both in cases in which a pure Nash strategy does not exist and in scenarios possessing multiple Nash equilibria. Another issue that needs to be overcome is the scalability of the Nash equilibrium. That is, as the dimensionality of the problem increases, the Nash strategies become unfeasible to compute using traditional methodologies. In this paper we introduce the concept of near-Nash strategies as a mechanism to overcome these difficulties. We then illustrate this concept by deriving the near-Nash strategies and using these strategies as the basis for an intelligent battle plan for heterogeneous teams of autonomous combat air vehicles in the Multi-Team Dynamic Weapon Target Assignment model.

Reasoning, Learning, and Creativity: Frontal Lobe Function and Human Decision-Making

PubMed Central

Collins, Anne; Koechlin, Etienne

2012-01-01

The frontal lobes subserve decision-making and executive control—that is, the selection and coordination of goal-directed behaviors. Current models of frontal executive function, however, do not explain human decision-making in everyday environments featuring uncertain, changing, and especially open-ended situations. Here, we propose a computational model of human executive function that clarifies this issue. Using behavioral experiments, we show that unlike others, the proposed model predicts human decisions and their variations across individuals in naturalistic situations. The model reveals that for driving action, the human frontal function monitors up to three/four concurrent behavioral strategies and infers online their ability to predict action outcomes: whenever one appears more reliable than unreliable, this strategy is chosen to guide the selection and learning of actions that maximize rewards. Otherwise, a new behavioral strategy is tentatively formed, partly from those stored in long-term memory, then probed, and if competitive confirmed to subsequently drive action. Thus, the human executive function has a monitoring capacity limited to three or four behavioral strategies. This limitation is compensated by the binary structure of executive control that in ambiguous and unknown situations promotes the exploration and creation of new behavioral strategies. The results support a model of human frontal function that integrates reasoning, learning, and creative abilities in the service of decision-making and adaptive behavior. PMID:22479152

Police corruption and psychological testing: a strategy for preemployment screening.

PubMed

Arrigo, Bruce A; Claussen, Natalie

2003-06-01

The prediction, control, and prevention of police corruption represent pervasive and enduring problems. Researchers have suggested that intervention at the preemployment screening stage may be the best solution. However, investigators have acknowledged that existing assessment practices are flawed. This article proposes a strategy for the preemployment screening of law enforcement personnel. In particular, it examines the utility of the Inwald Personality Inventory and the Revised-NEO Personality Inventory in relation to assessing antisocial behavioral tendencies and conscientious personality traits, respectively, and argues that their combined use, appropriately administered in a testing situation, represents a reliable and valid predictor of good job performance. The article speculatively comments on this strategy for purposes of psychological testing, future research in the field, and law enforcement administration practices.

Decisions on control of foot-and-mouth disease informed using model predictions.

PubMed

Halasa, T; Willeberg, P; Christiansen, L E; Boklund, A; Alkhamis, M; Perez, A; Enøe, C

2013-11-01

The decision on whether or not to change the control strategy, such as introducing emergency vaccination, is perhaps one of the most difficult decisions faced by the veterinary authorities during a foot-and-mouth disease (FMD) epidemic. A simple tool that may predict the epidemic outcome and consequences would be useful to assist the veterinary authorities in the decision-making process. A previously proposed simple quantitative tool based on the first 14 days outbreaks (FFO) of FMD was used with results from an FMD simulation exercise. Epidemic outcomes included the number of affected herds, epidemic duration, geographical size and costs. The first 14 days spatial spread (FFS) was also included to further support the prediction. The epidemic data was obtained from a Danish version (DTU-DADS) of a pre-existing FMD simulation model (Davis Animal Disease Spread - DADS) adapted to model the spread of FMD in Denmark. The European Union (EU) and Danish regulations for FMD control were used in the simulation. The correlations between FFO and FFS and the additional number of affected herds after day 14 following detection of the first infected herd were 0.66 and 0.82, respectively. The variation explained by the FFO at day 14 following detection was high (P-value<0.001). This indicates that the FFO may take a part in the decision of whether or not to intensify FMD control, for instance by introducing emergency vaccination and/or pre-emptive depopulation, which might prevent a "catastrophic situation". A significant part of the variation was explained by supplementing the model with the FFS (P-value<0.001). Furthermore, the type of the index-herd was also a significant predictor of the epidemic outcomes (P-value<0.05). The results of the current study suggest that national veterinary authorities should consider to model their national situation and to use FFO and FFS to help planning and updating their contingency plans and FMD emergency control strategies. Copyright © 2013 Elsevier B.V. All rights reserved.

A Longitudinal Study of Body Change Strategies among Adolescent Males.

ERIC Educational Resources Information Center

McCabe, Marita P.; Ricciardelli, Lina A.

2003-01-01

Examined factors predicting body change strategies to increase weight and muscle mass among adolescent males over an 8-month period. Results for 435 adolescent boys show that extreme body change strategies are predicted by the adoption of more normative body change strategies at an earlier time, and that body change strategies are affected by…

Prospective associations between friendship adjustment and social strategies: friendship as a context for building social skills.

PubMed

Glick, Gary C; Rose, Amanda J

2011-07-01

The proposal that friendships provide a context for the development of social skills is widely accepted. Yet little research exists to support this claim. In the present study, children and adolescents (N = 912) were presented with vignettes in which a friend encountered a social stressor and they could help the friend and vignettes in which they encountered a stressor and could seek help from the friend. Social strategies in response to these vignettes were assessed in the fall and spring of the school year. Different indicators of friendship adjustment had unique effects on youths' strategies in response to helping tasks. Whereas having more friends predicted decreases in avoidant or hostile strategies, having high-quality friendships predicted emotionally engaged strategies that involved talking about the problem. Moreover, whereas having more friends predicted increases in relatively disengaged strategies, like distraction and acting like the problem never happened, having high-quality friendships predicted decreases in these strategies. The present study also tested whether youths' strategies in the fall predicted changes in friendship adjustment by the spring. Only strategies which may be seen as major friendship transgressions (i.e., avoiding or blaming the friend when the friend encounters a problem) predicted changes in friendship over time. Collectively, these results provide important new information on the interplay between social competencies and friendship experiences and suggest that friendships may provide a critical venue for the development of important relationship skills. PsycINFO Database Record (c) 2011 APA, all rights reserved

Prospective Associations Between Friendship Adjustment and Social Strategies: Friendship as a Context for Building Social Skills

PubMed Central

Glick, Gary C.; Rose, Amanda J.

2012-01-01

The proposal that friendships provide a context for the development of social skills is widely accepted. Yet little research exists to support these claims. In the present study, children and adolescents (N = 912) were presented with vignettes in which their friend encountered a social stressor and they could help the friend and vignettes in which they encountered a stressor and could seek help from the friend. Social strategies in response to these vignettes were assessed in the fall and spring of the school year. Notably, different indicators of friendship adjustment had unique effects on youths’ strategies in response to helping tasks. Whereas having more friends predicted decreases in avoidant or hostile strategies, having high-quality friendships predicted emotionally-engaged strategies that involved talking about the problem. Moreover, whereas having more friends predicted increases in relatively disengaged strategies, like distraction and acting like the problem never happened, having high-quality predicted decreases in these strategies. The present study also tested whether youths’ strategies in fall predicted changes in friendship adjustment by the spring. Only strategies which may be seen as major friendship transgressions (i.e., avoiding or blaming the friend when the friend encounters a problem) predicted changes in friendship over time. Collectively, these results provide important new information on the interplay between social competencies and friendship experiences and suggest that friendships may provide a critical venue for the development of important relationship skills. PMID:21443336

Model Predictive Control application for real time operation of controlled structures for the Water Authority Noorderzijlvest, The Netherlands

NASA Astrophysics Data System (ADS)

van Heeringen, Klaas-Jan; Gooijer, Jan; Knot, Floris; Talsma, Jan

2015-04-01

In the Netherlands, flood protection has always been a key issue to protect settlements against storm surges and riverine floods. Whereas flood protection traditionally focused on structural measures, nowadays the availability of meteorological and hydrological forecasts enable the application of more advanced real-time control techniques for operating the existing hydraulic infrastructure in an anticipatory and more efficient way. Model Predictive Control (MPC) is a powerful technique to derive optimal control variables with the help of model based predictions evaluated against a control objective. In a project for the regional water authority Noorderzijlvest in the north of the Netherlands, it has been shown that MPC can increase the safety level of the system during flood events by an anticipatory pre-release of water. Furthermore, energy costs of pumps can be reduced by making tactical use of the water storage and shifting pump activities during normal operating conditions to off-peak hours. In this way cheap energy is used in combination of gravity flow through gates during low tide periods. MPC has now been implemented for daily operational use of the whole water system of the water authority Noorderzijlvest. The system developed to a real time decision support system which not only supports the daily operation but is able to directly implement the optimal control settings at the structures. We explain how we set-up and calibrated a prediction model (RTC-Tools) that is accurate and fast enough for optimization purposes, and how we integrated it in the operational flood early warning system (Delft-FEWS). Beside the prediction model, the weights and the factors of the objective function are an important element of MPC, since they shape the control objective. We developed special features in Delft-FEWS to allow the operators to adjust the objective function in order to meet changing requirements and to evaluate different control strategies.

An Optimal Current Observer for Predictive Current Controlled Buck DC-DC Converters

PubMed Central

Min, Run; Chen, Chen; Zhang, Xiaodong; Zou, Xuecheng; Tong, Qiaoling; Zhang, Qiao

2014-01-01

In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally. PMID:24854061

Novel Formulation of Adaptive MPC as EKF Using ANN Model: Multiproduct Semibatch Polymerization Reactor Case Study.

PubMed

Kamesh, Reddi; Rani, Kalipatnapu Yamuna

2017-12-01

In this paper, a novel formulation for nonlinear model predictive control (MPC) has been proposed incorporating the extended Kalman filter (EKF) control concept using a purely data-driven artificial neural network (ANN) model based on measurements for supervisory control. The proposed scheme consists of two modules focusing on online parameter estimation based on past measurements and control estimation over control horizon based on minimizing the deviation of model output predictions from set points along the prediction horizon. An industrial case study for temperature control of a multiproduct semibatch polymerization reactor posed as a challenge problem has been considered as a test bed to apply the proposed ANN-EKFMPC strategy at supervisory level as a cascade control configuration along with proportional integral controller [ANN-EKFMPC with PI (ANN-EKFMPC-PI)]. The proposed approach is formulated incorporating all aspects of MPC including move suppression factor for control effort minimization and constraint-handling capability including terminal constraints. The nominal stability analysis and offset-free tracking capabilities of the proposed controller are proved. Its performance is evaluated by comparison with a standard MPC-based cascade control approach using the same adaptive ANN model. The ANN-EKFMPC-PI control configuration has shown better controller performance in terms of temperature tracking, smoother input profiles, as well as constraint-handling ability compared with the ANN-MPC with PI approach for two products in summer and winter. The proposed scheme is found to be versatile although it is based on a purely data-driven model with online parameter estimation.

Improving spatial prediction of Schistosoma haematobium prevalence in southern Ghana through new remote sensors and local water access profiles.

PubMed

Kulinkina, Alexandra V; Walz, Yvonne; Koch, Magaly; Biritwum, Nana-Kwadwo; Utzinger, Jürg; Naumova, Elena N

2018-06-04

Schistosomiasis is a water-related neglected tropical disease. In many endemic low- and middle-income countries, insufficient surveillance and reporting lead to poor characterization of the demographic and geographic distribution of schistosomiasis cases. Hence, modeling is relied upon to predict areas of high transmission and to inform control strategies. We hypothesized that utilizing remotely sensed (RS) environmental data in combination with water, sanitation, and hygiene (WASH) variables could improve on the current predictive modeling approaches. Schistosoma haematobium prevalence data, collected from 73 rural Ghanaian schools, were used in a random forest model to investigate the predictive capacity of 15 environmental variables derived from RS data (Landsat 8, Sentinel-2, and Global Digital Elevation Model) with fine spatial resolution (10-30 m). Five methods of variable extraction were tested to determine the spatial linkage between school-based prevalence and the environmental conditions of potential transmission sites, including applying the models to known human water contact locations. Lastly, measures of local water access and groundwater quality were incorporated into RS-based models to assess the relative importance of environmental and WASH variables. Predictive models based on environmental characterization of specific locations where people contact surface water bodies offered some improvement as compared to the traditional approach based on environmental characterization of locations where prevalence is measured. A water index (MNDWI) and topographic variables (elevation and slope) were important environmental risk factors, while overall, groundwater iron concentration predominated in the combined model that included WASH variables. The study helps to understand localized drivers of schistosomiasis transmission. Specifically, unsatisfactory water quality in boreholes perpetuates reliance of surface water bodies, indirectly increasing schistosomiasis risk and resulting in rapid reinfection (up to 40% prevalence six months following preventive chemotherapy). Considering WASH-related risk factors in schistosomiasis prediction can help shift the focus of control strategies from treating symptoms to reducing exposure.

Epidemiological modeling of invasion in heterogeneous landscapes: Spread of sudden oak death in California (1990-2030)

Treesearch

R.K. Meentemeyer; N.J. Cunniffe; A.R. Cook; J.A.N. Filipe; R.D. Hunter; D.M. Rizzo; C.A. Gilligan

2011-01-01

The spread of emerging infectious diseases (EIDs) in natural environments poses substantial risks to biodiversity and ecosystem function. As EIDs and their impacts grow, landscape- to regional-scale models of disease dynamics are increasingly needed for quantitative prediction of epidemic outcomes and design of practicable strategies for control. Here we use spatio-...

Modeling the spatial and temporal dynamics of isolated emerald ash borer populations

Treesearch

Nathan W. Siegert; Andrew M. Liebhold; Deborah G. McCullough

2008-01-01

The ability to predict the distance and rate of emerald ash borer (EAB) spread in outlier populations is needed to continue development of effective management strategies for improved EAB control. We have developed a coupled map lattice model to estimate the spread and dispersal of isolated emerald ash borer populations. This model creates an artificial environment in...

Testing Stage-Specific Effects of a Stage-Matched Intervention: A Randomized Controlled Trial Targeting Physical Exercise and Its Predictors

ERIC Educational Resources Information Center

Lippke, Sonia; Schwarzer, Ralf; Ziegelmann, Jochen P.; Scholz, Urte; Schuz, Benjamin

2010-01-01

Health education interventions can be tailored toward stages of change. This strategy is based on theories that predict at which stage which variables are indicative of subsequent behavior change processes. For example, planning is regarded as being effective in intenders. However, rather few studies have tested whether matched interventions are…

Protective mechanical ventilation in United Kingdom critical care units: A multicentre audit

PubMed Central

Martin, Matthew J; Richardson, Neil; Bourdeaux, Christopher P

2016-01-01

Lung protective ventilation is becoming increasingly used for all critically ill patients being mechanically ventilated on a mandatory ventilator mode. Compliance with the universal application of this ventilation strategy in intensive care units in the United Kingdom is unknown. This 24-h audit of ventilation practice took place in 16 intensive care units in two regions of the United Kingdom. The mean tidal volume for all patients being ventilated on a mandatory ventilator mode was 7.2(±1.4) ml kg−1 predicted body weight and overall compliance with low tidal volume ventilation (≤6.5 ml kg−1 predicted body weight) was 34%. The mean tidal volume for patients ventilated with volume-controlled ventilation was 7.0(±1.2) ml kg−1 predicted body weight and 7.9(±1.8) ml kg−1 predicted body weight for pressure-controlled ventilation (P < 0.0001). Overall compliance with recommended levels of positive end-expiratory pressure was 72%. Significant variation in practice existed both at a regional and individual unit level. PMID:28979556

Protective mechanical ventilation in United Kingdom critical care units: A multicentre audit.

PubMed

Newell, Christopher P; Martin, Matthew J; Richardson, Neil; Bourdeaux, Christopher P

2017-05-01

Lung protective ventilation is becoming increasingly used for all critically ill patients being mechanically ventilated on a mandatory ventilator mode. Compliance with the universal application of this ventilation strategy in intensive care units in the United Kingdom is unknown. This 24-h audit of ventilation practice took place in 16 intensive care units in two regions of the United Kingdom. The mean tidal volume for all patients being ventilated on a mandatory ventilator mode was 7.2(±1.4) ml kg -1 predicted body weight and overall compliance with low tidal volume ventilation (≤6.5 ml kg -1 predicted body weight) was 34%. The mean tidal volume for patients ventilated with volume-controlled ventilation was 7.0(±1.2) ml kg -1 predicted body weight and 7.9(±1.8) ml kg -1 predicted body weight for pressure-controlled ventilation ( P  < 0.0001). Overall compliance with recommended levels of positive end-expiratory pressure was 72%. Significant variation in practice existed both at a regional and individual unit level.

Drug Resistance Strategies and Substance Use among Adolescents in Monterrey, Mexico

PubMed Central

Marsiglia, Flavio Francisco; Castillo, Jason; Becerra, David; Nieri, Tanya

2011-01-01

This study examined drug resistance strategies and substance use among adolescents from Monterrey, Mexico. The focus was strategies that U.S. adolescents use most often to resist using substances, including refuse (saying no), explain (declining with an explanation), avoid (staying away from situations where drugs are offered), and leave (exiting situations where drugs are offered). Using self-administered questionnaire data from a convenience sample of 327 Mexican students enrolled at two secondary schools (preparatorias), we tested whether frequent use of particular drug resistance strategies predicted actual substance use. Multiple regression results showed that different strategies were effective for different substances, that some effects were mediated by number of offers received, and that certain effects were stronger for females than for males. Students using the refuse strategy reported less cigarette use and less binge drinking; those using the avoid strategy reported less alcohol and cigarette use; and those using the leave strategy reported less binge drinking and, for females only, less marijuana use. Use of the explain strategy was not significantly related to substance use after controlling for use of other strategies. Findings are discussed in terms of Mexican cultural values and their implications for the design of prevention programs for Mexican youth. PMID:18365314

Online and offline peer led models against bullying and cyberbullying.

PubMed

Palladino, Benedetta Emanuela; Nocentini, Annalaura; Menesini, Ersilia

2012-11-01

The aim of the present study is to describe and evaluate an ongoing peer-led model against bullying and cyberbullying carried out with Italian adolescents. The evaluation of the project was made through an experimental design consisting of a pre-test and a post-test. Participants in the study were 375 adolescents (20.3% males), enrolled in 9th to 13th grades. The experimental group involved 231 students with 42 peer educators, and the control group involved 144 students. Results showed a significant decrease in the experimental group as compared to the control group for all the variables except for cyberbullying. Besides, in the experimental group we found a significant increase in adaptive coping strategies like problem solving and a significant decrease in maladaptive coping strategies like avoidance: these changes mediate the changes in the behavioural variables. In particular, the decrease in avoidance predicts the decrease in victimization and cybervictimization for peer educators and for the other students in the experimental classes whereas the increase in problem solving predicts the decrease in cyberbullying only in the peer educators group. Results are discussed following recent reviews on evidence based efficacy of peer led models.

Predicted impact of thermal power generation emission control measures in the Beijing-Tianjin-Hebei region on air pollution over Beijing, China.

PubMed

Wang, Liqiang; Li, Pengfei; Yu, Shaocai; Mehmood, Khalid; Li, Zhen; Chang, Shucheng; Liu, Weiping; Rosenfeld, Daniel; Flagan, Richard C; Seinfeld, John H

2018-01-17

Widespread economic growth in China has led to increasing episodes of severe air pollution, especially in major urban areas. Thermal power plants represent a particularly important class of emissions. Here we present an evaluation of the predicted effectiveness of a series of recently proposed thermal power plant emission controls in the Beijing-Tianjin-Hebei (BTH) region on air quality over Beijing using the Community Multiscale Air Quality(CMAQ) atmospheric chemical transport model to predict CO, SO 2 , NO 2 , PM 2.5 , and PM 10 levels. A baseline simulation of the hypothetical removal of all thermal power plants in the BTH region is predicted to lead to 38%, 23%, 23%, 24%, and 24% reductions in current annual mean levels of CO, SO 2 , NO 2 , PM 2.5 , and PM 10 in Beijing, respectively. Similar percentage reductions are predicted in the major cities in the BTH region. Simulations of the air quality impact of six proposed thermal power plant emission reduction strategies over the BTH region provide an estimate of the potential improvement in air quality in the Beijing metropolitan area, as a function of the time of year.

Children's Goals and Strategies in Response to Conflicts within a Friendship.

ERIC Educational Resources Information Center

Rose, Amanda J.; Asher, Steven R.

1999-01-01

Examined whether fourth- and fifth-grade children's social goals and strategies in friendship conflict situations are predictive of their friendship adjustment, after accounting for level of peer acceptance. Found that children's goals were highly related to their strategies and that children's goals and strategies were predictive of their…

Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E²)

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

Hou, Yunfei; Seliman, Salaheldeen M. S.; Wang, Enshu

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly consideringmore » the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.« less

Cooperative and Integrated Vehicle and Intersection Control for Energy Efficiency (CIVIC-E²)

DOE PAGES

Hou, Yunfei; Seliman, Salaheldeen M. S.; Wang, Enshu; ...

2018-02-15

Recent advances in connected vehicle technologies enable vehicles and signal controllers to cooperate and improve the traffic management at intersections. This paper explores the opportunity for cooperative and integrated vehicle and intersection control for energy efficiency (CIVIC-E 2) to contribute to a more sustainable transportation system. We propose a two-level approach that jointly optimizes the traffic signal timing and vehicles' approach speed, with the objective being to minimize total energy consumption for all vehicles passing through an isolated intersection. More specifically, at the intersection level, a dynamic programming algorithm is designed to find the optimal signal timing by explicitly consideringmore » the arrival time and energy profile of each vehicle. At the vehicle level, a model predictive control strategy is adopted to ensure that vehicles pass through the intersection in a timely fashion. Our simulation study has shown that the proposed CIVIC-E 2 system can significantly improve intersection performance under various traffic conditions. Compared with conventional fixed-time and actuated signal control strategies, the proposed algorithm can reduce energy consumption and queue length by up to 31% and 95%, respectively.« less

Increased performance in the short-term water demand forecasting through the use of a parallel adaptive weighting strategy

NASA Astrophysics Data System (ADS)

Sardinha-Lourenço, A.; Andrade-Campos, A.; Antunes, A.; Oliveira, M. S.

2018-03-01

Recent research on water demand short-term forecasting has shown that models using univariate time series based on historical data are useful and can be combined with other prediction methods to reduce errors. The behavior of water demands in drinking water distribution networks focuses on their repetitive nature and, under meteorological conditions and similar consumers, allows the development of a heuristic forecast model that, in turn, combined with other autoregressive models, can provide reliable forecasts. In this study, a parallel adaptive weighting strategy of water consumption forecast for the next 24-48 h, using univariate time series of potable water consumption, is proposed. Two Portuguese potable water distribution networks are used as case studies where the only input data are the consumption of water and the national calendar. For the development of the strategy, the Autoregressive Integrated Moving Average (ARIMA) method and a short-term forecast heuristic algorithm are used. Simulations with the model showed that, when using a parallel adaptive weighting strategy, the prediction error can be reduced by 15.96% and the average error by 9.20%. This reduction is important in the control and management of water supply systems. The proposed methodology can be extended to other forecast methods, especially when it comes to the availability of multiple forecast models.

A Dynamic Model for the Evaluation of Aircraft Engine Icing Detection and Control-Based Mitigation Strategies

NASA Technical Reports Server (NTRS)

Simon, Donald L.; Rinehart, Aidan W.; Jones, Scott M.

2017-01-01

Aircraft flying in regions of high ice crystal concentrations are susceptible to the buildup of ice within the compression system of their gas turbine engines. This ice buildup can restrict engine airflow and cause an uncommanded loss of thrust, also known as engine rollback, which poses a potential safety hazard. The aviation community is conducting research to understand this phenomena, and to identify avoidance and mitigation strategies to address the concern. To support this research, a dynamic turbofan engine model has been created to enable the development and evaluation of engine icing detection and control-based mitigation strategies. This model captures the dynamic engine response due to high ice water ingestion and the buildup of ice blockage in the engines low pressure compressor. It includes a fuel control system allowing engine closed-loop control effects during engine icing events to be emulated. The model also includes bleed air valve and horsepower extraction actuators that, when modulated, change overall engine operating performance. This system-level model has been developed and compared against test data acquired from an aircraft turbofan engine undergoing engine icing studies in an altitude test facility and also against outputs from the manufacturers customer deck. This paper will describe the model and show results of its dynamic response under open-loop and closed-loop control operating scenarios in the presence of ice blockage buildup compared against engine test cell data. Planned follow-on use of the model for the development and evaluation of icing detection and control-based mitigation strategies will also be discussed. The intent is to combine the model and control mitigation logic with an engine icing risk calculation tool capable of predicting the risk of engine icing based on current operating conditions. Upon detection of an operating region of risk for engine icing events, the control mitigation logic will seek to change the engines operating point to a region of lower risk through the modulation of available control actuators while maintaining the desired engine thrust output. Follow-on work will assess the feasibility and effectiveness of such control-based mitigation strategies.

Strategy of arm movement control is determined by minimization of neural effort for joint coordination.

PubMed

Dounskaia, Natalia; Shimansky, Yury

2016-06-01

Optimality criteria underlying organization of arm movements are often validated by testing their ability to adequately predict hand trajectories. However, kinematic redundancy of the arm allows production of the same hand trajectory through different joint coordination patterns. We therefore consider movement optimality at the level of joint coordination patterns. A review of studies of multi-joint movement control suggests that a 'trailing' pattern of joint control is consistently observed during which a single ('leading') joint is rotated actively and interaction torque produced by this joint is the primary contributor to the motion of the other ('trailing') joints. A tendency to use the trailing pattern whenever the kinematic redundancy is sufficient and increased utilization of this pattern during skillful movements suggests optimality of the trailing pattern. The goal of this study is to determine the cost function minimization of which predicts the trailing pattern. We show that extensive experimental testing of many known cost functions cannot successfully explain optimality of the trailing pattern. We therefore propose a novel cost function that represents neural effort for joint coordination. That effort is quantified as the cost of neural information processing required for joint coordination. We show that a tendency to reduce this 'neurocomputational' cost predicts the trailing pattern and that the theoretically developed predictions fully agree with the experimental findings on control of multi-joint movements. Implications for future research of the suggested interpretation of the trailing joint control pattern and the theory of joint coordination underlying it are discussed.

Evaluation of peripheral binocular visual field in patients with glaucoma: a pilot study

PubMed Central

Ana, Banc; Cristina, Stan; Dorin, Chiselita

2016-01-01

Objective: The objective of this study was to evaluate the peripheral binocular visual field (PBVF) in patients with glaucoma using the threshold strategy of Humphrey Field Analyzer. Methods: We conducted a case-control pilot study in which we enrolled 59 patients with glaucoma and 20 controls. All participants were evaluated using a custom PBVF test and central 24° monocular visual field tests for each eye using the threshold strategy. The central binocular visual field (CBVF) was predicted from the monocular tests using the most sensitive point at each field location. The glaucoma patients were grouped according to Hodapp classification and age. The PBVF was compared to controls and the relationship between the PBVF and CBVF was tested. Results: The areas of frame-induced artefacts were determined (over 50° in each temporal field, 24° superiorly and 45° inferiorly) and excluded from interpretation. The patients presented a statistically significant generalized decrease of the peripheral retinal sensitivity compared to controls for Hodapp initial stage - groups aged 50-59 (t = 11.93 > 2.06; p < 0.05) and 60-69 (t = 7.55 > 2.06; p < 0.05). For the initial Hodapp stage there was no significant relationship between PBVF and CBVF (r = 0.39). For the moderate and advanced Hodapp stages, the interpretation of data was done separately for each patient. Conclusions: This pilot study suggests that glaucoma patients present a decrease of PBVF compared to controls and CBVF cannot predict the PBVF in glaucoma. Abbreviations: CBVF = central binocular visual field, PBVF = peripheral binocular visual field, MD = mean deviation PMID:27220228

Phenotypic plasticity and specialization in clonal versus non-clonal plants: A data synthesis

NASA Astrophysics Data System (ADS)

Fazlioglu, Fatih; Bonser, Stephen P.

2016-11-01

Reproductive strategies can be associated with ecological specialization and generalization. Clonal plants produce lineages adapted to the maternal habitat that can lead to specialization. However, clonal plants frequently display high phenotypic plasticity (e.g. clonal foraging for resources), factors linked to ecological generalization. Alternately, sexual reproduction can be associated with generalization via increasing genetic variation or specialization through rapid adaptive evolution. Moreover, specializing to high or low quality habitats can determine how phenotypic plasticity is expressed in plants. The specialization hypothesis predicts that specialization to good environments results in high performance trait plasticity and specialization to bad environments results in low performance trait plasticity. The interplay between reproductive strategies, phenotypic plasticity, and ecological specialization is important for understanding how plants adapt to variable environments. However, we currently have a poor understanding of these relationships. In this study, we addressed following questions: 1) Is there a relationship between phenotypic plasticity, specialization, and reproductive strategies in plants? 2) Do good habitat specialists express greater performance trait plasticity than bad habitat specialists? We searched the literature for studies examining plasticity for performance traits and functional traits in clonal and non-clonal plant species from different habitat types. We found that non-clonal (obligate sexual) plants expressed greater performance trait plasticity and functional trait plasticity than clonal plants. That is, non-clonal plants exhibited a specialist strategy where they perform well only in a limited range of habitats. Clonal plants expressed less performance loss across habitats and a more generalist strategy. In addition, specialization to good habitats did not result in greater performance trait plasticity. This result was contrary to the predictions of the specialization hypothesis. Overall, reproductive strategies are associated with ecological specialization or generalization through phenotypic plasticity. While specialization is common in plant populations, the evolution of specialization does not control the nature of phenotypic plasticity as predicted under the specialization hypothesis.

Hybridization of an invasive shrub affects tolerance and resistance to defoliation by a biological control agent

USGS Publications Warehouse

Williams, Wyatt I.; Friedman, Jonathan M.; Gaskin, John F.; Norton, Andrew P.

2014-01-01

Evolution has contributed to the successful invasion of exotic plant species in their introduced ranges, but how evolution affects particular control strategies is still under evaluation. For instance, classical biological control, a common strategy involving the utilization of highly specific natural enemies to control exotic pests, may be negatively affected by host hybridization because of shifts in plant traits, such as root allocation or chemical constituents. We investigated introgression between two parent species of the invasive shrub tamarisk (Tamarix spp.) in the western United States, and how differences in plant traits affect interactions with a biological control agent. Introgression varied strongly with latitude of origin and was highly correlated with plant performance. Increased levels of T. ramosissima introgression resulted in both higher investment in roots and tolerance to defoliation and less resistance to insect attack. Because tamarisk hybridization occurs predictably on the western U.S. landscape, managers may be able to exploit this information to maximize control efforts. Genetic differentiation in plant traits in this system underpins the importance of plant hybridization and may explain why some biological control releases are more successful than others.

Advances and trends in computational structural mechanics

NASA Technical Reports Server (NTRS)

Noor, A. K.

1986-01-01

Recent developments in computational structural mechanics are reviewed with reference to computational needs for future structures technology, advances in computational models for material behavior, discrete element technology, assessment and control of numerical simulations of structural response, hybrid analysis, and techniques for large-scale optimization. Research areas in computational structural mechanics which have high potential for meeting future technological needs are identified. These include prediction and analysis of the failure of structural components made of new materials, development of computational strategies and solution methodologies for large-scale structural calculations, and assessment of reliability and adaptive improvement of response predictions.

Critical Source Area Delineation: The representation of hydrology in effective erosion modeling.

NASA Astrophysics Data System (ADS)

Fowler, A.; Boll, J.; Brooks, E. S.; Boylan, R. D.

2017-12-01

Despite decades of conservation and millions of conservation dollars, nonpoint source sediment loading associated with agricultural disturbance continues to be a significant problem in many parts of the world. Local and national conservation organizations are interested in targeting critical source areas for control strategy implementation. Currently, conservation practices are selected and located based on the Revised Universal Soil Loss Equation (RUSLE) hillslope erosion modeling, and the National Resource Conservation Service will soon be transiting to the Watershed Erosion Predict Project (WEPP) model for the same purpose. We present an assessment of critical source areas targeted with RUSLE, WEPP and a regionally validated hydrology model, the Soil Moisture Routing (SMR) model, to compare the location of critical areas for sediment loading and the effectiveness of control strategies. The three models are compared for the Palouse dryland cropping region of the inland northwest, with un-calibrated analyses of the Kamiache watershed using publicly available soils, land-use and long-term simulated climate data. Critical source areas were mapped and the side-by-side comparison exposes the differences in the location and timing of runoff and erosion predictions. RUSLE results appear most sensitive to slope driving processes associated with infiltration excess. SMR captured saturation excess driven runoff events located at the toe slope position, while WEPP was able to capture both infiltration excess and saturation excess processes depending on soil type and management. A methodology is presented for down-scaling basin level screening to the hillslope management scale for local control strategies. Information on the location of runoff and erosion, driven by the runoff mechanism, is critical for effective treatment and conservation.

Cognitive Control Predicts Use of Model-Based Reinforcement-Learning

PubMed Central

Otto, A. Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D.

2015-01-01

Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information—in the service of overcoming habitual, stimulus-driven responses—in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791

Experimental Evaluation of Balance Prediction Models for Sit-to-Stand Movement in the Sagittal Plane

PubMed Central

Pena Cabra, Oscar David; Watanabe, Takashi

2013-01-01

Evaluation of balance control ability would become important in the rehabilitation training. In this paper, in order to make clear usefulness and limitation of a traditional simple inverted pendulum model in balance prediction in sit-to-stand movements, the traditional simple model was compared to an inertia (rotational radius) variable inverted pendulum model including multiple-joint influence in the balance predictions. The predictions were tested upon experimentation with six healthy subjects. The evaluation showed that the multiple-joint influence model is more accurate in predicting balance under demanding sit-to-stand conditions. On the other hand, the evaluation also showed that the traditionally used simple inverted pendulum model is still reliable in predicting balance during sit-to-stand movement under non-demanding (normal) condition. Especially, the simple model was shown to be effective for sit-to-stand movements with low center of mass velocity at the seat-off. Moreover, almost all trajectories under the normal condition seemed to follow the same control strategy, in which the subjects used extra energy than the minimum one necessary for standing up. This suggests that the safety considerations come first than the energy efficiency considerations during a sit to stand, since the most energy efficient trajectory is close to the backward fall boundary. PMID:24187580

Acquisition and production of skilled behavior in dynamic decision-making tasks: Modeling strategic behavior in human-automation interaction: Why and aid can (and should) go unused

NASA Technical Reports Server (NTRS)

Kirlik, Alex

1991-01-01

Advances in computer and control technology offer the opportunity for task-offload aiding in human-machine systems. A task-offload aid (e.g., an autopilot, an intelligent assistant) can be selectively engaged by the human operator to dynamically delegate tasks to an automated system. Successful design and performance prediction in such systems requires knowledge of the factors influencing the strategy the operator develops and uses for managing interaction with the task-offload aid. A model is presented that shows how such strategies can be predicted as a function of three task context properties (frequency and duration of secondary tasks and costs of delaying secondary tasks) and three aid design properties (aid engagement and disengagement times, aid performance relative to human performance). Sensitivity analysis indicates how each of these contextual and design factors affect the optimal aid aid usage strategy and attainable system performance. The model is applied to understanding human-automation interaction in laboratory experiments on human supervisory control behavior. The laboratory task allowed subjects freedom to determine strategies for using an autopilot in a dynamic, multi-task environment. Modeling results suggested that many subjects may indeed have been acting appropriately by not using the autopilot in the way its designers intended. Although autopilot function was technically sound, this aid was not designed with due regard to the overall task context in which it was placed. These results demonstrate the need for additional research on how people may strategically manage their own resources, as well as those provided by automation, in an effort to keep workload and performance at acceptable levels.

Global elimination of leprosy by 2020: are we on track?

PubMed

Blok, David J; De Vlas, Sake J; Richardus, Jan Hendrik

2015-10-22

Every year more than 200,000 new leprosy cases are registered globally. This number has been fairly stable over the past 8 years. WHO has set a target to interrupt the transmission of leprosy globally by 2020. The aim of this study is to investigate whether this target, interpreted as global elimination, is feasible given the current control strategy. We focus on the three most important endemic countries, India, Brazil and Indonesia, which together account for more than 80 % of all newly registered leprosy cases. We used the existing individual-based model SIMCOLEP to predict future trends of leprosy incidence given the current control strategy in each country. SIMCOLEP simulates the spread of M. leprae in a population that is structured in households. Current control consists of passive and active case detection, and multidrug therapy (MDT). Predictions of leprosy incidence were made for each country as well as for one high-endemic region within each country: Chhattisgarh (India), Pará State (Brazil) and Madura (Indonesia). Data for model quantification came from: National Leprosy Elimination Program (India), SINAN database (Brazil), and Netherlands Leprosy Relief (Indonesia). Our projections of future leprosy incidence all show a downward trend. In 2020, the country-level leprosy incidence has decreased to 6.2, 6.1 and 3.3 per 100,000 in India, Brazil and Indonesia, respectively, meeting the elimination target of less than 10 per 100,000. However, elimination may not be achieved in time for the high-endemic regions. The leprosy incidence in 2020 is predicted to be 16.2, 21.1 and 19.3 per 100,000 in Chhattisgarh, Pará and Madura, respectively, and the target may only be achieved in another 5 to 10 years. Our predictions show that although country-level elimination is reached by 2020, leprosy is likely to remain a problem in the high-endemic regions (i.e. states, districts and provinces with multimillion populations), which account for most of the cases in a country.

Recalled Aspects of Original Encoding Strategies Influence Episodic Feeling of Knowing

PubMed Central

Hertzog, Christopher; Fulton, Erika K.; Sinclair, Starlette M.; Dunlosky, John

2013-01-01

We tested the hypothesis that feeling of knowing (FOK) after a failed recall attempt is influenced by recalling aspects of the original encoding strategy. Individuals were instructed to use interactive imagery to encode unrelated word pairs. We manipulated item concreteness (abstract versus concrete) and item repetition at study (1 versus 3). Participants orally described the mediator produced immediately after studying each item, if any. After a delay they were given cued recall, made FOK ratings, and attempted to recall their original mediator. Concreteness and item repetition enhanced strategy recall, which had a large effect on FOKs. Controlling on strategy recall reduced the predictive validity of FOKs for recognition memory, indicating that access to original aspects of encoding influenced FOK accuracy. Confidence judgments (CJs) for correctly recognized items covaried with FOKs, but FOKs did not fully track strategy recall associations with CJs, suggesting emergent effects of strategy cues elicited by recognition tests not accessed at the time of the FOK judgment. In summary, cue-generated access to aspects of the original encoding strategy strongly influenced episodic FOK, although other influences are also implicated. PMID:23835601

Recalled aspects of original encoding strategies influence episodic feelings of knowing.

PubMed

Hertzog, Christopher; Fulton, Erika K; Sinclair, Starlette M; Dunlosky, John

2014-01-01

We tested the hypothesis that the feeling of knowing (FOK) after a failed recall attempt is influenced by recalling aspects of the original encoding strategy. Individuals were instructed to use interactive imagery to encode unrelated word pairs. We manipulated item concreteness (abstract vs. concrete) and item repetitions at study (one vs. three). Participants orally described the mediator produced immediately after studying each item, if any. After a delay, they were given cued recall, made FOK ratings, and attempted to recall their original mediator. Concreteness and item repetition enhanced strategy recall, which had a large effect on FOKs. Controlling on strategy recall reduced the predictive validity of FOKs for recognition memory, indicating that access to the original aspects of encoding influenced FOK accuracy. Confidence judgments (CJs) for correctly recognized items covaried with FOKs, but FOKs did not fully track the strategy recall associations with CJs, suggesting emergent effects of strategy cues that were elicited by recognition tests but not accessed at the time of the FOK judgment. In summary, cue-generated access to aspects of the original encoding strategy strongly influenced episodic FOKs, although other influences were also implicated.

To master or perform? Exploring relations between achievement goals and conceptual change learning.

PubMed

Ranellucci, John; Muis, Krista R; Duffy, Melissa; Wang, Xihui; Sampasivam, Lavanya; Franco, Gina M

2013-09-01

Research is needed to explore conceptual change in relation to achievement goal orientations and depth of processing. To address this need, we examined relations between achievement goals, use of deep versus shallow processing strategies, and conceptual change learning using a think-aloud protocol. Seventy-three undergraduate students were assessed on their prior knowledge and misconceptions about Newtonian mechanics, and then reported their achievement goals and participated in think-aloud protocols while reading Newtonian physics texts. A mastery-approach goal orientation positively predicted deep processing strategies, shallow processing strategies, and conceptual change. In contrast, a performance-approach goal orientation did not predict either of the processing strategies, but negatively predicted conceptual change. A performance-avoidance goal orientation negatively predicted deep processing strategies and conceptual change. Moreover, deep and shallow processing strategies positively predicted conceptual change as well as recall. Finally, both deep and shallow processing strategies mediated relations between mastery-approach goals and conceptual change. Results provide some support for Dole and Sinatra's (1998) Cognitive Reconstruction of Knowledge Model of conceptual change but also challenge specific facets with regard to the role of depth of processing in conceptual change. © 2012 The British Psychological Society.

Testing models of parental investment strategy and offspring size in ants.

PubMed

Gilboa, Smadar; Nonacs, Peter

2006-01-01

Parental investment strategies can be fixed or flexible. A fixed strategy predicts making all offspring a single 'optimal' size. Dynamic models predict flexible strategies with more than one optimal size of offspring. Patterns in the distribution of offspring sizes may thus reveal the investment strategy. Static strategies should produce normal distributions. Dynamic strategies should often result in non-normal distributions. Furthermore, variance in morphological traits should be positively correlated with the length of developmental time the traits are exposed to environmental influences. Finally, the type of deviation from normality (i.e., skewed left or right, or platykurtic) should be correlated with the average offspring size. To test the latter prediction, we used simulations to detect significant departures from normality and categorize distribution types. Data from three species of ants strongly support the predicted patterns for dynamic parental investment. Offspring size distributions are often significantly non-normal. Traits fixed earlier in development, such as head width, are less variable than final body weight. The type of distribution observed correlates with mean female dry weight. The overall support for a dynamic parental investment model has implications for life history theory. Predicted conflicts over parental effort, sex investment ratios, and reproductive skew in cooperative breeders follow from assumptions of static parental investment strategies and omnipresent resource limitations. By contrast, with flexible investment strategies such conflicts can be either absent or maladaptive.

Optimal Reservoir Operation using Stochastic Model Predictive Control

NASA Astrophysics Data System (ADS)

Sahu, R.; McLaughlin, D.

2016-12-01

Hydropower operations are typically designed to fulfill contracts negotiated with consumers who need reliable energy supplies, despite uncertainties in reservoir inflows. In addition to providing reliable power the reservoir operator needs to take into account environmental factors such as downstream flooding or compliance with minimum flow requirements. From a dynamical systems perspective, the reservoir operating strategy must cope with conflicting objectives in the presence of random disturbances. In order to achieve optimal performance, the reservoir system needs to continually adapt to disturbances in real time. Model Predictive Control (MPC) is a real-time control technique that adapts by deriving the reservoir release at each decision time from the current state of the system. Here an ensemble-based version of MPC (SMPC) is applied to a generic reservoir to determine both the optimal power contract, considering future inflow uncertainty, and a real-time operating strategy that attempts to satisfy the contract. Contract selection and real-time operation are coupled in an optimization framework that also defines a Pareto trade off between the revenue generated from energy production and the environmental damage resulting from uncontrolled reservoir spills. Further insight is provided by a sensitivity analysis of key parameters specified in the SMPC technique. The results demonstrate that SMPC is suitable for multi-objective planning and associated real-time operation of a wide range of hydropower reservoir systems.

Isotopic studies of metabolic systems by mass spectrometry: using Pascal's triangle to produce biological standards with fully controlled labeling patterns.

PubMed

Millard, Pierre; Massou, Stéphane; Portais, Jean-Charles; Létisse, Fabien

2014-10-21

Mass spectrometry (MS) is widely used for isotopic studies of metabolism in which detailed information about biochemical processes is obtained from the analysis of isotope incorporation into metabolites. The biological value of such experiments is dependent on the accuracy of the isotopic measurements. Using MS, isotopologue distributions are measured from the quantitative analysis of isotopic clusters. These measurements are prone to various biases, which can occur during the experimental workflow and/or MS analysis. The lack of relevant standards limits investigations of the quality of the measured isotopologue distributions. To meet that need, we developed a complete theoretical and experimental framework for the biological production of metabolites with fully controlled and predictable labeling patterns. This strategy is valid for different isotopes and different types of metabolisms and organisms, and was applied to two model microorganisms, Pichia augusta and Escherichia coli, cultivated on (13)C-labeled methanol and acetate as sole carbon source, respectively. The isotopic composition of the substrates was designed to obtain samples in which the isotopologue distribution of all the metabolites should give the binomial coefficients found in Pascal's triangle. The strategy was validated on a liquid chromatography-tandem mass spectrometry (LC-MS/MS) platform by quantifying the complete isotopologue distributions of different intracellular metabolites, which were in close agreement with predictions. This strategy can be used to evaluate entire experimental workflows (from sampling to data processing) or different analytical platforms in the context of isotope labeling experiments.

Animal movement in the absence of predation: environmental drivers of movement strategies in a partial migration system

USGS Publications Warehouse

Bastille-Rousseau, Guillaume; Gibbs, James P.; Yackulic, Charles B.; Frair, Jacqueline L.; Cabrera, Fredy; Rousseau, Louis-Philippe

2016-01-01

Animal movement strategies including migration, dispersal, nomadism, and residency are shaped by broad-scale spatial-temporal structuring of the environment, including factors such as the degrees of spatial variation, seasonality and inter-annual predictability. Animal movement strategies, in turn, interact with the characteristics of individuals and the local distribution of resources to determine local patterns of resource selection with complex and poorly understood implications for animal fitness. Here we present a multi-scale investigation of animal movement strategies and resource selection. We consider the degree to which spatial variation, seasonality, and inter-annual predictability in resources drive migration patterns among different taxa and how movement strategies in turn shape local resource selection patterns. We focus on adult Galapagos giant tortoises Chelonoidis spp. as a model system since they display many movement strategies and evolved in the absence of predators of adults. Specifically, our analysis is based on 63 individuals among four taxa tracked on three islands over six years and almost 106 tortoise re-locations. Tortoises displayed a continuum of movement strategies from migration to sedentarism that were linked to the spatio-temporal scale and predictability of resource distributions. Movement strategies shaped patterns of resource selection. Specifically, migratory individuals displayed stronger selection toward areas where resources were more predictable among years than did non-migratory individuals, which indicates a selective advantage for migrants in seasonally structured, more predictable environments. Our analytical framework combines large-scale predictions for movement strategies, based on environmental structuring, with finer-scale analysis of space-use. Integrating different organizational levels of analysis provides a deeper understanding of the eco-evolutionary dynamics at play in the emergence and maintenance of migration and the critical role of resource predictability. Our results highlight that assessing the potential benefits of differential behavioral responses first requires an understanding of the interactions among movement strategies, resource selection and individual characteristics.

Single-layer model to predict the source/sink behavior of diffusion-controlled building materials.

PubMed

Kumar, Deept; Little, John C

2003-09-01

Building materials may act as both sources of and sinks forvolatile organic compounds (VOCs) in indoor air. A strategy to characterize the rate of absorption and desorption of VOCs by diffusion-controlled building materials is validated. A previously developed model that predicts mass transfer between a flat slab of material and the well-mixed air within a chamber or room is extended. The generalized model allows a nonuniform initial material-phase concentration and a transient influent gas-phase concentration to be simultaneously considered. An analytical solution to the more general model is developed. Experimental data are obtained by placing samples of vinyl flooring inside a small stainless steel chamber and exposing them to absorption/desorption cycles of n-dodecane and phenol. Measured values for the material-air partition coefficient and the material-phase diffusion coefficient were obtained previously in a series of completely independent experiments. The a priori model predictions are in close agreement with the observed experimental data.

Development of hybrid method for the prediction of underwater propeller noise

NASA Astrophysics Data System (ADS)

Seol, Hanshin; Suh, Jung-Chun; Lee, Soogab

2005-11-01

Noise reduction and control is an important problem in the performance of underwater acoustic systems and in the habitability of the passenger ship for crew and passenger. Furthermore, sound generated by a propeller is critical in underwater detection and it is often related to the survivability of the vessel especially for military purpose. This paper presents a numerical study on the non-cavitating and blade sheet cavitation noises of the underwater propeller. A brief summary of numerical method with verification and results are presented. The noise is predicted using time-domain acoustic analogy. The flow field is analyzed with potential-based panel method, and then the time-dependent pressure and sheet cavity volume data are used as the input for Ffowcs Williams-Hawkings formulation to predict the far-field acoustics. Noise characteristics are presented according to noise sources and conditions. Through this study, the dominant noise source of the underwater propeller is analyzed, which will provide a basis for proper noise control strategies.

The Application of Satellite-Derived, High-Resolution Land Use/Land Cover Data to Improve Urban Air Quality Model Forecasts

NASA Technical Reports Server (NTRS)

Quattrochi, D. A.; Lapenta, W. M.; Crosson, W. L.; Estes, M. G., Jr.; Limaye, A.; Kahn, M.

2006-01-01

Local and state agencies are responsible for developing state implementation plans to meet National Ambient Air Quality Standards. Numerical models used for this purpose simulate the transport and transformation of criteria pollutants and their precursors. The specification of land use/land cover (LULC) plays an important role in controlling modeled surface meteorology and emissions. NASA researchers have worked with partners and Atlanta stakeholders to incorporate an improved high-resolution LULC dataset for the Atlanta area within their modeling system and to assess meteorological and air quality impacts of Urban Heat Island (UHI) mitigation strategies. The new LULC dataset provides a more accurate representation of land use, has the potential to improve model accuracy, and facilitates prediction of LULC changes. Use of the new LULC dataset for two summertime episodes improved meteorological forecasts, with an existing daytime cold bias of approx. equal to 3 C reduced by 30%. Model performance for ozone prediction did not show improvement. In addition, LULC changes due to Atlanta area urbanization were predicted through 2030, for which model simulations predict higher urban air temperatures. The incorporation of UHI mitigation strategies partially offset this warming trend. The data and modeling methods used are generally applicable to other U.S. cities.

Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

PubMed

Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

2016-08-01

Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.

Within-and among-year germination in Sonoran Desert winter annuals: bet hedging and predictive germination in a variable environment.

PubMed

Gremer, Jennifer R; Kimball, Sarah; Venable, D Lawrence

2016-10-01

In variable environments, organisms must have strategies to ensure fitness as conditions change. For plants, germination can time emergence with favourable conditions for later growth and reproduction (predictive germination), spread the risk of unfavourable conditions (bet hedging) or both (integrated strategies). Here we explored the adaptive value of within- and among-year germination timing for 12 species of Sonoran Desert winter annual plants. We parameterised models with long-term demographic data to predict optimal germination fractions and compared them to observed germination. At both temporal scales we found that bet hedging is beneficial and that predicted optimal strategies corresponded well with observed germination. We also found substantial fitness benefits to varying germination timing, suggesting some degree of predictive germination in nature. However, predictive germination was imperfect, calling for some degree of bet hedging. Together, our results suggest that desert winter annuals have integrated strategies combining both predictive plasticity and bet hedging. © 2016 John Wiley & Sons Ltd/CNRS.

Statistical modeling of crystalline silica exposure by trade in the construction industry using a database compiled from the literature.

PubMed

Sauvé, Jean-François; Beaudry, Charles; Bégin, Denis; Dion, Chantal; Gérin, Michel; Lavoué, Jérôme

2012-09-01

A quantitative determinants-of-exposure analysis of respirable crystalline silica (RCS) levels in the construction industry was performed using a database compiled from an extensive literature review. Statistical models were developed to predict work-shift exposure levels by trade. Monte Carlo simulation was used to recreate exposures derived from summarized measurements which were combined with single measurements for analysis. Modeling was performed using Tobit models within a multimodel inference framework, with year, sampling duration, type of environment, project purpose, project type, sampling strategy and use of exposure controls as potential predictors. 1346 RCS measurements were included in the analysis, of which 318 were non-detects and 228 were simulated from summary statistics. The model containing all the variables explained 22% of total variability. Apart from trade, sampling duration, year and strategy were the most influential predictors of RCS levels. The use of exposure controls was associated with an average decrease of 19% in exposure levels compared to none, and increased concentrations were found for industrial, demolition and renovation projects. Predicted geometric means for year 1999 were the highest for drilling rig operators (0.238 mg m(-3)) and tunnel construction workers (0.224 mg m(-3)), while the estimated exceedance fraction of the ACGIH TLV by trade ranged from 47% to 91%. The predicted geometric means in this study indicated important overexposure compared to the TLV. However, the low proportion of variability explained by the models suggests that the construction trade is only a moderate predictor of work-shift exposure levels. The impact of the different tasks performed during a work shift should also be assessed to provide better management and control of RCS exposure levels on construction sites.

Attracted to power: challenge/threat and promotion/prevention focus differentially predict the attractiveness of group power

PubMed Central

Scholl, Annika; Sassenrath, Claudia; Sassenberg, Kai

2015-01-01

Depending on their motivation, individuals prefer different group contexts for social interactions. The present research sought to provide more insight into this relationship. More specifically, we tested how challenge/threat and a promotion/prevention focus predict attraction to groups with high- or low-power. As such, we examined differential outcomes of threat and prevention focus as well as challenge and promotion focus that have often been regarded as closely related. According to regulatory focus, individuals should prefer groups that they expect to “feel right” for them to join: Low-power groups should be more attractive in a prevention (than a promotion) focus, as these groups suggest security-oriented strategies, which fit a prevention focus. High-power groups should be more attractive in a promotion (rather than a prevention) focus, as these groups are associated with promotion strategies fitting a promotion focus (Sassenberg et al., 2007). In contrast, under threat (vs. challenge), groups that allow individuals to restore their (perceived) lack of control should be preferred: Low-power groups should be less attractive under threat (than challenge) because they provide low resources which threatened individuals already perceive as insufficient and high-power groups might be more attractive under threat (than under challenge), because their high resources allow individuals to restore control. Two experiments (N = 140) supported these predictions. The attractiveness of a group often depends on the motivation to engage in what fits (i.e., prefer a group that feels right in the light of one’s regulatory focus). However, under threat the striving to restore control (i.e., prefer a group allowing them to change the status quo under threat vs. challenge) overrides the fit effect, which may in turn guide individuals’ behavior in social interactions. PMID:25904887

Calibration and simulation of two large wastewater treatment plants operated for nutrient removal.

PubMed

Ferrer, J; Morenilla, J J; Bouzas, A; García-Usach, F

2004-01-01

Control and optimisation of plant processes has become a priority for WWTP managers. The calibration and verification of a mathematical model provides an important tool for the investigation of advanced control strategies that may assist in the design or optimization of WWTPs. This paper describes the calibration of the ASM2d model for two full scale biological nitrogen and phosphorus removal plants in order to characterize the biological process and to upgrade the plants' performance. Results from simulation showed a good correspondence with experimental data demonstrating that the model and the calibrated parameters were able to predict the behaviour of both WWTPs. Once the calibration and simulation process was finished, a study for each WWTP was done with the aim of improving its performance. Modifications focused on reactor configuration and operation strategies were proposed.

Cognitive biases to healthy and unhealthy food words predict change in BMI.

PubMed

Calitri, Raff; Pothos, Emmanuel M; Tapper, Katy; Brunstrom, Jeffrey M; Rogers, Peter J

2010-12-01

The current study explored the predictive value of cognitive biases to food cues (assessed by emotional Stroop and dot probe tasks) on weight change over a 1-year period. This was a longitudinal study with undergraduate students (N = 102) living in shared student accommodation. After controlling for the effects of variables associated with weight (e.g., physical activity, stress, restrained eating, external eating, and emotional eating), no effects of cognitive bias were found with the dot probe. However, for the emotional Stroop, cognitive bias to unhealthy foods predicted an increase in BMI whereas cognitive bias to healthy foods was associated with a decrease in BMI. Results parallel findings in substance abuse research; cognitive biases appear to predict behavior change. Accordingly, future research should consider strategies for attentional retraining, encouraging individuals to reorient attention away from unhealthy eating cues.

Predicting active school travel: the role of planned behavior and habit strength.

PubMed

Murtagh, Shemane; Rowe, David A; Elliott, Mark A; McMinn, David; Nelson, Norah M

2012-05-30

Despite strong support for predictive validity of the theory of planned behavior (TPB) substantial variance in both intention and behavior is unaccounted for by the model's predictors. The present study tested the extent to which habit strength augments the predictive validity of the TPB in relation to a currently under-researched behavior that has important health implications, namely children's active school travel. Participants (N = 126 children aged 8-9 years; 59 % males) were sampled from five elementary schools in the west of Scotland and completed questionnaire measures of all TPB constructs in relation to walking to school and both walking and car/bus use habit. Over the subsequent week, commuting steps on school journeys were measured objectively using an accelerometer. Hierarchical multiple regressions were used to test the predictive utility of the TPB and habit strength in relation to both intention and subsequent behavior. The TPB accounted for 41 % and 10 % of the variance in intention and objectively measured behavior, respectively. Together, walking habit and car/bus habit significantly increased the proportion of explained variance in both intention and behavior by 6 %. Perceived behavioral control and both walking and car/bus habit independently predicted intention. Intention and car/bus habit independently predicted behavior. The TPB significantly predicts children's active school travel. However, habit strength augments the predictive validity of the model. The results indicate that school travel is controlled by both intentional and habitual processes. In practice, interventions could usefully decrease the habitual use of motorized transport for travel to school and increase children's intention to walk (via increases in perceived behavioral control and walking habit, and decreases in car/bus habit). Further research is needed to identify effective strategies for changing these antecedents of children's active school travel.

IECON '87: Industrial applications of control and simulation; Proceedings of the 1987 International Conference on Industrial Electronics, Control, and Instrumentation, Cambridge, MA, Nov. 3, 4, 1987

NASA Technical Reports Server (NTRS)

Hartley, Tom T. (Editor)

1987-01-01

Recent advances in control-system design and simulation are discussed in reviews and reports. Among the topics considered are fast algorithms for generating near-optimal binary decision programs, trajectory control of robot manipulators with compensation of load effects via a six-axis force sensor, matrix integrators for real-time simulation, a high-level control language for an autonomous land vehicle, and a practical engineering design method for stable model-reference adaptive systems. Also addressed are the identification and control of flexible-limb robots with unknown loads, adaptive control and robust adaptive control for manipulators with feedforward compensation, adaptive pole-placement controllers with predictive action, variable-structure strategies for motion control, and digital signal-processor-based variable-structure controls.

Neural control of fast nonlinear systems--application to a turbocharged SI engine with VCT.

PubMed

Colin, Guillaume; Chamaillard, Yann; Bloch, Gérard; Corde, Gilles

2007-07-01

Today, (engine) downsizing using turbocharging appears as a major way in reducing fuel consumption and pollutant emissions of spark ignition (SI) engines. In this context, an efficient control of the air actuators [throttle, turbo wastegate, and variable camshaft timing (VCT)] is needed for engine torque control. This paper proposes a nonlinear model-based control scheme which combines separate, but coordinated, control modules. Theses modules are based on different control strategies: internal model control (IMC), model predictive control (MPC), and optimal control. It is shown how neural models can be used at different levels and included in the control modules to replace physical models, which are too complex to be online embedded, or to estimate nonmeasured variables. The results obtained from two different test benches show the real-time applicability and good control performance of the proposed methods.

Phenotype heterogeneity in cancer cell populations

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

Almeida, Luis; Chisholm, Rebecca; Clairambault, Jean

2016-06-08

Phenotype heterogeneity in cancer cell populations, be it of genetic, epigenetic or stochastic origin, has been identified as a main source of resistance to drug treatments and a major source of therapeutic failures in cancers. The molecular mechanisms of drug resistance are partly understood at the single cell level (e.g., overexpression of ABC transporters or of detoxication enzymes), but poorly predictable in tumours, where they are hypothesised to rely on heterogeneity at the cell population scale, which is thus the right level to describe cancer growth and optimise its control by therapeutic strategies in the clinic. We review a fewmore » results from the biological literature on the subject, and from mathematical models that have been published to predict and control evolution towards drug resistance in cancer cell populations. We propose, based on the latter, optimisation strategies of combined treatments to limit emergence of drug resistance to cytotoxic drugs in cancer cell populations, in the monoclonal situation, which limited as it is still retains consistent features of cell population heterogeneity. The polyclonal situation, that may be understood as “bet hedging” of the tumour, thus protecting itself from different sources of drug insults, may lie beyond such strategies and will need further developments. In the monoclonal situation, we have designed an optimised therapeutic strategy relying on a scheduled combination of cytotoxic and cytostatic treatments that can be adapted to different situations of cancer treatments. Finally, we review arguments for biological theoretical frameworks proposed at different time and development scales, the so-called atavistic model (diachronic view relying on Darwinian genotype selection in the coursof billions of years) and the Waddington-like epigenetic landscape endowed with evolutionary quasi-potential (synchronic view relying on Lamarckian phenotype instruction of a given genome by reversible mechanisms), to represent evolution towards heterogeneity, possibly polyclonal, in cancer cell populations and propose innovative directions for therapeutic strategies based on such frameworks.« less

Phenotype heterogeneity in cancer cell populations

NASA Astrophysics Data System (ADS)

Almeida, Luis; Chisholm, Rebecca; Clairambault, Jean; Escargueil, Alexandre; Lorenzi, Tommaso; Lorz, Alexander; Trélat, Emmanuel

2016-06-01

Phenotype heterogeneity in cancer cell populations, be it of genetic, epigenetic or stochastic origin, has been identified as a main source of resistance to drug treatments and a major source of therapeutic failures in cancers. The molecular mechanisms of drug resistance are partly understood at the single cell level (e.g., overexpression of ABC transporters or of detoxication enzymes), but poorly predictable in tumours, where they are hypothesised to rely on heterogeneity at the cell population scale, which is thus the right level to describe cancer growth and optimise its control by therapeutic strategies in the clinic. We review a few results from the biological literature on the subject, and from mathematical models that have been published to predict and control evolution towards drug resistance in cancer cell populations. We propose, based on the latter, optimisation strategies of combined treatments to limit emergence of drug resistance to cytotoxic drugs in cancer cell populations, in the monoclonal situation, which limited as it is still retains consistent features of cell population heterogeneity. The polyclonal situation, that may be understood as "bet hedging" of the tumour, thus protecting itself from different sources of drug insults, may lie beyond such strategies and will need further developments. In the monoclonal situation, we have designed an optimised therapeutic strategy relying on a scheduled combination of cytotoxic and cytostatic treatments that can be adapted to different situations of cancer treatments. Finally, we review arguments for biological theoretical frameworks proposed at different time and development scales, the so-called atavistic model (diachronic view relying on Darwinian genotype selection in the coursof billions of years) and the Waddington-like epigenetic landscape endowed with evolutionary quasi-potential (synchronic view relying on Lamarckian phenotype instruction of a given genome by reversible mechanisms), to represent evolution towards heterogeneity, possibly polyclonal, in cancer cell populations and propose innovative directions for therapeutic strategies based on such frameworks.

Impaired strategic decision making in schizophrenia.

PubMed

Kim, Hyojin; Lee, Daeyeol; Shin, Young-Min; Chey, Jeanyung

2007-11-14

Adaptive decision making in dynamic social settings requires frequent re-evaluation of choice outcomes and revision of strategies. This requires an array of multiple cognitive abilities, such as working memory and response inhibition. Thus, the disruption of such abilities in schizophrenia can have significant implications for social dysfunctions in affected patients. In the present study, 20 schizophrenia patients and 20 control subjects completed two computerized binary decision-making tasks. In the first task, the participants played a competitive zero-sum game against a computer in which the predictable choice behavior was penalized and the optimal strategy was to choose the two targets stochastically. In the second task, the expected payoffs of the two targets were fixed and unaffected by the subject's choices, so the optimal strategy was to choose the target with the higher expected payoff exclusively. The schizophrenia patients earned significantly less money during the first task, even though their overall choice probabilities were not significantly different from the control subjects. This was mostly because patients were impaired in integrating the outcomes of their previous choices appropriately in order to maintain the optimal strategy. During the second task, the choices of patients and control subjects displayed more similar patterns. This study elucidated the specific components in strategic decision making that are impaired in schizophrenia. The deficit, which can be characterized as strategic stiffness, may have implications for the poor social adjustment in schizophrenia patients.

Illusory versus genuine control in agent-based games

NASA Astrophysics Data System (ADS)

Satinover, J. B.; Sornette, D.

2009-02-01

In the Minority, Majority and Dollar Games (MG, MAJG, G) agents compete for rewards, acting in accord with the previously best-performing of their strategies. Different aspects/kinds of real-world markets are modelled by these games. In the MG, agents compete for scarce resources; in the MAJG agents imitate the group to exploit a trend; in the G agents attempt to predict and benefit both from trends and changes in the direction of a market. It has been previously shown that in the MG for a reasonable number of preliminary time steps preceding equilibrium (Time Horizon MG, THMG), agents’ attempt to optimize their gains by active strategy selection is “illusory”: the hypothetical gains of their strategies is greater on average than agents’ actual average gains. Furthermore, if a small proportion of agents deliberately choose and act in accord with their seemingly worst performing strategy, these outperform all other agents on average, and even attain mean positive gain, otherwise rare for agents in the MG. This latter phenomenon raises the question as to how well the optimization procedure works in the THMAJG and THG. We demonstrate that the illusion of control is absent in THMAJG and THG. This provides further clarification of the kinds of situations subject to genuine control, and those not, in set-ups a priori defined to emphasize the importance of optimization.

The Role of Metacognitive Reading Strategies, Metacognitive Study and Learning Strategies, and Behavioral Study and Learning Strategies in Predicting Academic Success in Students with and without a History of Reading Difficulties

ERIC Educational Resources Information Center

Chevalier, Thérèse M.; Parrila, Rauno; Ritchie, Krista C.; Deacon, S. Hélène

2017-01-01

We examined the self-reported use of reading, study, and learning strategies in university students with a history of reading difficulties (HRD; n = 77) and with no history of reading difficulties (NRD; n = 295). We examined both between-groups differences in strategy use and strategy use as a predictive measure of academic success. Participants…

The pulmonary physician in critical care * 4: Nosocomial pneumonia.

PubMed

Ewig, S; Bauer, T; Torres, A

2002-04-01

Much progress has been made in the understanding of nosocomial pneumonia but important issues in diagnosis and treatment remain unresolved. The controversy over diagnostic tools should be closed. Instead, every effort should be made to increase our ability to make valid clinical predictions about the presence of ventilator associated pneumonia and to establish criteria to guide restricting empirical antimicrobial treatment without causing patient harm. More emphasis must be put on local infection control measures such as routine surveillance of pathogens, definition of controlled policies of antimicrobial treatment, and effective implementation of strategies of prevention.

Control of complex networks requires both structure and dynamics

NASA Astrophysics Data System (ADS)

Gates, Alexander J.; Rocha, Luis M.

2016-04-01

The study of network structure has uncovered signatures of the organization of complex systems. However, there is also a need to understand how to control them; for example, identifying strategies to revert a diseased cell to a healthy state, or a mature cell to a pluripotent state. Two recent methodologies suggest that the controllability of complex systems can be predicted solely from the graph of interactions between variables, without considering their dynamics: structural controllability and minimum dominating sets. We demonstrate that such structure-only methods fail to characterize controllability when dynamics are introduced. We study Boolean network ensembles of network motifs as well as three models of biochemical regulation: the segment polarity network in Drosophila melanogaster, the cell cycle of budding yeast Saccharomyces cerevisiae, and the floral organ arrangement in Arabidopsis thaliana. We demonstrate that structure-only methods both undershoot and overshoot the number and which sets of critical variables best control the dynamics of these models, highlighting the importance of the actual system dynamics in determining control. Our analysis further shows that the logic of automata transition functions, namely how canalizing they are, plays an important role in the extent to which structure predicts dynamics.

How the type of input function affects the dynamic response of conducting polymer actuators

NASA Astrophysics Data System (ADS)

Xiang, Xingcan; Alici, Gursel; Mutlu, Rahim; Li, Weihua

2014-10-01

There has been a growing interest in smart actuators typified by conducting polymer actuators, especially in their (i) fabrication, modeling and control with minimum external data and (ii) applications in bio-inspired devices, robotics and mechatronics. Their control is a challenging research problem due to the complex and nonlinear properties of these actuators, which cannot be predicted accurately. Based on an input-shaping technique, we propose a new method to improve the conducting polymer actuators’ command-following ability, while minimizing their electric power consumption. We applied four input functions with smooth characteristics to a trilayer conducting polymer actuator to experimentally evaluate its command-following ability under an open-loop control strategy and a simulated feedback control strategy, and, more importantly, to quantify how the type of input function affects the dynamic response of this class of actuators. We have found that the four smooth inputs consume less electrical power than sharp inputs such as a step input with discontinuous higher-order derivatives. We also obtained an improved transient response performance from the smooth inputs, especially under the simulated feedback control strategy, which we have proposed previously [X Xiang, R Mutlu, G Alici, and W Li, 2014 “Control of conducting polymer actuators without physical feedback: simulated feedback control approach with particle swarm optimization’, Journal of Smart Materials and Structure, 23]. The idea of using a smooth input command, which results in lower power consumption and better control performance, can be extended to other smart actuators. Consuming less electrical energy or power will have a direct effect on enhancing the operational life of these actuators.

Contribution of organizational strategy to verbal learning and memory in adults with attention-deficit/hyperactivity disorder.

PubMed

Roth, Robert M; Wishart, Heather A; Flashman, Laura A; Riordan, Henry J; Huey, Leighton; Saykin, Andrew J

2004-01-01

Statistical mediation modeling was used to test the hypothesis that poor use of a semantic organizational strategy contributes to verbal learning and memory deficits in adults with attention-deficit/hyperactivity disorder (ADHD). Comparison of 28 adults with ADHD and 34 healthy controls revealed lower performance by the ADHD group on tests of verbal learning and memory, sustained attention, and use of semantic organization during encoding. Mediation modeling indicated that state anxiety, but not semantic organization, significantly contributed to the prediction of both learning and delayed recall in the ADHD group. The pattern of findings suggests that decreased verbal learning and memory in adult ADHD is due in part to situational anxiety and not to poor use of organizational strategies during encoding. ((c) 2004 APA, all rights reserved)

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.

Topographic models for predicting malaria vector breeding habitats: potential tools for vector control managers.

PubMed

Nmor, Jephtha C; Sunahara, Toshihiko; Goto, Kensuke; Futami, Kyoko; Sonye, George; Akweywa, Peter; Dida, Gabriel; Minakawa, Noboru

2013-01-16

Identification of malaria vector breeding sites can enhance control activities. Although associations between malaria vector breeding sites and topography are well recognized, practical models that predict breeding sites from topographic information are lacking. We used topographic variables derived from remotely sensed Digital Elevation Models (DEMs) to model the breeding sites of malaria vectors. We further compared the predictive strength of two different DEMs and evaluated the predictability of various habitat types inhabited by Anopheles larvae. Using GIS techniques, topographic variables were extracted from two DEMs: 1) Shuttle Radar Topography Mission 3 (SRTM3, 90-m resolution) and 2) the Advanced Spaceborne Thermal Emission Reflection Radiometer Global DEM (ASTER, 30-m resolution). We used data on breeding sites from an extensive field survey conducted on an island in western Kenya in 2006. Topographic variables were extracted for 826 breeding sites and for 4520 negative points that were randomly assigned. Logistic regression modelling was applied to characterize topographic features of the malaria vector breeding sites and predict their locations. Model accuracy was evaluated using the area under the receiver operating characteristics curve (AUC). All topographic variables derived from both DEMs were significantly correlated with breeding habitats except for the aspect of SRTM. The magnitude and direction of correlation for each variable were similar in the two DEMs. Multivariate models for SRTM and ASTER showed similar levels of fit indicated by Akaike information criterion (3959.3 and 3972.7, respectively), though the former was slightly better than the latter. The accuracy of prediction indicated by AUC was also similar in SRTM (0.758) and ASTER (0.755) in the training site. In the testing site, both SRTM and ASTER models showed higher AUC in the testing sites than in the training site (0.829 and 0.799, respectively). The predictability of habitat types varied. Drains, foot-prints, puddles and swamp habitat types were most predictable. Both SRTM and ASTER models had similar predictive potentials, which were sufficiently accurate to predict vector habitats. The free availability of these DEMs suggests that topographic predictive models could be widely used by vector control managers in Africa to complement malaria control strategies.

An empirical machine learning method for predicting potential fire control locations for pre-fire planning and operational fire management

Treesearch

Christopher D. O' Connor; David E. Calkin; Matthew P. Thompson

2017-01-01

During active fire incidents, decisions regarding where and how to safely and effectively deploy resources to meet management objectives are often made under rapidly evolving conditions, with limited time to assess management strategies or for development of backup plans if initial efforts prove unsuccessful. Under all but the most extreme fire weather conditions,...