Distributed robust adaptive control of high order nonlinear multi agent systems.

PubMed

Hashemi, Mahnaz; Shahgholian, Ghazanfar

2018-03-01

In this paper, a robust adaptive neural network based controller is presented for multi agent high order nonlinear systems with unknown nonlinear functions, unknown control gains and unknown actuator failures. At first, Neural Network (NN) is used to approximate the nonlinear uncertainty terms derived from the controller design procedure for the followers. Then, a novel distributed robust adaptive controller is developed by combining the backstepping method and the Dynamic Surface Control (DSC) approach. The proposed controllers are distributed in the sense that the designed controller for each follower agent only requires relative state information between itself and its neighbors. By using the Young's inequality, only few parameters need to be tuned regardless of NN nodes number. Accordingly, the problems of dimensionality curse and explosion of complexity are counteracted, simultaneously. New adaptive laws are designed by choosing the appropriate Lyapunov-Krasovskii functionals. The proposed approach proves the boundedness of all the closed-loop signals in addition to the convergence of the distributed tracking errors to a small neighborhood of the origin. Simulation results indicate that the proposed controller is effective and robust. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

NASA Astrophysics Data System (ADS)

Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian

2017-09-01

Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Applications

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1998-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

A Multi-Resolution Nonlinear Mapping Technique for Design and Analysis Application

NASA Technical Reports Server (NTRS)

Phan, Minh Q.

1997-01-01

This report describes a nonlinear mapping technique where the unknown static or dynamic system is approximated by a sum of dimensionally increasing functions (one-dimensional curves, two-dimensional surfaces, etc.). These lower dimensional functions are synthesized from a set of multi-resolution basis functions, where the resolutions specify the level of details at which the nonlinear system is approximated. The basis functions also cause the parameter estimation step to become linear. This feature is taken advantage of to derive a systematic procedure to determine and eliminate basis functions that are less significant for the particular system under identification. The number of unknown parameters that must be estimated is thus reduced and compact models obtained. The lower dimensional functions (identified curves and surfaces) permit a kind of "visualization" into the complexity of the nonlinearity itself.

Adaptive robust control of a class of non-affine variable-speed variable-pitch wind turbines with unmodeled dynamics.

PubMed

Bagheri, Pedram; Sun, Qiao

2016-07-01

In this paper, a novel synthesis of Nussbaum-type functions, and an adaptive radial-basis function neural network is proposed to design controllers for variable-speed, variable-pitch wind turbines. Dynamic equations of the wind turbine are highly nonlinear, uncertain, and affected by unknown disturbance sources. Furthermore, the dynamic equations are non-affine with respect to the pitch angle, which is a control input. To address these problems, a Nussbaum-type function, along with a dynamic control law are adopted to resolve the non-affine nature of the equations. Moreover, an adaptive radial-basis function neural network is designed to approximate non-parametric uncertainties. Further, the closed-loop system is made robust to unknown disturbance sources, where no prior knowledge of disturbance bound is assumed in advance. Finally, the Lyapunov stability analysis is conducted to show the stability of the entire closed-loop system. In order to verify analytical results, a simulation is presented and the results are compared to both a PI and an existing adaptive controllers. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Synthetic Molecular Evolution of Membrane-Active Peptides

NASA Astrophysics Data System (ADS)

Wimley, William

The physical chemistry of membrane partitioning largely determines the function of membrane active peptides. Membrane-active peptides have potential utility in many areas, including in the cellular delivery of polar compounds, cancer therapy, biosensor design, and in antibacterial, antiviral and antifungal therapies. Yet, despite decades of research on thousands of known examples, useful sequence-structure-function relationships are essentially unknown. Because peptide-membrane interactions within the highly fluid bilayer are dynamic and heterogeneous, accounts of mechanism are necessarily vague and descriptive, and have little predictive power. This creates a significant roadblock to advances in the field. We are bypassing that roadblock with synthetic molecular evolution: iterative peptide library design and orthogonal high-throughput screening. We start with template sequences that have at least some useful activity, and create small, focused libraries using structural and biophysical principles to design the sequence space around the template. Orthogonal high-throughput screening is used to identify gain-of-function peptides by simultaneously selecting for several different properties (e.g. solubility, activity and toxicity). Multiple generations of iterative library design and screening have enabled the identification of membrane-active sequences with heretofore unknown properties, including clinically relevant, broad-spectrum activity against drug-resistant bacteria and enveloped viruses as well as pH-triggered macromolecular poration.

Adaptive NN controller design for a class of nonlinear MIMO discrete-time systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip

2015-05-01

An adaptive neural network tracking control is studied for a class of multiple-input multiple-output (MIMO) nonlinear systems. The studied systems are in discrete-time form and the discretized dead-zone inputs are considered. In addition, the studied MIMO systems are composed of N subsystems, and each subsystem contains unknown functions and external disturbance. Due to the complicated framework of the discrete-time systems, the existence of the dead zone and the noncausal problem in discrete-time, it brings about difficulties for controlling such a class of systems. To overcome the noncausal problem, by defining the coordinate transformations, the studied systems are transformed into a special form, which is suitable for the backstepping design. The radial basis functions NNs are utilized to approximate the unknown functions of the systems. The adaptation laws and the controllers are designed based on the transformed systems. By using the Lyapunov method, it is proved that the closed-loop system is stable in the sense that the semiglobally uniformly ultimately bounded of all the signals and the tracking errors converge to a bounded compact set. The simulation examples and the comparisons with previous approaches are provided to illustrate the effectiveness of the proposed control algorithm.

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

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

NASA Astrophysics Data System (ADS)

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

2015-10-01

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

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

PubMed

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

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

Neuro-adaptive backstepping control of SISO non-affine systems with unknown gain sign.

PubMed

Ramezani, Zahra; Arefi, Mohammad Mehdi; Zargarzadeh, Hassan; Jahed-Motlagh, Mohammad Reza

2016-11-01

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. Copyright © 2016 ISA. All rights reserved.

Rendezvous with connectivity preservation for multi-robot systems with an unknown leader

NASA Astrophysics Data System (ADS)

Dong, Yi

2018-02-01

This paper studies the leader-following rendezvous problem with connectivity preservation for multi-agent systems composed of uncertain multi-robot systems subject to external disturbances and an unknown leader, both of which are generated by a so-called exosystem with parametric uncertainty. By combining internal model design, potential function technique and adaptive control, two distributed control strategies are proposed to maintain the connectivity of the communication network, to achieve the asymptotic tracking of all the followers to the output of the unknown leader system, as well as to reject unknown external disturbances. It is also worth to mention that the uncertain parameters in the multi-robot systems and exosystem are further allowed to belong to unknown and unbounded sets when applying the second fully distributed control law containing a dynamic gain inspired by high-gain adaptive control or self-tuning regulator.

Adaptive fuzzy prescribed performance control for MIMO nonlinear systems with unknown control direction and unknown dead-zone inputs.

PubMed

Shi, Wuxi; Luo, Rui; Li, Baoquan

2017-01-01

In this study, an adaptive fuzzy prescribed performance control approach is developed for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems with unknown control direction and unknown dead-zone inputs. The properties of symmetric matrix are exploited to design adaptive fuzzy prescribed performance controller, and a Nussbaum-type function is incorporated in the controller to estimate the unknown control direction. This method has two prominent advantages: it does not require the priori knowledge of control direction and only three parameters need to be updated on-line for this MIMO systems. It is proved that all the signals in the resulting closed-loop system are bounded and that the tracking errors converge to a small residual set with the prescribed performance bounds. The effectiveness of the proposed approach is validated by simulation results. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning.

PubMed

Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai

2014-07-01

In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

L∞-gain adaptive fuzzy fault accommodation control design for nonlinear time-delay systems.

PubMed

Wu, Huai-Ning; Qiang, Xiao-Hong; Guo, Lei

2011-06-01

In this paper, an adaptive fuzzy fault accommodation (FA) control design with a guaranteed L(∞)-gain performance is developed for a class of nonlinear time-delay systems with persistent bounded disturbances. Using the Lyapunov technique and the Razumikhin-type lemma, the existence condition of the L(∞) -gain adaptive fuzzy FA controllers is provided in terms of linear matrix inequalities (LMIs). In the proposed FA scheme, a fuzzy logic system is employed to approximate the unknown term in the derivative of the Lyapunov function due to the unknown fault function; a continuous-state feedback control strategy is adopted for the control design to avoid the undesirable chattering phenomenon. The resulting FA controllers can ensure that every response of the closed-loop system is uniformly ultimately bounded with a guaranteed L(∞)-gain performance in the presence of a fault. Moreover, by the existing LMI optimization technique, a suboptimal controller is obtained in the sense of minimizing an upper bound of the L(∞)-gain. Finally, the achieved simulation results on the FA control of a continuous stirred tank reactor (CSTR) show the effectiveness of the proposed design procedure.

Self-evaluation on Motion Adaptation for Service Robots

NASA Astrophysics Data System (ADS)

Funabora, Yuki; Yano, Yoshikazu; Doki, Shinji; Okuma, Shigeru

We suggest self motion evaluation method to adapt to environmental changes for service robots. Several motions such as walking, dancing, demonstration and so on are described with time series patterns. These motions are optimized with the architecture of the robot and under certain surrounding environment. Under unknown operating environment, robots cannot accomplish their tasks. We propose autonomous motion generation techniques based on heuristic search with histories of internal sensor values. New motion patterns are explored under unknown operating environment based on self-evaluation. Robot has some prepared motions which realize the tasks under the designed environment. Internal sensor values observed under the designed environment with prepared motions show the interaction results with the environment. Self-evaluation is composed of difference of internal sensor values between designed environment and unknown operating environment. Proposed method modifies the motions to synchronize the interaction results on both environment. New motion patterns are generated to maximize self-evaluation function without external information, such as run length, global position of robot, human observation and so on. Experimental results show that the possibility to adapt autonomously patterned motions to environmental changes.

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

Analysis of mammalian gene function through broad based phenotypic screens across a consortium of mouse clinics

PubMed Central

Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Mike; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; El Fertak, Lahcen; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl MJ; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Ed; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie

2015-01-01

The function of the majority of genes in the mouse and human genomes remains unknown. The mouse ES cell knockout resource provides a basis for characterisation of relationships between gene and phenotype. The EUMODIC consortium developed and validated robust methodologies for broad-based phenotyping of knockouts through a pipeline comprising 20 disease-orientated platforms. We developed novel statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no prior functional annotation. We captured data from over 27,000 mice finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. Novel phenotypes were uncovered for many genes with unknown function providing a powerful basis for hypothesis generation and further investigation in diverse systems. PMID:26214591

Adaptive Robust Output Feedback Control for a Marine Dynamic Positioning System Based on a High-Gain Observer.

PubMed

Du, Jialu; Hu, Xin; Liu, Hongbo; Chen, C L Philip

2015-11-01

This paper develops an adaptive robust output feedback control scheme for dynamically positioned ships with unavailable velocities and unknown dynamic parameters in an unknown time-variant disturbance environment. The controller is designed by incorporating the high-gain observer and radial basis function (RBF) neural networks in vectorial backstepping method. The high-gain observer provides the estimations of the ship position and heading as well as velocities. The RBF neural networks are employed to compensate for the uncertainties of ship dynamics. The adaptive laws incorporating a leakage term are designed to estimate the weights of RBF neural networks and the bounds of unknown time-variant environmental disturbances. In contrast to the existing results of dynamic positioning (DP) controllers, the proposed control scheme relies only on the ship position and heading measurements and does not require a priori knowledge of the ship dynamics and external disturbances. By means of Lyapunov functions, it is theoretically proved that our output feedback controller can control a ship's position and heading to the arbitrarily small neighborhood of the desired target values while guaranteeing that all signals in the closed-loop DP control system are uniformly ultimately bounded. Finally, simulations involving two ships are carried out, and simulation results demonstrate the effectiveness of the proposed control scheme.

Finite-time sliding surface constrained control for a robot manipulator with an unknown deadzone and disturbance.

PubMed

Ik Han, Seong; Lee, Jangmyung

2016-11-01

This paper presents finite-time sliding mode control (FSMC) with predefined constraints for the tracking error and sliding surface in order to obtain robust positioning of a robot manipulator with input nonlinearity due to an unknown deadzone and external disturbance. An assumed model feedforward FSMC was designed to avoid tedious identification procedures for the manipulator parameters and to obtain a fast response time. Two constraint switching control functions based on the tracking error and finite-time sliding surface were added to the FSMC to guarantee the predefined tracking performance despite the presence of an unknown deadzone and disturbance. The tracking error due to the deadzone and disturbance can be suppressed within the predefined error boundary simply by tuning the gain value of the constraint switching function and without the addition of an extra compensator. Therefore, the designed constraint controller has a simpler structure than conventional transformed error constraint methods and the sliding surface constraint scheme can also indirectly guarantee the tracking error constraint while being more stable than the tracking error constraint control. A simulation and experiment were performed on an articulated robot manipulator to validate the proposed control schemes. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

PubMed

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

Formation tracker design of multiple mobile robots with wheel perturbations: adaptive output-feedback approach

NASA Astrophysics Data System (ADS)

Yoo, Sung Jin

2016-11-01

This paper presents a theoretical design approach for output-feedback formation tracking of multiple mobile robots under wheel perturbations. It is assumed that these perturbations are unknown and the linear and angular velocities of the robots are unmeasurable. First, adaptive state observers for estimating unmeasurable velocities of the robots are developed under the robots' kinematics and dynamics including wheel perturbation effects. Then, we derive a virtual-structure-based formation tracker scheme according to the observer dynamic surface design procedure. The main difficulty of the output-feedback control design is to manage the coupling problems between unmeasurable velocities and unknown wheel perturbation effects. These problems are avoided by using the adaptive technique and the function approximation property based on fuzzy logic systems. From the Lyapunov stability analysis, it is shown that point tracking errors of each robot and synchronisation errors for the desired formation converge to an adjustable neighbourhood of the origin, while all signals in the controlled closed-loop system are semiglobally uniformly ultimately bounded.

Switched-Observer-Based Adaptive Neural Control of MIMO Switched Nonlinear Systems With Unknown Control Gains.

PubMed

Long, Lijun; Zhao, Jun

2017-07-01

In this paper, the problem of adaptive neural output-feedback control is addressed for a class of multi-input multioutput (MIMO) switched uncertain nonlinear systems with unknown control gains. Neural networks (NNs) are used to approximate unknown nonlinear functions. In order to avoid the conservativeness caused by adoption of a common observer for all subsystems, an MIMO NN switched observer is designed to estimate unmeasurable states. A new switched observer-based adaptive neural control technique for the problem studied is then provided by exploiting the classical average dwell time (ADT) method and the backstepping method and the Nussbaum gain technique. It effectively handles the obstacle about the coexistence of multiple Nussbaum-type function terms, and improves the classical ADT method, since the exponential decline property of Lyapunov functions for individual subsystems is no longer satisfied. It is shown that the technique proposed is able to guarantee semiglobal uniformly ultimately boundedness of all the signals in the closed-loop system under a class of switching signals with ADT, and the tracking errors converge to a small neighborhood of the origin. The effectiveness of the approach proposed is illustrated by its application to a two inverted pendulum system.

Analysis of mammalian gene function through broad-based phenotypic screens across a consortium of mouse clinics.

PubMed

de Angelis, Martin Hrabě; Nicholson, George; Selloum, Mohammed; White, Jacqui; Morgan, Hugh; Ramirez-Solis, Ramiro; Sorg, Tania; Wells, Sara; Fuchs, Helmut; Fray, Martin; Adams, David J; Adams, Niels C; Adler, Thure; Aguilar-Pimentel, Antonio; Ali-Hadji, Dalila; Amann, Gregory; André, Philippe; Atkins, Sarah; Auburtin, Aurelie; Ayadi, Abdel; Becker, Julien; Becker, Lore; Bedu, Elodie; Bekeredjian, Raffi; Birling, Marie-Christine; Blake, Andrew; Bottomley, Joanna; Bowl, Mike; Brault, Véronique; Busch, Dirk H; Bussell, James N; Calzada-Wack, Julia; Cater, Heather; Champy, Marie-France; Charles, Philippe; Chevalier, Claire; Chiani, Francesco; Codner, Gemma F; Combe, Roy; Cox, Roger; Dalloneau, Emilie; Dierich, André; Di Fenza, Armida; Doe, Brendan; Duchon, Arnaud; Eickelberg, Oliver; Esapa, Chris T; El Fertak, Lahcen; Feigel, Tanja; Emelyanova, Irina; Estabel, Jeanne; Favor, Jack; Flenniken, Ann; Gambadoro, Alessia; Garrett, Lilian; Gates, Hilary; Gerdin, Anna-Karin; Gkoutos, George; Greenaway, Simon; Glasl, Lisa; Goetz, Patrice; Da Cruz, Isabelle Goncalves; Götz, Alexander; Graw, Jochen; Guimond, Alain; Hans, Wolfgang; Hicks, Geoff; Hölter, Sabine M; Höfler, Heinz; Hancock, John M; Hoehndorf, Robert; Hough, Tertius; Houghton, Richard; Hurt, Anja; Ivandic, Boris; Jacobs, Hughes; Jacquot, Sylvie; Jones, Nora; Karp, Natasha A; Katus, Hugo A; Kitchen, Sharon; Klein-Rodewald, Tanja; Klingenspor, Martin; Klopstock, Thomas; Lalanne, Valerie; Leblanc, Sophie; Lengger, Christoph; le Marchand, Elise; Ludwig, Tonia; Lux, Aline; McKerlie, Colin; Maier, Holger; Mandel, Jean-Louis; Marschall, Susan; Mark, Manuel; Melvin, David G; Meziane, Hamid; Micklich, Kateryna; Mittelhauser, Christophe; Monassier, Laurent; Moulaert, David; Muller, Stéphanie; Naton, Beatrix; Neff, Frauke; Nolan, Patrick M; Nutter, Lauryl Mj; Ollert, Markus; Pavlovic, Guillaume; Pellegata, Natalia S; Peter, Emilie; Petit-Demoulière, Benoit; Pickard, Amanda; Podrini, Christine; Potter, Paul; Pouilly, Laurent; Puk, Oliver; Richardson, David; Rousseau, Stephane; Quintanilla-Fend, Leticia; Quwailid, Mohamed M; Racz, Ildiko; Rathkolb, Birgit; Riet, Fabrice; Rossant, Janet; Roux, Michel; Rozman, Jan; Ryder, Ed; Salisbury, Jennifer; Santos, Luis; Schäble, Karl-Heinz; Schiller, Evelyn; Schrewe, Anja; Schulz, Holger; Steinkamp, Ralf; Simon, Michelle; Stewart, Michelle; Stöger, Claudia; Stöger, Tobias; Sun, Minxuan; Sunter, David; Teboul, Lydia; Tilly, Isabelle; Tocchini-Valentini, Glauco P; Tost, Monica; Treise, Irina; Vasseur, Laurent; Velot, Emilie; Vogt-Weisenhorn, Daniela; Wagner, Christelle; Walling, Alison; Weber, Bruno; Wendling, Olivia; Westerberg, Henrik; Willershäuser, Monja; Wolf, Eckhard; Wolter, Anne; Wood, Joe; Wurst, Wolfgang; Yildirim, Ali Önder; Zeh, Ramona; Zimmer, Andreas; Zimprich, Annemarie; Holmes, Chris; Steel, Karen P; Herault, Yann; Gailus-Durner, Valérie; Mallon, Ann-Marie; Brown, Steve Dm

2015-09-01

The function of the majority of genes in the mouse and human genomes remains unknown. The mouse embryonic stem cell knockout resource provides a basis for the characterization of relationships between genes and phenotypes. The EUMODIC consortium developed and validated robust methodologies for the broad-based phenotyping of knockouts through a pipeline comprising 20 disease-oriented platforms. We developed new statistical methods for pipeline design and data analysis aimed at detecting reproducible phenotypes with high power. We acquired phenotype data from 449 mutant alleles, representing 320 unique genes, of which half had no previous functional annotation. We captured data from over 27,000 mice, finding that 83% of the mutant lines are phenodeviant, with 65% demonstrating pleiotropy. Surprisingly, we found significant differences in phenotype annotation according to zygosity. New phenotypes were uncovered for many genes with previously unknown function, providing a powerful basis for hypothesis generation and further investigation in diverse systems.

Adaptive Fuzzy Control Design for Stochastic Nonlinear Switched Systems With Arbitrary Switchings and Unmodeled Dynamics.

PubMed

Li, Yongming; Sui, Shuai; Tong, Shaocheng

2017-02-01

This paper deals with the problem of adaptive fuzzy output feedback control for a class of stochastic nonlinear switched systems. The controlled system in this paper possesses unmeasured states, completely unknown nonlinear system functions, unmodeled dynamics, and arbitrary switchings. A state observer which does not depend on the switching signal is constructed to tackle the unmeasured states. Fuzzy logic systems are employed to identify the completely unknown nonlinear system functions. Based on the common Lyapunov stability theory and stochastic small-gain theorem, a new robust adaptive fuzzy backstepping stabilization control strategy is developed. The stability of the closed-loop system on input-state-practically stable in probability is proved. The simulation results are given to verify the efficiency of the proposed fuzzy adaptive control scheme.

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

PubMed

Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Half-blind remote sensing image restoration with partly unknown degradation

NASA Astrophysics Data System (ADS)

Xie, Meihua; Yan, Fengxia

2017-01-01

The problem of image restoration has been extensively studied for its practical importance and theoretical interest. This paper mainly discusses the problem of image restoration with partly unknown kernel. In this model, the degraded kernel function is known but its parameters are unknown. With this model, we should estimate the parameters in Gaussian kernel and the real image simultaneity. For this new problem, a total variation restoration model is put out and an intersect direction iteration algorithm is designed. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index Measurement (SSIM) are used to measure the performance of the method. Numerical results show that we can estimate the parameters in kernel accurately, and the new method has both much higher PSNR and much higher SSIM than the expectation maximization (EM) method in many cases. In addition, the accuracy of estimation is not sensitive to noise. Furthermore, even though the support of the kernel is unknown, we can also use this method to get accurate estimation.

Adaptive Neural Tracking Control for Switched High-Order Stochastic Nonlinear Systems.

PubMed

Zhao, Xudong; Wang, Xinyong; Zong, Guangdeng; Zheng, Xiaolong

2017-10-01

This paper deals with adaptive neural tracking control design for a class of switched high-order stochastic nonlinear systems with unknown uncertainties and arbitrary deterministic switching. The considered issues are: 1) completely unknown uncertainties; 2) stochastic disturbances; and 3) high-order nonstrict-feedback system structure. The considered mathematical models can represent many practical systems in the actual engineering. By adopting the approximation ability of neural networks, common stochastic Lyapunov function method together with adding an improved power integrator technique, an adaptive state feedback controller with multiple adaptive laws is systematically designed for the systems. Subsequently, a controller with only two adaptive laws is proposed to solve the problem of over parameterization. Under the designed controllers, all the signals in the closed-loop system are bounded-input bounded-output stable in probability, and the system output can almost surely track the target trajectory within a specified bounded error. Finally, simulation results are presented to show the effectiveness of the proposed approaches.

Global tracking for a class of uncertain nonlinear systems with unknown sign-switching control direction by output feedback

NASA Astrophysics Data System (ADS)

Roux Oliveira, Tiago; Jacoud Peixoto, Alessandro; Hsu, Liu

2015-09-01

This paper addresses the design of a sliding mode controller for a class of high-order uncertain nonlinear plants with unmatched state-dependent nonlinearities and unknown sign of the high frequency gain, i.e., the control direction is assumed unknown. Differently from most previous studies, the control direction is allowed to switch its sign. We show that it is possible to obtain global exact tracking using only output-feedback by coupling a relay periodic switching function with a norm state observer. One significant advantage of the new scheme is its robustness and improved transient response under arbitrary changes of the control direction which have been theoretically demonstrated for jump variations and successfully tested by simulations. The proposed controller is also evaluated with a DC motor control experiment.

A Measure Approximation for Distributionally Robust PDE-Constrained Optimization Problems

DOE PAGES

Kouri, Drew Philip

2017-12-19

In numerous applications, scientists and engineers acquire varied forms of data that partially characterize the inputs to an underlying physical system. This data is then used to inform decisions such as controls and designs. Consequently, it is critical that the resulting control or design is robust to the inherent uncertainties associated with the unknown probabilistic characterization of the model inputs. Here in this work, we consider optimal control and design problems constrained by partial differential equations with uncertain inputs. We do not assume a known probabilistic model for the inputs, but rather we formulate the problem as a distributionally robustmore » optimization problem where the outer minimization problem determines the control or design, while the inner maximization problem determines the worst-case probability measure that matches desired characteristics of the data. We analyze the inner maximization problem in the space of measures and introduce a novel measure approximation technique, based on the approximation of continuous functions, to discretize the unknown probability measure. Finally, we prove consistency of our approximated min-max problem and conclude with numerical results.« less

Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

2013-09-01

In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

Observed-Based Adaptive Fuzzy Tracking Control for Switched Nonlinear Systems With Dead-Zone.

PubMed

Tong, Shaocheng; Sui, Shuai; Li, Yongming

2015-12-01

In this paper, the problem of adaptive fuzzy output-feedback control is investigated for a class of uncertain switched nonlinear systems in strict-feedback form. The considered switched systems contain unknown nonlinearities, dead-zone, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, a switched fuzzy state observer is designed and thus the immeasurable states are obtained by it. By applying the adaptive backstepping design principle and the average dwell time method, an adaptive fuzzy output-feedback tracking control approach is developed. It is proved that the proposed control approach can guarantee that all the variables in the closed-loop system are bounded under a class of switching signals with average dwell time, and also that the system output can track a given reference signal as closely as possible. The simulation results are given to check the effectiveness of the proposed approach.

Neural network L1 adaptive control of MIMO systems with nonlinear uncertainty.

PubMed

Zhen, Hong-tao; Qi, Xiao-hui; Li, Jie; Tian, Qing-min

2014-01-01

An indirect adaptive controller is developed for a class of multiple-input multiple-output (MIMO) nonlinear systems with unknown uncertainties. This control system is comprised of an L 1 adaptive controller and an auxiliary neural network (NN) compensation controller. The L 1 adaptive controller has guaranteed transient response in addition to stable tracking. In this architecture, a low-pass filter is adopted to guarantee fast adaptive rate without generating high-frequency oscillations in control signals. The auxiliary compensation controller is designed to approximate the unknown nonlinear functions by MIMO RBF neural networks to suppress the influence of uncertainties. NN weights are tuned on-line with no prior training and the project operator ensures the weights bounded. The global stability of the closed-system is derived based on the Lyapunov function. Numerical simulations of an MIMO system coupled with nonlinear uncertainties are used to illustrate the practical potential of our theoretical results.

Adaptive output feedback NN control of a class of discrete-time MIMO nonlinear systems with unknown control directions.

PubMed

Li, Yanan; Yang, Chenguang; Ge, Shuzhi Sam; Lee, Tong Heng

2011-04-01

In this paper, adaptive neural network (NN) control is investigated for a class of block triangular multiinput-multioutput nonlinear discrete-time systems with each subsystem in pure-feedback form with unknown control directions. These systems are of couplings in every equation of each subsystem, and different subsystems may have different orders. To avoid the noncausal problem in the control design, the system is transformed into a predictor form by rigorous derivation. By exploring the properties of the block triangular form, implicit controls are developed for each subsystem such that the couplings of inputs and states among subsystems have been completely decoupled. The radial basis function NN is employed to approximate the unknown control. Each subsystem achieves a semiglobal uniformly ultimately bounded stability with the proposed control, and simulation results are presented to demonstrate its efficiency.

Optical design for reliability and efficiency in concentrating photovoltaics

NASA Astrophysics Data System (ADS)

Leutz, Ralf; Annen, Hans Philipp; Fu, Ling

2010-08-01

Complex systems like modules in concentrating photovoltaics (CPV) are designed in a systems approach. The better the components are concerted, the better the performance goals of the system can be fulfilled. Optics are central to the CPV module's reliability and efficiency. Fresnel lens optics provide the module cover, and protect the module against the environment. Fresnel lenses on glass can provide the module's structural integrity. The secondary optical element, used to increase the collection of light, the acceptance half-angle, and the uniformity on the cell, may provide encapsulation for the receiver. This encapsulation function may be provided by some optical designs in sol gel, or silicone. Both materials are unknown in their longevity in this application. We present optical designs fulfilling structural or protective functions, discuss the optical penalties to be paid, and the innovative materials and manufacturing technologies to be tested.

Reinforcement learning neural-network-based controller for nonlinear discrete-time systems with input constraints.

PubMed

He, Pingan; Jagannathan, S

2007-04-01

A novel adaptive-critic-based neural network (NN) controller in discrete time is designed to deliver a desired tracking performance for a class of nonlinear systems in the presence of actuator constraints. The constraints of the actuator are treated in the controller design as the saturation nonlinearity. The adaptive critic NN controller architecture based on state feedback includes two NNs: the critic NN is used to approximate the "strategic" utility function, whereas the action NN is employed to minimize both the strategic utility function and the unknown nonlinear dynamic estimation errors. The critic and action NN weight updates are derived by minimizing certain quadratic performance indexes. Using the Lyapunov approach and with novel weight updates, the uniformly ultimate boundedness of the closed-loop tracking error and weight estimates is shown in the presence of NN approximation errors and bounded unknown disturbances. The proposed NN controller works in the presence of multiple nonlinearities, unlike other schemes that normally approximate one nonlinearity. Moreover, the adaptive critic NN controller does not require an explicit offline training phase, and the NN weights can be initialized at zero or random. Simulation results justify the theoretical analysis.

Adjoint-Based, Three-Dimensional Error Prediction and Grid Adaptation

NASA Technical Reports Server (NTRS)

Park, Michael A.

2002-01-01

Engineering computational fluid dynamics (CFD) analysis and design applications focus on output functions (e.g., lift, drag). Errors in these output functions are generally unknown and conservatively accurate solutions may be computed. Computable error estimates can offer the possibility to minimize computational work for a prescribed error tolerance. Such an estimate can be computed by solving the flow equations and the linear adjoint problem for the functional of interest. The computational mesh can be modified to minimize the uncertainty of a computed error estimate. This robust mesh-adaptation procedure automatically terminates when the simulation is within a user specified error tolerance. This procedure for estimating and adapting to error in a functional is demonstrated for three-dimensional Euler problems. An adaptive mesh procedure that links to a Computer Aided Design (CAD) surface representation is demonstrated for wing, wing-body, and extruded high lift airfoil configurations. The error estimation and adaptation procedure yielded corrected functions that are as accurate as functions calculated on uniformly refined grids with ten times as many grid points.

Observer-Based Adaptive NN Control for a Class of Uncertain Nonlinear Systems With Nonsymmetric Input Saturation.

PubMed

Yong-Feng Gao; Xi-Ming Sun; Changyun Wen; Wei Wang

2017-07-01

This paper is concerned with the problem of adaptive tracking control for a class of uncertain nonlinear systems with nonsymmetric input saturation and immeasurable states. The radial basis function of neural network (NN) is employed to approximate unknown functions, and an NN state observer is designed to estimate the immeasurable states. To analyze the effect of input saturation, an auxiliary system is employed. By the aid of adaptive backstepping technique, an adaptive tracking control approach is developed. Under the proposed adaptive tracking controller, the boundedness of all the signals in the closed-loop system is achieved. Moreover, distinct from most of the existing references, the tracking error can be bounded by an explicit function of design parameters and saturation input error. Finally, an example is given to show the effectiveness of the proposed method.

Type-2 fuzzy logic control of a 2-DOF helicopter (TRMS system)

NASA Astrophysics Data System (ADS)

Zeghlache, Samir; Kara, Kamel; Saigaa, Djamel

2014-09-01

The helicopter dynamic includes nonlinearities, parametric uncertainties and is subject to unknown external disturbances. Such complicated dynamics involve designing sophisticated control algorithms that can deal with these difficulties. In this paper, a type 2 fuzzy logic PID controller is proposed for TRMS (twin rotor mimo system) control problem. Using triangular membership functions and based on a human operator experience, two controllers are designed to control the position of the yaw and the pitch angles of the TRMS. Simulation results are given to illustrate the effectiveness of the proposed control scheme.

A Randomized, Crossover Clinical Trial of Exoskeletal-Assisted Walking to Improve Mobility, Bowel Function, and Cardiometabolic Profiles in Persons with SCI

DTIC Science & Technology

2015-10-01

comply with a collection of information if it does not display a currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS...participants and at three study sites. It is also designed to determine if the body composition and bowel function benefits that were observed with as few...demonstrated that ten participants were able to use the device to successfully walk for four to six hours per week for three months. It is unknown if a

Searching for an Axis-Parallel Shoreline

NASA Astrophysics Data System (ADS)

Langetepe, Elmar

We are searching for an unknown horizontal or vertical line in the plane under the competitive framework. We design a framework for lower bounds on all cyclic and monotone strategies that result in two-sequence functionals. For optimizing such functionals we apply a method that combines two main paradigms. The given solution shows that the combination method is of general interest. Finally, we obtain the current best strategy and can prove that this is the best strategy among all cyclic and monotone strategies which is a main step toward a lower bound construction.

Stability of Nonlinear Systems with Unknown Time-varying Feedback Delay

NASA Astrophysics Data System (ADS)

Chunodkar, Apurva A.; Akella, Maruthi R.

2013-12-01

This paper considers the problem of stabilizing a class of nonlinear systems with unknown bounded delayed feedback wherein the time-varying delay is 1) piecewise constant 2) continuous with a bounded rate. We also consider application of these results to the stabilization of rigid-body attitude dynamics. In the first case, the time-delay in feedback is modeled specifically as a switch among an arbitrarily large set of unknown constant values with a known strict upper bound. The feedback is a linear function of the delayed states. In the case of linear systems with switched delay feedback, a new sufficiency condition for average dwell time result is presented using a complete type Lyapunov-Krasovskii (L-K) functional approach. Further, the corresponding switched system with nonlinear perturbations is proven to be exponentially stable inside a well characterized region of attraction for an appropriately chosen average dwell time. In the second case, the concept of the complete type L-K functional is extended to a class of nonlinear time-delay systems with unknown time-varying time-delay. This extension ensures stability robustness to time-delay in the control design for all values of time-delay less than the known upper bound. Model-transformation is used in order to partition the nonlinear system into a nominal linear part that is exponentially stable with a bounded perturbation. We obtain sufficient conditions which ensure exponential stability inside a region of attraction estimate. A constructive method to evaluate the sufficient conditions is presented together with comparison with the corresponding constant and piecewise constant delay. Numerical simulations are performed to illustrate the theoretical results of this paper.

Plant functional genomics

NASA Astrophysics Data System (ADS)

Holtorf, Hauke; Guitton, Marie-Christine; Reski, Ralf

2002-04-01

Functional genome analysis of plants has entered the high-throughput stage. The complete genome information from key species such as Arabidopsis thaliana and rice is now available and will further boost the application of a range of new technologies to functional plant gene analysis. To broadly assign functions to unknown genes, different fast and multiparallel approaches are currently used and developed. These new technologies are based on known methods but are adapted and improved to accommodate for comprehensive, large-scale gene analysis, i.e. such techniques are novel in the sense that their design allows researchers to analyse many genes at the same time and at an unprecedented pace. Such methods allow analysis of the different constituents of the cell that help to deduce gene function, namely the transcripts, proteins and metabolites. Similarly the phenotypic variations of entire mutant collections can now be analysed in a much faster and more efficient way than before. The different methodologies have developed to form their own fields within the functional genomics technological platform and are termed transcriptomics, proteomics, metabolomics and phenomics. Gene function, however, cannot solely be inferred by using only one such approach. Rather, it is only by bringing together all the information collected by different functional genomic tools that one will be able to unequivocally assign functions to unknown plant genes. This review focuses on current technical developments and their impact on the field of plant functional genomics. The lower plant Physcomitrella is introduced as a new model system for gene function analysis, owing to its high rate of homologous recombination.

Locally optimal control under unknown dynamics with learnt cost function: application to industrial robot positioning

NASA Astrophysics Data System (ADS)

Guérin, Joris; Gibaru, Olivier; Thiery, Stéphane; Nyiri, Eric

2017-01-01

Recent methods of Reinforcement Learning have enabled to solve difficult, high dimensional, robotic tasks under unknown dynamics using iterative Linear Quadratic Gaussian control theory. These algorithms are based on building a local time-varying linear model of the dynamics from data gathered through interaction with the environment. In such tasks, the cost function is often expressed directly in terms of the state and control variables so that it can be locally quadratized to run the algorithm. If the cost is expressed in terms of other variables, a model is required to compute the cost function from the variables manipulated. We propose a method to learn the cost function directly from the data, in the same way as for the dynamics. This way, the cost function can be defined in terms of any measurable quantity and thus can be chosen more appropriately for the task to be carried out. With our method, any sensor information can be used to design the cost function. We demonstrate the efficiency of this method through simulating, with the V-REP software, the learning of a Cartesian positioning task on several industrial robots with different characteristics. The robots are controlled in joint space and no model is provided a priori. Our results are compared with another model free technique, consisting in writing the cost function as a state variable.

Predicting the Functional Impact of KCNQ1 Variants of Unknown Significance.

PubMed

Li, Bian; Mendenhall, Jeffrey L; Kroncke, Brett M; Taylor, Keenan C; Huang, Hui; Smith, Derek K; Vanoye, Carlos G; Blume, Jeffrey D; George, Alfred L; Sanders, Charles R; Meiler, Jens

2017-10-01

An emerging standard-of-care for long-QT syndrome uses clinical genetic testing to identify genetic variants of the KCNQ1 potassium channel. However, interpreting results from genetic testing is confounded by the presence of variants of unknown significance for which there is inadequate evidence of pathogenicity. In this study, we curated from the literature a high-quality set of 107 functionally characterized KCNQ1 variants. Based on this data set, we completed a detailed quantitative analysis on the sequence conservation patterns of subdomains of KCNQ1 and the distribution of pathogenic variants therein. We found that conserved subdomains generally are critical for channel function and are enriched with dysfunctional variants. Using this experimentally validated data set, we trained a neural network, designated Q1VarPred, specifically for predicting the functional impact of KCNQ1 variants of unknown significance. The estimated predictive performance of Q1VarPred in terms of Matthew's correlation coefficient and area under the receiver operating characteristic curve were 0.581 and 0.884, respectively, superior to the performance of 8 previous methods tested in parallel. Q1VarPred is publicly available as a web server at http://meilerlab.org/q1varpred. Although a plethora of tools are available for making pathogenicity predictions over a genome-wide scale, previous tools fail to perform in a robust manner when applied to KCNQ1. The contrasting and favorable results for Q1VarPred suggest a promising approach, where a machine-learning algorithm is tailored to a specific protein target and trained with a functionally validated data set to calibrate informatics tools. © 2017 American Heart Association, Inc.

Adaptive output-feedback control for switched stochastic uncertain nonlinear systems with time-varying delay.

PubMed

Song, Zhibao; Zhai, Junyong

2018-04-01

This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Fault-tolerant optimised tracking control for unknown discrete-time linear systems using a combined reinforcement learning and residual compensation methodology

NASA Astrophysics Data System (ADS)

Han, Ke-Zhen; Feng, Jian; Cui, Xiaohong

2017-10-01

This paper considers the fault-tolerant optimised tracking control (FTOTC) problem for unknown discrete-time linear system. A research scheme is proposed on the basis of data-based parity space identification, reinforcement learning and residual compensation techniques. The main characteristic of this research scheme lies in the parity-space-identification-based simultaneous tracking control and residual compensation. The specific technical line consists of four main contents: apply subspace aided method to design observer-based residual generator; use reinforcement Q-learning approach to solve optimised tracking control policy; rely on robust H∞ theory to achieve noise attenuation; adopt fault estimation triggered by residual generator to perform fault compensation. To clarify the design and implementation procedures, an integrated algorithm is further constructed to link up these four functional units. The detailed analysis and proof are subsequently given to explain the guaranteed FTOTC performance of the proposed conclusions. Finally, a case simulation is provided to verify its effectiveness.

Distributed Adaptive Fuzzy Control for Nonlinear Multiagent Systems Via Sliding Mode Observers.

PubMed

Shen, Qikun; Shi, Peng; Shi, Yan

2016-12-01

In this paper, the problem of distributed adaptive fuzzy control is investigated for high-order uncertain nonlinear multiagent systems on directed graph with a fixed topology. It is assumed that only the outputs of each follower and its neighbors are available in the design of its distributed controllers. Equivalent output injection sliding mode observers are proposed for each follower to estimate the states of itself and its neighbors, and an observer-based distributed adaptive controller is designed for each follower to guarantee that it asymptotically synchronizes to a leader with tracking errors being semi-globally uniform ultimate bounded, in which fuzzy logic systems are utilized to approximate unknown functions. Based on algebraic graph theory and Lyapunov function approach, using Filippov-framework, the closed-loop system stability analysis is conducted. Finally, numerical simulations are provided to illustrate the effectiveness and potential of the developed design techniques.

M-MRAC Backstepping for Systems with Unknown Virtual Control Coefficients

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje

2015-01-01

The paper presents an over-parametrization free certainty equivalence state feedback backstepping adaptive control design method for systems of any relative degree with unmatched uncertainties and unknown virtual control coefficients. It uses a fast prediction model to estimate the unknown parameters, which is independent of the control design. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters. The benefits of the approach are demonstrated in numerical simulations.

RNA structures as mediators of neurological diseases and as drug targets

PubMed Central

Bernat, Viachaslau; Disney, Matthew D.

2015-01-01

RNAs adopt diverse folded structures that are essential for function and thus play critical roles in cellular biology. A striking example of this is the ribosome, a complex, three-dimensionally folded macromolecular machine that orchestrates protein synthesis. Advances in RNA biochemistry, structural and molecular biology, and bioinformatics have revealed other non-coding RNAs whose functions are dictated by their structure. It is not surprising that aberrantly folded RNA structures contribute to disease. In this review, we provide a brief introduction into RNA structural biology and then describe how RNA structures function in cells and cause or contribute to neurological disease. Finally, we highlight successful applications of rational design principles to provide chemical probes and lead compounds targeting structured RNAs. Based on several examples of well-characterized RNA-driven neurological disorders, we demonstrate how designed small molecules can facilitate study of RNA dysfunction, elucidating previously unknown roles for RNA in disease, and provide lead therapeutics. PMID:26139368

Distributed adaptive asymptotically consensus tracking control of uncertain Euler-Lagrange systems under directed graph condition.

PubMed

Wang, Wei; Wen, Changyun; Huang, Jiangshuai; Fan, Huijin

2017-11-01

In this paper, a backstepping based distributed adaptive control scheme is proposed for multiple uncertain Euler-Lagrange systems under directed graph condition. The common desired trajectory is allowed totally unknown by part of the subsystems and the linearly parameterized trajectory model assumed in currently available results is no longer needed. To compensate the effects due to unknown trajectory information, a smooth function of consensus errors and certain positive integrable functions are introduced in designing virtual control inputs. Besides, to overcome the difficulty of completely counteracting the coupling terms of distributed consensus errors and parameter estimation errors in the presence of asymmetric Laplacian matrix, extra information transmission of local parameter estimates are introduced among linked subsystem and adaptive gain technique is adopted to generate distributed torque inputs. It is shown that with the proposed distributed adaptive control scheme, global uniform boundedness of all the closed-loop signals and asymptotically output consensus tracking can be achieved. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Via generalized function projective synchronization in nonlinear Schrödinger equation for secure communication

NASA Astrophysics Data System (ADS)

Zhao, L. W.; Du, J. G.; Yin, J. L.

2018-05-01

This paper proposes a novel secured communication scheme in a chaotic system by applying generalized function projective synchronization of the nonlinear Schrödinger equation. This phenomenal approach guarantees a secured and convenient communication. Our study applied the Melnikov theorem with an active control strategy to suppress chaos in the system. The transmitted information signal is modulated into the parameter of the nonlinear Schrödinger equation in the transmitter and it is assumed that the parameter of the receiver system is unknown. Based on the Lyapunov stability theory and the adaptive control technique, the controllers are designed to make two identical nonlinear Schrödinger equation with the unknown parameter asymptotically synchronized. The numerical simulation results of our study confirmed the validity, effectiveness and the feasibility of the proposed novel synchronization method and error estimate for a secure communication. The Chaos masking signals of the information communication scheme, further guaranteed a safer and secured information communicated via this approach.

Quasi-finite-time control for high-order nonlinear systems with mismatched disturbances via mapping filtered forwarding technique

NASA Astrophysics Data System (ADS)

Zhang, X.; Huang, X. L.; Lu, H. Q.

2017-02-01

In this study, a quasi-finite-time control method for designing stabilising control laws is developed for high-order strict-feedback nonlinear systems with mismatched disturbances. By using mapping filtered forwarding technique, a virtual control is designed to force the off-the-manifold coordinate to converge to zero in quasi-finite time at each step of the design; at the same time, the manifold is rendered insensitive to time-varying, bounded and unknown disturbances. In terms of standard forwarding methodology, the algorithm proposed here not only does not require the Lyapunov function for controller design, but also avoids to calculate the derivative of sign function. As far as the dynamic performance of closed-loop systems is concerned, we essentially obtain the finite-time performances, which is typically reflected in the following aspects: fast and accurate responses, high tracking precision, and robust disturbance rejection. Spring, mass, and damper system and flexible joints robot are tested to demonstrate the proposed controller performance.

How to Frame the Un-Known? The Odd Alliance of Design and "Fundamental Physics" in a Design School

ERIC Educational Resources Information Center

Gentes, Annie; Renon, Anne-Lyse; Bobroff, Julien

2017-01-01

This paper analyzes the introduction of fundamental physics in design education as a pedagogical method that trains designers to create with the un-known. It studies how three workshops offered design students to work on: superconductivity in 2011, quantum physics in 2013 and light and optics in 2014. The authors observe that introducing physics…

Design Pedagogy for an Unknown Future: A View from the Expanding Field of Design Scholarship and Professional Practice

ERIC Educational Resources Information Center

Wilson, Stephanie Elizabeth; Zamberlan, Lisa

2017-01-01

This article draws on current research investigating the notion of design for an unknown future. It reflects on recent thinking about the role of creativity in design practice and discusses implications for the development and assessment of creativity in the design studio. It begins with a review of literature on the issues and challenges…

An Approach to Function Annotation for Proteins of Unknown Function (PUFs) in the Transcriptome of Indian Mulberry.

PubMed

Dhanyalakshmi, K H; Naika, Mahantesha B N; Sajeevan, R S; Mathew, Oommen K; Shafi, K Mohamed; Sowdhamini, Ramanathan; N Nataraja, Karaba

2016-01-01

The modern sequencing technologies are generating large volumes of information at the transcriptome and genome level. Translation of this information into a biological meaning is far behind the race due to which a significant portion of proteins discovered remain as proteins of unknown function (PUFs). Attempts to uncover the functional significance of PUFs are limited due to lack of easy and high throughput functional annotation tools. Here, we report an approach to assign putative functions to PUFs, identified in the transcriptome of mulberry, a perennial tree commonly cultivated as host of silkworm. We utilized the mulberry PUFs generated from leaf tissues exposed to drought stress at whole plant level. A sequence and structure based computational analysis predicted the probable function of the PUFs. For rapid and easy annotation of PUFs, we developed an automated pipeline by integrating diverse bioinformatics tools, designated as PUFs Annotation Server (PUFAS), which also provides a web service API (Application Programming Interface) for a large-scale analysis up to a genome. The expression analysis of three selected PUFs annotated by the pipeline revealed abiotic stress responsiveness of the genes, and hence their potential role in stress acclimation pathways. The automated pipeline developed here could be extended to assign functions to PUFs from any organism in general. PUFAS web server is available at http://caps.ncbs.res.in/pufas/ and the web service is accessible at http://capservices.ncbs.res.in/help/pufas.

Proteins of unknown function in the Protein Data Bank (PDB): an inventory of true uncharacterized proteins and computational tools for their analysis.

PubMed

Nadzirin, Nurul; Firdaus-Raih, Mohd

2012-10-08

Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB). Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files) that were categorized under "unknown function" are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.

Decentralized Adaptive Neural Output-Feedback DSC for Switched Large-Scale Nonlinear Systems.

PubMed

Lijun Long; Jun Zhao

2017-04-01

In this paper, for a class of switched large-scale uncertain nonlinear systems with unknown control coefficients and unmeasurable states, a switched-dynamic-surface-based decentralized adaptive neural output-feedback control approach is developed. The approach proposed extends the classical dynamic surface control (DSC) technique for nonswitched version to switched version by designing switched first-order filters, which overcomes the problem of multiple "explosion of complexity." Also, a dual common coordinates transformation of all subsystems is exploited to avoid individual coordinate transformations for subsystems that are required when applying the backstepping recursive design scheme. Nussbaum-type functions are utilized to handle the unknown control coefficients, and a switched neural network observer is constructed to estimate the unmeasurable states. Combining with the average dwell time method and backstepping and the DSC technique, decentralized adaptive neural controllers of subsystems are explicitly designed. It is proved that the approach provided can guarantee the semiglobal uniformly ultimately boundedness for all the signals in the closed-loop system under a class of switching signals with average dwell time, and the tracking errors to a small neighborhood of the origin. A two inverted pendulums system is provided to demonstrate the effectiveness of the method proposed.

Identification of vehicle suspension parameters by design optimization

NASA Astrophysics Data System (ADS)

Tey, J. Y.; Ramli, R.; Kheng, C. W.; Chong, S. Y.; Abidin, M. A. Z.

2014-05-01

The design of a vehicle suspension system through simulation requires accurate representation of the design parameters. These parameters are usually difficult to measure or sometimes unavailable. This article proposes an efficient approach to identify the unknown parameters through optimization based on experimental results, where the covariance matrix adaptation-evolutionary strategy (CMA-es) is utilized to improve the simulation and experimental results against the kinematic and compliance tests. This speeds up the design and development cycle by recovering all the unknown data with respect to a set of kinematic measurements through a single optimization process. A case study employing a McPherson strut suspension system is modelled in a multi-body dynamic system. Three kinematic and compliance tests are examined, namely, vertical parallel wheel travel, opposite wheel travel and single wheel travel. The problem is formulated as a multi-objective optimization problem with 40 objectives and 49 design parameters. A hierarchical clustering method based on global sensitivity analysis is used to reduce the number of objectives to 30 by grouping correlated objectives together. Then, a dynamic summation of rank value is used as pseudo-objective functions to reformulate the multi-objective optimization to a single-objective optimization problem. The optimized results show a significant improvement in the correlation between the simulated model and the experimental model. Once accurate representation of the vehicle suspension model is achieved, further analysis, such as ride and handling performances, can be implemented for further optimization.

'Unknown' proteins and 'orphan' enzymes: the missing half of the engineering parts list--and how to find it.

PubMed

Hanson, Andrew D; Pribat, Anne; Waller, Jeffrey C; de Crécy-Lagard, Valérie

2009-12-14

Like other forms of engineering, metabolic engineering requires knowledge of the components (the 'parts list') of the target system. Lack of such knowledge impairs both rational engineering design and diagnosis of the reasons for failures; it also poses problems for the related field of metabolic reconstruction, which uses a cell's parts list to recreate its metabolic activities in silico. Despite spectacular progress in genome sequencing, the parts lists for most organisms that we seek to manipulate remain highly incomplete, due to the dual problem of 'unknown' proteins and 'orphan' enzymes. The former are all the proteins deduced from genome sequence that have no known function, and the latter are all the enzymes described in the literature (and often catalogued in the EC database) for which no corresponding gene has been reported. Unknown proteins constitute up to about half of the proteins in prokaryotic genomes, and much more than this in higher plants and animals. Orphan enzymes make up more than a third of the EC database. Attacking the 'missing parts list' problem is accordingly one of the great challenges for post-genomic biology, and a tremendous opportunity to discover new facets of life's machinery. Success will require a co-ordinated community-wide attack, sustained over years. In this attack, comparative genomics is probably the single most effective strategy, for it can reliably predict functions for unknown proteins and genes for orphan enzymes. Furthermore, it is cost-efficient and increasingly straightforward to deploy owing to a proliferation of databases and associated tools.

Generation and Analysis of Expressed Sequence Tags from Olea europaea L.

PubMed Central

Ozdemir Ozgenturk, Nehir; Oruç, Fatma; Sezerman, Ugur; Kuçukural, Alper; Vural Korkut, Senay; Toksoz, Feriha; Un, Cemal

2010-01-01

Olive (Olea europaea L.) is an important source of edible oil which was originated in Near-East region. In this study, two cDNA libraries were constructed from young olive leaves and immature olive fruits for generation of ESTs to discover the novel genes and search the function of unknown genes of olive. The randomly selected 3840 colonies were sequenced for EST collection from both libraries. Readable 2228 sequences for olive leaf and 1506 sequences for olive fruit were assembled into 205 and 69 contigs, respectively, whereas 2478 were singletons. Putative functions of all 2752 differentially expressed unique sequences were designated by gene homology based on BLAST and annotated using BLAST2GO. While 1339 ESTs show no homology to the database, 2024 ESTs have homology (under 80%) with hypothetical proteins, putative proteins, expressed proteins, and unknown proteins in NCBI-GenBank. 635 EST's unique genes sequence have been identified by over 80% homology to known function in other species which were not previously described in Olea family. Only 3.1% of total EST's was shown similarity with olive database existing in NCBI. This generated EST's data and consensus sequences were submitted to NCBI as valuable source for functional genome studies of olive. PMID:21197085

Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints

NASA Astrophysics Data System (ADS)

Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.

2018-02-01

This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.

An analytic-numerical method for the construction of the reference law of operation for a class of mechanical controlled systems

NASA Astrophysics Data System (ADS)

Mizhidon, A. D.; Mizhidon, K. A.

2017-04-01

An analytic-numerical method for the construction of a reference law of operation for a class of dynamic systems describing vibrations in controlled mechanical systems is proposed. By the reference law of operation of a system, we mean a law of the system motion that satisfies all the requirements for the quality and design features of the system under permanent external disturbances. As disturbances, we consider polyharmonic functions with known amplitudes and frequencies of the harmonics but unknown initial phases. For constructing the reference law of motion, an auxiliary optimal control problem is solved in which the cost function depends on a weighting coefficient. The choice of the weighting coefficient ensures the design of the reference law. Theoretical foundations of the proposed method are given.

Transcriptome analysis of salinity stress responses in common wheat using a 22k oligo-DNA microarray.

PubMed

Kawaura, Kanako; Mochida, Keiichi; Yamazaki, Yukiko; Ogihara, Yasunari

2006-04-01

In this study, we constructed a 22k wheat oligo-DNA microarray. A total of 148,676 expressed sequence tags of common wheat were collected from the database of the Wheat Genomics Consortium of Japan. These were grouped into 34,064 contigs, which were then used to design an oligonucleotide DNA microarray. Following a multistep selection of the sense strand, 21,939 60-mer oligo-DNA probes were selected for attachment on the microarray slide. This 22k oligo-DNA microarray was used to examine the transcriptional response of wheat to salt stress. More than 95% of the probes gave reproducible hybridization signals when targeted with RNAs extracted from salt-treated wheat shoots and roots. With the microarray, we identified 1,811 genes whose expressions changed more than 2-fold in response to salt. These included genes known to mediate response to salt, as well as unknown genes, and they were classified into 12 major groups by hierarchical clustering. These gene expression patterns were also confirmed by real-time reverse transcription-PCR. Many of the genes with unknown function were clustered together with genes known to be involved in response to salt stress. Thus, analysis of gene expression patterns combined with gene ontology should help identify the function of the unknown genes. Also, functional analysis of these wheat genes should provide new insight into the response to salt stress. Finally, these results indicate that the 22k oligo-DNA microarray is a reliable method for monitoring global gene expression patterns in wheat.

A Report on Applying EEGnet to Discriminate Human State Effects on Task Performance

DTIC Science & Technology

2018-01-01

whether we could identify what task the participant was performing from differences in the recorded brain time series . We modeled the relationship...between input data (brain time series ) and output labels (task A and task B) as an unknown function, and we found an optimal approximation of that...this report are not to be construed as an official Department of the Army position unless so designated by other authorized documents. Citation of

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

Andrews, Madison Theresa; Bates, Cameron Russell; Mckigney, Edward Allen

Accurate detector modeling is a requirement to design systems in many non-proliferation scenarios; by determining a Detector’s Response Function (DRF) to incident radiation, it is possible characterize measurements of unknown sources. DRiFT is intended to post-process MCNP® output and create realistic detector spectra. Capabilities currently under development include the simulation of semiconductor, gas, and (as is discussed in this work) scintillator detector physics. Energy spectra and pulse shape discrimination (PSD) trends for incident photon and neutron radiation have been reproduced by DRiFT.

Characterization and inhibition of a cholecystokinin-inactivating serine peptidase.

PubMed

Rose, C; Vargas, F; Facchinetti, P; Bourgeat, P; Bambal, R B; Bishop, P B; Chan, S M; Moore, A N; Ganellin, C R; Schwartz, J C

1996-04-04

A cholecystokinin (CCK)-inactivating peptidase was purified and identified as a membrane-bound isoform of tripeptidyl peptidase II (EC 3.4.14.10), a cytosolic subtilisin-like peptidase of previously unknown functions. The peptidase was found in neurons responding to cholecystokinin, as well as in non-neuronal cells. Butabindide, a potent and specific inhibitor, was designed and shown to protect endogenous cholecystokinin from inactivation and to display pro-satiating effects mediated by the CCKA receptor.

A robust H∞-tracking design for uncertain Takagi-Sugeno fuzzy systems with unknown premise variables using descriptor redundancy approach

NASA Astrophysics Data System (ADS)

Hassan Asemani, Mohammad; Johari Majd, Vahid

2015-12-01

This paper addresses a robust H∞ fuzzy observer-based tracking design problem for uncertain Takagi-Sugeno fuzzy systems with external disturbances. To have a practical observer-based controller, the premise variables of the system are assumed to be not measurable in general, which leads to a more complex design process. The tracker is synthesised based on a fuzzy Lyapunov function approach and non-parallel distributed compensation (non-PDC) scheme. Using the descriptor redundancy approach, the robust stability conditions are derived in the form of strict linear matrix inequalities (LMIs) even in the presence of uncertainties in the system, input, and output matrices simultaneously. Numerical simulations are provided to show the effectiveness of the proposed method.

Neural network-based adaptive dynamic surface control for permanent magnet synchronous motors.

PubMed

Yu, Jinpeng; Shi, Peng; Dong, Wenjie; Chen, Bing; Lin, Chong

2015-03-01

This brief considers the problem of neural networks (NNs)-based adaptive dynamic surface control (DSC) for permanent magnet synchronous motors (PMSMs) with parameter uncertainties and load torque disturbance. First, NNs are used to approximate the unknown and nonlinear functions of PMSM drive system and a novel adaptive DSC is constructed to avoid the explosion of complexity in the backstepping design. Next, under the proposed adaptive neural DSC, the number of adaptive parameters required is reduced to only one, and the designed neural controllers structure is much simpler than some existing results in literature, which can guarantee that the tracking error converges to a small neighborhood of the origin. Then, simulations are given to illustrate the effectiveness and potential of the new design technique.

Design of microstrip patch antennas using knowledge insertion through retraining

NASA Astrophysics Data System (ADS)

Divakar, T. V. S.; Sudhakar, A.

2018-04-01

The traditional way of analyzing/designing neural network is to collect experimental data and train neural network. Then, the trained neural network acts as global approximate function. The network is then used to calculate parameters for unknown configurations. The main drawback of this method is one does not have enough experimental data, cost of prototypes being a major factor [1-4]. Therefore, in this method the author collected training data from available approximate formulas with in full design range and trained the network with it. After successful training, the network is retrained with available measured results. This simple way inserts experimental knowledge into the network [5]. This method is tested for rectangular microstrip antenna and circular microstrip antenna.

Adaptive neural network decentralized backstepping output-feedback control for nonlinear large-scale systems with time delays.

PubMed

Tong, Shao Cheng; Li, Yong Ming; Zhang, Hua-Guang

2011-07-01

In this paper, two adaptive neural network (NN) decentralized output feedback control approaches are proposed for a class of uncertain nonlinear large-scale systems with immeasurable states and unknown time delays. Using NNs to approximate the unknown nonlinear functions, an NN state observer is designed to estimate the immeasurable states. By combining the adaptive backstepping technique with decentralized control design principle, an adaptive NN decentralized output feedback control approach is developed. In order to overcome the problem of "explosion of complexity" inherent in the proposed control approach, the dynamic surface control (DSC) technique is introduced into the first adaptive NN decentralized control scheme, and a simplified adaptive NN decentralized output feedback DSC approach is developed. It is proved that the two proposed control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded, and the observer errors and the tracking errors converge to a small neighborhood of the origin. Simulation results are provided to show the effectiveness of the proposed approaches.

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

NASA Astrophysics Data System (ADS)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

Indication for Dialysis Initiation and Mortality in Patients With Chronic Kidney Failure: A Retrospective Cohort Study

PubMed Central

Rivara, Matthew B.; Chen, Chang Huei; Nair, Anupama; Cobb, Denise; Himmelfarb, Jonathan; Mehrotra, Rajnish

2016-01-01

Background Initiation of maintenance dialysis for patients with chronic kidney failure is a period of high risk for adverse patient outcomes. Whether indications for dialysis initiation are associated with mortality among this population is unknown. Study Design Retrospective cohort study. Setting & Participants 461 patients who initiated dialysis (hemodialysis, 437; peritoneal dialysis, 24) from January 1st, 2004 through December 31st, 2012 and were treated in facilities operated by a single dialysis organization. Follow-up for the primary outcome was through December 31st, 2013. Predictor Clinically documented primary indication for dialysis initiation, as categorized into four groups: laboratory evidence of kidney function decline (reference category), uremic symptoms, volume overload or hypertension, and other/unknown. Outcomes All-cause mortality Results Over a median follow-up of 2.4 years, 183 (40%) patients died. Crude mortality rates were 10.0 (95% CI, 6.8–14.7), 12.7 (95% CI, 10.2–15.7), 21.7 (95% CI, 16.4–28.6), and 12.2 (95% CI, 6.8–14.7) per 100 patient-years among patients initiating dialysis primarily for laboratory evidence of kidney function decline, uremic symptoms, volume overload or hypertension, and other/unknown reason, respectively. Following adjustment for demographic variables, coexisting illnesses, and estimated glomerular filtration rate, initiation of dialysis for uremic symptoms, volume overload or hypertension, or for other/unknown reasons were associated with 1.12 (95% CI, 0.72–1.77), 1.71 (95% CI, 1.03–2.84), and 1.28 (95% CI, 0.73–2.26) times higher risk, respectively, for subsequent mortality compared to initiation for laboratory evidence of kidney function decline. Limitations Possibility of residual confounding by unmeasured variables; reliance on clinical documentation to ascertain exposure Conclusions Patients initiating dialysis due to volume overload may have increased risk for mortality compared to patients initiating dialysis due to laboratory evidence of kidney function decline. Further studies are needed to identify and test interventions that might reduce this risk. PMID:27637132

Designing lymphocyte functional structure for optimal signal detection: voilà, T cells.

PubMed

Noest, A J

2000-11-21

One basic task of immune systems is to detect signals from unknown "intruders" amidst a noisy background of harmless signals. To clarify the functional importance of many observed lymphocyte properties, I ask: What properties would a cell have if one designed it according to the theory of optimal detection, with minimal regard for biological constraints? Sparse and reasonable assumptions about the statistics of available signals prove sufficient for deriving many features of the optimal functional structure, in an incremental and modular design. The use of one common formalism guarantees that all parts of the design collaborate to solve the detection task. Detection performance is computed at several stages of the design. Comparison between design variants reveals e.g. the importance of controlling the signal integration time. This predicts that an appropriate control mechanism should exist. Comparing the design to reality, I find a striking similarity with many features of T cells. For example, the formalism dictates clonal specificity, serial receptor triggering, (grades of) anergy, negative and positive selection, co-stimulation, high-zone tolerance, and clonal production of cytokines. Serious mismatches should be found if T cells were hindered by mechanistic constraints or vestiges of their (co-)evolutionary history, but I have not found clear examples. By contrast, fundamental mismatches abound when comparing the design to immune systems of e.g. invertebrates. The wide-ranging differences seem to hinge on the (in)ability to generate a large diversity of receptors. Copyright 2000 Academic Press.

Confronting the catalytic dark matter encoded by sequenced genomes

PubMed Central

Ellens, Kenneth W.; Christian, Nils; Singh, Charandeep; Satagopam, Venkata P.

2017-01-01

Abstract The post-genomic era has provided researchers with a deluge of protein sequences. However, a significant fraction of the proteins encoded by sequenced genomes remains without an identified function. Here, we aim at determining how many enzymes of uncertain or unknown function are still present in the Saccharomyces cerevisiae and human proteomes. Using information available in the Swiss-Prot, BRENDA and KEGG databases in combination with a Hidden Markov Model-based method, we estimate that >600 yeast and 2000 human proteins (>30% of their proteins of unknown function) are enzymes whose precise function(s) remain(s) to be determined. This illustrates the impressive scale of the ‘unknown enzyme problem’. We extensively review classical biochemical as well as more recent systematic experimental and computational approaches that can be used to support enzyme function discovery research. Finally, we discuss the possible roles of the elusive catalysts in light of recent developments in the fields of enzymology and metabolism as well as the significance of the unknown enzyme problem in the context of metabolic modeling, metabolic engineering and rare disease research. PMID:29059321

A spectral reflectance estimation technique using multispectral data from the Viking lander camera

NASA Technical Reports Server (NTRS)

Park, S. K.; Huck, F. O.

1976-01-01

A technique is formulated for constructing spectral reflectance curve estimates from multispectral data obtained with the Viking lander camera. The multispectral data are limited to six spectral channels in the wavelength range from 0.4 to 1.1 micrometers and most of these channels exhibit appreciable out-of-band response. The output of each channel is expressed as a linear (integral) function of the (known) solar irradiance, atmospheric transmittance, and camera spectral responsivity and the (unknown) spectral responsivity and the (unknown) spectral reflectance. This produces six equations which are used to determine the coefficients in a representation of the spectral reflectance as a linear combination of known basis functions. Natural cubic spline reflectance estimates are produced for a variety of materials that can be reasonably expected to occur on Mars. In each case the dominant reflectance features are accurately reproduced, but small period features are lost due to the limited number of channels. This technique may be a valuable aid in selecting the number of spectral channels and their responsivity shapes when designing a multispectral imaging system.

RNA Structures as Mediators of Neurological Diseases and as Drug Targets.

PubMed

Bernat, Viachaslau; Disney, Matthew D

2015-07-01

RNAs adopt diverse folded structures that are essential for function and thus play critical roles in cellular biology. A striking example of this is the ribosome, a complex, three-dimensionally folded macromolecular machine that orchestrates protein synthesis. Advances in RNA biochemistry, structural and molecular biology, and bioinformatics have revealed other non-coding RNAs whose functions are dictated by their structure. It is not surprising that aberrantly folded RNA structures contribute to disease. In this Review, we provide a brief introduction into RNA structural biology and then describe how RNA structures function in cells and cause or contribute to neurological disease. Finally, we highlight successful applications of rational design principles to provide chemical probes and lead compounds targeting structured RNAs. Based on several examples of well-characterized RNA-driven neurological disorders, we demonstrate how designed small molecules can facilitate the study of RNA dysfunction, elucidating previously unknown roles for RNA in disease, and provide lead therapeutics. Copyright © 2015 Elsevier Inc. All rights reserved.

Mutation of a Broadly Conserved Operon (RL3499-RL3502) from Rhizobium leguminosarum Biovar viciae Causes Defects in Cell Morphology and Envelope Integrity▿†

PubMed Central

Vanderlinde, Elizabeth M.; Magnus, Samantha A.; Tambalo, Dinah D.; Koval, Susan F.; Yost, Christopher K.

2011-01-01

The bacterial cell envelope is of critical importance to the function and survival of the cell; it acts as a barrier against harmful toxins while allowing the flow of nutrients into the cell. It also serves as a point of physical contact between a bacterial cell and its host. Hence, the cell envelope of Rhizobium leguminosarum is critical to cell survival under both free-living and symbiotic conditions. Transposon mutagenesis of R. leguminosarum strain 3841 followed by a screen to isolate mutants with defective cell envelopes led to the identification of a novel conserved operon (RL3499-RL3502) consisting of a putative moxR-like AAA+ ATPase, a hypothetical protein with a domain of unknown function (designated domain of unknown function 58), and two hypothetical transmembrane proteins. Mutation of genes within this operon resulted in increased sensitivity to membrane-disruptive agents such as detergents, hydrophobic antibiotics, and alkaline pH. On minimal media, the mutants retain their rod shape but are roughly 3 times larger than the wild type. On media containing glycine or peptides such as yeast extract, the mutants form large, distorted spheres and are incapable of sustained growth under these culture conditions. Expression of the operon is maximal during the stationary phase of growth and is reduced in a chvG mutant, indicating a role for this sensor kinase in regulation of the operon. Our findings provide the first functional insight into these genes of unknown function, suggesting a possible role in cell envelope development in Rhizobium leguminosarum. Given the broad conservation of these genes among the Alphaproteobacteria, the results of this study may also provide insight into the physiological role of these genes in other Alphaproteobacteria, including the animal pathogen Brucella. PMID:21357485

Active disturbance rejection controller of fine tracking system for free space optical communication

NASA Astrophysics Data System (ADS)

Cui, Ning; Liu, Yang; Chen, Xinglin; Wang, Yan

2013-08-01

Free space optical communication is one of the best approaches in future communications. Laser beam's acquisition, pointing and tracking are crucial technologies of free space optical communication. Fine tracking system is important component of APT (acquisition, pointing and tracking) system. It cooperates with the coarse pointing system in executing the APT mission. Satellite platform vibration and disturbance, which reduce received optical power, increase bit error rate and affect seriously the natural performance of laser communication. For the characteristic of satellite platform, an active disturbance rejection controller was designed to reduce the vibration and disturbance. There are three major contributions in the paper. Firstly, the effects of vibration on the inter satellite optical communications were analyzed, and the reasons and characters of vibration of the satellite platform were summarized. The amplitude-frequency response of a filter was designed according to the power spectral density of platform vibration of SILEX (Semiconductor Inter-satellite Laser Experiment), and then the signals of platform vibration were generated by filtering white Gaussian noise using the filter. Secondly, the fast steering mirror is a key component of the fine tracking system for optical communication. The mechanical design and model analysis was made to the tip/tilt mirror driven by the piezoelectric actuator and transmitted by the flexure hinge. The transfer function of the fast steering mirror, camera, D/A data acquisition card was established, and the theory model of transfer function of this system was further obtained. Finally, an active disturbance rejection control method is developed, multiple parallel extended state observers were designed for estimation of unknown dynamics and external disturbance, and the estimated states were used for nonlinear feedback control and compensation to improve system performance. The simulation results show that the designed controller not only accurately estimates and compensates the disturbances, but also realizes the robustness to estimation of unknown dynamics. The controller can satisfy the requirement of fine tracking accuracy for free space optical communication system.

Nonparametric Stochastic Model for Uncertainty Quantifi cation of Short-term Wind Speed Forecasts

NASA Astrophysics Data System (ADS)

AL-Shehhi, A. M.; Chaouch, M.; Ouarda, T.

2014-12-01

Wind energy is increasing in importance as a renewable energy source due to its potential role in reducing carbon emissions. It is a safe, clean, and inexhaustible source of energy. The amount of wind energy generated by wind turbines is closely related to the wind speed. Wind speed forecasting plays a vital role in the wind energy sector in terms of wind turbine optimal operation, wind energy dispatch and scheduling, efficient energy harvesting etc. It is also considered during planning, design, and assessment of any proposed wind project. Therefore, accurate prediction of wind speed carries a particular importance and plays significant roles in the wind industry. Many methods have been proposed in the literature for short-term wind speed forecasting. These methods are usually based on modeling historical fixed time intervals of the wind speed data and using it for future prediction. The methods mainly include statistical models such as ARMA, ARIMA model, physical models for instance numerical weather prediction and artificial Intelligence techniques for example support vector machine and neural networks. In this paper, we are interested in estimating hourly wind speed measures in United Arab Emirates (UAE). More precisely, we predict hourly wind speed using a nonparametric kernel estimation of the regression and volatility functions pertaining to nonlinear autoregressive model with ARCH model, which includes unknown nonlinear regression function and volatility function already discussed in the literature. The unknown nonlinear regression function describe the dependence between the value of the wind speed at time t and its historical data at time t -1, t - 2, … , t - d. This function plays a key role to predict hourly wind speed process. The volatility function, i.e., the conditional variance given the past, measures the risk associated to this prediction. Since the regression and the volatility functions are supposed to be unknown, they are estimated using nonparametric kernel methods. In addition, to the pointwise hourly wind speed forecasts, a confidence interval is also provided which allows to quantify the uncertainty around the forecasts.

SYNTHESIS OF NOVEL ALL-DIELECTRIC GRATING FILTERS USING GENETIC ALGORITHMS

NASA Technical Reports Server (NTRS)

Zuffada, Cinzia; Cwik, Tom; Ditchman, Christopher

1997-01-01

We are concerned with the design of inhomogeneous, all dielectric (lossless) periodic structures which act as filters. Dielectric filters made as stacks of inhomogeneous gratings and layers of materials are being used in optical technology, but are not common at microwave frequencies. The problem is then finding the periodic cell's geometric configuration and permittivity values which correspond to a specified reflectivity/transmittivity response as a function of frequency/illumination angle. This type of design can be thought of as an inverse-source problem, since it entails finding a distribution of sources which produce fields (or quantities derived from them) of given characteristics. Electromagnetic sources (electric and magnetic current densities) in a volume are related to the outside fields by a well known linear integral equation. Additionally, the sources are related to the fields inside the volume by a constitutive equation, involving the material properties. Then, the relationship linking the fields outside the source region to those inside is non-linear, in terms of material properties such as permittivity, permeability and conductivity. The solution of the non-linear inverse problem is cast here as a combination of two linear steps, by explicitly introducing the electromagnetic sources in the computational volume as a set of unknowns in addition to the material unknowns. This allows to solve for material parameters and related electric fields in the source volume which are consistent with Maxwell's equations. Solutions are obtained iteratively by decoupling the two steps. First, we invert for the permittivity only in the minimization of a cost function and second, given the materials, we find the corresponding electric fields through direct solution of the integral equation in the source volume. The sources thus computed are used to generate the far fields and the synthesized triter response. The cost function is obtained by calculating the deviation between the synthesized value of reflectivity/transmittivity and the desired one. Solution geometries for the periodic cell are sought as gratings (ensembles of columns of different heights and widths), or combinations of homogeneous layers of different dielectric materials and gratings. Hence the explicit unknowns of the inversion step are the material permittivities and the relative boundaries separating homogeneous parcels of the periodic cell.

Aerodynamic design and optimization in one shot

NASA Technical Reports Server (NTRS)

Ta'asan, Shlomo; Kuruvila, G.; Salas, M. D.

1992-01-01

This paper describes an efficient numerical approach for the design and optimization of aerodynamic bodies. As in classical optimal control methods, the present approach introduces a cost function and a costate variable (Lagrange multiplier) in order to achieve a minimum. High efficiency is achieved by using a multigrid technique to solve for all the unknowns simultaneously, but restricting work on a design variable only to grids on which their changes produce nonsmooth perturbations. Thus, the effort required to evaluate design variables that have nonlocal effects on the solution is confined to the coarse grids. However, if a variable has a nonsmooth local effect on the solution in some neighborhood, it is relaxed in that neighborhood on finer grids. The cost of solving the optimal control problem is shown to be approximately two to three times the cost of the equivalent analysis problem. Examples are presented to illustrate the application of the method to aerodynamic design and constraint optimization.

Disturbance observer-based adaptive sliding mode hybrid projective synchronisation of identical fractional-order financial systems

NASA Astrophysics Data System (ADS)

Khan, Ayub; Tyagi, Arti

2018-05-01

In this paper, we have studied the hybrid projective synchronisation for incommensurate, integer and commensurate fractional-order financial systems with unknown disturbance. To tackle the problem of unknown bounded disturbance, fractional-order disturbance observer is designed to approximate the unknown disturbance. Further, we have introduced simple sliding mode surface and designed adaptive sliding mode controllers incorporating with the designed fractional-order disturbance observer to achieve a bounded hybrid projective synchronisation between two identical fractional-order financial model with different initial conditions. It is shown that the slave system with disturbance can be synchronised with the projection of the master system generated through state transformation. Simulation results are presented to ensure the validity and effectiveness of the proposed sliding mode control scheme in the presence of external bounded unknown disturbance. Also, synchronisation error for commensurate, integer and incommensurate fractional-order financial systems is studied in numerical simulation.

Reinforcement learning controller design for affine nonlinear discrete-time systems using online approximators.

PubMed

Yang, Qinmin; Jagannathan, Sarangapani

2012-04-01

In this paper, reinforcement learning state- and output-feedback-based adaptive critic controller designs are proposed by using the online approximators (OLAs) for a general multi-input and multioutput affine unknown nonlinear discretetime systems in the presence of bounded disturbances. The proposed controller design has two entities, an action network that is designed to produce optimal signal and a critic network that evaluates the performance of the action network. The critic estimates the cost-to-go function which is tuned online using recursive equations derived from heuristic dynamic programming. Here, neural networks (NNs) are used both for the action and critic whereas any OLAs, such as radial basis functions, splines, fuzzy logic, etc., can be utilized. For the output-feedback counterpart, an additional NN is designated as the observer to estimate the unavailable system states, and thus, separation principle is not required. The NN weight tuning laws for the controller schemes are also derived while ensuring uniform ultimate boundedness of the closed-loop system using Lyapunov theory. Finally, the effectiveness of the two controllers is tested in simulation on a pendulum balancing system and a two-link robotic arm system.

A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein.

PubMed

Agrawal, Neeraj J; Helk, Bernhard; Trout, Bernhardt L

2014-01-21

Identifying hot-spot residues - residues that are critical to protein-protein binding - can help to elucidate a protein's function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein-protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36-57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein-protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Adaptive Fuzzy Output Feedback Control for Switched Nonlinear Systems With Unmodeled Dynamics.

PubMed

Tong, Shaocheng; Li, Yongming

2017-02-01

This paper investigates a robust adaptive fuzzy control stabilization problem for a class of uncertain nonlinear systems with arbitrary switching signals that use an observer-based output feedback scheme. The considered switched nonlinear systems possess the unstructured uncertainties, unmodeled dynamics, and without requiring the states being available for measurement. A state observer which is independent of switching signals is designed to solve the problem of unmeasured states. Fuzzy logic systems are used to identify unknown lumped nonlinear functions so that the problem of unstructured uncertainties can be solved. By combining adaptive backstepping design principle and small-gain approach, a novel robust adaptive fuzzy output feedback stabilization control approach is developed. The stability of the closed-loop system is proved via the common Lyapunov function theory and small-gain theorem. Finally, the simulation results are given to demonstrate the validity and performance of the proposed control strategy.

4. VIEW NORTHEAST, radar tower (unknown function), prime search radar ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

4. VIEW NORTHEAST, radar tower (unknown function), prime search radar tower, emergency power building, and height finder radar tower - Fort Custer Military Reservation, P-67 Radar Station, .25 mile north of Dickman Road, east of Clark Road, Battle Creek, Calhoun County, MI

Adaptive Sliding Mode Control of Dynamic Systems Using Double Loop Recurrent Neural Network Structure.

PubMed

Fei, Juntao; Lu, Cheng

2018-04-01

In this paper, an adaptive sliding mode control system using a double loop recurrent neural network (DLRNN) structure is proposed for a class of nonlinear dynamic systems. A new three-layer RNN is proposed to approximate unknown dynamics with two different kinds of feedback loops where the firing weights and output signal calculated in the last step are stored and used as the feedback signals in each feedback loop. Since the new structure has combined the advantages of internal feedback NN and external feedback NN, it can acquire the internal state information while the output signal is also captured, thus the new designed DLRNN can achieve better approximation performance compared with the regular NNs without feedback loops or the regular RNNs with a single feedback loop. The new proposed DLRNN structure is employed in an equivalent controller to approximate the unknown nonlinear system dynamics, and the parameters of the DLRNN are updated online by adaptive laws to get favorable approximation performance. To investigate the effectiveness of the proposed controller, the designed adaptive sliding mode controller with the DLRNN is applied to a -axis microelectromechanical system gyroscope to control the vibrating dynamics of the proof mass. Simulation results demonstrate that the proposed methodology can achieve good tracking property, and the comparisons of the approximation performance between radial basis function NN, RNN, and DLRNN show that the DLRNN can accurately estimate the unknown dynamics with a fast speed while the internal states of DLRNN are more stable.

Efficient Bayesian experimental design for contaminant source identification

NASA Astrophysics Data System (ADS)

Zhang, J.; Zeng, L.

2013-12-01

In this study, an efficient full Bayesian approach is developed for the optimal sampling well location design and source parameter identification of groundwater contaminants. An information measure, i.e., the relative entropy, is employed to quantify the information gain from indirect concentration measurements in identifying unknown source parameters such as the release time, strength and location. In this approach, the sampling location that gives the maximum relative entropy is selected as the optimal one. Once the sampling location is determined, a Bayesian approach based on Markov Chain Monte Carlo (MCMC) is used to estimate unknown source parameters. In both the design and estimation, the contaminant transport equation is required to be solved many times to evaluate the likelihood. To reduce the computational burden, an interpolation method based on the adaptive sparse grid is utilized to construct a surrogate for the contaminant transport. The approximated likelihood can be evaluated directly from the surrogate, which greatly accelerates the design and estimation process. The accuracy and efficiency of our approach are demonstrated through numerical case studies. Compared with the traditional optimal design, which is based on the Gaussian linear assumption, the method developed in this study can cope with arbitrary nonlinearity. It can be used to assist in groundwater monitor network design and identification of unknown contaminant sources. Contours of the expected information gain. The optimal observing location corresponds to the maximum value. Posterior marginal probability densities of unknown parameters, the thick solid black lines are for the designed location. For comparison, other 7 lines are for randomly chosen locations. The true values are denoted by vertical lines. It is obvious that the unknown parameters are estimated better with the desinged location.

Unknown Gases: Student-Designed Experiments in the Introductory Laboratory.

ERIC Educational Resources Information Center

Hanson, John; Hoyt, Tim

2002-01-01

Introductory students design and carry-out experimental procedures to determine the identity of three unknown gases from a list of eight possibilities: air, nitrogen, oxygen, argon, carbon dioxide, helium, methane, and hydrogen. Students are excited and motivated by the opportunity to come up with their own experimental approach to solving a…

Theoretical design and discovery of the most-promising, previously overlooked hybrid perovskite compounds

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

Zunger, Alex; Kazmerski, Lawrence L.; Dalpian, Gustavo M.

The material class of hybrid organic-inorganic perovskites (AMX3) has risen rapidly from a virtually unknown material in photovoltaic applications a short 8-years ago into 20-23% efficient thin-film solar cell devices. As promising as this class of materials is, however, there are limitations associated with its poor long-term stability, non-optimal band gap, and the presence of toxic Pb atom on the metalloid site. An Edisonian laboratory exploration (i.e., growth + characterization) via trial-and-error processes of all other candidate materials, is unpractical. Our approach uses high speed computational design and discovery to screen the ‘best of class” candidates based upon optimal functionalities.

A fast approach to designing airfoils from given pressure distribution in compressible flows

NASA Technical Reports Server (NTRS)

Daripa, Prabir

1987-01-01

A new inverse method for aerodynamic design of airfols is presented for subcritical flows. The pressure distribution in this method can be prescribed as a function of the arc length of the as-yet unknown body. This inverse problem is shown to be mathematically equivalent to solving only one nonlinear boundary value problem subject to known Dirichlet data on the boundary. The solution to this problem determines the airfoil, the freestream Mach number, and the upstream flow direction. The existence of a solution to a given pressure distribution is discussed. The method is easy to implement and extremely efficient. A series of results for which comparisons are made with the known airfoils is presented.

Disregarding population specificity: its influence on the sex assessment methods from the tibia.

PubMed

Kotěrová, Anežka; Velemínská, Jana; Dupej, Ján; Brzobohatá, Hana; Pilný, Aleš; Brůžek, Jaroslav

2017-01-01

Forensic anthropology has developed classification techniques for sex estimation of unknown skeletal remains, for example population-specific discriminant function analyses. These methods were designed for populations that lived mostly in the late nineteenth and twentieth centuries. Their level of reliability or misclassification is important for practical use in today's forensic practice; it is, however, unknown. We addressed the question of what the likelihood of errors would be if population specificity of discriminant functions of the tibia were disregarded. Moreover, five classification functions in a Czech sample were proposed (accuracies 82.1-87.5 %, sex bias ranged from -1.3 to -5.4 %). We measured ten variables traditionally used for sex assessment of the tibia on a sample of 30 male and 26 female models from recent Czech population. To estimate the classification accuracy and error (misclassification) rates ignoring population specificity, we selected published classification functions of tibia for the Portuguese, south European, and the North American populations. These functions were applied on the dimensions of the Czech population. Comparing the classification success of the reference and the tested Czech sample showed that females from Czech population were significantly overestimated and mostly misclassified as males. Overall accuracy of sex assessment significantly decreased (53.6-69.7 %), sex bias -29.4-100 %, which is most probably caused by secular trend and the generally high variability of body size. Results indicate that the discriminant functions, developed for skeletal series representing geographically and chronologically diverse populations, are not applicable in current forensic investigations. Finally, implications and recommendations for future research are discussed.

Extracting scene feature vectors through modeling, volume 3

NASA Technical Reports Server (NTRS)

Berry, J. K.; Smith, J. A.

1976-01-01

The remote estimation of the leaf area index of winter wheat at Finney County, Kansas was studied. The procedure developed consists of three activities: (1) field measurements; (2) model simulations; and (3) response classifications. The first activity is designed to identify model input parameters and develop a model evaluation data set. A stochastic plant canopy reflectance model is employed to simulate reflectance in the LANDSAT bands as a function of leaf area index for two phenological stages. An atmospheric model is used to translate these surface reflectances into simulated satellite radiance. A divergence classifier determines the relative similarity between model derived spectral responses and those of areas with unknown leaf area index. The unknown areas are assigned the index associated with the closest model response. This research demonstrated that the SRVC canopy reflectance model is appropriate for wheat scenes and that broad categories of leaf area index can be inferred from the procedure developed.

Three-dimensional printed upper-limb prostheses lack randomised controlled trials: A systematic review

PubMed Central

Diment, Laura E; Thompson, Mark S; Bergmann, Jeroen HM

2017-01-01

Background: Three-dimensional printing provides an exciting opportunity to customise upper-limb prostheses. Objective: This review summarises the research that assesses the efficacy and effectiveness of three-dimensional printed upper-limb prostheses. Study design: Systematic review. Methods: PubMed, Web of Science and OVID were systematically searched for studies that reported human trials of three-dimensional printed upper-limb prostheses. The studies matching the language, peer-review and relevance criteria were ranked by level of evidence and critically appraised using the Downs and Black Quality Index. Results: After removing duplicates, 321 records were identified. Eight papers met the inclusion criteria. No studies used controls; five were case studies and three were small case-series studies. All studies showed promising results, but none demonstrated external validity, avoidance of bias or statistically significant improvements over conventional prostheses. The studies demonstrated proof-of-concept rather than assessing efficacy, and the devices were designed to prioritise reduction of manufacturing costs, not customisability for comfort and function. Conclusion: The potential of three-dimensional printing for individual customisation has yet to be fully realised, and the efficacy and effectiveness to be rigorously assessed. Until randomised controlled trials with follow-up are performed, the comfort, functionality, durability and long-term effects on quality of life remain unknown. Clinical relevance Initial studies suggest that three-dimensional printing shows promise for customising low-cost upper-limb prosthetics. However, the efficacy and effectiveness of these devices have yet to be rigorously assessed. Until randomised controlled trials with follow-up are performed, the comfort, functionality, durability and long-term effects on patient quality of life remain unknown. PMID:28649911

Design of a DNA chip for detection of unknown genetically modified organisms (GMOs).

PubMed

Nesvold, Håvard; Kristoffersen, Anja Bråthen; Holst-Jensen, Arne; Berdal, Knut G

2005-05-01

Unknown genetically modified organisms (GMOs) have not undergone a risk evaluation, and hence might pose a danger to health and environment. There are, today, no methods for detecting unknown GMOs. In this paper we propose a novel method intended as a first step in an approach for detecting unknown genetically modified (GM) material in a single plant. A model is designed where biological and combinatorial reduction rules are applied to a set of DNA chip probes containing all possible sequences of uniform length n, creating probes capable of detecting unknown GMOs. The model is theoretically tested for Arabidopsis thaliana Columbia, and the probabilities for detecting inserts and receiving false positives are assessed for various parameters for this organism. From a theoretical standpoint, the model looks very promising but should be tested further in the laboratory. The model and algorithms will be available upon request to the corresponding author.

Theoretical stability in coefficient inverse problems for general hyperbolic equations with numerical reconstruction

NASA Astrophysics Data System (ADS)

Yu, Jie; Liu, Yikan; Yamamoto, Masahiro

2018-04-01

In this article, we investigate the determination of the spatial component in the time-dependent second order coefficient of a hyperbolic equation from both theoretical and numerical aspects. By the Carleman estimates for general hyperbolic operators and an auxiliary Carleman estimate, we establish local Hölder stability with either partial boundary or interior measurements under certain geometrical conditions. For numerical reconstruction, we minimize a Tikhonov functional which penalizes the gradient of the unknown function. Based on the resulting variational equation, we design an iteration method which is updated by solving a Poisson equation at each step. One-dimensional prototype examples illustrate the numerical performance of the proposed iteration.

Far transfer to language and math of a short software-based gaming intervention.

PubMed

Goldin, Andrea Paula; Hermida, María Julia; Shalom, Diego E; Elias Costa, Martín; Lopez-Rosenfeld, Matías; Segretin, María Soledad; Fernández-Slezak, Diego; Lipina, Sebastián J; Sigman, Mariano

2014-04-29

Executive functions (EF) in children can be trained, but it remains unknown whether training-related benefits elicit far transfer to real-life situations. Here, we investigate whether a set of computerized games might yield near and far transfer on an experimental and an active control group of low-SES otherwise typically developing 6-y-olds in a 3-mo pretest-training-posttest design that was ecologically deployed (at school). The intervention elicits transfer to some (but not all) facets of executive function. These changes cascade to real-world measures of school performance. The intervention equalizes academic outcomes across children who regularly attend school and those who do not because of social and familiar circumstances.

Mobile robot dynamic path planning based on improved genetic algorithm

NASA Astrophysics Data System (ADS)

Wang, Yong; Zhou, Heng; Wang, Ying

2017-08-01

In dynamic unknown environment, the dynamic path planning of mobile robots is a difficult problem. In this paper, a dynamic path planning method based on genetic algorithm is proposed, and a reward value model is designed to estimate the probability of dynamic obstacles on the path, and the reward value function is applied to the genetic algorithm. Unique coding techniques reduce the computational complexity of the algorithm. The fitness function of the genetic algorithm fully considers three factors: the security of the path, the shortest distance of the path and the reward value of the path. The simulation results show that the proposed genetic algorithm is efficient in all kinds of complex dynamic environments.

Developing safety performance functions incorporating reliability-based risk measures.

PubMed

Ibrahim, Shewkar El-Bassiouni; Sayed, Tarek

2011-11-01

Current geometric design guides provide deterministic standards where the safety margin of the design output is generally unknown and there is little knowledge of the safety implications of deviating from these standards. Several studies have advocated probabilistic geometric design where reliability analysis can be used to account for the uncertainty in the design parameters and to provide a risk measure of the implication of deviation from design standards. However, there is currently no link between measures of design reliability and the quantification of safety using collision frequency. The analysis presented in this paper attempts to bridge this gap by incorporating a reliability-based quantitative risk measure such as the probability of non-compliance (P(nc)) in safety performance functions (SPFs). Establishing this link will allow admitting reliability-based design into traditional benefit-cost analysis and should lead to a wider application of the reliability technique in road design. The present application is concerned with the design of horizontal curves, where the limit state function is defined in terms of the available (supply) and stopping (demand) sight distances. A comprehensive collision and geometric design database of two-lane rural highways is used to investigate the effect of the probability of non-compliance on safety. The reliability analysis was carried out using the First Order Reliability Method (FORM). Two Negative Binomial (NB) SPFs were developed to compare models with and without the reliability-based risk measures. It was found that models incorporating the P(nc) provided a better fit to the data set than the traditional (without risk) NB SPFs for total, injury and fatality (I+F) and property damage only (PDO) collisions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Learning-based adaptive prescribed performance control of postcapture space robot-target combination without inertia identifications

NASA Astrophysics Data System (ADS)

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

2018-05-01

In this paper, a novel learning-based adaptive attitude takeover control method is investigated for the postcapture space robot-target combination with guaranteed prescribed performance in the presence of unknown inertial properties and external disturbance. First, a new static prescribed performance controller is developed to guarantee that all the involved attitude tracking errors are uniformly ultimately bounded by quantitatively characterizing the transient and steady-state performance of the combination. Then, a learning-based supplementary adaptive strategy based on adaptive dynamic programming is introduced to improve the tracking performance of static controller in terms of robustness and adaptiveness only utilizing the input/output data of the combination. Compared with the existing works, the prominent advantage is that the unknown inertial properties are not required to identify in the development of learning-based adaptive control law, which dramatically decreases the complexity and difficulty of the relevant controller design. Moreover, the transient and steady-state performance is guaranteed a priori by designer-specialized performance functions without resorting to repeated regulations of the controller parameters. Finally, the three groups of illustrative examples are employed to verify the effectiveness of the proposed control method.

Disturbance rejection control for vibration suppression of piezoelectric laminated thin-walled structures

NASA Astrophysics Data System (ADS)

Zhang, S. Q.; Li, H. N.; Schmidt, R.; Müller, P. C.

2014-02-01

Thin-walled piezoelectric integrated smart structures are easily excited to vibrate by unknown disturbances. In order to design and simulate a control strategy, firstly, an electro-mechanically coupled dynamic finite element (FE) model of smart structures is developed based on first-order shear deformation (FOSD) hypothesis. Linear piezoelectric constitutive equations and the assumption of constant electric field through the thickness are considered. Based on the dynamic FE model, a disturbance rejection (DR) control with proportional-integral (PI) observer using step functions as the fictitious model of disturbances is developed for vibration suppression of smart structures. In order to achieve a better dynamic behavior of the fictitious model of disturbances, the PI observer is extended to generalized proportional-integral (GPI) observer, in which sine or polynomial functions can be used to represent disturbances resulting in better dynamics. Therefore the disturbances can be estimated either by PI or GPI observer, and then the estimated signals are fed back to the controller. The DR control is validated by various kinds of unknown disturbances, and compared with linear-quadratic regulator (LQR) control. The results illustrate that the vibrations are better suppressed by the proposed DR control.

MUSIC-type imaging of small perfectly conducting cracks with an unknown frequency

NASA Astrophysics Data System (ADS)

Park, Won-Kwang

2015-09-01

MUltiple SIgnal Classification (MUSIC) is a famous non-iterative detection algorithm in inverse scattering problems. However, when the applied frequency is unknown, inaccurate locations are identified via MUSIC. This fact has been confirmed through numerical simulations. However, the reason behind this phenomenon has not been investigated theoretically. Motivated by this fact, we identify the structure of MUSIC-type imaging functionals with unknown frequency, by establishing a relationship with Bessel functions of order zero of the first kind. Through this, we can explain why inaccurate results appear.

Leader-follower formation control of underactuated surface vehicles based on sliding mode control and parameter estimation.

PubMed

Sun, Zhijian; Zhang, Guoqing; Lu, Yu; Zhang, Weidong

2018-01-01

This paper studies the leader-follower formation control of underactuated surface vehicles with model uncertainties and environmental disturbances. A parameter estimation and upper bound estimation based sliding mode control scheme is proposed to solve the problem of the unknown plant parameters and environmental disturbances. For each of these leader-follower formation systems, the dynamic equations of position and attitude are analyzed using coordinate transformation with the aid of the backstepping technique. All the variables are guaranteed to be uniformly ultimately bounded stable in the closed-loop system, which is proven by the distribution design Lyapunov function synthesis. The main advantages of this approach are that: first, parameter estimation based sliding mode control can enhance the robustness of the closed-loop system in presence of model uncertainties and environmental disturbances; second, a continuous function is developed to replace the signum function in the design of sliding mode scheme, which devotes to reduce the chattering of the control system. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Market-Based Coordination of Thermostatically Controlled Loads—Part I: A Mechanism Design Formulation

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

Li, Sen; Zhang, Wei; Lian, Jianming

This paper focuses on the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. Using the mechanism design approach, we propose a market-based coordination framework, which can effectively incorporate heterogeneous load dynamics, systematically deal with user preferences, account for the unknown load model parameters, and enable the real-world implementation with limited communication resources. This paper is divided into two parts. Part I presents a mathematical formulation of themore » problem and develops a coordination framework using the mechanism design approach. Part II presents a learning scheme to account for the unknown load model parameters, and evaluates the proposed framework through realistic simulations.« less

Structure-based functional annotation of putative conserved proteins having lyase activity from Haemophilus influenzae.

PubMed

Shahbaaz, Mohd; Ahmad, Faizan; Imtaiyaz Hassan, Md

2015-06-01

Haemophilus influenzae is a small pleomorphic Gram-negative bacteria which causes several chronic diseases, including bacteremia, meningitis, cellulitis, epiglottitis, septic arthritis, pneumonia, and empyema. Here we extensively analyzed the sequenced genome of H. influenzae strain Rd KW20 using protein family databases, protein structure prediction, pathways and genome context methods to assign a precise function to proteins whose functions are unknown. These proteins are termed as hypothetical proteins (HPs), for which no experimental information is available. Function prediction of these proteins would surely be supportive to precisely understand the biochemical pathways and mechanism of pathogenesis of Haemophilus influenzae. During the extensive analysis of H. influenzae genome, we found the presence of eight HPs showing lyase activity. Subsequently, we modeled and analyzed three-dimensional structure of all these HPs to determine their functions more precisely. We found these HPs possess cystathionine-β-synthase, cyclase, carboxymuconolactone decarboxylase, pseudouridine synthase A and C, D-tagatose-1,6-bisphosphate aldolase and aminodeoxychorismate lyase-like features, indicating their corresponding functions in the H. influenzae. Lyases are actively involved in the regulation of biosynthesis of various hormones, metabolic pathways, signal transduction, and DNA repair. Lyases are also considered as a key player for various biological processes. These enzymes are critically essential for the survival and pathogenesis of H. influenzae and, therefore, these enzymes may be considered as a potential target for structure-based rational drug design. Our structure-function relationship analysis will be useful to search and design potential lead molecules based on the structure of these lyases, for drug design and discovery.

GNE-886: A Potent and Selective Inhibitor of the Cat Eye Syndrome Chromosome Region Candidate 2 Bromodomain (CECR2).

PubMed

Crawford, Terry D; Audia, James E; Bellon, Steve; Burdick, Daniel J; Bommi-Reddy, Archana; Côté, Alexandre; Cummings, Richard T; Duplessis, Martin; Flynn, E Megan; Hewitt, Michael; Huang, Hon-Ren; Jayaram, Hariharan; Jiang, Ying; Joshi, Shivangi; Kiefer, James R; Murray, Jeremy; Nasveschuk, Christopher G; Neiss, Arianne; Pardo, Eneida; Romero, F Anthony; Sandy, Peter; Sims, Robert J; Tang, Yong; Taylor, Alexander M; Tsui, Vickie; Wang, Jian; Wang, Shumei; Wang, Yongyun; Xu, Zhaowu; Zawadzke, Laura; Zhu, Xiaoqin; Albrecht, Brian K; Magnuson, Steven R; Cochran, Andrea G

2017-07-13

The biological function of bromodomains, epigenetic readers of acetylated lysine residues, remains largely unknown. Herein we report our efforts to discover a potent and selective inhibitor of the bromodomain of cat eye syndrome chromosome region candidate 2 (CECR2). Screening of our internal medicinal chemistry collection led to the identification of a pyrrolopyridone chemical lead, and subsequent structure-based drug design led to a potent and selective CECR2 bromodomain inhibitor (GNE-886) suitable for use as an in vitro tool compound.

Optimal Control-Based Adaptive NN Design for a Class of Nonlinear Discrete-Time Block-Triangular Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2016-11-01

In this paper, we propose an optimal control scheme-based adaptive neural network design for a class of unknown nonlinear discrete-time systems. The controlled systems are in a block-triangular multi-input-multi-output pure-feedback structure, i.e., there are both state and input couplings and nonaffine functions to be included in every equation of each subsystem. The design objective is to provide a control scheme, which not only guarantees the stability of the systems, but also achieves optimal control performance. The main contribution of this paper is that it is for the first time to achieve the optimal performance for such a class of systems. Owing to the interactions among subsystems, making an optimal control signal is a difficult task. The design ideas are that: 1) the systems are transformed into an output predictor form; 2) for the output predictor, the ideal control signal and the strategic utility function can be approximated by using an action network and a critic network, respectively; and 3) an optimal control signal is constructed with the weight update rules to be designed based on a gradient descent method. The stability of the systems can be proved based on the difference Lyapunov method. Finally, a numerical simulation is given to illustrate the performance of the proposed scheme.

Evolutionary and molecular foundations of multiple contemporary functions of the nitroreductase superfamily

PubMed Central

Akiva, Eyal; Copp, Janine N.; Tokuriki, Nobuhiko; Babbitt, Patricia C.

2017-01-01

Insight regarding how diverse enzymatic functions and reactions have evolved from ancestral scaffolds is fundamental to understanding chemical and evolutionary biology, and for the exploitation of enzymes for biotechnology. We undertook an extensive computational analysis using a unique and comprehensive combination of tools that include large-scale phylogenetic reconstruction to determine the sequence, structural, and functional relationships of the functionally diverse flavin mononucleotide-dependent nitroreductase (NTR) superfamily (>24,000 sequences from all domains of life, 54 structures, and >10 enzymatic functions). Our results suggest an evolutionary model in which contemporary subgroups of the superfamily have diverged in a radial manner from a minimal flavin-binding scaffold. We identified the structural design principle for this divergence: Insertions at key positions in the minimal scaffold that, combined with the fixation of key residues, have led to functional specialization. These results will aid future efforts to delineate the emergence of functional diversity in enzyme superfamilies, provide clues for functional inference for superfamily members of unknown function, and facilitate rational redesign of the NTR scaffold. PMID:29078300

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

NASA Astrophysics Data System (ADS)

Ji, Xuewu; He, Xiangkun; Lv, Chen; Liu, Yahui; Wu, Jian

2018-06-01

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.

Adaptive control of an exoskeleton robot with uncertainties on kinematics and dynamics.

PubMed

Brahmi, Brahim; Saad, Maarouf; Ochoa-Luna, Cristobal; Rahman, Mohammad H

2017-07-01

In this paper, we propose a new adaptive control technique based on nonlinear sliding mode control (JSTDE) taking into account kinematics and dynamics uncertainties. This approach is applied to an exoskeleton robot with uncertain kinematics and dynamics. The adaptation design is based on Time Delay Estimation (TDE). The proposed strategy does not necessitate the well-defined dynamic and kinematic models of the system robot. The updated laws are designed using Lyapunov-function to solve the adaptation problem systematically, proving the close loop stability and ensuring the convergence asymptotically of the outputs tracking errors. Experiments results show the effectiveness and feasibility of JSTDE technique to deal with the variation of the unknown nonlinear dynamics and kinematics of the exoskeleton model.

Determining the size of a complete disturbance landscape: multi-scale, continental analysis of forest change.

PubMed

Buma, Brian; Costanza, Jennifer K; Riitters, Kurt

2017-11-21

The scale of investigation for disturbance-influenced processes plays a critical role in theoretical assumptions about stability, variance, and equilibrium, as well as conservation reserve and long-term monitoring program design. Critical consideration of scale is required for robust planning designs, especially when anticipating future disturbances whose exact locations are unknown. This research quantified disturbance proportion and pattern (as contagion) at multiple scales across North America. This pattern of scale-associated variability can guide selection of study and management extents, for example, to minimize variance (measured as standard deviation) between any landscapes within an ecoregion. We identified the proportion and pattern of forest disturbance (30 m grain size) across multiple landscape extents up to 180 km 2 . We explored the variance in proportion of disturbed area and the pattern of that disturbance between landscapes (within an ecoregion) as a function of the landscape extent. In many ecoregions, variance between landscapes within an ecoregion was minimal at broad landscape extents (low standard deviation). Gap-dominated regions showed the least variance, while fire-dominated showed the largest. Intensively managed ecoregions displayed unique patterns. A majority of the ecoregions showed low variance between landscapes at some scale, indicating an appropriate extent for incorporating natural regimes and unknown future disturbances was identified. The quantification of the scales of disturbance at the ecoregion level provides guidance for individuals interested in anticipating future disturbances which will occur in unknown spatial locations. Information on the extents required to incorporate disturbance patterns into planning is crucial for that process.

Learning Rates and Known-to-Unknown Flash-Card Ratios: Comparing Effectiveness While Holding Instructional Time Constant

ERIC Educational Resources Information Center

Forbes, Bethany E.; Skinner, Christopher H.; Black, Michelle P.; Yaw, Jared; Booher, Joshua; Delisle, Jean

2013-01-01

Using alternating treatments designs, we compared learning rates across 2 computer-based flash-card interventions (3?min each): a traditional drill intervention with 15 unknown words and an interspersal intervention with 12 known words and 3 unknown words. Each student acquired more words under the traditional drill intervention. Discussion…

Solving the Unknown with Algebra: Poster/Teaching Guide for Pre-Algebra Students. Expect the Unexpected with Math[R

ERIC Educational Resources Information Center

Actuarial Foundation, 2013

2013-01-01

"Solving the Unknown with Algebra" is a new math program aligned with the National Council of Teachers of Mathematics (NCTM) standards and designed to help students practice pre-algebra skills including using formulas, solving for unknowns, and manipulating equations. Developed by The Actuarial Foundation with Scholastic, this program provides…

Testing the Hypothesis of a Homoscedastic Error Term in Simple, Nonparametric Regression

ERIC Educational Resources Information Center

Wilcox, Rand R.

2006-01-01

Consider the nonparametric regression model Y = m(X)+ [tau](X)[epsilon], where X and [epsilon] are independent random variables, [epsilon] has a median of zero and variance [sigma][squared], [tau] is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated…

Efficient Learning Algorithms with Limited Information

ERIC Educational Resources Information Center

De, Anindya

2013-01-01

The thesis explores efficient learning algorithms in settings which are more restrictive than the PAC model of learning (Valiant) in one of the following two senses: (i) The learning algorithm has a very weak access to the unknown function, as in, it does not get labeled samples for the unknown function (ii) The error guarantee required from the…

Far transfer to language and math of a short software-based gaming intervention

PubMed Central

Goldin, Andrea Paula; Hermida, María Julia; Shalom, Diego E.; Elias Costa, Martín; Lopez-Rosenfeld, Matías; Segretin, María Soledad; Fernández-Slezak, Diego; Lipina, Sebastián J.; Sigman, Mariano

2014-01-01

Executive functions (EF) in children can be trained, but it remains unknown whether training-related benefits elicit far transfer to real-life situations. Here, we investigate whether a set of computerized games might yield near and far transfer on an experimental and an active control group of low-SES otherwise typically developing 6-y-olds in a 3-mo pretest–training–posttest design that was ecologically deployed (at school). The intervention elicits transfer to some (but not all) facets of executive function. These changes cascade to real-world measures of school performance. The intervention equalizes academic outcomes across children who regularly attend school and those who do not because of social and familiar circumstances. PMID:24711403

Probabilistic Modeling of Aircraft Trajectories for Dynamic Separation Volumes

NASA Technical Reports Server (NTRS)

Lewis, Timothy A.

2016-01-01

With a proliferation of new and unconventional vehicles and operations expected in the future, the ab initio airspace design will require new approaches to trajectory prediction for separation assurance and other air traffic management functions. This paper presents an approach to probabilistic modeling of the trajectory of an aircraft when its intent is unknown. The approach uses a set of feature functions to constrain a maximum entropy probability distribution based on a set of observed aircraft trajectories. This model can be used to sample new aircraft trajectories to form an ensemble reflecting the variability in an aircraft's intent. The model learning process ensures that the variability in this ensemble reflects the behavior observed in the original data set. Computational examples are presented.

Improved mapping of radio sources from VLBI data by least-square fit

NASA Technical Reports Server (NTRS)

Rodemich, E. R.

1985-01-01

A method is described for producing improved mapping of radio sources from Very Long Base Interferometry (VLBI) data. The method described is more direct than existing Fourier methods, is often more accurate, and runs at least as fast. The visibility data is modeled here, as in existing methods, as a function of the unknown brightness distribution and the unknown antenna gains and phases. These unknowns are chosen so that the resulting function values are as near as possible to the observed values. If researchers use the radio mapping source deviation to measure the closeness of this fit to the observed values, they are led to the problem of minimizing a certain function of all the unknown parameters. This minimization problem cannot be solved directly, but it can be attacked by iterative methods which we show converge automatically to the minimum with no user intervention. The resulting brightness distribution will furnish the best fit to the data among all brightness distributions of given resolution.

Strategies for Editing Virulent Staphylococcal Phages Using CRISPR-Cas10.

PubMed

Bari, S M Nayeemul; Walker, Forrest C; Cater, Katie; Aslan, Barbaros; Hatoum-Aslan, Asma

2017-12-15

Staphylococci are prevalent skin-dwelling bacteria that are also leading causes of antibiotic-resistant infections. Viruses that infect and lyse these organisms (virulent staphylococcal phages) can be used as alternatives to conventional antibiotics and represent promising tools to eliminate or manipulate specific species in the microbiome. However, since over half their genes have unknown functions, virulent staphylococcal phages carry inherent risk to cause unknown downstream side effects. Further, their swift and destructive reproductive cycle make them intractable by current genetic engineering techniques. CRISPR-Cas10 is an elaborate prokaryotic immune system that employs small RNAs and a multisubunit protein complex to detect and destroy phages and other foreign nucleic acids. Some staphylococci naturally possess CRISPR-Cas10 systems, thus providing an attractive tool already installed in the host chromosome to harness for phage genome engineering. However, the efficiency of CRISPR-Cas10 immunity against virulent staphylococcal phages and corresponding utility as a tool to facilitate their genome editing has not been explored. Here, we show that the CRISPR-Cas10 system native to Staphylococcus epidermidis exhibits robust immunity against diverse virulent staphylococcal phages. On the basis of this activity, a general two-step approach was developed to edit these phages that relies upon homologous recombination machinery encoded in the host. Variations of this approach to edit toxic phage genes and access phages that infect CRISPR-less staphylococci are also presented. This versatile set of genetic tools enables the systematic study of phage genes of unknown functions and the design of genetically defined phage-based antimicrobials that can eliminate or manipulate specific Staphylococcus species.

An Exploratory Analysis of Economic Factors in the Navy Total Force Strength Model (NTFSM)

DTIC Science & Technology

2015-12-01

NTFSM is still in the testing phase and its overall behavior is largely unknown. In particular, the analysts that NTFSM was designed to help are...NTFSM is still in the testing phase and its overall behavior is largely unknown. In particular, the analysts that NTFSM was designed to help are...7 B. NTFSM VERIFICATION AND TESTING ......................................... 8 C

Using Project-Based Learning to Design, Build, and Test Student-Made Photometer by Measuring the Unknown Concentration of Colored Substances

ERIC Educational Resources Information Center

Diawati, Chansyanah; Liliasari; Setiabudi, Agus; Buchari

2018-01-01

Students learned the principles and practice of photometry through project-based learning. They addressed the challenge of measuring the unknown concentration of a colored substance using a photometer they were required to design, build, and test. Then, they used that instrument to carry out the experiment and fulfill the challenge. A photometer…

Allocating monitoring effort in the face of unknown unknowns

USGS Publications Warehouse

Wintle, B.A.; Runge, M.C.; Bekessy, S.A.

2010-01-01

There is a growing view that to make efficient use of resources, ecological monitoring should be hypothesis-driven and targeted to address specific management questions. 'Targeted' monitoring has been contrasted with other approaches in which a range of quantities are monitored in case they exhibit an alarming trend or provide ad hoc ecological insights. The second form of monitoring, described as surveillance, has been criticized because it does not usually aim to discern between competing hypotheses, and its benefits are harder to identify a priori. The alternative view is that the existence of surveillance data may enable rapid corroboration of emerging hypotheses or help to detect important 'unknown unknowns' that, if undetected, could lead to catastrophic outcomes or missed opportunities. We derive a model to evaluate and compare the efficiency of investments in surveillance and targeted monitoring. We find that a decision to invest in surveillance monitoring may be defensible if: (1) the surveillance design is more likely to discover or corroborate previously unknown phenomena than a targeted design and (2) the expected benefits (or avoided costs) arising from discovery are substantially higher than those arising from a well-planned targeted design. Our examination highlights the importance of being explicit about the objectives, costs and expected benefits of monitoring in a decision analytic framework. ?? 2010 Blackwell Publishing Ltd/CNRS.

Complete synchronization of uncertain chaotic systems via a single proportional adaptive controller: A comparative study

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

Ahmad, Israr, E-mail: iak-2000plus@yahoo.com; Saaban, Azizan Bin, E-mail: azizan.s@uum.edu.my; Ibrahim, Adyda Binti, E-mail: adyda@uum.edu.my

This paper addresses a comparative computational study on the synchronization quality, cost and converging speed for two pairs of identical chaotic and hyperchaotic systems with unknown time-varying parameters. It is assumed that the unknown time-varying parameters are bounded. Based on the Lyapunov stability theory and using the adaptive control method, a single proportional controller is proposed to achieve the goal of complete synchronizations. Accordingly, appropriate adaptive laws are designed to identify the unknown time-varying parameters. The designed control strategy is easy to implement in practice. Numerical simulations results are provided to verify the effectiveness of the proposed synchronization scheme.

A deterministic global optimization using smooth diagonal auxiliary functions

NASA Astrophysics Data System (ADS)

Sergeyev, Yaroslav D.; Kvasov, Dmitri E.

2015-04-01

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

Molecular Level Design Principle behind Optimal Sizes of Photosynthetic LH2 Complex: Taming Disorder through Cooperation of Hydrogen Bonding and Quantum Delocalization.

PubMed

Jang, Seogjoo; Rivera, Eva; Montemayor, Daniel

2015-03-19

The light harvesting 2 (LH2) antenna complex from purple photosynthetic bacteria is an efficient natural excitation energy carrier with well-known symmetric structure, but the molecular level design principle governing its structure-function relationship is unknown. Our all-atomistic simulations of nonnatural analogues of LH2 as well as those of a natural LH2 suggest that nonnatural sizes of LH2-like complexes could be built. However, stable and consistent hydrogen bonding (HB) between bacteriochlorophyll and the protein is shown to be possible only near naturally occurring sizes, leading to significantly smaller disorder than for nonnatural ones. Extensive quantum calculations of intercomplex exciton transfer dynamics, sampled for a large set of disorder, reveal that taming the negative effect of disorder through a reliable HB as well as quantum delocalization of the exciton is a critical mechanism that makes LH2 highly functional, which also explains why the natural sizes of LH2 are indeed optimal.

Drug-Eluting Fibers for HIV-1 Inhibition and Contraception

PubMed Central

Ball, Cameron; Krogstad, Emily; Chaowanachan, Thanyanan; Woodrow, Kim A.

2012-01-01

Multipurpose prevention technologies (MPTs) that simultaneously prevent sexually transmitted infections (STIs) and unintended pregnancy are a global health priority. Combining chemical and physical barriers offers the greatest potential to design effective MPTs, but integrating both functional modalities into a single device has been challenging. Here we show that drug-eluting fiber meshes designed for topical drug delivery can function as a combination chemical and physical barrier MPT. Using FDA-approved polymers, we fabricated nanofiber meshes with tunable fiber size and controlled degradation kinetics that facilitate simultaneous release of multiple agents against HIV-1, HSV-2, and sperm. We observed that drug-loaded meshes inhibited HIV-1 infection in vitro and physically obstructed sperm penetration. Furthermore, we report on a previously unknown activity of glycerol monolaurate (GML) to potently inhibit sperm motility and viability. The application of drug-eluting nanofibers for HIV-1 prevention and sperm inhibition may serve as an innovative platform technology for drug delivery to the lower female reproductive tract. PMID:23209601

Adaptive neural network output feedback control for stochastic nonlinear systems with unknown dead-zone and unmodeled dynamics.

PubMed

Tong, Shaocheng; Wang, Tong; Li, Yongming; Zhang, Huaguang

2014-06-01

This paper discusses the problem of adaptive neural network output feedback control for a class of stochastic nonlinear strict-feedback systems. The concerned systems have certain characteristics, such as unknown nonlinear uncertainties, unknown dead-zones, unmodeled dynamics and without the direct measurements of state variables. In this paper, the neural networks (NNs) are employed to approximate the unknown nonlinear uncertainties, and then by representing the dead-zone as a time-varying system with a bounded disturbance. An NN state observer is designed to estimate the unmeasured states. Based on both backstepping design technique and a stochastic small-gain theorem, a robust adaptive NN output feedback control scheme is developed. It is proved that all the variables involved in the closed-loop system are input-state-practically stable in probability, and also have robustness to the unmodeled dynamics. Meanwhile, the observer errors and the output of the system can be regulated to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach.

Proteins of Unknown Biochemical Function: A Persistent Problem and a Roadmap to Help Overcome It.

PubMed

Niehaus, Thomas D; Thamm, Antje M K; de Crécy-Lagard, Valérie; Hanson, Andrew D

2015-11-01

The number of sequenced genomes is rapidly increasing, but functional annotation of the genes in these genomes lags far behind. Even in Arabidopsis (Arabidopsis thaliana), only approximately 40% of enzyme- and transporter-encoding genes have credible functional annotations, and this number is even lower in nonmodel plants. Functional characterization of unknown genes is a challenge, but various databases (e.g. for protein localization and coexpression) can be mined to provide clues. If homologous microbial genes exist-and about one-half the genes encoding unknown enzymes and transporters in Arabidopsis have microbial homologs-cross-kingdom comparative genomics can powerfully complement plant-based data. Multiple lines of evidence can strengthen predictions and warrant experimental characterization. In some cases, relatively quick tests in genetically tractable microbes can determine whether a prediction merits biochemical validation, which is costly and demands specialized skills. © 2015 American Society of Plant Biologists. All Rights Reserved.

Adaptive NN control for discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints.

PubMed

Chen, Weisheng

2009-07-01

This paper focuses on the problem of adaptive neural network tracking control for a class of discrete-time pure-feedback systems with unknown control direction under amplitude and rate actuator constraints. Two novel state-feedback and output-feedback dynamic control laws are established where the function tanh(.) is employed to solve the saturation constraint problem. Implicit function theorem and mean value theorem are exploited to deal with non-affine variables that are used as actual control. Radial basis function neural networks are used to approximate the desired input function. Discrete Nussbaum gain is used to estimate the unknown sign of control gain. The uniform boundedness of all closed-loop signals is guaranteed. The tracking error is proved to converge to a small residual set around the origin. A simulation example is provided to illustrate the effectiveness of control schemes proposed in this paper.

Probabilistic and deterministic aspects of linear estimation in geodesy. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Dermanis, A.

1976-01-01

Recent advances in observational techniques related to geodetic work (VLBI, laser ranging) make it imperative that more consideration should be given to modeling problems. Uncertainties in the effect of atmospheric refraction, polar motion and precession-nutation parameters, cannot be dispensed with in the context of centimeter level geodesy. Even physical processes that have generally been previously altogether neglected (station motions) must now be taken into consideration. The problem of modeling functions of time or space, or at least their values at observation points (epochs) is explored. When the nature of the function to be modeled is unknown. The need to include a limited number of terms and to a priori decide upon a specific form may result in a representation which fails to sufficiently approximate the unknown function. An alternative approach of increasing application is the modeling of unknown functions as stochastic processes.

Concurrent hyperthermia estimation schemes based on extended Kalman filtering and reduced-order modelling.

PubMed

Potocki, J K; Tharp, H S

1993-01-01

The success of treating cancerous tissue with heat depends on the temperature elevation, the amount of tissue elevated to that temperature, and the length of time that the tissue temperature is elevated. In clinical situations the temperature of most of the treated tissue volume is unknown, because only a small number of temperature sensors can be inserted into the tissue. A state space model based on a finite difference approximation of the bioheat transfer equation (BHTE) is developed for identification purposes. A full-order extended Kalman filter (EKF) is designed to estimate both the unknown blood perfusion parameters and the temperature at unmeasured locations. Two reduced-order estimators are designed as computationally less intensive alternatives to the full-order EKF. Simulation results show that the success of the estimation scheme depends strongly on the number and location of the temperature sensors. Superior results occur when a temperature sensor exists in each unknown blood perfusion zone, and the number of sensors is at least as large as the number of unknown perfusion zones. Unacceptable results occur when there are more unknown perfusion parameters than temperature sensors, or when the sensors are placed in locations that do not sample the unknown perfusion information.

Adaptive Event-Triggered Control Based on Heuristic Dynamic Programming for Nonlinear Discrete-Time Systems.

PubMed

Dong, Lu; Zhong, Xiangnan; Sun, Changyin; He, Haibo

2017-07-01

This paper presents the design of a novel adaptive event-triggered control method based on the heuristic dynamic programming (HDP) technique for nonlinear discrete-time systems with unknown system dynamics. In the proposed method, the control law is only updated when the event-triggered condition is violated. Compared with the periodic updates in the traditional adaptive dynamic programming (ADP) control, the proposed method can reduce the computation and transmission cost. An actor-critic framework is used to learn the optimal event-triggered control law and the value function. Furthermore, a model network is designed to estimate the system state vector. The main contribution of this paper is to design a new trigger threshold for discrete-time systems. A detailed Lyapunov stability analysis shows that our proposed event-triggered controller can asymptotically stabilize the discrete-time systems. Finally, we test our method on two different discrete-time systems, and the simulation results are included.

Observer-based state tracking control of uncertain stochastic systems via repetitive controller

NASA Astrophysics Data System (ADS)

Sakthivel, R.; Susana Ramya, L.; Selvaraj, P.

2017-08-01

This paper develops the repetitive control scheme for state tracking control of uncertain stochastic time-varying delay systems via equivalent-input-disturbance approach. The main purpose of this work is to design a repetitive controller to guarantee the tracking performance under the effects of unknown disturbances with bounded frequency and parameter variations. Specifically, a new set of linear matrix inequality (LMI)-based conditions is derived based on the suitable Lyapunov-Krasovskii functional theory for designing a repetitive controller which guarantees stability and desired tracking performance. More precisely, an equivalent-input-disturbance estimator is incorporated into the control design to reduce the effect of the external disturbances. Simulation results are provided to demonstrate the desired control system stability and their tracking performance. A practical stream water quality preserving system is also provided to show the effectiveness and advantage of the proposed approach.

Lonely GPFUTV-the movement of water under the action of unknown vacuum

NASA Astrophysics Data System (ADS)

Lin, Weiyi

2013-11-01

In this paper, firstly, the experiment on the flow resistance of the aerated pipe flow is introduced. The experimental research on comparison between different volumes of air entrained is presented. Secondly, the characteristics of gravity pipe flow under the action of Torricelli's vacuum, shortly called as GPFUTV are dissertated, including creative and functional design, fundamental principle, etc. Under the joint action of an unknown vacuum energy and the formation of non-aerated flow the water flow is full-pipe and continuous, high-speed and non-rotational as distinguished from turbulent flow. Thirdly, an appeal in relation to the experimental research, the applied studies and basic theory research is given. For instance, experimental study of Torricelli's experiment phenomenon in the vacuum environment, applied study of the potential for GPFUTV to be developed for deep seawater suction technology and lifting technology for deep ocean mining, theoretical study of flow stability and flow resistance under GPFUTV condition, etc. At last, the famous GPFUTV project is illustrated. 12 years of rigorous and independent survey research.

A comparison of Monte Carlo-based Bayesian parameter estimation methods for stochastic models of genetic networks

PubMed Central

Zaikin, Alexey; Míguez, Joaquín

2017-01-01

We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency. PMID:28797087

Biomechanical forces in the skeleton and their relevance to bone metastasis: biology and engineering considerations

PubMed Central

Lynch, Maureen; Fischbach, Claudia

2014-01-01

Bone metastasis represents the leading cause of breast cancer related-deaths. However, the effect of skeleton-associated biomechanical signals on the initiation, progression, and therapy response of breast cancer bone metastasis is largely unknown. This review seeks to highlight possible functional connections between skeletal mechanical signals and breast cancer bone metastasis and their contribution to clinical outcome. It provides an introduction to the physical and biological signals underlying bone functional adaptation and discusses the modulatory roles of mechanical loading and breast cancer metastasis in this process. Following a definition of biophysical design criteria, in vitro and in vivo approaches from the fields of bone biomechanics and tissue engineering will be reviewed that may be suitable to investigate breast cancer bone metastasis as a function of varied mechano-signaling. Finally, an outlook of future opportunities and challenges associated with this newly emerging field will be provided. PMID:25174311

Using NMR spectroscopy to elucidate the role of molecular motions in enzyme function

PubMed Central

Lisi, George P.; Loria, J. Patrick

2015-01-01

Conformational motions play an essential role in enzyme function, often facilitating the formation of enzyme-substrate complexes and/or product release. Although considerable debate remains regarding the role of molecular motions in the conversion of enzymatic substrates to products, numerous examples have found motions to be crucial for optimization of enzyme scaffolds, effective substrate binding, and product dissociation. Conformational fluctuations are often rate-limiting to enzyme catalysis, primarily through product release, with the chemical reaction occurring much more quickly. As a result, the direct involvement of motions at various stages along the enzyme reaction coordinate remains largely unknown and untested. In the following review, we describe the use of solution NMR techniques designed to probe various timescales of molecular motions and detail examples in which motions play a role in propagating catalytic effects from the active site and directly participate in essential aspects of enzyme function. PMID:26952190

Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

NASA Technical Reports Server (NTRS)

Wen, John T.; Kreutz-Delgado, Kenneth; Bayard, David S.

1992-01-01

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

Observer-based robust finite time H∞ sliding mode control for Markovian switching systems with mode-dependent time-varying delay and incomplete transition rate.

PubMed

Gao, Lijun; Jiang, Xiaoxiao; Wang, Dandan

2016-03-01

This paper investigates the problem of robust finite time H∞ sliding mode control for a class of Markovian switching systems. The system is subjected to the mode-dependent time-varying delay, partly unknown transition rate and unmeasurable state. The main difficulty is that, a sliding mode surface cannot be designed based on the unknown transition rate and unmeasurable state directly. To overcome this obstacle, the set of modes is firstly divided into two subsets standing for known transition rate subset and unknown one, based on which a state observer is established. A component robust finite-time sliding mode controller is also designed to cope with the effect of partially unknown transition rate. It is illustrated that the reachability, finite-time stability, finite-time boundedness, finite-time H∞ state feedback stabilization of sliding mode dynamics can be ensured despite the unknown transition rate. Finally, the simulation results verify the effectiveness of robust finite time control problem. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

MXLKID: a maximum likelihood parameter identifier. [In LRLTRAN for CDC 7600

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

Gavel, D.T.

MXLKID (MaXimum LiKelihood IDentifier) is a computer program designed to identify unknown parameters in a nonlinear dynamic system. Using noisy measurement data from the system, the maximum likelihood identifier computes a likelihood function (LF). Identification of system parameters is accomplished by maximizing the LF with respect to the parameters. The main body of this report briefly summarizes the maximum likelihood technique and gives instructions and examples for running the MXLKID program. MXLKID is implemented LRLTRAN on the CDC7600 computer at LLNL. A detailed mathematical description of the algorithm is given in the appendices. 24 figures, 6 tables.

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

Off-Policy Actor-Critic Structure for Optimal Control of Unknown Systems With Disturbances.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai; Zhang, Huaguang

2016-05-01

An optimal control method is developed for unknown continuous-time systems with unknown disturbances in this paper. The integral reinforcement learning (IRL) algorithm is presented to obtain the iterative control. Off-policy learning is used to allow the dynamics to be completely unknown. Neural networks are used to construct critic and action networks. It is shown that if there are unknown disturbances, off-policy IRL may not converge or may be biased. For reducing the influence of unknown disturbances, a disturbances compensation controller is added. It is proven that the weight errors are uniformly ultimately bounded based on Lyapunov techniques. Convergence of the Hamiltonian function is also proven. The simulation study demonstrates the effectiveness of the proposed optimal control method for unknown systems with disturbances.

National Dam Safety Program. Moon Valley Dam (MO 11597), Missouri - Kansas City Basin, Boone County, Missouri. Phase I Inspection Report.

DTIC Science & Technology

1981-08-01

Design 6 2.2 Construction 6 2.3 Operation 6 2.4 Geology 6 2.5 Evaluation 6 SECTION 3 - VISUAL INSPECTION 3.1 Findings 7 3.2 Evaluation 9 SECTION 4...Downstream of Dam 9 Erosion Behind East Wingwall 10 Erosion and Debris Behind West Wingwall 11 Diagonal Crack in East Wingwall 12 West Wingwall...2.0 H to approximately 1.0 V on 6.0 H. (6) Zoning - Unknown. (7) Impervious core - Unknown. (8) Cutoff - Unknown. ( 9 ) Grout curtain - Unknown. h

ShiftNMFk 1.2

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

Alexandrov, Boian S.; Vesselinov, Velimir V.; Stanev, Valentin

The ShiftNMFk1.2 code, or as we call it, GreenNMFk, represents a hybrid algorithm combining unsupervised adaptive machine learning and Green's function inverse method. GreenNMFk allows an efficient and high performance de-mixing and feature extraction of a multitude of nonnegative signals that change their shape propagating through the medium. The signals are mixed and recorded by a network of uncorrelated sensors. The code couples Non-negative Matrix Factorization (NMF) and inverse-analysis Green's functions method. GreenNMF synergistically performs decomposition of the recorded mixtures, finds the number of the unknown sources and uses the Green's function of the governing partial differential equation to identifymore » the unknown sources and their charecteristics. GreenNMF can be applied directly to any problem controlled by a known partial-differential parabolic equation where mixtures of an unknown number of sources are measured at multiple locations. Full GreenNMFk method is a subject LANL U.S. Patent application S133364.000 August, 2017. The ShiftNMFk 1.2 version here is a toy version of this method that can work with a limited number of unknown sources (4 or less).« less

The longitudinal development of social and executive functions in late adolescence and early adulthood

PubMed Central

Taylor, Sophie J.; Barker, Lynne A.; Heavey, Lisa; McHale, Sue

2015-01-01

Our earlier work suggests that, executive functions and social cognition show protracted development into late adolescence and early adulthood (Taylor et al., 2013). However, it remains unknown whether these functions develop linearly or non-linearly corresponding to dynamic changes to white matter density at these age ranges. Executive functions are particularly in demand during the transition to independence and autonomy associated with this age range (Ahmed and Miller, 2011). Previous research examining executive function (Romine and Reynolds, 2005) and social cognition (Dumontheil et al., 2010a) in late adolescence has utilized a cross sectional design. The current study employed a longitudinal design with 58 participants aged 17, 18, and 19 years completing social cognition and executive function tasks, Wechsler Abbreviated Scale of Intelligence (Wechsler, 1999), Positive and Negative Affect Schedule (Watson et al., 1988), and Hospital Anxiety and Depression Scale (Zigmond and Snaith, 1983) at Time 1 with follow up testing 12–16 months later. Inhibition, rule detection, strategy generation and planning executive functions and emotion recognition with dynamic stimuli showed longitudinal development between time points. Self-report empathy and emotion recognition functions using visual static and auditory stimuli were stable by age 17 whereas concept formation declined between time points. The protracted development of some functions may reflect continued brain maturation into late adolescence and early adulthood including synaptic pruning (Sowell et al., 2001) and changes to functional connectivity (Stevens et al., 2007) and/or environmental change. Clinical implications, such as assessing the effectiveness of rehabilitation following Head Injury, are discussed. PMID:26441579

Dual control and prevention of the turn-off phenomenon in a class of mimo systems

NASA Technical Reports Server (NTRS)

Mookerjee, P.; Bar-Shalom, Y.; Molusis, J. A.

1985-01-01

A recently developed methodology of adaptive dual control based upon sensitivity functions is applied here to a multivariable input-output model. The plant has constant but unknown parameters. It represents a simplified linear version of the relationship between the vibration output and the higher harmonic control input for a helicopter. The cautious and the new dual controller are examined. In many instances, the cautious controller is seen to turn off. The new dual controller modifies the cautious control design by numerator and denominator correction terms which depend upon the sensitivity functions of the expected future cost and avoids the turn-off and burst phenomena. Monte Carlo simulations and statistical tests of significance indicate the superiority of the dual controller over the cautious and the heuristic certainity equivalence controllers.

The Associations of Naturalistic Classic Psychedelic Use, Mystical Experience, and Creative Problem Solving.

PubMed

Sweat, Noah W; Bates, Larry W; Hendricks, Peter S

2016-01-01

Developing methods for improving creativity is of broad interest. Classic psychedelics may enhance creativity; however, the underlying mechanisms of action are unknown. This study was designed to assess whether a relationship exists between naturalistic classic psychedelic use and heightened creative problem-solving ability and if so, whether this is mediated by lifetime mystical experience. Participants (N = 68) completed a survey battery assessing lifetime mystical experience and circumstances surrounding the most memorable experience. They were then administered a functional fixedness task in which faster completion times indicate greater creative problem-solving ability. Participants reporting classic psychedelic use concurrent with mystical experience (n = 11) exhibited significantly faster times on the functional fixedness task (Cohen's d = -.87; large effect) and significantly greater lifetime mystical experience (Cohen's d = .93; large effect) than participants not reporting classic psychedelic use concurrent with mystical experience. However, lifetime mystical experience was unrelated to completion times on the functional fixedness task (standardized β = -.06), and was therefore not a significant mediator. Classic psychedelic use may increase creativity independent of its effects on mystical experience. Maximizing the likelihood of mystical experience may need not be a goal of psychedelic interventions designed to boost creativity.

Predicting phenotype from genotype: Improving accuracy through more robust experimental and computational modeling

PubMed Central

Gallion, Jonathan; Koire, Amanda; Katsonis, Panagiotis; Schoenegge, Anne‐Marie; Bouvier, Michel

2017-01-01

Abstract Computational prediction yields efficient and scalable initial assessments of how variants of unknown significance may affect human health. However, when discrepancies between these predictions and direct experimental measurements of functional impact arise, inaccurate computational predictions are frequently assumed as the source. Here, we present a methodological analysis indicating that shortcomings in both computational and biological data can contribute to these disagreements. We demonstrate that incomplete assaying of multifunctional proteins can affect the strength of correlations between prediction and experiments; a variant's full impact on function is better quantified by considering multiple assays that probe an ensemble of protein functions. Additionally, many variants predictions are sensitive to protein alignment construction and can be customized to maximize relevance of predictions to a specific experimental question. We conclude that inconsistencies between computation and experiment can often be attributed to the fact that they do not test identical hypotheses. Aligning the design of the computational input with the design of the experimental output will require cooperation between computational and biological scientists, but will also lead to improved estimations of computational prediction accuracy and a better understanding of the genotype–phenotype relationship. PMID:28230923

Predicting phenotype from genotype: Improving accuracy through more robust experimental and computational modeling.

PubMed

Gallion, Jonathan; Koire, Amanda; Katsonis, Panagiotis; Schoenegge, Anne-Marie; Bouvier, Michel; Lichtarge, Olivier

2017-05-01

Computational prediction yields efficient and scalable initial assessments of how variants of unknown significance may affect human health. However, when discrepancies between these predictions and direct experimental measurements of functional impact arise, inaccurate computational predictions are frequently assumed as the source. Here, we present a methodological analysis indicating that shortcomings in both computational and biological data can contribute to these disagreements. We demonstrate that incomplete assaying of multifunctional proteins can affect the strength of correlations between prediction and experiments; a variant's full impact on function is better quantified by considering multiple assays that probe an ensemble of protein functions. Additionally, many variants predictions are sensitive to protein alignment construction and can be customized to maximize relevance of predictions to a specific experimental question. We conclude that inconsistencies between computation and experiment can often be attributed to the fact that they do not test identical hypotheses. Aligning the design of the computational input with the design of the experimental output will require cooperation between computational and biological scientists, but will also lead to improved estimations of computational prediction accuracy and a better understanding of the genotype-phenotype relationship. © 2017 The Authors. **Human Mutation published by Wiley Periodicals, Inc.

Solving differential equations with unknown constitutive relations as recurrent neural networks

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

Hagge, Tobias J.; Stinis, Panagiotis; Yeung, Enoch H.

We solve a system of ordinary differential equations with an unknown functional form of a sink (reaction rate) term. We assume that the measurements (time series) of state variables are partially available, and use a recurrent neural network to “learn” the reaction rate from this data. This is achieved by including discretized ordinary differential equations as part of a recurrent neural network training problem. We extend TensorFlow’s recurrent neural network architecture to create a simple but scalable and effective solver for the unknown functions, and apply it to a fedbatch bioreactor simulation problem. Use of techniques from recent deep learningmore » literature enables training of functions with behavior manifesting over thousands of time steps. Our networks are structurally similar to recurrent neural networks, but differ in purpose, and require modified training strategies.« less

Sequences Associated with Centromere Competency in the Human Genome

PubMed Central

Hayden, Karen E.; Strome, Erin D.; Merrett, Stephanie L.; Lee, Hye-Ran; Rudd, M. Katharine

2013-01-01

Centromeres, the sites of spindle attachment during mitosis and meiosis, are located in specific positions in the human genome, normally coincident with diverse subsets of alpha satellite DNA. While there is strong evidence supporting the association of some subfamilies of alpha satellite with centromere function, the basis for establishing whether a given alpha satellite sequence is or is not designated a functional centromere is unknown, and attempts to understand the role of particular sequence features in establishing centromere identity have been limited by the near identity and repetitive nature of satellite sequences. Utilizing a broadly applicable experimental approach to test sequence competency for centromere specification, we have carried out a genomic and epigenetic functional analysis of endogenous human centromere sequences available in the current human genome assembly. The data support a model in which functionally competent sequences confer an opportunity for centromere specification, integrating genomic and epigenetic signals and promoting the concept of context-dependent centromere inheritance. PMID:23230266

National Dam Safety Program. Highland Park Reservoir Dam (Inventory Number N.Y. 790), Genesee River Basin, Monroe County, New York. Phase I Inspection Report,

DTIC Science & Technology

1981-09-14

34 rga Highland Park Reservoir Dam Vi’.sual I. .. ’. •Genesee River Basin, ’!ydrolozy. ". ". . . Scabi tyMo r e C u t.,.- Js eps’ •; ::or.ation -3 :..i :n...dam impounds a municipal water storage reservoir. g. Design and Construction History The dam was designed and built around 1875. h. Normal Operating... History : Date Constructed Around 1875 Date(s) Reconstructed N/A Designer Unknown Constructed by Unknown Owner Water Department, City of Rochester, New

Nonholonomic Ofject Tracking with Optical Sensors and Ofject Recognition Feedback

NASA Technical Reports Server (NTRS)

Goddard, R. E.; Hadaegh, F.

1994-01-01

Robotic controllers frequently operate under constraints. Often, the constraints are imperfectly or completely unknown. In this paper, the Lagrangian dynamics of a planar robot arm are expressed as a function of a globally unknown consraint.

Numerical solution to generalized Burgers'-Fisher equation using Exp-function method hybridized with heuristic computation.

PubMed

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems.

Numerical Solution to Generalized Burgers'-Fisher Equation Using Exp-Function Method Hybridized with Heuristic Computation

PubMed Central

Malik, Suheel Abdullah; Qureshi, Ijaz Mansoor; Amir, Muhammad; Malik, Aqdas Naveed; Haq, Ihsanul

2015-01-01

In this paper, a new heuristic scheme for the approximate solution of the generalized Burgers'-Fisher equation is proposed. The scheme is based on the hybridization of Exp-function method with nature inspired algorithm. The given nonlinear partial differential equation (NPDE) through substitution is converted into a nonlinear ordinary differential equation (NODE). The travelling wave solution is approximated by the Exp-function method with unknown parameters. The unknown parameters are estimated by transforming the NODE into an equivalent global error minimization problem by using a fitness function. The popular genetic algorithm (GA) is used to solve the minimization problem, and to achieve the unknown parameters. The proposed scheme is successfully implemented to solve the generalized Burgers'-Fisher equation. The comparison of numerical results with the exact solutions, and the solutions obtained using some traditional methods, including adomian decomposition method (ADM), homotopy perturbation method (HPM), and optimal homotopy asymptotic method (OHAM), show that the suggested scheme is fairly accurate and viable for solving such problems. PMID:25811858

Bianchi type I in f(T) gravitational theories

NASA Astrophysics Data System (ADS)

M, I. Wanas; G, G. L. Nashed; O, A. Ibrahim

2016-05-01

A tetrad field that is homogeneous and anisotropic which contains two unknown functions A(t) and B(t) of cosmic time is applied to the field equations of f (T), where T is the torsion scalar, T = T μ νρ S μ νρ . We calculate the equation of continuity and rewrite it as a product of two brackets, the first is a function of f (T) and the second is a function of the two unknowns A(t) and B(t). We use two different relations between the two unknown functions A(t) and B(t) in the second bracket to solve it. Both of these relations give constant scalar torsion and solutions coincide with the de Sitter one. So, another assumption related to the contents of the matter fields is postulated. This assumption enables us to drive a solution with a non-constant value of the scalar torsion and a form of f (T) which represents ΛCDM. Project supported by the Egyptian Ministry of Scientific Research (Project No. 24-2-12).

Enriching the annotation of Mycobacterium tuberculosis H37Rv proteome using remote homology detection approaches: insights into structure and function.

PubMed

Ramakrishnan, Gayatri; Ochoa-Montaño, Bernardo; Raghavender, Upadhyayula S; Mudgal, Richa; Joshi, Adwait G; Chandra, Nagasuma R; Sowdhamini, Ramanathan; Blundell, Tom L; Srinivasan, Narayanaswamy

2015-01-01

The availability of the genome sequence of Mycobacterium tuberculosis H37Rv has encouraged determination of large numbers of protein structures and detailed definition of the biological information encoded therein; yet, the functions of many proteins in M. tuberculosis remain unknown. The emergence of multidrug resistant strains makes it a priority to exploit recent advances in homology recognition and structure prediction to re-analyse its gene products. Here we report the structural and functional characterization of gene products encoded in the M. tuberculosis genome, with the help of sensitive profile-based remote homology search and fold recognition algorithms resulting in an enhanced annotation of the proteome where 95% of the M. tuberculosis proteins were identified wholly or partly with information on structure or function. New information includes association of 244 proteins with 205 domain families and a separate set of new association of folds to 64 proteins. Extending structural information across uncharacterized protein families represented in the M. tuberculosis proteome, by determining superfamily relationships between families of known and unknown structures, has contributed to an enhancement in the knowledge of structural content. In retrospect, such superfamily relationships have facilitated recognition of probable structure and/or function for several uncharacterized protein families, eventually aiding recognition of probable functions for homologous proteins corresponding to such families. Gene products unique to mycobacteria for which no functions could be identified are 183. Of these 18 were determined to be M. tuberculosis specific. Such pathogen-specific proteins are speculated to harbour virulence factors required for pathogenesis. A re-annotated proteome of M. tuberculosis, with greater completeness of annotated proteins and domain assigned regions, provides a valuable basis for experimental endeavours designed to obtain a better understanding of pathogenesis and to accelerate the process of drug target discovery. Copyright © 2014 Elsevier Ltd. All rights reserved.

Functional specialization in nucleotide sugar transporters occurred through differentiation of the gene cluster EamA (DUF6) before the radiation of Viridiplantae

PubMed Central

2011-01-01

Background The drug/metabolite transporter superfamily comprises a diversity of protein domain families with multiple functions including transport of nucleotide sugars. Drug/metabolite transporter domains are contained in both solute carrier families 30, 35 and 39 proteins as well as in acyl-malonyl condensing enzyme proteins. In this paper, we present an evolutionary analysis of nucleotide sugar transporters in relation to the entire superfamily of drug/metabolite transporters that considers crucial intra-protein duplication events that have shaped the transporters. We use a method that combines the strengths of hidden Markov models and maximum likelihood to find relationships between drug/metabolite transporter families, and branches within families. Results We present evidence that the triose-phosphate transporters, domain unknown function 914, uracil-diphosphate glucose-N-acetylglucosamine, and nucleotide sugar transporter families have evolved from a domain duplication event before the radiation of Viridiplantae in the EamA family (previously called domain unknown function 6). We identify previously unknown branches in the solute carrier 30, 35 and 39 protein families that emerged simultaneously as key physiological developments after the radiation of Viridiplantae, including the "35C/E" branch of EamA, which formed in the lineage of T. adhaerens (Animalia). We identify a second cluster of DMTs, called the domain unknown function 1632 cluster, which has non-cytosolic N- and C-termini, and thus appears to have been formed from a different domain duplication event. We identify a previously uncharacterized motif, G-X(6)-G, which is overrepresented in the fifth transmembrane helix of C-terminal domains. We present evidence that the family called fatty acid elongases are homologous to transporters, not enzymes as had previously been thought. Conclusions The nucleotide sugar transporters families were formed through differentiation of the gene cluster EamA (domain unknown function 6) before Viridiplantae, showing for the first time the significance of EamA. PMID:21569384

Will Systems Biology Deliver Its Promise and Contribute to the Development of New or Improved Vaccines? What Really Constitutes the Study of "Systems Biology" and How Might Such an Approach Facilitate Vaccine Design.

PubMed

Germain, Ronald N

2017-10-16

A dichotomy exists in the field of vaccinology about the promise versus the hype associated with application of "systems biology" approaches to rational vaccine design. Some feel it is the only way to efficiently uncover currently unknown parameters controlling desired immune responses or discover what elements actually mediate these responses. Others feel that traditional experimental, often reductionist, methods for incrementally unraveling complex biology provide a more solid way forward, and that "systems" approaches are costly ways to collect data without gaining true insight. Here I argue that both views are inaccurate. This is largely because of confusion about what can be gained from classical experimentation versus statistical analysis of large data sets (bioinformatics) versus methods that quantitatively explain emergent properties of complex assemblies of biological components, with the latter reflecting what was previously called "physiology." Reductionist studies will remain essential for generating detailed insight into the functional attributes of specific elements of biological systems, but such analyses lack the power to provide a quantitative and predictive understanding of global system behavior. But by employing (1) large-scale screening methods for discovery of unknown components and connections in the immune system ( omics ), (2) statistical analysis of large data sets ( bioinformatics ), and (3) the capacity of quantitative computational methods to translate these individual components and connections into models of emergent behavior ( systems biology ), we will be able to better understand how the overall immune system functions and to determine with greater precision how to manipulate it to produce desired protective responses. Copyright © 2017 Cold Spring Harbor Laboratory Press; all rights reserved.

Considerations to improve functional annotations in biological databases.

PubMed

Benítez-Páez, Alfonso

2009-12-01

Despite the great effort to design efficient systems allowing the electronic indexation of information concerning genes, proteins, structures, and interactions published daily in scientific journals, some problems are still observed in specific tasks such as functional annotation. The annotation of function is a critical issue for bioinformatic routines, such as for instance, in functional genomics and the further prediction of unknown protein function, which are highly dependent of the quality of existing annotations. Some information management systems evolve to efficiently incorporate information from large-scale projects, but often, annotation of single records from the literature is difficult and slow. In this short report, functional characterizations of a representative sample of the entire set of uncharacterized proteins from Escherichia coli K12 was compiled from Swiss-Prot, PubMed, and EcoCyc and demonstrate a functional annotation deficit in biological databases. Some issues are postulated as causes of the lack of annotation, and different solutions are evaluated and proposed to avoid them. The hope is that as a consequence of these observations, there will be new impetus to improve the speed and quality of functional annotation and ultimately provide updated, reliable information to the scientific community.

Computational design and experimental verification of a symmetric protein homodimer.

PubMed

Mou, Yun; Huang, Po-Ssu; Hsu, Fang-Ciao; Huang, Shing-Jong; Mayo, Stephen L

2015-08-25

Homodimers are the most common type of protein assembly in nature and have distinct features compared with heterodimers and higher order oligomers. Understanding homodimer interactions at the atomic level is critical both for elucidating their biological mechanisms of action and for accurate modeling of complexes of unknown structure. Computation-based design of novel protein-protein interfaces can serve as a bottom-up method to further our understanding of protein interactions. Previous studies have demonstrated that the de novo design of homodimers can be achieved to atomic-level accuracy by β-strand assembly or through metal-mediated interactions. Here, we report the design and experimental characterization of a α-helix-mediated homodimer with C2 symmetry based on a monomeric Drosophila engrailed homeodomain scaffold. A solution NMR structure shows that the homodimer exhibits parallel helical packing similar to the design model. Because the mutations leading to dimer formation resulted in poor thermostability of the system, design success was facilitated by the introduction of independent thermostabilizing mutations into the scaffold. This two-step design approach, function and stabilization, is likely to be generally applicable, especially if the desired scaffold is of low thermostability.

Nonparametric Bayesian models for a spatial covariance.

PubMed

Reich, Brian J; Fuentes, Montserrat

2012-01-01

A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.

Newly designed 11-gene panel reveals first case of hereditary amyloidosis captured by massive parallel sequencing.

PubMed

Chyra Kufova, Zuzana; Sevcikova, Tereza; Januska, Jaroslav; Vojta, Petr; Boday, Arpad; Vanickova, Pavla; Filipova, Jana; Growkova, Katerina; Jelinek, Tomas; Hajduch, Marian; Hajek, Roman

2018-02-17

Amyloidosis is caused by deposition of abnormal protein fibrils, leading to damage of organ function. Hereditary amyloidosis represents a monogenic disease caused by germline mutations in 11 amyloidogenic precursor protein genes. One of the important but non-specific symptoms of amyloidosis is hypertrophic cardiomyopathy. Diagnostics of hereditary amyloidosis is complicated and the real cause can remain overlooked. We aimed to design hereditary amyloidosis gene panel and to introduce new next-generation sequencing (NGS) approach to investigate hereditary amyloidosis in a cohort of patients with hypertrophic cardiomyopathy of unknown significance. Design of target enrichment DNA library preparation using Haloplex Custom Kit containing 11 amyloidogenic genes was followed by MiSeq Illumina sequencing and bioinformatics identification of germline variants using tool VarScan in a cohort of 40 patients. We present design of NGS panel for 11 genes ( TTR , FGA , APOA1 , APOA2 , LYZ , GSN , CST3 , PRNP , APP , B2M , ITM2B ) connected to various forms of amyloidosis. We detected one mutation, which is responsible for hereditary amyloidosis. Some other single nucleotide variants are so far undescribed or rare variants or represent common polymorphisms in European population. We report one positive case of hereditary amyloidosis in a cohort of patients with hypertrophic cardiomyopathy of unknown significance and set up first panel for NGS in hereditary amyloidosis. This work may facilitate successful implementation of the NGS method by other researchers or clinicians and may improve the diagnostic process after validation. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

A new family of β-helix proteins with similarities to the polysaccharide lyases

DOE PAGES

Close, Devin W.; D'Angelo, Sara; Bradbury, Andrew R. M.

2014-09-27

Microorganisms that degrade biomass produce diverse assortments of carbohydrate-active enzymes and binding modules. Despite tremendous advances in the genomic sequencing of these organisms, many genes do not have an ascribed function owing to low sequence identity to genes that have been annotated. Consequently, biochemical and structural characterization of genes with unknown function is required to complement the rapidly growing pool of genomic sequencing data. A protein with previously unknown function (Cthe_2159) was recently isolated in a genome-wide screen using phage display to identify cellulose-binding protein domains from the biomass-degrading bacterium Clostridium thermocellum. Here, the crystal structure of Cthe_2159 is presentedmore » and it is shown that it is a unique right-handed parallel β-helix protein. Despite very low sequence identity to known β-helix or carbohydrate-active proteins, Cthe_2159 displays structural features that are very similar to those of polysaccharide lyase (PL) families 1, 3, 6 and 9. Cthe_2159 is conserved across bacteria and some archaea and is a member of the domain of unknown function family DUF4353. This suggests that Cthe_2159 is the first representative of a previously unknown family of cellulose and/or acid-sugar binding β-helix proteins that share structural similarities with PLs. More importantly, these results demonstrate how functional annotation by biochemical and structural analysis remains a critical tool in the characterization of new gene products.« less

A new family of β-helix proteins with similarities to the polysaccharide lyases

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

Close, Devin W.; D'Angelo, Sara; Bradbury, Andrew R. M.

Microorganisms that degrade biomass produce diverse assortments of carbohydrate-active enzymes and binding modules. Despite tremendous advances in the genomic sequencing of these organisms, many genes do not have an ascribed function owing to low sequence identity to genes that have been annotated. Consequently, biochemical and structural characterization of genes with unknown function is required to complement the rapidly growing pool of genomic sequencing data. A protein with previously unknown function (Cthe_2159) was recently isolated in a genome-wide screen using phage display to identify cellulose-binding protein domains from the biomass-degrading bacterium Clostridium thermocellum. Here, the crystal structure of Cthe_2159 is presentedmore » and it is shown that it is a unique right-handed parallel β-helix protein. Despite very low sequence identity to known β-helix or carbohydrate-active proteins, Cthe_2159 displays structural features that are very similar to those of polysaccharide lyase (PL) families 1, 3, 6 and 9. Cthe_2159 is conserved across bacteria and some archaea and is a member of the domain of unknown function family DUF4353. This suggests that Cthe_2159 is the first representative of a previously unknown family of cellulose and/or acid-sugar binding β-helix proteins that share structural similarities with PLs. More importantly, these results demonstrate how functional annotation by biochemical and structural analysis remains a critical tool in the characterization of new gene products.« less

A method for partitioning the information contained in a protein sequence between its structure and function.

PubMed

Possenti, Andrea; Vendruscolo, Michele; Camilloni, Carlo; Tiana, Guido

2018-05-23

Proteins employ the information stored in the genetic code and translated into their sequences to carry out well-defined functions in the cellular environment. The possibility to encode for such functions is controlled by the balance between the amount of information supplied by the sequence and that left after that the protein has folded into its structure. We study the amount of information necessary to specify the protein structure, providing an estimate that keeps into account the thermodynamic properties of protein folding. We thus show that the information remaining in the protein sequence after encoding for its structure (the 'information gap') is very close to what needed to encode for its function and interactions. Then, by predicting the information gap directly from the protein sequence, we show that it may be possible to use these insights from information theory to discriminate between ordered and disordered proteins, to identify unknown functions, and to optimize artificially-designed protein sequences. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Excitons in scintillator materials: Optical properties and electron-energy loss spectra of NaI, LaBr 3, BaI 2, and SrI 2

DOE PAGES

Schleife, Andre; Zhang, Xiao; Li, Qi; ...

2016-11-03

In this paper, materials for scintillator radiation detectors need to fulfill a diverse set of requirements such as radiation hardness and highly specific response to incoming radiation, rendering them a target of current materials design efforts. Even though they are amenable to cutting-edge theoretical spectroscopy techniques, surprisingly many fundamental properties of scintillator materials are still unknown or not well explored. In this work, we use first-principles approaches to thoroughly study the optical properties of four scintillator materials: NaI, LaBr 3, BaI 2, and SrI 2. By solving the Bethe–Salpeter equation for the optical polarization function we study the influence ofmore » excitonic effects on dielectric and electron-energy loss functions. This work sheds light into fundamental optical properties of these four scintillator materials and lays the ground-work for future work that is geared toward accurate modeling and computational materials design of advanced radiation detectors with unprecedented energy resolution.« less

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

Luo, Shaohua; School of Automation, Chongqing University, Chongqing 400044; Sun, Quanping

This paper addresses chaos control of the micro-electro- mechanical resonator by using adaptive dynamic surface technology with extended state observer. To reveal the mechanism of the micro- electro-mechanical resonator, the phase diagrams and corresponding time histories are given to research the nonlinear dynamics and chaotic behavior, and Homoclinic and heteroclinic chaos which relate closely with the appearance of chaos are presented based on the potential function. To eliminate the effect of chaos, an adaptive dynamic surface control scheme with extended state observer is designed to convert random motion into regular motion without precise system model parameters and measured variables. Puttingmore » tracking differentiator into chaos controller solves the ‘explosion of complexity’ of backstepping and poor precision of the first-order filters. Meanwhile, to obtain high performance, a neural network with adaptive law is employed to approximate unknown nonlinear function in the process of controller design. The boundedness of all the signals of the closed-loop system is proved in theoretical analysis. Finally, numerical simulations are executed and extensive results illustrate effectiveness and robustness of the proposed scheme.« less

Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach

NASA Astrophysics Data System (ADS)

Zheng, Taixiong

2005-12-01

A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.

Decentralised output feedback control of Markovian jump interconnected systems with unknown interconnections

NASA Astrophysics Data System (ADS)

Li, Li-Wei; Yang, Guang-Hong

2017-07-01

The problem of decentralised output feedback control is addressed for Markovian jump interconnected systems with unknown interconnections and general transition rates (TRs) allowed to be unknown or known with uncertainties. A class of decentralised dynamic output feedback controllers are constructed, and a cyclic-small-gain condition is exploited to dispose the unknown interconnections so that the resultant closed-loop system is stochastically stable and satisfies an H∞ performance. With slack matrices to cope with the nonlinearities incurred by unknown and uncertain TRs in control synthesis, a novel controller design condition is developed in linear matrix inequality formalism. Compared with the existing works, the proposed approach leads to less conservatism. Finally, two examples are used to illustrate the effectiveness of the new results.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Functional annotation from the genome sequence of the giant panda.

PubMed

Huo, Tong; Zhang, Yinjie; Lin, Jianping

2012-08-01

The giant panda is one of the most critically endangered species due to the fragmentation and loss of its habitat. Studying the functions of proteins in this animal, especially specific trait-related proteins, is therefore necessary to protect the species. In this work, the functions of these proteins were investigated using the genome sequence of the giant panda. Data on 21,001 proteins and their functions were stored in the Giant Panda Protein Database, in which the proteins were divided into two groups: 20,179 proteins whose functions can be predicted by GeneScan formed the known-function group, whereas 822 proteins whose functions cannot be predicted by GeneScan comprised the unknown-function group. For the known-function group, we further classified the proteins by molecular function, biological process, cellular component, and tissue specificity. For the unknown-function group, we developed a strategy in which the proteins were filtered by cross-Blast to identify panda-specific proteins under the assumption that proteins related to the panda-specific traits in the unknown-function group exist. After this filtering procedure, we identified 32 proteins (2 of which are membrane proteins) specific to the giant panda genome as compared against the dog and horse genomes. Based on their amino acid sequences, these 32 proteins were further analyzed by functional classification using SVM-Prot, motif prediction using MyHits, and interacting protein prediction using the Database of Interacting Proteins. Nineteen proteins were predicted to be zinc-binding proteins, thus affecting the activities of nucleic acids. The 32 panda-specific proteins will be further investigated by structural and functional analysis.

Design and analysis of adaptive Super-Twisting sliding mode control for a microgyroscope.

PubMed

Feng, Zhilin; Fei, Juntao

2018-01-01

This paper proposes a novel adaptive Super-Twisting sliding mode control for a microgyroscope under unknown model uncertainties and external disturbances. In order to improve the convergence rate of reaching the sliding surface and the accuracy of regulating and trajectory tracking, a high order Super-Twisting sliding mode control strategy is employed, which not only can combine the advantages of the traditional sliding mode control with the Super-Twisting sliding mode control, but also guarantee that the designed control system can reach the sliding surface and equilibrium point in a shorter finite time from any initial state and avoid chattering problems. In consideration of unknown parameters of micro gyroscope system, an adaptive algorithm based on Lyapunov stability theory is designed to estimate the unknown parameters and angular velocity of microgyroscope. Finally, the effectiveness of the proposed scheme is demonstrated by simulation results. The comparative study between adaptive Super-Twisting sliding mode control and conventional sliding mode control demonstrate the superiority of the proposed method.

Modeling of load lifting process with unknown center of gravity position

NASA Astrophysics Data System (ADS)

Kamanin, Y. N.; Zhukov, M. I.; Panichkin, A. V.; Redelin, R. A.

2018-03-01

The article proposes a new type of lifting beams that allows one to lift loads where the position of the center of gravity is unknown beforehand. The benefit of implementing this type of traverse is confirmed by the high demand for this product from the industrial enterprises and lack of their availability on the market. In conducted studies, the main kinematic and dynamic dependencies of the load lifting process with an unknown position of the center of gravity were described allowing for design and verification calculations of the traverse with flexible slings and an adjustable bail to be carried out. The obtained results can be useful to engineers and employees of enterprises engaged in the design and manufacturing of the lifting equipment and scientists doing research in “Carrying and lifting machines”.

Teleportation of a 3-dimensional GHZ State

NASA Astrophysics Data System (ADS)

Cao, Hai-Jing; Wang, Huai-Sheng; Li, Peng-Fei; Song, He-Shan

2012-05-01

The process of teleportation of a completely unknown 3-dimensional GHZ state is considered. Three maximally entangled 3-dimensional Bell states function as quantum channel in the scheme. This teleportation scheme can be directly generalized to teleport an unknown d-dimensional GHZ state.

The decision tree classifier - Design and potential. [for Landsat-1 data

NASA Technical Reports Server (NTRS)

Hauska, H.; Swain, P. H.

1975-01-01

A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

Elegant Gaussian beams for enhanced optical manipulation

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

Alpmann, Christina, E-mail: c.alpmann@uni-muenster.de; Schöler, Christoph; Denz, Cornelia

2015-06-15

Generation of micro- and nanostructured complex light beams attains increasing impact in photonics and laser applications. In this contribution, we demonstrate the implementation and experimental realization of the relatively unknown, but highly versatile class of complex-valued Elegant Hermite- and Laguerre-Gaussian beams. These beams create higher trapping forces compared to standard Gaussian light fields due to their propagation changing properties. We demonstrate optical trapping and alignment of complex functional particles as nanocontainers with standard and Elegant Gaussian light beams. Elegant Gaussian beams will inspire manifold applications in optical manipulation, direct laser writing, or microscopy, where the design of the point-spread functionmore » is relevant.« less

Protein domains of unknown function are essential in bacteria.

PubMed

Goodacre, Norman F; Gerloff, Dietlind L; Uetz, Peter

2013-12-31

More than 20% of all protein domains are currently annotated as "domains of unknown function" (DUFs). About 2,700 DUFs are found in bacteria compared with just over 1,500 in eukaryotes. Over 800 DUFs are shared between bacteria and eukaryotes, and about 300 of these are also present in archaea. A total of 2,786 bacterial Pfam domains even occur in animals, including 320 DUFs. Evolutionary conservation suggests that many of these DUFs are important. Here we show that 355 essential proteins in 16 model bacterial species contain 238 DUFs, most of which represent single-domain proteins, clearly establishing the biological essentiality of DUFs. We suggest that experimental research should focus on conserved and essential DUFs (eDUFs) for functional analysis given their important function and wide taxonomic distribution, including bacterial pathogens. The functional units of proteins are domains. Typically, each domain has a distinct structure and function. Genomes encode thousands of domains, and many of the domains have no known function (domains of unknown function [DUFs]). They are often ignored as of little relevance, given that many of them are found in only a few genomes. Here we show that many DUFs are essential DUFs (eDUFs) based on their presence in essential proteins. We also show that eDUFs are often essential even if they are found in relatively few genomes. However, in general, more common DUFs are more often essential than rare DUFs.

Bayesian statistics and Monte Carlo methods

NASA Astrophysics Data System (ADS)

Koch, K. R.

2018-03-01

The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability. If the statements refer to the numerical values of variables, the so-called random variables, univariate and multivariate distributions follow. They lead to the point estimation by which unknown quantities, i.e. unknown parameters, are computed from measurements. The unknown parameters are random variables, they are fixed quantities in traditional statistics which is not founded on Bayes' theorem. Bayesian statistics therefore recommends itself for Monte Carlo methods, which generate random variates from given distributions. Monte Carlo methods, of course, can also be applied in traditional statistics. The unknown parameters, are introduced as functions of the measurements, and the Monte Carlo methods give the covariance matrix and the expectation of these functions. A confidence region is derived where the unknown parameters are situated with a given probability. Following a method of traditional statistics, hypotheses are tested by determining whether a value for an unknown parameter lies inside or outside the confidence region. The error propagation of a random vector by the Monte Carlo methods is presented as an application. If the random vector results from a nonlinearly transformed vector, its covariance matrix and its expectation follow from the Monte Carlo estimate. This saves a considerable amount of derivatives to be computed, and errors of the linearization are avoided. The Monte Carlo method is therefore efficient. If the functions of the measurements are given by a sum of two or more random vectors with different multivariate distributions, the resulting distribution is generally not known. TheMonte Carlo methods are then needed to obtain the covariance matrix and the expectation of the sum.

Class Identification Efficacy in Piecewise GMM with Unknown Turning Points

ERIC Educational Resources Information Center

Ning, Ling; Luo, Wen

2018-01-01

Piecewise GMM with unknown turning points is a new procedure to investigate heterogeneous subpopulations' growth trajectories consisting of distinct developmental phases. Unlike the conventional PGMM, which relies on theory or experiment design to specify turning points a priori, the new procedure allows for an optimal location of turning points…

Approach for establishing approximate load carrying capacity for bridges with unknown material and unknown design properties.

DOT National Transportation Integrated Search

2011-07-01

There are 16 small to medium simple span bridges in Larimer County, Colorado that are currently load rated solely based on visual inspections. Most of these bridges are prestressed concrete bridges. The objective of this project is to load rate these...

Time-to-event continual reassessment method incorporating treatment cycle information with application to an oncology phase I trial.

PubMed

Huang, Bo; Kuan, Pei Fen

2014-11-01

Delayed dose limiting toxicities (i.e. beyond first cycle of treatment) is a challenge for phase I trials. The time-to-event continual reassessment method (TITE-CRM) is a Bayesian dose-finding design to address the issue of long observation time and early patient drop-out. It uses a weighted binomial likelihood with weights assigned to observations by the unknown time-to-toxicity distribution, and is open to accrual continually. To avoid dosing at overly toxic levels while retaining accuracy and efficiency for DLT evaluation that involves multiple cycles, we propose an adaptive weight function by incorporating cyclical data of the experimental treatment with parameters updated continually. This provides a reasonable estimate for the time-to-toxicity distribution by accounting for inter-cycle variability and maintains the statistical properties of consistency and coherence. A case study of a First-in-Human trial in cancer for an experimental biologic is presented using the proposed design. Design calibrations for the clinical and statistical parameters are conducted to ensure good operating characteristics. Simulation results show that the proposed TITE-CRM design with adaptive weight function yields significantly shorter trial duration, does not expose patients to additional risk, is competitive against the existing weighting methods, and possesses some desirable properties. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

An efficient and flexible Abel-inversion method for noisy data

NASA Astrophysics Data System (ADS)

Antokhin, Igor I.

2016-12-01

We propose an efficient and flexible method for solving the Abel integral equation of the first kind, frequently appearing in many fields of astrophysics, physics, chemistry, and applied sciences. This equation represents an ill-posed problem, thus solving it requires some kind of regularization. Our method is based on solving the equation on a so-called compact set of functions and/or using Tikhonov's regularization. A priori constraints on the unknown function, defining a compact set, are very loose and can be set using simple physical considerations. Tikhonov's regularization in itself does not require any explicit a priori constraints on the unknown function and can be used independently of such constraints or in combination with them. Various target degrees of smoothness of the unknown function may be set, as required by the problem at hand. The advantage of the method, apart from its flexibility, is that it gives uniform convergence of the approximate solution to the exact solution, as the errors of input data tend to zero. The method is illustrated on several simulated models with known solutions. An example of astrophysical application of the method is also given.

The structure of the cyanobactin domain of unknown function from PatG in the patellamide gene cluster

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

Mann, Greg; Koehnke, Jesko; Bent, Andrew F.

The highly conserved domain of unknown function in the cyanobactin superfamily has a novel fold. The protein does not appear to bind the most plausible substrates, leaving questions as to its role. Patellamides are members of the cyanobactin family of ribosomally synthesized and post-translationally modified cyclic peptide natural products, many of which, including some patellamides, are biologically active. A detailed mechanistic understanding of the biosynthetic pathway would enable the construction of a biotechnological ‘toolkit’ to make novel analogues of patellamides that are not found in nature. All but two of the protein domains involved in patellamide biosynthesis have been characterized.more » The two domains of unknown function (DUFs) are homologous to each other and are found at the C-termini of the multi-domain proteins PatA and PatG. The domain sequence is found in all cyanobactin-biosynthetic pathways characterized to date, implying a functional role in cyanobactin biosynthesis. Here, the crystal structure of the PatG DUF domain is reported and its binding interactions with plausible substrates are investigated.« less

Visionary Expectations and Novice Designers--Prototyping in Design Education

ERIC Educational Resources Information Center

Schaeffer, Jennie Andersson; Palmgren, Marianne

2017-01-01

In information design education, we strive to find methods that provide students with opportunities to explore different ways of learning and designing. We seek to support development of contextual competences that will be helpful in navigating an unknown future of design in society. A challenge in today's design education is to formulate and use…

Fast estimate of Hartley entropy in image sharpening

NASA Astrophysics Data System (ADS)

Krbcová, Zuzana; Kukal, Jaromír.; Svihlik, Jan; Fliegel, Karel

2016-09-01

Two classes of linear IIR filters: Laplacian of Gaussian (LoG) and Difference of Gaussians (DoG) are frequently used as high pass filters for contextual vision and edge detection. They are also used for image sharpening when linearly combined with the original image. Resulting sharpening filters are radially symmetric in spatial and frequency domains. Our approach is based on the radial approximation of unknown optimal filter, which is designed as a weighted sum of Gaussian filters with various radii. The novel filter is designed for MRI image enhancement where the image intensity represents anatomical structure plus additive noise. We prefer the gradient norm of Hartley entropy of whole image intensity as a measure which has to be maximized for the best sharpening. The entropy estimation procedure is as fast as FFT included in the filter but this estimate is a continuous function of enhanced image intensities. Physically motivated heuristic is used for optimum sharpening filter design by its parameter tuning. Our approach is compared with Wiener filter on MRI images.

A new statistical method for design and analyses of component tolerance

NASA Astrophysics Data System (ADS)

Movahedi, Mohammad Mehdi; Khounsiavash, Mohsen; Otadi, Mahmood; Mosleh, Maryam

2017-03-01

Tolerancing conducted by design engineers to meet customers' needs is a prerequisite for producing high-quality products. Engineers use handbooks to conduct tolerancing. While use of statistical methods for tolerancing is not something new, engineers often use known distributions, including the normal distribution. Yet, if the statistical distribution of the given variable is unknown, a new statistical method will be employed to design tolerance. In this paper, we use generalized lambda distribution for design and analyses component tolerance. We use percentile method (PM) to estimate the distribution parameters. The findings indicated that, when the distribution of the component data is unknown, the proposed method can be used to expedite the design of component tolerance. Moreover, in the case of assembled sets, more extensive tolerance for each component with the same target performance can be utilized.

Knockdown of metallothionein 1 and 2 does not affect atrophy or oxidant activity in a novel in vitro model.

PubMed

Hyldahl, Robert D; O'Fallon, Kevin S; Schwartz, Lawrence M; Clarkson, Priscilla M

2010-11-01

Skeletal muscle atrophy is a significant health problem that results in decreased muscle size and function and has been associated with increases in oxidative stress. The molecular mechanisms that regulate muscle atrophy, however, are largely unknown. The metallothioneins (MT), a family of genes with antioxidant properties, have been found to be consistently upregulated during muscle atrophy, although their function during muscle atrophy is unknown. Therefore, we hypothesized that MT knockdown would result in greater oxidative stress and an enhanced atrophy response in C(2)C(12) myotubes subjected to serum reduction (SR), a novel atrophy-inducing stimulus. Forty-eight hours before SR, myotubes were transfected with small interfering RNA (siRNA) sequences designed to decrease MT expression. Muscle atrophy and oxidative stress were then measured at baseline and for 72 h following SR. Muscle atrophy was quantified by immunocytochemistry and myotube diameter measurements. Oxidative stress was measured using the fluorescent probe 5-(and-6)-carboxy-2',7'-dichlorodihydrofluorescein. SR resulted in a significant increase in oxidative stress and a decrease in myotube size and protein content. However, there were no differences observed in the extent of muscle atrophy or oxidant activity following MT knockdown. We therefore conclude that the novel SR model results in a strong atrophy response and an increase in oxidant activity in cultured myotubes and that knockdown of MT does not affect that response.

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

Allan, Christopher M.; Awad, Agape M.; Johnson, Jarrett S.

Coenzyme Q (Q or ubiquinone) is a redox active lipid composed of a fully substituted benzoquinone ring and a polyisoprenoid tail and is required for mitochondrial electron transport. In the yeast Saccharomyces cerevisiae, Q is synthesized by the products of 11 known genes, COQ1–COQ9, YAH1, and ARH1. The function of some of the Coq proteins remains unknown, and several steps in the Q biosynthetic pathway are not fully characterized. Several of the Coq proteins are associated in a macromolecular complex on the matrix face of the inner mitochondrial membrane, and this complex is required for efficient Q synthesis. In thismore » paper, we further characterize this complex via immunoblotting and proteomic analysis of tandem affinity-purified tagged Coq proteins. We show that Coq8, a putative kinase required for the stability of the Q biosynthetic complex, is associated with a Coq6-containing complex. Additionally Q 6 and late stage Q biosynthetic intermediates were also found to co-purify with the complex. A mitochondrial protein of unknown function, encoded by the YLR290C open reading frame, is also identified as a constituent of the complex and is shown to be required for efficient de novo Q biosynthesis. Finally, given its effect on Q synthesis and its association with the biosynthetic complex, we propose that the open reading frame YLR290C be designated COQ11.« less

Cannabis Use Frequency and Use-Related Impairment among African American and White Users: The Impact of Cannabis Use Motives

PubMed Central

Shah, Sonia M.; Dean, Kimberlye E.; Zvolensky, Michael J.

2015-01-01

Objectives Cannabis use motives are differentially related to cannabis-related impairment and coping motives appear to have the strongest relation to use-related impairment. However, it is currently unknown whether African American individuals differ from White persons in reasons for using cannabis. It is also unknown whether motives’ relations to cannabis use and related impairment vary as a function of race. The present study examined the role of race on cannabis use motives and tested whether motives’ relations with cannabis use and related impairment differed by race. Design The sample consisted of 111 (67.6% non-Hispanic White, 32.4% African American) current cannabis-using adults. Results African American participants did not significantly differ from White participants on cannabis use frequency or use-related impairment. African American participants endorsed more social motives than White participants. Race interacted with social, coping, and conformity motives to predict cannabis-related impairment such that these motives were positively related to cannabis impairment among African American, but not White, participants. Conclusion Although African American and White participants do not differ in their cannabis use frequency or cannabis-related impairment, they appear to use cannabis for different reasons. Further, conformity, coping, and social motives were differentially associated with cannabis-related impairment as a function of race. Findings suggest motives for cannabis use should be contexualized in the context of race. PMID:26264291

The Protein Interactome of Mycobacteriophage Giles Predicts Functions for Unknown Proteins.

PubMed

Mehla, Jitender; Dedrick, Rebekah M; Caufield, J Harry; Siefring, Rachel; Mair, Megan; Johnson, Allison; Hatfull, Graham F; Uetz, Peter

2015-08-01

Mycobacteriophages are viruses that infect mycobacterial hosts and are prevalent in the environment. Nearly 700 mycobacteriophage genomes have been completely sequenced, revealing considerable diversity and genetic novelty. Here, we have determined the protein complement of mycobacteriophage Giles by mass spectrometry and mapped its genome-wide protein interactome to help elucidate the roles of its 77 predicted proteins, 50% of which have no known function. About 22,000 individual yeast two-hybrid (Y2H) tests with four different Y2H vectors, followed by filtering and retest screens, resulted in 324 reproducible protein-protein interactions, including 171 (136 nonredundant) high-confidence interactions. The complete set of high-confidence interactions among Giles proteins reveals new mechanistic details and predicts functions for unknown proteins. The Giles interactome is the first for any mycobacteriophage and one of just five known phage interactomes so far. Our results will help in understanding mycobacteriophage biology and aid in development of new genetic and therapeutic tools to understand Mycobacterium tuberculosis. Mycobacterium tuberculosis causes over 9 million new cases of tuberculosis each year. Mycobacteriophages, viruses of mycobacterial hosts, hold considerable potential to understand phage diversity, evolution, and mycobacterial biology, aiding in the development of therapeutic tools to control mycobacterial infections. The mycobacteriophage Giles protein-protein interaction network allows us to predict functions for unknown proteins and shed light on major biological processes in phage biology. For example, Giles gp76, a protein of unknown function, is found to associate with phage packaging and maturation. The functions of mycobacteriophage-derived proteins may suggest novel therapeutic approaches for tuberculosis. Our ORFeome clone set of Giles proteins and the interactome data will be useful resources for phage interactomics. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Adaptive backstepping fault-tolerant control for flexible spacecraft with unknown bounded disturbances and actuator failures.

PubMed

Jiang, Ye; Hu, Qinglei; Ma, Guangfu

2010-01-01

In this paper, a robust adaptive fault-tolerant control approach to attitude tracking of flexible spacecraft is proposed for use in situations when there are reaction wheel/actuator failures, persistent bounded disturbances and unknown inertia parameter uncertainties. The controller is designed based on an adaptive backstepping sliding mode control scheme, and a sufficient condition under which this control law can render the system semi-globally input-to-state stable is also provided such that the closed-loop system is robust with respect to any disturbance within a quantifiable restriction on the amplitude, as well as the set of initial conditions, if the control gains are designed appropriately. Moreover, in the design, the control law does not need a fault detection and isolation mechanism even if the failure time instants, patterns and values on actuator failures are also unknown for the designers, as motivated from a practical spacecraft control application. In addition to detailed derivations of the new controller design and a rigorous sketch of all the associated stability and attitude error convergence proofs, illustrative simulation results of an application to flexible spacecraft show that high precise attitude control and vibration suppression are successfully achieved using various scenarios of controlling effective failures. 2009. Published by Elsevier Ltd.

Slope Estimation in Noisy Piecewise Linear Functions.

PubMed

Ingle, Atul; Bucklew, James; Sethares, William; Varghese, Tomy

2015-03-01

This paper discusses the development of a slope estimation algorithm called MAPSlope for piecewise linear data that is corrupted by Gaussian noise. The number and locations of slope change points (also known as breakpoints) are assumed to be unknown a priori though it is assumed that the possible range of slope values lies within known bounds. A stochastic hidden Markov model that is general enough to encompass real world sources of piecewise linear data is used to model the transitions between slope values and the problem of slope estimation is addressed using a Bayesian maximum a posteriori approach. The set of possible slope values is discretized, enabling the design of a dynamic programming algorithm for posterior density maximization. Numerical simulations are used to justify choice of a reasonable number of quantization levels and also to analyze mean squared error performance of the proposed algorithm. An alternating maximization algorithm is proposed for estimation of unknown model parameters and a convergence result for the method is provided. Finally, results using data from political science, finance and medical imaging applications are presented to demonstrate the practical utility of this procedure.

Adaptive control of nonlinear uncertain active suspension systems with prescribed performance.

PubMed

Huang, Yingbo; Na, Jing; Wu, Xing; Liu, Xiaoqin; Guo, Yu

2015-01-01

This paper proposes adaptive control designs for vehicle active suspension systems with unknown nonlinear dynamics (e.g., nonlinear spring and piece-wise linear damper dynamics). An adaptive control is first proposed to stabilize the vertical vehicle displacement and thus to improve the ride comfort and to guarantee other suspension requirements (e.g., road holding and suspension space limitation) concerning the vehicle safety and mechanical constraints. An augmented neural network is developed to online compensate for the unknown nonlinearities, and a novel adaptive law is developed to estimate both NN weights and uncertain model parameters (e.g., sprung mass), where the parameter estimation error is used as a leakage term superimposed on the classical adaptations. To further improve the control performance and simplify the parameter tuning, a prescribed performance function (PPF) characterizing the error convergence rate, maximum overshoot and steady-state error is used to propose another adaptive control. The stability for the closed-loop system is proved and particular performance requirements are analyzed. Simulations are included to illustrate the effectiveness of the proposed control schemes. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal shutdown management

NASA Astrophysics Data System (ADS)

Bottasso, C. L.; Croce, A.; Riboldi, C. E. D.

2014-06-01

The paper presents a novel approach for the synthesis of the open-loop pitch profile during emergency shutdowns. The problem is of interest in the design of wind turbines, as such maneuvers often generate design driving loads on some of the machine components. The pitch profile synthesis is formulated as a constrained optimal control problem, solved numerically using a direct single shooting approach. A cost function expressing a compromise between load reduction and rotor overspeed is minimized with respect to the unknown blade pitch profile. Constraints may include a load reduction not-to-exceed the next dominating loads, a not-to-be-exceeded maximum rotor speed, and a maximum achievable blade pitch rate. Cost function and constraints are computed over a possibly large number of operating conditions, defined so as to cover as well as possible the operating situations encountered in the lifetime of the machine. All such conditions are simulated by using a high-fidelity aeroservoelastic model of the wind turbine, ensuring the accuracy of the evaluation of all relevant parameters. The paper demonstrates the capabilities of the novel proposed formulation, by optimizing the pitch profile of a multi-MW wind turbine. Results show that the procedure can reliably identify optimal pitch profiles that reduce design-driving loads, in a fully automated way.

NIR Color vs Launch Date: A 20-year Analysis of Space Weathering Effects on the Boeing 376 Spacecraft

NASA Astrophysics Data System (ADS)

Frith, J.; Anz-Meador, P.; Lederer, S.; Cowardin, H.; Buckalew, B.

The Boeing HS-376 spin stabilized spacecraft was a popular design that was launched continuously into geosynchronous orbit starting in 1980 with the last launch occurring in 2002. Over 50 of the HS-376 buses were produced to fulfill a variety of different communication missions for countries all over the world. The design of the bus is easily approximated as a telescoping cylinder that is covered with solar cells and an Earth facing antenna that is despun at the top of the cylinder. The similarity in design and the number of spacecraft launched over a long period of time make the HS-376 a prime target for studying the effects of solar weathering on solar panels as a function of time. A selection of primarily non-operational HS-376 spacecraft launched over a 20 year time period were observed using the United Kingdom Infrared Telescope on Mauna Kea and multi-band near-infrared photometry produced. Each spacecraft was observed for an entire night cycling through ZYJHK filters and time-varying colors produced to compare near-infrared color as a function of launch date. The resulting analysis shown here may help in the future to set launch date constraints on the parent object of unidentified debris objects or other unknown spacecraft.

NIR Color vs Launch Date: A 20-Year Analysis of Space Weathering Effects on the Boeing 376 Spacecraft

NASA Technical Reports Server (NTRS)

Frith, James; Anz-Meador, Philip; Lederer, Sue; Cowardin, Heather; Buckalew, Brent

2015-01-01

The Boeing HS-376 spin stabilized spacecraft was a popular design that was launched continuously into geosynchronous orbit starting in 1980 with the last launch occurring in 2002. Over 50 of the HS-376 buses were produced to fulfill a variety of different communication missions for countries all over the world. The design of the bus is easily approximated as a telescoping cylinder that is covered with solar cells and an Earth facing antenna that is despun at the top of the cylinder. The similarity in design and the number of spacecraft launched over a long period of time make the HS-376 a prime target for studying the effects of solar weathering on solar panels as a function of time. A selection of primarily non-operational HS-376 spacecraft launched over a 20 year time period were observed using the United Kingdom Infrared Telescope on Mauna Kea and multi-band near-infrared photometry produced. Each spacecraft was observed for an entire night cycling through ZYJHK filters and time-varying colors produced to compare near-infrared color as a function of launch date. The resulting analysis shown here may help in the future to set launch date constraints on the parent object of unidentified debris objects or other unknown spacecraft.

Data-based virtual unmodeled dynamics driven multivariable nonlinear adaptive switching control.

PubMed

Chai, Tianyou; Zhang, Yajun; Wang, Hong; Su, Chun-Yi; Sun, Jing

2011-12-01

For a complex industrial system, its multivariable and nonlinear nature generally make it very difficult, if not impossible, to obtain an accurate model, especially when the model structure is unknown. The control of this class of complex systems is difficult to handle by the traditional controller designs around their operating points. This paper, however, explores the concepts of controller-driven model and virtual unmodeled dynamics to propose a new design framework. The design consists of two controllers with distinct functions. First, using input and output data, a self-tuning controller is constructed based on a linear controller-driven model. Then the output signals of the controller-driven model are compared with the true outputs of the system to produce so-called virtual unmodeled dynamics. Based on the compensator of the virtual unmodeled dynamics, the second controller based on a nonlinear controller-driven model is proposed. Those two controllers are integrated by an adaptive switching control algorithm to take advantage of their complementary features: one offers stabilization function and another provides improved performance. The conditions on the stability and convergence of the closed-loop system are analyzed. Both simulation and experimental tests on a heavily coupled nonlinear twin-tank system are carried out to confirm the effectiveness of the proposed method.

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

NASA Astrophysics Data System (ADS)

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

2017-10-01

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

Endoscopic versus open radial artery harvest and mammario-radial versus aorto-radial grafting in patients undergoing coronary artery bypass surgery: protocol for the 2 × 2 factorial designed randomised NEO trial

PubMed Central

2014-01-01

Background Coronary artery bypass grafting using the radial artery has, since the 1990s, gone through a revival. Observational studies have indicated better long-term patency when using radial arteries. Therefore, radial artery might be preferred especially in younger patients where long time patency is important. During the last 10 years different endoscopic techniques to harvest the radial artery have evolved. Endoscopic radial artery harvest only requires a small incision near the wrist in contrast to open harvest, which requires an incision from the elbow to the wrist. However, it is unknown whether the endoscopic technique results in fewer complications or a graft patency comparable to open harvest. When the radial artery has been harvested, there are two ways to use the radial artery as a graft. One way is sewing it onto the aorta and another is sewing it onto the mammary artery. It is unknown which technique is the superior revascularisation technique. Methods/Design The NEO Trial is a randomised clinical trial with a 2 × 2 factorial design. We plan to randomise 300 participants into four intervention groups: (1) mammario-radial endoscopic group; (2) aorto-radial endoscopic group; (3) mammario-radial open surgery group; and (4) aorto-radial open surgery group. The hand function will be assessed by a questionnaire, a clinical examination, the change in cutaneous sensibility, and the measurement of both sensory and motor nerve conduction velocity at 3 months postoperatively. All the postoperative complications will be registered, and we will evaluate muscular function, scar appearance, vascular supply to the hand, and the graft patency including the patency of the central radial artery anastomosis. A patency evaluation by multi-slice computer tomography will be done at one year postoperatively. We expect the nerve conduction studies and the standardised neurological examinations to be able to discriminate differences in hand function comparing endoscopic to open harvest of the radial artery. The trial also aims to show if there is any patency difference between mammario-radial compared to aorto-radial revascularisation techniques but this objective is exploratory. Trial registration ClinicalTrials.gov identifier: NCT01848886. Danish Ethics committee number: H-3-2012-116. Danish Data Protection Agency: 2007-58-0015/jr.n:30–0838. PMID:24754891

5. VIEW EAST, height finder radar towers, radar tower (unknown ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

5. VIEW EAST, height finder radar towers, radar tower (unknown function), prime search radar tower, operations building, and central heating plant - Fort Custer Military Reservation, P-67 Radar Station, .25 mile north of Dickman Road, east of Clark Road, Battle Creek, Calhoun County, MI

Using NMR spectroscopy to elucidate the role of molecular motions in enzyme function.

PubMed

Lisi, George P; Loria, J Patrick

2016-02-01

Conformational motions play an essential role in enzyme function, often facilitating the formation of enzyme-substrate complexes and/or product release. Although considerable debate remains regarding the role of molecular motions in the conversion of enzymatic substrates to products, numerous examples have found motions to be crucial for optimization of enzyme scaffolds, effective substrate binding, and product dissociation. Conformational fluctuations are often rate-limiting to enzyme catalysis, primarily through product release, with the chemical reaction occurring much more quickly. As a result, the direct involvement of motions at various stages along the enzyme reaction coordinate remains largely unknown and untested. In the following review, we describe the use of solution NMR techniques designed to probe various timescales of molecular motions and detail examples in which motions play a role in propagating catalytic effects from the active site and directly participate in essential aspects of enzyme function. Copyright © 2015 Elsevier B.V. All rights reserved.

Quantization-Based Adaptive Actor-Critic Tracking Control With Tracking Error Constraints.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong; Ye, Dan

2018-04-01

In this paper, the problem of adaptive actor-critic (AC) tracking control is investigated for a class of continuous-time nonlinear systems with unknown nonlinearities and quantized inputs. Different from the existing results based on reinforcement learning, the tracking error constraints are considered and new critic functions are constructed to improve the performance further. To ensure that the tracking errors keep within the predefined time-varying boundaries, a tracking error transformation technique is used to constitute an augmented error system. Specific critic functions, rather than the long-term cost function, are introduced to supervise the tracking performance and tune the weights of the AC neural networks (NNs). A novel adaptive controller with a special structure is designed to reduce the effect of the NN reconstruction errors, input quantization, and disturbances. Based on the Lyapunov stability theory, the boundedness of the closed-loop signals and the desired tracking performance can be guaranteed. Finally, simulations on two connected inverted pendulums are given to illustrate the effectiveness of the proposed method.

Biomechanical forces in the skeleton and their relevance to bone metastasis: biology and engineering considerations.

PubMed

Lynch, Maureen E; Fischbach, Claudia

2014-12-15

Bone metastasis represents the leading cause of breast cancer related-deaths. However, the effect of skeleton-associated biomechanical signals on the initiation, progression, and therapy response of breast cancer bone metastasis is largely unknown. This review seeks to highlight possible functional connections between skeletal mechanical signals and breast cancer bone metastasis and their contribution to clinical outcome. It provides an introduction to the physical and biological signals underlying bone functional adaptation and discusses the modulatory roles of mechanical loading and breast cancer metastasis in this process. Following a definition of biophysical design criteria, in vitro and in vivo approaches from the fields of bone biomechanics and tissue engineering that may be suitable to investigate breast cancer bone metastasis as a function of varied mechano-signaling will be reviewed. Finally, an outlook of future opportunities and challenges associated with this newly emerging field will be provided. Copyright © 2014 Elsevier B.V. All rights reserved.

Improved prescribed performance control for air-breathing hypersonic vehicles with unknown deadzone input nonlinearity.

PubMed

Wang, Yingyang; Hu, Jianbo

2018-05-19

An improved prescribed performance controller is proposed for the longitudinal model of an air-breathing hypersonic vehicle (AHV) subject to uncertain dynamics and input nonlinearity. Different from the traditional non-affine model requiring non-affine functions to be differentiable, this paper utilizes a semi-decomposed non-affine model with non-affine functions being locally semi-bounded and possibly in-differentiable. A new error transformation combined with novel prescribed performance functions is proposed to bypass complex deductions caused by conventional error constraint approaches and circumvent high frequency chattering in control inputs. On the basis of backstepping technique, the improved prescribed performance controller with low structural and computational complexity is designed. The methodology guarantees the altitude and velocity tracking error within transient and steady state performance envelopes and presents excellent robustness against uncertain dynamics and deadzone input nonlinearity. Simulation results demonstrate the efficacy of the proposed method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments

PubMed Central

Yan, Zheping; Li, Jiyun; Zhang, Gengshi; Wu, Yi

2018-01-01

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle’s irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal. PMID:29393915

A Real-Time Reaction Obstacle Avoidance Algorithm for Autonomous Underwater Vehicles in Unknown Environments.

PubMed

Yan, Zheping; Li, Jiyun; Zhang, Gengshi; Wu, Yi

2018-02-02

A novel real-time reaction obstacle avoidance algorithm (RRA) is proposed for autonomous underwater vehicles (AUVs) that must adapt to unknown complex terrains, based on forward looking sonar (FLS). To accomplish this algorithm, obstacle avoidance rules are planned, and the RRA processes are split into five steps Introduction only lists 4 so AUVs can rapidly respond to various environment obstacles. The largest polar angle algorithm (LPAA) is designed to change detected obstacle's irregular outline into a convex polygon, which simplifies the obstacle avoidance process. A solution is designed to solve the trapping problem existing in U-shape obstacle avoidance by an outline memory algorithm. Finally, simulations in three unknown obstacle scenes are carried out to demonstrate the performance of this algorithm, where the obtained obstacle avoidance trajectories are safety, smooth and near-optimal.

An Alternative to the Physiological Psychology Laboratory: Identification of an Unknown Drug Through Behavioral Testing.

ERIC Educational Resources Information Center

Schumacher, Susan J.

1982-01-01

A laboratory project introduced physiological psychology students to research by requiring them to identify an unknown drug given to laboratory animals. Students read material about drugs and animal drug studies, designed behavioral tests, constructed the testing apparatus, conducted the tests, and wrote progress reports. (SR)

The challenge of annotating protein sequences: The tale of eight domains of unknown function in Pfam.

PubMed

Goonesekere, Nalin C W; Shipely, Krysten; O'Connor, Kevin

2010-06-01

The Pfam database is an important tool in genome annotation, since it provides a collection of curated protein families. However, a subset of these families, known as domains of unknown function (DUFs), remains poorly characterized. We have related sequences from DUF404, DUF407, DUF482, DUF608, DUF810, DUF853, DUF976 and DUF1111 to homologs in PDB, within the midnight zone (9-20%) of sequence identity. These relationships were extended to provide functional annotation by sequence analysis and model building. Also described are examples of residue plasticity within enzyme active sites, and change of function within homologous sequences of a DUF. Copyright 2010 Elsevier Ltd. All rights reserved.

Design and Analysis of a Petri Net Model of the Von Hippel-Lindau (VHL) Tumor Suppressor Interaction Network

PubMed Central

Minervini, Giovanni; Panizzoni, Elisabetta; Giollo, Manuel; Masiero, Alessandro; Ferrari, Carlo; Tosatto, Silvio C. E.

2014-01-01

Von Hippel-Lindau (VHL) syndrome is a hereditary condition predisposing to the development of different cancer forms, related to germline inactivation of the homonymous tumor suppressor pVHL. The best characterized function of pVHL is the ubiquitination dependent degradation of Hypoxia Inducible Factor (HIF) via the proteasome. It is also involved in several cellular pathways acting as a molecular hub and interacting with more than 200 different proteins. Molecular details of pVHL plasticity remain in large part unknown. Here, we present a novel manually curated Petri Net (PN) model of the main pVHL functional pathways. The model was built using functional information derived from the literature. It includes all major pVHL functions and is able to credibly reproduce VHL syndrome at the molecular level. The reliability of the PN model also allowed in silico knockout experiments, driven by previous model analysis. Interestingly, PN analysis suggests that the variability of different VHL manifestations is correlated with the concomitant inactivation of different metabolic pathways. PMID:24886840

Design and analysis of a Petri net model of the Von Hippel-Lindau (VHL) tumor suppressor interaction network.

PubMed

Minervini, Giovanni; Panizzoni, Elisabetta; Giollo, Manuel; Masiero, Alessandro; Ferrari, Carlo; Tosatto, Silvio C E

2014-01-01

Von Hippel-Lindau (VHL) syndrome is a hereditary condition predisposing to the development of different cancer forms, related to germline inactivation of the homonymous tumor suppressor pVHL. The best characterized function of pVHL is the ubiquitination dependent degradation of Hypoxia Inducible Factor (HIF) via the proteasome. It is also involved in several cellular pathways acting as a molecular hub and interacting with more than 200 different proteins. Molecular details of pVHL plasticity remain in large part unknown. Here, we present a novel manually curated Petri Net (PN) model of the main pVHL functional pathways. The model was built using functional information derived from the literature. It includes all major pVHL functions and is able to credibly reproduce VHL syndrome at the molecular level. The reliability of the PN model also allowed in silico knockout experiments, driven by previous model analysis. Interestingly, PN analysis suggests that the variability of different VHL manifestations is correlated with the concomitant inactivation of different metabolic pathways.

Experimental Design for Estimating Unknown Hydraulic Conductivity in a Confined Aquifer using a Genetic Algorithm and a Reduced Order Model

NASA Astrophysics Data System (ADS)

Ushijima, T.; Yeh, W.

2013-12-01

An optimal experimental design algorithm is developed to select locations for a network of observation wells that provides the maximum information about unknown hydraulic conductivity in a confined, anisotropic aquifer. The design employs a maximal information criterion that chooses, among competing designs, the design that maximizes the sum of squared sensitivities while conforming to specified design constraints. Because that the formulated problem is non-convex and contains integer variables (necessitating a combinatorial search), for a realistically-scaled model, the problem may be difficult, if not impossible, to solve through traditional mathematical programming techniques. Genetic Algorithms (GAs) are designed to search out the global optimum; however because a GA requires a large number of calls to a groundwater model, the formulated optimization problem may still be infeasible to solve. To overcome this, Proper Orthogonal Decomposition (POD) is applied to the groundwater model to reduce its dimension. The information matrix in the full model space can then be searched without solving the full model.

Variational formulation of hybrid problems for fully 3-D transonic flow with shocks in rotor

NASA Technical Reports Server (NTRS)

Liu, Gao-Lian

1991-01-01

Based on previous research, the unified variable domain variational theory of hybrid problems for rotor flow is extended to fully 3-D transonic rotor flow with shocks, unifying and generalizing the direct and inverse problems. Three variational principles (VP) families were established. All unknown boundaries and flow discontinuities (such as shocks, free trailing vortex sheets) are successfully handled via functional variations with variable domain, converting almost all boundary and interface conditions, including the Rankine Hugoniot shock relations, into natural ones. This theory provides a series of novel ways for blade design or modification and a rigorous theoretical basis for finite element applications and also constitutes an important part of the optimal design theory of rotor bladings. Numerical solutions to subsonic flow by finite elements with self-adapting nodes given in Refs., show good agreement with experimental results.

Robust Fuzzy Logic Stabilization with Disturbance Elimination

PubMed Central

Danapalasingam, Kumeresan A.

2014-01-01

A robust fuzzy logic controller is proposed for stabilization and disturbance rejection in nonlinear control systems of a particular type. The dynamic feedback controller is designed as a combination of a control law that compensates for nonlinear terms in a control system and a dynamic fuzzy logic controller that addresses unknown model uncertainties and an unmeasured disturbance. Since it is challenging to derive a highly accurate mathematical model, the proposed controller requires only nominal functions of a control system. In this paper, a mathematical derivation is carried out to prove that the controller is able to achieve asymptotic stability by processing state measurements. Robustness here refers to the ability of the controller to asymptotically steer the state vector towards the origin in the presence of model uncertainties and a disturbance input. Simulation results of the robust fuzzy logic controller application in a magnetic levitation system demonstrate the feasibility of the control design. PMID:25177713

Experimental Design and Bioinformatics Analysis for the Application of Metagenomics in Environmental Sciences and Biotechnology.

PubMed

Ju, Feng; Zhang, Tong

2015-11-03

Recent advances in DNA sequencing technologies have prompted the widespread application of metagenomics for the investigation of novel bioresources (e.g., industrial enzymes and bioactive molecules) and unknown biohazards (e.g., pathogens and antibiotic resistance genes) in natural and engineered microbial systems across multiple disciplines. This review discusses the rigorous experimental design and sample preparation in the context of applying metagenomics in environmental sciences and biotechnology. Moreover, this review summarizes the principles, methodologies, and state-of-the-art bioinformatics procedures, tools and database resources for metagenomics applications and discusses two popular strategies (analysis of unassembled reads versus assembled contigs/draft genomes) for quantitative or qualitative insights of microbial community structure and functions. Overall, this review aims to facilitate more extensive application of metagenomics in the investigation of uncultured microorganisms, novel enzymes, microbe-environment interactions, and biohazards in biotechnological applications where microbial communities are engineered for bioenergy production, wastewater treatment, and bioremediation.

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

Kato, Go

We consider the situation where s replicas of a qubit with an unknown state and its orthogonal k replicas are given as an input, and we try to make c clones of the qubit with the unknown state. As a function of s, k, and c, we obtain the optimal fidelity between the qubit with an unknown state and the clone by explicitly giving a completely positive trace-preserving (CPTP) map that represents a cloning machine. We discuss dependency of the fidelity on the values of the parameters s, k, and c.

Adaptive Incentive Controls for Stackelberg Games with Unknown Cost Functionals.

DTIC Science & Technology

1984-01-01

APR EZT:: F I AN 73S e OsL:-: UNCLASSI?:-- Q4~.’~- .A.., 6, *~*i i~~*~~*.- U ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH UNKNOWN COST...AD-A161 885 ADAPTIVE INCENTIVE CONTROLS FOR STACKELBERG GAMES WITH i/1 UNKNOWN COST FUNCTIONALSCU) ILLINOIS UNIV AT URBANA DECISION AND CONTROL LAB T...ORGANIZATION 6b. OFFICE SYMBOL 7.. NAME OF MONITORING ORGANIZATION CoriaeLcenef~pda~ Joint Services Electronics Program Laboratory, Univ. of Illinois N/A

Direct Adaptive Control of Systems with Actuator Failures: State of the Art and Continuing Challenges

NASA Technical Reports Server (NTRS)

Tao, Gang; Joshi, Suresh M.

2008-01-01

In this paper, the problem of controlling systems with failures and faults is introduced, and an overview of recent work on direct adaptive control for compensation of uncertain actuator failures is presented. Actuator failures may be characterized by some unknown system inputs being stuck at some unknown (fixed or varying) values at unknown time instants, that cannot be influenced by the control signals. The key task of adaptive compensation is to design the control signals in such a manner that the remaining actuators can automatically and seamlessly take over for the failed ones, and achieve desired stability and asymptotic tracking. A certain degree of redundancy is necessary to accomplish failure compensation. The objective of adaptive control design is to effectively use the available actuation redundancy to handle failures without the knowledge of the failure patterns, parameters, and time of occurrence. This is a challenging problem because failures introduce large uncertainties in the dynamic structure of the system, in addition to parametric uncertainties and unknown disturbances. The paper addresses some theoretical issues in adaptive actuator failure compensation: actuator failure modeling, redundant actuation requirements, plant-model matching, error system dynamics, adaptation laws, and stability, tracking, and performance analysis. Adaptive control designs can be shown to effectively handle uncertain actuator failures without explicit failure detection. Some open technical challenges and research problems in this important research area are discussed.

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights.

PubMed

Luo, Shaohua; Wu, Songli; Gao, Ruizhen

2015-07-01

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in the closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.

Chaos control of the brushless direct current motor using adaptive dynamic surface control based on neural network with the minimum weights

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

Luo, Shaohua; Department of Mechanical Engineering, Chongqing Aerospace Polytechnic, Chongqing, 400021; Wu, Songli

2015-07-15

This paper investigates chaos control for the brushless DC motor (BLDCM) system by adaptive dynamic surface approach based on neural network with the minimum weights. The BLDCM system contains parameter perturbation, chaotic behavior, and uncertainty. With the help of radial basis function (RBF) neural network to approximate the unknown nonlinear functions, the adaptive law is established to overcome uncertainty of the control gain. By introducing the RBF neural network and adaptive technology into the dynamic surface control design, a robust chaos control scheme is developed. It is proved that the proposed control approach can guarantee that all signals in themore » closed-loop system are globally uniformly bounded, and the tracking error converges to a small neighborhood of the origin. Simulation results are provided to show that the proposed approach works well in suppressing chaos and parameter perturbation.« less

Adaptive Neural Control of Uncertain MIMO Nonlinear Systems With State and Input Constraints.

PubMed

Chen, Ziting; Li, Zhijun; Chen, C L Philip

2017-06-01

An adaptive neural control strategy for multiple input multiple output nonlinear systems with various constraints is presented in this paper. To deal with the nonsymmetric input nonlinearity and the constrained states, the proposed adaptive neural control is combined with the backstepping method, radial basis function neural network, barrier Lyapunov function (BLF), and disturbance observer. By ensuring the boundedness of the BLF of the closed-loop system, it is demonstrated that the output tracking is achieved with all states remaining in the constraint sets and the general assumption on nonsingularity of unknown control coefficient matrices has been eliminated. The constructed adaptive neural control has been rigorously proved that it can guarantee the semiglobally uniformly ultimate boundedness of all signals in the closed-loop system. Finally, the simulation studies on a 2-DOF robotic manipulator system indicate that the designed adaptive control is effective.

Robustness of composite pulse sequences to time-dependent noise

NASA Astrophysics Data System (ADS)

Kabytayev, Chingiz; Green, Todd J.; Khodjasteh, Kaveh; Viola, Lorenza; Biercuk, Michael J.; Brown, Kenneth R.

2014-03-01

Quantum control protocols can minimize the effect of noise sources that reduce the quality of quantum operations. Originally developed for NMR, composite pulse sequences correct for unknown static control errors . We study these compensating pulses in the general case of time-varying Gaussian control noise using a filter-function approach and detailed numerics. Three different noise models were considered in this work: amplitude noise, detuning noise and simultaneous presence of both noises. Pulse sequences are shown to be robust to noise up to frequencies as high as ~10% of the Rabi frequency. Robustness of pulses designed for amplitude noise is explained using a geometric picture that naturally follows from filter function. We also discuss future directions including new pulses correcting for noise of certain frequency. True J. Merrill and Kenneth R. Brown. arXiv:1203.6392v1. In press Adv. Chem. Phys. (2013)

Form Follows Function: Learning about Function Helps Children Learn about Shape

ERIC Educational Resources Information Center

Ware, Elizabeth A.; Booth, Amy E.

2010-01-01

Object functions help young children to organize new artifact categories. However, the scope of their influence is unknown. We explore whether functions highlight property dimensions that are relevant to artifact categories in general. Specifically, using a longitudinal training procedure, we assessed whether experience with functions highlights…

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

PubMed

Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

2017-12-06

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Using Conductivity Measurements to Determine the Identities and Concentrations of Unknown Acids: An Inquiry Laboratory Experiment

ERIC Educational Resources Information Center

Smith, K. Christopher; Garza, Ariana

2015-01-01

This paper describes a student designed experiment using titrations involving conductivity measurements to identify unknown acids as being either HCl or H[subscript 2]SO[subscript 4], and to determine the concentrations of the acids, thereby improving the utility of standard acid-base titrations. Using an inquiry context, students gain experience…

Convergence Rates for Multivariate Smoothing Spline Functions.

DTIC Science & Technology

1982-10-01

GAI (,T) g (T)dT - g In order to show convergence of the series and obtain bounds on the terms, we need to estimate £ Now (1 + Ay v) AyV ( g ,#V...Cox* Technical Summary Report #2437 October 1982 ABSTRACT Given data z i - g (ti ) + ci, 1 4 i 4 n, where g is the unknown function, the ti are unknown...d-dimensional variables in a domain fl, and the ei are i.i.d. random errors, the smoothing spline estimate g n is defined to be the

Market-Based Coordination of Thermostatically Controlled Loads—Part II: Unknown Parameters and Case Studies

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

Li, Sen; Zhang, Wei; Lian, Jianming

This two-part paper considers the coordination of a population of Thermostatically Controlled Loads (TCLs) with unknown parameters to achieve group objectives. The problem involves designing the bidding and market clearing strategy to motivate self-interested users to realize efficient energy allocation subject to a peak power constraint. The companion paper (Part I) formulates the problem and proposes a load coordination framework using the mechanism design approach. To address the unknown parameters, Part II of this paper presents a joint state and parameter estimation framework based on the expectation maximization algorithm. The overall framework is then validated using real-world weather data andmore » price data, and is compared with other approaches in terms of aggregated power response. Simulation results indicate that our coordination framework can effectively improve the efficiency of the power grid operations and reduce power congestion at key times.« less

Development of a GC/Quadrupole-Orbitrap Mass Spectrometer, Part I: Design and Characterization

PubMed Central

2015-01-01

Identification of unknown compounds is of critical importance in GC/MS applications (metabolomics, environmental toxin identification, sports doping, petroleomics, and biofuel analysis, among many others) and remains a technological challenge. Derivation of elemental composition is the first step to determining the identity of an unknown compound by MS, for which high accuracy mass and isotopomer distribution measurements are critical. Here, we report on the development of a dedicated, applications-grade GC/MS employing an Orbitrap mass analyzer, the GC/Quadrupole-Orbitrap. Built from the basis of the benchtop Orbitrap LC/MS, the GC/Quadrupole-Orbitrap maintains the performance characteristics of the Orbitrap, enables quadrupole-based isolation for sensitive analyte detection, and includes numerous analysis modalities to facilitate structural elucidation. We detail the design and construction of the instrument, discuss its key figures-of-merit, and demonstrate its performance for the characterization of unknown compounds and environmental toxins. PMID:25208235

Paralimbic system and striatum are involved in motivational behavior.

PubMed

Nishimura, Masahiko; Yoshii, Yoshihiko; Watanabe, Jobu; Ishiuchi, Shogo

2009-10-28

Goal-directed rewarded behavior and goal-directed non-rewarded behavior are concerned with motivation. However, the neural substrates involved in goal-directed non-rewarded behaviors are unknown. Using functional magnetic resonance imaging, we investigated the brain activities of healthy individuals during a novel tool use (turning a screwdriver) to elucidate the relationship between the brain mechanism relevant to goal-directed non-rewarded behavior and motivation. We found that our designed behavioral task evoked activities in the orbitofrontal cortex, striatum, anterior insula, lateral prefrontal cortex, and anterior cingulate cortex compared with a meaningless task. These results suggest that activation in these cerebral regions play important roles in motivational behavior without tangible rewards.

Identification and sequence determination of a new chrysovirus infecting the entomopathogenic fungus Isaria javanica.

PubMed

Herrero, Noemi

2017-04-01

A new double-stranded RNA (dsRNA) mycovirus has been identified in the isolate NB IFR-19 of the entomopathogenic fungus Isaria javanica. Isaria javanica chrysovirus-1 (IjCV-1) constitutes a new member of the Chrysoviridae family, and its genome is made up of four dsRNA elements designated dsRNA1, 2, 3 and 4 from largest to smallest. dsRNA1 and dsRNA2 encode an RNA-dependent RNA polymerase (RdRp) and a coat protein (CP), respectively. dsRNA3 and 4 encode hypothetical proteins of unknown function. IjCV-1 constitutes the first report of a chrysovirus infecting the entomopathogenic fungus Isaria javanica.

Parametric system identification of catamaran for improving controller design

NASA Astrophysics Data System (ADS)

Timpitak, Surasak; Prempraneerach, Pradya; Pengwang, Eakkachai

2018-01-01

This paper presents an estimation of simplified dynamic model for only surge- and yaw- motions of catamaran by using system identification (SI) techniques to determine associated unknown parameters. These methods will enhance the performance of designing processes for the motion control system of Unmanned Surface Vehicle (USV). The simulation results demonstrate an effective way to solve for damping forces and to determine added masses by applying least-square and AutoRegressive Exogenous (ARX) methods. Both methods are then evaluated according to estimated parametric errors from the vehicle’s dynamic model. The ARX method, which yields better estimated accuracy, can then be applied to identify unknown parameters as well as to help improving a controller design of a real unmanned catamaran.

Adaptive pattern recognition by mini-max neural networks as a part of an intelligent processor

NASA Technical Reports Server (NTRS)

Szu, Harold H.

1990-01-01

In this decade and progressing into 21st Century, NASA will have missions including Space Station and the Earth related Planet Sciences. To support these missions, a high degree of sophistication in machine automation and an increasing amount of data processing throughput rate are necessary. Meeting these challenges requires intelligent machines, designed to support the necessary automations in a remote space and hazardous environment. There are two approaches to designing these intelligent machines. One of these is the knowledge-based expert system approach, namely AI. The other is a non-rule approach based on parallel and distributed computing for adaptive fault-tolerances, namely Neural or Natural Intelligence (NI). The union of AI and NI is the solution to the problem stated above. The NI segment of this unit extracts features automatically by applying Cauchy simulated annealing to a mini-max cost energy function. The feature discovered by NI can then be passed to the AI system for future processing, and vice versa. This passing increases reliability, for AI can follow the NI formulated algorithm exactly, and can provide the context knowledge base as the constraints of neurocomputing. The mini-max cost function that solves the unknown feature can furthermore give us a top-down architectural design of neural networks by means of Taylor series expansion of the cost function. A typical mini-max cost function consists of the sample variance of each class in the numerator, and separation of the center of each class in the denominator. Thus, when the total cost energy is minimized, the conflicting goals of intraclass clustering and interclass segregation are achieved simultaneously.

Desired Accuracy Estimation of Noise Function from ECG Signal by Fuzzy Approach

PubMed Central

Vahabi, Zahra; Kermani, Saeed

2012-01-01

Unknown noise and artifacts present in medical signals with non-linear fuzzy filter will be estimated and then removed. An adaptive neuro-fuzzy interference system which has a non-linear structure presented for the noise function prediction by before Samples. This paper is about a neuro-fuzzy method to estimate unknown noise of Electrocardiogram signal. Adaptive neural combined with Fuzzy System to construct a fuzzy Predictor. For this system setting parameters such as the number of Membership Functions for each input and output, training epochs, type of MFs for each input and output, learning algorithm and etc. is determined by learning data. At the end simulated experimental results are presented for proper validation. PMID:23717810

The Emergence of an Amplified Mindset of Design: Implications for Postgraduate Design Education

ERIC Educational Resources Information Center

Moreira, Mafalda; Murphy, Emma; McAra-McWilliam, Irene

2016-01-01

In a global scenario of complexity, research shows that emerging design practices are changing and expanding, creating a complex and ambiguous disciplinary landscape. This directly impacts on the field of design education, calling for new, flexible models able to tackle future practitioners' needs, unknown markets and emergent societal cultures.…

Mining high-throughput experimental data to link gene and function.

PubMed

Blaby-Haas, Crysten E; de Crécy-Lagard, Valérie

2011-04-01

Nearly 2200 genomes that encode around 6 million proteins have now been sequenced. Around 40% of these proteins are of unknown function, even when function is loosely and minimally defined as 'belonging to a superfamily'. In addition to in silico methods, the swelling stream of high-throughput experimental data can give valuable clues for linking these unknowns with precise biological roles. The goal is to develop integrative data-mining platforms that allow the scientific community at large to access and utilize this rich source of experimental knowledge. To this end, we review recent advances in generating whole-genome experimental datasets, where this data can be accessed, and how it can be used to drive prediction of gene function. Copyright © 2011 Elsevier Ltd. All rights reserved.

A flexible model for the mean and variance functions, with application to medical cost data.

PubMed

Chen, Jinsong; Liu, Lei; Zhang, Daowen; Shih, Ya-Chen T

2013-10-30

Medical cost data are often skewed to the right and heteroscedastic, having a nonlinear relation with covariates. To tackle these issues, we consider an extension to generalized linear models by assuming nonlinear associations of covariates in the mean function and allowing the variance to be an unknown but smooth function of the mean. We make no further assumption on the distributional form. The unknown functions are described by penalized splines, and the estimation is carried out using nonparametric quasi-likelihood. Simulation studies show the flexibility and advantages of our approach. We apply the model to the annual medical costs of heart failure patients in the clinical data repository at the University of Virginia Hospital System. Copyright © 2013 John Wiley & Sons, Ltd.

FitSearch: a robust way to interpret a yeast fitness profile in terms of drug's mode-of-action.

PubMed

Lee, Minho; Han, Sangjo; Chang, Hyeshik; Kwak, Youn-Sig; Weller, David M; Kim, Dongsup

2013-01-01

Yeast deletion-mutant collections have been successfully used to infer the mode-of-action of drugs especially by profiling chemical-genetic and genetic-genetic interactions on a genome-wide scale. Although tens of thousands of those profiles are publicly available, a lack of an accurate method for mining such data has been a major bottleneck for more widespread use of these useful resources. For general usage of those public resources, we designed FitRankDB as a general repository of fitness profiles, and developed a new search algorithm, FitSearch, for identifying the profiles that have a high similarity score with statistical significance for a given fitness profile. We demonstrated that our new repository and algorithm are highly beneficial to researchers who attempting to make hypotheses based on unknown modes-of-action of bioactive compounds, regardless of the types of experiments that have been performed using yeast deletion-mutant collection in various types of different measurement platforms, especially non-chip-based platforms. We showed that our new database and algorithm are useful when attempting to construct a hypothesis regarding the unknown function of a bioactive compound through small-scale experiments with a yeast deletion collection in a platform independent manner. The FitRankDB and FitSearch enhance the ease of searching public yeast fitness profiles and obtaining insights into unknown mechanisms of action of drugs. FitSearch is freely available at http://fitsearch.kaist.ac.kr.

FitSearch: a robust way to interpret a yeast fitness profile in terms of drug's mode-of-action

PubMed Central

2013-01-01

Background Yeast deletion-mutant collections have been successfully used to infer the mode-of-action of drugs especially by profiling chemical-genetic and genetic-genetic interactions on a genome-wide scale. Although tens of thousands of those profiles are publicly available, a lack of an accurate method for mining such data has been a major bottleneck for more widespread use of these useful resources. Results For general usage of those public resources, we designed FitRankDB as a general repository of fitness profiles, and developed a new search algorithm, FitSearch, for identifying the profiles that have a high similarity score with statistical significance for a given fitness profile. We demonstrated that our new repository and algorithm are highly beneficial to researchers who attempting to make hypotheses based on unknown modes-of-action of bioactive compounds, regardless of the types of experiments that have been performed using yeast deletion-mutant collection in various types of different measurement platforms, especially non-chip-based platforms. Conclusions We showed that our new database and algorithm are useful when attempting to construct a hypothesis regarding the unknown function of a bioactive compound through small-scale experiments with a yeast deletion collection in a platform independent manner. The FitRankDB and FitSearch enhance the ease of searching public yeast fitness profiles and obtaining insights into unknown mechanisms of action of drugs. FitSearch is freely available at http://fitsearch.kaist.ac.kr. PMID:23368702

Rationale and design of the ARCUS: Effects of trAnsRadial perCUtaneouS coronary intervention on upper extremity function.

PubMed

Zwaan, Eva M; IJsselmuiden, Alexander J J; van Rosmalen, Joost; van Geuns, Robert-Jan M; Amoroso, Giovanni; Moerman, Esther; Ritt, Marco J P F; Schreuders, Ton A R; Kofflard, Marcel J M; Holtzer, Carlo A J

2016-12-01

The aim of this study is to provide a complete insight in the access-site morbidity and upper extremity function after Transradial Percutaneous Coronary Intervention (TR-PCI). In percutaneous coronary intervention the Transradial Approach (TRA) is gaining popularity as a default technique. It is a very promising technique with respect to post-procedure complications, but the exact effects of TRA on upper extremity function are unknown. The effects of trAnsRadial perCUtaneouS coronary intervention on upper extremity function (ARCUS) trial is a multicenter prospective cohort study that will be conducted in all patients admitted for TR-PCI. Clinical outcomes will be monitored during a follow-up of 6 months, with its primary endpoint at two weeks of follow-up. To investigate the complete upper extremity function, a combination of physical examinations and validated questionnaires will be used to provide information on anatomical integrity, strength, range of motion (ROM), coordination, sensibility, pain, and functioning in everyday life. Procedural and material specifications will be registered in order to include all possible aspects influencing upper extremity function. Results from this study will elucidate the effect of TR-PCI on upper extremity function. This creates the opportunity to further optimize TR-PCI, to make improvements in functional outcome and to prevent morbidity regarding full upper extremity function. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A continuous optimization approach for inferring parameters in mathematical models of regulatory networks.

PubMed

Deng, Zhimin; Tian, Tianhai

2014-07-29

The advances of systems biology have raised a large number of sophisticated mathematical models for describing the dynamic property of complex biological systems. One of the major steps in developing mathematical models is to estimate unknown parameters of the model based on experimentally measured quantities. However, experimental conditions limit the amount of data that is available for mathematical modelling. The number of unknown parameters in mathematical models may be larger than the number of observation data. The imbalance between the number of experimental data and number of unknown parameters makes reverse-engineering problems particularly challenging. To address the issue of inadequate experimental data, we propose a continuous optimization approach for making reliable inference of model parameters. This approach first uses a spline interpolation to generate continuous functions of system dynamics as well as the first and second order derivatives of continuous functions. The expanded dataset is the basis to infer unknown model parameters using various continuous optimization criteria, including the error of simulation only, error of both simulation and the first derivative, or error of simulation as well as the first and second derivatives. We use three case studies to demonstrate the accuracy and reliability of the proposed new approach. Compared with the corresponding discrete criteria using experimental data at the measurement time points only, numerical results of the ERK kinase activation module show that the continuous absolute-error criteria using both function and high order derivatives generate estimates with better accuracy. This result is also supported by the second and third case studies for the G1/S transition network and the MAP kinase pathway, respectively. This suggests that the continuous absolute-error criteria lead to more accurate estimates than the corresponding discrete criteria. We also study the robustness property of these three models to examine the reliability of estimates. Simulation results show that the models with estimated parameters using continuous fitness functions have better robustness properties than those using the corresponding discrete fitness functions. The inference studies and robustness analysis suggest that the proposed continuous optimization criteria are effective and robust for estimating unknown parameters in mathematical models.

Inferring topologies via driving-based generalized synchronization of two-layer networks

NASA Astrophysics Data System (ADS)

Wang, Yingfei; Wu, Xiaoqun; Feng, Hui; Lu, Jun-an; Xu, Yuhua

2016-05-01

The interaction topology among the constituents of a complex network plays a crucial role in the network’s evolutionary mechanisms and functional behaviors. However, some network topologies are usually unknown or uncertain. Meanwhile, coupling delays are ubiquitous in various man-made and natural networks. Hence, it is necessary to gain knowledge of the whole or partial topology of a complex dynamical network by taking into consideration communication delay. In this paper, topology identification of complex dynamical networks is investigated via generalized synchronization of a two-layer network. Particularly, based on the LaSalle-type invariance principle of stochastic differential delay equations, an adaptive control technique is proposed by constructing an auxiliary layer and designing proper control input and updating laws so that the unknown topology can be recovered upon successful generalized synchronization. Numerical simulations are provided to illustrate the effectiveness of the proposed method. The technique provides a certain theoretical basis for topology inference of complex networks. In particular, when the considered network is composed of systems with high-dimension or complicated dynamics, a simpler response layer can be constructed, which is conducive to circuit design. Moreover, it is practical to take into consideration perturbations caused by control input. Finally, the method is applicable to infer topology of a subnetwork embedded within a complex system and locate hidden sources. We hope the results can provide basic insight into further research endeavors on understanding practical and economical topology inference of networks.

A novel salt-inducible gene SbSI-1 from Salicornia brachiata confers salt and desiccation tolerance in E. coli.

PubMed

Yadav, Narendra Singh; Rashmi, Deo; Singh, Dinkar; Agarwal, Pradeep K; Jha, Bhavanath

2012-02-01

Salicornia brachiata is one of the extreme salt tolerant plants and grows luxuriantly in coastal areas. Previously we have reported isolation and characterization of ESTs from S. brachiata with large number of unknown gene sequences. Reverse Northern analysis showed upregulation and downregulation of few unknown genes in response to salinity. Some of these unknown genes were made full length and their functional analysis is being tested. In this study, we have selected a novel unknown salt inducible gene SbSI-1 (Salicornia brachiata salt inducible-1) for the functional validation. The SbSI-1 (Gen-Bank accession number JF 965339) was made full length and characterized in detail for its functional validation under desiccation and salinity. The SbSI-1 gene is 917 bp long, and contained 437 bp 3' UTR, and 480 bp ORF region encoding 159 amino acids protein with estimated molecular mass of 18.39 kDa and pI 8.58. The real time PCR analysis revealed high transcript expression in salt, desiccation, cold and heat stresses. However, the maximum expression was obtained by desiccation. The ORF region of SbSI-1 was cloned in pET28a vector and transformed in BL21 (DE3) E. coli cells. The SbSI-1 recombinant E. coli cells showed tolerance to desiccation and salinity stress compared to only vector in the presence of stress.

UFO (UnFold Operator) user guide

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

Kissel, L.; Biggs, F.; Marking, T.R.

UFO is a collection of interactive utility programs for estimating unknown functions of one variable using a wide-ranging class of information as input, for miscellaneous data-analysis applications, for performing feasibility studies, and for supplementing our other software. Inverse problems, which include spectral unfolds, inverse heat-transfer problems, time-domain deconvolution, and unusual or difficult curve-fit problems, are classes of applications for which UFO is well suited. Extensive use of B-splines and (X,Y)-datasets is made to represent functions. The (X,Y)-dataset representation is unique in that it is not restricted to equally-spaced data. This feature is used, for example, in a table-generating algorithm thatmore » evaluates a function to a user-specified interpolation accuracy while minimizing the number of points stored in the corresponding dataset. UFO offers a variety of miscellaneous data-analysis options such as plotting, comparing, transforming, scaling, integrating; and adding, subtracting, multiplying, and dividing functions together. These options are often needed as intermediate steps in analyzing and solving difficult inverse problems, but they also find frequent use in other applications. Statistical options are available to calculate goodness-of-fit to measurements, specify error bands on solutions, give confidence limits on calculated quantities, and to point out the statistical consequences of operations such as smoothing. UFO is designed to do feasibility studies on a variety of engineering measurements. It is also tailored to supplement our Test Analysis and Design codes, SRAD Test-Data Archive software, and Digital Signal Analysis routines.« less

Reconstruction of the unknown optimization cost functions from experimental recordings during static multi-finger prehension

PubMed Central

Niu, Xun; Terekhov, Alexander V.; Latash, Mark L.; Zatsiorsky, Vladimir M.

2013-01-01

The goal of the research is to reconstruct the unknown cost (objective) function(s) presumably used by the neural controller for sharing the total force among individual fingers in multi-finger prehension. The cost function was determined from experimental data by applying the recently developed Analytical Inverse Optimization (ANIO) method (Terekhov et al 2010). The core of the ANIO method is the Theorem of Uniqueness that specifies conditions for unique (with some restrictions) estimation of the objective functions. In the experiment, subjects (n=8) grasped an instrumented handle and maintained it at rest in the air with various external torques, loads, and target grasping forces applied to the object. The experimental data recorded from 80 trials showed a tendency to lie on a 2-dimensional hyperplane in the 4-dimensional finger-force space. Because the constraints in each trial were different, such a propensity is a manifestation of a neural mechanism (not the task mechanics). In agreement with the Lagrange principle for the inverse optimization, the plane of experimental observations was close to the plane resulting from the direct optimization. The latter plane was determined using the ANIO method. The unknown cost function was reconstructed successfully for each performer, as well as for the group data. The cost functions were found to be quadratic with non-zero linear terms. The cost functions obtained with the ANIO method yielded more accurate results than other optimization methods. The ANIO method has an evident potential for addressing the problem of optimization in motor control. PMID:22104742

How Much Is that Exam Grade Really Worth? An Estimation of Student Risk Aversion to Their Unknown Final College Course Grades

ERIC Educational Resources Information Center

Nalley, Lanier; McKenzie, Andrew

2011-01-01

This study created an experimental design with which students can empirically assess their risk behavior with respect to exam grades within an expected utility framework. Specifically, the authors analyzed students' risk preferences associated with taking exams and earning a "risky" unknown grade versus not taking exams and instead…

A conserved 19-kDa Eimeria tenella antigen is a profilin-like protein.

PubMed

Fetterer, R H; Miska, K B; Jenkins, M C; Barfield, R C

2004-12-01

A wide range of recombinant proteins from Eimeria species have been reported to offer some degree of protection against infection and disease, but the specific biological function of these proteins is largely unknown. Previous studies have demonstrated a 19-kDa protein of unknown function designated SZ-1 in sporozoites and merozoites of Eimeria acervulina that can be used to confer partial protection against coccidiosis. Reverse transcriptase-polymerase chain reaction indicated that the gene for SZ-1 is expressed by all the asexual stages of Eimeria tenella. Rabbit antisera to recombinant SZ-1 recognized an approximately 19-kDa protein from extracts of E. tenella sporozoites, merozoites, sporulated oocysts, and oocysts in various stages of sporulation. Immunofluorescence antibody staining indicated specific staining of E. tenella sporozoites and merozoites. Staining was most intense in the cytoplasm of the posterior end of the parasite. The primary amino acid sequence of the gene for E. tenella SZ-1 deduced from the E. tenella genome indicated a conserved domain for the actin-regulatory protein profilin. A conserved binding site for poly-L-proline (PLP), characteristic of profilin was also observed. SZ-1 was separated from soluble extract of E. tenella proteins by affinity chromatography using a PLP ligand, confirming the ability of SZ-1 to bind PLP. SZ-1 also partially inhibited the polymerization of actin. The current results are consistent with the classification of SZ-1 as a profilin-related protein.

Identification of Coq11, a New Coenzyme Q Biosynthetic Protein in the CoQ-Synthome in Saccharomyces cerevisiae*

PubMed Central

Allan, Christopher M.; Awad, Agape M.; Johnson, Jarrett S.; Shirasaki, Dyna I.; Wang, Charles; Blaby-Haas, Crysten E.; Merchant, Sabeeha S.; Loo, Joseph A.; Clarke, Catherine F.

2015-01-01

Coenzyme Q (Q or ubiquinone) is a redox active lipid composed of a fully substituted benzoquinone ring and a polyisoprenoid tail and is required for mitochondrial electron transport. In the yeast Saccharomyces cerevisiae, Q is synthesized by the products of 11 known genes, COQ1–COQ9, YAH1, and ARH1. The function of some of the Coq proteins remains unknown, and several steps in the Q biosynthetic pathway are not fully characterized. Several of the Coq proteins are associated in a macromolecular complex on the matrix face of the inner mitochondrial membrane, and this complex is required for efficient Q synthesis. Here, we further characterize this complex via immunoblotting and proteomic analysis of tandem affinity-purified tagged Coq proteins. We show that Coq8, a putative kinase required for the stability of the Q biosynthetic complex, is associated with a Coq6-containing complex. Additionally Q6 and late stage Q biosynthetic intermediates were also found to co-purify with the complex. A mitochondrial protein of unknown function, encoded by the YLR290C open reading frame, is also identified as a constituent of the complex and is shown to be required for efficient de novo Q biosynthesis. Given its effect on Q synthesis and its association with the biosynthetic complex, we propose that the open reading frame YLR290C be designated COQ11. PMID:25631044

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation

PubMed Central

Yu, Hongyi

2018-01-01

A novel geolocation architecture, termed “Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)” is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér–Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML. PMID:29562601

Identification of Coq11, a New Coenzyme Q Biosynthetic Protein in the CoQ-Synthome in Saccharomyces cerevisiae

DOE PAGES

Allan, Christopher M.; Awad, Agape M.; Johnson, Jarrett S.; ...

2015-01-28

Coenzyme Q (Q or ubiquinone) is a redox active lipid composed of a fully substituted benzoquinone ring and a polyisoprenoid tail and is required for mitochondrial electron transport. In the yeast Saccharomyces cerevisiae, Q is synthesized by the products of 11 known genes, COQ1–COQ9, YAH1, and ARH1. The function of some of the Coq proteins remains unknown, and several steps in the Q biosynthetic pathway are not fully characterized. Several of the Coq proteins are associated in a macromolecular complex on the matrix face of the inner mitochondrial membrane, and this complex is required for efficient Q synthesis. In thismore » paper, we further characterize this complex via immunoblotting and proteomic analysis of tandem affinity-purified tagged Coq proteins. We show that Coq8, a putative kinase required for the stability of the Q biosynthetic complex, is associated with a Coq6-containing complex. Additionally Q 6 and late stage Q biosynthetic intermediates were also found to co-purify with the complex. A mitochondrial protein of unknown function, encoded by the YLR290C open reading frame, is also identified as a constituent of the complex and is shown to be required for efficient de novo Q biosynthesis. Finally, given its effect on Q synthesis and its association with the biosynthetic complex, we propose that the open reading frame YLR290C be designated COQ11.« less

Direct Position Determination of Unknown Signals in the Presence of Multipath Propagation.

PubMed

Du, Jianping; Wang, Ding; Yu, Wanting; Yu, Hongyi

2018-03-17

A novel geolocation architecture, termed "Multiple Transponders and Multiple Receivers for Multiple Emitters Positioning System (MTRE)" is proposed in this paper. Existing Direct Position Determination (DPD) methods take advantage of a rather simple channel assumption (line of sight channels with complex path attenuations) and a simplified MUltiple SIgnal Classification (MUSIC) algorithm cost function to avoid the high dimension searching. We point out that the simplified assumption and cost function reduce the positioning accuracy because of the singularity of the array manifold in a multi-path environment. We present a DPD model for unknown signals in the presence of Multi-path Propagation (MP-DPD) in this paper. MP-DPD adds non-negative real path attenuation constraints to avoid the mistake caused by the singularity of the array manifold. The Multi-path Propagation MUSIC (MP-MUSIC) method and the Active Set Algorithm (ASA) are designed to reduce the dimension of searching. A Multi-path Propagation Maximum Likelihood (MP-ML) method is proposed in addition to overcome the limitation of MP-MUSIC in the sense of a time-sensitive application. An iterative algorithm and an approach of initial value setting are given to make the MP-ML time consumption acceptable. Numerical results validate the performances improvement of MP-MUSIC and MP-ML. A closed form of the Cramér-Rao Lower Bound (CRLB) is derived as a benchmark to evaluate the performances of MP-MUSIC and MP-ML.

Edaravone and its clinical development for amyotrophic lateral sclerosis.

PubMed

Takei, Koji; Watanabe, Kazutoshi; Yuki, Satoshi; Akimoto, Makoto; Sakata, Takeshi; Palumbo, Joseph

2017-10-01

The etiology of amyotrophic lateral sclerosis (ALS) is unknown. Oxidative stress may be one of the major mechanisms involved. In vitro and in vivo data of edaravone suggest that it may possess broad free radical scavenging activity and protect neurons, glia, and vascular endothelial cells against oxidative stress. During the 1980s and 1990s, edaravone was developed for the treatment of acute ischemic stroke. In 2001, a clinical program in ALS was initiated and five clinical studies were conducted in Japan. Phase III studies were designed to rapidly evaluate (within a 24-week double-blind study window) functional changes using the Revised ALS Functional Rating Scale (ALSFRS-R) as a primary endpoint. The study populations were selected according to these considerations and were further refined as the studies proceeded. Although the first phase III study did not meet its primary endpoint, post-hoc analyses showed an apparent effect of edaravone, when additional patient inclusion criteria defined by ALSFRS-R score, pulmonary function, certainty of ALS diagnosis, and duration of disease were applied. This population was hypothesized not only to have retained broad functionality and normal respiratory function at study baseline but also to be likely to show measurable disease progression over 24 weeks. A second confirmatory phase III study applying these refinements in patient selection was prospectively designed and successfully documented a statistically significant difference between the edaravone and placebo groups in the ALSFRS-R primary endpoint. This paper describes and reviews data pertinent to the potential mechanism of action of edaravone, and reviews the development history of edaravone for the treatment of ALS.

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

LECTINPred: web Server that Uses Complex Networks of Protein Structure for Prediction of Lectins with Potential Use as Cancer Biomarkers or in Parasite Vaccine Design.

PubMed

Munteanu, Cristian R; Pedreira, Nieves; Dorado, Julián; Pazos, Alejandro; Pérez-Montoto, Lázaro G; Ubeira, Florencio M; González-Díaz, Humberto

2014-04-01

Lectins (Ls) play an important role in many diseases such as different types of cancer, parasitic infections and other diseases. Interestingly, the Protein Data Bank (PDB) contains +3000 protein 3D structures with unknown function. Thus, we can in principle, discover new Ls mining non-annotated structures from PDB or other sources. However, there are no general models to predict new biologically relevant Ls based on 3D chemical structures. We used the MARCH-INSIDE software to calculate the Markov-Shannon 3D electrostatic entropy parameters for the complex networks of protein structure of 2200 different protein 3D structures, including 1200 Ls. We have performed a Linear Discriminant Analysis (LDA) using these parameters as inputs in order to seek a new Quantitative Structure-Activity Relationship (QSAR) model, which is able to discriminate 3D structure of Ls from other proteins. We implemented this predictor in the web server named LECTINPred, freely available at http://bio-aims.udc.es/LECTINPred.php. This web server showed the following goodness-of-fit statistics: Sensitivity=96.7 % (for Ls), Specificity=87.6 % (non-active proteins), and Accuracy=92.5 % (for all proteins), considering altogether both the training and external prediction series. In mode 2, users can carry out an automatic retrieval of protein structures from PDB. We illustrated the use of this server, in operation mode 1, performing a data mining of PDB. We predicted Ls scores for +2000 proteins with unknown function and selected the top-scored ones as possible lectins. In operation mode 2, LECTINPred can also upload 3D structural models generated with structure-prediction tools like LOMETS or PHYRE2. The new Ls are expected to be of relevance as cancer biomarkers or useful in parasite vaccine design. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2015-01-01

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

Wave Intensity Analysis of Right Ventricular Function during Pulsed Operation of Rotary Left Ventricular Assist Devices.

PubMed

Bouwmeester, J Christopher; Park, Jiheum; Valdovinos, John; Bonde, Pramod

2018-05-29

Changing the speed of left ventricular assist devices (LVADs) cyclically may be useful to restore aortic pulsatility; however, the effects of this pulsation on right ventricular (RV) function are unknown. This study investigates the effects of direct ventricular interaction by quantifying the amount of wave energy created by RV contraction when axial and centrifugal LVADs are used to assist the left ventricle. In 4 anesthetized pigs, pressure and flow were measured in the main pulmonary artery and wave intensity analysis was used to identify and quantify the energy of waves created by the RV. The axial pump depressed the intensity of waves created by RV contraction compared with the centrifugal pump. In both pump designs, there were only minor and variable differences between the continuous and pulsed operation on RV function. The axial pump causes the RV to contract with less energy compared with a centrifugal design. Diminishing the ability of the RV to produce less energy translates to less pressure and flow produced, which may lead to LVAD-induced RV failure. The effects of pulsed LVAD operation on the RV appear to be minimal during acute observation of healthy hearts. Further study is necessary to uncover the effects of other modes of speed modulation with healthy and unhealthy hearts to determine if pulsed operation will benefit patients by reducing LVAD complications.

Skin and scales of teleost fish: Simple structure but high performance and multiple functions

NASA Astrophysics Data System (ADS)

Vernerey, Franck J.; Barthelat, Francois

2014-08-01

Natural and man-made structural materials perform similar functions such as structural support or protection. Therefore they rely on the same types of properties: strength, robustness, lightweight. Nature can therefore provide a significant source of inspiration for new and alternative engineering designs. We report here some results regarding a very common, yet largely unknown, type of biological material: fish skin. Within a thin, flexible and lightweight layer, fish skins display a variety of strain stiffening and stabilizing mechanisms which promote multiple functions such as protection, robustness and swimming efficiency. We particularly discuss four important features pertaining to scaled skins: (a) a strongly elastic tensile behavior that is independent from the presence of rigid scales, (b) a compressive response that prevents buckling and wrinkling instabilities, which are usually predominant for thin membranes, (c) a bending response that displays nonlinear stiffening mechanisms arising from geometric constraints between neighboring scales and (d) a robust structure that preserves the above characteristics upon the loss or damage of structural elements. These important properties make fish skin an attractive model for the development of very thin and flexible armors and protective layers, especially when combined with the high penetration resistance of individual scales. Scaled structures inspired by fish skin could find applications in ultra-light and flexible armor systems, flexible electronics or the design of smart and adaptive morphing structures for aerospace vehicles.

Kurtosis Approach for Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation.

Graphical derivations of radar, sonar, and communication signals

NASA Technical Reports Server (NTRS)

Altes, R. A.; Titlebaum, E. L.

1975-01-01

The designer of a communication system often has knowledge concerning the changes in distance between transmitter and receiver as a function of time. This information can be exploited to reduce multipath interference via proper signal design. A radar or sonar may also have good a priori information about possible target trajectories. Such knowledge can again be used to reduce the receiver's response to clutter (MTI), to enhance signal-to-noise ratio, or to simplify receiver design. There are also situations in which prior knowledge about trajectories is lacking. The system should then utilize a single-filter pair which is insensitive to the effects induced by relative motion between transmitter, receiver, and reflectors. For waveforms with large time-bandwidth products, such as long pulse trains, it is possible to graphically derive signal formats for both situations (trajectory known and unknown). Although the exact form of the signal is sometimes not specified by the graphical procedure, the problem in such cases is reduced to one which has already been solved, i.e., the generation of an impulse equivalent code.

Nonlinear Control of the Doubly Fed Induction Motor with Copper Losses Minimization for Electrical Vehicle

NASA Astrophysics Data System (ADS)

Drid, S.; Nait-Said, M.-S.; Tadjine, M.; Makouf, A.

2008-06-01

There is an increasing interest in electric vehicles due to environmental concerns. Recent efforts are directed toward developing an improved propulsion system for electric vehicles applications with minimal power losses. This paper deals with the high efficient vector control for the reduction of copper losses of the doubly fed motor. Firstly, the feedback linearization control based on Lyapunov approach is employed to design the underlying controller achieving the double fluxes orientation. The fluxes controllers are designed independently of the speed. The speed controller is designed using the Lyapunov method especially employed to the unknown load torques. The global asymptotic stability of the overall system is theoretically proven. Secondly, a new Torque Copper Losses Factor is proposed to deal with the problem of the machine copper losses. Its main function is to optimize the torque in keeping the machine saturation at an acceptable level. This leads to a reduction in machine currents and therefore their accompanied copper losses guaranteeing improved machine efficiency. The simulation results in comparative presentation confirm largely the effectiveness of the proposed DFIM control with a very interesting energy saving contribution.

Novel adaptive neural control design for a constrained flexible air-breathing hypersonic vehicle based on actuator compensation

NASA Astrophysics Data System (ADS)

Bu, Xiangwei; Wu, Xiaoyan; He, Guangjun; Huang, Jiaqi

2016-03-01

This paper investigates the design of a novel adaptive neural controller for the longitudinal dynamics of a flexible air-breathing hypersonic vehicle with control input constraints. To reduce the complexity of controller design, the vehicle dynamics is decomposed into the velocity subsystem and the altitude subsystem, respectively. For each subsystem, only one neural network is utilized to approach the lumped unknown function. By employing a minimal-learning parameter method to estimate the norm of ideal weight vectors rather than their elements, there are only two adaptive parameters required for neural approximation. Thus, the computational burden is lower than the ones derived from neural back-stepping schemes. Specially, to deal with the control input constraints, additional systems are exploited to compensate the actuators. Lyapunov synthesis proves that all the closed-loop signals involved are uniformly ultimately bounded. Finally, simulation results show that the adopted compensation scheme can tackle actuator constraint effectively and moreover velocity and altitude can stably track their reference trajectories even when the physical limitations on control inputs are in effect.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System

PubMed Central

Li, Xiangfei; Lin, Yuliang

2017-01-01

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system. PMID:29211017

Optimal hemodynamic response model for functional near-infrared spectroscopy

PubMed Central

Kamran, Muhammad A.; Jeong, Myung Yung; Mannan, Malik M. N.

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650–950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > tcritical and p-value < 0.05). PMID:26136668

Optimal hemodynamic response model for functional near-infrared spectroscopy.

PubMed

Kamran, Muhammad A; Jeong, Myung Yung; Mannan, Malik M N

2015-01-01

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive brain imaging technique and measures brain activities by means of near-infrared light of 650-950 nm wavelengths. The cortical hemodynamic response (HR) differs in attributes at different brain regions and on repetition of trials, even if the experimental paradigm is kept exactly the same. Therefore, an HR model that can estimate such variations in the response is the objective of this research. The canonical hemodynamic response function (cHRF) is modeled by two Gamma functions with six unknown parameters (four of them to model the shape and other two to scale and baseline respectively). The HRF model is supposed to be a linear combination of HRF, baseline, and physiological noises (amplitudes and frequencies of physiological noises are supposed to be unknown). An objective function is developed as a square of the residuals with constraints on 12 free parameters. The formulated problem is solved by using an iterative optimization algorithm to estimate the unknown parameters in the model. Inter-subject variations in HRF and physiological noises have been estimated for better cortical functional maps. The accuracy of the algorithm has been verified using 10 real and 15 simulated data sets. Ten healthy subjects participated in the experiment and their HRF for finger-tapping tasks have been estimated and analyzed. The statistical significance of the estimated activity strength parameters has been verified by employing statistical analysis (i.e., t-value > t critical and p-value < 0.05).

Variational Methods in Sensitivity Analysis and Optimization for Aerodynamic Applications

NASA Technical Reports Server (NTRS)

Ibrahim, A. H.; Hou, G. J.-W.; Tiwari, S. N. (Principal Investigator)

1996-01-01

Variational methods (VM) sensitivity analysis, which is the continuous alternative to the discrete sensitivity analysis, is employed to derive the costate (adjoint) equations, the transversality conditions, and the functional sensitivity derivatives. In the derivation of the sensitivity equations, the variational methods use the generalized calculus of variations, in which the variable boundary is considered as the design function. The converged solution of the state equations together with the converged solution of the costate equations are integrated along the domain boundary to uniquely determine the functional sensitivity derivatives with respect to the design function. The determination of the sensitivity derivatives of the performance index or functional entails the coupled solutions of the state and costate equations. As the stable and converged numerical solution of the costate equations with their boundary conditions are a priori unknown, numerical stability analysis is performed on both the state and costate equations. Thereafter, based on the amplification factors obtained by solving the generalized eigenvalue equations, the stability behavior of the costate equations is discussed and compared with the state (Euler) equations. The stability analysis of the costate equations suggests that the converged and stable solution of the costate equation is possible only if the computational domain of the costate equations is transformed to take into account the reverse flow nature of the costate equations. The application of the variational methods to aerodynamic shape optimization problems is demonstrated for internal flow problems at supersonic Mach number range. The study shows, that while maintaining the accuracy of the functional sensitivity derivatives within the reasonable range for engineering prediction purposes, the variational methods show a substantial gain in computational efficiency, i.e., computer time and memory, when compared with the finite difference sensitivity analysis.

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Kashima, Hisashi; Tanaka, Isao

2018-01-01

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine learning is a unique approach to search for currently unknown CRCs from vast candidates. Herein we propose matrix- and tensor-based recommender system approaches to predict currently unknown CRCs from database entries of CRCs. Firstly, the performance of the recommender system approaches to discover currently unknown CRCs is examined. A Tucker decomposition recommender system shows the best discovery rate of CRCs as the majority of the top 100 recommended ternary and quaternary compositions correspond to CRCs. Secondly, systematic density functional theory (DFT) calculations are performed to investigate the phase stability of the recommended compositions. The phase stability of the 27 compositions reveals that 23 currently unknown compounds are newly found to be stable. These results indicate that the recommender system has great potential to accelerate the discovery of new compounds.

PhylArray: phylogenetic probe design algorithm for microarray.

PubMed

Militon, Cécile; Rimour, Sébastien; Missaoui, Mohieddine; Biderre, Corinne; Barra, Vincent; Hill, David; Moné, Anne; Gagne, Geneviève; Meier, Harald; Peyretaillade, Eric; Peyret, Pierre

2007-10-01

Microbial diversity is still largely unknown in most environments, such as soils. In order to get access to this microbial 'black-box', the development of powerful tools such as microarrays are necessary. However, the reliability of this approach relies on probe efficiency, in particular sensitivity, specificity and explorative power, in order to obtain an image of the microbial communities that is close to reality. We propose a new probe design algorithm that is able to select microarray probes targeting SSU rRNA at any phylogenetic level. This original approach, implemented in a program called 'PhylArray', designs a combination of degenerate and non-degenerate probes for each target taxon. Comparative experimental evaluations indicate that probes designed with PhylArray yield a higher sensitivity and specificity than those designed by conventional approaches. Applying the combined PhyArray/GoArrays strategy helps to optimize the hybridization performance of short probes. Finally, hybridizations with environmental targets have shown that the use of the PhylArray strategy can draw attention to even previously unknown bacteria.

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Functions of maize genes encoding pyruvate phosphate dikinase in developing endosperm

USDA-ARS?s Scientific Manuscript database

Pyruvate phosphate dikinase reversibly converts AMP, pyrophosphate and phosphoenolpyruvate (PEP) to ATP, orthophosphate and pyruvate. Maize PPDK functions in mesophyll in C4 photosynthesis, yet also is highly abundant in starchy endosperm during grain fill where its function is unknown. To investiga...

What Bacteria Are Living in My Food?: An Open-Ended Practical Series Involving Identification of Unknown Foodborne Bacteria Using Molecular Techniques

ERIC Educational Resources Information Center

Prasad, Prascilla; Turner, Mark S.

2011-01-01

This open-ended practical series titled "Molecular Identification of Unknown Food Bacteria" which extended over a 6-week period was designed with the aims of giving students an opportunity to gain an understanding of naturally occurring food bacteria and skills in contemporary molecular methods using real food samples. The students first isolated…

8. Photocopy of photograph, date unknown (original print on file ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

8. Photocopy of photograph, date unknown (original print on file at U.S. Army Intelligence Security Command, Fort Belvoir, Virginia). VIEW OF SULLINS COLLEGE, BRISTOL, VIRGINIA. SULLINS COLLEGE PRESIDENT WILLIAM MARTIN FOUNDED ARLINGTON HALL JUNIOR COLLEGE, AND APPEARS TO HAVE LOOSELY BASED THE DESIGN OF THE NEW SCHOOL'S BUILDINGS UPON THOSE AT SULLINS. - Arlington Hall Station, 4000 Arlington Boulevard, Arlington, Arlington County, VA

Fictional privacy among Facebook users.

PubMed

Lemieux, Robert

2012-08-01

The current study involved the creation of a fictional Facebook account with limited information and was designed to assess whether participants would accept the friendship of an ambiguous, unknown person. Results indicated that 325 Facebook members (72% of the sample) willingly accepted the friendship of the unknown individual. Results are discussed in relation to privacy concerns, norms of reciprocity, and allowing access to potentially embarrassing information and/or pictures.

New Ideas for an Old Enzyme: A Short, Question-Based Laboratory Project for the Purification and Identification of an Unknown LDH Isozyme

ERIC Educational Resources Information Center

Coleman, Aaron B.

2010-01-01

Enzyme purification projects are an excellent way to introduce many aspects of protein biochemistry, but can be difficult to carry out under the constraints of a typical undergraduate laboratory course. We have designed a short laboratory project for the purification and identification of an "unknown" lactate dehydrogenase (LDH) isozyme that can…

Function-based Biosensor for Hazardous Waste Toxin Detection

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

James J Hickman

There is a need for new types of toxicity sensors in the DOE and other agencies that are based on biological function as the toxins encountered during decontamination or waste remediation may be previously unknown or their effects subtle. Many times the contents of the environmental waste, especially the minor components, have not been fully identified and characterized. New sensors of this type could target unknown toxins that cause death as well as intermediate levels of toxicity that impair function or cause long term impairment that may eventually lead to death. The primary question posed in this grant was tomore » create an electronically coupled neuronal cellular circuit to be used as sensor elements for a hybrid non-biological/biological toxin sensor system. A sensor based on the electrical signals transmitted between two mammalian neurons would allow the marriage of advances in solid state electronics with a functioning biological system to develop a new type of biosensor. Sensors of this type would be a unique addition to the field of sensor technology but would also be complementary to existing sensor technology that depends on knowledge of what is to be detected beforehand. We integrated physics, electronics, surface chemistry, biotechnology, and fundamental neuroscience in the development of this biosensor. Methods were developed to create artificial surfaces that enabled the patterning of discrete cells, and networks of cells, in culture; the networks were then aligned with transducers. The transducers were designed to measure electromagnetic fields (EMF) at low field strength. We have achieved all of the primary goals of the project. We can now pattern neurons routinely in our labs as well as align them with transducers. We have also shown the signals between neurons can be modulated by different biochemicals. In addition, we have made another significant advance where we have repeated the patterning results with adult hippocampal cells. Finally, we demonstrated that patterned cardiac cells on microelectrode arrays could act as sensors as well.« less

Autonomic nervous system function in young children with functional abdominal pain or irritable bowel syndrome

USDA-ARS?s Scientific Manuscript database

Adults with irritable bowel syndrome (IBS) have been reported to have alterations in autonomic nervous system function as measured by vagal activity via heart rate variability. Whether the same is true for children is unknown. We compared young children 7 to 10 years of age with functional abdominal...

Genome-wide protein-protein interactions and protein function exploration in cyanobacteria

PubMed Central

Lv, Qi; Ma, Weimin; Liu, Hui; Li, Jiang; Wang, Huan; Lu, Fang; Zhao, Chen; Shi, Tieliu

2015-01-01

Genome-wide network analysis is well implemented to study proteins of unknown function. Here, we effectively explored protein functions and the biological mechanism based on inferred high confident protein-protein interaction (PPI) network in cyanobacteria. We integrated data from seven different sources and predicted 1,997 PPIs, which were evaluated by experiments in molecular mechanism, text mining of literatures in proved direct/indirect evidences, and “interologs” in conservation. Combined the predicted PPIs with known PPIs, we obtained 4,715 no-redundant PPIs (involving 3,231 proteins covering over 90% of genome) to generate the PPI network. Based on the PPI network, terms in Gene ontology (GO) were assigned to function-unknown proteins. Functional modules were identified by dissecting the PPI network into sub-networks and analyzing pathway enrichment, with which we investigated novel function of underlying proteins in protein complexes and pathways. Examples of photosynthesis and DNA repair indicate that the network approach is a powerful tool in protein function analysis. Overall, this systems biology approach provides a new insight into posterior functional analysis of PPIs in cyanobacteria. PMID:26490033

Modular architecture of the T4 phage superfamily: A conserved core genome and a plastic periphery

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

Comeau, Andre M.; Bertrand, Claire; Letarov, Andrei

2007-06-05

Among the most numerous objects in the biosphere, phages show enormous diversity in morphology and genetic content. We have sequenced 7 T4-like phages and compared their genome architecture. All seven phages share a core genome with T4 that is interrupted by several hyperplastic regions (HPRs) where most of their divergence occurs. The core primarily includes homologues of essential T4 genes, such as the virion structure and DNA replication genes. In contrast, the HPRs contain mostly novel genes of unknown function and origin. A few of the HPR genes that can be assigned putative functions, such as a series of novelmore » Internal Proteins, are implicated in phage adaptation to the host. Thus, the T4-like genome appears to be partitioned into discrete segments that fulfil different functions and behave differently in evolution. Such partitioning may be critical for these large and complex phages to maintain their flexibility, while simultaneously allowing them to conserve their highly successful virion design and mode of replication.« less

TESS: a geometric hashing algorithm for deriving 3D coordinate templates for searching structural databases. Application to enzyme active sites.

PubMed Central

Wallace, A. C.; Borkakoti, N.; Thornton, J. M.

1997-01-01

It is well established that sequence templates such as those in the PROSITE and PRINTS databases are powerful tools for predicting the biological function and tertiary structure for newly derived protein sequences. The number of X-ray and NMR protein structures is increasing rapidly and it is apparent that a 3D equivalent of the sequence templates is needed. Here, we describe an algorithm called TESS that automatically derives 3D templates from structures deposited in the Brookhaven Protein Data Bank. While a new sequence can be searched for sequence patterns, a new structure can be scanned against these 3D templates to identify functional sites. As examples, 3D templates are derived for enzymes with an O-His-O "catalytic triad" and for the ribonucleases and lysozymes. When these 3D templates are applied to a large data set of nonidentical proteins, several interesting hits are located. This suggests that the development of a 3D template database may help to identify the function of new protein structures, if unknown, as well as to design proteins with specific functions. PMID:9385633

Variability in Cadence During Forced Cycling Predicts Motor Improvement in Individuals With Parkinson’s Disease

PubMed Central

Ridgel, Angela L.; Abdar, Hassan Mohammadi; Alberts, Jay L.; Discenzo, Fred M.; Loparo, Kenneth A.

2014-01-01

Variability in severity and progression of Parkinson’s disease symptoms makes it challenging to design therapy interventions that provide maximal benefit. Previous studies showed that forced cycling, at greater pedaling rates, results in greater improvements in motor function than voluntary cycling. The precise mechanism for differences in function following exercise is unknown. We examined the complexity of biomechanical and physiological features of forced and voluntary cycling and correlated these features to improvements in motor function as measured by the Unified Parkinson’s Disease Rating Scale (UPDRS). Heart rate, cadence, and power were analyzed using entropy signal processing techniques. Pattern variability in heart rate and power were greater in the voluntary group when compared to forced group. In contrast, variability in cadence was higher during forced cycling. UPDRS Motor III scores predicted from the pattern variability data were highly correlated to measured scores in the forced group. This study shows how time series analysis methods of biomechanical and physiological parameters of exercise can be used to predict improvements in motor function. This knowledge will be important in the development of optimal exercise-based rehabilitation programs for Parkinson’s disease. PMID:23144045

Rapid production of functionalized recombinant proteins: marrying ligation independent cloning and in vitro protein ligation.

PubMed

Kushnir, Susanna; Marsac, Yoann; Breitling, Reinhard; Granovsky, Igor; Brok-Volchanskaya, Vera; Goody, Roger S; Becker, Christian F W; Alexandrov, Kirill

2006-01-01

Functional genomics and proteomics have been very active fields since the sequencing of several genomes was completed. To assign a physiological role to the newly discovered coding genes with unknown function, new generic methods for protein production, purification, and targeted functionalization are needed. This work presents a new vector, pCYSLIC, that allows rapid generation of Escherichia coli expression constructs via ligation-independent cloning (LIC). The vector is designed to facilitate protein purification by either Ni-NTA or GSH affinity chromatography. Subsequent proteolytic removal of affinity tags liberates an N-terminal cysteine residue that is then used for covalent modification of the target protein with different biophysical probes via protein ligation. The described system has been tested on 36 mammalian Rab GTPases, and it was demonstrated that recombinant GTPases produced with pCYSLIC could be efficiently modified with fluorescein or biotin in vitro. Finally, LIC was compared with the recently developed In-Fusion cloning method, and it was demonstrated that In-Fusion provides superior flexibility in choice of expression vector. By the application of In-Fusion cloning Cys-Rab6A GTPase with an N-terminal cysteine residue was generated employing unmodified pET30a vector and TVMV protease.

Customization of Artificial MicroRNA Design.

PubMed

Van Vu, Tien; Do, Vinh Nang

2017-01-01

RNAi approaches, including microRNA (miRNA) regulatory pathway, offer great tools for functional characterization of unknown genes. Moreover, the applications of artificial microRNA (amiRNA) in the field of plant transgenesis have also been advanced to engineer pathogen-resistant or trait-improved transgenic plants. Until now, despite the high potency of amiRNA approach, no commercial plant cultivar expressing amiRNAs with improved traits has been released yet. Beside the issues of biosafety policies, the specificity and efficacy of amiRNAs are of major concerns. Sufficient cares should be taken for the specificity and efficacy of amiRNAs due to their potential off-target effects and other issues relating to in vivo expression of pre-amiRNAs. For these reasons, the proper design of amiRNAs with the lowest off-target possibility is very important for successful applications of the approach in plant. Therefore, there are many studies with the aim to improve the amiRNA design and amiRNA expressing backbones for obtaining better specificity and efficacy. However, the requirement for an efficient reference for the design is still needed. In the present chapter, we attempt to summarize and discuss all the major concerns relating to amiRNA design with the hope to provide a significant guideline for this approach.

Efficient Bayesian experimental design for contaminant source identification

NASA Astrophysics Data System (ADS)

Zhang, Jiangjiang; Zeng, Lingzao; Chen, Cheng; Chen, Dingjiang; Wu, Laosheng

2015-01-01

In this study, an efficient full Bayesian approach is developed for the optimal sampling well location design and source parameters identification of groundwater contaminants. An information measure, i.e., the relative entropy, is employed to quantify the information gain from concentration measurements in identifying unknown parameters. In this approach, the sampling locations that give the maximum expected relative entropy are selected as the optimal design. After the sampling locations are determined, a Bayesian approach based on Markov Chain Monte Carlo (MCMC) is used to estimate unknown parameters. In both the design and estimation, the contaminant transport equation is required to be solved many times to evaluate the likelihood. To reduce the computational burden, an interpolation method based on the adaptive sparse grid is utilized to construct a surrogate for the contaminant transport equation. The approximated likelihood can be evaluated directly from the surrogate, which greatly accelerates the design and estimation process. The accuracy and efficiency of our approach are demonstrated through numerical case studies. It is shown that the methods can be used to assist in both single sampling location and monitoring network design for contaminant source identifications in groundwater.

Automated genomic context analysis and experimental validation platform for discovery of prokaryote transcriptional regulator functions

DOE PAGES

Martí-Arbona, Ricardo; Mu, Fangping; Nowak-Lovato, Kristy L.; ...

2014-12-18

In this study, the clustering of genes in a pathway and the co-location of functionally related genes is widely recognized in prokaryotes. We used these characteristics to predict the metabolic involvement for a Transcriptional Regulator (TR) of unknown function, identified and confirmed its biological activity. software tool that identifies the genes encoded within a defined genomic neighborhood for the subject TR and its homologs was developed. The output lists of genes in the genetic neighborhoods, their annotated functions, the reactants/products, and identifies the metabolic pathway in which the encoded-proteins function. When a set of TRs of known function was analyzed,more » we observed that their homologs frequently had conserved genomic neighborhoods that co-located the metabolically related genes regulated by the subject TR. We postulate that TR effectors are metabolites in the identified pathways; indeed the known effectors were present. We analyzed Bxe_B3018 from Burkholderia xenovorans, a TR of unknown function and predicted that this TR was related to the glycine, threonine and serine degradation. We tested the binding of metabolites in these pathways and for those that bound, their ability to modulate TR binding to its specific DNA operator sequence. Using rtPCR, we confirmed that methylglyoxal was an effector of Bxe_3018. These studies provide the proof of concept and validation of a systematic approach to the discovery of the biological activity for proteins of unknown function, in this case a TR. Bxe_B3018 is a methylglyoxal responsive TR that controls the expression of an operon composed of a putative efflux system.« less

A Framework for Globular Proteins

NASA Astrophysics Data System (ADS)

Lezon, Timothy

2006-03-01

Due to their remarkable chemical specificity and diversity, globular proteins play a crucial role in the network of molecular interactions of life. Over the past several decades, much experimental data has been accumulated on proteins, but the overarching principles that govern the general features of proteins remain largely unknown. Here, a novel framework for understanding many key attributes of globular proteins is presented. This framework suggests that the characteristics of globular proteins that make them well-suited for biological function are the emergent properties of a unique phase of matter. Implications of this picture include the provision of a fixed backdrop for molecular evolution and natural selection and design restrictions on molecular machinery. The work described here was carried out in collaboration with Jayanth Banavar and Amos Maritan.

Synthetic genetic polymers capable of heredity and evolution.

PubMed

Pinheiro, Vitor B; Taylor, Alexander I; Cozens, Christopher; Abramov, Mikhail; Renders, Marleen; Zhang, Su; Chaput, John C; Wengel, Jesper; Peak-Chew, Sew-Yeu; McLaughlin, Stephen H; Herdewijn, Piet; Holliger, Philipp

2012-04-20

Genetic information storage and processing rely on just two polymers, DNA and RNA, yet whether their role reflects evolutionary history or fundamental functional constraints is currently unknown. With the use of polymerase evolution and design, we show that genetic information can be stored in and recovered from six alternative genetic polymers based on simple nucleic acid architectures not found in nature [xeno-nucleic acids (XNAs)]. We also select XNA aptamers, which bind their targets with high affinity and specificity, demonstrating that beyond heredity, specific XNAs have the capacity for Darwinian evolution and folding into defined structures. Thus, heredity and evolution, two hallmarks of life, are not limited to DNA and RNA but are likely to be emergent properties of polymers capable of information storage.

Protein function prediction using neighbor relativity in protein-protein interaction network.

PubMed

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

Linking product design to consumer behavior: the moderating role of consumption experience.

PubMed

Gilal, Naeem Gul; Zhang, Jing; Gilal, Faheem Gul

2018-01-01

Previous investigations of product design broadly link aesthetic, functional, and symbolic designs to sales growth, high turnover, and market share. However, the effect of product design dimensions on consumer willingness-to-buy (WTB) and word-of-mouth (WOM) is virtually ignored by consumer researchers. Similarly, whether the consumption experience can differentiate the effect of the three product design dimensions on WTB and WOM is completely unknown. Using categorization theory as a lens, our study aims to explore the effect of product design dimensions on consumer WTB and WOM directly and indirectly through the moderation of the consumption experience. A convenience sample of (n=357) Chinese and (n=277) Korean shoppers was utilized to test the hypotheses in the fashion apparel industry. Our results showed that the aesthetic design was more prominent in capturing consumer WTB for both Chinese and Koreans. Similarly, the aesthetic design was more salient in enhancing WOM for Chinese, whereas the symbolic design was more promising in terms of improving WOM for Koreans. Further, our moderation results demonstrated that the consumption experience could differentiate the effects of the three product design dimensions on consumer WTB and WOM for Chinese. By contrast, the consumption experience could only interact with the aesthetic design to improve WOM for South Koreans. To the best of authors' knowledge, the present study is one of the initial attempts to link three product design dimensions with consumer WTB and WOM in the fashion apparel context and explored whether consumption experience competes or complement with three product design dimensions to shape consumer WTB and WOM for Chinese and Koreans.

Reachable set estimation for Takagi-Sugeno fuzzy systems against unknown output delays with application to tracking control of AUVs.

PubMed

Zhong, Zhixiong; Zhu, Yanzheng; Ahn, Choon Ki

2018-07-01

In this paper, we address the problem of reachable set estimation for continuous-time Takagi-Sugeno (T-S) fuzzy systems subject to unknown output delays. Based on the reachable set concept, a new controller design method is also discussed for such systems. An effective method is developed to attenuate the negative impact from the unknown output delays, which likely degrade the performance/stability of systems. First, an augmented fuzzy observer is proposed to capacitate a synchronous estimation for the system state and the disturbance term owing to the unknown output delays, which ensures that the reachable set of the estimation error is limited via the intersection operation of ellipsoids. Then, a compensation technique is employed to eliminate the influence on the system performance stemmed from the unknown output delays. Finally, the effectiveness and correctness of the obtained theories are verified by the tracking control of autonomous underwater vehicles. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Power and Roots by Recursion.

ERIC Educational Resources Information Center

Aieta, Joseph F.

1987-01-01

This article illustrates how questions from elementary finance can serve as motivation for studying high order powers, roots, and exponential functions using Logo procedures. A second discussion addresses a relatively unknown algorithm for the trigonometric exponential and hyperbolic functions. (PK)

Thalamic amplification of cortical connectivity sustains attentional control

PubMed Central

Schmitt, L. Ian; Wimmer, Ralf D.; Nakajima, Miho; Happ, Michael; Mofakham, Sima; Halassa, Michael M.

2017-01-01

While interactions between the thalamus and cortex are critical for cognitive function1–3, the exact contribution of the thalamus to these interactions is often unclear. Recent studies have shown diverse connectivity patterns across the thalamus 4,5, but whether this diversity translates to thalamic functions beyond relaying information to or between cortical regions6 is unknown. Here, by investigating prefrontal cortical (PFC) representation of two rules used to guide attention, we find that the mediodorsal thalamus (MD) sustains these representations without relaying categorical information. Specifically, MD input amplifies local PFC connectivity, enabling rule-specific neural sequences to emerge and thereby maintain rule representations. Consistent with this notion, broadly enhancing PFC excitability diminishes rule specificity and behavioral performance, while enhancing MD excitability improves both. Overall, our results define a previously unknown principle in neuroscience; thalamic control of functional cortical connectivity. This function indicates that the thalamus plays much more central roles in cognition than previously thought. PMID:28467827

Serine phosphorylation by SYK is critical for nuclear localization and transcription factor function of Ikaros

PubMed Central

Uckun, Fatih M.; Ma, Hong; Zhang, Jian; Ozer, Zahide; Dovat, Sinisa; Mao, Cheney; Ishkhanian, Rita; Goodman, Patricia; Qazi, Sanjive

2012-01-01

Ikaros is a zinc finger-containing DNA-binding protein that plays a pivotal role in immune homeostasis through transcriptional regulation of the earliest stages of lymphocyte ontogeny and differentiation. Functional deficiency of Ikaros has been implicated in the pathogenesis of acute lymphoblastic leukemia, the most common form of childhood cancer. Therefore, a stringent regulation of Ikaros activity is considered of paramount importance, but the operative molecular mechanisms responsible for its regulation remain largely unknown. Here we provide multifaceted genetic and biochemical evidence for a previously unknown function of spleen tyrosine kinase (SYK) as a partner and posttranslational regulator of Ikaros. We demonstrate that SYK phoshorylates Ikaros at unique C-terminal serine phosphorylation sites S358 and S361, thereby augmenting its nuclear localization and sequence-specific DNA binding activity. Mechanistically, we establish that SYK-induced Ikaros activation is essential for its nuclear localization and optimal transcription factor function. PMID:23071339

Nonlinear adaptive control system design with asymptotically stable parameter estimation error

NASA Astrophysics Data System (ADS)

Mishkov, Rumen; Darmonski, Stanislav

2018-01-01

The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.

Hybrid diversity method utilizing adaptive diversity function for recovering unknown aberrations in an optical system

NASA Technical Reports Server (NTRS)

Dean, Bruce H. (Inventor)

2009-01-01

A method of recovering unknown aberrations in an optical system includes collecting intensity data produced by the optical system, generating an initial estimate of a phase of the optical system, iteratively performing a phase retrieval on the intensity data to generate a phase estimate using an initial diversity function corresponding to the intensity data, generating a phase map from the phase retrieval phase estimate, decomposing the phase map to generate a decomposition vector, generating an updated diversity function by combining the initial diversity function with the decomposition vector, generating an updated estimate of the phase of the optical system by removing the initial diversity function from the phase map. The method may further include repeating the process beginning with iteratively performing a phase retrieval on the intensity data using the updated estimate of the phase of the optical system in place of the initial estimate of the phase of the optical system, and using the updated diversity function in place of the initial diversity function, until a predetermined convergence is achieved.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

The Development of Executive Functions and Early Mathematics: A Dynamic Relationship

ERIC Educational Resources Information Center

Van der Ven, Sanne H. G.; Kroesbergen, Evelyn H.; Boom, Jan; Leseman, Paul P. M.

2012-01-01

Background: The relationship between executive functions and mathematical skills has been studied extensively, but results are inconclusive, and how this relationship evolves longitudinally is largely unknown. Aim: The aim was to investigate the factor structure of executive functions in inhibition, shifting, and updating; the longitudinal…

RMND5 from Xenopus laevis is an E3 ubiquitin-ligase and functions in early embryonic forebrain development.

PubMed

Pfirrmann, Thorsten; Villavicencio-Lorini, Pablo; Subudhi, Abinash K; Menssen, Ruth; Wolf, Dieter H; Hollemann, Thomas

2015-01-01

In Saccharomyces cerevisiae the Gid-complex functions as an ubiquitin-ligase complex that regulates the metabolic switch between glycolysis and gluconeogenesis. In higher organisms six conserved Gid proteins form the CTLH protein-complex with unknown function. Here we show that Rmnd5, the Gid2 orthologue from Xenopus laevis, is an ubiquitin-ligase embedded in a high molecular weight complex. Expression of rmnd5 is strongest in neuronal ectoderm, prospective brain, eyes and ciliated cells of the skin and its suppression results in malformations of the fore- and midbrain. We therefore suggest that Xenopus laevis Rmnd5, as a subunit of the CTLH complex, is a ubiquitin-ligase targeting an unknown factor for polyubiquitination and subsequent proteasomal degradation for proper fore- and midbrain development.

The hypothetical protein Atu4866 from Agrobacterium tumefaciens adopts a streptavidin-like fold

PubMed Central

Ai, Xuanjun; Semesi, Anthony; Yee, Adelinda; Arrowsmith, Cheryl H.; Choy, Wing-Yiu; Li, Shawn S.C.

2008-01-01

Atu4866 is a 79-residue conserved hypothetical protein of unknown function from Agrobacterium tumefaciens. Protein sequence alignments show that it shares ≥60% sequence identity with 20 other hypothetical proteins of bacterial origin. However, the structures and functions of these proteins remain unknown so far. To gain insight into the function of this family of proteins, we have determined the structure of Atu4866 as a target of a structural genomics project using solution NMR spectroscopy. Our results reveal that Atu4866 adopts a streptavidin-like fold featuring a β-barrel/sandwich formed by eight antiparallel β-strands. Further structural analysis identified a continuous patch of conserved residues on the surface of Atu4866 that may constitute a potential ligand-binding site. PMID:18042676

Playing piano can improve upper extremity function after stroke: case studies.

PubMed

Villeneuve, Myriam; Lamontagne, Anouk

2013-01-01

Music-supported therapy (MST) is an innovative approach that was shown to improve manual dexterity in acute stroke survivors. The feasibility of such intervention in chronic stroke survivors and its longer-term benefits, however, remain unknown. The objective of this pilot study was to estimate the short- and long-term effects of a 3-week piano training program on upper extremity function in persons with chronic stroke. A multiple pre-post sequential design was used, with measurements taken at baseline (week0, week3), prior to (week6) and after the intervention (week9), and at 3-week follow-up (week12). Three persons with stroke participated in the 3-week piano training program that combined structured piano lessons to home practice program. The songs, played on an electronic keyboard, involved all 5 digits of the affected hand and were displayed using a user-friendly MIDI program. After intervention, all the three participants showed improvements in their fine (nine hole peg test) and gross (box and block test) manual dexterity, as well as in the functional use of the upper extremity (Jebsen hand function test). Improvements were maintained at follow-up. These preliminary results support the feasibility of using an MST approach that combines structured lessons to home practice to improve upper extremity function in chronic stroke.

The Association Between Cognitive Function and Subsequent Depression: A Systematic Review and Meta-Analysis

PubMed Central

Scult, Matthew A.; Paulli, Athelia R.; Mazure, Emily S.; Moffitt, Terrie E.; Hariri, Ahmad R.; Strauman, Timothy J.

2016-01-01

Despite a growing interest in understanding the cognitive deficits associated with major depressive disorder (MDD), it is largely unknown whether such deficits exist before disorder onset or how they might influence the severity of subsequent illness. The purpose of the present study was to conduct a systematic review and meta-analysis of longitudinal datasets to determine whether cognitive function acts as a predictor of later MDD diagnosis or change in depression symptoms. Eligible studies included longitudinal designs with baseline measures of cognitive functioning, and later unipolar MDD diagnosis or symptom assessment. The systematic review identified 29 publications, representing 34 unique samples, and 121,749 participants, that met the inclusion/exclusion criteria. Quantitative meta-analysis demonstrated that higher cognitive function was associated with decreased levels of subsequent depression (r=−0.088; 95% CI: −0.121, −0.054; p<0.001). However, sensitivity analyses revealed that this association is likely driven by concurrent depression symptoms at the time of cognitive assessment. Our review and meta-analysis indicate that the association between lower cognitive function and later depression is confounded by the presence of contemporaneous depression symptoms at the time of cognitive assessment. Thus, cognitive deficits predicting MDD likely represent deleterious effects of subclinical depression symptoms on performance rather than premorbid risk factors for disorder. PMID:27624847

Playing Piano Can Improve Upper Extremity Function after Stroke: Case Studies

PubMed Central

Villeneuve, Myriam; Lamontagne, Anouk

2013-01-01

Music-supported therapy (MST) is an innovative approach that was shown to improve manual dexterity in acute stroke survivors. The feasibility of such intervention in chronic stroke survivors and its longer-term benefits, however, remain unknown. The objective of this pilot study was to estimate the short- and long-term effects of a 3-week piano training program on upper extremity function in persons with chronic stroke. A multiple pre-post sequential design was used, with measurements taken at baseline (week0, week3), prior to (week6) and after the intervention (week9), and at 3-week follow-up (week12). Three persons with stroke participated in the 3-week piano training program that combined structured piano lessons to home practice program. The songs, played on an electronic keyboard, involved all 5 digits of the affected hand and were displayed using a user-friendly MIDI program. After intervention, all the three participants showed improvements in their fine (nine hole peg test) and gross (box and block test) manual dexterity, as well as in the functional use of the upper extremity (Jebsen hand function test). Improvements were maintained at follow-up. These preliminary results support the feasibility of using an MST approach that combines structured lessons to home practice to improve upper extremity function in chronic stroke. PMID:23533954

Rocketdyne LOX bearing tester program

NASA Technical Reports Server (NTRS)

Keba, J. E.; Beatty, R. F.

1988-01-01

The cause, or causes, for the Space Shuttle Main Engine ball wear were unknown, however, several mechanisms were suspected. Two testers were designed and built for operation in liquid oxygen to empirically gain insight into the problems and iterate solutions in a timely and cost efficient manner independent of engine testing. Schedules and test plans were developed that defined a test matrix consisting of parametric variations of loading, cooling or vapor margin, cage lubrication, material, and geometry studies. Initial test results indicated that the low pressure pump thrust bearing surface distress is a function of high axial load. Initial high pressure turbopump bearing tests produced the wear phenomenon observed in the turbopump and identified an inadequate vapor margin problem and a coolant flowrate sensitivity issue. These tests provided calibration data of analytical model predictions to give high confidence in the positive impact of future turbopump design modification for flight. Various modifications will be evaluated in these testers, since similar turbopump conditions can be produced and the benefit of the modification will be quantified in measured wear life comparisons.

Validation (not just verification) of Deep Space Missions

NASA Technical Reports Server (NTRS)

Duren, Riley M.

2006-01-01

ion & Validation (V&V) is a widely recognized and critical systems engineering function. However, the often used definition 'Verification proves the design is right; validation proves it is the right design' is rather vague. And while Verification is a reasonably well standardized systems engineering process, Validation is a far more abstract concept and the rigor and scope applied to it varies widely between organizations and individuals. This is reflected in the findings in recent Mishap Reports for several NASA missions, in which shortfalls in Validation (not just Verification) were cited as root- or contributing-factors in catastrophic mission loss. Furthermore, although there is strong agreement in the community that Test is the preferred method for V&V, many people equate 'V&V' with 'Test', such that Analysis and Modeling aren't given comparable attention. Another strong motivator is a realization that the rapid growth in complexity of deep-space missions (particularly Planetary Landers and Space Observatories given their inherent unknowns) is placing greater demands on systems engineers to 'get it right' with Validation.

Bayesian Revision of Residual Detection Power

NASA Technical Reports Server (NTRS)

DeLoach, Richard

2013-01-01

This paper addresses some issues with quality assessment and quality assurance in response surface modeling experiments executed in wind tunnels. The role of data volume on quality assurance for response surface models is reviewed. Specific wind tunnel response surface modeling experiments are considered for which apparent discrepancies exist between fit quality expectations based on implemented quality assurance tactics, and the actual fit quality achieved in those experiments. These discrepancies are resolved by using Bayesian inference to account for certain imperfections in the assessment methodology. Estimates of the fraction of out-of-tolerance model predictions based on traditional frequentist methods are revised to account for uncertainty in the residual assessment process. The number of sites in the design space for which residuals are out of tolerance is seen to exceed the number of sites where the model actually fails to fit the data. A method is presented to estimate how much of the design space in inadequately modeled by low-order polynomial approximations to the true but unknown underlying response function.

Designing an Awareness Display for Senior Home Care Professionals

NASA Astrophysics Data System (ADS)

Vastenburg, Martijn H.; Vroegindeweij, Robbert J.

Home care professionals play a central role in supporting elderly people when they need help to continue living in their own homes. Using awareness systems, caregivers might better be able to consider the actual and changing needs of individual clients, and better be prepared for the home visits. In the present situation, the functional requirements on a awareness systems for professional caregivers are unknown, and caregivers tend to be unaware of the potential use of these sensor-based systems. This paper presents a case study in which the user needs are studied using a working prototype; the prototype is used to make target users experience an awareness system in their everyday work practice, and thereby enable them to better reflect upon the user needs and the potential use of these systemsWhereas caregivers were skeptical at first, they did value the prototype in the evaluation phase. In the exit interviews, the caregivers came up with an interesting list of requirements and design directions for a future awareness display.

Sudden cardiac death in haemodialysis: clinical epidemiology and mechanisms.

PubMed

Banerjee, Debasish

Sudden cardiac death, which causes premature loss of lives on haemodialysis of the elderly, youths and even children; cannot be prevented, because the aetiology is poorly understood and effective interventions are yet unknown. Improving our knowledge of mechanisms causing sudden cardiac death in haemodialysis patients may help us to design better interventions; and clinical epidemiology of sudden cardiac death could be an important tool to further guide human and animal studies. This review researches the clinical epidemiology of sudden cardiac death to suggest possible mechanisms, although they require further studies. The research shows how traditional cardiovascular risk factors such as age, diabetes and smoking have an impact; non-traditional risk factors such as inflammation, mineral-bone disease and even uraemia itself have higher impact; and how cardiac structural, functional and electrocardiographic markers predict sudden cardiac death in dialysis patients. More in-depth human and animal studies, guided with existing knowledge, are necessary to better understand the mechanisms and design successful interventions. Copyright © 2016 Elsevier Inc. All rights reserved.

Analysis and design of second-order sliding-mode algorithms for quadrotor roll and pitch estimation.

PubMed

Chang, Jing; Cieslak, Jérôme; Dávila, Jorge; Zolghadri, Ali; Zhou, Jun

2017-11-01

The problem addressed in this paper is that of quadrotor roll and pitch estimation without any assumption about the knowledge of perturbation bounds when Inertial Measurement Units (IMU) data or position measurements are available. A Smooth Sliding Mode (SSM) algorithm is first designed to provide reliable estimation under a smooth disturbance assumption. This assumption is next relaxed with the second proposed Adaptive Sliding Mode (ASM) algorithm that deals with disturbances of unknown bounds. In addition, the analysis of the observers are extended to the case where measurements are corrupted by bias and noise. The gains of the proposed algorithms were deduced from the Lyapunov function. Furthermore, some useful guidelines are provided for the selection of the observer turning parameters. The performance of these two approaches is evaluated using a nonlinear simulation model and considering either accelerometer or position measurements. The simulation results demonstrate the benefits of the proposed solutions. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Neural-Learning-Based Telerobot Control With Guaranteed Performance.

PubMed

Yang, Chenguang; Wang, Xinyu; Cheng, Long; Ma, Hongbin

2017-10-01

In this paper, a neural networks (NNs) enhanced telerobot control system is designed and tested on a Baxter robot. Guaranteed performance of the telerobot control system is achieved at both kinematic and dynamic levels. At kinematic level, automatic collision avoidance is achieved by the control design at the kinematic level exploiting the joint space redundancy, thus the human operator would be able to only concentrate on motion of robot's end-effector without concern on possible collision. A posture restoration scheme is also integrated based on a simulated parallel system to enable the manipulator restore back to the natural posture in the absence of obstacles. At dynamic level, adaptive control using radial basis function NNs is developed to compensate for the effect caused by the internal and external uncertainties, e.g., unknown payload. Both the steady state and the transient performance are guaranteed to satisfy a prescribed performance requirement. Comparative experiments have been performed to test the effectiveness and to demonstrate the guaranteed performance of the proposed methods.

Rational design of novel TLR4 ligands by in silico screening and their functional and structural characterization in vitro.

PubMed

Honegr, Jan; Malinak, David; Dolezal, Rafael; Soukup, Ondrej; Benkova, Marketa; Hroch, Lukas; Benek, Ondrej; Janockova, Jana; Kuca, Kamil; Prymula, Roman

2018-02-25

The purpose of this study was to identify new small molecules that possess activity on human toll-like receptor 4 associated with the myeloid differentiation protein 2 (hTLR4/MD2). Following current rational drug design principles, we firstly performed a ligand and structure based virtual screening of more than 130 000 compounds to discover until now unknown class of hTLR4/MD2 modulators that could be used as novel type of immunologic adjuvants. The core of the in silico study was molecular docking of flexible ligands in a partially flexible hTLR4/MD2 receptor model using a peta-flops-scale supercomputer. The most promising substances resulting from this study, related to anthracene-succimide hybrids, were synthesized and tested. The best prepared candidate exhibited 80% of Monophosphoryl Lipid A in vitro agonistic activity in cell lines expressing hTLR4/MD2. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

LQ optimal and reaching law-based sliding modes for inventory management systems

NASA Astrophysics Data System (ADS)

Ignaciuk, Przemysław; Bartoszewicz, Andrzej

2012-01-01

In this article, the theory of discrete sliding-mode control is used to design new supply strategies for periodic-review inventory systems. In the considered systems, the stock used to fulfil an unknown, time-varying demand can be replenished from a single supply source or from multiple suppliers procuring orders with different delays. The proposed strategies guarantee that demand is always entirely satisfied from the on-hand stock (yielding the maximum service level), and the warehouse capacity is not exceeded (which eliminates the cost of emergency storage). In contrast to the classical, stochastic approaches, in this article, we focus on optimising the inventory system dynamics. The parameters of the first control strategy are selected by minimising a quadratic cost functional. Next, it is shown how the system dynamical performance can be improved by applying the concept of a reaching law with the appropriately adjusted reaching phase. The stable, nonoscillatory behaviour of the closed-loop system is demonstrated and the properties of the designed controllers are discussed and strictly proved.

Model-Based Adaptive Event-Triggered Control of Strict-Feedback Nonlinear Systems.

PubMed

Li, Yuan-Xin; Yang, Guang-Hong

2018-04-01

This paper is concerned with the adaptive event-triggered control problem of nonlinear continuous-time systems in strict-feedback form. By using the event-sampled neural network (NN) to approximate the unknown nonlinear function, an adaptive model and an associated event-triggered controller are designed by exploiting the backstepping method. In the proposed method, the feedback signals and the NN weights are aperiodically updated only when the event-triggered condition is violated. A positive lower bound on the minimum intersample time is guaranteed to avoid accumulation point. The closed-loop stability of the resulting nonlinear impulsive dynamical system is rigorously proved via Lyapunov analysis under an adaptive event sampling condition. In comparing with the traditional adaptive backstepping design with a fixed sample period, the event-triggered method samples the state and updates the NN weights only when it is necessary. Therefore, the number of transmissions can be significantly reduced. Finally, two simulation examples are presented to show the effectiveness of the proposed control method.

Kurtosis Approach Nonlinear Blind Source Separation

NASA Technical Reports Server (NTRS)

Duong, Vu A.; Stubbemd, Allen R.

2005-01-01

In this paper, we introduce a new algorithm for blind source signal separation for post-nonlinear mixtures. The mixtures are assumed to be linearly mixed from unknown sources first and then distorted by memoryless nonlinear functions. The nonlinear functions are assumed to be smooth and can be approximated by polynomials. Both the coefficients of the unknown mixing matrix and the coefficients of the approximated polynomials are estimated by the gradient descent method conditional on the higher order statistical requirements. The results of simulation experiments presented in this paper demonstrate the validity and usefulness of our approach for nonlinear blind source signal separation Keywords: Independent Component Analysis, Kurtosis, Higher order statistics.

Long term clinical history of an Italian cohort of infantile onset Pompe disease treated with enzyme replacement therapy.

PubMed

Parini, Rossella; De Lorenzo, Paola; Dardis, Andrea; Burlina, Alberto; Cassio, Alessandra; Cavarzere, Paolo; Concolino, Daniela; Della Casa, Roberto; Deodato, Federica; Donati, Maria Alice; Fiumara, Agata; Gasperini, Serena; Menni, Francesca; Pagliardini, Veronica; Sacchini, Michele; Spada, Marco; Taurisano, Roberta; Valsecchi, Maria Grazia; Di Rocco, Maja; Bembi, Bruno

2018-02-08

Enzyme replacement therapy (ERT) has deeply modified the clinical history of Infantile Onset Pompe Disease (IOPD). However, its long-term effectiveness is still not completely defined. Available data shows a close relationship between clinical outcome and patients' cross-reactive immunological status (CRIM), being CRIM-negative status a negative prognostic factor. At the same time limited data are available on the long-term treatment in CRIM-positive infants. A retrospective multicentre observational study was designed to analyse the long-term effectiveness of ERT in IOPD. Thirteen Italian centres spread throughout the country were involved and a cohort of 28 patients (15 females, 13 males, born in the period: February 2002-January 2013) was enrolled. IOPD diagnosis was based on clinical symptoms, enzymatic and molecular analysis. All patients received ERT within the first year of life. Clinical, laboratory, and functional data (motor, cardiac and respiratory) were collected and followed for a median period of 71 months (5 years 11 months). Median age at onset, diagnosis and start of ERT were 2, 3 and 4 months, respectively. CRIM status was available for 24/28 patients: 17/24 (71%) were CRIM-positive. Nineteen patients (67%) survived > 2 years: 4 were CRIM-negative, 14 CRIM-positive and one unknown. Six patients (5 CRIM-positive and one unknown) never needed ventilation support (21,4%) and seven (6 CRIM-positive and one unknown: 25%) developed independent ambulation although one subsequently lost this function. Brain imaging study was performed in 6 patients and showed peri-ventricular white matter abnormalities in all of them. Clinical follow-up confirmed the better prognosis for CRIM-positive patients, though a slow, progressive worsening of motor and/or respiratory functions was detected in 8 patients. These data are the result of the longest independent retrospective study on ERT in IOPD reported so far outside clinical trials. The data obtained confirmed the better outcome of the CRIM-positive patients but at the same time, showed the inability of the current therapeutic approach to reverse or stabilize the disease progression. The results also evidenced the involvement of central nervous system in Pompe disease. To better understand the disease clinical history and to improve treatment efficacy larger multicentre studies are needed as well as the development of new therapeutic approaches.

An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

PubMed

Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

2017-12-01

The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

Unified sensor management in unknown dynamic clutter

NASA Astrophysics Data System (ADS)

Mahler, Ronald; El-Fallah, Adel

2010-04-01

In recent years the first author has developed a unified, computationally tractable approach to multisensor-multitarget sensor management. This approach consists of closed-loop recursion of a PHD or CPHD filter with maximization of a "natural" sensor management objective function called PENT (posterior expected number of targets). In this paper we extend this approach so that it can be used in unknown, dynamic clutter backgrounds.

Using Evolutionary Theory to Guide Mental Health Research.

PubMed

Durisko, Zachary; Mulsant, Benoit H; McKenzie, Kwame; Andrews, Paul W

2016-03-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating "normally" (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. © The Author(s) 2016.

Using Evolutionary Theory to Guide Mental Health Research

PubMed Central

Mulsant, Benoit H.; McKenzie, Kwame; Andrews, Paul W.

2016-01-01

Evolutionary approaches to medicine can shed light on the origins and etiology of disease. Such an approach may be especially useful in psychiatry, which frequently addresses conditions with heterogeneous presentation and unknown causes. We review several previous applications of evolutionary theory that highlight the ways in which psychiatric conditions may persist despite and because of natural selection. One lesson from the evolutionary approach is that some conditions currently classified as disorders (because they cause distress and impairment) may actually be caused by functioning adaptations operating “normally” (as designed by natural selection). Such conditions suggest an alternative illness model that may generate alternative intervention strategies. Thus, the evolutionary approach suggests that psychiatry should sometimes think differently about distress and impairment. The complexity of the human brain, including normal functioning and potential for dysfunctions, has developed over evolutionary time and has been shaped by natural selection. Understanding the evolutionary origins of psychiatric conditions is therefore a crucial component to a complete understanding of etiology. PMID:27254091

Microgrid energy dispatching for industrial zones with renewable generations and electric vehicles via stochastic optimization and learning

NASA Astrophysics Data System (ADS)

Zhang, Kai; Li, Jingzhi; He, Zhubin; Yan, Wanfeng

2018-07-01

In this paper, a stochastic optimization framework is proposed to address the microgrid energy dispatching problem with random renewable generation and vehicle activity pattern, which is closer to the practical applications. The patterns of energy generation, consumption and storage availability are all random and unknown at the beginning, and the microgrid controller design (MCD) is formulated as a Markov decision process (MDP). Hence, an online learning-based control algorithm is proposed for the microgrid, which could adapt the control policy with increasing knowledge of the system dynamics and converges to the optimal algorithm. We adopt the linear approximation idea to decompose the original value functions as the summation of each per-battery value function. As a consequence, the computational complexity is significantly reduced from exponential growth to linear growth with respect to the size of battery states. Monte Carlo simulation of different scenarios demonstrates the effectiveness and efficiency of our algorithm.

Integration of two RAB5 groups during endosomal transport in plants

PubMed Central

Ebine, Kazuo; Choi, Seung-won; Ichinose, Sakura; Uemura, Tomohiro; Nakano, Akihiko

2018-01-01

RAB5 is a key regulator of endosomal functions in eukaryotic cells. Plants possess two different RAB5 groups, canonical and plant-unique types, which act via unknown counteracting mechanisms. Here, we identified an effector molecule of the plant-unique RAB5 in Arabidopsis thaliana, ARA6, which we designated PLANT-UNIQUE RAB5 EFFECTOR 2 (PUF2). Preferential colocalization with canonical RAB5 on endosomes and genetic interaction analysis indicated that PUF2 coordinates vacuolar transport with canonical RAB5, although PUF2 was identified as an effector of ARA6. Competitive binding of PUF2 with GTP-bound ARA6 and GDP-bound canonical RAB5, together interacting with the shared activating factor VPS9a, showed that ARA6 negatively regulates canonical RAB5-mediated vacuolar transport by titrating PUF2 and VPS9a. These results suggest a unique and unprecedented function for a RAB effector involving the integration of two RAB groups to orchestrate endosomal trafficking in plant cells. PMID:29749929

34 CFR Appendix to Part 5 - Unknown Title

Code of Federal Regulations, 2010 CFR

2010-07-01

... the Department. Research protocol, design, processing, and other technical information to the extent... report submitted for comment prior to acceptance. Research protocol, design, processing, and other...-10) Pt. 5, App. Appendix to Part 5 [The following are some examples of specific records (or specific...

How does lower urinary tract dysfunction (LUTD) affect sexual function in men and women? ICI-RS 2015-Part 2.

PubMed

Apostolidis, Apostolos; Rantell, Angie; Anding, Ralf; Kirschner-Hermanns, Ruth; Cardozo, Linda

2017-04-01

To discuss available data on the links between LUTD and sexual dysfunction, what is still unknown about the causative effect of disease processes on sexual function (SF), and to suggest proposals for further research. At the 2015 International Consultation on Incontinence-Research Society (ICI-RS), a multi-disciplinary group presented a literature search of what is known about the effect of LUTD on SF in men and women. Wider discussions regarding knowledge gaps, and ideal research methodology ensued and are presented. The underlying mechanisms of the impact of LUTD on SF remain largely unknown. Risk factors for the metabolic syndrome may cause both LUTS and ED in men, and their improvement may improve both conditions. In women, neurovascular changes may be common in LUTD and FSD. Successful LUTS management results in FSD improvement, but the mechanisms are ill understood. Gaps in standardization of sexual dysfunction terminology, variations of assessment, and treatment in clinical practice and research make most studies not comparable. The sensitive knowledge and subjective nature of the problem present challenges and often result in neglecting it. Neurovascular and hormonal factors, but also indirect effects may link LUTD to SD in both sexes, but the evidence is not robust and the mechanisms unclear. There is a need for defining the terminology and standardizing outcomes assessed in clinical trials. The multifactorial nature of SF in both sexes makes trial design challenging and "real world" studies may prove more beneficial for patients' outcomes and clinicians' understanding. © 2017 Wiley Periodicals, Inc.

Evolutionary algorithm based heuristic scheme for nonlinear heat transfer equations.

PubMed

Ullah, Azmat; Malik, Suheel Abdullah; Alimgeer, Khurram Saleem

2018-01-01

In this paper, a hybrid heuristic scheme based on two different basis functions i.e. Log Sigmoid and Bernstein Polynomial with unknown parameters is used for solving the nonlinear heat transfer equations efficiently. The proposed technique transforms the given nonlinear ordinary differential equation into an equivalent global error minimization problem. Trial solution for the given nonlinear differential equation is formulated using a fitness function with unknown parameters. The proposed hybrid scheme of Genetic Algorithm (GA) with Interior Point Algorithm (IPA) is opted to solve the minimization problem and to achieve the optimal values of unknown parameters. The effectiveness of the proposed scheme is validated by solving nonlinear heat transfer equations. The results obtained by the proposed scheme are compared and found in sharp agreement with both the exact solution and solution obtained by Haar Wavelet-Quasilinearization technique which witnesses the effectiveness and viability of the suggested scheme. Moreover, the statistical analysis is also conducted for investigating the stability and reliability of the presented scheme.

Quantum pattern recognition with multi-neuron interactions

NASA Astrophysics Data System (ADS)

Fard, E. Rezaei; Aghayar, K.; Amniat-Talab, M.

2018-03-01

We present a quantum neural network with multi-neuron interactions for pattern recognition tasks by a combination of extended classic Hopfield network and adiabatic quantum computation. This scheme can be used as an associative memory to retrieve partial patterns with any number of unknown bits. Also, we propose a preprocessing approach to classifying the pattern space S to suppress spurious patterns. The results of pattern clustering show that for pattern association, the number of weights (η ) should equal the numbers of unknown bits in the input pattern ( d). It is also remarkable that associative memory function depends on the location of unknown bits apart from the d and load parameter α.

Interpolating Spherical Harmonics for Computing Antenna Patterns

DTIC Science & Technology

2011-07-01

4∞. If gNF denotes the spline computed from the uniform partition of NF + 1 frequency points, the splines converge as O[N−4F ]: ‖gN − g‖∞ ≤ C0‖g(4...splines. There is the possibility of estimating the error ‖g− gNF ‖∞ even though the function g is unknown. Table 1 compares these unknown errors ‖g − gNF ...to the computable estimates ‖ gNF − g2NF ‖∞. The latter is a strong predictor of the unknown error. The triple bar is the sup-norm error over all the

A Cell Model to Evaluate Chemical Effects on Adult Human Cardiac Progenitor Cell Differentiation and Function

EPA Science Inventory

Adult cardiac stem cells (CSC) and progenitor cells (CPC) represent a population of cells in the heart critical for its regeneration and function over a lifetime. The impact of chemicals on adult human CSC/CPC differentiation and function is unknown. Research was conducted to dev...

Training and Transfer Effects of Executive Functions in Preschool Children

ERIC Educational Resources Information Center

Thorell, Lisa B.; Lindqvist, Sofia; Nutley, Sissela Bergman; Bohlin, Gunilla; Klingberg, Torkel

2009-01-01

Executive functions, including working memory and inhibition, are of central importance to much of human behavior. Interventions intended to improve executive functions might therefore serve an important purpose. Previous studies show that working memory can be improved by training, but it is unknown if this also holds for inhibition, and whether…

Solutions to Kuessner's integral equation in unsteady flow using local basis functions

NASA Technical Reports Server (NTRS)

Fromme, J. A.; Halstead, D. W.

1975-01-01

The computational procedure and numerical results are presented for a new method to solve Kuessner's integral equation in the case of subsonic compressible flow about harmonically oscillating planar surfaces with controls. Kuessner's equation is a linear transformation from pressure to normalwash. The unknown pressure is expanded in terms of prescribed basis functions and the unknown basis function coefficients are determined in the usual manner by satisfying the given normalwash distribution either collocationally or in the complex least squares sense. The present method of solution differs from previous ones in that the basis functions are defined in a continuous fashion over a relatively small portion of the aerodynamic surface and are zero elsewhere. This method, termed the local basis function method, combines the smoothness and accuracy of distribution methods with the simplicity and versatility of panel methods. Predictions by the local basis function method for unsteady flow are shown to be in excellent agreement with other methods. Also, potential improvements to the present method and extensions to more general classes of solutions are discussed.

Two Person Zero-Sum Semi-Markov Games with Unknown Holding Times Distribution on One Side: A Discounted Payoff Criterion

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

Minjarez-Sosa, J. Adolfo, E-mail: aminjare@gauss.mat.uson.mx; Luque-Vasquez, Fernando

This paper deals with two person zero-sum semi-Markov games with a possibly unbounded payoff function, under a discounted payoff criterion. Assuming that the distribution of the holding times H is unknown for one of the players, we combine suitable methods of statistical estimation of H with control procedures to construct an asymptotically discount optimal pair of strategies.

Teaching-learning-based Optimization Algorithm for Parameter Identification in the Design of IIR Filters

NASA Astrophysics Data System (ADS)

Singh, R.; Verma, H. K.

2013-12-01

This paper presents a teaching-learning-based optimization (TLBO) algorithm to solve parameter identification problems in the designing of digital infinite impulse response (IIR) filter. TLBO based filter modelling is applied to calculate the parameters of unknown plant in simulations. Unlike other heuristic search algorithms, TLBO algorithm is an algorithm-specific parameter-less algorithm. In this paper big bang-big crunch (BB-BC) optimization and PSO algorithms are also applied to filter design for comparison. Unknown filter parameters are considered as a vector to be optimized by these algorithms. MATLAB programming is used for implementation of proposed algorithms. Experimental results show that the TLBO is more accurate to estimate the filter parameters than the BB-BC optimization algorithm and has faster convergence rate when compared to PSO algorithm. TLBO is used where accuracy is more essential than the convergence speed.

Design for the sacubitril/valsartan (LCZ696) compared with enalapril study of pediatric patients with heart failure due to systemic left ventricle systolic dysfunction (PANORAMA-HF study).

PubMed

Shaddy, Robert; Canter, Charles; Halnon, Nancy; Kochilas, Lazaros; Rossano, Joseph; Bonnet, Damien; Bush, Christopher; Zhao, Ziqiang; Kantor, Paul; Burch, Michael; Chen, Fabian

2017-11-01

Sacubitril/valsartan (LCZ696) is an angiotensin receptor neprilysin inhibitor approved for the treatment of adult heart failure (HF); however, the benefit of sacubitril/valsartan in pediatric HF patients is unknown. This global multi-center study will use an adaptive, seamless two-part design. Part 1 will assess the pharmacokinetics/pharmacodynamics of single ascending doses of sacubitril/valsartan in pediatric (1 month to <18 years) HF patients with systemic left ventricle and reduced left ventricular systolic function stratified into 3 age groups (Group 1: 6 to <18 years; Group 2: 1 to <6 years; Group 3: 1 month to <1 year). Part 2 is a 52-week, efficacy and safety study where 360 eligible patients will be randomized to sacubitril/valsartan or enalapril. A novel global rank primary endpoint derived by ranking patients (worst-to-best outcome) based on clinical events such as death, initiation of mechanical life support, listing for urgent heart transplant, worsening HF, measures of functional capacity (NYHA/Ross scores), and patient-reported HF symptoms will be used to assess efficacy. The PANORAMA-HF study, which will be the largest prospective pediatric HF trial conducted to date and the first to use a global rank primary endpoint, will determine whether sacubitril/valsartan is superior to enalapril for treatment of pediatric HF patients with reduced systemic left ventricular systolic function. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Robust Control Design for Uncertain Nonlinear Dynamic Systems

NASA Technical Reports Server (NTRS)

Kenny, Sean P.; Crespo, Luis G.; Andrews, Lindsey; Giesy, Daniel P.

2012-01-01

Robustness to parametric uncertainty is fundamental to successful control system design and as such it has been at the core of many design methods developed over the decades. Despite its prominence, most of the work on robust control design has focused on linear models and uncertainties that are non-probabilistic in nature. Recently, researchers have acknowledged this disparity and have been developing theory to address a broader class of uncertainties. This paper presents an experimental application of robust control design for a hybrid class of probabilistic and non-probabilistic parametric uncertainties. The experimental apparatus is based upon the classic inverted pendulum on a cart. The physical uncertainty is realized by a known additional lumped mass at an unknown location on the pendulum. This unknown location has the effect of substantially altering the nominal frequency and controllability of the nonlinear system, and in the limit has the capability to make the system neutrally stable and uncontrollable. Another uncertainty to be considered is a direct current motor parameter. The control design objective is to design a controller that satisfies stability, tracking error, control power, and transient behavior requirements for the largest range of parametric uncertainties. This paper presents an overview of the theory behind the robust control design methodology and the experimental results.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

PubMed

Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

2018-05-01

High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Molecular definition of the identity and activation of natural killer cells.

PubMed

Bezman, Natalie A; Kim, Charles C; Sun, Joseph C; Min-Oo, Gundula; Hendricks, Deborah W; Kamimura, Yosuke; Best, J Adam; Goldrath, Ananda W; Lanier, Lewis L

2012-10-01

Using whole-genome microarray data sets of the Immunological Genome Project, we demonstrate a closer transcriptional relationship between NK cells and T cells than between any other leukocytes, distinguished by their shared expression of genes encoding molecules with similar signaling functions. Whereas resting NK cells are known to share expression of a few genes with cytotoxic CD8(+) T cells, our transcriptome-wide analysis demonstrates that the commonalities extend to hundreds of genes, many encoding molecules with unknown functions. Resting NK cells demonstrate a 'preprimed' state compared with naive T cells, which allows NK cells to respond more rapidly to viral infection. Collectively, our data provide a global context for known and previously unknown molecular aspects of NK cell identity and function by delineating the genome-wide repertoire of gene expression of NK cells in various states.

Backstepping Design of Adaptive Neural Fault-Tolerant Control for MIMO Nonlinear Systems.

PubMed

Gao, Hui; Song, Yongduan; Wen, Changyun

In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.In this paper, an adaptive controller is developed for a class of multi-input and multioutput nonlinear systems with neural networks (NNs) used as a modeling tool. It is shown that all the signals in the closed-loop system with the proposed adaptive neural controller are globally uniformly bounded for any external input in . In our control design, the upper bound of the NN modeling error and the gains of external disturbance are characterized by unknown upper bounds, which is more rational to establish the stability in the adaptive NN control. Filter-based modification terms are used in the update laws of unknown parameters to improve the transient performance. Finally, fault-tolerant control is developed to accommodate actuator failure. An illustrative example applying the adaptive controller to control a rigid robot arm shows the validation of the proposed controller.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Optimal design of high-rise buildings with respect to fundamental eigenfrequency

NASA Astrophysics Data System (ADS)

Alavi, Arsalan; Rahgozar, Reza; Torkzadeh, Peyman; Hajabasi, Mohamad Ali

2017-12-01

In modern tall and slender structures, dynamic responses are usually the dominant design requirements, instead of strength criteria. Resonance is often a threatening phenomenon for such structures. To avoid this problem, the fundamental eigenfrequency, an eigenfrequency of higher order, should be maximized. An optimization problem with this objective is constructed in this paper and is applied to a high-rise building. Using variational method, the objective function is maximized, contributing to a particular profile for the first mode shape. Based on this preselected profile, a parametric formulation for flexural stiffness is calculated. Due to some near-zero values for stiffness, the obtained formulation will be modified by adding a lower bound constraint. To handle this constraint some new parameters are introduced; thereby allowing for construction of a model relating the unknown parameters. Based on this mathematical model, a design algorithmic procedure is presented. For the sake of convenience, a single-input design graph is presented as well. The main merit of the proposed method, compared to previous researches, is its hand calculation aspect, suitable for parametric studies and sensitivity analysis. As the presented formulations are dimensionless, they are applicable in any dimensional system. Accuracy and practicality of the proposed method is illustrated at the end by applying it to a real-life structure.

Masters of defence: biomechanics of stinging nettles

NASA Astrophysics Data System (ADS)

Jensen, Kaare H.; Knoblauch, Jan

2017-11-01

The techniques employed by plants and animals to defend themselves are very varied. Some involve extremely refined armaments. Stinging nettles employ hollow needle-like stinging hairs constructed from silica, the mineral from which we make glass, and they are filled with poison. The hairs are remarkably rigid and rarely break. Yet the tip is so sharp that the slightest touch cuts human skin, and so fragile that it breaks at that touch and releases poison into the wound. How the seemingly antagonist mechanical functions of rigidity and fragility are achieved, however, is unknown. We combine experiments on real and synthetic stingers to elucidate the poison injection mechanism. The design of plant stingers is compared to other natural systems and optimal stinging strategies are discussed. This work was supported by a research Grant (13166) from VILLUM FONDEN.

QSAR Study and Molecular Design of Open-Chain Enaminones as Anticonvulsant Agents

PubMed Central

Garro Martinez, Juan C.; Duchowicz, Pablo R.; Estrada, Mario R.; Zamarbide, Graciela N.; Castro, Eduardo A.

2011-01-01

Present work employs the QSAR formalism to predict the ED50 anticonvulsant activity of ringed-enaminones, in order to apply these relationships for the prediction of unknown open-chain compounds containing the same types of functional groups in their molecular structure. Two different modeling approaches are applied with the purpose of comparing the consistency of our results: (a) the search of molecular descriptors via multivariable linear regressions; and (b) the calculation of flexible descriptors with the CORAL (CORrelation And Logic) program. Among the results found, we propose some potent candidate open-chain enaminones having ED50 values lower than 10 mg·kg−1 for corresponding pharmacological studies. These compounds are classified as Class 1 and Class 2 according to the Anticonvulsant Selection Project. PMID:22272137

Ecosystem Services Connect Environmental Change to Human Health Outcomes

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

Bayles, Brett R.; Brauman, Kate A.; Adkins, Joshua N.

Global environmental change, driven in large part by human activities, profoundly impacts the structure and functioning of Earth’s ecosystems (Millennium Ecosystem Assessment 2005). We are beginning to push beyond planetary boundaries (Steffan et al. 2015), and the consequences for human health remain largely unknown (Myers et al. 2013). Growing evidence suggests that ecological transformations can dramatically affect human health in ways that are both obvious and obscure (Myers and Patz 2009; Myers et al. 2013). The framework of ecosystem services, designed to evaluate the benefits that people derive from ecosystem products and processes, provides a compelling framework for integrating themore » many factors that influence the human health response to global change, as well as for integrating health impacts into broader analyses of the impacts of this change« less

Self-Learning Variable Structure Control for a Class of Sensor-Actuator Systems

PubMed Central

Chen, Sanfeng; Li, Shuai; Liu, Bo; Lou, Yuesheng; Liang, Yongsheng

2012-01-01

Variable structure strategy is widely used for the control of sensor-actuator systems modeled by Euler-Lagrange equations. However, accurate knowledge on the model structure and model parameters are often required for the control design. In this paper, we consider model-free variable structure control of a class of sensor-actuator systems, where only the online input and output of the system are available while the mathematic model of the system is unknown. The problem is formulated from an optimal control perspective and the implicit form of the control law are analytically obtained by using the principle of optimality. The control law and the optimal cost function are explicitly solved iteratively. Simulations demonstrate the effectiveness and the efficiency of the proposed method. PMID:22778633

A Stochastic Total Least Squares Solution of Adaptive Filtering Problem

PubMed Central

Ahmad, Noor Atinah

2014-01-01

An efficient and computationally linear algorithm is derived for total least squares solution of adaptive filtering problem, when both input and output signals are contaminated by noise. The proposed total least mean squares (TLMS) algorithm is designed by recursively computing an optimal solution of adaptive TLS problem by minimizing instantaneous value of weighted cost function. Convergence analysis of the algorithm is given to show the global convergence of the proposed algorithm, provided that the stepsize parameter is appropriately chosen. The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. It provides minimum mean square deviation by exhibiting better convergence in misalignment for unknown system identification under noisy inputs. PMID:24688412

New fossils from Tadkeshwar Mine (Gujarat, India) increase primate diversity from the early Eocene Cambay Shale.

PubMed

Rose, Kenneth D; Dunn, Rachel H; Kumar, Kishor; Perry, Jonathan M G; Prufrock, Kristen A; Rana, Rajendra S; Smith, Thierry

2018-06-07

Several new fossil specimens from the Cambay Shale Formation at Tadkeshwar Lignite Mine in Gujarat document the presence of two previously unknown early Eocene primate species from India. A new species of Asiadapis is named based on a jaw fragment preserving premolars similar in morphology to those of A. cambayensis but substantially larger. Also described is an exceptionally preserved edentulous dentary (designated cf. Asiadapis, unnamed sp. nov.) that is slightly larger and much more robust than previously known Cambay Shale primates. Its anatomy most closely resembles that of Eocene adapoids, and the dental formula is the same as in A. cambayensis. A femur and calcaneus are tentatively allocated to the same taxon. Although the dentition is unknown, exquisite preservation of the dentary of cf. Asiadapis sp. nov. enables an assessment of masticatory musculature, function, and gape adaptations, as well as comparison with an equally well-preserved dentary of the asiadapid Marcgodinotius indicus, also from Tadkeshwar. The new M. indicus specimen shows significant gape adaptations but was probably capable of only weak bite force, whereas cf. Asiadapis sp. nov. probably used relatively smaller gapes but could generate relatively greater bite forces. Copyright © 2018 Elsevier Ltd. All rights reserved.

Directly data processing algorithm for multi-wavelength pyrometer (MWP).

PubMed

Xing, Jian; Peng, Bo; Ma, Zhao; Guo, Xin; Dai, Li; Gu, Weihong; Song, Wenlong

2017-11-27

Data processing of multi-wavelength pyrometer (MWP) is a difficult problem because unknown emissivity. So far some solutions developed generally assumed particular mathematical relations for emissivity versus wavelength or emissivity versus temperature. Due to the deviation between the hypothesis and actual situation, the inversion results can be seriously affected. So directly data processing algorithm of MWP that does not need to assume the spectral emissivity model in advance is main aim of the study. Two new data processing algorithms of MWP, Gradient Projection (GP) algorithm and Internal Penalty Function (IPF) algorithm, each of which does not require to fix emissivity model in advance, are proposed. The novelty core idea is that data processing problem of MWP is transformed into constraint optimization problem, then it can be solved by GP or IPF algorithms. By comparison of simulation results for some typical spectral emissivity models, it is found that IPF algorithm is superior to GP algorithm in terms of accuracy and efficiency. Rocket nozzle temperature experiment results show that true temperature inversion results from IPF algorithm agree well with the theoretical design temperature as well. So the proposed combination IPF algorithm with MWP is expected to be a directly data processing algorithm to clear up the unknown emissivity obstacle for MWP.

Linking product design to consumer behavior: the moderating role of consumption experience

PubMed Central

Gilal, Naeem Gul; Zhang, Jing; Gilal, Faheem Gul

2018-01-01

Background Previous investigations of product design broadly link aesthetic, functional, and symbolic designs to sales growth, high turnover, and market share. However, the effect of product design dimensions on consumer willingness-to-buy (WTB) and word-of-mouth (WOM) is virtually ignored by consumer researchers. Similarly, whether the consumption experience can differentiate the effect of the three product design dimensions on WTB and WOM is completely unknown. Using categorization theory as a lens, our study aims to explore the effect of product design dimensions on consumer WTB and WOM directly and indirectly through the moderation of the consumption experience. Methods A convenience sample of (n=357) Chinese and (n=277) Korean shoppers was utilized to test the hypotheses in the fashion apparel industry. Results Our results showed that the aesthetic design was more prominent in capturing consumer WTB for both Chinese and Koreans. Similarly, the aesthetic design was more salient in enhancing WOM for Chinese, whereas the symbolic design was more promising in terms of improving WOM for Koreans. Further, our moderation results demonstrated that the consumption experience could differentiate the effects of the three product design dimensions on consumer WTB and WOM for Chinese. By contrast, the consumption experience could only interact with the aesthetic design to improve WOM for South Koreans. Conclusion To the best of authors’ knowledge, the present study is one of the initial attempts to link three product design dimensions with consumer WTB and WOM in the fashion apparel context and explored whether consumption experience competes or complement with three product design dimensions to shape consumer WTB and WOM for Chinese and Koreans. PMID:29785145

Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models

USDA-ARS?s Scientific Manuscript database

Cumulative nitrous oxide (N2O) emissions calculated from discrete chamber-based flux measurements have unknown uncertainty. This study used an agroecosystems simulation model to design sampling strategies that yield accurate cumulative N2O flux estimates with a known uncertainty level. Daily soil N2...

The Hungry Fly: Hydrodynamics of feeding in the common house fly

NASA Astrophysics Data System (ADS)

Prakash, Manu; Steele, Miles

2010-11-01

A large number of insect species feed primarily on a fluid diet. To do so, they must overcome the numerous challenges that arise in the design of high-efficiency, miniature pumps. Although the morphology of insect feeding structures has been described for decades, their dynamics remain largely unknown even in the most well studied species (e.g. fruit fly). Here, we use invivo imaging and microsurgery to elucidate the design principles of feeding structures of the common house fly. Using high-resolution X-ray microscopy, we record invivo flow of sucrose solutions through the body over many hours during fly feeding. Borrowing from microsurgery techniques common in neurophysiology, we are able to perturb the pump to a stall position and thus evaluate function under load conditions. Furthermore, fluid viscosity-dependent feedback is observed for optimal pump performance. As the gut of the fly starts to fill up, feedback from the stretch receptors in the cuticle dictates the effective flow rate. Finally, via comparative analysis between the house fly, blow fly, fruit fly and bumble bees, we highlight the common design principles and the role of interfacial phenomena in feeding.

Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form.

PubMed

Jagannathan, Sarangapani; He, Pingan

2008-12-01

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights in order to attain the near-optimal control action. Both the NN control methods present a well-defined controller design and the noncausal problem in discrete-time backstepping design is avoided via NN approximation. A comparison between the controller methodologies is highlighted. The stability analysis of the closed-loop control schemes is demonstrated. The NN controller schemes do not require an offline learning phase and the NN weights can be initialized at zero or random. Results show that the performance of the proposed controller schemes is highly satisfactory while meeting the closed-loop stability.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions.

PubMed

Wuchty, S; Rajagopala, S V; Blazie, S M; Parrish, J R; Khuri, S; Finley, R L; Uetz, P

2017-01-01

The functions of roughly a third of all proteins in Streptococcus pneumoniae , a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein's function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae . We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae , the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins.

Classification of longitudinal data through a semiparametric mixed-effects model based on lasso-type estimators.

PubMed

Arribas-Gil, Ana; De la Cruz, Rolando; Lebarbier, Emilie; Meza, Cristian

2015-06-01

We propose a classification method for longitudinal data. The Bayes classifier is classically used to determine a classification rule where the underlying density in each class needs to be well modeled and estimated. This work is motivated by a real dataset of hormone levels measured at the early stages of pregnancy that can be used to predict normal versus abnormal pregnancy outcomes. The proposed model, which is a semiparametric linear mixed-effects model (SLMM), is a particular case of the semiparametric nonlinear mixed-effects class of models (SNMM) in which finite dimensional (fixed effects and variance components) and infinite dimensional (an unknown function) parameters have to be estimated. In SNMM's maximum likelihood estimation is performed iteratively alternating parametric and nonparametric procedures. However, if one can make the assumption that the random effects and the unknown function interact in a linear way, more efficient estimation methods can be used. Our contribution is the proposal of a unified estimation procedure based on a penalized EM-type algorithm. The Expectation and Maximization steps are explicit. In this latter step, the unknown function is estimated in a nonparametric fashion using a lasso-type procedure. A simulation study and an application on real data are performed. © 2015, The International Biometric Society.

Structural RNAs of known and unknown function identified in malaria parasites by comparative genomics and RNA analysis

PubMed Central

Chakrabarti, Kausik; Pearson, Michael; Grate, Leslie; Sterne-Weiler, Timothy; Deans, Jonathan; Donohue, John Paul; Ares, Manuel

2007-01-01

As the genomes of more eukaryotic pathogens are sequenced, understanding how molecular differences between parasite and host might be exploited to provide new therapies has become a major focus. Central to cell function are RNA-containing complexes involved in gene expression, such as the ribosome, the spliceosome, snoRNAs, RNase P, and telomerase, among others. In this article we identify by comparative genomics and validate by RNA analysis numerous previously unknown structural RNAs encoded by the Plasmodium falciparum genome, including the telomerase RNA, U3, 31 snoRNAs, as well as previously predicted spliceosomal snRNAs, SRP RNA, MRP RNA, and RNAse P RNA. Furthermore, we identify six new RNA coding genes of unknown function. To investigate the relationships of the RNA coding genes to other genomic features in related parasites, we developed a genome browser for P. falciparum (http://areslab.ucsc.edu/cgi-bin/hgGateway). Additional experiments provide evidence supporting the prediction that snoRNAs guide methylation of a specific position on U4 snRNA, as well as predicting an snRNA promoter element particular to Plasmodium sp. These findings should allow detailed structural comparisons between the RNA components of the gene expression machinery of the parasite and its vertebrate hosts. PMID:17901154

Nucleotide sequence and phylogenetic analysis of Cucurbit yellow stunting disorder virus RNA 2.

PubMed

Livieratos, Ioannis C; Coutts, Robert H A

2002-06-01

The complete nucleotide sequence of Cucurbit yellow stunting disorder virus (CYSDV) RNA 2, a whitefly (Bemisia tabaci)-transmitted closterovirus with a bi-partite genome, is reported. CYSDV RNA 2 is 7,281 nucleotides long and contains the closterovirus hallmark gene array with a similar arrangement to the prototype member of the genus Crinivirus, Lettuce infectious yellows virus (LIYV). CYSDV RNA 2 contains open reading frames (ORFs) potentially encoding in a 5' to 3' direction for proteins of 5 kDa (ORF 1; hydrophobic protein), 62 kDa (ORF 2; heat shock protein 70 homolog, HSP70h), 59 kDa (ORF 3; protein of unknown function), 9 kDa (ORF 4; protein of unknown function), 28.5 kDa (ORF 5; coat protein, CP), 53 kDa (ORF 6; coat protein minor, CPm), and 26.5 kDa (ORF 7; protein of unknown function). Pairwise comparisons of CYSDV RNA 2-encoded proteins (HSP70h, p59 and CPm) among the closteroviruses showed that CYSDV is closely related to LIYV. Phylogenetic analysis based on the amino acid sequence of the HSP70h, indicated that CYSDV clusters with other members of the genus Crinivirus, and it is related to Little cherry virus-1 (LChV-1), but is distinct from the aphid- or mealybug-transmitted closteroviruses.

Chemo-enzymatic synthesis of physiologically modified avenanthramides

USDA-ARS?s Scientific Manuscript database

Avenanthramides are a group of phenolic alkaloids produced, among food crops, uniquely by oats. These metabolites function as phytoalexins in vegetative tissue and they are produced in the grain where their function is unknown. In vitro the avenanthramides inhibit the activation of nuclear factor ka...

Prostatic acid phosphatase is an ectonucleotidase and suppresses pain by generating adenosine

PubMed Central

Zylka, Mark J.; Sowa, Nathaniel A.; Taylor-Blake, Bonnie; Twomey, Margaret A.; Herrala, Annakaisa; Voikar, Vootele; Vihko, Pirkko

2008-01-01

SUMMARY Thiamine monophosphatase (TMPase, also known as Fluoride-Resistant Acid Phosphatase) is a classic histochemical marker of small-diameter dorsal root ganglia neurons. The molecular identity of TMPase is currently unknown. We found that TMPase is identical to the transmembrane isoform of Prostatic Acid Phosphatase (PAP), an enzyme with unknown molecular and physiological functions. We then found that PAP knockout mice have normal acute pain sensitivity but enhanced sensitivity in chronic inflammatory and neuropathic pain models. In gain-of-function studies, intraspinal injection of PAP protein has potent anti-nociceptive, anti-hyperalgesic and anti-allodynic effects that last longer than the opioid analgesic morphine. PAP suppresses pain by functioning as an ecto-5’-nucleotidase. Specifically, PAP dephosphorylates extracellular adenosine monophosphate (AMP) to adenosine and activates A1-adenosine receptors in dorsal spinal cord. Our studies reveal molecular and physiological functions for PAP in purine nucleotide metabolism and nociception and suggest a novel use for PAP in the treatment of chronic pain. PMID:18940592

Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

NASA Technical Reports Server (NTRS)

Shaeffer, John

2008-01-01

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.

Subgenual anterior cingulate cortex controls sadness-induced modulations of cognitive and emotional network hubs.

PubMed

Ramirez-Mahaluf, Juan P; Perramon, Joan; Otal, Begonya; Villoslada, Pablo; Compte, Albert

2018-06-04

The regulation of cognitive and emotional processes is critical for proper executive functions and social behavior, but its specific mechanisms remain unknown. Here, we addressed this issue by studying with functional magnetic resonance imaging the changes in network topology that underlie competitive interactions between emotional and cognitive networks in healthy participants. Our behavioral paradigm contrasted periods with high emotional and cognitive demands by including a sadness provocation task followed by a spatial working memory task. The sharp contrast between successive tasks was designed to enhance the separability of emotional and cognitive networks and reveal areas that regulate the flow of information between them (hubs). By applying graph analysis methods on functional connectivity between 20 regions of interest in 22 participants we identified two main brain network modules, one dorsal and one ventral, and their hub areas: the left dorsolateral prefrontal cortex (dlPFC) and the left medial frontal pole (mFP). These hub areas did not modulate their mutual functional connectivity following sadness but they did so through an interposed area, the subgenual anterior cingulate cortex (sACC). Our results identify dlPFC and mFP as areas regulating interactions between emotional and cognitive networks, and suggest that their modulation by sadness experience is mediated by sACC.

Adaptive super-twisting observer for estimation of random road excitation profile in automotive suspension systems.

PubMed

Rath, J J; Veluvolu, K C; Defoort, M

2014-01-01

The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system.

Adaptive Super-Twisting Observer for Estimation of Random Road Excitation Profile in Automotive Suspension Systems

PubMed Central

Rath, J. J.; Veluvolu, K. C.; Defoort, M.

2014-01-01

The estimation of road excitation profile is important for evaluation of vehicle stability and vehicle suspension performance for autonomous vehicle control systems. In this work, the nonlinear dynamics of the active automotive system that is excited by the unknown road excitation profile are considered for modeling. To address the issue of estimation of road profile, we develop an adaptive supertwisting observer for state and unknown road profile estimation. Under Lipschitz conditions for the nonlinear functions, the convergence of the estimation error is proven. Simulation results with Ford Fiesta MK2 demonstrate the effectiveness of the proposed observer for state and unknown input estimation for nonlinear active suspension system. PMID:24683321

Closing the gap on Achilles tendon rupture: A cadaveric study quantifying the tendon apposition achieved with commonly used immobilisation practices.

PubMed

Collins, Ruaraidh; Sudlow, Alexis; Loizou, Constantinos; Loveday, David T; Smith, George

2018-04-01

The relative benefits of surgical and conservative treatment of Achilles tendon rupture are widely debated. With modern conservative management protocols, the re-rupture risk appears to fall to one similar to surgical repair with negligible loss of function. Conservative management typically employs a period of time in an equinus cast with sequential ankle dorsiflexion in a functional orthosis. The optimal duration of immobilisation and rate of dorsiflexion is unknown. We aimed to quantify the change in Achilles tendon approximation achieved in common immobilisation techniques to assist the design of rehabilitation protocols. Twelve fresh-frozen cadaveric specimens had 2.5cm of Achilles tendon excised. The gap between the tendon ends were measured via windowed full equinus casts and compared with functional boots with successively removed heel wedges. The greatest tendon apposition was achieved with the equinus cast. Each wedge removed decreased the reapproximation by approximately 5mm. This paper supports the early use of maximal equinus casting in early management of acute Achilles tendon ruptures. Copyright © 2017 European Foot and Ankle Society. Published by Elsevier Ltd. All rights reserved.

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

The influence of iron on the proteomic profile of Chromobacterium violaceum.

PubMed

Lima, Daniel C; Duarte, Fábio T; Medeiros, Viviane K S; Lima, Diogo B; Carvalho, Paulo C; Bonatto, Diego; Batistuzzo de Medeiros, Silvia R

2014-10-20

Chromobacterium violaceum is a bacterium commonly found in tropical and subtropical regions and is associated with important pharmacological and industrial attributes such as producing substances with therapeutic properties and synthesizing biodegradable polymers. Its genome was sequenced, however, approximately 40% of its genes still remain with unknown functions. Although C. violaceum is known by its versatile capacity of living in a wide range of environments, little is known on how it achieves such success. Here, we investigated the proteomic profile of C. violaceum cultivated in the absence and presence of high iron concentration, describing some proteins of unknown function that might play an important role in iron homeostasis, amongst others. Briefly, C. violaceum was cultivated in the absence and in the presence of 9 mM of iron during four hours. Total proteins were identified by LC-MS and through the PatternLab pipeline. Our proteomic analysis indicates major changes in the energetic metabolism, and alterations in the synthesis of key transport and stress proteins. In addition, it may suggest the presence of a yet unidentified operon that could be related to oxidative stress, together with a set of other proteins with unknown function. The protein-protein interaction network also pinpointed the importance of energetic metabolism proteins to the acclimatation of C. violaceum in high concentration of iron. This is the first proteomic analysis of the opportunistic pathogen C. violaceum in the presence of high iron concentration. Our data allowed us to identify a yet undescribed operon that might have a role in oxidative stress defense. Our work provides new data that will contribute to understand how this bacterium achieve its capacity of surviving in harsh conditions as well as to open a way to explore the yet little availed biotechnological characteristics of this bacterium with the further exploring of the proteins of unknown function that we showed to be up-regulated in high iron concentration.

Extension of the lod score: the mod score.

PubMed

Clerget-Darpoux, F

2001-01-01

In 1955 Morton proposed the lod score method both for testing linkage between loci and for estimating the recombination fraction between them. If a disease is controlled by a gene at one of these loci, the lod score computation requires the prior specification of an underlying model that assigns the probabilities of genotypes from the observed phenotypes. To address the case of linkage studies for diseases with unknown mode of inheritance, we suggested (Clerget-Darpoux et al., 1986) extending the lod score function to a so-called mod score function. In this function, the variables are both the recombination fraction and the disease model parameters. Maximizing the mod score function over all these parameters amounts to maximizing the probability of marker data conditional on the disease status. Under the absence of linkage, the mod score conforms to a chi-square distribution, with extra degrees of freedom in comparison to the lod score function (MacLean et al., 1993). The mod score is asymptotically maximum for the true disease model (Clerget-Darpoux and Bonaïti-Pellié, 1992; Hodge and Elston, 1994). Consequently, the power to detect linkage through mod score will be highest when the space of models where the maximization is performed includes the true model. On the other hand, one must avoid overparametrization of the model space. For example, when the approach is applied to affected sibpairs, only two constrained disease model parameters should be used (Knapp et al., 1994) for the mod score maximization. It is also important to emphasize the existence of a strong correlation between the disease gene location and the disease model. Consequently, there is poor resolution of the location of the susceptibility locus when the disease model at this locus is unknown. Of course, this is true regardless of the statistics used. The mod score may also be applied in a candidate gene strategy to model the potential effect of this gene in the disease. Since, however, it ignores the information provided both by disease segregation and by linkage disequilibrium between the marker alleles and the functional disease alleles, its power of discrimination between genetic models is weak. The MASC method (Clerget-Darpoux et al., 1988) has been designed to address more efficiently the objectives of a candidate gene approach.

An interprofessional palliative care oncology rehabilitation program: effects on function and predictors of program completion.

PubMed

Chasen, M R; Feldstain, A; Gravelle, D; Macdonald, N; Pereira, J

2013-12-01

After treatment, patients with active cancer face a considerable burden from the effects of both the disease and its treatment. The Palliative Rehabilitation Program (prp) is designed to ameliorate disease effects and to improve the patient's functioning. The present study evaluated predictors of program completion and changes in functioning, symptoms, and well-being after the program. The program received referrals for 173 patients who had finished anticancer therapy. Of those 173 patients, 116 with advanced cancer were eligible and enrolled in the 8-week interprofessional prp; 67 completed it. Measures of physical, nutritional, social, and psychological functioning were evaluated at entry to the program and at completion. Participants experienced significant improvements in physical performance (p < 0.000), nutrition (p = 0.001), symptom severity (p = 0.005 to 0.001), symptom interference with functioning (p = 0.003 to 0.001), fatigue (p = 0.001), and physical endurance, mobility, and balance or function (p = 0.001 to 0.001). Reasons that participants did not complete the prp were disease progression, geographic inaccessibility, being too well (program not challenging enough), death, and personal or unknown reasons. A normal level of C-reactive protein (<10 mg/L, p = 0.029) was a predictor of program completion. Patients living with advanced cancers who underwent the interprofessional prp experienced significant improvement in functioning across several domains. Program completion can be predicted by a normal level of C-reactive protein.

Survivorship and functional outcomes of patellofemoral arthroplasty: a systematic review.

PubMed

van der List, J P; Chawla, H; Zuiderbaan, H A; Pearle, A D

2017-08-01

Historically poor results of survivorship and functional outcomes of patellofemoral arthroplasty (PFA) have been reported in the setting of isolated patellofemoral osteoarthritis. More recently, however, fairly good results of PFA were reported, but the current status of PFA outcomes is unknown. Therefore, a systematic review was performed to assess overall PFA survivorship and functional outcomes. A search was performed using PubMed, Embase and Cochrane systems, and the registries were searched. Twenty-three cohort studies and one registry reported survivorship using Kaplan-Meier curve, while 51 cohort studies reported functional outcomes of PFA. Twelve studies were level II studies, while 45 studies were level III or IV studies. Heterogeneity was mainly seen in type of prosthesis and year the cohort started. Nine hundred revisions in 9619 PFAs were reported yielding 5-, 10-, 15- and 20-year PFA survivorships of 91.7, 83.3, 74.9 and 66.6 %, respectively, and an annual revision rate of 2.18. Functional outcomes were reported in 2587 PFAs with an overall score of 82.2 % of the maximum score. KSS and Knee Function Score were 87.5 and 81.6 %, respectively. This systematic review showed that fairly good results of PFA survivorship and functional outcomes were reported at short- and midterm follow-up in the setting of isolated patellofemoral osteoarthritis. Heterogeneity existed mainly in prosthesis design and year the cohort started. These results provide a clear overview of the current status of PFA in the setting of isolated patellofemoral osteoarthritis. IV.

Leading singularities and off-shell conformal integrals

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

Drummond, James; Duhr, Claude; Eden, Burkhard

2013-08-29

The three-loop four-point function of stress-tensor multiplets in N=4 super Yang-Mills theory contains two so far unknown, off-shell, conformal integrals, in addition to the known, ladder-type integrals. In our paper we evaluate the unknown integrals, thus obtaining the three-loop correlation function analytically. The integrals have the generic structure of rational functions multiplied by (multiple) polylogarithms. We use the idea of leading singularities to obtain the rational coefficients, the symbol — with an appropriate ansatz for its structure — as a means of characterising multiple polylogarithms, and the technique of asymptotic expansion of Feynman integrals to obtain the integrals in certainmore » limits. The limiting behaviour uniquely fixes the symbols of the integrals, which we then lift to find the corresponding polylogarithmic functions. The final formulae are numerically confirmed. Furthermore, we develop techniques that can be applied more generally, and we illustrate this by analytically evaluating one of the integrals contributing to the same four-point function at four loops. This example shows a connection between the leading singularities and the entries of the symbol.« less

An Augmented Pocketome: Detection and Analysis of Small-Molecule Binding Pockets in Proteins of Known 3D Structure.

PubMed

Bhagavat, Raghu; Sankar, Santhosh; Srinivasan, Narayanaswamy; Chandra, Nagasuma

2018-03-06

Protein-ligand interactions form the basis of most cellular events. Identifying ligand binding pockets in proteins will greatly facilitate rationalizing and predicting protein function. Ligand binding sites are unknown for many proteins of known three-dimensional (3D) structure, creating a gap in our understanding of protein structure-function relationships. To bridge this gap, we detect pockets in proteins of known 3D structures, using computational techniques. This augmented pocketome (PocketDB) consists of 249,096 pockets, which is about seven times larger than what is currently known. We deduce possible ligand associations for about 46% of the newly identified pockets. The augmented pocketome, when subjected to clustering based on similarities among pockets, yielded 2,161 site types, which are associated with 1,037 ligand types, together providing fold-site-type-ligand-type associations. The PocketDB resource facilitates a structure-based function annotation, delineation of the structural basis of ligand recognition, and provides functional clues for domains of unknown functions, allosteric proteins, and druggable pockets. Copyright © 2018 Elsevier Ltd. All rights reserved.

Osiris9a is a major component of silk fiber in lepidopteran insects.

PubMed

Liu, Chun; Hu, Wenbo; Cheng, Tingcai; Peng, Zhangchuan; Mita, Kazuei; Xia, Qingyou

2017-10-01

In a previous high-throughput proteomics study, it was found that the silkworm cocoon contains hundreds of complex proteins, many of which have unknown functions, in addition to fibroins, sericins, and some protease inhibitors. Osiris was one of the proteins with no known function. In this study, we identified the Osiris gene family members and constructed a phylogenetic tree based on the sequences from different species. Our results indicate that the Osiris9 gene subfamily contains six members; it is specifically expressed in lepidopteran insects and has evolved by gene duplication. An Osiris gene family member from Bombyx mori was designated as BmOsiris9a (BmOsi9a) on the basis of its homology to Drosophila melanogaster Osiris9. The expression pattern of BmOsi9a showed that it was highly expressed only in the middle silk gland of silkworm larvae, similar to Sericin1 (Ser1). BmOsi9a was visualized as two bands in western blot analysis, implying that it probably undergoes post-translational modifications. Immunohistochemistry analysis revealed that BmOsi9a was synthesized and secreted into the lumen of the middle silk gland, and was localized in the sericin layer in the silk fiber. BmOsi9a was found in the silk fibers of not only three Bombycidae species, viz. B. mori, B. mandarina, and B. huttoni, but also in the fibers collected from Saturniidae species, including Antheraea assama, Antheraea mylitta, and Samia cynthia. Although the exact biological function of Osi9a in the silk fibers is unknown, our results are important because they demonstrate that Osi9a is a common structural component of silk fiber and is expressed widely among the silk-producing Bombycidae and Saturniidae insects. Our results should help in understanding the role of Osi9a in silk fibers. Copyright © 2017 Elsevier Ltd. All rights reserved.

Clinical Examination Results in Individuals With Functional Ankle Instability and Ankle-Sprain Copers

PubMed Central

Wright, Cynthia J.; Arnold, Brent L.; Ross, Scott E.; Ketchum, Jessica; Ericksen, Jeffrey; Pidcoe, Peter

2013-01-01

Context: Why some individuals with ankle sprains develop functional ankle instability and others do not (ie, copers) is unknown. Current understanding of the clinical profile of copers is limited. Objective: To contrast individuals with functional ankle instability (FAI), copers, and uninjured individuals on both self-reported variables and clinical examination findings. Design: Cross-sectional study. Setting: Sports medicine research laboratory. Patients or Other Participants: Participants consisted of 23 individuals with a history of 1 or more ankle sprains and at least 2 episodes of giving way in the past year (FAI: Cumberland Ankle Instability Tool [CAIT] score = 20.52 ± 2.94, episodes of giving way = 5.8 ± 8.4 per month), 23 individuals with a history of a single ankle sprain and no subsequent episodes of instability (copers: CAIT score = 27.74 ± 1.69), and 23 individuals with no history of ankle sprain and no instability (uninjured: CAIT score = 28.78 ± 1.78). Intervention(s): Self-reported disability was recorded using the CAIT and Foot and Ankle Ability Measure for Activities of Daily Living and for Sports. On clinical examination, ligamentous laxity and tenderness, range of motion (ROM), and pain at end ROM were recorded. Main Outcome Measure(s): Questionnaire scores for the CAIT, Foot and Ankle Ability Measure for Activities of Daily Living and for Sports, ankle inversion and anterior drawer laxity scores, pain with palpation of the lateral ligaments, ankle ROM, and pain at end ROM. Results: Individuals with FAI had greater self-reported disability for all measures (P < .05). On clinical examination, individuals with FAI were more likely to have greater talar tilt laxity, pain with inversion, and limited sagittal-plane ROM than copers (P < .05). Conclusions: Differences in both self-reported disability and clinical examination variables distinguished individuals with FAI from copers at least 1 year after injury. Whether the deficits could be detected immediately postinjury to prospectively identify potential copers is unknown. PMID:23914879

Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

PubMed Central

Xu, Min; Wang, Yemin; Zhao, Zhilong; Gao, Guixi; Huang, Sheng-Xiong; Kang, Qianjin; He, Xinyi; Lin, Shuangjun; Pang, Xiuhua; Deng, Zixin

2016-01-01

ABSTRACT Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei. This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways. IMPORTANCE Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces. The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic from Streptomyces rochei Sal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery. PMID:27451447

Metastatic Neuroendocrine Carcinoma of Unknown Origin Arising in the Femoral Nerve Sheath.

PubMed

Candy, Nicholas; Young, Adam; Allinson, Kieren; Carr, Oliver; McMillen, Jason; Trivedi, Rikin

2017-08-01

Metastatic neuroendocrine carcinoma of unknown origin is a rare condition, usually presenting with lesions in the liver and/or lung. We present the first reported case of a metastatic neuroendocrine carcinoma of unknown origin arising in the femoral nerve sheath. Magnetic resonance imaging demonstrated what was thought to be a schwannoma in the left femoral nerve sheath in the proximal femoral triangle, immediately inferior to the anterior inferior iliac spine. At the time of operation, the tumor capsule was invading surrounding tissue, as well as three trunks of the femoral nerve. The patient underwent a subtotal resection, preserving the integrity of the residual functioning femoral nerve trunks. Histologic evaluation determined that the tumor had features consistent with a metastatic neuroendocrine carcinoma of unknown primary origin. The patient recovered well postoperatively, and subsequent radiologic evaluation failed to demonstrate a potential primary site. Unfortunately, the patient re-presented with disease progression and was subsequently referred to palliative care. We recommend that there is a definite role for surgery in the management of solitary neuroendocrine carcinoma of unknown origin. Copyright © 2017 Elsevier Inc. All rights reserved.

An analysis of the benefits of ethnography design methods for product modelling

NASA Astrophysics Data System (ADS)

Butlewski, M.; Misztal, A.; Belu, N.

2016-08-01

The essence of modelling is to reflect the studied piece of reality in such a way that best describes the selected elements of the designed system. A model is used in design to optimize the structure and parameters of the constructed object and is a tool for assessing the quality of construction, eliminating weak links and ensuring adequate safety components. In view of the aim of modelling, it can be divided into functional modelling, showing the complexity of the object, and reliability modelling, specifying its states at variable threshold values. In design, modelling allows for significant savings in resources that would otherwise be spent because of problems appearing at the prototype stage, but also during production or in the course of using the product. In the practice of ergonomic design many problems could be avoided if early enough in the design process the values of parameters and their relations would be taken into account through modelling. On the other hand, the modelling process can be costly and time-consuming to carry out, and against the currently pervasive lean production it is a highly undesirable factor. Therefore, the modelling process should be supported with the use of appropriate cognitive techniques namely ethnography design, which would determine inadequacies of existing models as well as indicate the equivalent conditions for modelling. The justification of the use of this technique results both from the possibility of providing additional information, as well as the opportunity to “test” the phenomena affecting the design process. Ergonomic modelling tests developed solutions towards their adaptation to users’ anthropometric, biomechanical and psychomotor characteristics, as well as behaviour patterns. However, knowledge of the latter and achieving a sufficient ergonomic and functional quality of proposed solutions often requires the use of the ethnography design approach. The aim of this article is to test the practical application of ethnography design methodology in product design and to analyse the benefits of its use. The analysis is based on effects of its application with the support of product design from various industries, along with a discussion of the method's limitations. Among benefits of ethnography design, the greatest proved to be providing knowledge of nonspecific user behaviour previously unknown to designers, which when rendered by models allowed to develop innovative solutions.

Laboratory Practical Exams in the Biochemistry Lab Course.

ERIC Educational Resources Information Center

Robyt, John F.; White, Bernard J.

1990-01-01

Described are the composition, design, administration, and evaluation of practical examinations. A table of the composition of biochemical unknowns for analysis in practical examinations is included. (CW)

Identification of substances migrating from plastic baby bottles using a combination of low-resolution and high-resolution mass spectrometric analysers coupled to gas and liquid chromatography.

PubMed

Onghena, Matthias; Van Hoeck, Els; Van Loco, Joris; Ibáñez, María; Cherta, Laura; Portolés, Tania; Pitarch, Elena; Hernandéz, Félix; Lemière, Filip; Covaci, Adrian

2015-11-01

This work presents a strategy for elucidation of unknown migrants from plastic food contact materials (baby bottles) using a combination of analytical techniques in an untargeted approach. First, gas chromatography (GC) coupled to mass spectrometry (MS) in electron ionisation mode was used to identify migrants through spectral library matching. When no acceptable match was obtained, a second analysis by GC-(electron ionisation) high resolution mass spectrometry time of flight (TOF) was applied to obtain accurate mass fragmentation spectra and isotopic patterns. Databases were then searched to find a possible elemental composition for the unknown compounds. Finally, a GC hybrid quadrupole-TOF-MS with an atmospheric pressure chemical ionisation source was used to obtain the molecular ion or the protonated molecule. Accurate mass data also provided additional information on the fragmentation behaviour as two acquisition functions with different collision energies were available (MS(E) approach). In the low-energy function, limited fragmentation took place, whereas for the high-energy function, fragmentation was enhanced. For less volatile unknowns, ultra-high pressure liquid chromatography-quadrupole-TOF-MS was additionally applied. Using a home-made database containing common migrating compounds and plastic additives, tentative identification was made for several positive findings based on accurate mass of the (de)protonated molecule, product ion fragments and characteristic isotopic ions. Six illustrative examples are shown to demonstrate the modus operandi and the difficulties encountered during identification. The combination of these techniques was proven to be a powerful tool for the elucidation of unknown migrating compounds from plastic baby bottles. Copyright © 2015 John Wiley & Sons, Ltd.

PDB-UF: database of predicted enzymatic functions for unannotated protein structures from structural genomics.

PubMed

von Grotthuss, Marcin; Plewczynski, Dariusz; Ginalski, Krzysztof; Rychlewski, Leszek; Shakhnovich, Eugene I

2006-02-06

The number of protein structures from structural genomics centers dramatically increases in the Protein Data Bank (PDB). Many of these structures are functionally unannotated because they have no sequence similarity to proteins of known function. However, it is possible to successfully infer function using only structural similarity. Here we present the PDB-UF database, a web-accessible collection of predictions of enzymatic properties using structure-function relationship. The assignments were conducted for three-dimensional protein structures of unknown function that come from structural genomics initiatives. We show that 4 hypothetical proteins (with PDB accession codes: 1VH0, 1NS5, 1O6D, and 1TO0), for which standard BLAST tools such as PSI-BLAST or RPS-BLAST failed to assign any function, are probably methyltransferase enzymes. We suggest that the structure-based prediction of an EC number should be conducted having the different similarity score cutoff for different protein folds. Moreover, performing the annotation using two different algorithms can reduce the rate of false positive assignments. We believe, that the presented web-based repository will help to decrease the number of protein structures that have functions marked as "unknown" in the PDB file. http://paradox.harvard.edu/PDB-UF and http://bioinfo.pl/PDB-UF.

Case Study: Test Results of a Tool and Method for In-Flight, Adaptive Control System Verification on a NASA F-15 Flight Research Aircraft

NASA Technical Reports Server (NTRS)

Jacklin, Stephen A.; Schumann, Johann; Guenther, Kurt; Bosworth, John

2006-01-01

Adaptive control technologies that incorporate learning algorithms have been proposed to enable autonomous flight control and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments [1-2]. At the present time, however, it is unknown how adaptive algorithms can be routinely verified, validated, and certified for use in safety-critical applications. Rigorous methods for adaptive software verification end validation must be developed to ensure that. the control software functions as required and is highly safe and reliable. A large gap appears to exist between the point at which control system designers feel the verification process is complete, and when FAA certification officials agree it is complete. Certification of adaptive flight control software verification is complicated by the use of learning algorithms (e.g., neural networks) and degrees of system non-determinism. Of course, analytical efforts must be made in the verification process to place guarantees on learning algorithm stability, rate of convergence, and convergence accuracy. However, to satisfy FAA certification requirements, it must be demonstrated that the adaptive flight control system is also able to fail and still allow the aircraft to be flown safely or to land, while at the same time providing a means of crew notification of the (impending) failure. It was for this purpose that the NASA Ames Confidence Tool was developed [3]. This paper presents the Confidence Tool as a means of providing in-flight software assurance monitoring of an adaptive flight control system. The paper will present the data obtained from flight testing the tool on a specially modified F-15 aircraft designed to simulate loss of flight control faces.

13. Photographic copy of original Design For New Sluice Gate ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

13. Photographic copy of original Design For New Sluice Gate drawing, date and engineer unknown (original in possession of United States Department of Agriculture-Forest Service-Allegheny National Forest). - Loleta Recreation Area, Lower Dam, 6 miles Southeast of interesection of State Route 24041 & State Route 66, Loleta, Elk County, PA

Chapter 11: Dinkey north and south project

Treesearch

M North; R. Rojas

2012-01-01

Designing and implementing vegetation treatments that can move a forest landscape toward a desired future condition is often challenging. Faced with diverse stakeholder interests and the unknown effects of changing climate conditions, managers need to engage and build collaborative projects. One such effort is the Dinkey project designed to help restore a healthy,...

Bristol Stool Form Scale reliability and agreement decreases when determining Rome III stool form designations

USDA-ARS?s Scientific Manuscript database

Rater reproducibility of the Bristol Stool Form Scale (BSFS), which categorizes stools into one of seven types, is unknown. We sought to determine reliability and agreement by individual stool type and when responses are categorized by Rome III clinical designation as normal or abnormal (constipatio...

A least squares approach to estimating the probability distribution of unobserved data in multiphoton microscopy

NASA Astrophysics Data System (ADS)

Salama, Paul

2008-02-01

Multi-photon microscopy has provided biologists with unprecedented opportunities for high resolution imaging deep into tissues. Unfortunately deep tissue multi-photon microscopy images are in general noisy since they are acquired at low photon counts. To aid in the analysis and segmentation of such images it is sometimes necessary to initially enhance the acquired images. One way to enhance an image is to find the maximum a posteriori (MAP) estimate of each pixel comprising an image, which is achieved by finding a constrained least squares estimate of the unknown distribution. In arriving at the distribution it is assumed that the noise is Poisson distributed, the true but unknown pixel values assume a probability mass function over a finite set of non-negative values, and since the observed data also assumes finite values because of low photon counts, the sum of the probabilities of the observed pixel values (obtained from the histogram of the acquired pixel values) is less than one. Experimental results demonstrate that it is possible to closely estimate the unknown probability mass function with these assumptions.

Reconstruction of phonon relaxation times from systems featuring interfaces with unknown properties

NASA Astrophysics Data System (ADS)

Forghani, Mojtaba; Hadjiconstantinou, Nicolas G.

2018-05-01

We present a method for reconstructing the phonon relaxation-time function τω=τ (ω ) (including polarization) and associated phonon free-path distribution from thermal spectroscopy data for systems featuring interfaces with unknown properties. Our method does not rely on the effective thermal-conductivity approximation or a particular physical model of the interface behavior. The reconstruction is formulated as an optimization problem in which the relaxation times are determined as functions of frequency by minimizing the discrepancy between the experimentally measured temperature profiles and solutions of the Boltzmann transport equation for the same system. Interface properties such as transmissivities are included as unknowns in the optimization; however, because for the thermal spectroscopy problems considered here the reconstruction is not very sensitive to the interface properties, the transmissivities are only approximately reconstructed and can be considered as byproducts of the calculation whose primary objective is the accurate determination of the relaxation times. The proposed method is validated using synthetic experimental data obtained from Monte Carlo solutions of the Boltzmann transport equation. The method is shown to remain robust in the presence of uncertainty (noise) in the measurement.

Natural History of Thyroid Function in Adults with Down Syndrome--10-Year Follow-Up Study

ERIC Educational Resources Information Center

Prasher, V.; Gomez, G.

2007-01-01

Background: The natural history of thyroid function in adults with Down syndrome (DS) is unknown. Method: This study investigated annual thyroid function tests in 200 adults with DS over a 10-year period. Results: Transient and persistent thyroid dysfunction was common. The 5- and 10-year incidence of definite hypothyroidism was 0.9%-1.64% and…

Increased lipolysis, diminished adipose tissue insulin sensitivity and impaired B-cell function relative to adipose tissue insulin sensitivity in obese youth with impaired glucose tolerance (IGT)

USDA-ARS?s Scientific Manuscript database

Despite evidence of insulin resistance and B-cell dysfunction in glucose metabolism in youth with prediabetes, the relationship between adipose tissue insulin sensitivity (ATIS) and B-cell function remains unknown. We investigated whole-body lipolysis, ATIS and B-cell function relative to ATIS [adip...

Efficacy of function specific 3D-motifs in enzyme classification according to their EC-numbers.

PubMed

Rahimi, Amir; Madadkar-Sobhani, Armin; Touserkani, Rouzbeh; Goliaei, Bahram

2013-11-07

Due to the increasing number of protein structures with unknown function originated from structural genomics projects, protein function prediction has become an important subject in bioinformatics. Among diverse function prediction methods, exploring known 3D-motifs, which are associated with functional elements in unknown protein structures is one of the most biologically meaningful methods. Homologous enzymes inherit such motifs in their active sites from common ancestors. However, slight differences in the properties of these motifs, results in variation in the reactions and substrates of the enzymes. In this study, we examined the possibility of discriminating highly related active site patterns according to their EC-numbers by 3D-motifs. For each EC-number, the spatial arrangement of an active site, which has minimum average distance to other active sites with the same function, was selected as a representative 3D-motif. In order to characterize the motifs, various points in active site elements were tested. The results demonstrated the possibility of predicting full EC-number of enzymes by 3D-motifs. However, the discriminating power of 3D-motifs varies among different enzyme families and depends on selecting the appropriate points and features. © 2013 Elsevier Ltd. All rights reserved.

Visual determinants of reduced performance on the Stroop color-word test in normal aging individuals.

PubMed

van Boxtel, M P; ten Tusscher, M P; Metsemakers, J F; Willems, B; Jolles, J

2001-10-01

It is unknown to what extent the performance on the Stroop color-word test is affected by reduced visual function in older individuals. We tested the impact of common deficiencies in visual function (reduced distant and close acuity, reduced contrast sensitivity, and color weakness) on Stroop performance among 821 normal individuals aged 53 and older. After adjustment for age, sex, and educational level, low contrast sensitivity was associated with more time needed on card I (word naming), red/green color weakness with slower card 2 performance (color naming), and reduced distant acuity with slower performance on card 3 (interference). Half of the age-related variance in speed performance was shared with visual function. The actual impact of reduced visual function may be underestimated in this study when some of this age-related variance in Stroop performance is mediated by visual function decrements. It is suggested that reduced visual function has differential effects on Stroop performance which need to be accounted for when the Stroop test is used both in research and in clinical settings. Stroop performance measured from older individuals with unknown visual status should be interpreted with caution.

Bio-Inspired In-Air Sonar Localization: What Artificial Pinnae do for Robotic Bats

NASA Astrophysics Data System (ADS)

Schillebeeckx, Filips

This dissertation investigates the hypothesis that binaural spectral cues, as generated by biomimetic microphone-baffle shapes in a suitable configuration, are both a sufficient and efficient means to realize real-time 3D localization capabilities for an in-air sonar system. We demonstrate 3D localization of real reflectors under realistic noise conditions, a task previously not performed successfully with a single binaural sonar measurement. The principal driving force behind this new approach is the use of two complex artificial pinna structures acting as complex direction-dependent spectral filters on the returning echoes. The technique makes use of broadband spectral cues in the received echoes only. Experiments with complex reflectors illustrate that the active head-related transfer function dominates the echo spectrum, allowing 3D localization in the presence of spectrum distortions caused by unknown reflector filtering. Also, experimental results in which multiple targets are localized simultaneously are presented. It is then investigated how binaural sonar system configuration choices affect 3D spectrum-based reflector localization. The proposed model demonstrates the limits of the spectral cue information provided by conventional transducers. Configurations composed of conventional receivers are evaluated as a function of unknown reflection strength and compared with a system with artificial pinnae receivers. Localization performance is quantified by an information theoretic performance criterion expressing the mutual information carried by a binaural spectrum on the corresponding 3D reflector location. Optimal configurations with conventional transducers are shown to be a function of echo reflection strength and the specific region of interest. The more complex spatial sensitivity patterns of organic pinna forms such as that of the Phyllostomus discolor bat species provide additional spectral cues that greatly improve localization information transfer compared to conventional transducers. Results indicate that the varying acoustic axis in the head-related transfer function of the pinna and even more so the higher peripheral sensitivity around the varying acoustic axis are the driving forces behind the artificial pinna's superior localization performance. Finally, it is shown that technical antennas that do not reproduce all the structural details seen in natural biosonar antennas can be suitable and robust design alternatives for in-air sonar systems intended for use on autonomous robots.

Photocopy of photograph (from NBPPNSY) photographer unknown, c. 1950's view ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph (from NBP-PNSY) photographer unknown, c. 1950's view northwest from 350-ton crane of drydock no. 2 (Haer no. Pa-387-B), 1950's. Pump house for the drydock is the round building below center of the photograph. The large building at the left center is building 546, the Turret Shop where naval gun turrets were assembled at the center rear is the foundry/propeller shop (Haer No. Pa-387-O) built in 1919. The foundry/propeller shop (building no. 20), designed by Warren-Moore and Company, resembles the Contemporaneous Architecture of Albert Kahn, who designed similar buildings for Henry Ford and the Chrysler Corporation in the 1920's and 1930's. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

Cryogenic propellant thermal control system design considerations, analyses, and concepts applied to a Mars human exploration mission

NASA Technical Reports Server (NTRS)

Plachta, David W.; Tucker, Stephen; Hoffman, David J.

1993-01-01

This paper analyzes, defines, and sizes cryogenic storage thermal control systems that meet the requirements of future NASA Mars human exploration missions. The design issues of this system include the projection of the existing Multilayer Insulation data base for cryogenic storage to much thicker (10 cm or more) insulation systems, the unknown heat leak from mechanical interfaces, and the thermal and structural performance effects of the large tank sizes required for a Mars mission. Acknowledging these unknown effects, heat loss projections are made based on extrapolation of the existing data base. The results indicate that hydrogen, methane, and oxygen are feasible propellants, and that the best suited thermal control sytems are 'thick' MLI, thermodynamic vent sytems, cryocoolers, and vacuum jackets.

On supporting students' understanding of solving linear equation by using flowchart

NASA Astrophysics Data System (ADS)

Toyib, Muhamad; Kusmayadi, Tri Atmojo; Riyadi

2017-05-01

The aim of this study was to support 7th graders to gradually understand the concepts and procedures of solving linear equation. Thirty-two 7th graders of a Junior High School in Surakarta, Indonesia were involved in this study. Design research was used as the research approach to achieve the aim. A set of learning activities in solving linear equation with one unknown were designed based on Realistic Mathematics Education (RME) approach. The activities were started by playing LEGO to find a linear equation then solve the equation by using flowchart. The results indicate that using the realistic problems, playing LEGO could stimulate students to construct linear equation. Furthermore, Flowchart used to encourage students' reasoning and understanding on the concepts and procedures of solving linear equation with one unknown.

LIBP-Pred: web server for lipid binding proteins using structural network parameters; PDB mining of human cancer biomarkers and drug targets in parasites and bacteria.

PubMed

González-Díaz, Humberto; Munteanu, Cristian R; Postelnicu, Lucian; Prado-Prado, Francisco; Gestal, Marcos; Pazos, Alejandro

2012-03-01

Lipid-Binding Proteins (LIBPs) or Fatty Acid-Binding Proteins (FABPs) play an important role in many diseases such as different types of cancer, kidney injury, atherosclerosis, diabetes, intestinal ischemia and parasitic infections. Thus, the computational methods that can predict LIBPs based on 3D structure parameters became a goal of major importance for drug-target discovery, vaccine design and biomarker selection. In addition, the Protein Data Bank (PDB) contains 3000+ protein 3D structures with unknown function. This list, as well as new experimental outcomes in proteomics research, is a very interesting source to discover relevant proteins, including LIBPs. However, to the best of our knowledge, there are no general models to predict new LIBPs based on 3D structures. We developed new Quantitative Structure-Activity Relationship (QSAR) models based on 3D electrostatic parameters of 1801 different proteins, including 801 LIBPs. We calculated these electrostatic parameters with the MARCH-INSIDE software and they correspond to the entire protein or to specific protein regions named core, inner, middle, and surface. We used these parameters as inputs to develop a simple Linear Discriminant Analysis (LDA) classifier to discriminate 3D structure of LIBPs from other proteins. We implemented this predictor in the web server named LIBP-Pred, freely available at , along with other important web servers of the Bio-AIMS portal. The users can carry out an automatic retrieval of protein structures from PDB or upload their custom protein structural models from their disk created with LOMETS server. We demonstrated the PDB mining option performing a predictive study of 2000+ proteins with unknown function. Interesting results regarding the discovery of new Cancer Biomarkers in humans or drug targets in parasites have been discussed here in this sense.

Development of a high-frequency in vivo transposon mutagenesis system for Synechocystis sp. PCC 6803 and Synechococcus elongatus PCC 7942.

PubMed

Watabe, Kazuyuki; Mimuro, Mamoru; Tsuchiya, Tohru

2014-11-01

Synechocystis sp. PCC 6803 (Synechocystis) is the first sequenced photosynthetic organism and has two advantages: natural transformation and light-activated heterotrophic growth. Such characteristics have mainly promoted reverse genetic analysis in this organism, however, to date approximately 50% of genes are still annotated as 'unknown protein' or 'hypothetical protein'. Therefore, forward genetic analysis is required for the identification of significant genes responsible for photosynthesis and other physiological phenomena among the genes of unknown function. The in vivo transposon mutagenesis system is one of the major methods for random mutagenesis. However, present in vivo transposon mutagenesis systems for cyanobacteria face problems such as relatively low frequency of transposition and repeated transposition in the host cells. In this study, we constructed vectors based on a mini-Tn5-derived vector that was designed to prevent repeated transposition. Our vectors carry a hyperactive transposase and optimized recognition sequence of transposase, which were reported to enhance frequency of transposition. Using the vector, we succeeded in highly frequent transposition (9×10(-3) per recipient cell) in Synechocystis. Transposon insertion sites of 10 randomly selected mutants indicated that the insertion sites spread throughout the genome with low sequence dependency. Furthermore, one of the 10 mutants exhibited the slow-growing phenotype, and the mutant was functionally complemented by using our expression vector. Our system also worked with another model cyanobacterium, Synechococcus elongatus PCC 7942, with high frequency. These results indicate that the developed system can be applied to the forward genetic analysis of a broad range of cyanobacteria. © The Author 2014. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.

The Essential Gene EMB1611 Maintains Shoot Apical Meristem Function During Arabidopsis Development

USDA-ARS?s Scientific Manuscript database

The Arabidopsis thaliana genome contains hundreds of genes essential for seed development. Because null mutations in these genes cause embryo lethality, their specific molecular and developmental functions are largely unknown. Here, we identify a role for EMB1611/MEE22, an essential gene in Arabidop...

Cross-Setting Correspondence in Sociometric Nominations among Children with Attention-Deficit/Hyperactivity Disorder

ERIC Educational Resources Information Center

Mikami, Amori Yee; Hoza, Betsy; Hinshaw, Stephen P.; Arnold, L. Eugene; Hechtman, Lily; Pelham, William E., Jr.

2015-01-01

Peer problems are common among children with emotional and behavioral disorders (EBD). However, the extent to which children's peer functioning varies across settings is unknown, as is the incremental power of peer functioning in different settings in predicting subsequent psychopathology. Participants were 57 children with…

Socioeconomic Status and Executive Function: Developmental Trajectories and Mediation

ERIC Educational Resources Information Center

Hackman, Daniel A.; Gallop, Robert; Evans, Gary W.; Farah, Martha J.

2015-01-01

Childhood socioeconomic status (SES) predicts executive function (EF), but fundamental aspects of this relation remain unknown: the developmental course of the SES disparity, its continued sensitivity to SES changes during that course, and the features of childhood experience responsible for the SES-EF relation. Regarding course, early disparities…

A set of GFP organelle marker lines for intracellular localization studies in Medicago truncatula

USDA-ARS?s Scientific Manuscript database

Genomics advances in the model legume Medicago truncatula have led to an increase in the number of identified genes encoding proteins with unknown biological function. Determining the intracellular location of uncharacterized proteins often aids in the elucidation of biological function. To expedite...

The Influence of Relational Knowledge and Executive Function on Preschoolers' Repeating Pattern Knowledge

ERIC Educational Resources Information Center

Miller, Michael R.; Rittle-Johnson, Bethany; Loehr, Abbey M.; Fyfe, Emily R.

2016-01-01

Children's knowledge of repeating patterns (e.g., ABBABB) is a central component of early mathematics, but the developmental mechanisms underlying this knowledge are currently unknown. We sought clarity on the importance of relational knowledge and executive function (EF) to preschoolers' understanding of repeating patterns. One hundred…

Listen, Imagine, and Create.

ERIC Educational Resources Information Center

Baumgartel, Marguerite; Lamb, Louise

1979-01-01

Presented is a very short story about a visit to an unknown, imaginary planet. The story is designed to provoke creative artistic responses from elementary level children in an art education class. (KC)

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

NASA Astrophysics Data System (ADS)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

The Study on Mental Health at Work: Design and sampling.

PubMed

Rose, Uwe; Schiel, Stefan; Schröder, Helmut; Kleudgen, Martin; Tophoven, Silke; Rauch, Angela; Freude, Gabriele; Müller, Grit

2017-08-01

The Study on Mental Health at Work (S-MGA) generates the first nationwide representative survey enabling the exploration of the relationship between working conditions, mental health and functioning. This paper describes the study design, sampling procedures and data collection, and presents a summary of the sample characteristics. S-MGA is a representative study of German employees aged 31-60 years subject to social security contributions. The sample was drawn from the employment register based on a two-stage cluster sampling procedure. Firstly, 206 municipalities were randomly selected from a pool of 12,227 municipalities in Germany. Secondly, 13,590 addresses were drawn from the selected municipalities for the purpose of conducting 4500 face-to-face interviews. The questionnaire covers psychosocial working and employment conditions, measures of mental health, work ability and functioning. Data from personal interviews were combined with employment histories from register data. Descriptive statistics of socio-demographic characteristics and logistic regressions analyses were used for comparing population, gross sample and respondents. In total, 4511 face-to-face interviews were conducted. A test for sampling bias revealed that individuals in older cohorts participated more often, while individuals with an unknown educational level, residing in major cities or with a non-German ethnic background were slightly underrepresented. There is no indication of major deviations in characteristics between the basic population and the sample of respondents. Hence, S-MGA provides representative data for research on work and health, designed as a cohort study with plans to rerun the survey 5 years after the first assessment.

The statistical mechanics of complex signaling networks: nerve growth factor signaling

NASA Astrophysics Data System (ADS)

Brown, K. S.; Hill, C. C.; Calero, G. A.; Myers, C. R.; Lee, K. H.; Sethna, J. P.; Cerione, R. A.

2004-10-01

The inherent complexity of cellular signaling networks and their importance to a wide range of cellular functions necessitates the development of modeling methods that can be applied toward making predictions and highlighting the appropriate experiments to test our understanding of how these systems are designed and function. We use methods of statistical mechanics to extract useful predictions for complex cellular signaling networks. A key difficulty with signaling models is that, while significant effort is being made to experimentally measure the rate constants for individual steps in these networks, many of the parameters required to describe their behavior remain unknown or at best represent estimates. To establish the usefulness of our approach, we have applied our methods toward modeling the nerve growth factor (NGF)-induced differentiation of neuronal cells. In particular, we study the actions of NGF and mitogenic epidermal growth factor (EGF) in rat pheochromocytoma (PC12) cells. Through a network of intermediate signaling proteins, each of these growth factors stimulates extracellular regulated kinase (Erk) phosphorylation with distinct dynamical profiles. Using our modeling approach, we are able to predict the influence of specific signaling modules in determining the integrated cellular response to the two growth factors. Our methods also raise some interesting insights into the design and possible evolution of cellular systems, highlighting an inherent property of these systems that we call 'sloppiness.'

Proprioception and Throwing Accuracy in the Dominant Shoulder After Cryotherapy

PubMed Central

Wassinger, Craig A; Myers, Joseph B; Gatti, Joseph M; Conley, Kevin M; Lephart, Scott M

2007-01-01

Context: Application of cryotherapy modalities is common after acute shoulder injury and as part of rehabilitation. During athletic events, athletes may return to play after this treatment. The effects of cryotherapy on dominant shoulder proprioception have been assessed, yet the effects on throwing performance are unknown. Objective: To determine the effects of a cryotherapy application on shoulder proprioception and throwing accuracy. Design: Single-group, pretest-posttest control session design. Setting: University-based biomechanics laboratory. Patients or Other Participants: Healthy college-aged subjects (n = 22). Intervention(s): Twenty-minute ice pack application to the dominant shoulder. Main Outcome Measure(s): Active joint position replication, path of joint motion replication, and the Functional Throwing Performance Index. Results: Subjects demonstrated significant increases in deviation for path of joint motion replication when moving from 90° of abduction with 90° of external rotation to 20° of flexion with neutral shoulder rotation after ice pack application. Also, subjects exhibited a decrease in Functional Throwing Performance Index after cryotherapy application. No differences were found in subjects for active joint position replication after cryotherapy application. Conclusions: Proprioception and throwing accuracy were decreased after ice pack application to the shoulder. It is important that clinicians understand the deficits that occur after cryotherapy, as this modality is commonly used following acute injury and during rehabilitation. This information should also be considered when attempting to return an athlete to play after treatment. PMID:17597948

Ultra Safe And Secure Blasting System

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

Hart, M M

2009-07-27

The Ultra is a blasting system that is designed for special applications where the risk and consequences of unauthorized demolition or blasting are so great that the use of an extraordinarily safe and secure blasting system is justified. Such a blasting system would be connected and logically welded together through digital code-linking as part of the blasting system set-up and initialization process. The Ultra's security is so robust that it will defeat the people who designed and built the components in any attempt at unauthorized detonation. Anyone attempting to gain unauthorized control of the system by substituting components or tappingmore » into communications lines will be thwarted in their inability to provide encrypted authentication. Authentication occurs through the use of codes that are generated by the system during initialization code-linking and the codes remain unknown to anyone, including the authorized operator. Once code-linked, a closed system has been created. The system requires all components connected as they were during initialization as well as a unique code entered by the operator for function and blasting.« less

Searching molecular structure databases with tandem mass spectra using CSI:FingerID

PubMed Central

Dührkop, Kai; Shen, Huibin; Meusel, Marvin; Rousu, Juho; Böcker, Sebastian

2015-01-01

Metabolites provide a direct functional signature of cellular state. Untargeted metabolomics experiments usually rely on tandem MS to identify the thousands of compounds in a biological sample. Today, the vast majority of metabolites remain unknown. We present a method for searching molecular structure databases using tandem MS data of small molecules. Our method computes a fragmentation tree that best explains the fragmentation spectrum of an unknown molecule. We use the fragmentation tree to predict the molecular structure fingerprint of the unknown compound using machine learning. This fingerprint is then used to search a molecular structure database such as PubChem. Our method is shown to improve on the competing methods for computational metabolite identification by a considerable margin. PMID:26392543

Adaptive fuzzy wavelet network control of second order multi-agent systems with unknown nonlinear dynamics.

PubMed

Taheri, Mehdi; Sheikholeslam, Farid; Najafi, Majddedin; Zekri, Maryam

2017-07-01

In this paper, consensus problem is considered for second order multi-agent systems with unknown nonlinear dynamics under undirected graphs. A novel distributed control strategy is suggested for leaderless systems based on adaptive fuzzy wavelet networks. Adaptive fuzzy wavelet networks are employed to compensate for the effect of unknown nonlinear dynamics. Moreover, the proposed method is developed for leader following systems and leader following systems with state time delays. Lyapunov functions are applied to prove uniformly ultimately bounded stability of closed loop systems and to obtain adaptive laws. Three simulation examples are presented to illustrate the effectiveness of the proposed control algorithms. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Functional buckling behavior of silicone rubber shells for biomedical use.

PubMed

van der Houwen, E B; Kuiper, L H; Burgerhof, J G M; van der Laan, B F A M; Verkerke, G J

2013-12-01

The use of soft elastic biomaterials in medical devices enables substantial function integration. The consequent increased simplification in design can improve reliability at a lower cost in comparison to traditional (hard) biomaterials. Functional bi-stable buckling is one of the many new mechanisms made possible by soft materials. The buckling behavior of shells, however, is typically described from a structural failure point of view: the collapse of arches or rupture of steam vessels, for example. There is little or no literature about the functional elastic buckling of small-sized silicone rubber shells, and it is unknown whether or not theory can predict their behavior. Is functional buckling possible within the scale, material and pressure normally associated with physiological applications? An automatic speech valve is used as an example application. Silicone rubber spherical shells (diameter 30mm) with hinged and double-hinged boundaries were subjected to air pressure loading. Twelve different geometrical configurations were tested for buckling and reverse buckling pressures. Data were compared with the theory. Buckling pressure increases linearly with shell thickness and shell height. Reverse buckling shows these same relations, with pressures always below normal buckling pressure. Secondary hinges change normal/reverse buckling pressure ratios and promote symmetrical buckling. All tested configurations buckled within or closely around physiological pressures. Functional bi-stable buckling of silicone rubber shells is possible with adjustable properties in the physiological pressure range. Results can be predicted using the proposed relations and equations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Neural activity predicts attitude change in cognitive dissonance.

PubMed

van Veen, Vincent; Krug, Marie K; Schooler, Jonathan W; Carter, Cameron S

2009-11-01

When our actions conflict with our prior attitudes, we often change our attitudes to be more consistent with our actions. This phenomenon, known as cognitive dissonance, is considered to be one of the most influential theories in psychology. However, the neural basis of this phenomenon is unknown. Using a Solomon four-group design, we scanned participants with functional MRI while they argued that the uncomfortable scanner environment was nevertheless a pleasant experience. We found that cognitive dissonance engaged the dorsal anterior cingulate cortex and anterior insula; furthermore, we found that the activation of these regions tightly predicted participants' subsequent attitude change. These effects were not observed in a control group. Our findings elucidate the neural representation of cognitive dissonance, and support the role of the anterior cingulate cortex in detecting cognitive conflict and the neural prediction of attitude change.

A matter of distance-The effect of oxytocin on social discounting is empathy-dependent.

PubMed

Strang, Sabrina; Gerhardt, Holger; Marsh, Nina; Oroz Artigas, Sergio; Hu, Yang; Hurlemann, René; Park, Soyoung Q

2017-04-01

Generosity is an important behavior enriching human society and can be observed across cultures. However, generosity has been shown to be modulated as a function of social distance, also referred to as social discounting. Oxytocin and empathy are other factors that have been shown to play an important role in generous behavior. However, how exactly oxytocin and empathy impact social discounting is yet unknown. Here, we administered oxytocin or placebo in a double-blind design, and measured social discounting behavior. Additionally, individual differences in empathy were assessed. Our results show that the effect of oxytocin on generous behavior is modulated by trait empathy; only for those subjects who received oxytocin there was a positive correlation between individual trait empathy and their generous behavior towards close others. Copyright © 2017 Elsevier Ltd. All rights reserved.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations

PubMed Central

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results. PMID:28467431

Structural and Functional Dissection of the Heterocyclic Peptide Cytotoxin Streptolysin S*S⃞

PubMed Central

Mitchell, Douglas A.; Lee, Shaun W.; Pence, Morgan A.; Markley, Andrew L.; Limm, Joyce D.; Nizet, Victor; Dixon, Jack E.

2009-01-01

The human pathogen Streptococcus pyogenes secretes a highly cytolytic toxin known as streptolysin S (SLS). SLS is a key virulence determinant and responsible for the β-hemolytic phenotype of these bacteria. Despite over a century of research, the chemical structure of SLS remains unknown. Recent experiments have revealed that SLS is generated from an inactive precursor peptide that undergoes extensive post-translational modification to an active form. In this work, we address outstanding questions regarding the SLS biosynthetic process, elucidating the features of substrate recognition and sites of posttranslational modification to the SLS precursor peptide. Further, we exploit these findings to guide the design of artificial cytolytic toxins that are recognized by the SLS biosynthetic enzymes and others that are intrinsically cytolytic. This new structural information has ramifications for future antimicrobial therapies. PMID:19286651

Multigrid method for stability problems

NASA Technical Reports Server (NTRS)

Ta'asan, Shlomo

1988-01-01

The problem of calculating the stability of steady state solutions of differential equations is addressed. Leading eigenvalues of large matrices that arise from discretization are calculated, and an efficient multigrid method for solving these problems is presented. The resulting grid functions are used as initial approximations for appropriate eigenvalue problems. The method employs local relaxation on all levels together with a global change on the coarsest level only, which is designed to separate the different eigenfunctions as well as to update their corresponding eigenvalues. Coarsening is done using the FAS formulation in a nonstandard way in which the right-hand side of the coarse grid equations involves unknown parameters to be solved on the coarse grid. This leads to a new multigrid method for calculating the eigenvalues of symmetric problems. Numerical experiments with a model problem are presented which demonstrate the effectiveness of the method.

Adaptive control for a class of nonlinear complex dynamical systems with uncertain complex parameters and perturbations.

PubMed

Liu, Jian; Liu, Kexin; Liu, Shutang

2017-01-01

In this paper, adaptive control is extended from real space to complex space, resulting in a new control scheme for a class of n-dimensional time-dependent strict-feedback complex-variable chaotic (hyperchaotic) systems (CVCSs) in the presence of uncertain complex parameters and perturbations, which has not been previously reported in the literature. In detail, we have developed a unified framework for designing the adaptive complex scalar controller to ensure this type of CVCSs asymptotically stable and for selecting complex update laws to estimate unknown complex parameters. In particular, combining Lyapunov functions dependent on complex-valued vectors and back-stepping technique, sufficient criteria on stabilization of CVCSs are derived in the sense of Wirtinger calculus in complex space. Finally, numerical simulation is presented to validate our theoretical results.

Robust adaptive tracking control for nonholonomic mobile manipulator with uncertainties.

PubMed

Peng, Jinzhu; Yu, Jie; Wang, Jie

2014-07-01

In this paper, mobile manipulator is divided into two subsystems, that is, nonholonomic mobile platform subsystem and holonomic manipulator subsystem. First, the kinematic controller of the mobile platform is derived to obtain a desired velocity. Second, regarding the coupling between the two subsystems as disturbances, Lyapunov functions of the two subsystems are designed respectively. Third, a robust adaptive tracking controller is proposed to deal with the unknown upper bounds of parameter uncertainties and disturbances. According to the Lyapunov stability theory, the derived robust adaptive controller guarantees global stability of the closed-loop system, and the tracking errors and adaptive coefficient errors are all bounded. Finally, simulation results show that the proposed robust adaptive tracking controller for nonholonomic mobile manipulator is effective and has good tracking capacity. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Electrostatics-driven assembly of uni-lamellar catanionic facetted vesicles

NASA Astrophysics Data System (ADS)

Leung, Cheuk-Yui; Palmer, Liam; Kewalramani, Sumit; Sknepnek, Rastko; Vernizzi, Graziano; Greenfield, Megan; Stupp, Samuel; Bedzyk, Michael; Olvera de La Cruz, Monica

2012-02-01

Nature utilizes shape to generate function. Organelle and halophilic bacteria wall envelopes, for example, adopt various polyhedral shapes to compartmentalize matter. The origin of these shapes is unknown. A large variety of shell geometries, either fully faceted polyhedra or mixed Janus-like vesicles with faceted and curved domains that resemble cellular shells can be generated by coassembling water-insoluble anionic (--1) amphiphiles with high valence cationic (+2 and +3) amphiphiles. Electron microscopy, X-ray scattering, theory and simulations demonstrate that the resulting faceted ionic shells are crystalline, and stable at high salt concentrations. The crystallization of the co-assembled single tail amphiphiles is induced by ionic correlations, and modified by the solution pH. This work promotes the design of faceted shapes for various applications and improves our understanding of the origin of polyhedral shells in nature.

Multiparametric AFM reveals turgor-responsive net-like peptidoglycan architecture in live streptococci

NASA Astrophysics Data System (ADS)

Saar Dover, Ron; Bitler, Arkady; Shimoni, Eyal; Trieu-Cuot, Patrick; Shai, Yechiel

2015-05-01

Cell-wall peptidoglycan (PG) of Gram-positive bacteria is a strong and elastic multi-layer designed to resist turgor pressure and determine the cell shape and growth. Despite its crucial role, its architecture remains largely unknown. Here using high-resolution multiparametric atomic force microscopy (AFM), we studied how the structure and elasticity of PG change when subjected to increasing turgor pressure in live Group B Streptococcus. We show a new net-like arrangement of PG, which stretches and stiffens following osmotic challenge. The same structure also exists in isogenic mutants lacking surface appendages. Cell aging does not alter the elasticity of the cell wall, yet destroys the net architecture and exposes single segmented strands with the same circumferential orientation as predicted for intact glycans. Together, we show a new functional PG architecture in live Gram-positive bacteria.

The Protein Interactome of Streptococcus pneumoniae and Bacterial Meta-interactomes Improve Function Predictions

PubMed Central

Rajagopala, S. V.; Blazie, S. M.; Parrish, J. R.; Khuri, S.; Finley, R. L.

2017-01-01

ABSTRACT The functions of roughly a third of all proteins in Streptococcus pneumoniae, a significant human-pathogenic bacterium, are unknown. Using a yeast two-hybrid approach, we have determined more than 2,000 novel protein interactions in this organism. We augmented this network with meta-interactome data that we defined as the pool of all interactions between evolutionarily conserved proteins in other bacteria. We found that such interactions significantly improved our ability to predict a protein’s function, allowing us to provide functional predictions for 299 S. pneumoniae proteins with previously unknown functions. IMPORTANCE Identification of protein interactions in bacterial species can help define the individual roles that proteins play in cellular pathways and pathogenesis. Very few protein interactions have been identified for the important human pathogen S. pneumoniae. We used an experimental approach to identify over 2,000 new protein interactions for S. pneumoniae, the most extensive interactome data for this bacterium to date. To predict protein function, we used our interactome data augmented with interactions from other closely related bacteria. The combination of the experimental data and meta-interactome data significantly improved the prediction results, allowing us to assign possible functions to a large number of poorly characterized proteins. PMID:28744484

Tracking problem for electromechanical system under influence of external perturbations

NASA Astrophysics Data System (ADS)

Kochetkov, Sergey A.; Krasnova, Svetlana A.; Utkin, Victor A.

2017-01-01

For electromechanical objects the new control algorithms (vortex algprithms) are developed on the base of discontinuous functions. The distinctive feature of these algorithms is providing of asymptotical convergence of the output variables to zero under influence of unknown bounded disturbances of prescribed class. The advantages of proposed approach is demonstrated for direct current motor with permanent excitation. It is shown that inner variables of the system converge to unknown bounded disturbances and guarantee asymptotical convergence of output variables to zero.

Analysis of Soft Drinks Using Nuclear Magnetic Resonance Spectroscopy: A Mentorship

NASA Astrophysics Data System (ADS)

Wilson, Arkim; Myers, Craig; Crull, George; Curtis, Michael; Pasciak Patterson, Pamela

1999-10-01

This mentorship was designed to expose a student to the laboratory routine for a chemist at Bristol Myers Squibb Company (BMS). The student visited BMS, collaborated with BMS scientists, and actually completed a project on site. He was asked to determine the identity of an unknown sample of soft drink retrieved from a fictitious crime scene using NMR spectroscopy. He designed an experiment to test the unknown sample and used samples of purified sugar, purified caffeine, purified citric acid, Coke, Diet Coke, Pepsi, Mountain Dew, Diet 7-Up, and Sam's Diet Cola as controls. The results were analyzed and presented in a final report. The student was able to determine if the unknown contained sugar, caffeine, Nutrasweet, or sodium benzoate. He learned how to compile relevant information, conduct an experiment, collect and analyze data, draw conclusions, and prepare and edit a formal report. In addition to learning the uses of NMR, he also learned some of its limitations. In the final report, he was encouraged to reflect on the difficulties a scientist might encounter when trying to identify NMR peaks without an "ingredient list" like those of the soft drink cans. The experience was rewarding for the student and all scientists involved.

Known structure, unknown function: An inquiry-based undergraduate biochemistry laboratory course.

PubMed

Gray, Cynthia; Price, Carol W; Lee, Christopher T; Dewald, Alison H; Cline, Matthew A; McAnany, Charles E; Columbus, Linda; Mura, Cameron

2015-01-01

Undergraduate biochemistry laboratory courses often do not provide students with an authentic research experience, particularly when the express purpose of the laboratory is purely instructional. However, an instructional laboratory course that is inquiry- and research-based could simultaneously impart scientific knowledge and foster a student's research expertise and confidence. We have developed a year-long undergraduate biochemistry laboratory curriculum wherein students determine, via experiment and computation, the function of a protein of known three-dimensional structure. The first half of the course is inquiry-based and modular in design; students learn general biochemical techniques while gaining preparation for research experiments in the second semester. Having learned standard biochemical methods in the first semester, students independently pursue their own (original) research projects in the second semester. This new curriculum has yielded an improvement in student performance and confidence as assessed by various metrics. To disseminate teaching resources to students and instructors alike, a freely accessible Biochemistry Laboratory Education resource is available at http://biochemlab.org. © 2015 The Authors Biochemistry and Molecular Biology Education published by Wiley Periodicals, Inc. on behalf of International Union of Biochemistry and Molecular Biology.

Links between parental depression and longitudinal changes in youths’ neural sensitivity to rewards

PubMed Central

Fuligni, Andrew J.; Galván, Adriana; Lieberman, Matthew D.; Telzer, Eva H.

2016-01-01

Parental depression is a significant risk factor for adolescents’ engagement in risk taking. Yet the neural processes that mediate the link between parental depression and adolescents’ functioning remain unknown. Using a longitudinal functional magnetic resonance imaging design, we investigated how parental depression is associated with changes in adolescents’ neural reactivity to rewards during a risk-taking task, and how such changes in neural reactivity are associated with changes in risk-taking behavior. Greater parental depressive symptoms were associated with increases in their adolescent child’s risk taking and self-reported externalizing behavior over time. At the neural level, adolescents of parents with greater depressive symptoms showed longitudinal increases in the ventral striatum and dorsolateral prefrontal cortex to rewards during risk taking. Longitudinal increases in adolescents’ ventral striatum activation mediates the link between greater parental depression and increases in adolescents’ risk taking and externalizing behavior. These findings provide novel evidence that parental depression may contribute to changes in adolescents’ neural reactivity to rewards over time, which is associated with greater increases in their risk taking and externalizing behavior. PMID:27013103

Adaptive NN tracking control of uncertain nonlinear discrete-time systems with nonaffine dead-zone input.

PubMed

Liu, Yan-Jun; Tong, Shaocheng

2015-03-01

In the paper, an adaptive tracking control design is studied for a class of nonlinear discrete-time systems with dead-zone input. The considered systems are of the nonaffine pure-feedback form and the dead-zone input appears nonlinearly in the systems. The contributions of the paper are that: 1) it is for the first time to investigate the control problem for this class of discrete-time systems with dead-zone; 2) there are major difficulties for stabilizing such systems and in order to overcome the difficulties, the systems are transformed into an n-step-ahead predictor but nonaffine function is still existent; and 3) an adaptive compensative term is constructed to compensate for the parameters of the dead-zone. The neural networks are used to approximate the unknown functions in the transformed systems. Based on the Lyapunov theory, it is proven that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero. Two simulation examples are provided to verify the effectiveness of the control approach in the paper.

Symmetry Breaking in Space-Time Hierarchies Shapes Brain Dynamics and Behavior.

PubMed

Pillai, Ajay S; Jirsa, Viktor K

2017-06-07

In order to maintain brain function, neural activity needs to be tightly coordinated within the brain network. How this coordination is achieved and related to behavior is largely unknown. It has been previously argued that the study of the link between brain and behavior is impossible without a guiding vision. Here we propose behavioral-level concepts and mechanisms embodied as structured flows on manifold (SFM) that provide a formal description of behavior as a low-dimensional process emerging from a network's dynamics dependent on the symmetry and invariance properties of the network connectivity. Specifically, we demonstrate that the symmetry breaking of network connectivity constitutes a timescale hierarchy resulting in the emergence of an attractive functional subspace. We show that behavior emerges when appropriate conditions imposed upon the couplings are satisfied, justifying the conductance-based nature of synaptic couplings. Our concepts propose design principles for networks predicting how behavior and task rules are represented in real neural circuits and open new avenues for the analyses of neural data. Copyright © 2017 Elsevier Inc. All rights reserved.

Performance of resonant radar target identification algorithms using intra-class weighting functions

NASA Astrophysics Data System (ADS)

Mustafa, A.

The use of calibrated resonant-region radar cross section (RCS) measurements of targets for the classification of large aircraft is discussed. Errors in the RCS estimate of full scale aircraft flying over an ocean, introduced by the ionospheric variability and the sea conditions were studied. The Weighted Target Representative (WTR) classification algorithm was developed, implemented, tested and compared with the nearest neighbor (NN) algorithm. The WTR-algorithm has a low sensitivity to the uncertainty in the aspect angle of the unknown target returns. In addition, this algorithm was based on the development of a new catalog of representative data which reduces the storage requirements and increases the computational efficiency of the classification system compared to the NN-algorithm. Experiments were designed to study and evaluate the characteristics of the WTR- and the NN-algorithms, investigate the classifiability of targets and study the relative behavior of the number of misclassifications as a function of the target backscatter features. The classification results and statistics were shown in the form of performance curves, performance tables and confusion tables.

Towards force spectroscopy of single tip-link bonds

NASA Astrophysics Data System (ADS)

Koussa, Mounir A.; Sotomayor, Marcos; Wong, Wesley P.; Corey, David P.

2015-12-01

Inner-ear mechanotransduction relies on tip links, fine protein filaments made of cadherin-23 and protocadherin-15 that convey tension to mechanosensitive channels at the tips of hair-cell stereocilia. The tip-link cadherins are thought to form a heterotetrameric complex, with two cadherin-23 molecules forming the upper part of the filament and two protocadherin-15 molecules forming the lower end. The interaction between cadherin-23 and protocadherin-15 is mediated by their N-terminal tips. Missense mutations that modify the interaction interface impair binding and lead to deafness. Molecular dynamics simulations predict that the tip-link bond is mechanically strong enough to withstand forces in hair cells, but its experimentally determined strength is unknown. We have developed molecular tools to facilitate single-molecule force spectroscopy on the tip link bond. Self-assembling DNA nanoswitches are functionalized with the interacting tips of cadherin-23 and protocadherin-15 using the enzyme sortase under conditions that preserve protein function. These tip link nanoswitches are designed to provide a signature force-extension profile. This molecular signature should allow us to identify single-molecule rupture events in pulling experiments.

Lack of Spartin Protein in Troyer Syndrome

PubMed Central

Bakowska, Joanna C.; Wang, Heng; Xin, Baozhong; Sumner, Charlotte J.; Blackstone, Craig

2017-01-01

Background Hereditary spastic paraplegias (SPG1-SPG33) are characterized by progressive spastic weakness of the lower limbs. A nucleotide deletion (1110delA) in the (SPG20; OMIM 275900) spartin gene is the origin of autosomal recessive Troyer syndrome. This mutation is predicted to cause premature termination of the spartin protein. However, it remains unknown whether this truncated spartin protein is absent or is present and partially functional in patients. Objective To determine whether the truncated spartin protein is present or absent in cells derived from patients with Troyer syndrome. Design Case report. Setting Academic research. Patients We describe a new family with Troyer syndrome due to the 1110delA mutation. Main Outcome Measures We cultured primary fibroblasts and generated lymphoblasts from affected individuals, carriers, and control subjects and subjected these cells to immunoblot analyses. Results Spartin protein is undetectable in several cell lines derived from patients with Troyer syndrome. Conclusions Our data suggest that Troyer syndrome results from complete loss of spartin protein rather than from the predicted partly functional fragment. This may reflect increased protein degradation or impaired translation. PMID:18413476

Binding Leverage as a Molecular Basis for Allosteric Regulation

PubMed Central

Mitternacht, Simon; Berezovsky, Igor N.

2011-01-01

Allosteric regulation involves conformational transitions or fluctuations between a few closely related states, caused by the binding of effector molecules. We introduce a quantity called binding leverage that measures the ability of a binding site to couple to the intrinsic motions of a protein. We use Monte Carlo simulations to generate potential binding sites and either normal modes or pairs of crystal structures to describe relevant motions. We analyze single catalytic domains and multimeric allosteric enzymes with complex regulation. For the majority of the analyzed proteins, we find that both catalytic and allosteric sites have high binding leverage. Furthermore, our analysis of the catabolite activator protein, which is allosteric without conformational change, shows that its regulation involves other types of motion than those modulated at sites with high binding leverage. Our results point to the importance of incorporating dynamic information when predicting functional sites. Because it is possible to calculate binding leverage from a single crystal structure it can be used for characterizing proteins of unknown function and predicting latent allosteric sites in any protein, with implications for drug design. PMID:21935347

Mean-square state and parameter estimation for stochastic linear systems with Gaussian and Poisson noises

NASA Astrophysics Data System (ADS)

Basin, M.; Maldonado, J. J.; Zendejo, O.

2016-07-01

This paper proposes new mean-square filter and parameter estimator design for linear stochastic systems with unknown parameters over linear observations, where unknown parameters are considered as combinations of Gaussian and Poisson white noises. The problem is treated by reducing the original problem to a filtering problem for an extended state vector that includes parameters as additional states, modelled as combinations of independent Gaussian and Poisson processes. The solution to this filtering problem is based on the mean-square filtering equations for incompletely polynomial states confused with Gaussian and Poisson noises over linear observations. The resulting mean-square filter serves as an identifier for the unknown parameters. Finally, a simulation example shows effectiveness of the proposed mean-square filter and parameter estimator.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

Dana-Farber Cancer Institute: Mapping the Function of Rare Oncogenic Variants | Office of Cancer Genomics

Cancer.gov

Although some oncogenes and tumor suppressor genes are recurrently mutated at high frequency, the majority of somatic sequence alterations found in cancers occur at low frequency, and the functional consequences of the majority of these mutated alleles remain unknown. We are developing a scalable systematic approach to interrogate the function of cancer-associated gene variants. Read the abstract

Executive Function Variation in Children with Conduct Problems: Influences of Coexisting Reading Difficulties

ERIC Educational Resources Information Center

Kallitsoglou, Angeliki

2018-01-01

It is unknown whether children with conduct problems (CP) and poor reading (PR) skills exhibit more profound executive function impairments than children with CP only and whether such impairments are explained by coexisting PR. Executive functions were compared in four groups of 7- to 8-year-old children: 26 CP only, 35 PR only, 27 CP-PR, and 31…

Systematic wavelength selection for improved multivariate spectral analysis

DOEpatents

Thomas, Edward V.; Robinson, Mark R.; Haaland, David M.

1995-01-01

Methods and apparatus for determining in a biological material one or more unknown values of at least one known characteristic (e.g. the concentration of an analyte such as glucose in blood or the concentration of one or more blood gas parameters) with a model based on a set of samples with known values of the known characteristics and a multivariate algorithm using several wavelength subsets. The method includes selecting multiple wavelength subsets, from the electromagnetic spectral region appropriate for determining the known characteristic, for use by an algorithm wherein the selection of wavelength subsets improves the model's fitness of the determination for the unknown values of the known characteristic. The selection process utilizes multivariate search methods that select both predictive and synergistic wavelengths within the range of wavelengths utilized. The fitness of the wavelength subsets is determined by the fitness function F=.function.(cost, performance). The method includes the steps of: (1) using one or more applications of a genetic algorithm to produce one or more count spectra, with multiple count spectra then combined to produce a combined count spectrum; (2) smoothing the count spectrum; (3) selecting a threshold count from a count spectrum to select these wavelength subsets which optimize the fitness function; and (4) eliminating a portion of the selected wavelength subsets. The determination of the unknown values can be made: (1) noninvasively and in vivo; (2) invasively and in vivo; or (3) in vitro.

Expression, sorting, and segregation of Golgi proteins during germ cell differentiation in the testis

PubMed Central

Au, Catherine E.; Hermo, Louis; Byrne, Elliot; Smirle, Jeffrey; Fazel, Ali; Simon, Paul H. G.; Kearney, Robert E.; Cameron, Pamela H.; Smith, Charles E.; Vali, Hojatollah; Fernandez-Rodriguez, Julia; Ma, Kewei; Nilsson, Tommy; Bergeron, John J. M.

2015-01-01

The molecular basis of changes in structure, cellular location, and function of the Golgi apparatus during male germ cell differentiation is unknown. To deduce cognate Golgi proteins, we isolated germ cell Golgi fractions, and 1318 proteins were characterized, with 20 localized in situ. The most abundant protein, GL54D of unknown function, is characterized as a germ cell–specific Golgi-localized type II integral membrane glycoprotein. TM9SF3, also of unknown function, was revealed to be a universal Golgi marker for both somatic and germ cells. During acrosome formation, several Golgi proteins (GBF1, GPP34, GRASP55) localize to both the acrosome and Golgi, while GL54D, TM9SF3, and the Golgi trafficking protein TMED7/p27 are segregated from the acrosome. After acrosome formation, GL54D, TM9SF3, TMED4/p25, and TMED7/p27 continue to mark Golgi identity as it migrates away from the acrosome, while the others (GBF1, GPP34, GRASP55) remain in the acrosome and are progressively lost in later steps of differentiation. Cytoplasmic HSP70.2 and the endoplasmic reticulum luminal protein-folding enzyme PDILT are also Golgi recruited but only during acrosome formation. This resource identifies abundant Golgi proteins that are expressed differentially during mitosis, meiosis, and postacrosome Golgi migration, including the last step of differentiation. PMID:25808494

An Observational Study of Peer Learning for High School Students at a Cybersecurity Camp

ERIC Educational Resources Information Center

Pittman, Jason M.; Pike, Ronald E.

2016-01-01

This paper reports on the design and implementation of a cybersecurity camp offered as a cybersecurity learning experience to a group of female and male high school students. Students ranged in grade level from freshmen to senior. Student demographics, including any existing pre-requisite knowledge, were unknown to camp designers prior to the…

Bayesian Estimation of Reliability Burr Type XII Under Al-Bayyatis’ Suggest Loss Function with Numerical Solution

NASA Astrophysics Data System (ADS)

Mohammed, Amal A.; Abraheem, Sudad K.; Fezaa Al-Obedy, Nadia J.

2018-05-01

In this paper is considered with Burr type XII distribution. The maximum likelihood, Bayes methods of estimation are used for estimating the unknown scale parameter (α). Al-Bayyatis’ loss function and suggest loss function are used to find the reliability with the least loss. So the reliability function is expanded in terms of a set of power function. For this performance, the Matlab (ver.9) is used in computations and some examples are given.

Third-Party Software's Trust Quagmire.

PubMed

Voas, J; Hurlburt, G

2015-12-01

Current software development has trended toward the idea of integrating independent software sub-functions to create more complete software systems. Software sub-functions are often not homegrown - instead they are developed by unknown 3 rd party organizations and reside in software marketplaces owned or controlled by others. Such software sub-functions carry plausible concern in terms of quality, origins, functionality, security, interoperability, to name a few. This article surveys key technical difficulties in confidently building systems from acquired software sub-functions by calling out the principle software supply chain actors.

Arabidopsis VASCULAR-RELATED UNKNOWN PROTEIN1 Regulates Xylem Development and Growth by a Conserved Mechanism That Modulates Hormone Signaling1[W][OPEN

PubMed Central

Grienenberger, Etienne; Douglas, Carl J.

2014-01-01

Despite a strict conservation of the vascular tissues in vascular plants (tracheophytes), our understanding of the genetic basis underlying the differentiation of secondary cell wall-containing cells in the xylem of tracheophytes is still far from complete. Using coexpression analysis and phylogenetic conservation across sequenced tracheophyte genomes, we identified a number of Arabidopsis (Arabidopsis thaliana) genes of unknown function whose expression is correlated with secondary cell wall deposition. Among these, the Arabidopsis VASCULAR-RELATED UNKNOWN PROTEIN1 (VUP1) gene encodes a predicted protein of 24 kD with no annotated functional domains but containing domains that are highly conserved in tracheophytes. Here, we show that the VUP1 expression pattern, determined by promoter-β-glucuronidase reporter gene expression, is associated with vascular tissues, while vup1 loss-of-function mutants exhibit collapsed morphology of xylem vessel cells. Constitutive overexpression of VUP1 caused dramatic and pleiotropic developmental defects, including severe dwarfism, dark green leaves, reduced apical dominance, and altered photomorphogenesis, resembling brassinosteroid-deficient mutants. Constitutive overexpression of VUP homologs from multiple tracheophyte species induced similar defects. Whole-genome transcriptome analysis revealed that overexpression of VUP1 represses the expression of many brassinosteroid- and auxin-responsive genes. Additionally, deletion constructs and site-directed mutagenesis were used to identify critical domains and amino acids required for VUP1 function. Altogether, our data suggest a conserved role for VUP1 in regulating secondary wall formation during vascular development by tissue- or cell-specific modulation of hormone signaling pathways. PMID:24567189

ATP-binding Cassette (ABC) Transport System Solute-binding Protein-guided Identification of Novel d-Altritol and Galactitol Catabolic Pathways in Agrobacterium tumefaciens C58*

PubMed Central

Wichelecki, Daniel J.; Vetting, Matthew W.; Chou, Liyushang; Al-Obaidi, Nawar; Bouvier, Jason T.; Almo, Steven C.; Gerlt, John A.

2015-01-01

Innovations in the discovery of the functions of uncharacterized proteins/enzymes have become increasingly important as advances in sequencing technology flood protein databases with an exponentially growing number of open reading frames. This study documents one such innovation developed by the Enzyme Function Initiative (EFI; U54GM093342), the use of solute-binding proteins for transport systems to identify novel metabolic pathways. In a previous study, this strategy was applied to the tripartite ATP-independent periplasmic transporters. Here, we apply this strategy to the ATP-binding cassette transporters and report the discovery of novel catabolic pathways for d-altritol and galactitol in Agrobacterium tumefaciens C58. These efforts resulted in the description of three novel enzymatic reactions as follows: 1) oxidation of d-altritol to d-tagatose via a dehydrogenase in Pfam family PF00107, a previously unknown reaction; 2) phosphorylation of d-tagatose to d-tagatose 6-phosphate via a kinase in Pfam family PF00294, a previously orphan EC number; and 3) epimerization of d-tagatose 6-phosphate C-4 to d-fructose 6-phosphate via a member of Pfam family PF08013, another previously unknown reaction. The epimerization reaction catalyzed by a member of PF08013 is especially noteworthy, because the functions of members of PF08013 have been unknown. These discoveries were assisted by the following two synergistic bioinformatics web tools made available by the Enzyme Function Initiative: the EFI-Enzyme Similarity Tool and the EFI-Genome Neighborhood Tool. PMID:26472925

Executive function in children with intellectual disability--the effects of sex, level and aetiology of intellectual disability.

PubMed

Memisevic, H; Sinanovic, O

2014-09-01

Executive function is very important in the children's overall development. The goal of this study was to assess the executive function in children with intellectual disability (ID) through the use of the Behavior Rating Inventory of Executive Function (BRIEF) teacher version. An additional goal was to examine the differences in executive function in relation to child's sex, level and aetiology of ID. The sample consisted of 90 children with ID attending two special education schools in Sarajevo, Bosnia and Herzegovina. There were 42 children with mild ID and 48 children with moderate ID. Of those, 54 were boys and 36 were girls. Children were classified into three etiological categories: 30 children with Down syndrome, 30 children with other genetic cause or organic brain injury and 30 children with unknown aetiology of ID. Special education teachers, who knew the children for at least 6 months filled the BRIEF. Children with ID had a significant deficit in executive function as measured by the BRIEF. There were no statistically significant differences in executive function in relation to the child's sex. Level of ID had a significant effect on executive function. In relation to the aetiology of ID, the only significant difference was on the Shift scale of the BRIEF. Knowing what executive function is most impaired in children with ID will help professionals design better intervention strategies. More attention needs to be given to the assessment of executive function and its subsequent intervention in the school settings. © 2013 MENCAP and International Association of the Scientific Study of Intellectual and Developmental Disabilities and John Wiley & Sons Ltd.

Optical Neural Classification Of Binary Patterns

NASA Astrophysics Data System (ADS)

Gustafson, Steven C.; Little, Gordon R.

1988-05-01

Binary pattern classification that may be implemented using optical hardware and neural network algorithms is considered. Pattern classification problems that have no concise description (as in classifying handwritten characters) or no concise computation (as in NP-complete problems) are expected to be particularly amenable to this approach. For example, optical processors that efficiently classify binary patterns in accordance with their Boolean function complexity might be designed. As a candidate for such a design, an optical neural network model is discussed that is designed for binary pattern classification and that consists of an optical resonator with a dynamic multiplex-recorded reflection hologram and a phase conjugate mirror with thresholding and gain. In this model, learning or training examples of binary patterns may be recorded on the hologram such that one bit in each pattern marks the pattern class. Any input pattern, including one with an unknown class or marker bit, will be modified by a large number of parallel interactions with the reflection hologram and nonlinear mirror. After perhaps several seconds and 100 billion interactions, a steady-state pattern may develop with a marker bit that represents a minimum-Boolean-complexity classification of the input pattern. Computer simulations are presented that illustrate progress in understanding the behavior of this model and in developing a processor design that could have commanding and enduring performance advantages compared to current pattern classification techniques.

Antidepressants Normalize the Default Mode Network in Patients With Dysthymia

PubMed Central

Posner, Jonathan; Hellerstein, David J.; Gat, Inbal; Mechling, Anna; Klahr, Kristin; Wang, Zhishun; McGrath, Patrick J.; Stewart, Jonathan W.; Peterson, Bradley S.

2014-01-01

Importance The default mode network (DMN) is a collection of brain regions that reliably deactivate during goal-directed behaviors and is more active during a baseline, or so-called resting, condition. Coherence of neural activity, or functional connectivity, within the brain’s DMN is increased in major depressive disorder relative to healthy control (HC) subjects; however, whether similar abnormalities are present in persons with dysthymic disorder (DD) is unknown. Moreover, the effect of antidepressant medications on DMN connectivity in patients with DD is also unknown. Objective To use resting-state functional-connectivity magnetic resonance imaging (MRI) to study (1) the functional connectivity of the DMN in subjects with DD vs HC participants and (2) the effects of antidepressant therapy on DMN connectivity. Design After collecting baseline MRI scans from subjects with DD and HC participants, we enrolled the participants with DD into a 10-week prospective, double-blind, placebo-controlled trial of duloxetine and collected MRI scans again at the conclusion of the study. Enrollment occurred between 2007 and 2011. Setting University research institute. Participants Volunteer sample of 41 subjects with DD and 25 HC participants aged 18 to 53 years. Control subjects were group matched to patients with DD by age and sex. Main Outcome Measures We used resting-state functional-connectivity MRI to measure the functional connectivity of the brain’s DMN in persons with DD compared with HC subjects, and we examined the effects of treatment with duloxetine vs placebo on DMN connectivity. Results Of the 41 subjects with DD, 32 completed the clinical trial and MRI scans, along with the 25 HC participants. At baseline, we found that the coherence of neural activity within the brain’s DMN was greater in persons with DD compared with HC subjects. Following a 10-week clinical trial, we found that treatment with duloxetine, but not placebo, normalized DMN connectivity. Conclusions and Relevance The baseline imaging findings are consistent with those found in patients with major depressive disorder and suggest that increased connectivity within the DMN may be important in the pathophysiology of both acute and chronic manifestations of depressive illness. The normalization of DMN connectivity following antidepressant treatment suggests an important causal pathway through which antidepressants may reduce depression. PMID:23389382

Adolescent Borderline Symptoms in the Community: Prognosis for Functioning over 20 Years

ERIC Educational Resources Information Center

Winograd, Greta; Cohen, Patricia; Chen, Henian

2008-01-01

Background: The long-term prognosis associated with adolescent symptoms of borderline personality disorder (BPD) in the general population is virtually unknown. In this study, the relationship of early borderline symptoms to subsequent psychosocial functioning and attainment was investigated based on data from the Children in the Community cohort.…

Changes of Pain Perception, Autonomic Function, and Endocrine Parameters during Treatment of Anorectic Adolescents

ERIC Educational Resources Information Center

Bar, Karl-Jurgen; Boettger, Silke; Wagner, Gerd; Wilsdorf, Christine; Gerhard, Uwe Jens; Boettger, Michael K.; Blanz, Bernhard; Sauer, Heinrich

2006-01-01

Objectives: The underlying mechanisms of reduced pain perception in anorexia nervosa (AN) are unknown. To gain more insight into the pathology, the authors investigated pain perception, autonomic function, and endocrine parameters before and during successful treatment of adolescent AN patients. Method: Heat pain perception was assessed in 15…

A Qualitative Organic Analysis that Exploits the Senses of Smell, Touch, and Sound

ERIC Educational Resources Information Center

Bromfield-Lee, Deborah C.; Oliver-Hoyo, Maria T.

2007-01-01

This laboratory experiment utilizes the characteristic aromas of some functional groups to exploit the sense of smell as a discriminating tool in an organic qualitative analysis scheme. Students differentiate a variety of compounds by their aromas and based on their olfactory classification identify an unknown functional group. Students then…

Analysis of multinomial models with unknown index using data augmentation

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, R.M.; Link, W.A.

2007-01-01

Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.

[Clinical electro-ophthalmology at the Max Planck Institute of the Frankfurt University Ophthalmology Clinic 1970-1991].

PubMed

Lorenz, R; Baier, M; Eckl, G; Raile, A

1996-07-01

The survey shows the frequency and distribution of diseases evaluated by electroophthalmological methods. Patients with retinal diseases (51.2%) and those with diseases of the optic nerve (21.8%) were examined most frequently. In a high percentage these investigations lead to a clinically useful assessment: described as confirmation or exclusion of a clinical diagnosis, as establishing a possible differential diagnosis or clearing up formerly unknown aspects of a disease. In cases of hereditary retinal disorders only 11% remained unclear, with presumed optic neuritis only 6%. The importance of electroophthalmological investigations is there ability to assess functional deficits in the visual system especially in somehow more rare retinal and centrally located disorders, functional deficits of unknown origins or in general diseases including the visual system.

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

PubMed Central

Cui, Jian; Liu, Jinghua; Li, Yuhua; Shi, Tieliu

2011-01-01

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome. PMID:21297957

A molecular identification system for grasses: a novel technology for forensic botany.

PubMed

Ward, J; Peakall, R; Gilmore, S R; Robertson, J

2005-09-10

Our present inability to rapidly, accurately and cost-effectively identify trace botanical evidence remains the major impediment to the routine application of forensic botany. Grasses are amongst the most likely plant species encountered as forensic trace evidence and have the potential to provide links between crime scenes and individuals or other vital crime scene information. We are designing a molecular DNA-based identification system for grasses consisting of several PCR assays that, like a traditional morphological taxonomic key, provide criteria that progressively identify an unknown grass sample to a given taxonomic rank. In a prior study of DNA sequences across 20 phylogenetically representative grass species, we identified a series of potentially informative indels in the grass mitochondrial genome. In this study we designed and tested five PCR assays spanning these indels and assessed the feasibility of these assays to aid identification of unknown grass samples. We confirmed that for our control set of 20 samples, on which the design of the PCR assays was based, the five primer combinations produced the expected results. Using these PCR assays in a 'blind test', we were able to identify 25 unknown grass samples with some restrictions. Species belonging to genera represented in our control set were all correctly identified to genus with one exception. Similarly, genera belonging to tribes in the control set were correctly identified to the tribal level. Finally, for those samples for which neither the tribal or genus specific PCR assays were designed, we could confidently exclude these samples from belonging to certain tribes and genera. The results confirmed the utility of the PCR assays and the feasibility of developing a robust full-scale usable grass identification system for forensic purposes.

Optimal experimental designs for the estimation of thermal properties of composite materials

NASA Technical Reports Server (NTRS)

Scott, Elaine P.; Moncman, Deborah A.

1994-01-01

Reliable estimation of thermal properties is extremely important in the utilization of new advanced materials, such as composite materials. The accuracy of these estimates can be increased if the experiments are designed carefully. The objectives of this study are to design optimal experiments to be used in the prediction of these thermal properties and to then utilize these designs in the development of an estimation procedure to determine the effective thermal properties (thermal conductivity and volumetric heat capacity). The experiments were optimized by choosing experimental parameters that maximize the temperature derivatives with respect to all of the unknown thermal properties. This procedure has the effect of minimizing the confidence intervals of the resulting thermal property estimates. Both one-dimensional and two-dimensional experimental designs were optimized. A heat flux boundary condition is required in both analyses for the simultaneous estimation of the thermal properties. For the one-dimensional experiment, the parameters optimized were the heating time of the applied heat flux, the temperature sensor location, and the experimental time. In addition to these parameters, the optimal location of the heat flux was also determined for the two-dimensional experiments. Utilizing the optimal one-dimensional experiment, the effective thermal conductivity perpendicular to the fibers and the effective volumetric heat capacity were then estimated for an IM7-Bismaleimide composite material. The estimation procedure used is based on the minimization of a least squares function which incorporates both calculated and measured temperatures and allows for the parameters to be estimated simultaneously.

Hierarchical and non-hierarchical {lambda} elements for one dimensional problems with unknown strength of singularity

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

Wong, K.K.; Surana, K.S.

1996-10-01

This paper presents a new and general procedure for designing hierarchical and non-hierarchical special elements called {lambda} elements for one dimensional singular problems where the strength of the singularity is unknown. The {lambda} element formulations presented here permit correct numerical simulation of linear as well as non-linear singular problems without a priori knowledge of the strength of the singularity. A procedure is also presented for determining the exact strength of the singularity using the converged solution. It is shown that in special instances, the general formulation of {lambda} elements can also be made hierarchical. The {lambda} elements presented here aremore » of type C{sup 0} and provide C{sup 0} inter-element continuity with p-version elements. One dimensional steady state radial flow of an upper convected Maxwell fluid is considered as a sample problem. Since in this case {lambda}{sub i} are known, this problem provides a good example for investigating the performance of the formulation proposed here. Least squares approach (or Least Squares Finite Element Formulation: LSFEF) is used to construct the integral form (error functional I) from the differential equations. Numerical studies are presented for radially inward flow of an upper convected Maxwell fluid with inner radius r{sub i} = .1 and .01 etc. and Deborah number De = 2.« less

Performance and robustness of optimal fractional fuzzy PID controllers for pitch control of a wind turbine using chaotic optimization algorithms.

PubMed

Asgharnia, Amirhossein; Shahnazi, Reza; Jamali, Ali

2018-05-11

The most studied controller for pitch control of wind turbines is proportional-integral-derivative (PID) controller. However, due to uncertainties in wind turbine modeling and wind speed profiles, the need for more effective controllers is inevitable. On the other hand, the parameters of PID controller usually are unknown and should be selected by the designer which is neither a straightforward task nor optimal. To cope with these drawbacks, in this paper, two advanced controllers called fuzzy PID (FPID) and fractional-order fuzzy PID (FOFPID) are proposed to improve the pitch control performance. Meanwhile, to find the parameters of the controllers the chaotic evolutionary optimization methods are used. Using evolutionary optimization methods not only gives us the unknown parameters of the controllers but also guarantees the optimality based on the chosen objective function. To improve the performance of the evolutionary algorithms chaotic maps are used. All the optimization procedures are applied to the 2-mass model of 5-MW wind turbine model. The proposed optimal controllers are validated using simulator FAST developed by NREL. Simulation results demonstrate that the FOFPID controller can reach to better performance and robustness while guaranteeing fewer fatigue damages in different wind speeds in comparison to FPID, fractional-order PID (FOPID) and gain-scheduling PID (GSPID) controllers. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

A Novel Approach to Implement Takagi-Sugeno Fuzzy Models.

PubMed

Chang, Chia-Wen; Tao, Chin-Wang

2017-09-01

This paper proposes new algorithms based on the fuzzy c-regressing model algorithm for Takagi-Sugeno (T-S) fuzzy modeling of the complex nonlinear systems. A fuzzy c-regression state model (FCRSM) algorithm is a T-S fuzzy model in which the functional antecedent and the state-space-model-type consequent are considered with the available input-output data. The antecedent and consequent forms of the proposed FCRSM consists mainly of two advantages: one is that the FCRSM has low computation load due to only one input variable is considered in the antecedent part; another is that the unknown system can be modeled to not only the polynomial form but also the state-space form. Moreover, the FCRSM can be extended to FCRSM-ND and FCRSM-Free algorithms. An algorithm FCRSM-ND is presented to find the T-S fuzzy state-space model of the nonlinear system when the input-output data cannot be precollected and an assumed effective controller is available. In the practical applications, the mathematical model of controller may be hard to be obtained. In this case, an online tuning algorithm, FCRSM-FREE, is designed such that the parameters of a T-S fuzzy controller and the T-S fuzzy state model of an unknown system can be online tuned simultaneously. Four numerical simulations are given to demonstrate the effectiveness of the proposed approach.

Learning from ISS-modular adaptive NN control of nonlinear strict-feedback systems.

PubMed

Wang, Cong; Wang, Min; Liu, Tengfei; Hill, David J

2012-10-01

This paper studies learning from adaptive neural control (ANC) for a class of nonlinear strict-feedback systems with unknown affine terms. To achieve the purpose of learning, a simple input-to-state stability (ISS) modular ANC method is first presented to ensure the boundedness of all the signals in the closed-loop system and the convergence of tracking errors in finite time. Subsequently, it is proven that learning with the proposed stable ISS-modular ANC can be achieved. The cascade structure and unknown affine terms of the considered systems make it very difficult to achieve learning using existing methods. To overcome these difficulties, the stable closed-loop system in the control process is decomposed into a series of linear time-varying (LTV) perturbed subsystems with the appropriate state transformation. Using a recursive design, the partial persistent excitation condition for the radial basis function neural network (NN) is established, which guarantees exponential stability of LTV perturbed subsystems. Consequently, accurate approximation of the closed-loop system dynamics is achieved in a local region along recurrent orbits of closed-loop signals, and learning is implemented during a closed-loop feedback control process. The learned knowledge is reused to achieve stability and an improved performance, thereby avoiding the tremendous repeated training process of NNs. Simulation studies are given to demonstrate the effectiveness of the proposed method.

Linear parameter varying representations for nonlinear control design

NASA Astrophysics Data System (ADS)

Carter, Lance Huntington

Linear parameter varying (LPV) systems are investigated as a framework for gain-scheduled control design and optimal hybrid control. An LPV system is defined as a linear system whose dynamics depend upon an a priori unknown but measurable exogenous parameter. A gain-scheduled autopilot design is presented for a bank-to-turn (BTT) missile. The method is novel in that the gain-scheduled design does not involve linearizations about operating points. Instead, the missile dynamics are brought to LPV form via a state transformation. This idea is applied to the design of a coupled longitudinal/lateral BTT missile autopilot. The pitch and yaw/roll dynamics are separately transformed to LPV form, where the cross axis states are treated as "exogenous" parameters. These are actually endogenous variables, so such a plant is called "quasi-LPV." Once in quasi-LPV form, a family of robust controllers using mu synthesis is designed for both the pitch and yaw/roll channels, using angle-of-attack and roll rate as the scheduling variables. The closed-loop time response is simulated using the original nonlinear model and also using perturbed aerodynamic coefficients. Modeling and control of engine idle speed is investigated using LPV methods. It is shown how generalized discrete nonlinear systems may be transformed into quasi-LPV form. A discrete nonlinear engine model is developed and expressed in quasi-LPV form with engine speed as the scheduling variable. An example control design is presented using linear quadratic methods. Simulations are shown comparing the LPV based controller performance to that using PID control. LPV representations are also shown to provide a setting for hybrid systems. A hybrid system is characterized by control inputs consisting of both analog signals and discrete actions. A solution is derived for the optimal control of hybrid systems with generalized cost functions. This is shown to be computationally intensive, so a suboptimal strategy is proposed that neglects a subset of possible parameter trajectories. A computational algorithm is constructed for this suboptimal solution applied to a class of linear non-quadratic cost functions.

A functional gene array for detection of bacterial virulence elements

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

Jaing, C

2007-11-01

We report our development of the first of a series of microarrays designed to detect pathogens with known mechanisms of virulence and antibiotic resistance. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples. To validate our approach, we developed a first generation array targeting genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for microorganism detection and discrimination, measured the required target concentration, and assessedmore » tolerance for mismatches between probe and target sequences. Mismatch tolerance is a priority for this application, due to DNA sequence variability among members of gene families. Arrays were created using the NimbleGen Maskless Array Synthesizer at Lawrence Livermore National Laboratory. Purified genomic DNA from combinations of one or more of the four target organisms, pure cultures of four related organisms, and environmental aerosol samples with spiked-in genomic DNA were hybridized to the arrays. Based on the success of this prototype, we plan to design further arrays in this series, with the goal of detecting all known virulence and antibiotic resistance gene families in a greatly expanded set of organisms.« less

Sequence Elucidation of an Unknown Cyclic Peptide of High Doping Potential by ETD and CID Tandem Mass Spectrometry

NASA Astrophysics Data System (ADS)

Guan, Fuyu; Uboh, Cornelius E.; Soma, Lawrence R.; Rudy, Jeffrey

2011-04-01

Identification of an unknown substance without any information remains a daunting challenge despite advances in chemistry and mass spectrometry. However, an unknown cyclic peptide in a sample with very limited volume seized at a Pennsylvania racetrack has been successfully identified. The unknown sample was determined by accurate mass measurements to contain a small unknown peptide as the major component. Collision-induced dissociation (CID) of the unknown peptide revealed the presence of Lys (not Gln, by accurate mass), Phe, and Arg residues, and absence of any y-type product ion. The latter, together with the tryptic digestion results of the unusual deamidation and absence of any tryptic cleavage, suggests a cyclic structure for the peptide. Electron-transfer dissociation (ETD) of the unknown peptide indicated the presence of Gln (not Lys, by the unusual deamidation), Phe, and Arg residues and their connectivity. After all the results were pieced together, a cyclic tetrapeptide, cyclo[Arg-Lys-N(C6H9)Gln-Phe], is proposed for the unknown peptide. Observations of different amino acid residues from CID and ETD experiments for the peptide were interpreted by a fragmentation pathway proposed, as was preferential CID loss of a Lys residue from the peptide. ETD was used for the first time in sequencing of a cyclic peptide; product ions resulting from ETD of the peptide identified were categorized into two types and named pseudo-b and pseudo-z ions that are important for sequencing of cyclic peptides. The ETD product ions were interpreted by fragmentation pathways proposed. Additionally, multi-stage CID mass spectrometry cannot provide complete sequence information for cyclic peptides containing adjacent Arg and Lys residues. The identified cyclic peptide has not been documented in the literature, its pharmacological effects are unknown, but it might be a "designer" drug with athletic performance-enhancing effects.

Dana-Farber Cancer Institute: Mapping the Function of Rare Oncogenic Variants | Office of Cancer Genomics

Cancer.gov

Although some oncogenes and tumor suppressor genes are recurrently mutated at high frequency, the majority of somatic sequence alterations found in cancers occur at low frequency, and the functional consequences of the majority of these mutated alleles remain unknown. We are developing a scalable systematic approach to interrogate the function of cancer-associated gene variants. Read the abstract: Kim et al., 2016

The impact of virtual reality functions of a hotel website on travel anxiety.

PubMed

Lee, Ook; Oh, Ji-Eun

2007-08-01

This study deals with the impact of virtual reality (VR) features that are embedded in a hotel website on travelers' anxiety. Having more information is thought to be a factor in relieving anxiety in travel. A hotel website can be a good place for gathering information about the accommodation. In this study, we posit that a hotel website with VR functions should lead to a reduction in travelers' anxiety about travel. We built a website of a hotel and used VR functions to show the exterior, the lobby, a guest room, and a restaurant through an interactive and spatial shot of the hotel images. The experiment was conducted with a premise that the subjects were about to embark on a journey to an unknown place and to stay at an unknown hotel whose website contained VR functions. The subjects were asked to play with VR functions of the hotel website and then to complete a survey with questions regarding the degree of anxiety on the travel and psychological relief that might have been perceived by the subjects. The result confirms our hypothesis that there is a statistically significant relationship between the degree of travel anxiety and psychological relief caused by the use of VR functions of a hotel website.

Functional assignment of solute-binding proteins of ABC transporters using a fluorescence-based thermal shift assay.

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

Giulliani, S. E.; Frank, A. E.; Collart, F. R.

2008-12-08

We have used a fluorescence-based thermal shift (FTS) assay to identify amino acids that bind to solute-binding proteins in the bacterial ABC transporter family. The assay was validated with a set of six proteins with known binding specificity and was consistently able to map proteins with their known binding ligands. The assay also identified additional candidate binding ligands for several of the amino acid-binding proteins in the validation set. We extended this approach to additional targets and demonstrated the ability of the FTS assay to unambiguously identify preferential binding for several homologues of amino acid-binding proteins with known specificity andmore » to functionally annotate proteins of unknown binding specificity. The assay is implemented in a microwell plate format and provides a rapid approach to validate an anticipated function or to screen proteins of unknown function. The ABC-type transporter family is ubiquitous and transports a variety of biological compounds, but the current annotation of the ligand-binding proteins is limited to mostly generic descriptions of function. The results illustrate the feasibility of the FTS assay to improve the functional annotation of binding proteins associated with ABC-type transporters and suggest this approach that can also be extended to other protein families.« less

Towards high-speed autonomous navigation of unknown environments

NASA Astrophysics Data System (ADS)

Richter, Charles; Roy, Nicholas

2015-05-01

In this paper, we summarize recent research enabling high-speed navigation in unknown environments for dynamic robots that perceive the world through onboard sensors. Many existing solutions to this problem guarantee safety by making the conservative assumption that any unknown portion of the map may contain an obstacle, and therefore constrain planned motions to lie entirely within known free space. In this work, we observe that safety constraints may significantly limit performance and that faster navigation is possible if the planner reasons about collision with unobserved obstacles probabilistically. Our overall approach is to use machine learning to approximate the expected costs of collision using the current state of the map and the planned trajectory. Our contribution is to demonstrate fast but safe planning using a learned function to predict future collision probabilities.

Modularization and epistatic hierarchy determine homeostatic actions of multiple blood pressure quantitative trait loci.

PubMed

Chauvet, Cristina; Crespo, Kimberley; Ménard, Annie; Roy, Julie; Deng, Alan Y

2013-11-15

Hypertension, the most frequently diagnosed clinical condition world-wide, predisposes individuals to morbidity and mortality, yet its underlying pathological etiologies are poorly understood. So far, a large number of quantitative trait loci (QTLs) have been identified in both humans and animal models, but how they function together in determining overall blood pressure (BP) in physiological settings is unknown. Here, we systematically and comprehensively performed pair-wise comparisons of individual QTLs to create a global picture of their functionality in an inbred rat model. Rather than each of numerous QTLs contributing to infinitesimal BP increments, a modularized pattern arises: two epistatic 'blocks' constitute basic functional 'units' for nearly all QTLs, designated as epistatic module 1 (EM1) and EM2. This modularization dictates the magnitude and scope of BP effects. Any EM1 member can contribute to BP additively to that of EM2, but not to those of the same module. Members of each EM display epistatic hierarchy, which seems to reflect a related functional pathway. Rat homologues of 11 human BP QTLs belong to either EM1 or EM2. Unique insights emerge into the novel genetic mechanism and hierarchy determining BP in the Dahl salt-sensitive SS/Jr (DSS) rat model that implicate a portion of human QTLs. Elucidating the pathways underlying EM1 and EM2 may reveal the genetic regulation of BP.

Event-Triggered Distributed Approximate Optimal State and Output Control of Affine Nonlinear Interconnected Systems.

PubMed

Narayanan, Vignesh; Jagannathan, Sarangapani

2017-06-08

This paper presents an approximate optimal distributed control scheme for a known interconnected system composed of input affine nonlinear subsystems using event-triggered state and output feedback via a novel hybrid learning scheme. First, the cost function for the overall system is redefined as the sum of cost functions of individual subsystems. A distributed optimal control policy for the interconnected system is developed using the optimal value function of each subsystem. To generate the optimal control policy, forward-in-time, neural networks are employed to reconstruct the unknown optimal value function at each subsystem online. In order to retain the advantages of event-triggered feedback for an adaptive optimal controller, a novel hybrid learning scheme is proposed to reduce the convergence time for the learning algorithm. The development is based on the observation that, in the event-triggered feedback, the sampling instants are dynamic and results in variable interevent time. To relax the requirement of entire state measurements, an extended nonlinear observer is designed at each subsystem to recover the system internal states from the measurable feedback. Using a Lyapunov-based analysis, it is demonstrated that the system states and the observer errors remain locally uniformly ultimately bounded and the control policy converges to a neighborhood of the optimal policy. Simulation results are presented to demonstrate the performance of the developed controller.

Influence of posterior dental arch length on brain activity during chewing in patients with mandibular distal extension removable partial dentures.

PubMed

Shoi, K; Fueki, K; Usui, N; Taira, M; Wakabayashi, N

2014-07-01

It is well known that shortened dental arch decreases masticatory function. However, its potential to change brain activity during mastication is unknown. The present study investigates the effect of a shortened posterior dental arch with mandibular removable partial dentures (RPDs) on brain activity during gum chewing. Eleven subjects with missing mandibular molars (mean age, 66.1 years) on both sides received experimental RPDs with interchangeable artificial molars in a crossover trial design. Brain activity during gum chewing with RPDs containing (full dental arch) and lacking artificial molars (shortened dental arch) was measured using functional magnetic resonance imaging. Additionally, masticatory function was evaluated for each dental arch type. Food comminuting and mixing ability and the perceived chewing ability were significantly lower in subjects with a shortened dental arch than those with a full dental arch (P < 0.05). Brain activation during gum chewing with the full dental arch occurred in the middle frontal gyrus, primary sensorimotor cortex extending to the pre-central gyrus, supplementary motor area, putamen, insula and cerebellum. However, middle frontal gyrus activation was not observed during gum chewing with the shortened dental arch. These results suggest that shortened dental arch affects human brain activity in the middle frontal gyrus during gum chewing, and the decreased middle frontal gyrus activation may be associated with decreased masticatory function. © 2014 John Wiley & Sons Ltd.

Changes in brain activation induced by visual stimulus during and after propofol conscious sedation: a functional MRI study.

PubMed

Shinohe, Yutaka; Higuchi, Satomi; Sasaki, Makoto; Sato, Masahito; Noda, Mamoru; Joh, Shigeharu; Satoh, Kenichi

2016-12-07

Conscious sedation with propofol sometimes causes amnesia while keeping the patient awake. However, it remains unknown how propofol compromises the memory function. Therefore, we investigated the changes in brain activation induced by visual stimulation during and after conscious sedation with propofol using serial functional MRI. Healthy volunteers received a target-controlled infusion of propofol, and underwent functional MRI scans with a block-design paradigm of visual stimulus before, during, and after conscious sedation. Random-effect model analyses were performed using Statistical Parametric Mapping software. Among the areas showing significant activation in response to the visual stimulus, the visual cortex and fusiform gyrus were significantly suppressed in the sedation session and tended to recover in the early-recovery session of ∼20 min (P<0.001, uncorrected). In contrast, decreased activations of the hippocampus, thalamus, inferior frontal cortex (ventrolateral prefrontal cortex), and cerebellum were maintained during the sedation and early-recovery sessions (P<0.001, uncorrected) and were recovered in the late-recovery session of ∼40 min. Temporal changes in the signals from these areas varied in a manner comparable to that described by the random-effect model analysis (P<0.05, corrected). In conclusion, conscious sedation with propofol may cause prolonged suppression of the activation of memory-related structures, such as the hippocampus, during the early-recovery period, which may lead to transient amnesia.

A resource for functional profiling of noncoding RNA in the yeast Saccharomyces cerevisiae.

PubMed

Parker, Steven; Fraczek, Marcin G; Wu, Jian; Shamsah, Sara; Manousaki, Alkisti; Dungrattanalert, Kobchai; de Almeida, Rogerio Alves; Estrada-Rivadeneyra, Diego; Omara, Walid; Delneri, Daniela; O'Keefe, Raymond T

2017-08-01

Eukaryotic genomes are extensively transcribed, generating many different RNAs with no known function. We have constructed 1502 molecular barcoded ncRNA gene deletion strains encompassing 443 ncRNAs in the yeast Saccharomyces cerevisiae as tools for ncRNA functional analysis. This resource includes deletions of small nuclear RNAs (snRNAs), transfer RNAs (tRNAs), small nucleolar RNAs (snoRNAs), and other annotated ncRNAs as well as the more recently identified stable unannotated transcripts (SUTs) and cryptic unstable transcripts (CUTs) whose functions are largely unknown. Specifically, deletions have been constructed for ncRNAs found in the intergenic regions, not overlapping genes or their promoters (i.e., at least 200 bp minimum distance from the closest gene start codon). The deletion strains carry molecular barcodes designed to be complementary with the protein gene deletion collection enabling parallel analysis experiments. These strains will be useful for the numerous genomic and molecular techniques that utilize deletion strains, including genome-wide phenotypic screens under different growth conditions, pooled chemogenomic screens with drugs or chemicals, synthetic genetic array analysis to uncover novel genetic interactions, and synthetic dosage lethality screens to analyze gene dosage. Overall, we created a valuable resource for the RNA community and for future ncRNA research. © 2017 Parker et al.; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

Recognition of functional sites in protein structures.

PubMed

Shulman-Peleg, Alexandra; Nussinov, Ruth; Wolfson, Haim J

2004-06-04

Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.

Gut vagal sensory signaling regulates hippocampus function through multi-order pathways.

PubMed

Suarez, Andrea N; Hsu, Ted M; Liu, Clarissa M; Noble, Emily E; Cortella, Alyssa M; Nakamoto, Emily M; Hahn, Joel D; de Lartigue, Guillaume; Kanoski, Scott E

2018-06-05

The vagus nerve is the primary means of neural communication between the gastrointestinal (GI) tract and the brain. Vagally mediated GI signals activate the hippocampus (HPC), a brain region classically linked with memory function. However, the endogenous relevance of GI-derived vagal HPC communication is unknown. Here we utilize a saporin (SAP)-based lesioning procedure to reveal that selective GI vagal sensory/afferent ablation in rats impairs HPC-dependent episodic and spatial memory, effects associated with reduced HPC neurotrophic and neurogenesis markers. To determine the neural pathways connecting the gut to the HPC, we utilize monosynaptic and multisynaptic virus-based tracing methods to identify the medial septum as a relay connecting the medial nucleus tractus solitarius (where GI vagal afferents synapse) to dorsal HPC glutamatergic neurons. We conclude that endogenous GI-derived vagal sensory signaling promotes HPC-dependent memory function via a multi-order brainstem-septal pathway, thereby identifying a previously unknown role for the gut-brain axis in memory control.

Crystal structure of the toxin Msmeg_6760, the structural homolog of Mycobacterium tuberculosis Rv2035, a novel type II toxin involved in the hypoxic response

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

Bajaj, R. Alexandra; Arbing, Mark A.; Shin, Annie

The structure of Msmeg_6760, a protein of unknown function, has been determined. Biochemical and bioinformatics analyses determined that Msmeg_6760 interacts with a protein encoded in the same operon, Msmeg_6762, and predicted that the operon is a toxin–antitoxin (TA) system. Structural comparison of Msmeg_6760 with proteins of known function suggests that Msmeg_6760 binds a hydrophobic ligand in a buried cavity lined by large hydrophobic residues. Access to this cavity could be controlled by a gate–latch mechanism. The function of the Msmeg_6760 toxin is unknown, but structure-based predictions revealed that Msmeg_6760 and Msmeg_6762 are homologous to Rv2034 and Rv2035, a predicted novelmore » TA system involved inMycobacterium tuberculosislatency during macrophage infection. The Msmeg_6760 toxin fold has not been previously described for bacterial toxins and its unique structural features suggest that toxin activation is likely to be mediated by a novel mechanism.« less

Polychromatic sparse image reconstruction and mass attenuation spectrum estimation via B-spline basis function expansion

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

Gu, Renliang, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu; Dogandžić, Aleksandar, E-mail: Venliang@iastate.edu, E-mail: ald@iastate.edu

2015-03-31

We develop a sparse image reconstruction method for polychromatic computed tomography (CT) measurements under the blind scenario where the material of the inspected object and the incident energy spectrum are unknown. To obtain a parsimonious measurement model parameterization, we first rewrite the measurement equation using our mass-attenuation parameterization, which has the Laplace integral form. The unknown mass-attenuation spectrum is expanded into basis functions using a B-spline basis of order one. We develop a block coordinate-descent algorithm for constrained minimization of a penalized negative log-likelihood function, where constraints and penalty terms ensure nonnegativity of the spline coefficients and sparsity of themore » density map image in the wavelet domain. This algorithm alternates between a Nesterov’s proximal-gradient step for estimating the density map image and an active-set step for estimating the incident spectrum parameters. Numerical simulations demonstrate the performance of the proposed scheme.« less

Discontinuous dual-primal mixed finite elements for elliptic problems

NASA Technical Reports Server (NTRS)

Bottasso, Carlo L.; Micheletti, Stefano; Sacco, Riccardo

2000-01-01

We propose a novel discontinuous mixed finite element formulation for the solution of second-order elliptic problems. Fully discontinuous piecewise polynomial finite element spaces are used for the trial and test functions. The discontinuous nature of the test functions at the element interfaces allows to introduce new boundary unknowns that, on the one hand enforce the weak continuity of the trial functions, and on the other avoid the need to define a priori algorithmic fluxes as in standard discontinuous Galerkin methods. Static condensation is performed at the element level, leading to a solution procedure based on the sole interface unknowns. The resulting family of discontinuous dual-primal mixed finite element methods is presented in the one and two-dimensional cases. In the one-dimensional case, we show the equivalence of the method with implicit Runge-Kutta schemes of the collocation type exhibiting optimal behavior. Numerical experiments in one and two dimensions demonstrate the order accuracy of the new method, confirming the results of the analysis.

Dual adaptive dynamic control of mobile robots using neural networks.

PubMed

Bugeja, Marvin K; Fabri, Simon G; Camilleri, Liberato

2009-02-01

This paper proposes two novel dual adaptive neural control schemes for the dynamic control of nonholonomic mobile robots. The two schemes are developed in discrete time, and the robot's nonlinear dynamic functions are assumed to be unknown. Gaussian radial basis function and sigmoidal multilayer perceptron neural networks are used for function approximation. In each scheme, the unknown network parameters are estimated stochastically in real time, and no preliminary offline neural network training is used. In contrast to other adaptive techniques hitherto proposed in the literature on mobile robots, the dual control laws presented in this paper do not rely on the heuristic certainty equivalence property but account for the uncertainty in the estimates. This results in a major improvement in tracking performance, despite the plant uncertainty and unmodeled dynamics. Monte Carlo simulation and statistical hypothesis testing are used to illustrate the effectiveness of the two proposed stochastic controllers as applied to the trajectory-tracking problem of a differentially driven wheeled mobile robot.

A chromatographic objective function to characterise chromatograms with unknown compounds or without standards available.

PubMed

Alvarez-Segura, T; Gómez-Díaz, A; Ortiz-Bolsico, C; Torres-Lapasió, J R; García-Alvarez-Coque, M C

2015-08-28

Getting useful chemical information from samples containing many compounds is still a challenge to analysts in liquid chromatography. The highest complexity corresponds to samples for which there is no prior knowledge about their chemical composition. Computer-based methodologies are currently considered as the most efficient tools to optimise the chromatographic resolution, and further finding the optimal separation conditions. However, most chromatographic objective functions (COFs) described in the literature to measure the resolution are based on mathematical models fitted with the information obtained from standards, and cannot be applied to samples with unknown compounds. In this work, a new COF based on the automatic measurement of the protruding part of the chromatographic peaks (or peak prominences) that indicates the number of perceptible peaks and global resolution, without the need of standards, is developed. The proposed COF was found satisfactory with regard to the peak purity criterion when applied to artificial peaks and simulated chromatograms of mixtures built using the information of standards. The approach was applied to mixtures of drugs containing unknown impurities and degradation products and to extracts of medicinal herbs, eluted with acetonitrile-water mixtures using isocratic and gradient elution. Copyright © 2015 Elsevier B.V. All rights reserved.

Biological differences between the evolutionary lineages within Phytophthora ramorum and Phytophthora lateralis: Should the lineages be formally taxonomically designated?

Treesearch

Clive Brasier

2017-01-01

It is now generally accepted that the four evolutionary lineages of Phytophthora ramorum (informally designated NA1, NA2, EU1, and EU2) are relatively anciently divergent populations, recently introduced into Europe and North America from different, unknown geographic locations; that recombinants between them are genetically unstable and probably...

Food Microbiology--Design and Testing of a Virtual Laboratory Exercise

ERIC Educational Resources Information Center

Flint, Steve; Stewart, Terry

2010-01-01

A web-based virtual laboratory exercise in identifying an unknown microorganism was designed for use with a cohort of 3rd-year university food-technology students. They were presented with a food-contamination case, and then walked through a number of diagnostic steps to identify the microorganism. At each step, the students were asked to select 1…

Designing efficient nitrous oxide sampling strategies in agroecosystems using simulation models

Treesearch

Debasish Saha; Armen R. Kemanian; Benjamin M. Rau; Paul R. Adler; Felipe Montes

2017-01-01

Annual cumulative soil nitrous oxide (N2O) emissions calculated from discrete chamber-based flux measurements have unknown uncertainty. We used outputs from simulations obtained with an agroecosystem model to design sampling strategies that yield accurate cumulative N2O flux estimates with a known uncertainty level. Daily soil N2O fluxes were simulated for Ames, IA (...

The Design of Video-Based Professional Development: An Exploratory Experiment Intended to Identify Effective Features

ERIC Educational Resources Information Center

Beisiegel, Mary; Mitchell, Rebecca; Hill, Heather C.

2018-01-01

Although video cases and video clubs have become popular forms of teacher professional development, there have been few systematic investigations of designs for such programs. Programs may vary according to (a) whether teachers watch videos of their own/their peers' instruction, or whether teachers watch stock video of unknown teachers; and (b)…

Relationship between histopathological changes in post partum renal biopsies and renal function tests of African women with early onset pre-eclampsia.

PubMed

Khedun, S M; Naicker, T; Moodley, J

2000-05-01

To improve the diagnostic accuracy of concurrent renal disease in hypertension of pregnancy, biopsy evaluation is essential. In addition, establishing underlying renal disease is important for prognosis on future pregnancies. We therefore designed a study to determine the diagnostic yield of postpartum renal biopsy and the nature and frequency of complications associated with this procedure. Also, to determine relationships, if any, between renal function tests and ultrastructural and histopathological findings. Fifty renal biopsies were performed in the immediate postpartum period in black African women with early onset pre-eclampsia. Each biopsy specimen was placed in a separate container and coded so that sampling was unknown to the electron microscopist. Each biopsy specimen was divided into three parts, and processed and stained for light, fluorescent and transmission electron microscopy using conventional techniques. Renal tissue biopsies were adequate for diagnostic purposes in all cases. There were no complications in any of the 50 patients studied. Ultrastructural examination confirmed the light microscopy findings. In addition the ultrastructural findings showed intramembranous deposits, foot process fusion and mesangial deposits. In 16 patients with normal renal function tests; the biopsies evaluation from these patients showed ultrastructural changes. In the remaining 34 patients with abnormal renal function tests of varying severity; biopsy evaluation from these patients showed both ultrastructural and histopathological changes. Renal biopsy procedure is safe, and ultrastructural and histological findings obtained from postpartum renal biopsies are more informative than the routine renal function tests.

Fundamentals of translational neuroscience in toxicologic pathology: optimizing the value of animal data for human risk assessment.

PubMed

Morrison, James P; Sharma, Alok K; Rao, Deepa; Pardo, Ingrid D; Garman, Robert H; Kaufmann, Wolfgang; Bolon, Brad

2015-01-01

A half-day Society of Toxicologic Pathology continuing education course on "Fundamentals of Translational Neuroscience in Toxicologic Pathology" presented some current major issues faced when extrapolating animal data regarding potential neurological consequences to assess potential human outcomes. Two talks reviewed functional-structural correlates in rodent and nonrodent mammalian brains needed to predict behavioral consequences of morphologic changes in discrete neural cell populations. The third lecture described practical steps for ensuring that specimens from rodent developmental neurotoxicity tests will be processed correctly to produce highly homologous sections. The fourth talk detailed demographic factors (e.g., species, strain, sex, and age); physiological traits (body composition, brain circulation, pharmacokinetic/pharmacodynamic patterns, etc.); and husbandry influences (e.g., group housing) known to alter the effects of neuroactive agents. The last presentation discussed the appearance, unknown functional effects, and potential relevance to humans of polyethylene glycol (PEG)-associated vacuoles within the choroid plexus epithelium of animals. Speakers provided real-world examples of challenges with data extrapolation among species or with study design considerations that may impact the interpretability of results. Translational neuroscience will be bolstered in the future as less invasive and/or more quantitative techniques are devised for linking overt functional deficits to subtle anatomic and chemical lesions. © 2014 by The Author(s).

Genes expressed during the development and ripening of watermelon fruit.

PubMed

Levi, A; Davis, A; Hernandez, A; Wechter, P; Thimmapuram, J; Trebitsh, T; Tadmor, Y; Katzir, N; Portnoy, V; King, S

2006-11-01

A normalized cDNA library was constructed using watermelon flesh mRNA from three distinct developmental time-points and was subtracted by hybridization with leaf cDNA. Random cDNA clones of the watermelon flesh subtraction library were sequenced from the 5' end in order to identify potentially informative genes associated with fruit setting, development, and ripening. One-thousand and forty-six 5'-end sequences (expressed sequence tags; ESTs) were assembled into 832 non-redundant sequences, designated as "EST-unigenes". Of these 832 "EST-unigenes", 254 ( approximately 30%) have no significant homology to sequences published so far for other plant species. Additionally, 168 "EST-unigenes" ( approximately 20%) correspond to genes with unknown function, whereas 410 "EST-unigenes" ( approximately 50%) correspond to genes with known function in other plant species. These "EST-unigenes" are mainly associated with metabolism, membrane transport, cytoskeleton synthesis and structure, cell wall formation and cell division, signal transduction, nucleic acid binding and transcription factors, defense and stress response, and secondary metabolism. This study provides the scientific community with novel genetic information for watermelon as well as an expanded pool of genes associated with fruit development in watermelon. These genes will be useful targets in future genetic and functional genomic studies of watermelon and its development.

Cloning of a human homolog of the yeast nucleotide excision repair gene MMS19 and interaction with transcription repair factor TFIIH via the XPB and XPD helicases.

PubMed

Seroz, T; Winkler, G S; Auriol, J; Verhage, R A; Vermeulen, W; Smit, B; Brouwer, J; Eker, A P; Weeda, G; Egly, J M; Hoeijmakers, J H

2000-11-15

Nucleotide excision repair (NER) removes UV-induced photoproducts and numerous other DNA lesions in a highly conserved 'cut-and-paste' reaction that involves approximately 25 core components. In addition, several other proteins have been identified which are dispensable for NER in vitro but have an undefined role in vivo and may act at the interface of NER and other cellular processes. An intriguing example is the Saccharomyces cerevisiae Mms19 protein that has an unknown dual function in NER and RNA polymerase II transcription. Here we report the cloning and characterization of a human homolog, designated hMMS19, that encodes a 1030 amino acid protein with 26% identity and 51% similarity to S.cerevisiae Mms19p and with a strikingly similar size. The expression profile and nuclear location are consistent with a repair function. Co-immunoprecipitation experiments revealed that hMMS19 directly interacts with the XPB and XPD subunits of NER-transcription factor TFIIH. These findings extend the conservation of the NER apparatus and the link between NER and basal transcription and suggest that hMMS19 exerts its function in repair and transcription by interacting with the XPB and XPD helicases.

Analyte species and concentration identification using differentially functionalized microcantilever arrays and artificial neural networks

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

Senesac, Larry R; Datskos, Panos G; Sepaniak, Michael J

2006-01-01

In the present work, we have performed analyte species and concentration identification using an array of ten differentially functionalized microcantilevers coupled with a back-propagation artificial neural network pattern recognition algorithm. The array consists of ten nanostructured silicon microcantilevers functionalized by polymeric and gas chromatography phases and macrocyclic receptors as spatially dense, differentially responding sensing layers for identification and quantitation of individual analyte(s) and their binary mixtures. The array response (i.e. cantilever bending) to analyte vapor was measured by an optical readout scheme and the responses were recorded for a selection of individual analytes as well as several binary mixtures. Anmore » artificial neural network (ANN) was designed and trained to recognize not only the individual analytes and binary mixtures, but also to determine the concentration of individual components in a mixture. To the best of our knowledge, ANNs have not been applied to microcantilever array responses previously to determine concentrations of individual analytes. The trained ANN correctly identified the eleven test analyte(s) as individual components, most with probabilities greater than 97%, whereas it did not misidentify an unknown (untrained) analyte. Demonstrated unique aspects of this work include an ability to measure binary mixtures and provide both qualitative (identification) and quantitative (concentration) information with array-ANN-based sensor methodologies.« less