Interference effects in learning similar sequences of discrete movements
Koedijker, J.M.; Oudejans, R.R.D.; Beek, P.J.
2010-01-01
Three experiments were conducted to examine proactive and retroactive interference effects in learning two similar sequences of discrete movements. In each experiment, the participants in the experimental group practiced two movement sequences on consecutive days (1 on each day, order
Learning Bayesian networks for discrete data
Liang, Faming; Zhang, Jian
2009-01-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly
Learning Bayesian networks for discrete data
Liang, Faming
2009-02-01
Bayesian networks have received much attention in the recent literature. In this article, we propose an approach to learn Bayesian networks using the stochastic approximation Monte Carlo (SAMC) algorithm. Our approach has two nice features. Firstly, it possesses the self-adjusting mechanism and thus avoids essentially the local-trap problem suffered by conventional MCMC simulation-based approaches in learning Bayesian networks. Secondly, it falls into the class of dynamic importance sampling algorithms; the network features can be inferred by dynamically weighted averaging the samples generated in the learning process, and the resulting estimates can have much lower variation than the single model-based estimates. The numerical results indicate that our approach can mix much faster over the space of Bayesian networks than the conventional MCMC simulation-based approaches. © 2008 Elsevier B.V. All rights reserved.
Switching dynamics in reaction networks induced by molecular discreteness
International Nuclear Information System (INIS)
Togashi, Yuichi; Kaneko, Kunihiko
2007-01-01
To study the fluctuations and dynamics in chemical reaction processes, stochastic differential equations based on the rate equation involving chemical concentrations are often adopted. When the number of molecules is very small, however, the discreteness in the number of molecules cannot be neglected since the number of molecules must be an integer. This discreteness can be important in biochemical reactions, where the total number of molecules is not significantly larger than the number of chemical species. To elucidate the effects of such discreteness, we study autocatalytic reaction systems comprising several chemical species through stochastic particle simulations. The generation of novel states is observed; it is caused by the extinction of some molecular species due to the discreteness in their number. We demonstrate that the reaction dynamics are switched by a single molecule, which leads to the reconstruction of the acting network structure. We also show the strong dependence of the chemical concentrations on the system size, which is caused by transitions to discreteness-induced novel states
Fast and Epsilon-Optimal Discretized Pursuit Learning Automata.
Zhang, JunQi; Wang, Cheng; Zhou, MengChu
2015-10-01
Learning automata (LA) are powerful tools for reinforcement learning. A discretized pursuit LA is the most popular one among them. During an iteration its operation consists of three basic phases: 1) selecting the next action; 2) finding the optimal estimated action; and 3) updating the state probability. However, when the number of actions is large, the learning becomes extremely slow because there are too many updates to be made at each iteration. The increased updates are mostly from phases 1 and 3. A new fast discretized pursuit LA with assured ε -optimality is proposed to perform both phases 1 and 3 with the computational complexity independent of the number of actions. Apart from its low computational complexity, it achieves faster convergence speed than the classical one when operating in stationary environments. This paper can promote the applications of LA toward the large-scale-action oriented area that requires efficient reinforcement learning tools with assured ε -optimality, fast convergence speed, and low computational complexity for each iteration.
Discretization of the induced-charge boundary integral equation.
Bardhan, Jaydeep P; Eisenberg, Robert S; Gillespie, Dirk
2009-07-01
Boundary-element methods (BEMs) for solving integral equations numerically have been used in many fields to compute the induced charges at dielectric boundaries. In this paper, we consider a more accurate implementation of BEM in the context of ions in aqueous solution near proteins, but our results are applicable more generally. The ions that modulate protein function are often within a few angstroms of the protein, which leads to the significant accumulation of polarization charge at the protein-solvent interface. Computing the induced charge accurately and quickly poses a numerical challenge in solving a popular integral equation using BEM. In particular, the accuracy of simulations can depend strongly on seemingly minor details of how the entries of the BEM matrix are calculated. We demonstrate that when the dielectric interface is discretized into flat tiles, the qualocation method of Tausch [IEEE Trans Comput.-Comput.-Aided Des. 20, 1398 (2001)] to compute the BEM matrix elements is always more accurate than the traditional centroid-collocation method. Qualocation is not more expensive to implement than collocation and can save significant computational time by reducing the number of boundary elements needed to discretize the dielectric interfaces.
Discretization of the induced-charge boundary integral equation.
Energy Technology Data Exchange (ETDEWEB)
Bardhan, J. P.; Eisenberg, R. S.; Gillespie, D.; Rush Univ. Medical Center
2009-07-01
Boundary-element methods (BEMs) for solving integral equations numerically have been used in many fields to compute the induced charges at dielectric boundaries. In this paper, we consider a more accurate implementation of BEM in the context of ions in aqueous solution near proteins, but our results are applicable more generally. The ions that modulate protein function are often within a few angstroms of the protein, which leads to the significant accumulation of polarization charge at the protein-solvent interface. Computing the induced charge accurately and quickly poses a numerical challenge in solving a popular integral equation using BEM. In particular, the accuracy of simulations can depend strongly on seemingly minor details of how the entries of the BEM matrix are calculated. We demonstrate that when the dielectric interface is discretized into flat tiles, the qualocation method of Tausch et al. [IEEE Trans Comput.-Comput.-Aided Des. 20, 1398 (2001)] to compute the BEM matrix elements is always more accurate than the traditional centroid-collocation method. Qualocation is not more expensive to implement than collocation and can save significant computational time by reducing the number of boundary elements needed to discretize the dielectric interfaces.
The Effect of Haptic Guidance on Learning a Hybrid Rhythmic-Discrete Motor Task.
Marchal-Crespo, Laura; Bannwart, Mathias; Riener, Robert; Vallery, Heike
2015-01-01
Bouncing a ball with a racket is a hybrid rhythmic-discrete motor task, combining continuous rhythmic racket movements with discrete impact events. Rhythmicity is exceptionally important in motor learning, because it underlies fundamental movements such as walking. Studies suggested that rhythmic and discrete movements are governed by different control mechanisms at different levels of the Central Nervous System. The aim of this study is to evaluate the effect of fixed/fading haptic guidance on learning to bounce a ball to a desired apex in virtual reality with varying gravity. Changing gravity changes dominance of rhythmic versus discrete control: The higher the value of gravity, the more rhythmic the task; lower values reduce the bouncing frequency and increase dwell times, eventually leading to a repetitive discrete task that requires initiation and termination, resembling target-oriented reaching. Although motor learning in the ball-bouncing task with varying gravity has been studied, the effect of haptic guidance on learning such a hybrid rhythmic-discrete motor task has not been addressed. We performed an experiment with thirty healthy subjects and found that the most effective training condition depended on the degree of rhythmicity: Haptic guidance seems to hamper learning of continuous rhythmic tasks, but it seems to promote learning for repetitive tasks that resemble discrete movements.
Discretization-induced delays and their role in the dynamics
International Nuclear Information System (INIS)
Ramani, A; Grammaticos, B; Satsuma, J; Willox, R
2008-01-01
We show that a discretization of a continuous system may entail 'hidden' delays and thus introduce instabilities. In this case, while the continuous system has an attractive fixed point, the instabilities present in the equivalent discrete one may lead to the appearance of a limit cycle. We explain that it is possible, thanks to the proper staggering of the discrete variables, to eliminate the hidden delay. However, in general, other instabilities may appear in the discrete system which can even lead to chaotic behaviour
Paterson, Judy; Sneddon, Jamie
2011-01-01
This article reports on the learning conversations between a mathematician and a mathematics educator as they worked together to change the delivery model of a third year discrete mathematics course from a traditional lecture mode to team-based learning (TBL). This change prompted the mathematician to create team tasks which increasingly focused…
Discrete Learning Control with Application to Hydraulic Actuators
DEFF Research Database (Denmark)
Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Hansen, Michael R.
2015-01-01
In this paper the robustness of a class of learning control algorithms to state disturbances, output noise, and errors in initial conditions is studied. We present a simple learning algorithm and exhibit, via a concise proof, bounds on the asymptotic trajectory errors for the learned input...... and the corresponding state and output trajectories. Furthermore, these bounds are continuous functions of the bounds on the initial condition errors, state disturbance, and output noise, and the bounds are zero in the absence of these disturbances....
Evolutionarily stable learning schedules and cumulative culture in discrete generation models.
Aoki, Kenichi; Wakano, Joe Yuichiro; Lehmann, Laurent
2012-06-01
Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium. Copyright © 2012 Elsevier Inc. All rights reserved.
Yang, Peng; Kajiwara, Riki; Tonoki, Ayako; Itoh, Motoyuki
2018-05-01
We designed an automated device to study active avoidance learning abilities of zebrafish. Open source tools were used for the device control, statistical computing, and graphic outputs of data. Using the system, we developed active avoidance tests to examine the effects of trial spacing and aging on learning. Seven-month-old fish showed stronger avoidance behavior as measured by color preference index with discrete spaced training as compared to successive spaced training. Fifteen-month-old fish showed a similar trend, but with reduced cognitive abilities compared with 7-month-old fish. Further, in 7-month-old fish, an increase in learning ability during trials was observed with discrete, but not successive, spaced training. In contrast, 15-month-old fish did not show increase in learning ability during trials. Therefore, these data suggest that discrete spacing is more effective for learning than successive spacing, with the zebrafish active avoidance paradigm, and that the time course analysis of active avoidance using discrete spaced training is useful to detect age-related learning impairment. Copyright © 2017 Elsevier Ireland Ltd and Japan Neuroscience Society. All rights reserved.
Hall, Scott S.; Hustyi, Kristin M.; Hammond, Jennifer L.; Hirt, Melissa; Reiss, Allan L.
2014-01-01
We examined whether "discrete trial training" (DTT) could be used to identify learning impairments in mathematical reasoning in boys with fragile X syndrome (FXS). Boys with FXS, aged 10-23 years, and age and IQ-matched controls, were trained to match fractions to pie-charts and pie-charts to decimals either on a computer or with a…
Preventing Noise-Induced Extinction in Discrete Population Models
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Irina Bashkirtseva
2017-01-01
Full Text Available A problem of the analysis and prevention of noise-induced extinction in nonlinear population models is considered. For the solution of this problem, we suggest a general approach based on the stochastic sensitivity analysis. To prevent the noise-induced extinction, we construct feedback regulators which provide a low stochastic sensitivity and keep the system close to the safe equilibrium regime. For the demonstration of this approach, we apply our mathematical technique to the conceptual but quite representative Ricker-type models. A variant of the Ricker model with delay is studied along with the classic widely used one-dimensional system.
Autonomous learning by simple dynamical systems with a discrete-time formulation
Bilen, Agustín M.; Kaluza, Pablo
2017-05-01
We present a discrete-time formulation for the autonomous learning conjecture. The main feature of this formulation is the possibility to apply the autonomous learning scheme to systems in which the errors with respect to target functions are not well-defined for all times. This restriction for the evaluation of functionality is a typical feature in systems that need a finite time interval to process a unit piece of information. We illustrate its application on an artificial neural network with feed-forward architecture for classification and a phase oscillator system with synchronization properties. The main characteristics of the discrete-time formulation are shown by constructing these systems with predefined functions.
Electrostatic potential fluctuation induced by charge discreteness in a nanoscale trench
International Nuclear Information System (INIS)
Lee, Taesang; Kim, S. S.; Jho, Y. S.; Park, Gunyoung; Chang, C. S.
2007-01-01
A simplified two-dimensional Monte Carlo simulation is performed to estimate the charging potential fluctuations caused by strong binary Coulomb interactions between discrete charged particles in nanometer scale trenches. It is found that the discrete charge effect can be an important part of the nanoscale trench research, inducing scattering of ion trajectories in a nanoscale trench by a fluctuating electric field. The effect can enhance the ion deposition on the side walls and disperse the material contact energy of the incident ions, among others
Theory and simulation of discrete kinetic beta induced Alfven eigenmode in tokamak plasmas
International Nuclear Information System (INIS)
Wang, X; Zonca, F; Chen, L
2010-01-01
It is shown, both analytically and by numerical simulations, that, in the presence of thermal ion kinetic effects, the beta induced Alfven eigenmode (BAE)-shear Alfven wave continuous spectrum can be discretized into radially trapped eigenstates known as kinetic BAE (KBAE). While thermal ion compressibility gives rise to finite BAE accumulation point frequency, the discretization occurs via the finite Larmor radius and finite orbit width effects. Simulations and analytical theories agree both qualitatively and quantitatively. Simulations also demonstrate that KBAE can be readily excited by the finite radial gradients of energetic particles.
Discrete-Time Stable Generalized Self-Learning Optimal Control With Approximation Errors.
Wei, Qinglai; Li, Benkai; Song, Ruizhuo
2018-04-01
In this paper, a generalized policy iteration (GPI) algorithm with approximation errors is developed for solving infinite horizon optimal control problems for nonlinear systems. The developed stable GPI algorithm provides a general structure of discrete-time iterative adaptive dynamic programming algorithms, by which most of the discrete-time reinforcement learning algorithms can be described using the GPI structure. It is for the first time that approximation errors are explicitly considered in the GPI algorithm. The properties of the stable GPI algorithm with approximation errors are analyzed. The admissibility of the approximate iterative control law can be guaranteed if the approximation errors satisfy the admissibility criteria. The convergence of the developed algorithm is established, which shows that the iterative value function is convergent to a finite neighborhood of the optimal performance index function, if the approximate errors satisfy the convergence criterion. Finally, numerical examples and comparisons are presented.
Parallel, but Dissociable, Processing in Discrete Corticostriatal Inputs Encodes Skill Learning.
Kupferschmidt, David A; Juczewski, Konrad; Cui, Guohong; Johnson, Kari A; Lovinger, David M
2017-10-11
Changes in cortical and striatal function underlie the transition from novel actions to refined motor skills. How discrete, anatomically defined corticostriatal projections function in vivo to encode skill learning remains unclear. Using novel fiber photometry approaches to assess real-time activity of associative inputs from medial prefrontal cortex to dorsomedial striatum and sensorimotor inputs from motor cortex to dorsolateral striatum, we show that associative and sensorimotor inputs co-engage early in action learning and disengage in a dissociable manner as actions are refined. Disengagement of associative, but not sensorimotor, inputs predicts individual differences in subsequent skill learning. Divergent somatic and presynaptic engagement in both projections during early action learning suggests potential learning-related in vivo modulation of presynaptic corticostriatal function. These findings reveal parallel processing within associative and sensorimotor circuits that challenges and refines existing views of corticostriatal function and expose neuronal projection- and compartment-specific activity dynamics that encode and predict action learning. Published by Elsevier Inc.
McGeachie, Michael J; Chang, Hsun-Hsien; Weiss, Scott T
2014-06-01
Bayesian Networks (BN) have been a popular predictive modeling formalism in bioinformatics, but their application in modern genomics has been slowed by an inability to cleanly handle domains with mixed discrete and continuous variables. Existing free BN software packages either discretize continuous variables, which can lead to information loss, or do not include inference routines, which makes prediction with the BN impossible. We present CGBayesNets, a BN package focused around prediction of a clinical phenotype from mixed discrete and continuous variables, which fills these gaps. CGBayesNets implements Bayesian likelihood and inference algorithms for the conditional Gaussian Bayesian network (CGBNs) formalism, one appropriate for predicting an outcome of interest from, e.g., multimodal genomic data. We provide four different network learning algorithms, each making a different tradeoff between computational cost and network likelihood. CGBayesNets provides a full suite of functions for model exploration and verification, including cross validation, bootstrapping, and AUC manipulation. We highlight several results obtained previously with CGBayesNets, including predictive models of wood properties from tree genomics, leukemia subtype classification from mixed genomic data, and robust prediction of intensive care unit mortality outcomes from metabolomic profiles. We also provide detailed example analysis on public metabolomic and gene expression datasets. CGBayesNets is implemented in MATLAB and available as MATLAB source code, under an Open Source license and anonymous download at http://www.cgbayesnets.com.
Genome-wide prediction of discrete traits using bayesian regressions and machine learning
Directory of Open Access Journals (Sweden)
Forni Selma
2011-02-01
Full Text Available Abstract Background Genomic selection has gained much attention and the main goal is to increase the predictive accuracy and the genetic gain in livestock using dense marker information. Most methods dealing with the large p (number of covariates small n (number of observations problem have dealt only with continuous traits, but there are many important traits in livestock that are recorded in a discrete fashion (e.g. pregnancy outcome, disease resistance. It is necessary to evaluate alternatives to analyze discrete traits in a genome-wide prediction context. Methods This study shows two threshold versions of Bayesian regressions (Bayes A and Bayesian LASSO and two machine learning algorithms (boosting and random forest to analyze discrete traits in a genome-wide prediction context. These methods were evaluated using simulated and field data to predict yet-to-be observed records. Performances were compared based on the models' predictive ability. Results The simulation showed that machine learning had some advantages over Bayesian regressions when a small number of QTL regulated the trait under pure additivity. However, differences were small and disappeared with a large number of QTL. Bayesian threshold LASSO and boosting achieved the highest accuracies, whereas Random Forest presented the highest classification performance. Random Forest was the most consistent method in detecting resistant and susceptible animals, phi correlation was up to 81% greater than Bayesian regressions. Random Forest outperformed other methods in correctly classifying resistant and susceptible animals in the two pure swine lines evaluated. Boosting and Bayes A were more accurate with crossbred data. Conclusions The results of this study suggest that the best method for genome-wide prediction may depend on the genetic basis of the population analyzed. All methods were less accurate at correctly classifying intermediate animals than extreme animals. Among the different
DROpS: an object of learning in computer simulation of discrete events
Directory of Open Access Journals (Sweden)
Hugo Alves Silva Ribeiro
2015-09-01
Full Text Available This work presents the “Realistic Dynamics Of Simulated Operations” (DROpS, the name given to the dynamics using the “dropper” device as an object of teaching and learning. The objective is to present alternatives for professors teaching content related to simulation of discrete events to graduate students in production engineering. The aim is to enable students to develop skills related to data collection, modeling, statistical analysis, and interpretation of results. This dynamic has been developed and applied to the students by placing them in a situation analogous to a real industry, where various concepts related to computer simulation were discussed, allowing the students to put these concepts into practice in an interactive manner, thus facilitating learning
Directory of Open Access Journals (Sweden)
Jian Ding
2014-01-01
Full Text Available This paper addresses the problem of P-type iterative learning control for a class of multiple-input multiple-output linear discrete-time systems, whose aim is to develop robust monotonically convergent control law design over a finite frequency range. It is shown that the 2 D iterative learning control processes can be taken as 1 D state space model regardless of relative degree. With the generalized Kalman-Yakubovich-Popov lemma applied, it is feasible to describe the monotonically convergent conditions with the help of linear matrix inequality technique and to develop formulas for the control gain matrices design. An extension to robust control law design against systems with structured and polytopic-type uncertainties is also considered. Two numerical examples are provided to validate the feasibility and effectiveness of the proposed method.
Indirect iterative learning control for a discrete visual servo without a camera-robot model.
Jiang, Ping; Bamforth, Leon C A; Feng, Zuren; Baruch, John E F; Chen, YangQuan
2007-08-01
This paper presents a discrete learning controller for vision-guided robot trajectory imitation with no prior knowledge of the camera-robot model. A teacher demonstrates a desired movement in front of a camera, and then, the robot is tasked to replay it by repetitive tracking. The imitation procedure is considered as a discrete tracking control problem in the image plane, with an unknown and time-varying image Jacobian matrix. Instead of updating the control signal directly, as is usually done in iterative learning control (ILC), a series of neural networks are used to approximate the unknown Jacobian matrix around every sample point in the demonstrated trajectory, and the time-varying weights of local neural networks are identified through repetitive tracking, i.e., indirect ILC. This makes repetitive segmented training possible, and a segmented training strategy is presented to retain the training trajectories solely within the effective region for neural network approximation. However, a singularity problem may occur if an unmodified neural-network-based Jacobian estimation is used to calculate the robot end-effector velocity. A new weight modification algorithm is proposed which ensures invertibility of the estimation, thus circumventing the problem. Stability is further discussed, and the relationship between the approximation capability of the neural network and the tracking accuracy is obtained. Simulations and experiments are carried out to illustrate the validity of the proposed controller for trajectory imitation of robot manipulators with unknown time-varying Jacobian matrices.
GÖKCE, Kürşad; UYAROĞLU, Yılmaz
2013-01-01
This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Hénon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Hénon system verifies the validity of the proposed control system.
An induced charge readout scheme incorporating image charge splitting on discrete pixels
International Nuclear Information System (INIS)
Kataria, D.O.; Lapington, J.S.
2003-01-01
Top hat electrostatic analysers used in space plasma instruments typically use microchannel plates (MCPs) followed by discrete pixel anode readout for the angular definition of the incoming particles. Better angular definition requires more pixels/readout electronics channels but with stringent mass and power budgets common in space applications, the number of channels is restricted. We describe here a technique that improves the angular definition using induced charge and an interleaved anode pattern. The technique adopts the readout philosophy used on the CRRES and CLUSTER I instruments but has the advantages of the induced charge scheme and significantly reduced capacitance. Charge from the MCP collected by an anode pixel is inductively split onto discrete pixels whose geometry can be tailored to suit the scientific requirements of the instrument. For our application, the charge is induced over two pixels. One of them is used for a coarse angular definition but is read out by a single channel of electronics, allowing a higher rate handling. The other provides a finer angular definition but is interleaved and hence carries the expense of lower rate handling. Using the technique and adding four channels of electronics, a four-fold increase in the angular resolution is obtained. Details of the scheme and performance results are presented
Dynamics of a discrete geotropic sensor subject to rotation-induced gravity compensation
Energy Technology Data Exchange (ETDEWEB)
Silver, I.L.
1976-01-01
A clinostat achieves gravity compensation by providing circular rotation with uniform speed, about a horizontal axis. The dynamics of an assumed, discrete and free-moving subcellular gravity receptor, subject to clinostat rotation, is analyzed. The results imply that there is an optimum rotation rate; higher speeds result in circular motions with diameters more comparable to thermal noise fluctuations, but with greater linear velocities due to increasing centrifugal forces. An optimizing function is proposed. The nucleolus and mitochondrion is chosen as a gravity receptor for illustrating the use of this theory. The characteristics of their clinostat-induced motions are incorporated with experimental results on Avena plant shoots in an illustrative example.
Unsupervised Learning for Efficient Texture Estimation From Limited Discrete Orientation Data
Niezgoda, Stephen R.; Glover, Jared
2013-11-01
The estimation of orientation distribution functions (ODFs) from discrete orientation data, as produced by electron backscatter diffraction or crystal plasticity micromechanical simulations, is typically achieved via techniques such as the Williams-Imhof-Matthies-Vinel (WIMV) algorithm or generalized spherical harmonic expansions, which were originally developed for computing an ODF from pole figures measured by X-ray or neutron diffraction. These techniques rely on ad-hoc methods for choosing parameters, such as smoothing half-width and bandwidth, and for enforcing positivity constraints and appropriate normalization. In general, such approaches provide little or no information-theoretic guarantees as to their optimality in describing the given dataset. In the current study, an unsupervised learning algorithm is proposed which uses a finite mixture of Bingham distributions for the estimation of ODFs from discrete orientation data. The Bingham distribution is an antipodally-symmetric, max-entropy distribution on the unit quaternion hypersphere. The proposed algorithm also introduces a minimum message length criterion, a common tool in information theory for balancing data likelihood with model complexity, to determine the number of components in the Bingham mixture. This criterion leads to ODFs which are less likely to overfit (or underfit) the data, eliminating the need for a priori parameter choices.
Discrete emotions and persuasion: the role of emotion-induced expectancies.
DeSteno, David; Petty, Richard E; Rucker, Derek D; Wegener, Duane T; Braverman, Julia
2004-01-01
The authors argue that specific emotions can alter the persuasive impact of messages as a function of the emotional framing of persuasive appeals. Because specific emotions inflate expectancies for events possessing matching emotional overtones (D. DeSteno, R. E. Petty, D. T. Wegener, & D. D. Rucker, 2000), the authors predicted that attempts at persuasion would be more successful when messages were framed with emotional overtones matching the emotional state of the receiver and that these changes would be mediated by emotion-induced biases involving expectancies attached to arguments contained in the messages. Two studies manipulating discrete negative emotional states and message frames (i.e., sadness and anger) confirmed these predictions. The functioning of this emotion-matching bias in parallel with emotion-induced processing differences and the limitations of a valence-based approach to the study of attitude change are also considered.
Discrete Teaching-learning-based optimization Algorithm for Traveling Salesman Problems
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Wu Lehui
2017-01-01
Full Text Available In this paper, a discrete variant of TLBO (DTLBO is proposed for solving the traveling salesman problem (TSP. In the proposed method, an effective learner representation scheme is redefined based on the characteristics of TSP problem. Moreover, all learners are randomly divided into several sub-swarms with equal amounts of learners so as to increase the diversity of population and reduce the probability of being trapped in local optimum. In each sub-swarm, the new positions of learners in the teaching phase and the learning phase are generated by the crossover operation, the legality detection and mutation operation, and then the offspring learners are determined based on greedy selection. Finally, to verify the performance of the proposed algorithm, benchmark TSP problems are examined and the results indicate that DTLBO is effective compared with other algorithms used for TSP problems.
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Vicente D. Estruch
2017-08-01
Full Text Available The concept of random variable is a mathematical construct that presents some theoretical complexity. However, learning this concept can be facilitated if it is presented as the end of a sequential process of modeling of a real event. More specifically, to learn the concept of discrete random variable, the Monte Carlo simulation can provide an extremely useful tool because in the process of modeling / simulation one can approach the theoretical concept of random variable, while the random variable is observed \\in action". This paper presents a Research and Study Course (RSC based on series of activities related to random variables such as training and introduction of simulation elements, then the construction of the model is presented, which is the substantial part of the activity, generating a random variable and its probability function. Starting from a simple situation related to reproduction and survival of the litter of a rodent, with random components, step by step, the model that represents the real raised situation is built obtaining an \\original" random variable. In the intermediate stages of the construction of the model have a fundamental role the uniform discrete and binomial distributions. The trajectory of these stages allows reinforcing the concept of random variable while exploring the possibilities offered by Monte Carlo methods to simulate real cases and the simplicity of implementing these methods by means of the Matlab© programming language.
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Fushing Hsieh
2016-11-01
Full Text Available Discrete combinatorial optimization problems in real world are typically defined via an ensemble of potentially high dimensional measurements pertaining to all subjects of a system under study. We point out that such a data ensemble in fact embeds with system's information content that is not directly used in defining the combinatorial optimization problems. Can machine learning algorithms extract such information content and make combinatorial optimizing tasks more efficient? Would such algorithmic computations bring new perspectives into this classic topic of Applied Mathematics and Theoretical Computer Science? We show that answers to both questions are positive. One key reason is due to permutation invariance. That is, the data ensemble of subjects' measurement vectors is permutation invariant when it is represented through a subject-vs-measurement matrix. An unsupervised machine learning algorithm, called Data Mechanics (DM, is applied to find optimal permutations on row and column axes such that the permuted matrix reveals coupled deterministic and stochastic structures as the system's information content. The deterministic structures are shown to facilitate geometry-based divide-and-conquer scheme that helps optimizing task, while stochastic structures are used to generate an ensemble of mimicries retaining the deterministic structures, and then reveal the robustness pertaining to the original version of optimal solution. Two simulated systems, Assignment problem and Traveling Salesman problem, are considered. Beyond demonstrating computational advantages and intrinsic robustness in the two systems, we propose brand new robust optimal solutions. We believe such robust versions of optimal solutions are potentially more realistic and practical in real world settings.
Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces
Neukart, Florian; Von Dollen, David; Seidel, Christian; Compostella, Gabriele
2017-12-01
Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems, have been subject to multiple analyses in research, with the aim of characterizing the technology's usefulness for optimization and sampling tasks. Here, we present a way to partially embed both Monte Carlo policy iteration for finding an optimal policy on random observations, as well as how to embed n sub-optimal state-value functions for approximating an improved state-value function given a policy for finite horizon games with discrete state spaces on a D-Wave 2000Q quantum processing unit (QPU). We explain how both problems can be expressed as a quadratic unconstrained binary optimization (QUBO) problem, and show that quantum-enhanced Monte Carlo policy evaluation allows for finding equivalent or better state-value functions for a given policy with the same number episodes compared to a purely classical Monte Carlo algorithm. Additionally, we describe a quantum-classical policy learning algorithm. Our first and foremost aim is to explain how to represent and solve parts of these problems with the help of the QPU, and not to prove supremacy over every existing classical policy evaluation algorithm.
Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.
Franke, John E; Yakubu, Abdul-Aziz
2008-12-01
The dynamics of simple discrete-time epidemic models without disease-induced mortality are typically characterized by global transcritical bifurcation. We prove that in corresponding models with disease-induced mortality a tiny number of infectious individuals can drive an otherwise persistent population to extinction. Our model with disease-induced mortality supports multiple attractors. In addition, we use a Ricker recruitment function in an SIS model and obtained a three component discrete Hopf (Neimark-Sacker) cycle attractor coexisting with a fixed point attractor. The basin boundaries of the coexisting attractors are fractal in nature, and the example exhibits sensitive dependence of the long-term disease dynamics on initial conditions. Furthermore, we show that in contrast to corresponding models without disease-induced mortality, the disease-free state dynamics do not drive the disease dynamics.
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Benedito M.A.C.
2001-01-01
Full Text Available Some upper brainstem cholinergic neurons (pedunculopontine and laterodorsal tegmental nuclei are involved in the generation of rapid eye movement (REM sleep and project rostrally to the thalamus and caudally to the medulla oblongata. A previous report showed that 96 h of REM sleep deprivation in rats induced an increase in the activity of brainstem acetylcholinesterase (Achase, the enzyme which inactivates acetylcholine (Ach in the synaptic cleft. There was no change in the enzyme's activity in the whole brain and cerebrum. The components of the cholinergic synaptic endings (for example, Achase are not uniformly distributed throughout the discrete regions of the brain. In order to detect possible regional changes we measured Achase activity in several discrete rat brain regions (medulla oblongata, pons, thalamus, striatum, hippocampus and cerebral cortex after 96 h of REM sleep deprivation. Naive adult male Wistar rats were deprived of REM sleep using the flower-pot technique, while control rats were left in their home cages. Total, membrane-bound and soluble Achase activities (nmol of thiocholine formed min-1 mg protein-1 were assayed photometrically. The results (mean ± SD obtained showed a statistically significant (Student t-test increase in total Achase activity in the pons (control: 147.8 ± 12.8, REM sleep-deprived: 169.3 ± 17.4, N = 6 for both groups, P<0.025 and thalamus (control: 167.4 ± 29.0, REM sleep-deprived: 191.9 ± 15.4, N = 6 for both groups, P<0.05. Increases in membrane-bound Achase activity in the pons (control: 171.0 ± 14.7, REM sleep-deprived: 189.5 ± 19.5, N = 6 for both groups, P<0.05 and soluble enzyme activity in the medulla oblongata (control: 147.6 ± 16.3, REM sleep-deprived: 163.8 ± 8.3, N = 6 for both groups, P<0.05 were also observed. There were no statistically significant differences in the enzyme's activity in the other brain regions assayed. The present findings show that the increase in Achase activity
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.
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.
International Nuclear Information System (INIS)
More, Ameya; Dutta, B.K.; Durgaprasad, P.V.; Arya, A.K.
2012-01-01
Fe-Cr based Ferritic/Martensitic (F/M) steels are the candidate structural materials for future fusion reactors. In this work, a multi-scale approach comprising atomistic Molecular Dynamics (MD) simulations and Discrete Dislocation Dynamics (DDD) simulations are used to model the effect of irradiation dose on the flow stress of F/M steels. At the atomic scale, molecular dynamics simulations are used to study the dislocation interaction with irradiation induced defects, i.e. voids and He bubbles. Whereas, the DDD simulations are used to estimate the change in flow stress of the material as a result of irradiation hardening. (author)
International Nuclear Information System (INIS)
Duwel, A.E.; Watanabe, S.; Trias, E.; Orlando, T.P.; van der Zant, H.S.; Strogatz, S.H.
1997-01-01
New resonance steps are found in the experimental current-voltage characteristics of long, discrete, one-dimensional Josephson junction arrays with open boundaries and in an external magnetic field. The junctions are underdamped, connected in parallel, and dc biased. Numerical simulations based on the discrete sine-Gordon model are carried out, and show that the solutions on the steps are periodic trains of fluxons, phase locked by a finite amplitude radiation. Power spectra of the voltages consist of a small number of harmonic peaks, which may be exploited for possible oscillator applications. The steps form a family that can be numbered by the harmonic content of the radiation, the first member corresponding to the Eck step. Discreteness of the arrays is shown to be essential for appearance of the higher order steps. We use a multimode extension of the harmonic balance analysis, and estimate the resonance frequencies, the ac voltage amplitudes, and the theoretical limit on the output power on the first two steps. copyright 1997 American Institute of Physics
Discrete Mathematics Re "Tooled."
Grassl, Richard M.; Mingus, Tabitha T. Y.
1999-01-01
Indicates the importance of teaching discrete mathematics. Describes how the use of technology can enhance the teaching and learning of discrete mathematics. Explorations using Excel, Derive, and the TI-92 proved how preservice and inservice teachers experienced a new dimension in problem solving and discovery. (ASK)
What can we learn from HF signal scattered from a discrete arc?
Directory of Open Access Journals (Sweden)
E. Séran
2009-05-01
Full Text Available We present observations of a discrete southward propagating arc which appeared in the mid-night sector at latitudes equatorward of main substorm activity. The arc observations were made simultaneously by the ALFA (Auroral Light Fine Analysis optical camera, the SuperDARN-CUTLASS HF radar and the Demeter satellite during a coordinated multi-instrumental campaign conducted at the KEOPS/ESRANGE site in December 2006. The SuperDARN HF signal which is often lost in the regions of strong electron precipitation yields in our case clear backscatter from an isolated arc of weak intensity. Consequently we are able to study arc dynamics, the formation of meso-scale irregularities of the electron density along the arc, compare the arc motion with the convection of surrounding plasma and discuss the contribution of ionospheric ions in the arc erosion and its propagation.
Fuller, Alison; Kakavelakis, Kostas; Felstead, Alan; Jewson, Nick; Unwin, Lorna
2009-01-01
This paper explores the nature of the relationship between Head Office and stores in a large British supermarket chain. It focuses on the role played by a range of technological tools available for managing the stock and connecting different parts of the productive system and the implications this has for employee learning in stores. The evidence…
Carter, Jeffrey R.; Simon, Wayne E.
1990-08-01
Neural networks are trained using Recursive Error Minimization (REM) equations to perform statistical classification. Using REM equations with continuous input variables reduces the required number of training experiences by factors of one to two orders of magnitude over standard back propagation. Replacing the continuous input variables with discrete binary representations reduces the number of connections by a factor proportional to the number of variables reducing the required number of experiences by another order of magnitude. Undesirable effects of using recurrent experience to train neural networks for statistical classification problems are demonstrated and nonrecurrent experience used to avoid these undesirable effects. 1. THE 1-41 PROBLEM The statistical classification problem which we address is is that of assigning points in ddimensional space to one of two classes. The first class has a covariance matrix of I (the identity matrix) the covariance matrix of the second class is 41. For this reason the problem is known as the 1-41 problem. Both classes have equal probability of occurrence and samples from both classes may appear anywhere throughout the ddimensional space. Most samples near the origin of the coordinate system will be from the first class while most samples away from the origin will be from the second class. Since the two classes completely overlap it is impossible to have a classifier with zero error. The minimum possible error is known as the Bayes error and
A new discrete dynamic model of ABA-induced stomatal closure predicts key feedback loops.
Directory of Open Access Journals (Sweden)
Réka Albert
2017-09-01
Full Text Available Stomata, microscopic pores in leaf surfaces through which water loss and carbon dioxide uptake occur, are closed in response to drought by the phytohormone abscisic acid (ABA. This process is vital for drought tolerance and has been the topic of extensive experimental investigation in the last decades. Although a core signaling chain has been elucidated consisting of ABA binding to receptors, which alleviates negative regulation by protein phosphatases 2C (PP2Cs of the protein kinase OPEN STOMATA 1 (OST1 and ultimately results in activation of anion channels, osmotic water loss, and stomatal closure, over 70 additional components have been identified, yet their relationships with each other and the core components are poorly elucidated. We integrated and processed hundreds of disparate observations regarding ABA signal transduction responses underlying stomatal closure into a network of 84 nodes and 156 edges and, as a result, established those relationships, including identification of a 36-node, strongly connected (feedback-rich component as well as its in- and out-components. The network's domination by a feedback-rich component may reflect a general feature of rapid signaling events. We developed a discrete dynamic model of this network and elucidated the effects of ABA plus knockout or constitutive activity of 79 nodes on both the outcome of the system (closure and the status of all internal nodes. The model, with more than 1024 system states, is far from fully determined by the available data, yet model results agree with existing experiments in 82 cases and disagree in only 17 cases, a validation rate of 75%. Our results reveal nodes that could be engineered to impact stomatal closure in a controlled fashion and also provide over 140 novel predictions for which experimental data are currently lacking. Noting the paucity of wet-bench data regarding combinatorial effects of ABA and internal node activation, we experimentally confirmed
A new discrete dynamic model of ABA-induced stomatal closure predicts key feedback loops.
Albert, Réka; Acharya, Biswa R; Jeon, Byeong Wook; Zañudo, Jorge G T; Zhu, Mengmeng; Osman, Karim; Assmann, Sarah M
2017-09-01
Stomata, microscopic pores in leaf surfaces through which water loss and carbon dioxide uptake occur, are closed in response to drought by the phytohormone abscisic acid (ABA). This process is vital for drought tolerance and has been the topic of extensive experimental investigation in the last decades. Although a core signaling chain has been elucidated consisting of ABA binding to receptors, which alleviates negative regulation by protein phosphatases 2C (PP2Cs) of the protein kinase OPEN STOMATA 1 (OST1) and ultimately results in activation of anion channels, osmotic water loss, and stomatal closure, over 70 additional components have been identified, yet their relationships with each other and the core components are poorly elucidated. We integrated and processed hundreds of disparate observations regarding ABA signal transduction responses underlying stomatal closure into a network of 84 nodes and 156 edges and, as a result, established those relationships, including identification of a 36-node, strongly connected (feedback-rich) component as well as its in- and out-components. The network's domination by a feedback-rich component may reflect a general feature of rapid signaling events. We developed a discrete dynamic model of this network and elucidated the effects of ABA plus knockout or constitutive activity of 79 nodes on both the outcome of the system (closure) and the status of all internal nodes. The model, with more than 1024 system states, is far from fully determined by the available data, yet model results agree with existing experiments in 82 cases and disagree in only 17 cases, a validation rate of 75%. Our results reveal nodes that could be engineered to impact stomatal closure in a controlled fashion and also provide over 140 novel predictions for which experimental data are currently lacking. Noting the paucity of wet-bench data regarding combinatorial effects of ABA and internal node activation, we experimentally confirmed several predictions
Lemrich, Laure; Carmeliet, Jan; Johnson, Paul A.; Guyer, Robert; Jia, Xiaoping
2017-12-01
A granular system composed of frictional glass beads is simulated using the discrete element method. The intergrain forces are based on the Hertz contact law in the normal direction with frictional tangential force. The damping due to collision is also accounted for. Systems are loaded at various stresses and their quasistatic elastic moduli are characterized. Each system is subjected to an extensive dynamic testing protocol by measuring the resonant response to a broad range of ac drive amplitudes and frequencies via a set of diagnostic strains. The system, linear at small ac drive amplitudes, has resonance frequencies that shift downward (i.e., modulus softening) with increased ac drive amplitude. Detailed testing shows that the slipping contact ratio does not contribute significantly to this dynamic modulus softening, but the coordination number is strongly correlated to this reduction. This suggests that the softening arises from the extended structural change via break and remake of contacts during the rearrangement of bead positions driven by the ac amplitude.
Herman, Agnieszka
2017-11-01
In this paper, a coupled sea ice-wave model is developed and used to analyze wave-induced stress and breaking in sea ice for a range of wave and ice conditions. The sea ice module is a discrete-element bonded-particle model, in which ice is represented as cuboid grains floating on the water surface that can be connected to their neighbors by elastic joints. The joints may break if instantaneous stresses acting on them exceed their strength. The wave module is based on an open-source version of the Non-Hydrostatic WAVE model (NHWAVE). The two modules are coupled with proper boundary conditions for pressure and velocity, exchanged at every wave model time step. In the present version, the model operates in two dimensions (one vertical and one horizontal) and is suitable for simulating compact ice in which heave and pitch motion dominates over surge. In a series of simulations with varying sea ice properties and incoming wavelength it is shown that wave-induced stress reaches maximum values at a certain distance from the ice edge. The value of maximum stress depends on both ice properties and characteristics of incoming waves, but, crucially for ice breaking, the location at which the maximum occurs does not change with the incoming wavelength. Consequently, both regular and random (Jonswap spectrum) waves break the ice into floes with almost identical sizes. The width of the zone of broken ice depends on ice strength and wave attenuation rates in the ice.
Yoon, Jeoung Seok; Zang, Arno; Zimmermann, Günter; Stephansson, Ove
2016-04-01
, Ellsworth WL, Stump BW, Hayward C, Frohlich C, Oldham HR, Olson JE, Magnani MB, Brokaw C, Luetgert JH, 2015, Causal factors for seismicity near Azle, Texas, nature communications 6:6728, DOI: 10.1038/ncomms7728 [3] Yoon JS, Zimmermann G, Zang A, Stephansson O, 2015, Discrete element modeling of fluid injection-induced seismicity and activation of nearby fault, Can Geotech J 52: 1457-1465, DOI: 10.1139/cgj-2014-0435.
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.
DEFF Research Database (Denmark)
Sørensen, John Aasted
2011-01-01
The objectives of Discrete Mathematics (IDISM2) are: The introduction of the mathematics needed for analysis, design and verification of discrete systems, including the application within programming languages for computer systems. Having passed the IDISM2 course, the student will be able...... to accomplish the following: -Understand and apply formal representations in discrete mathematics. -Understand and apply formal representations in problems within discrete mathematics. -Understand methods for solving problems in discrete mathematics. -Apply methods for solving problems in discrete mathematics......; construct a finite state machine for a given application. Apply these concepts to new problems. The teaching in Discrete Mathematics is a combination of sessions with lectures and students solving problems, either manually or by using Matlab. Furthermore a selection of projects must be solved and handed...
Goodrich, Christopher
2015-01-01
This text provides the first comprehensive treatment of the discrete fractional calculus. Experienced researchers will find the text useful as a reference for discrete fractional calculus and topics of current interest. Students who are interested in learning about discrete fractional calculus will find this text to provide a useful starting point. Several exercises are offered at the end of each chapter and select answers have been provided at the end of the book. The presentation of the content is designed to give ample flexibility for potential use in a myriad of courses and for independent study. The novel approach taken by the authors includes a simultaneous treatment of the fractional- and integer-order difference calculus (on a variety of time scales, including both the usual forward and backwards difference operators). The reader will acquire a solid foundation in the classical topics of the discrete calculus while being introduced to exciting recent developments, bringing them to the frontiers of the...
Sleep disturbance induces neuroinflammation and impairment of learning and memory.
Zhu, Biao; Dong, Yuanlin; Xu, Zhipeng; Gompf, Heinrich S; Ward, Sarah A P; Xue, Zhanggang; Miao, Changhong; Zhang, Yiying; Chamberlin, Nancy L; Xie, Zhongcong
2012-12-01
Hospitalized patients can develop cognitive function decline, the mechanisms of which remain largely to be determined. Sleep disturbance often occurs in hospitalized patients, and neuroinflammation can induce learning and memory impairment. We therefore set out to determine whether sleep disturbance can induce neuroinflammation and impairment of learning and memory in rodents. Five to 6-month-old wild-type C57BL/6J male mice were used in the studies. The mice were placed in rocking cages for 24 h, and two rolling balls were present in each cage. The mice were tested for learning and memory function using the Fear Conditioning Test one and 7 days post-sleep disturbance. Neuroinflammation in the mouse brain tissues was also determined. Of the Fear Conditioning studies at one day and 7 days after sleep disturbance, twenty-four hour sleep disturbance decreased freezing time in the context test, which assesses hippocampus-dependent learning and memory; but not the tone test, which assesses hippocampus-independent learning and memory. Sleep disturbance increased pro-inflammatory cytokine IL-6 levels and induced microglia activation in the mouse hippocampus, but not the cortex. These results suggest that sleep disturbance induces neuroinflammation in the mouse hippocampus, and impairs hippocampus-dependent learning and memory in mice. Pending further studies, these findings suggest that sleep disturbance-induced neuroinflammation and impairment of learning and memory may contribute to the development of cognitive function decline in hospitalized patients. Copyright © 2012 Elsevier Inc. All rights reserved.
Reduction of the Misinformation Effect by Arousal Induced after Learning
English, Shaun M.; Nielson, Kristy A.
2010-01-01
Misinformation introduced after events have already occurred causes errors in later retrieval. Based on literature showing that arousal induced after learning enhances delayed retrieval, we investigated whether post-learning arousal can reduce the misinformation effect. 251 participants viewed four short film clips, each followed by a retention…
CREB Selectively Controls Learning-Induced Structural Remodeling of Neurons
Middei, Silvia; Spalloni, Alida; Longone, Patrizia; Pittenger, Christopher; O'Mara, Shane M.; Marie, Helene; Ammassari-Teule, Martine
2012-01-01
The modulation of synaptic strength associated with learning is post-synaptically regulated by changes in density and shape of dendritic spines. The transcription factor CREB (cAMP response element binding protein) is required for memory formation and in vitro dendritic spine rearrangements, but its role in learning-induced remodeling of neurons…
DEFF Research Database (Denmark)
Sørensen, John Aasted
2011-01-01
; construct a finite state machine for a given application. Apply these concepts to new problems. The teaching in Discrete Mathematics is a combination of sessions with lectures and students solving problems, either manually or by using Matlab. Furthermore a selection of projects must be solved and handed...... to accomplish the following: -Understand and apply formal representations in discrete mathematics. -Understand and apply formal representations in problems within discrete mathematics. -Understand methods for solving problems in discrete mathematics. -Apply methods for solving problems in discrete mathematics...... to new problems. Relations and functions: Define a product set; define and apply equivalence relations; construct and apply functions. Apply these concepts to new problems. Natural numbers and induction: Define the natural numbers; apply the principle of induction to verify a selection of properties...
DEFF Research Database (Denmark)
Busch, Peter Andre; Zinner Henriksen, Helle
2018-01-01
discretion is suggested to reduce this footprint by influencing or replacing their discretionary practices using ICT. What is less researched is whether digital discretion can cause changes in public policy outcomes, and under what conditions such changes can occur. Using the concept of public service values......This study reviews 44 peer-reviewed articles on digital discretion published in the period from 1998 to January 2017. Street-level bureaucrats have traditionally had a wide ability to exercise discretion stirring debate since they can add their personal footprint on public policies. Digital......, we suggest that digital discretion can strengthen ethical and democratic values but weaken professional and relational values. Furthermore, we conclude that contextual factors such as considerations made by policy makers on the macro-level and the degree of professionalization of street...
Kaufman, I; Luchinsky, D G; Tindjong, R; McClintock, P V E; Eisenberg, R S
2013-11-01
We use Brownian dynamics (BD) simulations to study the ionic conduction and valence selectivity of a generic electrostatic model of a biological ion channel as functions of the fixed charge Q(f) at its selectivity filter. We are thus able to reconcile the discrete calcium conduction bands recently revealed in our BD simulations, M0 (Q(f)=1e), M1 (3e), M2 (5e), with a set of sodium conduction bands L0 (0.5e), L1 (1.5e), thereby obtaining a completed pattern of conduction and selectivity bands vs Q(f) for the sodium-calcium channels family. An increase of Q(f) leads to an increase of calcium selectivity: L0 (sodium-selective, nonblocking channel) → M0 (nonselective channel) → L1 (sodium-selective channel with divalent block) → M1 (calcium-selective channel exhibiting the anomalous mole fraction effect). We create a consistent identification scheme where the L0 band is putatively identified with the eukaryotic sodium channel The scheme created is able to account for the experimentally observed mutation-induced transformations between nonselective channels, sodium-selective channels, and calcium-selective channels, which we interpret as transitions between different rows of the identification table. By considering the potential energy changes during permeation, we show explicitly that the multi-ion conduction bands of calcium and sodium channels arise as the result of resonant barrierless conduction. The pattern of periodic conduction bands is explained on the basis of sequential neutralization taking account of self-energy, as Q(f)(z,i)=ze(1/2+i), where i is the order of the band and z is the valence of the ion. Our results confirm the crucial influence of electrostatic interactions on conduction and on the Ca(2+)/Na(+) valence selectivity of calcium and sodium ion channels. The model and results could be also applicable to biomimetic nanopores with charged walls.
DEFF Research Database (Denmark)
Sørensen, John Aasted
2010-01-01
The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Spring 2010 Ectent: 5 ects Class size: 18......The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Spring 2010 Ectent: 5 ects Class size: 18...
DEFF Research Database (Denmark)
Sørensen, John Aasted
2010-01-01
The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Autumn 2010 Ectent: 5 ects Class size: 15......The introduction of the mathematics needed for analysis, design and verification of discrete systems, including applications within programming languages for computer systems. Course sessions and project work. Semester: Autumn 2010 Ectent: 5 ects Class size: 15...
Filip, Małgorzata; Frankowska, Małgorzata
2007-10-01
In the present study we investigated the effects of the GABA(B) receptor antagonist (2S)-(+)-5,5-dimethyl-2-morpholineacetic acid (SCH 50911), the agonists baclofen and 3-aminopropyl(methyl)phosphinic acid (SKF 97541), and the allosteric positive modulator 3,5-bis(1,1-dimethylethyl)-4-hydroxy-beta,beta-dimethylbenzenepropanol (CGP 7930) on cocaine seeking behavior. The effects of the above drugs on the reinstatement of responding induced by natural reinforcer (food) were also studied. Male Wistar rats were trained to self-administer either cocaine (0.5 mg/kg/infusion) or food (sweet milk) and responding on the reinforcer-paired lever was extinguished. Reinstatement of responding was induced by a noncontingent presentation of the self-administered reinforcer (10 mg/kg cocaine, i.p.), a discrete contextual cue, or a contingent presentation of food. SCH 50911 (3-10 mg/kg) dose-dependently attenuated responding on the previously cocaine-paired lever during both reinstatement conditions, with slightly greater efficacy at reducing conditioned cue reinstatement. At the same time, it failed to alter reinstatement of food-seeking behavior. Baclofen (1.25-5 mg/kg) and SKF 97541 (0.03-0.3 mg/kg) attenuated cocaine- or food-seeking behavior; the effect of the drug appeared more effective for cocaine-seeking than food-seeking. CGP 7930 (10-30 mg/kg) reduced cocaine seeking without affecting food-induced reinstatement on reward seeking. Our results indicate that tonic activation of GABA(B) receptors is required for cocaine seeking behavior in rats. Moreover, the GABA(B) receptor antagonist SCH 50911 was effective in reducing relapse to cocaine at doses that failed to alter reinstatement of food-seeking behavior (present study), basal locomotor activity, cocaine and food self-administration (Filip et al., submitted for publication), suggesting its selective effects on motivated drug-seeking behavior. The potent inhibitory responses on cocaine seeking behavior were also seen
Directory of Open Access Journals (Sweden)
Pooya Hamdi
2015-12-01
Full Text Available Heterogeneity is an inherent component of rock and may be present in different forms including mineral heterogeneity, geometrical heterogeneity, weak grain boundaries and micro-defects. Microcracks are usually observed in crystalline rocks in two forms: natural and stress-induced; the amount of stress-induced microcracking increases with depth and in-situ stress. Laboratory results indicate that the physical properties of rocks such as strength, deformability, P-wave velocity and permeability are influenced by increase in microcrack intensity. In this study, the finite-discrete element method (FDEM is used to model microcrack heterogeneity by introducing into a model sample sets of microcracks using the proposed micro discrete fracture network (μDFN approach. The characteristics of the microcracks required to create μDFN models are obtained through image analyses of thin sections of Lac du Bonnet granite adopted from published literature. A suite of two-dimensional laboratory tests including uniaxial, triaxial compression and Brazilian tests is simulated and the results are compared with laboratory data. The FDEM-μDFN models indicate that micro-heterogeneity has a profound influence on both the mechanical behavior and resultant fracture pattern. An increase in the microcrack intensity leads to a reduction in the strength of the sample and changes the character of the rock strength envelope. Spalling and axial splitting dominate the failure mode at low confinement while shear failure is the dominant failure mode at high confinement. Numerical results from simulated compression tests show that microcracking reduces the cohesive component of strength alone, and the frictional strength component remains unaffected. Results from simulated Brazilian tests show that the tensile strength is influenced by the presence of microcracks, with a reduction in tensile strength as microcrack intensity increases. The importance of microcrack heterogeneity in
Czech Academy of Sciences Publication Activity Database
Kempa, Martin; Ondrejkovič, Petr; Bourges, P.; Márton, Pavel; Hlinka, Jiří
2014-01-01
Roč. 89, č. 5 (2014), "054308-1"-"054308-5" ISSN 1098-0121 R&D Projects: GA ČR GPP204/11/P404 Institutional support: RVO:68378271 Keywords : NaI * alkali halides * inelastic neutron scattering * discrete breathers Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 3.736, year: 2014
Exarchakis, Georgios; Lücke, Jörg
2017-11-01
Sparse coding algorithms with continuous latent variables have been the subject of a large number of studies. However, discrete latent spaces for sparse coding have been largely ignored. In this work, we study sparse coding with latents described by discrete instead of continuous prior distributions. We consider the general case in which the latents (while being sparse) can take on any value of a finite set of possible values and in which we learn the prior probability of any value from data. This approach can be applied to any data generated by discrete causes, and it can be applied as an approximation of continuous causes. As the prior probabilities are learned, the approach then allows for estimating the prior shape without assuming specific functional forms. To efficiently train the parameters of our probabilistic generative model, we apply a truncated expectation-maximization approach (expectation truncation) that we modify to work with a general discrete prior. We evaluate the performance of the algorithm by applying it to a variety of tasks: (1) we use artificial data to verify that the algorithm can recover the generating parameters from a random initialization, (2) use image patches of natural images and discuss the role of the prior for the extraction of image components, (3) use extracellular recordings of neurons to present a novel method of analysis for spiking neurons that includes an intuitive discretization strategy, and (4) apply the algorithm on the task of encoding audio waveforms of human speech. The diverse set of numerical experiments presented in this letter suggests that discrete sparse coding algorithms can scale efficiently to work with realistic data sets and provide novel statistical quantities to describe the structure of the data.
Caltagirone, Jean-Paul
2014-01-01
This book presents the fundamental principles of mechanics to re-establish the equations of Discrete Mechanics. It introduces physics and thermodynamics associated to the physical modeling. The development and the complementarity of sciences lead to review today the old concepts that were the basis for the development of continuum mechanics. The differential geometry is used to review the conservation laws of mechanics. For instance, this formalism requires a different location of vector and scalar quantities in space. The equations of Discrete Mechanics form a system of equations where the H
International Nuclear Information System (INIS)
Lee, T.D.
1985-01-01
This paper reviews the role of time throughout all phases of mechanics: classical mechanics, non-relativistic quantum mechanics, and relativistic quantum theory. As an example of the relativistic quantum field theory, the case of a massless scalar field interacting with an arbitrary external current is discussed. The comparison between the new discrete theory and the usual continuum formalism is presented. An example is given of a two-dimensional random lattice and its duel. The author notes that there is no evidence that the discrete mechanics is more appropriate than the usual continuum mechanics
Directory of Open Access Journals (Sweden)
Feifan Zhang
2017-06-01
Full Text Available The formation of self-organized patterns in predator-prey models has been a very hot topic recently. The dynamics of these models, bifurcations and pattern formations are so complex that studies are urgently needed. In this research, we transformed a continuous predator-prey model with Lesie-Gower functional response into a discrete model. Fixed points and stability analyses were studied. Around the stable fixed point, bifurcation analyses including: flip, Neimark-Sacker and Turing bifurcation were done and bifurcation conditions were obtained. Based on these bifurcation conditions, parameters values were selected to carry out numerical simulations on pattern formation. The simulation results showed that Neimark-Sacker bifurcation induced spots, spirals and transitional patterns from spots to spirals. Turing bifurcation induced labyrinth patterns and spirals coupled with mosaic patterns, while flip bifurcation induced many irregular complex patterns. Compared with former studies on continuous predator-prey model with Lesie-Gower functional response, our research on the discrete model demonstrated more complex dynamics and varieties of self-organized patterns.
Experimentally Induced Learned Helplessness: How Far Does it Generalize?
Tuffin, Keith; And Others
1985-01-01
Assessed whether experimentally induced learned helplessness on a cognitive training task generalized to a situationally dissimilar social interaction test task. No significant differences were observed between groups on the subsequent test task, showing that helplessness failed to generalize. (Author/ABB)
Comparing dictionary-induced vocabulary learning and inferencing ...
African Journals Online (AJOL)
This research examines dictionary-induced vocabulary learning and inferencing in the context of reading. One hundred and four intermediate English learners completed one of two word-focused tasks: reading comprehension and dictionary consultation, and reading comprehen-sion and inferencing. In addition to ...
Contextual Learning Induces Dendritic Spine Clustering in Retrosplenial Cortex
Directory of Open Access Journals (Sweden)
Adam C Frank
2014-03-01
Full Text Available Molecular and electrophysiological studies find convergent evidence suggesting that plasticity within a dendritic tree is not randomly dispersed, but rather clustered into functional groups. Further, results from in silico neuronal modeling show that clustered plasticity is able to increase storage capacity 45 times compared to dispersed plasticity. Recent in vivo work utilizing chronic 2-photon microscopy tested the clustering hypothesis and showed that repetitive motor learning is able to induce clustered addition of new dendritic spines on apical dendrites of L5 neurons in primary motor cortex; moreover, clustered spines were found to be more stable than non-clustered spines, suggesting a physiological role for spine clustering. To further test this hypothesis we used in vivo 2-photon imaging in Thy1-YFP-H mice to chronically examine dendritic spine dynamics in retrosplenial cortex (RSC during spatial learning. RSC is a key component of an extended spatial learning and memory circuit that includes hippocampus and entorhinal cortex. Importantly, RSC is known from both lesion and immediate early gene studies to be critically involved in spatial learning and more specifically in contextual fear conditioning. We utilized a modified contextual fear conditioning protocol wherein animals received a mild foot shock each day for five days; this protocol induces gradual increases in context freezing over several days before the animals reach a behavioral plateau. We coupled behavioral training with four separate in vivo imaging sessions, two before training begins, one early in training, and a final session after training is complete. This allowed us to image spine dynamics before training as well as early in learning and after animals had reached behavioral asymptote. We find that this contextual learning protocol induces a statistically significant increase in the formation of clusters of new dendritic spines in trained animals when compared to home
Extinction of Learned Fear Induces Hippocampal Place Cell Remapping
Wang, Melissa E.; Yuan, Robin K.; Keinath, Alexander T.; Ramos Álvarez, Manuel M.
2015-01-01
The extinction of learned fear is a hippocampus-dependent process thought to embody new learning rather than erasure of the original fear memory, although it is unknown how these competing contextual memories are represented in the hippocampus. We previously demonstrated that contextual fear conditioning results in hippocampal place cell remapping and long-term stabilization of novel representations. Here we report that extinction learning also induces place cell remapping in C57BL/6 mice. Specifically, we observed cells that preferentially remapped during different stages of learning. While some cells remapped in both fear conditioning and extinction, others responded predominantly during extinction, which may serve to modify previous representations as well as encode new safe associations. Additionally, we found cells that remapped primarily during fear conditioning, which could facilitate reacquisition of the original fear association. Moreover, we also observed cells that were stable throughout learning, which may serve to encode the static aspects of the environment. The short-term remapping observed during extinction was not found in animals that did not undergo fear conditioning, or when extinction was conducted outside of the conditioning context. Finally, conditioning and extinction produced an increase in spike phase locking to the theta and gamma frequencies. However, the degree of remapping seen during conditioning and extinction only correlated with gamma synchronization. Our results suggest that the extinction learning is a complex process that involves both modification of pre-existing memories and formation of new ones, and these traces coexist within the same hippocampal representation. PMID:26085635
Parker, R Gary
1988-01-01
This book treats the fundamental issues and algorithmic strategies emerging as the core of the discipline of discrete optimization in a comprehensive and rigorous fashion. Following an introductory chapter on computational complexity, the basic algorithmic results for the two major models of polynomial algorithms are introduced--models using matroids and linear programming. Further chapters treat the major non-polynomial algorithms: branch-and-bound and cutting planes. The text concludes with a chapter on heuristic algorithms.Several appendixes are included which review the fundamental ideas o
Discrete mathematics with applications
Koshy, Thomas
2003-01-01
This approachable text studies discrete objects and the relationsips that bind them. It helps students understand and apply the power of discrete math to digital computer systems and other modern applications. It provides excellent preparation for courses in linear algebra, number theory, and modern/abstract algebra and for computer science courses in data structures, algorithms, programming languages, compilers, databases, and computation.* Covers all recommended topics in a self-contained, comprehensive, and understandable format for students and new professionals * Emphasizes problem-solving techniques, pattern recognition, conjecturing, induction, applications of varying nature, proof techniques, algorithm development and correctness, and numeric computations* Weaves numerous applications into the text* Helps students learn by doing with a wealth of examples and exercises: - 560 examples worked out in detail - More than 3,700 exercises - More than 150 computer assignments - More than 600 writing projects*...
Discrete gradients in discrete classical mechanics
International Nuclear Information System (INIS)
Renna, L.
1987-01-01
A simple model of discrete classical mechanics is given where, starting from the continuous Hamilton equations, discrete equations of motion are established together with a proper discrete gradient definition. The conservation laws of the total discrete momentum, angular momentum, and energy are demonstrated
Firth, Jean M
1992-01-01
The analysis of signals and systems using transform methods is a very important aspect of the examination of processes and problems in an increasingly wide range of applications. Whereas the initial impetus in the development of methods appropriate for handling discrete sets of data occurred mainly in an electrical engineering context (for example in the design of digital filters), the same techniques are in use in such disciplines as cardiology, optics, speech analysis and management, as well as in other branches of science and engineering. This text is aimed at a readership whose mathematical background includes some acquaintance with complex numbers, linear differen tial equations, matrix algebra, and series. Specifically, a familiarity with Fourier series (in trigonometric and exponential forms) is assumed, and an exposure to the concept of a continuous integral transform is desirable. Such a background can be expected, for example, on completion of the first year of a science or engineering degree cour...
International Nuclear Information System (INIS)
Gerber, G.; Moeller, R.
1982-01-01
Laser induced fluorescence spectra of the gaseous Sr 2 excimer molecule have been measured. The spectra contain discrete molecular fluorescence series, regularly modulated continuous fluorescence and an unstructured continuum. Analysis of the molecular line spectra yields for the first time Dunham coefficients for the X 1 Σsub(g) + ground state and the A 1 Σsub(u) + excited state. Using the intensity distribution of the modulated continuum which is associated with bound-free transitions the repulsive potential of the ground state up to 3000 cm -1 above the dissociation limit has been determined. The unstructured continuum can be analyzed as due to two types of continuous fluorescence. The dissociation energy of Sr 2 has been determined to Dsub(e)(X) = 965 +- 45 cm -1 . (Auth.)
International Nuclear Information System (INIS)
Gerber, G.; Moeller, R.
1982-01-01
Laser induced fluorescence spectra of the gaseous Sr 2 excimer molecule have been measured. The spectra contain discrete molecular fluorescence series, regularly modulated continuous fluorescence and an unstructured continuum. Analysis of the molecular line spectra yields for the first time Dunham coefficients for the X 1 μ + sub(g) ground state and the A 1 μ + sub(u) excited state. Using the intensity distribution of the modulated continuum which is associated with bound-free transitions the repulsive potential of the ground state up to 3000 cm - 1 above the dissociation limit has been determined. The unstructured continuum can be analyzed as due to two types of continuous fluorescence. The dissociation energy of Sr 2 has been determined to Dsub(e) (X) = 965 +- 45 cm - 1 . (Author)
Shih, Peter; Kaul, Brian C; Jagannathan, Sarangapani; Drallmeier, James A
2009-10-01
A novel reinforcement-learning-based output adaptive neural network (NN) controller, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility function and control inputs. All NN weights adapt online toward minimization of a performance index, utilizing the gradient-descent-based rule, in contrast with iteration-based adaptive-critic schemes. Lyapunov functions are used to show the stability of the closed-loop tracking error, weights, and observer estimates. Separation and certainty equivalence principles, persistency of excitation condition, and linearity in the unknown parameter assumption are not needed. Experimental results on a spark ignition (SI) engine operating lean at an equivalence ratio of 0.75 show a significant (25%) reduction in cyclic dispersion in heat release with control, while the average fuel input changes by less than 1% compared with the uncontrolled case. Consequently, oxides of nitrogen (NO(x)) drop by 30%, and unburned hydrocarbons drop by 16% with control. Overall, NO(x)'s are reduced by over 80% compared with stoichiometric levels.
Directory of Open Access Journals (Sweden)
Shih-Hsun Chang
2015-11-01
Full Text Available The governing factors that influence landslide occurrences are complicated by the different soil conditions at various sites. To resolve the problem, this study focused on spatial information technology to collect data and information on geology. GIS, remote sensing and digital elevation model (DEM were used in combination to extract the attribute values of the surface material in the vast study area of Shei-Pa National Park, Taiwan. The factors influencing landslides were collected and quantification values computed. The major soil component of loam and gravel in the Shei-Pa area resulted in different landslide problems. The major factors were successfully extracted from the influencing factors. Finally, the discrete rough set (DRS classifier was used as a tool to find the threshold of each attribute contributing to landslide occurrence, based upon the knowledge database. This rule-based knowledge database provides an effective and urgent system to manage landslides. NDVI (Normalized Difference Vegetation Index, VI (Vegetation Index, elevation, and distance from the road are the four major influencing factors for landslide occurrence. The landslide hazard potential diagrams (landslide susceptibility maps were drawn and a rational accuracy rate of landslide was calculated. This study thus offers a systematic solution to the investigation of landslide disasters.
Is Discrete Mathematics the New Math of the Eighties?
Hart, Eric W.
1985-01-01
Considered are what discrete mathematics includes, some parallels and differences between new math and discrete mathematics (listed in a table), and lessons to be learned. A list of references is included. (MNS)
Discrete Curvatures and Discrete Minimal Surfaces
Sun, Xiang
2012-01-01
This thesis presents an overview of some approaches to compute Gaussian and mean curvature on discrete surfaces and discusses discrete minimal surfaces. The variety of applications of differential geometry in visualization and shape design leads
Versteeg, D.H.G.; Kloet, E.R. de; Wied, D. de
1979-01-01
Summary Following the intracerebroventricular administration of α-endorphin, β-endorphin and (des-tyrosine1)-γ-endorphin in a dose of 100 ng, the α-MPT-induced catecholamine disappearance was found to be altered in discrete regions of the rat brain. In the regions in which α-endorphin exerted an
International Nuclear Information System (INIS)
Kaneoya, Katsuhiko; Ueda, Takuya; Suito, Hiroshi
2008-01-01
The aim of this study was to establish functional computed tomography (CT) imaging as a method for assessing tumor-induced angiogenesis. Functional CT imaging was mathematically analyzed for 14 renal cell carcinomas by means of two-compartment modeling using a computer-discretization approach. The model incorporated diffusible kinetics of contrast medium including leakage from the capillary to the extravascular compartment and back-flux to the capillary compartment. The correlations between functional CT parameters [relative blood volume (rbv), permeability 1 (Pm1), and permeability 2 (Pm2)] and histopathological markers of angiogenesis [microvessel density (MVD) and vascular endothelial growth factor (VEGF)] were statistically analyzed. The modeling was successfully performed, showing similarity between the mathematically simulated curve and the measured time-density curve. There were significant linear correlations between MVD grade and Pm1 (r=0.841, P=0.001) and between VEGF grade and Pm2 (r=0.804, P=0.005) by Pearson's correlation coefficient. This method may be a useful tool for the assessment of tumor-induced angiogenesis. (author)
Discrete Curvatures and Discrete Minimal Surfaces
Sun, Xiang
2012-06-01
This thesis presents an overview of some approaches to compute Gaussian and mean curvature on discrete surfaces and discusses discrete minimal surfaces. The variety of applications of differential geometry in visualization and shape design leads to great interest in studying discrete surfaces. With the rich smooth surface theory in hand, one would hope that this elegant theory can still be applied to the discrete counter part. Such a generalization, however, is not always successful. While discrete surfaces have the advantage of being finite dimensional, thus easier to treat, their geometric properties such as curvatures are not well defined in the classical sense. Furthermore, the powerful calculus tool can hardly be applied. The methods in this thesis, including angular defect formula, cotangent formula, parallel meshes, relative geometry etc. are approaches based on offset meshes or generalized offset meshes. As an important application, we discuss discrete minimal surfaces and discrete Koenigs meshes.
Fermion systems in discrete space-time
International Nuclear Information System (INIS)
Finster, Felix
2007-01-01
Fermion systems in discrete space-time are introduced as a model for physics on the Planck scale. We set up a variational principle which describes a non-local interaction of all fermions. This variational principle is symmetric under permutations of the discrete space-time points. We explain how for minimizers of the variational principle, the fermions spontaneously break this permutation symmetry and induce on space-time a discrete causal structure
Fermion systems in discrete space-time
Energy Technology Data Exchange (ETDEWEB)
Finster, Felix [NWF I - Mathematik, Universitaet Regensburg, 93040 Regensburg (Germany)
2007-05-15
Fermion systems in discrete space-time are introduced as a model for physics on the Planck scale. We set up a variational principle which describes a non-local interaction of all fermions. This variational principle is symmetric under permutations of the discrete space-time points. We explain how for minimizers of the variational principle, the fermions spontaneously break this permutation symmetry and induce on space-time a discrete causal structure.
Fermion Systems in Discrete Space-Time
Finster, Felix
2006-01-01
Fermion systems in discrete space-time are introduced as a model for physics on the Planck scale. We set up a variational principle which describes a non-local interaction of all fermions. This variational principle is symmetric under permutations of the discrete space-time points. We explain how for minimizers of the variational principle, the fermions spontaneously break this permutation symmetry and induce on space-time a discrete causal structure.
Fermion systems in discrete space-time
Finster, Felix
2007-05-01
Fermion systems in discrete space-time are introduced as a model for physics on the Planck scale. We set up a variational principle which describes a non-local interaction of all fermions. This variational principle is symmetric under permutations of the discrete space-time points. We explain how for minimizers of the variational principle, the fermions spontaneously break this permutation symmetry and induce on space-time a discrete causal structure.
DEFF Research Database (Denmark)
Armitage, Andrew E; Deforche, Koen; Chang, Chih-Hao
2012-01-01
The rapid evolution of Human Immunodeficiency Virus (HIV-1) allows studies of ongoing host-pathogen interactions. One key selective host factor is APOBEC3G (hA3G) that can cause extensive and inactivating Guanosine-to-Adenosine (G-to-A) mutation on HIV plus-strand DNA (termed hypermutation). HIV...... can inhibit this innate anti-viral defense through binding of the viral protein Vif to hA3G, but binding efficiency varies and hypermutation frequencies fluctuate in patients. A pivotal question is whether hA3G-induced G-to-A mutation is always lethal to the virus or if it may occur at sub......-lethal frequencies that could increase viral diversification. We show in vitro that limiting-levels of hA3G-activity (i.e. when only a single hA3G-unit is likely to act on HIV) produce hypermutation frequencies similar to those in patients and demonstrate in silico that potentially non-lethal G-to-A mutation rates...
Yan, Xuzhou; Wang, Haoze; Hauke, Cory E; Cook, Timothy R; Wang, Ming; Saha, Manik Lal; Zhou, Zhixuan; Zhang, Mingming; Li, Xiaopeng; Huang, Feihe; Stang, Peter J
2015-12-09
Materials that organize multiple functionally active sites, especially those with aggregation-induced emission (AIE) properties, are of growing interest due to their widespread applications. Despite promising early architectures, the fabrication and preparation of multiple AIEgens, such as multiple tetraphenylethylene (multi-TPE) units, in a single entity remain a big challenge due to the tedious covalent synthetic procedures often accompanying such preparations. Coordination-driven self-assembly is an alternative synthetic methodology with the potential to deliver multi-TPE architectures with light-emitting characteristics. Herein, we report the preparation of a new family of discrete multi-TPE metallacycles in which two pendant phenyl rings of the TPE units remain unused as a structural element, representing novel AIE-active metal-organic materials based on supramolecular coordination complex platforms. These metallacycles possess relatively high molar absorption coefficients but weak fluorescent emission under dilute conditions because of the ability of the untethered phenyl rings to undergo torsional motion as a non-radiative decay pathway. Upon molecular aggregation, the multi-TPE metallacycles show AIE-activity with markedly enhanced quantum yields. Moreover, on account of their AIE characteristics in the condensed state and ability to interact with electron-deficient substrates, the photophysics of these metallacycles is sensitive to the presence of nitroaromatics, motivating their use as sensors. This work represents a unification of themes including molecular self-assembly, AIE, and fluorescence sensing and establishes structure-property-application relationships of multi-TPE scaffolds. The fundamental knowledge obtained from the current research facilitates progress in the field of metal-organic materials, metal-coordination-induced emission, and fluorescent sensing.
Mimetic discretization methods
Castillo, Jose E
2013-01-01
To help solve physical and engineering problems, mimetic or compatible algebraic discretization methods employ discrete constructs to mimic the continuous identities and theorems found in vector calculus. Mimetic Discretization Methods focuses on the recent mimetic discretization method co-developed by the first author. Based on the Castillo-Grone operators, this simple mimetic discretization method is invariably valid for spatial dimensions no greater than three. The book also presents a numerical method for obtaining corresponding discrete operators that mimic the continuum differential and
Ledenyov, Dimitri O.; Ledenyov, Viktor O.
2014-01-01
The authors perform an original research on the fundamentals of winning virtuous strategies creation toward the leveraged buyout transactions implementation during the private equity investment in the conditions of the resonant absorption of discrete information in the diffusion - type financial system with the induced nonlinearities at the influences by the Schumpeterian creative disruption processes in the free market economy. We propose that the money is a financial computing process, whic...
Time Discretization Techniques
Gottlieb, S.; Ketcheson, David I.
2016-01-01
The time discretization of hyperbolic partial differential equations is typically the evolution of a system of ordinary differential equations obtained by spatial discretization of the original problem. Methods for this time evolution include
Discretization of four types of Weyl group orbit functions
International Nuclear Information System (INIS)
Hrivnák, Jiří
2013-01-01
The discrete Fourier calculus of the four families of special functions, called C–, S–, S s – and S l -functions, is summarized. Functions from each of the four families of special functions are discretely orthogonal over a certain finite set of points. The generalizations of discrete cosine and sine transforms of one variable — the discrete S s – and S l -transforms of the group F 4 — are considered in detail required for their exploitation in discrete Fourier spectral methods. The continuous interpolations, induced by the discrete expansions, are presented
Testing Preference Axioms in Discrete Choice experiments
DEFF Research Database (Denmark)
Hougaard, Jens Leth; Østerdal, Lars Peter; Tjur, Tue
Recent studies have tested the preference axioms of completeness and transitivity, and have detected other preference phenomena such as unstability, learning- and tiredness effects, ordering effects and dominance, in stated preference discrete choice experiments. However, it has not been explicitly...... of the preference axioms and other preference phenomena in the context of stated preference discrete choice experiments, and examine whether or how these can be subject to meaningful (statistical) tests...
Meng, Zhen-Zhi; Chen, Jia-Xu; Jiang, You-Ming; Zhang, Han-Ting
2013-01-01
Xiaoyaosan (XYS) decoction is a famous prescription which can protect nervous system from stress and treat liver stagnation and spleen deficiency syndrome (LSSDS). In this experiment, we observed the effect of XYS decoction on chronic immobilization stress (CIS) induced learning and memory deficit in rats from behaviors and changes of proteins in hippocampus. We used XYS decoction to treat CIS induced learning and memory deficit in rats with rolipram as positive control, used change of body w...
Learning induces the translin/trax RNase complex to express activin receptors for persistent memory
Park, Alan Jung; Havekes, Robbert; Fu, Xiuping; Hansen, Rolf; Tudor, Jennifer C; Peixoto, Lucia; Li, Zhi; Wu, Yen-Ching; Poplawski, Shane G; Baraban, Jay M; Abel, Ted
2017-01-01
Long-lasting forms of synaptic plasticity and memory require de novo protein synthesis. Yet, how learning triggers this process to form memory is unclear. Translin/trax is a candidate to drive this learning-induced memory mechanism by suppressing microRNA-mediated translational silencing at
Laplacians on discrete and quantum geometries
International Nuclear Information System (INIS)
Calcagni, Gianluca; Oriti, Daniele; Thürigen, Johannes
2013-01-01
We extend discrete calculus for arbitrary (p-form) fields on embedded lattices to abstract discrete geometries based on combinatorial complexes. We then provide a general definition of discrete Laplacian using both the primal cellular complex and its combinatorial dual. The precise implementation of geometric volume factors is not unique and, comparing the definition with a circumcentric and a barycentric dual, we argue that the latter is, in general, more appropriate because it induces a Laplacian with more desirable properties. We give the expression of the discrete Laplacian in several different sets of geometric variables, suitable for computations in different quantum gravity formalisms. Furthermore, we investigate the possibility of transforming from position to momentum space for scalar fields, thus setting the stage for the calculation of heat kernel and spectral dimension in discrete quantum geometries. (paper)
FKBP5 polymorphisms influence pre-learning stress-induced alterations of learning and memory.
Zoladz, Phillip R; Dailey, Alison M; Nagle, Hannah E; Fiely, Miranda K; Mosley, Brianne E; Brown, Callie M; Duffy, Tessa J; Scharf, Amanda R; Earley, McKenna B; Rorabaugh, Boyd R
2017-03-01
FK506 binding protein 51 (FKBP5) is a co-chaperone of heat shock protein 90 and significantly influences glucocorticoid receptor sensitivity. Single nucleotide polymorphisms (SNPs) in the FKBP5 gene are associated with altered hypothalamus-pituitary-adrenal (HPA) axis function, changes in the structure and function of several cognitive brain areas, and increased susceptibility to post-traumatic stress disorder, major depression, bipolar disorder and suicidal events. The mechanisms underlying these associations are largely unknown, but it has been speculated that the influence of these SNPs on emotional memory systems may play a role. In the present study, 112 participants were exposed to the socially evaluated cold pressor test (stress) or control (no stress) conditions immediately prior to learning a list of 42 words. Participant memory was assessed immediately after learning (free recall) and 24 h later (free recall and recognition). Participants provided a saliva sample that enabled the genotyping of three FKBP5 polymorphisms: rs1360780, rs3800373 and rs9296158. Results showed that stress impaired immediate recall in risk allele carriers. More importantly, stress enhanced long-term recall and recognition memory in non-carriers of the risk alleles, effects that were completely absent in risk allele carriers. Follow-up analyses revealed that memory performance was correlated with salivary cortisol levels in non-carriers, but not in carriers. These findings suggest that FKBP5 risk allele carriers may possess a sensitized stress response system, perhaps specifically for stress-induced changes in corticosteroid levels, which might aid our understanding of how SNPs in the FKBP5 gene confer increased risk for stress-related psychological disorders and their related phenotypes. © 2016 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.
Discrete mathematics using a computer
Hall, Cordelia
2000-01-01
Several areas of mathematics find application throughout computer science, and all students of computer science need a practical working understanding of them. These core subjects are centred on logic, sets, recursion, induction, relations and functions. The material is often called discrete mathematics, to distinguish it from the traditional topics of continuous mathematics such as integration and differential equations. The central theme of this book is the connection between computing and discrete mathematics. This connection is useful in both directions: • Mathematics is used in many branches of computer science, in applica tions including program specification, datastructures,design and analysis of algorithms, database systems, hardware design, reasoning about the correctness of implementations, and much more; • Computers can help to make the mathematics easier to learn and use, by making mathematical terms executable, making abstract concepts more concrete, and through the use of software tools su...
Song, Li; Che, Wang; Min-Wei, Wang; Murakami, Yukihisa; Matsumoto, Kinzo
2006-02-01
Increasing evidences indicate the concurrence and interrelationship of depression and cognitive impairments. The present study was undertaken to investigate the effects of two depressive animal models, learned helplessness (LH) and chronic mild stress (CMS), on the cognitive functions of mice in the Morris water maze task. Our results demonstrated that both LH and CMS significantly decreased the cognitive performance of stressed mice in the water maze task. The escaping latency to the platform was prolonged and the probe test percentage in the platform quadrant was reduced. These two models also increased the plasma corticosterone concentration and decreased the brain derived neurotrophic factor (BDNF) and cAMP-response element-biding protein (CREB) messenger ribonucleic acid (mRNA) levels in hippocampus, which might cause the spatial cognition deficits. Repeated treatment with antidepressant drugs, imipramine (Imi) and fluoxetine (Flu), significantly reduced the plasma corticosterone concentration and enhanced the BDNF and CREB levels. Furthermore, antidepressant treated animals showed an ameliorated cognitive performance compared with the vehicle treated stressed animals. These data suggest that both LH and CMS impair the spatial cognitive function and repeated treatment with antidepressant drugs decreases the prevalence of cognitive impairments induced by these two animal models. Those might in part be attributed to the reduced plasma corticosterone and enhanced hippocampal BDNF and CREB expressions. This study provided a better understanding of molecular mechanisms underlying interactions of depression and cognitive impairments, although animal models used in this study can mimic only some aspects of depression or cognition of human.
Pattern-Induced Covert Category Learning in Songbirds.
Comins, Jordan A; Gentner, Timothy Q
2015-07-20
Language is uniquely human, but its acquisition may involve cognitive capacities shared with other species. During development, language experience alters speech sound (phoneme) categorization. Newborn infants distinguish the phonemes in all languages but by 10 months show adult-like greater sensitivity to native language phonemic contrasts than non-native contrasts. Distributional theories account for phonetic learning by positing that infants infer category boundaries from modal distributions of speech sounds along acoustic continua. For example, tokens of the sounds /b/ and /p/ cluster around different mean voice onset times. To disambiguate overlapping distributions, contextual theories propose that phonetic category learning is informed by higher-level patterns (e.g., words) in which phonemes normally occur. For example, the vowel sounds /Ι/ and /e/ can occupy similar perceptual spaces but can be distinguished in the context of "with" and "well." Both distributional and contextual cues appear to function in speech acquisition. Non-human species also benefit from distributional cues for category learning, but whether category learning benefits from contextual information in non-human animals is unknown. The use of higher-level patterns to guide lower-level category learning may reflect uniquely human capacities tied to language acquisition or more general learning abilities reflecting shared neurobiological mechanisms. Using songbirds, European starlings, we show that higher-level pattern learning covertly enhances categorization of the natural communication sounds. This observation mirrors the support for contextual theories of phonemic category learning in humans and demonstrates a general form of learning not unique to humans or language. Copyright © 2015 Elsevier Ltd. All rights reserved.
Toxin-Induced Experimental Models of Learning and Memory Impairment.
More, Sandeep Vasant; Kumar, Hemant; Cho, Duk-Yeon; Yun, Yo-Sep; Choi, Dong-Kug
2016-09-01
Animal models for learning and memory have significantly contributed to novel strategies for drug development and hence are an imperative part in the assessment of therapeutics. Learning and memory involve different stages including acquisition, consolidation, and retrieval and each stage can be characterized using specific toxin. Recent studies have postulated the molecular basis of these processes and have also demonstrated many signaling molecules that are involved in several stages of memory. Most insights into learning and memory impairment and to develop a novel compound stems from the investigations performed in experimental models, especially those produced by neurotoxins models. Several toxins have been utilized based on their mechanism of action for learning and memory impairment such as scopolamine, streptozotocin, quinolinic acid, and domoic acid. Further, some toxins like 6-hydroxy dopamine (6-OHDA), 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) and amyloid-β are known to cause specific learning and memory impairment which imitate the disease pathology of Parkinson's disease dementia and Alzheimer's disease dementia. Apart from these toxins, several other toxins come under a miscellaneous category like an environmental pollutant, snake venoms, botulinum, and lipopolysaccharide. This review will focus on the various classes of neurotoxin models for learning and memory impairment with their specific mechanism of action that could assist the process of drug discovery and development for dementia and cognitive disorders.
Baecklund transformations for discrete Painleve equations: Discrete PII-PV
International Nuclear Information System (INIS)
Sakka, A.; Mugan, U.
2006-01-01
Transformation properties of discrete Painleve equations are investigated by using an algorithmic method. This method yields explicit transformations which relates the solutions of discrete Painleve equations, discrete P II -P V , with different values of parameters. The particular solutions which are expressible in terms of the discrete analogue of the classical special functions of discrete Painleve equations can also be obtained from these transformations
Discrete Gabor transform and discrete Zak transform
Bastiaans, M.J.; Namazi, N.M.; Matthews, K.
1996-01-01
Gabor's expansion of a discrete-time signal into a set of shifted and modulated versions of an elementary signal or synthesis window is introduced, along with the inverse operation, i.e. the Gabor transform, which uses an analysis window that is related to the synthesis window and with the help of
Crocin Improved Learning and Memory Impairments in Streptozotocin-Induced Diabetic Rats
Directory of Open Access Journals (Sweden)
Esmaeal Tamaddonfard
2013-01-01
Full Text Available Objective(s: Crocin influences many biological functions including memory and learning. The present study was aimed to investigate the effects of crocin on learning and memory impairments in streptozotocine-induced diabetic rats. Materials and Methods: Diabetes was induced by intraperitoneal (IP injection of streptozotocin (STZ, 45 mg/kg. Transfer latency (TL paradigm in elevated plus-maze (EPM was used as an index of learning and memory. Plasma levels of total antioxidant capacity (TAC and malondialdehyde (MDA, blood levels of glucose, and serum concentrations of insulin were measured. The number of hippocampal neurons was also counted. Results: STZ increased acquisition transfer latency (TL1 and retention transfer latency (TL2, and MDA, decreased transfer latency shortening (TLs and TCA, produced hyperglycemia and hypoinsulinemia, and reduced the number of neurons in the hippocampus. Learning and memory impairments and blood TCA, MDA, glucose, and insulin changes induced by streptozotocin were improved with long-term IP injection of crocin at doses of 15 and 30 mg/kg. Crocin prevented hippocampal neurons number loss in diabetic rats. Conclusion: The results indicate that oxidative stress, hyperglycemia, hypoinsulinemia, and reduction of hippocampal neurons may be involved in learning and memory impairments in STZ-induced diabetic rats. Antioxidant, antihyperglycemic, antihypoinsulinemic, and neuroprotective activities of crocin might be involved in improving learning and memory impairments.
Proinflammatory Factors Mediate Paclitaxel-Induced Impairment of Learning and Memory
Directory of Open Access Journals (Sweden)
Zhao Li
2018-01-01
Full Text Available The chemotherapeutic agent paclitaxel is widely used for cancer treatment. Paclitaxel treatment impairs learning and memory function, a side effect that reduces the quality of life of cancer survivors. However, the neural mechanisms underlying paclitaxel-induced impairment of learning and memory remain unclear. Paclitaxel treatment leads to proinflammatory factor release and neuronal apoptosis. Thus, we hypothesized that paclitaxel impairs learning and memory function through proinflammatory factor-induced neuronal apoptosis. Neuronal apoptosis was assessed by TUNEL assay in the hippocampus. Protein expression levels of tumor necrosis factor-α (TNF-α and interleukin-1β (IL-1β in the hippocampus tissue were analyzed by Western blot assay. Spatial learning and memory function were determined by using the Morris water maze (MWM test. Paclitaxel treatment significantly increased the escape latencies and decreased the number of crossing in the MWM test. Furthermore, paclitaxel significantly increased the number of TUNEL-positive neurons in the hippocampus. Also, paclitaxel treatment increased the expression levels of TNF-α and IL-1β in the hippocampus tissue. In addition, the TNF-α synthesis inhibitor thalidomide significantly attenuated the number of paclitaxel-induced TUNEL-positive neurons in the hippocampus and restored the impaired spatial learning and memory function in paclitaxel-treated rats. These data suggest that TNF-α is critically involved in the paclitaxel-induced impairment of learning and memory function.
Homogenization of discrete media
International Nuclear Information System (INIS)
Pradel, F.; Sab, K.
1998-01-01
Material such as granular media, beam assembly are easily seen as discrete media. They look like geometrical points linked together thanks to energetic expressions. Our purpose is to extend discrete kinematics to the one of an equivalent continuous material. First we explain how we build the localisation tool for periodic materials according to estimated continuum medium type (classical Cauchy, and Cosserat media). Once the bridge built between discrete and continuum media, we exhibit its application over two bidimensional beam assembly structures : the honey comb and a structural reinforced variation. The new behavior is then applied for the simple plan shear problem in a Cosserat continuum and compared with the real discrete solution. By the mean of this example, we establish the agreement of our new model with real structures. The exposed method has a longer range than mechanics and can be applied to every discrete problems like electromagnetism in which relationship between geometrical points can be summed up by an energetic function. (orig.)
International Nuclear Information System (INIS)
Aydin, Alhun; Sisman, Altug
2016-01-01
By considering the quantum-mechanically minimum allowable energy interval, we exactly count number of states (NOS) and introduce discrete density of states (DOS) concept for a particle in a box for various dimensions. Expressions for bounded and unbounded continua are analytically recovered from discrete ones. Even though substantial fluctuations prevail in discrete DOS, they're almost completely flattened out after summation or integration operation. It's seen that relative errors of analytical expressions of bounded/unbounded continua rapidly decrease for high NOS values (weak confinement or high energy conditions), while the proposed analytical expressions based on Weyl's conjecture always preserve their lower error characteristic. - Highlights: • Discrete density of states considering minimum energy difference is proposed. • Analytical DOS and NOS formulas based on Weyl conjecture are given. • Discrete DOS and NOS functions are examined for various dimensions. • Relative errors of analytical formulas are much better than the conventional ones.
Energy Technology Data Exchange (ETDEWEB)
Aydin, Alhun; Sisman, Altug, E-mail: sismanal@itu.edu.tr
2016-03-22
By considering the quantum-mechanically minimum allowable energy interval, we exactly count number of states (NOS) and introduce discrete density of states (DOS) concept for a particle in a box for various dimensions. Expressions for bounded and unbounded continua are analytically recovered from discrete ones. Even though substantial fluctuations prevail in discrete DOS, they're almost completely flattened out after summation or integration operation. It's seen that relative errors of analytical expressions of bounded/unbounded continua rapidly decrease for high NOS values (weak confinement or high energy conditions), while the proposed analytical expressions based on Weyl's conjecture always preserve their lower error characteristic. - Highlights: • Discrete density of states considering minimum energy difference is proposed. • Analytical DOS and NOS formulas based on Weyl conjecture are given. • Discrete DOS and NOS functions are examined for various dimensions. • Relative errors of analytical formulas are much better than the conventional ones.
Okuyama, Yoshifumi
2014-01-01
Discrete Control Systems establishes a basis for the analysis and design of discretized/quantized control systemsfor continuous physical systems. Beginning with the necessary mathematical foundations and system-model descriptions, the text moves on to derive a robust stability condition. To keep a practical perspective on the uncertain physical systems considered, most of the methods treated are carried out in the frequency domain. As part of the design procedure, modified Nyquist–Hall and Nichols diagrams are presented and discretized proportional–integral–derivative control schemes are reconsidered. Schemes for model-reference feedback and discrete-type observers are proposed. Although single-loop feedback systems form the core of the text, some consideration is given to multiple loops and nonlinearities. The robust control performance and stability of interval systems (with multiple uncertainties) are outlined. Finally, the monograph describes the relationship between feedback-control and discrete ev...
Discrete repulsive oscillator wavefunctions
International Nuclear Information System (INIS)
Munoz, Carlos A; Rueda-Paz, Juvenal; Wolf, Kurt Bernardo
2009-01-01
For the study of infinite discrete systems on phase space, the three-dimensional Lorentz algebra and group, so(2,1) and SO(2,1), provide a discrete model of the repulsive oscillator. Its eigenfunctions are found in the principal irreducible representation series, where the compact generator-that we identify with the position operator-has the infinite discrete spectrum of the integers Z, while the spectrum of energies is a double continuum. The right- and left-moving wavefunctions are given by hypergeometric functions that form a Dirac basis for l 2 (Z). Under contraction, the discrete system limits to the well-known quantum repulsive oscillator. Numerical computations of finite approximations raise further questions on the use of Dirac bases for infinite discrete systems.
Energy Technology Data Exchange (ETDEWEB)
Morris, J; Johnson, S
2007-12-03
The Distinct Element Method (also frequently referred to as the Discrete Element Method) (DEM) is a Lagrangian numerical technique where the computational domain consists of discrete solid elements which interact via compliant contacts. This can be contrasted with Finite Element Methods where the computational domain is assumed to represent a continuum (although many modern implementations of the FEM can accommodate some Distinct Element capabilities). Often the terms Discrete Element Method and Distinct Element Method are used interchangeably in the literature, although Cundall and Hart (1992) suggested that Discrete Element Methods should be a more inclusive term covering Distinct Element Methods, Displacement Discontinuity Analysis and Modal Methods. In this work, DEM specifically refers to the Distinct Element Method, where the discrete elements interact via compliant contacts, in contrast with Displacement Discontinuity Analysis where the contacts are rigid and all compliance is taken up by the adjacent intact material.
Learning-induced neural plasticity of speech processing before birth.
Partanen, Eino; Kujala, Teija; Näätänen, Risto; Liitola, Auli; Sambeth, Anke; Huotilainen, Minna
2013-09-10
Learning, the foundation of adaptive and intelligent behavior, is based on plastic changes in neural assemblies, reflected by the modulation of electric brain responses. In infancy, auditory learning implicates the formation and strengthening of neural long-term memory traces, improving discrimination skills, in particular those forming the prerequisites for speech perception and understanding. Although previous behavioral observations show that newborns react differentially to unfamiliar sounds vs. familiar sound material that they were exposed to as fetuses, the neural basis of fetal learning has not thus far been investigated. Here we demonstrate direct neural correlates of human fetal learning of speech-like auditory stimuli. We presented variants of words to fetuses; unlike infants with no exposure to these stimuli, the exposed fetuses showed enhanced brain activity (mismatch responses) in response to pitch changes for the trained variants after birth. Furthermore, a significant correlation existed between the amount of prenatal exposure and brain activity, with greater activity being associated with a higher amount of prenatal speech exposure. Moreover, the learning effect was generalized to other types of similar speech sounds not included in the training material. Consequently, our results indicate neural commitment specifically tuned to the speech features heard before birth and their memory representations.
Learning-induced pattern classification in a chaotic neural network
International Nuclear Information System (INIS)
Li, Yang; Zhu, Ping; Xie, Xiaoping; He, Guoguang; Aihara, Kazuyuki
2012-01-01
In this Letter, we propose a Hebbian learning rule with passive forgetting (HLRPF) for use in a chaotic neural network (CNN). We then define the indices based on the Euclidean distance to investigate the evolution of the weights in a simplified way. Numerical simulations demonstrate that, under suitable external stimulations, the CNN with the proposed HLRPF acts as a fuzzy-like pattern classifier that performs much better than an ordinary CNN. The results imply relationship between learning and recognition. -- Highlights: ► Proposing a Hebbian learning rule with passive forgetting (HLRPF). ► Defining indices to investigate the evolution of the weights simply. ► The chaotic neural network with HLRPF acts as a fuzzy-like pattern classifier. ► The pattern classifier ability of the network is improved much.
Genetically-induced cholinergic hyper-innervation enhances taste learning
Directory of Open Access Journals (Sweden)
Selin eNeseliler
2011-12-01
Full Text Available Acute inhibition of acetylcholine (ACh has been shown to impair many forms of simple learning, and notably conditioned taste aversion (CTA. The most adhered-to theory that has emerged as a result of this work—that ACh increases a taste’s perceived novelty, and thereby its associability—would be further strengthened by evidence showing that enhanced cholinergic function improves learning above normal levels. Experimental testing of this corollary hypothesis has been limited, however, by side-effects of pharmacological ACh agonism and by the absence of a model that achieves long-term increases in cholinergic signaling. Here, we present this further test of the ACh hypothesis, making use of mice lacking the p75 pan-neurotrophin receptor gene, which show a resultant over-abundance of cholinergic neurons in subregions of the basal forebrain (BF. We first demonstrate that the p75-/- abnormality directly affects portions of the CTA circuit, locating mouse gustatory cortex (GC using a functional assay and then using immunohistochemisty to demonstrate cholinergic hyperinnervation of GC in the mutant mice—hyperinnervation that is unaccompanied by changes in cell numbers or compensatory changes in muscarinic receptor densities. We then demonstrate that both p75-/- and wild-type mice learn robust CTAs, which extinguish more slowly in the mutants. Further testing to distinguish effects on learning from alterations in memory retention demonstrate that p75-/- mice do in fact learn stronger CTAs than wild-type mice. These data provide novel evidence for the hypothesis linking ACh and taste learning.
Siri, Benoît; Berry, Hugues; Cessac, Bruno; Delord, Bruno; Quoy, Mathias
2008-12-01
We present a mathematical analysis of the effects of Hebbian learning in random recurrent neural networks, with a generic Hebbian learning rule, including passive forgetting and different timescales, for neuronal activity and learning dynamics. Previous numerical work has reported that Hebbian learning drives the system from chaos to a steady state through a sequence of bifurcations. Here, we interpret these results mathematically and show that these effects, involving a complex coupling between neuronal dynamics and synaptic graph structure, can be analyzed using Jacobian matrices, which introduce both a structural and a dynamical point of view on neural network evolution. Furthermore, we show that sensitivity to a learned pattern is maximal when the largest Lyapunov exponent is close to 0. We discuss how neural networks may take advantage of this regime of high functional interest.
Crisis-induced learning in public sector organizations
Deverell, E.C.
2010-01-01
How do public organizations manage crises? How do public organizations learn from crises? These seemingly basic questions still pose virtual puzzles for crisis management researchers. This dissertation sheds light on the problems regarding the lack of knowledge on how public organizations manage and
Implicit versus explicit associative learning and experimentally induced placebo hypoalgesia
Directory of Open Access Journals (Sweden)
Andrea L Martin-Pichora
2011-03-01
Full Text Available Andrea L Martin-Pichora1,2, Tsipora D. Mankovsky-Arnold3, Joel Katz11Department of Psychology, York University, Toronto, ON, Canada; 2Centre for Student Development and Counseling, Ryerson University, Toronto, ON, Canada; 3Department of Psychology, McGill University, Montreal, QC, CanadaAbstract: The present study examined whether 1 placebo hypoalgesia can be generated through implicit associative learning (ie, conditioning in the absence of conscious awareness and 2 the magnitude of placebo hypoalgesia changes when expectations about pain are made explicit. The temperature of heat pain stimuli was surreptitiously lowered during conditioning trials for the placebo cream and the magnitude of the placebo effect was assessed during a subsequent set of trials when the temperature was the same for both placebo and control conditions. To assess whether placebo hypoalgesia could be generated from an implicit tactile stimulus, a 2 × 2 design was used with direction of cream application as one factor and verbal information about which cream was being applied as the second factor. A significant placebo effect was observed when participants received verbal information about which cream was being applied but not following implicit conditioning alone. However, 87.5% of those who showed a placebo response as the result of implicit conditioning were able to accurately guess the order of cream application during the final trial, despite a lack of awareness about the sensory manipulation and low confidence in their ratings, suggesting implicit learning in some participants. In summary, implicit associative learning was evident in some participants but it was not sufficient to produce a placebo effect suggesting some level of explicit expectation or cognitive mediation may be necessary. Notably, the placebo response was abolished when expectations were made explicit, suggesting a delicate interplay between attention and expectation.Keywords: placebo hypoalgesia
Brown, Ronald; Higgins, Philip J.
2002-01-01
The main result is that the fundamental groupoid of the orbit space of a discontinuous action of a discrete group on a Hausdorff space which admits a universal cover is the orbit groupoid of the fundamental groupoid of the space. We also describe work of Higgins and of Taylor which makes this result usable for calculations. As an example, we compute the fundamental group of the symmetric square of a space. The main result, which is related to work of Armstrong, is due to Brown and Higgins in ...
Izadi, F A; Bagirov, G
2009-01-01
With its origins stretching back several centuries, discrete calculus is now an increasingly central methodology for many problems related to discrete systems and algorithms. The topics covered here usually arise in many branches of science and technology, especially in discrete mathematics, numerical analysis, statistics and probability theory as well as in electrical engineering, but our viewpoint here is that these topics belong to a much more general realm of mathematics; namely calculus and differential equations because of the remarkable analogy of the subject to this branch of mathemati
Directory of Open Access Journals (Sweden)
Lan Zhu
Full Text Available Learning to fear dangerous situations requires the participation of basolateral amygdala (BLA. In the present study, we provide evidence that BLA is necessary for the synaptic strengthening occurring during memory formation in the cerebellum in rats. In the cerebellar vermis the parallel fibers (PF to Purkinje cell (PC synapse is potentiated one day following fear learning. Pretraining BLA inactivation impaired such a learning-induced long-term potentiation (LTP. Similarly, cerebellar LTP is affected when BLA is blocked shortly, but not 6 h, after training. The latter result shows that the effects of BLA inactivation on cerebellar plasticity, when present, are specifically related to memory processes and not due to an interference with sensory or motor functions. These data indicate that fear memory induces cerebellar LTP provided that a heterosynaptic input coming from BLA sets the proper local conditions. Therefore, in the cerebellum, learning-induced plasticity is a heterosynaptic phenomenon that requires inputs from other regions. Studies employing the electrically-induced LTP in order to clarify the cellular mechanisms of memory should therefore take into account the inputs arriving from other brain sites, considering them as integrative units. Based on previous and the present findings, we proposed that BLA enables learning-related plasticity to be formed in the cerebellum in order to respond appropriately to new stimuli or situations.
Finite Discrete Gabor Analysis
DEFF Research Database (Denmark)
Søndergaard, Peter Lempel
2007-01-01
frequency bands at certain times. Gabor theory can be formulated for both functions on the real line and for discrete signals of finite length. The two theories are largely the same because many aspects come from the same underlying theory of locally compact Abelian groups. The two types of Gabor systems...... can also be related by sampling and periodization. This thesis extends on this theory by showing new results for window construction. It also provides a discussion of the problems associated to discrete Gabor bases. The sampling and periodization connection is handy because it allows Gabor systems...... on the real line to be well approximated by finite and discrete Gabor frames. This method of approximation is especially attractive because efficient numerical methods exists for doing computations with finite, discrete Gabor systems. This thesis presents new algorithms for the efficient computation of finite...
Adaptive Discrete Hypergraph Matching.
Yan, Junchi; Li, Changsheng; Li, Yin; Cao, Guitao
2018-02-01
This paper addresses the problem of hypergraph matching using higher-order affinity information. We propose a solver that iteratively updates the solution in the discrete domain by linear assignment approximation. The proposed method is guaranteed to converge to a stationary discrete solution and avoids the annealing procedure and ad-hoc post binarization step that are required in several previous methods. Specifically, we start with a simple iterative discrete gradient assignment solver. This solver can be trapped in an -circle sequence under moderate conditions, where is the order of the graph matching problem. We then devise an adaptive relaxation mechanism to jump out this degenerating case and show that the resulting new path will converge to a fixed solution in the discrete domain. The proposed method is tested on both synthetic and real-world benchmarks. The experimental results corroborate the efficacy of our method.
International Nuclear Information System (INIS)
Williams, Ruth M
2006-01-01
A review is given of a number of approaches to discrete quantum gravity, with a restriction to those likely to be relevant in four dimensions. This paper is dedicated to Rafael Sorkin on the occasion of his sixtieth birthday
Discrete computational structures
Korfhage, Robert R
1974-01-01
Discrete Computational Structures describes discrete mathematical concepts that are important to computing, covering necessary mathematical fundamentals, computer representation of sets, graph theory, storage minimization, and bandwidth. The book also explains conceptual framework (Gorn trees, searching, subroutines) and directed graphs (flowcharts, critical paths, information network). The text discusses algebra particularly as it applies to concentrates on semigroups, groups, lattices, propositional calculus, including a new tabular method of Boolean function minimization. The text emphasize
Mechanisms of radiation-induced conditioned taste aversion learning
International Nuclear Information System (INIS)
Rabin, B.M.; Hunt, W.A.
1986-01-01
The literature on taste aversion learning is reviewed and discussed, with particular emphasis on those studies that have used exposure to ionizing radiation as an unconditioned stimulus to produce a conditioned taste aversion. The primary aim of the review is to attempt to define the mechanisms that lead to the initiation of the taste aversion response following exposure to ionizing radiation. Studies using drug treatments to produce a taste aversion have been included to the extent that they are relevant to understanding the mechanisms by which exposure to ionizing radiation can affect the behavior of the organism. 141 references
Digital and discrete geometry theory and algorithms
Chen, Li
2014-01-01
This book provides comprehensive coverage of the modern methods for geometric problems in the computing sciences. It also covers concurrent topics in data sciences including geometric processing, manifold learning, Google search, cloud data, and R-tree for wireless networks and BigData.The author investigates digital geometry and its related constructive methods in discrete geometry, offering detailed methods and algorithms. The book is divided into five sections: basic geometry; digital curves, surfaces and manifolds; discretely represented objects; geometric computation and processing; and a
Directory of Open Access Journals (Sweden)
Ori Liraz
Full Text Available Pyramidal neurons in the piriform cortex from olfactory-discrimination trained rats show enhanced intrinsic neuronal excitability that lasts for several days after learning. Such enhanced intrinsic excitability is mediated by long-term reduction in the post-burst after-hyperpolarization (AHP which is generated by repetitive spike firing. AHP reduction is due to decreased conductance of a calcium-dependent potassium current, the sI(AHP. We have previously shown that learning-induced AHP reduction is maintained by persistent protein kinase C (PKC and extracellular regulated kinase (ERK activation. However, the molecular machinery underlying this long-lasting modulation of intrinsic excitability is yet to be fully described. Here we examine whether the CaMKII, which is known to be crucial in learning, memory and synaptic plasticity processes, is instrumental for the maintenance of learning-induced AHP reduction. KN93, that selectively blocks CaMKII autophosphorylation at Thr286, reduced the AHP in neurons from trained and control rat to the same extent. Consequently, the differences in AHP amplitude and neuronal adaptation between neurons from trained rats and controls remained. Accordingly, the level of activated CaMKII was similar in pirifrom cortex samples taken form trained and control rats. Our data show that although CaMKII modulates the amplitude of AHP of pyramidal neurons in the piriform cortex, its activation is not required for maintaining learning-induced enhancement of neuronal excitability.
Effects of visual feedback-induced variability on motor learning of handrim wheelchair propulsion.
Leving, Marika T; Vegter, Riemer J K; Hartog, Johanneke; Lamoth, Claudine J C; de Groot, Sonja; van der Woude, Lucas H V
2015-01-01
It has been suggested that a higher intra-individual variability benefits the motor learning of wheelchair propulsion. The present study evaluated whether feedback-induced variability on wheelchair propulsion technique variables would also enhance the motor learning process. Learning was operationalized as an improvement in mechanical efficiency and propulsion technique, which are thought to be closely related during the learning process. 17 Participants received visual feedback-based practice (feedback group) and 15 participants received regular practice (natural learning group). Both groups received equal practice dose of 80 min, over 3 weeks, at 0.24 W/kg at a treadmill speed of 1.11 m/s. To compare both groups the pre- and post-test were performed without feedback. The feedback group received real-time visual feedback on seven propulsion variables with instruction to manipulate the presented variable to achieve the highest possible variability (1st 4-min block) and optimize it in the prescribed direction (2nd 4-min block). To increase motor exploration the participants were unaware of the exact variable they received feedback on. Energy consumption and the propulsion technique variables with their respective coefficient of variation were calculated to evaluate the amount of intra-individual variability. The feedback group, which practiced with higher intra-individual variability, improved the propulsion technique between pre- and post-test to the same extent as the natural learning group. Mechanical efficiency improved between pre- and post-test in the natural learning group but remained unchanged in the feedback group. These results suggest that feedback-induced variability inhibited the improvement in mechanical efficiency. Moreover, since both groups improved propulsion technique but only the natural learning group improved mechanical efficiency, it can be concluded that the improvement in mechanical efficiency and propulsion technique do not always appear
Antithyroid drug induced agranulocytosis: what still we need to learn ?
Chaudhry, Liaqat Ali; Mazen, Khalid Fouad; Ba-Essa, Ebtesam; Robert, Asirvatham Alwin
2016-01-01
Antithyroid drugs (ATDs) induced agranulocytosis is a rare but life threatening condition. We report a 29 years Filipino female diagnosed as having hyperthyroidism with normal base line blood counts, liver and renal profile. She was started on maximum 60mg (20mg TID) oral dose of carbimazole since one month by her treating physician. Exactly after one month of treatment she presented to emergency room (ER) with fever, sore throat and generalized weakness for several days. PMID:27200132
Activation of dopamine D3 receptors inhibits reward-related learning induced by cocaine.
Kong, H; Kuang, W; Li, S; Xu, M
2011-03-10
Memories of learned associations between the rewarding properties of drugs and environmental cues contribute to craving and relapse in humans. The mesocorticolimbic dopamine (DA) system is involved in reward-related learning induced by drugs of abuse. DA D3 receptors are preferentially expressed in mesocorticolimbic DA projection areas. Genetic and pharmacological studies have shown that DA D3 receptors suppress locomotor-stimulant effects of cocaine and reinstatement of cocaine-seeking behaviors. Activation of the extracellular signal-regulated kinase (ERK) induced by acute cocaine administration is also inhibited by D3 receptors. How D3 receptors modulate cocaine-induced reward-related learning and associated changes in cell signaling in reward circuits in the brain, however, have not been fully investigated. In the present study, we show that D3 receptor mutant mice exhibit potentiated acquisition of conditioned place preference (CPP) at low doses of cocaine compared to wild-type mice. Activation of ERK and CaMKIIα, but not the c-Jun N-terminal kinase and p38, in the nucleus accumbens, amygdala and prefrontal cortex is also potentiated in D3 receptor mutant mice compared to that in wild-type mice following CPP expression. These results support a model in which D3 receptors modulate reward-related learning induced by low doses of cocaine by inhibiting activation of ERK and CaMKIIα in reward circuits in the brain. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.
Effects of Multimedia and Schema Induced Analogical Reasoning on Science Learning
Zheng, R. Z.; Yang, W.; Garcia, D.; McCadden, E. P.
2008-01-01
The present study investigates the effects of multimedia and schema induced analogical reasoning on science learning. It involves 89 fourth grade elementary students in the north-east of the United States. Participants are randomly assigned into four conditions: (a) multimedia with analogy; (b) multimedia without analogy; (c) analogy without…
Unconscious Attentional Capture Effect Can be Induced by Perceptual Learning
Directory of Open Access Journals (Sweden)
Zhe Qu
2011-05-01
Full Text Available Previous ERP studies have shown that N2pc serves as an index for salient stimuli that capture attention, even if they are task irrelevant. This study aims to investigate whether nonsalient stimuli can capture attention automatically and unconsciously after perceptual learning. Adult subjects were trained with a visual search task for eight to ten sessions. The training task was to detect whether the target (triangle with one particular direction was present or not. After training, an ERP session was performed, in which subjects were required to detect the presence of either the trained triangle (i.e., the target triangle in the training sessions or an untrained triangle. Results showed that, while the untrained triangle did not elicit an N2pc effect, the trained triangle elicited a significant N2pc effect regardless of whether it was perceived correctly or not, even when it was task irrelevant. Moreover, the N2pc effect for the trained triangle was completely retained 3 months later. These results suggest that, after perceptual learning, previously unsalient stimuli become more salient and can capture attention automatically and unconsciously. Once the facilitating process of the unsalient stimulus has been built up in the brain, it can last for a long time.
Methylmercury chloride induces learning deficits in prenatally treated rats
Energy Technology Data Exchange (ETDEWEB)
Muesch, H.R.; Bornhausen, M.; Kriegel, H.; Greim, H.
1978-01-01
Methylmercury chloride (MMC) was given to pregnant rats on the 6th, 7th, 8th, and 9th day after conception in doses of 0.05 and 2.0 mg/kg/day. The female offspring of these animals were tested 90 days after birth for learning ability using operant conditioning procedures. The rats were kept at 90% of their normal body weight and trained in a lever-box to press a bar in order to obtain a food pellet. Significant differences in the acquisition speed became apparent when the ratio of bar presses to reward was increased in a classical contingency of differential reinforcement of high rates even at MMC-doses of 4 x 0.05 mg/kg. These differences were not found in the general motility level nor in motor coordination.
Homogenization of discrete media
Energy Technology Data Exchange (ETDEWEB)
Pradel, F.; Sab, K. [CERAM-ENPC, Marne-la-Vallee (France)
1998-11-01
Material such as granular media, beam assembly are easily seen as discrete media. They look like geometrical points linked together thanks to energetic expressions. Our purpose is to extend discrete kinematics to the one of an equivalent continuous material. First we explain how we build the localisation tool for periodic materials according to estimated continuum medium type (classical Cauchy, and Cosserat media). Once the bridge built between discrete and continuum media, we exhibit its application over two bidimensional beam assembly structures : the honey comb and a structural reinforced variation. The new behavior is then applied for the simple plan shear problem in a Cosserat continuum and compared with the real discrete solution. By the mean of this example, we establish the agreement of our new model with real structures. The exposed method has a longer range than mechanics and can be applied to every discrete problems like electromagnetism in which relationship between geometrical points can be summed up by an energetic function. (orig.) 7 refs.
DISCRETE MATHEMATICS/NUMBER THEORY
Mrs. Manju Devi*
2017-01-01
Discrete mathematics is the study of mathematical structures that are fundamentally discrete rather than continuous. In contrast to real numbers that have the property of varying "smoothly", the objects studied in discrete mathematics such as integers, graphs, and statements do not vary smoothly in this way, but have distinct, separated values. Discrete mathematics therefore excludes topics in "continuous mathematics" such as calculus and analysis. Discrete objects can often be enumerated by ...
Directory of Open Access Journals (Sweden)
Prateek Sharma
2015-04-01
Full Text Available Abstract Simulation can be regarded as the emulation of the behavior of a real-world system over an interval of time. The process of simulation relies upon the generation of the history of a system and then analyzing that history to predict the outcome and improve the working of real systems. Simulations can be of various kinds but the topic of interest here is one of the most important kind of simulation which is Discrete-Event Simulation which models the system as a discrete sequence of events in time. So this paper aims at introducing about Discrete-Event Simulation and analyzing how it is beneficial to the real world systems.
Discrete systems and integrability
Hietarinta, J; Nijhoff, F W
2016-01-01
This first introductory text to discrete integrable systems introduces key notions of integrability from the vantage point of discrete systems, also making connections with the continuous theory where relevant. While treating the material at an elementary level, the book also highlights many recent developments. Topics include: Darboux and Bäcklund transformations; difference equations and special functions; multidimensional consistency of integrable lattice equations; associated linear problems (Lax pairs); connections with Padé approximants and convergence algorithms; singularities and geometry; Hirota's bilinear formalism for lattices; intriguing properties of discrete Painlevé equations; and the novel theory of Lagrangian multiforms. The book builds the material in an organic way, emphasizing interconnections between the various approaches, while the exposition is mostly done through explicit computations on key examples. Written by respected experts in the field, the numerous exercises and the thoroug...
Introductory discrete mathematics
Balakrishnan, V K
2010-01-01
This concise text offers an introduction to discrete mathematics for undergraduate students in computer science and mathematics. Mathematics educators consider it vital that their students be exposed to a course in discrete methods that introduces them to combinatorial mathematics and to algebraic and logical structures focusing on the interplay between computer science and mathematics. The present volume emphasizes combinatorics, graph theory with applications to some stand network optimization problems, and algorithms to solve these problems.Chapters 0-3 cover fundamental operations involv
Prateek Sharma
2015-01-01
Abstract Simulation can be regarded as the emulation of the behavior of a real-world system over an interval of time. The process of simulation relies upon the generation of the history of a system and then analyzing that history to predict the outcome and improve the working of real systems. Simulations can be of various kinds but the topic of interest here is one of the most important kind of simulation which is Discrete-Event Simulation which models the system as a discrete sequence of ev...
International Nuclear Information System (INIS)
Pando L, C.L.; Doedel, E.J.
2006-08-01
We investigate the nonlinear dynamics in a trimer, described by the one-dimensional discrete nonlinear Schrodinger equation (DNLSE), with periodic boundary conditions in the presence of a single on-site defect. We make use of numerical continuation to study different families of stationary and periodic solutions, which allows us to consider suitable perturbations. Taking into account a Poincare section, we are able to study the dynamics in both a thin stochastic layer solution and a global stochasticity solution. We find that the time series of the transit times, the time intervals to traverse some suitable sets in phase space, generate 1/f noise for both stochastic solutions. In the case of the thin stochastic layer solution, we find that transport between two almost invariant sets along with intermittency in small and large time scales are relevant features of the dynamics. These results are reflected in the behaviour of the standard map with suitable parameters. In both chaotic solutions, the distribution of transit times has a maximum and a tail with exponential decay in spite of the presence of long-range correlations in the time series. We motivate our study by considering a ring of weakly-coupled Bose-Einstein condensates (BEC) with attractive interactions, where inversion of populations between two spatially symmetric sites and phase locking take place in both chaotic solutions. (author)
Role of the area postrema in radiation-induced taste aversion learning and emesis in cats
International Nuclear Information System (INIS)
Rabin, B.M.; Hunt, W.A.; Chedester, A.L.; Lee, J.
1986-01-01
The role of the area postrema in radiation-induced emesis and taste aversion learning and the relationship between these behaviors were studied in cats. The potential involvement of neural factors which might be independent of the area postrema was minimized by using low levels of ionizing radiation (100 rads at a dose rate of 40 rads/min) to elicit a taste aversion, and by using body-only exposures (4500 and 6000 rads at 450 rads/min) to produce emesis. Lesions of the area postrema disrupted both taste aversion learning and emesis following irradiation. These results, which indicate that the area postrema is involved in the mediation of both radiation-induced emesis and taste aversion learning in cats under these experimental conditions, are interpreted as being consistent with the hypotheses that similar mechanisms mediate both responses to exposure to ionizing radiation, and that the taste aversion learning paradigm can therefore serve as a model system for studying radiation-induced emesis
Establishing a pharmacotherapy induced ototoxicity programme within a service-learning approach
Directory of Open Access Journals (Sweden)
Natalie Schellack
2015-06-01
Full Text Available Pharmacotherapy-induced ototoxicity is growing, especially in developing countries such as South Africa. This highlights the importance of ototoxicity monitoring and management of hearing loss. This article focuses on the establishment of an ototoxicity clinic as a site for the implementation of a service-learning module in the Audiology programme. The clinic offers a unique opportunity of collaboration between pharmacists and an audiologist where pharmacotherapy-induced ototoxicity is uniquely monitored. The Sefako Makgatho Health Sciences University (SMU provides training to both the disciplines audiology and pharmacy. The main aim of this article is to describe how ototoxicity monitoring is implemented in the curriculum within such an academic service-learning approach. Through service learning students develop a deeper understanding of course content, acquire new knowledge and engage in civic activity. It simultaneously provides a unique opportunity for interdisciplinary collaboration between the disciplines of audiology and pharmacy. The objectives for this programme are therefore to facilitate learning and to provide a service to the local community by identifying, preventing and monitoring medicine-induced hearing loss in in-hospital and out-patients; as well as to establish inter-disciplinary collaboration between the disciplines and stakeholders for more effective service delivery. The constant interdisciplinary teamwork between the audiologist, pharmacist, physician and nursing staff in the wards results in best practice and management of patients with ototoxic damage.
Learning about hydrothermal volcanic activity by modeling induced geophysical changes
Currenti, Gilda M.; Napoli, Rosalba
2017-05-01
state-of-the-art instruments. Devising multidisciplinary and easy-to-use computational experiments enable us to learn how the hydrothermal system responds to un unrest and which fingerprints it may leave in the geophysical signals.
Indian Academy of Sciences (India)
We also describe discrete-time systems in terms of difference ... A more modern alternative, especially for larger systems, is to convert ... In other words, ..... picture?) State-variable equations are also called state-space equations because the ...
Discrete Lorentzian quantum gravity
Loll, R.
2000-01-01
Just as for non-abelian gauge theories at strong coupling, discrete lattice methods are a natural tool in the study of non-perturbative quantum gravity. They have to reflect the fact that the geometric degrees of freedom are dynamical, and that therefore also the lattice theory must be formulated
Sharp, Karen Tobey
This paper cites information received from a number of sources, e.g., mathematics teachers in two-year colleges, publishers, and convention speakers, about the nature of discrete mathematics and about what topics a course in this subject should contain. Note is taken of the book edited by Ralston and Young which discusses the future of college…
Learning about Hydrothermal Volcanic Activity by Modeling Induced Geophysical Changes
Directory of Open Access Journals (Sweden)
Gilda M. Currenti
2017-05-01
the modern state-of-the-art instruments, could be traced by continuously running multi-parametric monitoring networks. Devising multidisciplinary and easy-to-use computational experiments enable us to learn how the hydrothermal system responds to unrest and which fingerprints it may leave in the geophysical signals.
THE ROLE OF TASK-INDUCED INVOLVEMENT IN VOCABULARY LEARNING OF IRANIAN LANGUAGE LEARNERS
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Fatemeh Khonamri
2013-01-01
Full Text Available This study investigated Laufer and Hustijn’s (2001 Involvement Load Hypothesis in vocabulary learning. It comprised two experiments. Experiment 1 examined whether two tasks with equal involvement load but different distribution of components would yield the same result in initial learning and retention of target words. Experiment 2 investigated whether two tasks, one input and another output, with equal involvement load and the same distribution of components would result in equivalent initial learning and retention of target words. 126 advanced English learners completed one of three vocabulary learning tasks that equated in the amount of involvement they induced: sentence writing, fill-in, and translation (L2-L1. Receptive knowledge of the target words was assessed immediately after treatment and two weeks later, and one month interval after the first delayed posttest. The result of t-test for Experiment 1 showed that when two tasks had equal involvement load but different distribution of components they resulted in similar amounts of initial learning and retention of new words. The findings of Experiment 2 indicated when two tasks, one input and another output, had equal involvement load and the same distribution of components, they led to superiority of fill-in task over translation task in initial vocabulary learning, however, not in retention of new words.
Discrete Feature Model (DFM) User Documentation
International Nuclear Information System (INIS)
Geier, Joel
2008-06-01
This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this software, the
Discrete Feature Model (DFM) User Documentation
Energy Technology Data Exchange (ETDEWEB)
Geier, Joel (Clearwater Hardrock Consulting, Corvallis, OR (United States))
2008-06-15
This manual describes the Discrete-Feature Model (DFM) software package for modelling groundwater flow and solute transport in networks of discrete features. A discrete-feature conceptual model represents fractures and other water-conducting features around a repository as discrete conductors surrounded by a rock matrix which is usually treated as impermeable. This approximation may be valid for crystalline rocks such as granite or basalt, which have very low permeability if macroscopic fractures are excluded. A discrete feature is any entity that can conduct water and permit solute transport through bedrock, and can be reasonably represented as a piecewise-planar conductor. Examples of such entities may include individual natural fractures (joints or faults), fracture zones, and disturbed-zone features around tunnels (e.g. blasting-induced fractures or stress-concentration induced 'onion skin' fractures around underground openings). In a more abstract sense, the effectively discontinuous nature of pathways through fractured crystalline bedrock may be idealized as discrete, equivalent transmissive features that reproduce large-scale observations, even if the details of connective paths (and unconnected domains) are not precisely known. A discrete-feature model explicitly represents the fundamentally discontinuous and irregularly connected nature of systems of such systems, by constraining flow and transport to occur only within such features and their intersections. Pathways for flow and solute transport in this conceptualization are a consequence not just of the boundary conditions and hydrologic properties (as with continuum models), but also the irregularity of connections between conductive/transmissive features. The DFM software package described here is an extensible code for investigating problems of flow and transport in geological (natural or human-altered) systems that can be characterized effectively in terms of discrete features. With this
Machine learning-based prediction of adverse drug effects: An example of seizure-inducing compounds
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Mengxuan Gao
2017-02-01
Full Text Available Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machine learning-based in vitro system designed to detect seizure-inducing side effects. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices, while 14 drugs were bath-perfused at 5 different concentrations each. For each experimental condition, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning. In the space of the first two principal components, the support vector machine completely separated the vectors (i.e., doses of individual drugs that induced seizure-like events and identified diphenhydramine, enoxacin, strychnine and theophylline as “seizure-inducing” drugs, which indeed were reported to induce seizures in clinical situations. Thus, this artificial intelligence-based classification may provide a new platform to detect the seizure-inducing side effects of preclinical drugs.
Discrete Exterior Calculus Discretization of Incompressible Navier-Stokes Equations
Mohamed, Mamdouh S.; Hirani, Anil N.; Samtaney, Ravi
2017-01-01
A conservative discretization of incompressible Navier-Stokes equations over surface simplicial meshes is developed using discrete exterior calculus (DEC). Numerical experiments for flows over surfaces reveal a second order accuracy
Discrete mKdV and discrete sine-Gordon flows on discrete space curves
International Nuclear Information System (INIS)
Inoguchi, Jun-ichi; Kajiwara, Kenji; Matsuura, Nozomu; Ohta, Yasuhiro
2014-01-01
In this paper, we consider the discrete deformation of the discrete space curves with constant torsion described by the discrete mKdV or the discrete sine-Gordon equations, and show that it is formulated as the torsion-preserving equidistant deformation on the osculating plane which satisfies the isoperimetric condition. The curve is reconstructed from the deformation data by using the Sym–Tafel formula. The isoperimetric equidistant deformation of the space curves does not preserve the torsion in general. However, it is possible to construct the torsion-preserving deformation by tuning the deformation parameters. Further, it is also possible to make an arbitrary choice of the deformation described by the discrete mKdV equation or by the discrete sine-Gordon equation at each step. We finally show that the discrete deformation of discrete space curves yields the discrete K-surfaces. (paper)
Visual Learning Induces Changes in Resting-State fMRI Multivariate Pattern of Information.
Guidotti, Roberto; Del Gratta, Cosimo; Baldassarre, Antonello; Romani, Gian Luca; Corbetta, Maurizio
2015-07-08
When measured with functional magnetic resonance imaging (fMRI) in the resting state (R-fMRI), spontaneous activity is correlated between brain regions that are anatomically and functionally related. Learning and/or task performance can induce modulation of the resting synchronization between brain regions. Moreover, at the neuronal level spontaneous brain activity can replay patterns evoked by a previously presented stimulus. Here we test whether visual learning/task performance can induce a change in the patterns of coded information in R-fMRI signals consistent with a role of spontaneous activity in representing task-relevant information. Human subjects underwent R-fMRI before and after perceptual learning on a novel visual shape orientation discrimination task. Task-evoked fMRI patterns to trained versus novel stimuli were recorded after learning was completed, and before the second R-fMRI session. Using multivariate pattern analysis on task-evoked signals, we found patterns in several cortical regions, as follows: visual cortex, V3/V3A/V7; within the default mode network, precuneus, and inferior parietal lobule; and, within the dorsal attention network, intraparietal sulcus, which discriminated between trained and novel visual stimuli. The accuracy of classification was strongly correlated with behavioral performance. Next, we measured multivariate patterns in R-fMRI signals before and after learning. The frequency and similarity of resting states representing the task/visual stimuli states increased post-learning in the same cortical regions recruited by the task. These findings support a representational role of spontaneous brain activity. Copyright © 2015 the authors 0270-6474/15/359786-13$15.00/0.
Zhao, Shan-shan; Yang, Wei-na; Jin, Hui; Ma, Kai-ge; Feng, Gai-feng
2015-12-01
Puerarin (PUE), an isoflavone purified from the root of Pueraria lobata (Chinese herb), has been reported to attenuate learning and memory impairments in the transgenic mouse model of Alzheimer's disease (AD). In the present study, we tested PUE in a sporadic AD (SAD) mouse model which was induced by the intracerebroventricular injection of streptozotocin (STZ). The mice were administrated PUE (25, 50, or 100mg/kg/d) for 28 days. Learning and memory abilities were assessed by the Morris water maze test. After behavioral test, the biochemical parameters of oxidative stress (glutathione peroxidase (GSH-Px), superoxide dismutases (SOD), and malondialdehyde (MDA)) were measured in the cerebral cortex and hippocampus. The SAD mice exhibited significantly decreased learning and memory ability, while PUE attenuated these impairments. The activities of GSH-Px and SOD were decreased while MDA was increased in the SAD animals. After PUE treatment, the activities of GSH-Px and SOD were elevated, and the level of MDA was decreased. The middle dose PUE was more effective than others. These results indicate that PUE attenuates learning and memory impairments and inhibits oxidative stress in STZ-induced SAD mice. PUE may be a promising therapeutic agent for SAD. Copyright © 2015 Elsevier Inc. All rights reserved.
Protective Effect of Vitamin E Against Lead-induced Memory and Learning Impairment in Male Rats
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Salehi
2015-02-01
Full Text Available Background Lead (Pb2+ is a neurotoxin substance that has been known for its adverse effects on central nervous system and memory. Previous studies reported the potential effect of vitamin E as a memory enhancer. Objectives The purpose of the present study was to assess the protective effects of vitamin E against Pb-induced amnesia. Materials and Methods Forty-eight male Wistar rats (200-250 g were divided equally into the saline, Pb, Pb + vitamin E, and vitamin E alone groups. To induce Pb toxicity, rats received water that contained 0.2% Pb instead of regular water for 1 month. Rats pretreated, treated or post treated with vitamin E (150 mg/kg for 2 months. Passive avoidance learning was assessed using Shuttle-Box after two months. Retention was tested 24 and 48 hours after training. Results The results showed that Pb caused impairment in acquisition and retrieval processes in passive avoidance learning. Vitamin E reversed learning and memory deficits in pre, post or co- exposure with Pb (P < 0.001. Conclusions According to the results of this study, administration of vitamin E to rats counteracts the negative effects of Pb on learning and memory. To more precisely extrapolate these findings to humans, future clinical studies are warranted.
Vogel, Susanne; Klumpers, Floris; Schröder, Tobias Navarro; Oplaat, Krista T; Krugers, Harm J; Oitzl, Melly S; Joëls, Marian; Doeller, Christian F; Fernández, Guillén
2017-05-01
Stress is assumed to cause a shift from flexible 'cognitive' memory to more rigid 'habit' memory. In the spatial memory domain, stress impairs place learning depending on the hippocampus whereas stimulus-response learning based on the striatum appears to be improved. While the neural basis of this shift is still unclear, previous evidence in rodents points towards cortisol interacting with the mineralocorticoid receptor (MR) to affect amygdala functioning. The amygdala is in turn assumed to orchestrate the stress-induced shift in memory processing. However, an integrative study testing these mechanisms in humans is lacking. Therefore, we combined functional neuroimaging of a spatial memory task, stress-induction, and administration of an MR-antagonist in a full-factorial, randomized, placebo-controlled between-subjects design in 101 healthy males. We demonstrate that stress-induced increases in cortisol lead to enhanced stimulus-response learning, accompanied by increased amygdala activity and connectivity to the striatum. Importantly, this shift was prevented by an acute administration of the MR-antagonist spironolactone. Our findings support a model in which the MR and the amygdala play an important role in the stress-induced shift towards habit memory systems, revealing a fundamental mechanism of adaptively allocating neural resources that may have implications for stress-related mental disorders.
Effects of visual feedback-induced variability on motor learning of handrim wheelchair propulsion.
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Marika T Leving
Full Text Available It has been suggested that a higher intra-individual variability benefits the motor learning of wheelchair propulsion. The present study evaluated whether feedback-induced variability on wheelchair propulsion technique variables would also enhance the motor learning process. Learning was operationalized as an improvement in mechanical efficiency and propulsion technique, which are thought to be closely related during the learning process.17 Participants received visual feedback-based practice (feedback group and 15 participants received regular practice (natural learning group. Both groups received equal practice dose of 80 min, over 3 weeks, at 0.24 W/kg at a treadmill speed of 1.11 m/s. To compare both groups the pre- and post-test were performed without feedback. The feedback group received real-time visual feedback on seven propulsion variables with instruction to manipulate the presented variable to achieve the highest possible variability (1st 4-min block and optimize it in the prescribed direction (2nd 4-min block. To increase motor exploration the participants were unaware of the exact variable they received feedback on. Energy consumption and the propulsion technique variables with their respective coefficient of variation were calculated to evaluate the amount of intra-individual variability.The feedback group, which practiced with higher intra-individual variability, improved the propulsion technique between pre- and post-test to the same extent as the natural learning group. Mechanical efficiency improved between pre- and post-test in the natural learning group but remained unchanged in the feedback group.These results suggest that feedback-induced variability inhibited the improvement in mechanical efficiency. Moreover, since both groups improved propulsion technique but only the natural learning group improved mechanical efficiency, it can be concluded that the improvement in mechanical efficiency and propulsion technique do not
Discrete and computational geometry
Devadoss, Satyan L
2011-01-01
Discrete geometry is a relatively new development in pure mathematics, while computational geometry is an emerging area in applications-driven computer science. Their intermingling has yielded exciting advances in recent years, yet what has been lacking until now is an undergraduate textbook that bridges the gap between the two. Discrete and Computational Geometry offers a comprehensive yet accessible introduction to this cutting-edge frontier of mathematics and computer science. This book covers traditional topics such as convex hulls, triangulations, and Voronoi diagrams, as well as more recent subjects like pseudotriangulations, curve reconstruction, and locked chains. It also touches on more advanced material, including Dehn invariants, associahedra, quasigeodesics, Morse theory, and the recent resolution of the Poincaré conjecture. Connections to real-world applications are made throughout, and algorithms are presented independently of any programming language. This richly illustrated textbook also fe...
2002-01-01
Discrete geometry investigates combinatorial properties of configurations of geometric objects. To a working mathematician or computer scientist, it offers sophisticated results and techniques of great diversity and it is a foundation for fields such as computational geometry or combinatorial optimization. This book is primarily a textbook introduction to various areas of discrete geometry. In each area, it explains several key results and methods, in an accessible and concrete manner. It also contains more advanced material in separate sections and thus it can serve as a collection of surveys in several narrower subfields. The main topics include: basics on convex sets, convex polytopes, and hyperplane arrangements; combinatorial complexity of geometric configurations; intersection patterns and transversals of convex sets; geometric Ramsey-type results; polyhedral combinatorics and high-dimensional convexity; and lastly, embeddings of finite metric spaces into normed spaces. Jiri Matousek is Professor of Com...
Time Discretization Techniques
Gottlieb, S.
2016-10-12
The time discretization of hyperbolic partial differential equations is typically the evolution of a system of ordinary differential equations obtained by spatial discretization of the original problem. Methods for this time evolution include multistep, multistage, or multiderivative methods, as well as a combination of these approaches. The time step constraint is mainly a result of the absolute stability requirement, as well as additional conditions that mimic physical properties of the solution, such as positivity or total variation stability. These conditions may be required for stability when the solution develops shocks or sharp gradients. This chapter contains a review of some of the methods historically used for the evolution of hyperbolic PDEs, as well as cutting edge methods that are now commonly used.
Czech Academy of Sciences Publication Activity Database
Mesiar, Radko; Li, J.; Pap, E.
2013-01-01
Roč. 54, č. 3 (2013), s. 357-364 ISSN 0888-613X R&D Projects: GA ČR GAP402/11/0378 Institutional support: RVO:67985556 Keywords : concave integral * pseudo-addition * pseudo-multiplication Subject RIV: BA - General Mathematics Impact factor: 1.977, year: 2013 http://library.utia.cas.cz/separaty/2013/E/mesiar-discrete pseudo-integrals.pdf
Discrete variational Hamiltonian mechanics
International Nuclear Information System (INIS)
Lall, S; West, M
2006-01-01
The main contribution of this paper is to present a canonical choice of a Hamiltonian theory corresponding to the theory of discrete Lagrangian mechanics. We make use of Lagrange duality and follow a path parallel to that used for construction of the Pontryagin principle in optimal control theory. We use duality results regarding sensitivity and separability to show the relationship between generating functions and symplectic integrators. We also discuss connections to optimal control theory and numerical algorithms
International Nuclear Information System (INIS)
Jalnapurkar, Sameer M; Leok, Melvin; Marsden, Jerrold E; West, Matthew
2006-01-01
This paper develops the theory of Abelian Routh reduction for discrete mechanical systems and applies it to the variational integration of mechanical systems with Abelian symmetry. The reduction of variational Runge-Kutta discretizations is considered, as well as the extent to which symmetry reduction and discretization commute. These reduced methods allow the direct simulation of dynamical features such as relative equilibria and relative periodic orbits that can be obscured or difficult to identify in the unreduced dynamics. The methods are demonstrated for the dynamics of an Earth orbiting satellite with a non-spherical J 2 correction, as well as the double spherical pendulum. The J 2 problem is interesting because in the unreduced picture, geometric phases inherent in the model and those due to numerical discretization can be hard to distinguish, but this issue does not appear in the reduced algorithm, where one can directly observe interesting dynamical structures in the reduced phase space (the cotangent bundle of shape space), in which the geometric phases have been removed. The main feature of the double spherical pendulum example is that it has a non-trivial magnetic term in its reduced symplectic form. Our method is still efficient as it can directly handle the essential non-canonical nature of the symplectic structure. In contrast, a traditional symplectic method for canonical systems could require repeated coordinate changes if one is evoking Darboux' theorem to transform the symplectic structure into canonical form, thereby incurring additional computational cost. Our method allows one to design reduced symplectic integrators in a natural way, despite the non-canonical nature of the symplectic structure
Discrete structures in F-theory compactifications
Energy Technology Data Exchange (ETDEWEB)
Till, Oskar
2016-05-04
In this thesis we study global properties of F-theory compactifications on elliptically and genus-one fibered Calabi-Yau varieties. This is motivated by phenomenological considerations as well as by the need for a deeper understanding of the set of consistent F-theory vacua. The global geometric features arise from discrete and arithmetic structures in the torus fiber and can be studied in detail for fibrations over generic bases. In the case of elliptic fibrations we study the role of the torsion subgroup of the Mordell-Weil group of sections in four dimensional compactifications. We show how the existence of a torsional section restricts the admissible matter representations in the theory. This is shown to be equivalent to inducing a non-trivial fundamental group of the gauge group. Compactifying F-theory on genus-one fibrations with multisections gives rise to discrete selection rules. In field theory the discrete symmetry is a broken U(1) symmetry. In the geometry the higgsing corresponds to a conifold transition. We explain in detail the origin of the discrete symmetry from two different M-theory phases and put the result into the context of torsion homology. Finally we systematically construct consistent gauge fluxes on genus-one fibrations and show that these induce an anomaly free chiral spectrum.
Directory of Open Access Journals (Sweden)
ELISABETTA eMONFARDINI
2012-09-01
Full Text Available Much theoretical attention is currently devoted to social learning. Yet, empirical studies formally comparing its effectiveness relative to individual learning are rare. Here, we focus on free choice, which is at the heart of individual reward-based learning, but absent in social learning. Choosing among two equally valued options is known to create a preference for the selected option in both humans and monkeys. We thus surmised that social learning should be more helpful when choice-induced preferences retard individual learning than when they optimize it. To test this prediction, the same task requiring to find which among two items concealed a reward was applied to rhesus macaques and humans. The initial trial was individual or social, rewarded or unrewarded. Learning was assessed on the second trial. Choice-induced preference strongly affected individual learning. Monkeys and humans performed much more poorly after an initial negative choice than after an initial positive choice. Comparison with social learning verified our prediction. For negative outcome, social learning surpassed or at least equaled individual learning in all subjects. For positive outcome, the predicted superiority of individual learning did occur in a majority of subjects (5/6 monkeys and 6/12 humans. A minority kept learning better socially though, perhaps due to a more dominant/aggressive attitude toward peers. Poor learning from errors due to over-valuation of personal choices is among the decision-making biases shared by humans and animals. The present study suggests that choice-immune social learning may help curbing this potentially harmful tendency. Learning from successes is an easier path. The present data suggest that whether one tends to walk it alone or with a peer's help might depend on the social dynamics within the actor/observer dyad.
Effect of vitamin E on lead exposure-induced learning and memory impairment in rats.
Khodamoradi, Nasrin; Komaki, Alireza; Salehi, Iraj; Shahidi, Siamak; Sarihi, Abdolrahman
2015-05-15
Chronic lead (Pb(2+)) exposure has been associated with learning and memory impairments, whereas vitamin E improves cognitive deficits. In this study, using a passive avoidance learning model in rats, we investigated the effects of vitamin E on Pb(2+) exposure-induced learning and memory impairments in rats. In the present study, 56 Wistar male rats (weighting 230-250g) were divided into eight groups (n=7). The Pb(2+) exposure involved gavages of lead acetate solution using three different doses (0.05%, 0.1%, and 0.2%) and the vitamin E consisted of three different doses (10, 25, 50μg/rat) for 30days. After the 30-day period, the rats were tested using a passive avoidance task (acquisition test). In a retrieval test conducted 48h after the training, step through latency (STL) and time in the dark compartment (TDC) were recorded. The statistical analysis of data was performed using ANOVA followed by Tukey's post hoc analysis. In all cases, differences were considered significant if plearning and the TDC, whereas it decreased the STL in the passive avoidance test. Administration of vitamin E ameliorated the effects of Pb(2+) on animal behavior in the passive avoidance learning and memory task. Our results indicate that impairments of learning and memory in Pb(2+)-exposed rats are dose dependent and can be inhibited by antioxidants such as vitamin E. Copyright © 2015 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Guangxin Yuan
2018-01-01
Full Text Available Our previous research revealed that Cordyceps militaris can improve the learning and memory, and although the main active ingredient should be its polypeptide complexes, the underlying mechanism of its activity remains poorly understood. In this study, we explored the mechanisms by which Cordyceps militaris improves learning and memory in a mouse model. Mice were given scopolamine hydrobromide intraperitoneally to establish a mouse model of learning and memory impairment. The effects of Cordyceps polypeptide in this model were tested using the Morris water maze test; serum superoxide dismutase activity; serum malondialdehyde levels; activities of acetyl cholinesterase, Na+-k+-ATPase, and nitric oxide synthase; and gamma aminobutyric acid and glutamate contents in brain tissue. Moreover, differentially expressed genes and the related cellular signaling pathways were screened using an mRNA expression profile chip. The results showed that the genes Pik3r5, Il-1β, and Slc18a2 were involved in the effects of Cordyceps polypeptide on the nervous system of these mice. Our findings suggest that Cordyceps polypeptide may improve learning and memory in the scopolamine-induced mouse model of learning and memory impairment by scavenging oxygen free radicals, preventing oxidative damage, and protecting the nervous system.
Learning induces the translin/trax RNase complex to express activin receptors for persistent memory.
Park, Alan Jung; Havekes, Robbert; Fu, Xiuping; Hansen, Rolf; Tudor, Jennifer C; Peixoto, Lucia; Li, Zhi; Wu, Yen-Ching; Poplawski, Shane G; Baraban, Jay M; Abel, Ted
2017-09-20
Long-lasting forms of synaptic plasticity and memory require de novo protein synthesis. Yet, how learning triggers this process to form memory is unclear. Translin/trax is a candidate to drive this learning-induced memory mechanism by suppressing microRNA-mediated translational silencing at activated synapses. We find that mice lacking translin/trax display defects in synaptic tagging, which requires protein synthesis at activated synapses, and long-term memory. Hippocampal samples harvested from these mice following learning show increases in several disease-related microRNAs targeting the activin A receptor type 1C (ACVR1C), a component of the transforming growth factor-β receptor superfamily. Furthermore, the absence of translin/trax abolishes synaptic upregulation of ACVR1C protein after learning. Finally, synaptic tagging and long-term memory deficits in mice lacking translin/trax are mimicked by ACVR1C inhibition. Thus, we define a new memory mechanism by which learning reverses microRNA-mediated silencing of the novel plasticity protein ACVR1C via translin/trax.
Discrete port-Hamiltonian systems
Talasila, V.; Clemente-Gallardo, J.; Schaft, A.J. van der
2006-01-01
Either from a control theoretic viewpoint or from an analysis viewpoint it is necessary to convert smooth systems to discrete systems, which can then be implemented on computers for numerical simulations. Discrete models can be obtained either by discretizing a smooth model, or by directly modeling
A paradigm for discrete physics
International Nuclear Information System (INIS)
Noyes, H.P.; McGoveran, D.; Etter, T.; Manthey, M.J.; Gefwert, C.
1987-01-01
An example is outlined for constructing a discrete physics using as a starting point the insight from quantum physics that events are discrete, indivisible and non-local. Initial postulates are finiteness, discreteness, finite computability, absolute nonuniqueness (i.e., homogeneity in the absence of specific cause) and additivity
Two new discrete integrable systems
International Nuclear Information System (INIS)
Chen Xiao-Hong; Zhang Hong-Qing
2013-01-01
In this paper, we focus on the construction of new (1+1)-dimensional discrete integrable systems according to a subalgebra of loop algebra Ã 1 . By designing two new (1+1)-dimensional discrete spectral problems, two new discrete integrable systems are obtained, namely, a 2-field lattice hierarchy and a 3-field lattice hierarchy. When deriving the two new discrete integrable systems, we find the generalized relativistic Toda lattice hierarchy and the generalized modified Toda lattice hierarchy. Moreover, we also obtain the Hamiltonian structures of the two lattice hierarchies by means of the discrete trace identity
Walking patterns induced by learned odors in the honeybee, Apis mellifera L.
Yamashita, Toshiya; Haupt, S Shuichi; Ikeno, Hidetoshi; Ai, Hiroyuki
2016-01-01
The odor localization strategy induced by odors learned via differential conditioning of the proboscis extension response was investigated in honeybees. In response to reward-associated but not non-reward-associated odors, learners walked longer paths than non-learners and control bees. When orange odor reward association was learned, the path length and the body turn angles were small during odor stimulation and greatly increased after stimulation ceased. In response to orange odor, bees walked locally with alternate left and right turns during odor stimulation to search for the reward-associated odor source. After odor stimulation, bees walked long paths with large turn angles to explore the odor plume. For clove odor, learning-related modulations of locomotion were less pronounced, presumably due to a spontaneous preference for orange in the tested population of bees. This study is the first to describe how an odor-reward association modulates odor-induced walking in bees. © 2016. Published by The Company of Biologists Ltd.
Postretrieval new learning does not reliably induce human memory updating via reconsolidation.
Hardwicke, Tom E; Taqi, Mahdi; Shanks, David R
2016-05-10
Reconsolidation theory proposes that retrieval can destabilize an existing memory trace, opening a time-dependent window during which that trace is amenable to modification. Support for the theory is largely drawn from nonhuman animal studies that use invasive pharmacological or electroconvulsive interventions to disrupt a putative postretrieval restabilization ("reconsolidation") process. In human reconsolidation studies, however, it is often claimed that postretrieval new learning can be used as a means of "updating" or "rewriting" existing memory traces. This proposal warrants close scrutiny because the ability to modify information stored in the memory system has profound theoretical, clinical, and ethical implications. The present study aimed to replicate and extend a prominent 3-day motor-sequence learning study [Walker MP, Brakefield T, Hobson JA, Stickgold R (2003) Nature 425(6958):616-620] that is widely cited as a convincing demonstration of human reconsolidation. However, in four direct replication attempts (n = 64), we did not observe the critical impairment effect that has previously been taken to indicate disruption of an existing motor memory trace. In three additional conceptual replications (n = 48), we explored the broader validity of reconsolidation-updating theory by using a declarative recall task and sequences similar to phone numbers or computer passwords. Rather than inducing vulnerability to interference, memory retrieval appeared to aid the preservation of existing sequence knowledge relative to a no-retrieval control group. These findings suggest that memory retrieval followed by new learning does not reliably induce human memory updating via reconsolidation.
Hirsch, M; Peinado, E; Valle, J W F
2010-01-01
We propose a new motivation for the stability of dark matter (DM). We suggest that the same non-abelian discrete flavor symmetry which accounts for the observed pattern of neutrino oscillations, spontaneously breaks to a Z2 subgroup which renders DM stable. The simplest scheme leads to a scalar doublet DM potentially detectable in nuclear recoil experiments, inverse neutrino mass hierarchy, hence a neutrinoless double beta decay rate accessible to upcoming searches, while reactor angle equal to zero gives no CP violation in neutrino oscillations.
Wuensche, Andrew
DDLab is interactive graphics software for creating, visualizing, and analyzing many aspects of Cellular Automata, Random Boolean Networks, and Discrete Dynamical Networks in general and studying their behavior, both from the time-series perspective — space-time patterns, and from the state-space perspective — attractor basins. DDLab is relevant to research, applications, and education in the fields of complexity, self-organization, emergent phenomena, chaos, collision-based computing, neural networks, content addressable memory, genetic regulatory networks, dynamical encryption, generative art and music, and the study of the abstract mathematical/physical/dynamical phenomena in their own right.
Isorhynchophylline improves learning and memory impairments induced by D-galactose in mice.
Xian, Yan-Fang; Su, Zi-Ren; Chen, Jian-Nan; Lai, Xiao-Ping; Mao, Qing-Qiu; Cheng, Christopher H K; Ip, Siu-Po; Lin, Zhi-Xiu
2014-10-01
Isorhynchophylline (IRN), an alkaloid isolated from Uncaria rhynchophylla, has been reported to improve cognitive impairment induced by beta-amyloid in rats. However, whether IRN could also ameliorate the D-galactose (D-gal)-induced mouse memory deficits is still not clear. In the present study, we aimed to investigate whether IRN had potential protective effect against the D-gal-induced cognitive deficits in mice. Mice were given a subcutaneous injection of D-gal (100mg/kg) and orally administered IRN (20 or 40mg/kg) daily for 8weeks, followed by assessing spatial learning and memory function by the Morris water maze test. The results showed that IRN significantly improved spatial learning and memory function in the D-gal-treated mice. In the mechanistic studies, IRN significantly increased the level of glutathione (GSH) and the activities of superoxide dismutase (SOD) and catalase (CAT), while decreased the level of malondialdehyde (MDA) in the brain tissues of the D-gal-treated mice. Moreover, IRN (20 or 40mg/kg) significantly inhibited the production of prostaglandin E 2 (PGE2) and nitric oxide (NO), and the mRNA expression of cyclooxygenase-2 (COX-2) and inducible nitric oxide synthase (iNOS), as well as the activation of nuclear factor kappa B (NF-κB) in the brain tissues of D-gal-treated mice. Our results amply demonstrated that IRN was able to ameliorate cognitive deficits induced by D-gal in mice, and the observed cognition-improving action may be mediated, at least in part, through enhancing the antioxidant status and anti-inflammatory effect of brain tissues via NFκB signaling. Copyright © 2014 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Singletary Keith W
2010-01-01
Full Text Available Abstract Breast cancer is the most prevalent cancer in American women. Dietary factors are thought to have a strong influence on breast cancer incidence. This study utilized a meal-feeding protocol with female Sprague-Dawley rats to evaluate effects of two ratios of carbohydrate:protein on promotion and early progression of breast tissue carcinomas. Mammary tumors were induced by N-methyl-N-nitrosourea (MNU at 52 d of age. Post-induction, animals were assigned to consume either a low protein high carbohydrate diet (LPHC; 15% and 60% of energy, respectively or a high protein moderate carbohydrate diet (HPMC; 35% and 40% of energy, respectively for 10 wk. Animals were fed 3 meals/day to mimic human absorption and metabolism patterns. The rate of palpable tumor incidence was reduced in HPMC relative to LPHC (12.9 ± 1.4%/wk vs. 18.2 ± 1.3%/wk. At 3 wk, post-prandial serum insulin was larger in the LPHC relative to HPMC (+136.4 ± 33.1 pmol/L vs. +38.1 ± 23.4 pmol/L, while at 10 wk there was a trend for post-prandial IGF-I to be increased in HPMC (P = 0.055. There were no differences in tumor latency, tumor surface area, or cumulative tumor mass between diet groups. The present study provides evidence that reducing the dietary carbohydrate:protein ratio attenuates the development of mammary tumors. These findings are consistent with reduced post-prandial insulin release potentially diminishing the proliferative environment required for breast cancer tumors to progress.
Neurotoxicity induced by alkyl nitrites: Impairment in learning/memory and motor coordination.
Cha, Hye Jin; Kim, Yun Ji; Jeon, Seo Young; Kim, Young-Hoon; Shin, Jisoon; Yun, Jaesuk; Han, Kyoungmoon; Park, Hye-Kyung; Kim, Hyung Soo
2016-04-21
Although alkyl nitrites are used as recreational drugs, there is only little research data regarding their effects on the central nervous system including their neurotoxicity. This study investigated the neurotoxicity of three representative alkyl nitrites (isobutyl nitrite, isoamyl nitrite, and butyl nitrite), and whether it affected learning/memory function and motor coordination in rodents. Morris water maze test was performed in mice after administrating the mice with varying doses of the substances in two different injection schedules of memory acquisition and memory retention. A rota-rod test was then performed in rats. All tested alkyl nitrites lowered the rodents' capacity for learning and memory, as assessed by both the acquisition and retention tests. The results of the rota-rod test showed that isobutyl nitrite in particular impaired motor coordination in chronically treated rats. The mice chronically injected with isoamyl nitrite also showed impaired function, while butyl nitrite had no significant effect. The results of the water maze test suggest that alkyl nitrites may impair learning and memory. Additionally, isoamyl nitrite affected the rodents' motor coordination ability. Collectively, our findings suggest that alkyl nitrites may induce neurotoxicity, especially on the aspect of learning and memory function. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Iuculano, Teresa; Rosenberg-Lee, Miriam; Richardson, Jennifer; Tenison, Caitlin; Fuchs, Lynn; Supekar, Kaustubh; Menon, Vinod
2015-09-30
Competency with numbers is essential in today's society; yet, up to 20% of children exhibit moderate to severe mathematical learning disabilities (MLD). Behavioural intervention can be effective, but the neurobiological mechanisms underlying successful intervention are unknown. Here we demonstrate that eight weeks of 1:1 cognitive tutoring not only remediates poor performance in children with MLD, but also induces widespread changes in brain activity. Neuroplasticity manifests as normalization of aberrant functional responses in a distributed network of parietal, prefrontal and ventral temporal-occipital areas that support successful numerical problem solving, and is correlated with performance gains. Remarkably, machine learning algorithms show that brain activity patterns in children with MLD are significantly discriminable from neurotypical peers before, but not after, tutoring, suggesting that behavioural gains are not due to compensatory mechanisms. Our study identifies functional brain mechanisms underlying effective intervention in children with MLD and provides novel metrics for assessing response to intervention.
Technology-Induced Errors and Adverse Event Reporting in an Organizational Learning Perspective.
Vinther, Line Dausel; Jensen, Christian Møller; Hjelmager, Ditte Meulengracht; Lyhne, Nicoline; Nøhr, Christian
2017-01-01
This paper addresses the possibilities of evaluating technology-induced errors, through the utilization of experiences of the Danish adverse event reporting system. The learning loop in the adverse event reporting system is identified and analyzed, to examine which elements can be utilized to evaluate technologies. The empirical data was collected through interviews and a workshop with members of the nursing staff at a nursing home in Aalborg, Denmark. It was found that, the establishment of sustainable feedback learning loops depends on shared visions in the organization and how creating shared visions requires involvement and participation. Secondly, care workers must possess fundamental knowledge about the technologies available to them. Thirdly comprehensive classification of adverse events should be established to allow for a systematic and goal directed feed-back process.
International Nuclear Information System (INIS)
Souza, Manoelito M. de
1997-01-01
We discuss the physical meaning and the geometric interpretation of implementation in classical field theories. The origin of infinities and other inconsistencies in field theories is traced to fields defined with support on the light cone; a finite and consistent field theory requires a light-cone generator as the field support. Then, we introduce a classical field theory with support on the light cone generators. It results on a description of discrete (point-like) interactions in terms of localized particle-like fields. We find the propagators of these particle-like fields and discuss their physical meaning, properties and consequences. They are conformally invariant, singularity-free, and describing a manifestly covariant (1 + 1)-dimensional dynamics in a (3 = 1) spacetime. Remarkably this conformal symmetry remains even for the propagation of a massive field in four spacetime dimensions. We apply this formalism to Classical electrodynamics and to the General Relativity Theory. The standard formalism with its distributed fields is retrieved in terms of spacetime average of the discrete field. Singularities are the by-products of the averaging process. This new formalism enlighten the meaning and the problem of field theory, and may allow a softer transition to a quantum theory. (author)
Discrete Exterior Calculus Discretization of Incompressible Navier-Stokes Equations
Mohamed, Mamdouh S.
2017-05-23
A conservative discretization of incompressible Navier-Stokes equations over surface simplicial meshes is developed using discrete exterior calculus (DEC). Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy otherwise. The mimetic character of many of the DEC operators provides exact conservation of both mass and vorticity, in addition to superior kinetic energy conservation. The employment of barycentric Hodge star allows the discretization to admit arbitrary simplicial meshes. The discretization scheme is presented along with various numerical test cases demonstrating its main characteristics.
Directory of Open Access Journals (Sweden)
Maximiliano Rapanelli
Full Text Available Circuit modification associated with learning and memory involves multiple events, including the addition and remotion of newborn cells trough adulthood. Adult neurogenesis and gliogenesis were mainly described in models of voluntary exercise, enriched environments, spatial learning and memory task; nevertheless, it is unknown whether it is a common mechanism among different learning paradigms, like reward dependent tasks. Therefore, we evaluated cell proliferation, neurogenesis, astrogliogenesis, survival and neuronal maturation in the medial prefrontal cortex (mPFC and the hippocampus (HIPP during learning an operant conditioning task. This was performed by using endogenous markers of cell proliferation, and a bromodeoxiuridine (BrdU injection schedule in two different phases of learning. Learning an operant conditioning is divided in two phases: a first phase when animals were considered incompletely trained (IT, animals that were learning the task when they performed between 50% and 65% of the responses, and a second phase when animals were considered trained (Tr, animals that completely learned the task when they reached 100% of the responses with a latency time lower than 5 seconds. We found that learning an operant conditioning task promoted cell proliferation in both phases of learning in the mPFC and HIPP. Additionally, the results presented showed that astrogliogenesis was induced in the medial prefrontal cortex (mPFC in both phases, however, the first phase promoted survival of these new born astrocytes. On the other hand, an increased number of new born immature neurons was observed in the HIPP only in the first phase of learning, whereas, decreased values were observed in the second phase. Finally, we found that neuronal maturation was induced only during the first phase. This study shows for the first time that learning a reward-dependent task, like the operant conditioning, promotes neurogenesis, astrogliogenesis, survival and
Advances in discrete differential geometry
2016-01-01
This is one of the first books on a newly emerging field of discrete differential geometry and an excellent way to access this exciting area. It surveys the fascinating connections between discrete models in differential geometry and complex analysis, integrable systems and applications in computer graphics. The authors take a closer look at discrete models in differential geometry and dynamical systems. Their curves are polygonal, surfaces are made from triangles and quadrilaterals, and time is discrete. Nevertheless, the difference between the corresponding smooth curves, surfaces and classical dynamical systems with continuous time can hardly be seen. This is the paradigm of structure-preserving discretizations. Current advances in this field are stimulated to a large extent by its relevance for computer graphics and mathematical physics. This book is written by specialists working together on a common research project. It is about differential geometry and dynamical systems, smooth and discrete theories, ...
Poisson hierarchy of discrete strings
International Nuclear Information System (INIS)
Ioannidou, Theodora; Niemi, Antti J.
2016-01-01
The Poisson geometry of a discrete string in three dimensional Euclidean space is investigated. For this the Frenet frames are converted into a spinorial representation, the discrete spinor Frenet equation is interpreted in terms of a transfer matrix formalism, and Poisson brackets are introduced in terms of the spinor components. The construction is then generalised, in a self-similar manner, into an infinite hierarchy of Poisson algebras. As an example, the classical Virasoro (Witt) algebra that determines reparametrisation diffeomorphism along a continuous string, is identified as a particular sub-algebra, in the hierarchy of the discrete string Poisson algebra. - Highlights: • Witt (classical Virasoro) algebra is derived in the case of discrete string. • Infinite dimensional hierarchy of Poisson bracket algebras is constructed for discrete strings. • Spinor representation of discrete Frenet equations is developed.
Poisson hierarchy of discrete strings
Energy Technology Data Exchange (ETDEWEB)
Ioannidou, Theodora, E-mail: ti3@auth.gr [Faculty of Civil Engineering, School of Engineering, Aristotle University of Thessaloniki, 54249, Thessaloniki (Greece); Niemi, Antti J., E-mail: Antti.Niemi@physics.uu.se [Department of Physics and Astronomy, Uppsala University, P.O. Box 803, S-75108, Uppsala (Sweden); Laboratoire de Mathematiques et Physique Theorique CNRS UMR 6083, Fédération Denis Poisson, Université de Tours, Parc de Grandmont, F37200, Tours (France); Department of Physics, Beijing Institute of Technology, Haidian District, Beijing 100081 (China)
2016-01-28
The Poisson geometry of a discrete string in three dimensional Euclidean space is investigated. For this the Frenet frames are converted into a spinorial representation, the discrete spinor Frenet equation is interpreted in terms of a transfer matrix formalism, and Poisson brackets are introduced in terms of the spinor components. The construction is then generalised, in a self-similar manner, into an infinite hierarchy of Poisson algebras. As an example, the classical Virasoro (Witt) algebra that determines reparametrisation diffeomorphism along a continuous string, is identified as a particular sub-algebra, in the hierarchy of the discrete string Poisson algebra. - Highlights: • Witt (classical Virasoro) algebra is derived in the case of discrete string. • Infinite dimensional hierarchy of Poisson bracket algebras is constructed for discrete strings. • Spinor representation of discrete Frenet equations is developed.
López-Alonso, Virginia; Cheeran, Binith; Fernández-del-Olmo, Miguel
2015-01-01
Cortical plasticity plays a key role in motor learning (ML). Non-invasive brain stimulation (NIBS) paradigms have been used to modulate plasticity in the human motor cortex in order to facilitate ML. However, little is known about the relationship between NIBS-induced plasticity over M1 and ML capacity. NIBS-induced MEP changes are related to ML capacity. 56 subjects participated in three NIBS (paired associative stimulation, anodal transcranial direct current stimulation and intermittent theta-burst stimulation), and in three lab-based ML task (serial reaction time, visuomotor adaptation and sequential visual isometric pinch task) sessions. After clustering the patterns of response to the different NIBS protocols, we compared the ML variables between the different patterns found. We used regression analysis to explore further the relationship between ML capacity and summary measures of the MEPs change. We ran correlations with the "responders" group only. We found no differences in ML variables between clusters. Greater response to NIBS protocols may be predictive of poor performance within certain blocks of the VAT. "Responders" to AtDCS and to iTBS showed significantly faster reaction times than "non-responders." However, the physiological significance of these results is uncertain. MEP changes induced in M1 by PAS, AtDCS and iTBS appear to have little, if any, association with the ML capacity tested with the SRTT, the VAT and the SVIPT. However, cortical excitability changes induced in M1 by AtDCS and iTBS may be related to reaction time and retention of newly acquired skills in certain motor learning tasks. Copyright © 2015 Elsevier Inc. All rights reserved.
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
Objective: To examine the protective effect of Ginkgo biloba leaf extract (GbE) on learning and memory deficit induced by aluminum chloride (AlCl3), and explore its mechanisms. Methods: The rat models with learning and memory deficit were induced by administering via gastrogavage and drinking of AlCl3 solution. And the model rats were treated with GbE at the dose of 50, 100, 200 mg/kg every day for 2months accompanied with drinking of AlCl3 solution, respectively. Their abilities of spatial learning and memory were tested by Morris water maze, and the acetylcholinesterase (AChE) activity in serum was assayed with chemical method, the AChE expression in hippocampus was observed by immunohistochemistry assay,and then quantitative analysis was done by BI 2000 image analysis system. Results: Learning and memory deficit of rats could be induced by AlCl3 solution (P＜0.01), and AChE expressions in rats hippocampus were increased (P＜0.01); GbE ameliorated learning and memory deficit and reduced AChE expression in rats hippocampus in a dose-dependent manner, while GbE significantly increased serum AChE activity at the dose of 200 mg/kg each day (P＜0.05). Conclusion: GbE can ameliorate learning and memory deficit induced by AlCl3, which may be due to its inhibition of the AChE expression in hippocampus.
Principles of discrete time mechanics
Jaroszkiewicz, George
2014-01-01
Could time be discrete on some unimaginably small scale? Exploring the idea in depth, this unique introduction to discrete time mechanics systematically builds the theory up from scratch, beginning with the historical, physical and mathematical background to the chronon hypothesis. Covering classical and quantum discrete time mechanics, this book presents all the tools needed to formulate and develop applications of discrete time mechanics in a number of areas, including spreadsheet mechanics, classical and quantum register mechanics, and classical and quantum mechanics and field theories. A consistent emphasis on contextuality and the observer-system relationship is maintained throughout.
Dark discrete gauge symmetries
International Nuclear Information System (INIS)
Batell, Brian
2011-01-01
We investigate scenarios in which dark matter is stabilized by an Abelian Z N discrete gauge symmetry. Models are surveyed according to symmetries and matter content. Multicomponent dark matter arises when N is not prime and Z N contains one or more subgroups. The dark sector interacts with the visible sector through the renormalizable kinetic mixing and Higgs portal operators, and we highlight the basic phenomenology in these scenarios. In particular, multiple species of dark matter can lead to an unconventional nuclear recoil spectrum in direct detection experiments, while the presence of new light states in the dark sector can dramatically affect the decays of the Higgs at the Tevatron and LHC, thus providing a window into the gauge origin of the stability of dark matter.
International Nuclear Information System (INIS)
Noyes, H.P.; Starson, S.
1991-03-01
Discrete physics, because it replaces time evolution generated by the energy operator with a global bit-string generator (program universe) and replaces ''fields'' with the relativistic Wheeler-Feynman ''action at a distance,'' allows the consistent formulation of the concept of signed gravitational charge for massive particles. The resulting prediction made by this version of the theory is that free anti-particles near the surface of the earth will ''fall'' up with the same acceleration that the corresponding particles fall down. So far as we can see, no current experimental information is in conflict with this prediction of our theory. The experiment crusis will be one of the anti-proton or anti-hydrogen experiments at CERN. Our prediction should be much easier to test than the small effects which those experiments are currently designed to detect or bound. 23 refs
Wang, Xue; Casadio, Maura; Weber, Kenneth A; Mussa-Ivaldi, Ferdinando A; Parrish, Todd B
2014-03-01
The purpose of this study is to identify white matter microstructure changes following bilateral upper extremity motor skill training to increase our understanding of learning-induced structural plasticity and enhance clinical strategies in physical rehabilitation. Eleven healthy subjects performed two visuo-spatial motor training tasks over 9 sessions (2-3 sessions per week). Subjects controlled a cursor with bilateral simultaneous movements of the shoulders and upper arms using a body machine interface. Before the start and within 2days of the completion of training, whole brain diffusion tensor MR imaging data were acquired. Motor training increased fractional anisotropy (FA) values in the posterior and anterior limbs of the internal capsule, the corona radiata, and the body of the corpus callosum by 4.19% on average indicating white matter microstructure changes induced by activity-dependent modulation of axon number, axon diameter, or myelin thickness. These changes may underlie the functional reorganization associated with motor skill learning. Copyright © 2013 Elsevier Inc. All rights reserved.
Hyperoside protects against chronic mild stress-induced learning and memory deficits.
Gong, Yeli; Yang, Youhua; Chen, Xiaoqing; Yang, Min; Huang, Dan; Yang, Rong; Zhou, Lianying; Li, Changlei; Xiong, Qiuju; Xiong, Zhe
2017-07-01
Hyperoside (quercetin-3-O-b-d-galactosidepyranose) is a plant-derived flavonoid mainly found in fruits, fruit juices (most notably flavanols, flavanones, and anthocyanins) and Chinese traditional medicines. It has been applied to relieve pain and improve cardiovascular functions in clinic. However, the effects of hyperoside on cognitive impairment induced by chronic stress and the underlying molecular mechanisms remain unclear. In the current study, we used chronic mild stress (CMS) rats to investigate the effects of hyperoside on learning and memory and further explore the possible mechanisms. Our results demonstrated that hyperoside reduced the escape latency and the swimming distance of CMS rats in Morris water maze test and reversed depressive symptoms in forced swim test (FST) and sucrose preference test. In addition, hyperoside increased the expression of brain-derived neurotrophic factor (BDNF) in hippocampus of CMS rats without influencing the corticosterone (CORT) level in blood plasma. Furthermore, K252a, an inhibitor of the BDNF receptor TrkB, prevented the protective effects of hyperoside on learning and memory in CMS rats. Taken together, these results indicate that hyperoside reverses the cognitive impairment induced by CMS, which is associated with the regulation of BDNF signaling pathway. Copyright © 2017 Elsevier Masson SAS. All rights reserved.
Directory of Open Access Journals (Sweden)
K. Richard eRidderinkhof
2012-06-01
Full Text Available Reward-based decision-learning refers to the process of learning to select those actions that lead to rewards while avoiding actions that lead to punishments. This process, known to rely on dopaminergic activity in striatal brain regions, is compromised in Parkinson’s disease (PD. We hypothesized that such decision-learning deficits are alleviated by induced positive affect, which is thought to incur transient boosts in midbrain and striatal dopaminergic activity. Computational measures of probabilistic reward-based decision-learning were determined for 51 patients diagnosed with PD. Previous work has shown these measures to rely on the nucleus caudatus (outcome evaluation during the early phases of learning and the putamen (reward prediction during later phases of learning. We observed that induced positive affect facilitated learning, through its effects on reward prediction rather than outcome evaluation. Viewing a few minutes of comedy clips served to remedy dopamine-related problems in putamen-based frontostriatal circuitry and, consequently, in learning to predict which actions will yield reward.
Finite Volumes Discretization of Topology Optimization Problems
DEFF Research Database (Denmark)
Evgrafov, Anton; Gregersen, Misha Marie; Sørensen, Mads Peter
, FVMs represent a standard method of discretization within engineering communities dealing with computational uid dy- namics, transport, and convection-reaction problems. Among various avours of FVMs, cell based approaches, where all variables are associated only with cell centers, are particularly...... computations is done using nite element methods (FEMs). Despite some limited recent eorts [1, 2], we have only started to develop our understanding of the interplay between the control in the coecients and FVMs. Recent advances in discrete functional analysis allow us to analyze convergence of FVM...... of the induced parametrization of the design space that allows optimization algorithms to eciently explore it, and the ease of integration with existing computational codes in a variety of application areas, the simplicity and eciency of sensitivity analyses|all stemming from the use of the same grid throughout...
Directory of Open Access Journals (Sweden)
Samaneh Ghanei Nasab
2017-06-01
Full Text Available Introduction: It has been shown that three new synthetic coumarins-3-carboxamides including 3-fluorobenzilchloride, 4-fluorobenzilchloride and 2-hidroxy-3 metoxybenzaldehyde, have acetylcholinesterase inhibitory activity. This study was performed to estimate ameliorating effect of these new coumarin-3-carboxamides on memory impairments induced by scopolamine (1 mg/kg, induced prolongation in mice. Methods: 30 male mice were divided into five groups, 6 mice in each group. Three experiment groups received coumarins-3- carboxamides (10 mg/kg body weight 30 min before scopalamin injection and two other groups considered as normal (saline-treated groups and finally one negative control (scopalamin only group. The experiment groups were treated with coumarins of 3-fluorobenzilchloride, 4-fluorobenzilchloride and 2-hidroxy-3 metoxybenzaldehyde. The passive avoidance test was performed in an automatic conventional shuttle box set-up. The stepped down latency and number of errors was recorded. Results: With reference to saline-treated group, scopolamine-treated mice demonstrated impairment of learning and memory as a reduction of latency and an increased numbers of errors in step-down testp < 0.01. Treated mice receiving these coumarins at the dose of 10 mg/kg showed an increase in the number of avoidances on the memory tests compared to the scopolamine group (p < 0.01. Conclusion: The study has demonstrated some therapeutic effects of coumarin-3-carboxamides on learning and memory deficit induced by scopolamine. Further investigation is needed to explore whether coumarin-3-carboxamides could be beneficial for memory impairment in Alzheimer’s disease in which cholinergic deficit is one of the hallmarks.
Institute of Scientific and Technical Information of China (English)
Yan-Jiong Chen; Teng Chen; Yan-Ling Liu; Qing Zhong; Yan-Fang Yu; Hong-Liang Su; Haroldo A.Toque; Yong-Hui Dang; Feng Chen; Ming Xu
2012-01-01
[Objective] The purpose of this study was to investigate the effect of methamphetamine (MA) on spatial learning and memory and the role of tetrahydropalmatine (THP) in MA-induced changes in these phenomena in mice.[Methods]Male C57BL/6 mice were randomly divided into eight groups,according to different doses of MA,different doses of THP,treatment with both MA and THP,and saline controls.Spatial learning and memory were assessed using the Morris water maze.Western blot was used to detect the expression of extracellular signal-regulated protein kinase (ERK) in the mouse prefrontal cortex (PFC) and hippocampus.[Results] Repeated MA treatment significantly increased the escape latency in the learning phase and decreased the number of platform site crossings in the memory-test phase.ERK1/2 expression was decreased in the PFC but not in the hippocampus of the MA-treated mice.Repeated THP treatment alone did not affect the escape latency,the number of platform site crossings or the total ERK1/2 expression in the brain.Statistically significantly shorter escape latencies and more platform site crossings occurred in MA+THP-trcatcd mice than in MA-treated mice.[Conclusion]Repeated MA administration impairs spatial learning and memory in mice,and its co-administration with THP prevents this impairment,which is probably attributable to changed ERK1/2 expression in the PFC.This study contributes to uncovering the mechanism underlying MA abuse,and to exploring potential therapies.
Sieling, Fred; Bédécarrats, Alexis; Simmers, John; Prinz, Astrid A; Nargeot, Romuald
2014-05-05
Rewarding stimuli in associative learning can transform the irregularly and infrequently generated motor patterns underlying motivated behaviors into output for accelerated and stereotyped repetitive action. This transition to compulsive behavioral expression is associated with modified synaptic and membrane properties of central neurons, but establishing the causal relationships between cellular plasticity and motor adaptation has remained a challenge. We found previously that changes in the intrinsic excitability and electrical synapses of identified neurons in Aplysia's central pattern-generating network for feeding are correlated with a switch to compulsive-like motor output expression induced by in vivo operant conditioning. Here, we used specific computer-simulated ionic currents in vitro to selectively replicate or suppress the membrane and synaptic plasticity resulting from this learning. In naive in vitro preparations, such experimental manipulation of neuronal membrane properties alone increased the frequency but not the regularity of feeding motor output found in preparations from operantly trained animals. On the other hand, changes in synaptic strength alone switched the regularity but not the frequency of feeding output from naive to trained states. However, simultaneously imposed changes in both membrane and synaptic properties reproduced both major aspects of the motor plasticity. Conversely, in preparations from trained animals, experimental suppression of the membrane and synaptic plasticity abolished the increase in frequency and regularity of the learned motor output expression. These data establish direct causality for the contributions of distinct synaptic and nonsynaptic adaptive processes to complementary facets of a compulsive behavior resulting from operant reward learning. Copyright © 2014 Elsevier Ltd. All rights reserved.
Control of Discrete Event Systems
Smedinga, Rein
1989-01-01
Systemen met discrete gebeurtenissen spelen in vele gebieden een rol. In dit proefschrift staat de volgorde van gebeurtenissen centraal en worden tijdsaspecten buiten beschouwing gelaten. In dat geval kunnen systemen met discrete gebeurtenissen goed worden gemodelleerd door gebruik te maken van
Discrete Mathematics and Its Applications
Oxley, Alan
2010-01-01
The article gives ideas that lecturers of undergraduate Discrete Mathematics courses can use in order to make the subject more interesting for students and encourage them to undertake further studies in the subject. It is possible to teach Discrete Mathematics with little or no reference to computing. However, students are more likely to be…
Discrete Mathematics and Curriculum Reform.
Kenney, Margaret J.
1996-01-01
Defines discrete mathematics as the mathematics necessary to effect reasoned decision making in finite situations and explains how its use supports the current view of mathematics education. Discrete mathematics can be used by curriculum developers to improve the curriculum for students of all ages and abilities. (SLD)
Connections on discrete fibre bundles
International Nuclear Information System (INIS)
Manton, N.S.; Cambridge Univ.
1987-01-01
A new approach to gauge fields on a discrete space-time is proposed, in which the fundamental object is a discrete version of a principal fibre bundle. If the bundle is twisted, the gauge fields are topologically non-trivial automatically. (orig.)
Discrete dynamics versus analytic dynamics
DEFF Research Database (Denmark)
Toxværd, Søren
2014-01-01
For discrete classical Molecular dynamics obtained by the “Verlet” algorithm (VA) with the time increment h there exists a shadow Hamiltonian H˜ with energy E˜(h) , for which the discrete particle positions lie on the analytic trajectories for H˜ . Here, we proof that there, independent...... of such an analytic analogy, exists an exact hidden energy invariance E * for VA dynamics. The fact that the discrete VA dynamics has the same invariances as Newtonian dynamics raises the question, which of the formulations that are correct, or alternatively, the most appropriate formulation of classical dynamics....... In this context the relation between the discrete VA dynamics and the (general) discrete dynamics investigated by Lee [Phys. Lett. B122, 217 (1983)] is presented and discussed....
Modern approaches to discrete curvature
Romon, Pascal
2017-01-01
This book provides a valuable glimpse into discrete curvature, a rich new field of research which blends discrete mathematics, differential geometry, probability and computer graphics. It includes a vast collection of ideas and tools which will offer something new to all interested readers. Discrete geometry has arisen as much as a theoretical development as in response to unforeseen challenges coming from applications. Discrete and continuous geometries have turned out to be intimately connected. Discrete curvature is the key concept connecting them through many bridges in numerous fields: metric spaces, Riemannian and Euclidean geometries, geometric measure theory, topology, partial differential equations, calculus of variations, gradient flows, asymptotic analysis, probability, harmonic analysis, graph theory, etc. In spite of its crucial importance both in theoretical mathematics and in applications, up to now, almost no books have provided a coherent outlook on this emerging field.
Moringa oleifera Seed Extract Alleviates Scopolamine-Induced Learning and Memory Impairment in Mice
Directory of Open Access Journals (Sweden)
Juan Zhou
2018-04-01
Full Text Available The extract of Moringa oleifera seeds has been shown to possess various pharmacological properties. In the present study, we assessed the neuropharmacological effects of 70% ethanolic M. oleifera seed extract (MSE on cognitive impairment caused by scopolamine injection in mice using the passive avoidance and Morris water maze (MWM tests. MSE (250 or 500 mg/kg was administered to mice by oral gavage for 7 or 14 days, and cognitive impairment was induced by intraperitoneal injection of scopolamine (4 mg/kg for 1 or 6 days. Mice that received scopolamine alone showed impaired learning and memory retention and considerably decreased cholinergic system reactivity and neurogenesis in the hippocampus. MSE pretreatment significantly ameliorated scopolamine-induced cognitive impairment and enhanced cholinergic system reactivity and neurogenesis in the hippocampus. Additionally, the protein expressions of phosphorylated Akt, ERK1/2, and CREB in the hippocampus were significantly decreased by scopolamine, but these decreases were reversed by MSE treatment. These results suggest that MSE-induced ameliorative cognitive effects are mediated by enhancement of the cholinergic neurotransmission system and neurogenesis via activation of the Akt, ERK1/2, and CREB signaling pathways. These findings suggest that MSE could be a potent neuropharmacological drug against amnesia, and its mechanism might be modulation of cholinergic activity via the Akt, ERK1/2, and CREB signaling pathways.
Beneficial Effect of Leptin on Spatial Learning and Memory in Streptozotocin-Induced Diabetic Rats
Directory of Open Access Journals (Sweden)
Mohsen Ghasemi
2016-02-01
Full Text Available Background: Diabetes mellitus is a chronic disease which may be accompanied by cognitive impairments. The expression of the obesity gene (ob is decreased in insulin-deficient diabetic animals and increased after the administration of insulin or leptin. Plasma leptin levels are reduced in the streptozotocin (STZ-induced diabetic rats. Therefore, the deleterious effects of diabetes on memory may be due to the reduction of leptin. Aims: Investigate the effect of subcutaneous injection of leptin on spatial learning and memory in STZ-induced diabetic rats. Study Design: Animal experimentation. Methods: The rats were divided into three groups: 1- control, 2- diabetic, and 3- diabetic-leptin. Diabetes was induced in groups 2 and 3 by STZ injection (55 mg/kg intraperitoneally (i.p. The animals received leptin (0.1 mg/kg or saline subcutaneously (s.c for 10 days before behavioral studies. Then, they were examined in the Morris water maze over 3 blocks after 3 days of the last injection of leptin. Results: The travelled path length and time spent to reach the platform significantly increased in the diabetic group (p<0.001 and decreased with leptin treatment (p<0.01 & p<0.001 respectively; also, a significant increase in path length and time was observed between the diabetic-leptin group and the diabetic group (p<0.01, p<0.001, respectively in the probe test. Conclusion: Leptin can exert positive effects on memory impairments in diabetic rats.
Discretion and Disproportionality
Directory of Open Access Journals (Sweden)
Jason A. Grissom
2015-12-01
Full Text Available Students of color are underrepresented in gifted programs relative to White students, but the reasons for this underrepresentation are poorly understood. We investigate the predictors of gifted assignment using nationally representative, longitudinal data on elementary students. We document that even among students with high standardized test scores, Black students are less likely to be assigned to gifted services in both math and reading, a pattern that persists when controlling for other background factors, such as health and socioeconomic status, and characteristics of classrooms and schools. We then investigate the role of teacher discretion, leveraging research from political science suggesting that clients of government services from traditionally underrepresented groups benefit from diversity in the providers of those services, including teachers. Even after conditioning on test scores and other factors, Black students indeed are referred to gifted programs, particularly in reading, at significantly lower rates when taught by non-Black teachers, a concerning result given the relatively low incidence of assignment to own-race teachers among Black students.
International Nuclear Information System (INIS)
Vlad, Valentin I.; Ionescu-Pallas, Nicholas
2000-10-01
The Planck radiation spectrum of ideal cubic and spherical cavities, in the region of small adiabatic invariance, γ = TV 1/3 , is shown to be discrete and strongly dependent on the cavity geometry and temperature. This behavior is the consequence of the random distribution of the state weights in the cubic cavity and of the random overlapping of the successive multiplet components, for the spherical cavity. The total energy (obtained by summing up the exact contributions of the eigenvalues and their weights, for low values of the adiabatic invariance) does not obey any longer Stefan-Boltzmann law. The new law includes a corrective factor depending on γ and imposes a faster decrease of the total energy to zero, for γ → 0. We have defined the double quantized regime both for cubic and spherical cavities by the superior and inferior limits put on the principal quantum numbers or the adiabatic invariance. The total energy of the double quantized cavities shows large differences from the classical calculations over unexpected large intervals, which are measurable and put in evidence important macroscopic quantum effects. (author)
Effects of Compound Yi-Zhi on D-galactose-induced learning and memory deficits in mice
Institute of Scientific and Technical Information of China (English)
XUJiang-Ping; WUHang-Yu; LILin
2004-01-01
AIM: To explore the effects of Compound Yi-Zhi (YZC) on learning and memory capacity and free radical metabolism in D-galactose induced mice dementia model. METHODS: The mice dementia model was induced by a daily D-galactose 0.15g/kg sc for 45 days and after 5 days'D-galactose injection, the mice were treated with three doses of YZC
Using Continuous Action Spaces to Solve Discrete Problems
van Hasselt, Hado; Wiering, Marco
2009-01-01
Real-world control problems are often modeled as Markov Decision Processes (MDPs) with discrete action spaces to facilitate the use of the many reinforcement learning algorithms that exist to find solutions for such MDPs. For many of these problems an underlying continuous action space can be
Directory of Open Access Journals (Sweden)
Junie P Warrington
Full Text Available Whole brain radiation therapy (WBRT is commonly used for treatment of primary and metastatic brain tumors; however, cognitive impairment occurs in 40-50% of brain tumor survivors. The etiology of the cognitive impairment following WBRT remains elusive. We recently reported that radiation-induced cerebrovascular rarefaction within hippocampal subregions could be completely reversed by systemic hypoxia. However, the effects of this intervention on learning and memory have not been reported. In this study, we assessed the time-course for WBRT-induced impairments in contextual and spatial learning and the capacity of systemic hypoxia to reverse WBRT-induced deficits in spatial memory. A clinical fractionated series of 4.5Gy WBRT was administered to mice twice weekly for 4 weeks, and after various periods of recovery, behavioral analyses were performed. To study the effects of systemic hypoxia, mice were subjected to 11% (hypoxia or 21% oxygen (normoxia for 28 days, initiated 1 month after the completion of WBRT. Our results indicate that WBRT induces a transient deficit in contextual learning, disruption of working memory, and progressive impairment of spatial learning. Additionally, systemic hypoxia completely reversed WBRT-induced impairments in learning and these behavioral effects as well as increased vessel density persisted for at least 2 months following hypoxia treatment. Our results provide critical support for the hypothesis that cerebrovascular rarefaction is a key component of cognitive impairment post-WBRT and indicate that processes of learning and memory, once thought to be permanently impaired after WBRT, can be restored.
Spencer, Sarah J.; Almiron Bonnin, Damian; Deasy, Joseph O.; Bradley, Jeffrey D.; El Naqa, Issam
2009-01-01
Radiotherapy outcomes are determined by complex interactions between physical and biological factors, reflecting both treatment conditions and underlying genetics. Recent advances in radiotherapy and biotechnology provide new opportunities and challenges for predicting radiation-induced toxicities, particularly radiation pneumonitis (RP), in lung cancer patients. In this work, we utilize datamining methods based on machine learning to build a predictive model of lung injury by retrospective analysis of treatment planning archives. In addition, biomarkers for this model are extracted from a prospective clinical trial that collects blood serum samples at multiple time points. We utilize a 3-way proteomics methodology to screen for differentially expressed proteins that are related to RP. Our preliminary results demonstrate that kernel methods can capture nonlinear dose-volume interactions, but fail to address missing biological factors. Our proteomics strategy yielded promising protein candidates, but their role in RP as well as their interactions with dose-volume metrics remain to be determined. PMID:19704920
A deep learning-based reconstruction of cosmic ray-induced air showers
Erdmann, M.; Glombitza, J.; Walz, D.
2018-01-01
We describe a method of reconstructing air showers induced by cosmic rays using deep learning techniques. We simulate an observatory consisting of ground-based particle detectors with fixed locations on a regular grid. The detector's responses to traversing shower particles are signal amplitudes as a function of time, which provide information on transverse and longitudinal shower properties. In order to take advantage of convolutional network techniques specialized in local pattern recognition, we convert all information to the image-like grid of the detectors. In this way, multiple features, such as arrival times of the first particles and optimized characterizations of time traces, are processed by the network. The reconstruction quality of the cosmic ray arrival direction turns out to be competitive with an analytic reconstruction algorithm. The reconstructed shower direction, energy and shower depth show the expected improvement in resolution for higher cosmic ray energy.
Institute of Scientific and Technical Information of China (English)
DragoCrneci; Radu Silaghi-Dumitrescu
2013-01-01
Reactive oxygen species have been implicated in conditions ranging from cardiovascular dysfunc-tion, arthritis, cancer, to aging and age-related disorders. The organism developed several path-ways to counteract these effects, with base excision repair being responsible for repairing one of the major base lesions (8-oxoG) in al organisms. Epidemiological evidence suggests that cognitive stimulation makes the brain more resilient to damage or degeneration. Recent studies have linked enriched environment to reduction of oxidative stressin neurons of mice with Alzheimer’s dis-ease-like disease, but given its complexity it is not clear what specific aspect of enriched environ-ment has therapeutic effects. Studies from molecular biology have shown that the protein p300, which is a transcription co-activator required for consolidation of memories during specific learning tasks, is at the same time involved in DNA replication and repair, playing a central role in the long-patch pathway of base excision repair. Based on the evidence, we propose that learning tasks such as novel object recognition could be tested as possible methods of base excision repair faci-litation, hence inducing DNA repair in the hippocampal neurons. If this method proves to be effective, it could be the start for designing similar tasks for humans, as a behavioral therapeutic complement to the classical drug-based therapy in treating neurodegenerative disorders. This review presents the current status of therapeutic methods used in treating neurodegenerative diseases induced by reactive oxygen species and proposes a new approach based on existing data.
Perfect discretization of path integrals
International Nuclear Information System (INIS)
Steinhaus, Sebastian
2012-01-01
In order to obtain a well-defined path integral one often employs discretizations. In the case of General Relativity these generically break diffeomorphism symmetry, which has severe consequences since these symmetries determine the dynamics of the corresponding system. In this article we consider the path integral of reparametrization invariant systems as a toy example and present an improvement procedure for the discretized propagator. Fixed points and convergence of the procedure are discussed. Furthermore we show that a reparametrization invariant path integral implies discretization independence and acts as a projector onto physical states.
Perfect discretization of path integrals
Steinhaus, Sebastian
2012-05-01
In order to obtain a well-defined path integral one often employs discretizations. In the case of General Relativity these generically break diffeomorphism symmetry, which has severe consequences since these symmetries determine the dynamics of the corresponding system. In this article we consider the path integral of reparametrization invariant systems as a toy example and present an improvement procedure for the discretized propagator. Fixed points and convergence of the procedure are discussed. Furthermore we show that a reparametrization invariant path integral implies discretization independence and acts as a projector onto physical states.
The origin of discrete particles
Bastin, T
2009-01-01
This book is a unique summary of the results of a long research project undertaken by the authors on discreteness in modern physics. In contrast with the usual expectation that discreteness is the result of mathematical tools for insertion into a continuous theory, this more basic treatment builds up the world from the discrimination of discrete entities. This gives an algebraic structure in which certain fixed numbers arise. As such, one agrees with the measured value of the fine-structure constant to one part in 10,000,000 (10 7 ). Sample Chapter(s). Foreword (56 KB). Chapter 1: Introduction
Amaral, Jorge L M; Lopes, Agnaldo J; Jansen, José M; Faria, Alvaro C D; Melo, Pedro L
2013-12-01
The purpose of this study was to develop an automatic classifier to increase the accuracy of the forced oscillation technique (FOT) for diagnosing early respiratory abnormalities in smoking patients. The data consisted of FOT parameters obtained from 56 volunteers, 28 healthy and 28 smokers with low tobacco consumption. Many supervised learning techniques were investigated, including logistic linear classifiers, k nearest neighbor (KNN), neural networks and support vector machines (SVM). To evaluate performance, the ROC curve of the most accurate parameter was established as baseline. To determine the best input features and classifier parameters, we used genetic algorithms and a 10-fold cross-validation using the average area under the ROC curve (AUC). In the first experiment, the original FOT parameters were used as input. We observed a significant improvement in accuracy (KNN=0.89 and SVM=0.87) compared with the baseline (0.77). The second experiment performed a feature selection on the original FOT parameters. This selection did not cause any significant improvement in accuracy, but it was useful in identifying more adequate FOT parameters. In the third experiment, we performed a feature selection on the cross products of the FOT parameters. This selection resulted in a further increase in AUC (KNN=SVM=0.91), which allows for high diagnostic accuracy. In conclusion, machine learning classifiers can help identify early smoking-induced respiratory alterations. The use of FOT cross products and the search for the best features and classifier parameters can markedly improve the performance of machine learning classifiers. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Epigenetic regulation of BDNF in the learned helplessness-induced animal model of depression.
Su, Chun-Lin; Su, Chun-Wei; Hsiao, Ya-Hsin; Gean, Po-Wu
2016-05-01
Major depressive disorder (MDD), one of the most common mental disorders, is a significant risk factor for suicide and causes a low quality of life for many people. However, the causes and underlying mechanism of depression remain elusive. In the current work, we investigated epigenetic regulation of BDNF in the learned helplessness-induced animal model of depression. Mice were exposed to inescapable stress and divided into learned helplessness (LH) and resilient (LH-R) groups depending on the number they failed to escape. We found that the LH group had longer immobility duration in the forced swimming test (FST) and tail suspension tests (TST), which is consistent with a depression-related phenotype. Western blotting analysis and enzyme-linked immunosorbent assay (ELISA) revealed that the LH group had lower BDNF expression than that of the LH-R group. The LH group consistently had lower BDNF mRNA levels, as detected by qPCR assay. In addition, we found BDNF exon IV was down-regulated in the LH group. Intraperitoneal injection of imipramine or histone deacetylase inhibitors (HDACi) to the LH mice for 14 consecutive days ameliorated depression-like behaviors and reversed the decrease in BDNF. The expression of HDAC5 was up-regulated in the LH mice, and a ChIP assay revealed that the level of HDAC5 binding to the promoter region of BDNF exon IV was higher than that seen in other groups. Knockdown of HDAC5 reduced depression-like behaviors in the LH mice. Taken together, these results suggest that epigenetic regulation of BDNF by HDAC5 plays an important role in the learned helplessness model of depression. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cocaine induces state-dependent learning of sexual conditioning in male Japanese quail.
Gill, Karin E; Rice, Beth Ann; Akins, Chana K
2015-01-01
State dependent learning effects have been widely studied in a variety of drugs of abuse. However, they have yet to be studied in relation to sexual motivation. The current study investigated state-dependent learning effects of cocaine in male Japanese quail (Coturnix japonica) using a sexual conditioning paradigm. Cocaine-induced state-dependent learning effects were investigated using a 2×2 factorial design with training state as one factor and test state as the other factor. During a 14-day training phase, male quail were injected once daily with 10mg/kg cocaine or saline and then placed in a test chamber after 15min. In the test chamber, sexual conditioning trials consisted of presentation of a light conditioned stimulus (CS) followed by sexual reinforcement. During the state dependent test, half of the birds received a shift in drug state from training to testing (Coc→Sal or Sal→Coc) while the other half remained in the same drug state (Coc→Coc or Sal→Sal). Results showed that male quail that were trained and tested in the same state (Coc→Coc or Sal→Sal) showed greater sexual conditioning than male quail that were trained and tested in different states (Sal→Coc) except when cocaine was administered chronically prior to the test (Coc→Sal). For the latter condition, sexual conditioning persisted from cocaine training to the saline test. The findings suggest that state dependent effects may alter sexual motivation and that repeated exposure to cocaine during sexual activity may increase sexual motivation which, in turn, may lead to high risk sexual activities. An alternative explanation for the findings is also discussed. Copyright © 2014 Elsevier Inc. All rights reserved.
Reznik, Samantha J; Nusslock, Robin; Pornpattananangkul, Narun; Abramson, Lyn Y; Coan, James A; Harmon-Jones, Eddie
2017-08-01
Research suggests that midline posterior versus frontal electroencephalographic (EEG) theta activity (PFTA) may reflect a novel neurophysiological index of approach motivation. Elevated PFTA has been associated with approach-related tendencies both at rest and during laboratory tasks designed to enhance approach motivation. PFTA is sensitive to changes in dopamine signaling within the fronto-striatal neural circuit, which is centrally involved in approach motivation, reward processing, and goal-directed behavior. To date, however, no studies have examined PFTA during a laboratory task designed to reduce approach motivation or goal-directed behavior. Considerable animal and human research supports the hypothesis put forth by the learned helplessness theory that exposure to uncontrollable aversive stimuli decreases approach motivation by inducing a state of perceived uncontrollability. Accordingly, the present study examined the effect of perceived uncontrollability (i.e., learned helplessness) on PFTA. EEG data were collected from 74 participants (mean age = 19.21 years; 40 females) exposed to either Controllable (n = 26) or Uncontrollable (n = 25) aversive noise bursts, or a No-Noise Condition (n = 23). In line with prediction, individuals exposed to uncontrollable aversive noise bursts displayed a significant decrease in PFTA, reflecting reduced approach motivation, relative to both individuals exposed to controllable noise bursts or the No-Noise Condition. There was no relationship between perceived uncontrollability and frontal EEG alpha asymmetry, another commonly used neurophysiological index of approach motivation. Results have implications for understanding the neurophysiology of approach motivation and establishing PFTA as a neurophysiological index of approach-related tendencies.
Mazzaferri, Javier; Larrivée, Bruno; Cakir, Bertan; Sapieha, Przemyslaw; Costantino, Santiago
2018-03-02
Preclinical studies of vascular retinal diseases rely on the assessment of developmental dystrophies in the oxygen induced retinopathy rodent model. The quantification of vessel tufts and avascular regions is typically computed manually from flat mounted retinas imaged using fluorescent probes that highlight the vascular network. Such manual measurements are time-consuming and hampered by user variability and bias, thus a rapid and objective method is needed. Here, we introduce a machine learning approach to segment and characterize vascular tufts, delineate the whole vasculature network, and identify and analyze avascular regions. Our quantitative retinal vascular assessment (QuRVA) technique uses a simple machine learning method and morphological analysis to provide reliable computations of vascular density and pathological vascular tuft regions, devoid of user intervention within seconds. We demonstrate the high degree of error and variability of manual segmentations, and designed, coded, and implemented a set of algorithms to perform this task in a fully automated manner. We benchmark and validate the results of our analysis pipeline using the consensus of several manually curated segmentations using commonly used computer tools. The source code of our implementation is released under version 3 of the GNU General Public License ( https://www.mathworks.com/matlabcentral/fileexchange/65699-javimazzaf-qurva ).
Farley, J; Auerbach, S
Phosphorylation of ion channels has been suggested as one molecular mechanism responsible for learning-produced long-term changes in neuronal excitability. Persistent training-produced changes in two distinct K+ currents (IA (ref. 2), IK-Ca (refs 3,4)) and a voltage-dependent calcium current (ICa; refs 3,4) have previously been shown to occur in type B photoreceptors of Hermissenda, as a result of associative learning. But the identity of the phosphorylation pathway(s) responsible for these changes has not as yet been determined. Injections of cyclic AMP-dependent protein kinase reduce a K+ current (IK) in B cells which is different from those changed by training, but fails to reduce IA and IK-Ca. Phosphorylase b kinase (an exogenous calcium/calmodulin-dependent kinase) reduces IA, but whether IK-Ca and ICa are changed in the manner of associative training is not yet known. Another protein kinase present in high concentrations in both mammalian brain and molluscan nervous systems is protein kinase C, which is both calcium- and phospholipid-sensitive. We now present evidence that activation of protein kinase C by the tumour promoter phorbol ester (PDB) and intracellular injection of the enzyme induce conductance changes similar to those caused by associative training in Hermissenda B cells (that is a reduction of IA and IK-Ca, and enhancement of ICa). These results represent the first direct demonstration that protein kinase C affects membrane K+ ion conductance mechanisms.
2013-01-01
Objective. To assess second-year pharmacy students’ acquisition of pharmacotherapy knowledge and clinical competence from participation in a high-fidelity simulation, and to determine the impact on the simulation experience of implementing feedback from previous students. Design. A high-fidelity simulation was used to present a patient case scenario of drug-induced dyspepsia with gastrointestinal bleeding. The simulation was revised based on feedback from a previous class of students to include a smaller group size, provision of session material to students in advance, and an improved learning environment. Assessment. Student performance on pre- and post-simulation knowledge and clinical competence tests documented significant improvements in students' knowledge of dyspepsia and associated symptoms, with the greatest improvement on questions relating to the hemodynamic effects of gastrointestinal bleeding. Students were more satisfied with the simulation experience compared to students in the earlier study. Conclusion. Participation in a high-fidelity simulation allowed pharmacy students to apply knowledge and skills learned in the classroom. Improved student satisfaction with the simulation suggests that implementing feedback obtained through student course evaluations can be an effective means of improving the curriculum. PMID:23519773
Entropic Phase Maps in Discrete Quantum Gravity
Directory of Open Access Journals (Sweden)
Benjamin F. Dribus
2017-06-01
Full Text Available Path summation offers a flexible general approach to quantum theory, including quantum gravity. In the latter setting, summation is performed over a space of evolutionary pathways in a history configuration space. Discrete causal histories called acyclic directed sets offer certain advantages over similar models appearing in the literature, such as causal sets. Path summation defined in terms of these histories enables derivation of discrete Schrödinger-type equations describing quantum spacetime dynamics for any suitable choice of algebraic quantities associated with each evolutionary pathway. These quantities, called phases, collectively define a phase map from the space of evolutionary pathways to a target object, such as the unit circle S 1 ⊂ C , or an analogue such as S 3 or S 7 . This paper explores the problem of identifying suitable phase maps for discrete quantum gravity, focusing on a class of S 1 -valued maps defined in terms of “structural increments” of histories, called terminal states. Invariants such as state automorphism groups determine multiplicities of states, and induce families of natural entropy functions. A phase map defined in terms of such a function is called an entropic phase map. The associated dynamical law may be viewed as an abstract combination of Schrödinger’s equation and the second law of thermodynamics.
New formulation of the discrete element method
Rojek, Jerzy; Zubelewicz, Aleksander; Madan, Nikhil; Nosewicz, Szymon
2018-01-01
A new original formulation of the discrete element method based on the soft contact approach is presented in this work. The standard DEM has heen enhanced by the introduction of the additional (global) deformation mode caused by the stresses in the particles induced by the contact forces. Uniform stresses and strains are assumed for each particle. The stresses are calculated from the contact forces. The strains are obtained using an inverse constitutive relationship. The strains allow us to obtain deformed particle shapes. The deformed shapes (ellipses) are taken into account in contact detection and evaluation of the contact forces. A simple example of a uniaxial compression of a rectangular specimen, discreti.zed with equal sized particles is simulated to verify the DDEM algorithm. The numerical example shows that a particle deformation changes the particle interaction and the distribution of forces in the discrete element assembly. A quantitative study of micro-macro elastic properties proves the enhanced capabilities of the DDEM as compared to standard DEM.
Improving the Teaching of Discrete-Event Control Systems Using a LEGO Manufacturing Prototype
Sanchez, A.; Bucio, J.
2012-01-01
This paper discusses the usefulness of employing LEGO as a teaching-learning aid in a post-graduate-level first course on the control of discrete-event systems (DESs). The final assignment of the course is presented, which asks students to design and implement a modular hierarchical discrete-event supervisor for the coordination layer of a…
Synchronization Techniques in Parallel Discrete Event Simulation
Lindén, Jonatan
2018-01-01
Discrete event simulation is an important tool for evaluating system models in many fields of science and engineering. To improve the performance of large-scale discrete event simulations, several techniques to parallelize discrete event simulation have been developed. In parallel discrete event simulation, the work of a single discrete event simulation is distributed over multiple processing elements. A key challenge in parallel discrete event simulation is to ensure that causally dependent ...
3-D Discrete Analytical Ridgelet Transform
Helbert , David; Carré , Philippe; Andrès , Éric
2006-01-01
International audience; In this paper, we propose an implementation of the 3-D Ridgelet transform: the 3-D discrete analytical Ridgelet transform (3-D DART). This transform uses the Fourier strategy for the computation of the associated 3-D discrete Radon transform. The innovative step is the definition of a discrete 3-D transform with the discrete analytical geometry theory by the construction of 3-D discrete analytical lines in the Fourier domain. We propose two types of 3-D discrete lines:...
Institute of Scientific and Technical Information of China (English)
XUJiang-Ping; WUHang-Yu; LILin
2004-01-01
AIM To investigate the effects of Capsule Yi-Zhi (CYZ) on learning and memory disorder and beta-amyloid protein induced neurotoxieity in rats. Methods Various doses of CYZ were administered to Sprague-Dawley (SD) rats for 8 days, twice a day. Then scopolamine hydrobromide (Sco) intraperitoneal injection was performed on each rat and the
Sczesny-Kaiser, Matthias; Beckhaus, Katharina; Dinse, Hubert R; Schwenkreis, Peter; Tegenthoff, Martin; Höffken, Oliver
2016-01-01
Studies on noninvasive motor cortex stimulation and motor learning demonstrated cortical excitability as a marker for a learning effect. Transcranial direct current stimulation (tDCS) is a non-invasive tool to modulate cortical excitability. It is as yet unknown how tDCS-induced excitability changes and perceptual learning in visual cortex correlate. Our study aimed to examine the influence of tDCS on visual perceptual learning in healthy humans. Additionally, we measured excitability in primary visual cortex (V1). We hypothesized that anodal tDCS would improve and cathodal tDCS would have minor or no effects on visual learning. Anodal, cathodal or sham tDCS were applied over V1 in a randomized, double-blinded design over four consecutive days (n = 30). During 20 min of tDCS, subjects had to learn a visual orientation-discrimination task (ODT). Excitability parameters were measured by analyzing paired-stimulation behavior of visual-evoked potentials (ps-VEP) and by measuring phosphene thresholds (PTs) before and after the stimulation period of 4 days. Compared with sham-tDCS, anodal tDCS led to an improvement of visual discrimination learning (p learning effect. For cathodal tDCS, no significant effects on learning or on excitability could be seen. Our results showed that anodal tDCS over V1 resulted in improved visual perceptual learning and increased cortical excitability. tDCS is a promising tool to alter V1 excitability and, hence, perceptual visual learning.
Exact analysis of discrete data
Hirji, Karim F
2005-01-01
Researchers in fields ranging from biology and medicine to the social sciences, law, and economics regularly encounter variables that are discrete or categorical in nature. While there is no dearth of books on the analysis and interpretation of such data, these generally focus on large sample methods. When sample sizes are not large or the data are otherwise sparse, exact methods--methods not based on asymptotic theory--are more accurate and therefore preferable.This book introduces the statistical theory, analysis methods, and computation techniques for exact analysis of discrete data. After reviewing the relevant discrete distributions, the author develops the exact methods from the ground up in a conceptually integrated manner. The topics covered range from univariate discrete data analysis, a single and several 2 x 2 tables, a single and several 2 x K tables, incidence density and inverse sampling designs, unmatched and matched case -control studies, paired binary and trinomial response models, and Markov...
Discrete geometric structures for architecture
Pottmann, Helmut
2010-01-01
. The talk will provide an overview of recent progress in this field, with a particular focus on discrete geometric structures. Most of these result from practical requirements on segmenting a freeform shape into planar panels and on the physical realization
Causal Dynamics of Discrete Surfaces
Directory of Open Access Journals (Sweden)
Pablo Arrighi
2014-03-01
Full Text Available We formalize the intuitive idea of a labelled discrete surface which evolves in time, subject to two natural constraints: the evolution does not propagate information too fast; and it acts everywhere the same.
Perfect discretization of path integrals
Steinhaus, Sebastian
2011-01-01
In order to obtain a well-defined path integral one often employs discretizations. In the case of General Relativity these generically break diffeomorphism symmetry, which has severe consequences since these symmetries determine the dynamics of the corresponding system. In this article we consider the path integral of reparametrization invariant systems as a toy example and present an improvement procedure for the discretized propagator. Fixed points and convergence of the procedure are discu...
Alfa, Attahiru S
2016-01-01
This book introduces the theoretical fundamentals for modeling queues in discrete-time, and the basic procedures for developing queuing models in discrete-time. There is a focus on applications in modern telecommunication systems. It presents how most queueing models in discrete-time can be set up as discrete-time Markov chains. Techniques such as matrix-analytic methods (MAM) that can used to analyze the resulting Markov chains are included. This book covers single node systems, tandem system and queueing networks. It shows how queues with time-varying parameters can be analyzed, and illustrates numerical issues associated with computations for the discrete-time queueing systems. Optimal control of queues is also covered. Applied Discrete-Time Queues targets researchers, advanced-level students and analysts in the field of telecommunication networks. It is suitable as a reference book and can also be used as a secondary text book in computer engineering and computer science. Examples and exercises are includ...
Chen, Weiping; Yang, Qiongjie; Wei, Xing
2013-11-01
To investigate the effects of chrysalis oil on learning, memory and oxidative stress in D-galactose-induced ageing model of mice. Mice were injected intraperitoneally with D-galactose daily and received chrysalis oil intragastrically simultaneously for 30 d. Then mice underwent space navigation test and spatial probe test, superoxide dismutase (SOD), glutathione peroxidase (GSH-PX) activity and malondialdehyde (MDA) contents in mouse brain were measured. Compared to model group, escape latency in mice treated with 6 ml/kg*d chrysalis oil was significantly shorter (Pchrysalis oil were significantly increased (PChrysalis oil treatment (12ml/kg*d) significantly increased SOD and GSH-PX activity and reduced MDA contents in brain of D-galactose-induced aging mice. Chrysalis oil can improve the ability of learning and memory in D-galactose-induced aging mice, and inhibit peroxidation in brain tissue.
Discrete Curvature Theories and Applications
Sun, Xiang
2016-08-25
Discrete Di erential Geometry (DDG) concerns discrete counterparts of notions and methods in di erential geometry. This thesis deals with a core subject in DDG, discrete curvature theories on various types of polyhedral surfaces that are practically important for free-form architecture, sunlight-redirecting shading systems, and face recognition. Modeled as polyhedral surfaces, the shapes of free-form structures may have to satisfy di erent geometric or physical constraints. We study a combination of geometry and physics { the discrete surfaces that can stand on their own, as well as having proper shapes for the manufacture. These proper shapes, known as circular and conical meshes, are closely related to discrete principal curvatures. We study curvature theories that make such surfaces possible. Shading systems of freeform building skins are new types of energy-saving structures that can re-direct the sunlight. From these systems, discrete line congruences across polyhedral surfaces can be abstracted. We develop a new curvature theory for polyhedral surfaces equipped with normal congruences { a particular type of congruences de ned by linear interpolation of vertex normals. The main results are a discussion of various de nitions of normality, a detailed study of the geometry of such congruences, and a concept of curvatures and shape operators associated with the faces of a triangle mesh. These curvatures are compatible with both normal congruences and the Steiner formula. In addition to architecture, we consider the role of discrete curvatures in face recognition. We use geometric measure theory to introduce the notion of asymptotic cones associated with a singular subspace of a Riemannian manifold, which is an extension of the classical notion of asymptotic directions. We get a simple expression of these cones for polyhedral surfaces, as well as convergence and approximation theorems. We use the asymptotic cones as facial descriptors and demonstrate the
Bravo, Àlex; Li, Tong Shu; Su, Andrew I; Good, Benjamin M; Furlong, Laura I
2016-01-01
Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln¼en#.VsL3yDLWR_V. © The Author(s) 2016. Published by Oxford University Press.
Vadillo, Miguel A; Orgaz, Cristina; Luque, David; Cobos, Pedro L; López, Francisco J; Matute, Helena
2013-05-01
Current associative theories of contingency learning assume that inhibitory learning plays a part in the interference between outcomes. However, it is unclear whether this inhibitory learning results in the inhibition of the outcome representation or whether it simply counteracts previous excitatory learning so that the outcome representation is neither activated nor inhibited. Additionally, these models tend to conceptualize inhibition as a relatively transient and cue-dependent state. However, research on retrieval-induced forgetting suggests that the inhibition of representations is a real process that can be relatively independent of the retrieval cue used to access the inhibited information. Consistent with this alternative view, we found that interference between outcomes reduces the retrievability of the target outcome even when the outcome is associated with a novel (non-inhibitory) cue. This result has important theoretical implications for associative models of interference and shows that the empirical facts and theories developed in studies of retrieval-induced forgetting might be relevant in contingency learning and vice versa. © 2012 The British Psychological Society.
Analysis of Discrete Mittag - Leffler Functions
Directory of Open Access Journals (Sweden)
N. Shobanadevi
2015-03-01
Full Text Available Discrete Mittag - Leffler functions play a major role in the development of the theory of discrete fractional calculus. In the present article, we analyze qualitative properties of discrete Mittag - Leffler functions and establish sufficient conditions for convergence, oscillation and summability of the infinite series associated with discrete Mittag - Leffler functions.
Foundations of a discrete physics
International Nuclear Information System (INIS)
McGoveran, D.; Noyes, P.
1988-01-01
Starting from the principles of finiteness, discreteness, finite computability and absolute nonuniqueness, we develop the ordering operator calculus, a strictly constructive mathematical system having the empirical properties required by quantum mechanical and special relativistic phenomena. We show how to construct discrete distance functions, and both rectangular and spherical coordinate systems(with a discrete version of ''π''). The richest discrete space constructible without a preferred axis and preserving translational and rotational invariance is shown to be a discrete 3-space with the usual symmetries. We introduce a local ordering parameter with local (proper) time-like properties and universal ordering parameters with global (cosmological) time-like properties. Constructed ''attribute velocities'' connect ensembles with attributes that are invariant as the appropriate time-like parameter increases. For each such attribute, we show how to construct attribute velocities which must satisfy the '' relativistic Doppler shift'' and the ''relativistic velocity composition law,'' as well as the Lorentz transformations. By construction, these velocities have finite maximum and minimum values. In the space of all attributes, the minimum of these maximum velocities will predominate in all multiple attribute computations, and hence can be identified as a fundamental limiting velocity, General commutation relations are constructed which under the physical interpretation are shown to reduce to the usual quantum mechanical commutation relations. 50 refs., 18 figs
Świder, Karolina; Bąbel, Przemysław
2016-01-01
Research shows that placebo analgesia and nocebo hyperalgesia can be induced through observational learning. Our aim was to replicate and extend these results by studying the influence of the type and colour of stimuli used as placebos on the placebo effects induced by observational learning. Three experimental and two control groups were tested. All participants received pain stimuli of the same intensity preceded by colour lights (green and red) or geometric shapes (circles and squares). Before receiving pain stimuli, participants in the experimental groups, but not in the control groups, observed a model who rated pain stimuli that were preceded by either green lights (green placebo group), red lights (red placebo group), or circles (circle placebo group) as being less painful than those preceded by either red lights (green placebo group), green lights (red placebo group), or squares (circle placebo group). As a result participants in the experimental groups rated pain stimuli preceded by either green lights (green placebo group), red lights (red placebo group), or circles (circle placebo group) as being less painful than the participants in the control groups did, indicating that placebo effect was induced. No statistically significant differences were found in the magnitudes of the placebo effects between the three experimental groups (green placebo, red placebo, and circle placebo groups), indicating that neither the type nor the colour of placebo stimuli affected the placebo effects induced by observational learning. The placebo effects induced by observational learning were found to be unrelated to the individual differences in pain anxiety, fear of pain, and empathy. PMID:27362552
Discrete differential geometry. Consistency as integrability
Bobenko, Alexander I.; Suris, Yuri B.
2005-01-01
A new field of discrete differential geometry is presently emerging on the border between differential and discrete geometry. Whereas classical differential geometry investigates smooth geometric shapes (such as surfaces), and discrete geometry studies geometric shapes with finite number of elements (such as polyhedra), the discrete differential geometry aims at the development of discrete equivalents of notions and methods of smooth surface theory. Current interest in this field derives not ...
Integrable structure in discrete shell membrane theory.
Schief, W K
2014-05-08
We present natural discrete analogues of two integrable classes of shell membranes. By construction, these discrete shell membranes are in equilibrium with respect to suitably chosen internal stresses and external forces. The integrability of the underlying equilibrium equations is proved by relating the geometry of the discrete shell membranes to discrete O surface theory. We establish connections with generalized barycentric coordinates and nine-point centres and identify a discrete version of the classical Gauss equation of surface theory.
Analysis of stochastic effects in Kaldor-type business cycle discrete model
Bashkirtseva, Irina; Ryashko, Lev; Sysolyatina, Anna
2016-07-01
We study nonlinear stochastic phenomena in the discrete Kaldor model of business cycles. A numerical parametric analysis of stochastically forced attractors (equilibria, closed invariant curves, discrete cycles) of this model is performed using the stochastic sensitivity functions technique. A spatial arrangement of random states in stochastic attractors is modeled by confidence domains. The phenomenon of noise-induced transitions ;chaos-order; is discussed.
Degree distribution in discrete case
International Nuclear Information System (INIS)
Wang, Li-Na; Chen, Bin; Yan, Zai-Zai
2011-01-01
Vertex degree of many network models and real-life networks is limited to non-negative integer. By means of measure and integral, the relation of the degree distribution and the cumulative degree distribution in discrete case is analyzed. The degree distribution, obtained by the differential of its cumulative, is only suitable for continuous case or discrete case with constant degree change. When degree change is not a constant but proportional to degree itself, power-law degree distribution and its cumulative have the same exponent and the mean value is finite for power-law exponent greater than 1. -- Highlights: → Degree change is the crux for using the cumulative degree distribution method. → It suits for discrete case with constant degree change. → If degree change is proportional to degree, power-law degree distribution and its cumulative have the same exponent. → In addition, the mean value is finite for power-law exponent greater than 1.
Spatial learning and memory deficits induced by exposure to iron-56-particle radiation
Shukitt-Hale, B.; Casadesus, G.; McEwen, J. J.; Rabin, B. M.; Joseph, J. A.
2000-01-01
It has previously been shown that exposing rats to particles of high energy and charge (HZE) disrupts the functioning of the dopaminergic system and behaviors mediated by this system, such as motor performance and an amphetamine-induced conditioned taste aversion; these adverse behavioral and neuronal effects are similar to those seen in aged animals. Because cognition declines with age, spatial learning and memory were assessed in the Morris water maze 1 month after whole-body irradiation with 1.5 Gy of 1 GeV/nucleon high-energy (56)Fe particles, to test the cognitive behavioral consequences of radiation exposure. Irradiated rats demonstrated cognitive impairment compared to the control group as seen in their increased latencies to find the hidden platform, particularly on the reversal day when the platform was moved to the opposite quadrant. Also, the irradiated group used nonspatial strategies during the probe trials (swim with no platform), i.e. less time spent in the platform quadrant, fewer crossings of and less time spent in the previous platform location, and longer latencies to the previous platform location. These findings are similar to those seen in aged rats, suggesting that an increased release of reactive oxygen species may be responsible for the induction of radiation- and age-related cognitive deficits. If these decrements in behavior also occur in humans, they may impair the ability of astronauts to perform critical tasks during long-term space travel beyond the magnetosphere.
Unraveling Network-induced Memory Contention: Deeper Insights with Machine Learning
International Nuclear Information System (INIS)
Groves, Taylor Liles; Grant, Ryan; Gonzales, Aaron; Arnold, Dorian
2017-01-01
Remote Direct Memory Access (RDMA) is expected to be an integral communication mechanism for future exascale systems enabling asynchronous data transfers, so that applications may fully utilize CPU resources while simultaneously sharing data amongst remote nodes. We examine Network-induced Memory Contention (NiMC) on Infiniband networks. We expose the interactions between RDMA, main-memory and cache, when applications and out-of-band services compete for memory resources. We then explore NiMCs resulting impact on application-level performance. For a range of hardware technologies and HPC workloads, we quantify NiMC and show that NiMCs impact grows with scale resulting in up to 3X performance degradation at scales as small as 8K processes even in applications that previously have been shown to be performance resilient in the presence of noise. In addition, this work examines the problem of predicting NiMC's impact on applications by leveraging machine learning and easily accessible performance counters. This approach provides additional insights about the root cause of NiMC and facilitates dynamic selection of potential solutions. Finally, we evaluated three potential techniques to reduce NiMCs impact, namely hardware offloading, core reservation and network throttling.
Reversal of Trimethyltin-Induced Learning and Memory Deficits by 3,5-Dicaffeoylquinic Acid
Directory of Open Access Journals (Sweden)
Jin Yong Kang
2016-01-01
Full Text Available The antiamnesic effect of 3,5-dicaffeoylquinic acid (3,5-diCQA as the main phenolic compound in Artemisia argyi H. extract on cognitive dysfunction induced by trimethyltin (TMT (7.1 μg/kg of body weight; intraperitoneal injection was investigated in order to assess its ameliorating function in mice. In several behavioral tests, namely, the Y-maze, passive avoidance, and Morris water maze (MWM test, 3,5-diCQA significantly ameliorated learning and memory deficits. After the behavioral tests, brain tissues from the mice were analyzed to characterize the basis of the neuroprotective effect. Acetylcholine (ACh levels increased, whereas the activity of acetylcholinesterase (AChE decreased upon administration of 3,5-diCQA. In addition, 3,5-diCQA effectively protected against an increase in malondialdehyde (MDA content, an increase in the oxidized glutathione (GSH ratio, and a decline of total superoxide dismutase (SOD level. 3,5-diCQA may prevent neuronal apoptosis through the protection of mitochondrial activities and the repression of apoptotic signaling molecules such as p-Akt, BAX, and p-tau (Ser 404.
On the discrete Gabor transform and the discrete Zak transform
Bastiaans, M.J.; Geilen, M.C.W.
1996-01-01
Gabor's expansion of a discrete-time signal into a set of shifted and modulated versions of an elementary signal (or synthesis window) and the inverse operation -- the Gabor transform -- with which Gabor's expansion coefficients can be determined, are introduced. It is shown how, in the case of a
Discrete Choice and Rational Inattention
DEFF Research Database (Denmark)
Fosgerau, Mogens; Melo, Emerson; de Palma, André
2017-01-01
This paper establishes a general equivalence between discrete choice and rational inattention models. Matejka and McKay (2015, AER) showed that when information costs are modelled using the Shannon entropy, the result- ing choice probabilities in the rational inattention model take the multinomial...... logit form. We show that when information costs are modelled using a class of generalized entropies, then the choice probabilities in any rational inattention model are observationally equivalent to some additive random utility discrete choice model and vice versa. This equivalence arises from convex...
Motor sequence learning-induced neural efficiency in functional brain connectivity.
Karim, Helmet T; Huppert, Theodore J; Erickson, Kirk I; Wollam, Mariegold E; Sparto, Patrick J; Sejdić, Ervin; VanSwearingen, Jessie M
2017-02-15
Previous studies have shown the functional neural circuitry differences before and after an explicitly learned motor sequence task, but have not assessed these changes during the process of motor skill learning. Functional magnetic resonance imaging activity was measured while participants (n=13) were asked to tap their fingers to visually presented sequences in blocks that were either the same sequence repeated (learning block) or random sequences (control block). Motor learning was associated with a decrease in brain activity during learning compared to control. Lower brain activation was noted in the posterior parietal association area and bilateral thalamus during the later periods of learning (not during the control). Compared to the control condition, we found the task-related motor learning was associated with decreased connectivity between the putamen and left inferior frontal gyrus and left middle cingulate brain regions. Motor learning was associated with changes in network activity, spatial extent, and connectivity. Copyright © 2016 Elsevier B.V. All rights reserved.
DEFF Research Database (Denmark)
Bubser, Michael; Bridges, Thomas M; Dencker, Ditte
2014-01-01
PAMs, enabling a more extensive characterization of M4 actions in rodent models. We used VU0467154 to test the hypothesis that selective potentiation of M4 receptor signaling could ameliorate the behavioral, cognitive, and neurochemical impairments induced by the noncompetitive NMDAR antagonist MK-801....... VU0467154 produced a robust dose-dependent reversal of MK-801-induced hyperlocomotion and deficits in preclinical models of associative learning and memory functions, including the touchscreen pairwise visual discrimination task in wild-type mice, but failed to reverse these stimulant...
Group-theoretical aspects of the discrete sine-Gordon equation
International Nuclear Information System (INIS)
Orfanidis, S.J.
1980-01-01
The group-theoretical interpretation of the sine-Gordon equation in terms of connection forms on fiber bundles is extended to the discrete case. Solutions of the discrete sine-Gordon equation induce surfaces on a lattice in the SU(2) group space. The inverse scattering representation, expressing the parallel transport of fibers, is implemented by means of finite rotations. Discrete Baecklund transformations are realized as gauge transformations. The three-dimensional inverse scattering representation is used to derive a discrete nonlinear sigma model, and the corresponding Baecklund transformation and Pohlmeyer's R transformation are constructed
Learning from induced changes in opponent (re)actions in multi-agent games
P.J. 't Hoen (Pieter Jan); S.M. Bohte (Sander); J.A. La Poutré (Han)
2005-01-01
textabstractMulti-agent learning is a growing area of research. An important topic is to formulate how an agent can learn a good policy in the face of adaptive, competitive opponents. Most research has focused on extensions of single agent learning techniques originally designed for agents in more
Li, Ning; Liu, Cong; Jing, Shu; Wang, Mengyang; Wang, Han; Sun, Jinghui; Wang, Chunmei; Chen, Jianguang; Li, He
2017-01-01
Schisandra, Ginseng, Notoginseng, and Lycium barbarum are traditional Chinese medicinal plants sharing cognitive-enhancing properties. To design a functional food to improve memory, we prepared a compound Schisandra-Ginseng-Notoginseng-Lycium (CSGNL) extract and investigated its effect on scopolamine-induced learning and memory loss in mice. To optimize the dose ratios of the four herbal extracts in CSGNL, orthogonal experiments were performed. Mice were administered CSGNL by gavage once a da...
Directory of Open Access Journals (Sweden)
Darkhah
2016-04-01
Full Text Available Background Stress induced by sleep deprivation can cause degradation of learning in the acquisition phase, and low-intensity exercise can prevent the negative effects of stress. Objectives The aim of this study was to investigate the moderating role of aerobic exercise on spatial memory and learning following stress-induced insomnia (sleep REM in animal models. Materials and Methods This experimental study was conducted on adult male Wistar rats that were randomly divided into two groups. Both groups were exposed to sleep deprivation induced stress, following which the experimental group was exposed to exercise training (experimental, n = 8; control, n = 8. The stress intervention was undertaken through 24 hours of sleep deprivation using a modified sleep deprivation platform (MMD. The exercise protocol included mild aerobic exercise on a treadmill (30 minutes a day, seven days, and Morris Water Maze (MWM protocols were applied to assess spatial memory and learning. Data were analyzed by an independent t-test and dependent t-test. Results The results showed that, after seven days of aerobic exercise on a treadmill, the experimental group showed better performance escape latency (P < 0.05 and distance traveled (P < 0.05 than the control group in the MWM, while there was no difference between these two groups in the pre-test. Conclusions The role of exercise is greater in the retention than the acquisition phase for recalling past experiences.
Discrete Hamiltonian evolution and quantum gravity
International Nuclear Information System (INIS)
Husain, Viqar; Winkler, Oliver
2004-01-01
We study constrained Hamiltonian systems by utilizing general forms of time discretization. We show that for explicit discretizations, the requirement of preserving the canonical Poisson bracket under discrete evolution imposes strong conditions on both allowable discretizations and Hamiltonians. These conditions permit time discretizations for a limited class of Hamiltonians, which does not include homogeneous cosmological models. We also present two general classes of implicit discretizations which preserve Poisson brackets for any Hamiltonian. Both types of discretizations generically do not preserve first class constraint algebras. Using this observation, we show that time discretization provides a complicated time gauge fixing for quantum gravity models, which may be compared with the alternative procedure of gauge fixing before discretization
Mohamed, Mamdouh S.; Hirani, Anil N.; Samtaney, Ravi
2016-01-01
A conservative discretization of incompressible Navier–Stokes equations is developed based on discrete exterior calculus (DEC). A distinguishing feature of our method is the use of an algebraic discretization of the interior product operator and a
Solving discrete zero point problems
van der Laan, G.; Talman, A.J.J.; Yang, Z.F.
2004-01-01
In this paper an algorithm is proposed to .nd a discrete zero point of a function on the collection of integral points in the n-dimensional Euclidean space IRn.Starting with a given integral point, the algorithm generates a .nite sequence of adjacent integral simplices of varying dimension and
Succinct Sampling from Discrete Distributions
DEFF Research Database (Denmark)
Bringmann, Karl; Larsen, Kasper Green
2013-01-01
We revisit the classic problem of sampling from a discrete distribution: Given n non-negative w-bit integers x_1,...,x_n, the task is to build a data structure that allows sampling i with probability proportional to x_i. The classic solution is Walker's alias method that takes, when implemented...
Symplectomorphisms and discrete braid invariants
Czechowski, Aleksander; Vandervorst, Robert
2017-01-01
Area and orientation preserving diffeomorphisms of the standard 2-disc, referred to as symplectomorphisms of D2, allow decompositions in terms of positive twist diffeomorphisms. Using the latter decomposition, we utilize the Conley index theory of discrete braid classes as introduced in Ghrist et
The remarkable discreteness of being
Indian Academy of Sciences (India)
Life is a discrete, stochastic phenomenon: for a biological organism, the time of the two most important events of its life (reproduction and death) is random and these events change the number of individuals of the species by single units. These facts can have surprising, counterintuitive consequences. I review here three ...
Discrete tomography in neutron radiography
International Nuclear Information System (INIS)
Kuba, Attila; Rodek, Lajos; Kiss, Zoltan; Rusko, Laszlo; Nagy, Antal; Balasko, Marton
2005-01-01
Discrete tomography (DT) is an imaging technique for reconstructing discrete images from their projections using the knowledge that the object to be reconstructed contains only a few homogeneous materials characterized by known discrete absorption values. One of the main reasons for applying DT is that we will hopefully require relatively few projections. Using discreteness and some a priori information (such as an approximate shape of the object) we can apply two DT methods in neutron imaging by reducing the problem to an optimization task. The first method is a special one because it is only suitable if the object is composed of cylinders and sphere shapes. The second method is a general one in the sense that it can be used for reconstructing objects of any shape. Software was developed and physical experiments performed in order to investigate the effects of several reconstruction parameters: the number of projections, noise levels, and complexity of the object to be reconstructed. We give a summary of the experimental results and make a comparison of the results obtained using a classical reconstruction technique (FBP). The programs we developed are available in our DT reconstruction program package DIRECT
Discrete elements method of neutron transport
International Nuclear Information System (INIS)
Mathews, K.A.
1988-01-01
In this paper a new neutron transport method, called discrete elements (L N ) is derived and compared to discrete ordinates methods, theoretically and by numerical experimentation. The discrete elements method is based on discretizing the Boltzmann equation over a set of elements of angle. The discrete elements method is shown to be more cost-effective than discrete ordinates, in terms of accuracy versus execution time and storage, for the cases tested. In a two-dimensional test case, a vacuum duct in a shield, the L N method is more consistently convergent toward a Monte Carlo benchmark solution
Learning-induced uncertainty reduction in perceptual decisions is task-dependent
Directory of Open Access Journals (Sweden)
Feitong eYang
2014-05-01
Full Text Available Perceptual decision making in which decisions are reached primarily from extracting and evaluating sensory information requires close interactions between the sensory system and decision-related networks in the brain. Uncertainty pervades every aspect of this process and can be considered related to either the stimulus signal or decision criterion. Here, we investigated the learning-induced reduction of both the signal and criterion uncertainty in two perceptual decision tasks based on two Glass pattern stimulus sets. This was achieved by manipulating spiral angle and signal level of radial and concentric Glass patterns. The behavioral results showed that the participants trained with a task based on criterion comparison improved their categorization accuracy for both tasks, whereas the participants who were trained on a task based on signal detection improved their categorization accuracy only on their trained task. We fitted the behavioral data with a computational model that can dissociate the contribution of the signal and criterion uncertainties. The modeling results indicated that the participants trained on the criterion comparison task reduced both the criterion and signal uncertainty. By contrast, the participants who were trained on the signal detection task only reduced their signal uncertainty after training. Our results suggest that the signal uncertainty can be resolved by training participants to extract signals from noisy environments and to discriminate between clear signals, which are evidenced by reduced perception variance after both training procedures. Conversely, the criterion uncertainty can only be resolved by the training of fine discrimination. These findings demonstrate that uncertainty in perceptual decision-making can be reduced with training but that the reduction of different types of uncertainty is task-dependent.
Sucrose-induced analgesia during early life modulates adulthood learning and memory formation.
Nuseir, Khawla Q; Alzoubi, Karem H; Alabwaini, Jehad; Khabour, Omar F; Kassab, Manal I
2015-06-01
This study is aimed at examining the long-term effects of chronic pain during early life (postnatal day 0 to 8weeks), and intervention using sucrose, on cognitive functions during adulthood in rats. Pain was induced in rat pups via needle pricks of the paws. Sucrose solution or paracetamol was administered for analgesia before the paw prick. Control groups include tactile stimulation to account for handling and touching the paws, and sucrose alone was used. All treatments were started on day one of birth and continued for 8weeks. At the end of the treatments, behavioral studies were conducted to test the spatial learning and memory using radial arm water maze (RAWM), as well as pain threshold via foot-withdrawal response to a hot plate apparatus. Additionally, the hippocampus was dissected, and blood was collected. Levels of neurotrophins (BDNF, IGF-1 and NT-3) and endorphins were assessed using ELISA. The results show that chronic noxious stimulation resulted in comparable foot-withdrawal latency between noxious and tactile groups. On the other hand, pretreatment with sucrose or paracetamol increased pain threshold significantly both in naive rats and noxiously stimulated rats (Pmemory, and sucrose treatment prevented such impairment (Pmemory impairment, and pretreatment with sucrose prevented this impairment via mechanisms that seem to involve BDNF. As evident in the results, sucrose, whether alone or in the presence of pre-noxious stimulation, increases pain threshold in such circumstances; most likely via a mechanism that involves an increase in endogenous opioids. Copyright © 2015 Elsevier Inc. All rights reserved.
Chau, Lily S; Galvez, Roberto
2012-01-01
It is widely accepted that the amygdala plays a critical role in acquisition and consolidation of fear-related memories. Some of the more widely employed behavioral paradigms that have assisted in solidifying the amygdala's role in fear-related memories are associative learning paradigms. With most associative learning tasks, a neutral conditioned stimulus (CS) is paired with a salient unconditioned stimulus (US) that elicits an unconditioned response (UR). After multiple CS-US pairings, the subject learns that the CS predicts the onset or delivery of the US, and thus elicits a learned conditioned response (CR). Most fear-related associative paradigms have suggested that an aspect of the fear association is stored in the amygdala; however, some fear-motivated associative paradigms suggest that the amygdala is not a site of storage, but rather facilitates consolidation in other brain regions. Based upon various learning theories, one of the most likely sites for storage of long-term memories is the neocortex. In support of these theories, findings from our laboratory, and others, have demonstrated that trace-conditioning, an associative paradigm where there is a separation in time between the CS and US, induces learning-specific neocortical plasticity. The following review will discuss the amygdala's involvement, either as a site of storage or facilitating storage in other brain regions such as the neocortex, in fear- and non-fear-motivated associative paradigms. In this review, we will discuss recent findings suggesting a broader role for the amygdala in increasing the saliency of behaviorally relevant information, thus facilitating acquisition for all forms of memory, both fear- and non-fear-related. This proposed promiscuous role of the amygdala in facilitating acquisition for all memories further suggests a potential role of the amygdala in general learning disabilities.
Directory of Open Access Journals (Sweden)
Lily S Chau
2012-10-01
Full Text Available It is widely accepted that the amygdala plays a critical role in acquisition and consolidation of fear-related memories. Some of the more widely employed behavioral paradigms that have assisted in solidifying the amygdala’s role in fear-related memories are associative learning paradigms. With most associative learning tasks, a neutral conditioned stimulus (CS is paired with a salient unconditioned stimulus (US that elicits an unconditioned response (UR. After multiple CS-US pairings, the subject learns that the CS predicts the onset or delivery of the US, and thus elicits a learned conditioned response (CR. Most fear-related associative paradigms have suggested that an aspect of the fear association is stored in the amygdala; however, some fear-motivated associative paradigms suggest that the amygdala is not a site of storage, but rather facilitates consolidation in other brain regions. Based upon various learning theories, one of the most likely sites for storage of long-term memories is the neocortex. In support of these theories, findings from our laboratory, and others, have demonstrated that trace-conditioning, an associative paradigm where there is a separation in time between the CS and US, induces learning-specific neocortical plasticity. The following review will discuss the amygdala’s involvement, either as a site of storage or facilitating storage in other brain regions such as the neocortex, in fear- and non-fear-motivated associative paradigms. In this review, we will discuss recent findings suggesting a broader role for the amygdala in increasing the saliency of behaviorally relevant information, thus facilitating acquisition for all forms of memory, both fear- and non-fear-related. This proposed promiscuous role of the amygdala in facilitating acquisition for all memories further suggests a potential role of the amygdala in general learning disabilities.
Discrete gauge symmetries in discrete MSSM-like orientifolds
International Nuclear Information System (INIS)
Ibáñez, L.E.; Schellekens, A.N.; Uranga, A.M.
2012-01-01
Motivated by the necessity of discrete Z N symmetries in the MSSM to insure baryon stability, we study the origin of discrete gauge symmetries from open string sector U(1)'s in orientifolds based on rational conformal field theory. By means of an explicit construction, we find an integral basis for the couplings of axions and U(1) factors for all simple current MIPFs and orientifolds of all 168 Gepner models, a total of 32 990 distinct cases. We discuss how the presence of discrete symmetries surviving as a subgroup of broken U(1)'s can be derived using this basis. We apply this procedure to models with MSSM chiral spectrum, concretely to all known U(3)×U(2)×U(1)×U(1) and U(3)×Sp(2)×U(1)×U(1) configurations with chiral bi-fundamentals, but no chiral tensors, as well as some SU(5) GUT models. We find examples of models with Z 2 (R-parity) and Z 3 symmetries that forbid certain B and/or L violating MSSM couplings. Their presence is however relatively rare, at the level of a few percent of all cases.
Positivity for Convective Semi-discretizations
Fekete, Imre; Ketcheson, David I.; Loczi, Lajos
2017-01-01
We propose a technique for investigating stability properties like positivity and forward invariance of an interval for method-of-lines discretizations, and apply the technique to study positivity preservation for a class of TVD semi-discretizations
Quantum chaos on discrete graphs
International Nuclear Information System (INIS)
Smilansky, Uzy
2007-01-01
Adapting a method developed for the study of quantum chaos on quantum (metric) graphs (Kottos and Smilansky 1997 Phys. Rev. Lett. 79 4794, Kottos and Smilansky 1999 Ann. Phys., NY 274 76), spectral ζ functions and trace formulae for discrete Laplacians on graphs are derived. This is achieved by expressing the spectral secular equation in terms of the periodic orbits of the graph and obtaining functions which belong to the class of ζ functions proposed originally by Ihara (1966 J. Mat. Soc. Japan 18 219) and expanded by subsequent authors (Stark and Terras 1996 Adv. Math. 121 124, Kotani and Sunada 2000 J. Math. Sci. Univ. Tokyo 7 7). Finally, a model of 'classical dynamics' on the discrete graph is proposed. It is analogous to the corresponding classical dynamics derived for quantum graphs (Kottos and Smilansky 1997 Phys. Rev. Lett. 79 4794, Kottos and Smilansky 1999 Ann. Phys., NY 274 76). (fast track communication)
Dark energy from discrete spacetime.
Directory of Open Access Journals (Sweden)
Aaron D Trout
Full Text Available Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, [Formula: see text] in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies.
Applied geometry and discrete mathematics
Sturm; Gritzmann, Peter; Sturmfels, Bernd
1991-01-01
This volume, published jointly with the Association for Computing Machinery, comprises a collection of research articles celebrating the occasion of Victor Klee's sixty-fifth birthday in September 1990. During his long career, Klee has made contributions to a wide variety of areas, such as discrete and computational geometry, convexity, combinatorics, graph theory, functional analysis, mathematical programming and optimization, and theoretical computer science. In addition, Klee made important contributions to mathematics education, mathematical methods in economics and the decision sciences, applications of discrete mathematics in the biological and social sciences, and the transfer of knowledge from applied mathematics to industry. In honor of Klee's achievements, this volume presents more than forty papers on topics related to Klee's research. While the majority of the papers are research articles, a number of survey articles are also included. Mirroring the breadth of Klee's mathematical contributions, th...
Emissivity of discretized diffusion problems
International Nuclear Information System (INIS)
Densmore, Jeffery D.; Davidson, Gregory; Carrington, David B.
2006-01-01
The numerical modeling of radiative transfer by the diffusion approximation can produce artificially damped radiation propagation if spatial cells are too optically thick. In this paper, we investigate this nonphysical behavior at external problem boundaries by examining the emissivity of the discretized diffusion approximation. We demonstrate that the standard cell-centered discretization produces an emissivity that is too low for optically thick cells, a situation that leads to the lack of radiation propagation. We then present a modified boundary condition that yields an accurate emissivity regardless of cell size. This modified boundary condition can be used with a deterministic calculation or as part of a hybrid transport-diffusion method for increasing the efficiency of Monte Carlo simulations. We also discuss the range of applicability, as a function of cell size and material properties, when this modified boundary condition is employed in a hybrid technique. With a set of numerical calculations, we demonstrate the accuracy and usefulness of this modified boundary condition
Discrete symmetries in the MSSM
Energy Technology Data Exchange (ETDEWEB)
Schieren, Roland
2010-12-02
The use of discrete symmetries, especially abelian ones, in physics beyond the standard model of particle physics is discussed. A method is developed how a general, abelian, discrete symmetry can be obtained via spontaneous symmetry breaking. In addition, anomalies are treated in the path integral approach with special attention to anomaly cancellation via the Green-Schwarz mechanism. All this is applied to the minimal supersymmetric standard model. A unique Z{sup R}{sub 4} symmetry is discovered which solves the {mu}-problem as well as problems with proton decay and allows to embed the standard model gauge group into a simple group, i.e. the Z{sup R}{sub 4} is compatible with grand unification. Also the flavor problem in the context of minimal flavor violation is addressed. Finally, a string theory model is presented which exhibits the mentioned Z{sup R}{sub 4} symmetry and other desirable features. (orig.)
Domain Discretization and Circle Packings
DEFF Research Database (Denmark)
Dias, Kealey
A circle packing is a configuration of circles which are tangent with one another in a prescribed pattern determined by a combinatorial triangulation, where the configuration fills a planar domain or a two-dimensional surface. The vertices in the triangulation correspond to centers of circles...... to domain discretization problems such as triangulation and unstructured mesh generation techniques. We wish to ask ourselves the question: given a cloud of points in the plane (we restrict ourselves to planar domains), is it possible to construct a circle packing preserving the positions of the vertices...... and constrained meshes having predefined vertices as constraints. A standard method of two-dimensional mesh generation involves conformal mapping of the surface or domain to standardized shapes, such as a disk. Since circle packing is a new technique for constructing discrete conformal mappings, it is possible...
Discrete Bose-Einstein spectra
International Nuclear Information System (INIS)
Vlad, Valentin I.; Ionescu-Pallas, Nicholas
2001-03-01
The Bose-Einstein energy spectrum of a quantum gas, confined in a rigid cubic box, is shown to become discrete and strongly dependent on the box geometry (size L), temperature, T and atomic mass number, A at , in the region of small γ=A at TV 1/3 . This behavior is the consequence of the random state degeneracy in the box. Furthermore, we demonstrate that the total energy does not obey the conventional law any longer, but a new law, which depends on γ and on the quantum gas fugacity. This energy law imposes a faster decrease to zero than it is classically expected, for γ→0. The lighter the gas atoms, the higher the temperatures or the box size, for the same effects in the discrete Bose-Einstein regime. (author)
Discrete symmetries in the MSSM
International Nuclear Information System (INIS)
Schieren, Roland
2010-01-01
The use of discrete symmetries, especially abelian ones, in physics beyond the standard model of particle physics is discussed. A method is developed how a general, abelian, discrete symmetry can be obtained via spontaneous symmetry breaking. In addition, anomalies are treated in the path integral approach with special attention to anomaly cancellation via the Green-Schwarz mechanism. All this is applied to the minimal supersymmetric standard model. A unique Z R 4 symmetry is discovered which solves the μ-problem as well as problems with proton decay and allows to embed the standard model gauge group into a simple group, i.e. the Z R 4 is compatible with grand unification. Also the flavor problem in the context of minimal flavor violation is addressed. Finally, a string theory model is presented which exhibits the mentioned Z R 4 symmetry and other desirable features. (orig.)
Dark energy from discrete spacetime.
Trout, Aaron D
2013-01-01
Dark energy accounts for most of the matter-energy content of our universe, yet current theories of its origin rely on radical physical assumptions such as the holographic principle or controversial anthropic arguments. We give a better motivated explanation for dark energy, claiming that it arises from a small negative scalar-curvature present even in empty spacetime. The vacuum has this curvature because spacetime is fundamentally discrete and there are more ways for a discrete geometry to have negative curvature than positive. We explicitly compute this effect using a variant of the well known dynamical-triangulations (DT) model for quantum gravity. Our model predicts a time-varying non-zero cosmological constant with a current value, [Formula: see text] in natural units, in agreement with observation. This calculation is made possible by a novel characterization of the possible DT action values combined with numerical evidence concerning their degeneracies.
Duality for discrete integrable systems
International Nuclear Information System (INIS)
Quispel, G R W; Capel, H W; Roberts, J A G
2005-01-01
A new class of discrete dynamical systems is introduced via a duality relation for discrete dynamical systems with a number of explicitly known integrals. The dual equation can be defined via the difference of an arbitrary linear combination of integrals and its upshifted version. We give an example of an integrable mapping with two parameters and four integrals leading to a (four-dimensional) dual mapping with four parameters and two integrals. We also consider a more general class of higher-dimensional mappings arising via a travelling-wave reduction from the (integrable) MKdV partial-difference equation. By differencing the trace of the monodromy matrix we obtain a class of novel dual mappings which is shown to be integrable as level-set-dependent versions of the original ones
Observability of discretized partial differential equations
Cohn, Stephen E.; Dee, Dick P.
1988-01-01
It is shown that complete observability of the discrete model used to assimilate data from a linear partial differential equation (PDE) system is necessary and sufficient for asymptotic stability of the data assimilation process. The observability theory for discrete systems is reviewed and applied to obtain simple observability tests for discretized constant-coefficient PDEs. Examples are used to show how numerical dispersion can result in discrete dynamics with multiple eigenvalues, thereby detracting from observability.
Lee, Vallent; MacKenzie, Georgina; Hooper, Andrew; Maguire, Jamie
2016-10-01
It is well established that stress impacts the underlying processes of learning and memory. The effects of stress on memory are thought to involve, at least in part, effects on the hippocampus, which is particularly vulnerable to stress. Chronic stress induces hippocampal alterations, including but not limited to dendritic atrophy and decreased neurogenesis, which are thought to contribute to chronic stress-induced hippocampal dysfunction and deficits in learning and memory. Changes in synaptic transmission, including changes in GABAergic inhibition, have been documented following chronic stress. Recently, our laboratory demonstrated shifts in EGABA in CA1 pyramidal neurons following chronic stress, compromising GABAergic transmission and increasing excitability of these neurons. Interestingly, here we demonstrate that these alterations are unique to CA1 pyramidal neurons, since we do not observe shifts in EGABA following chronic stress in dentate gyrus granule cells. Following chronic stress, there is a decrease in the expression of the GABAA receptor (GABAA R) δ subunit and tonic GABAergic inhibition in dentate gyrus granule cells, whereas there is an increase in the phasic component of GABAergic inhibition, evident by an increase in the peak amplitude of spontaneous inhibitory postsynaptic currents (sIPSCs). Given the numerous changes observed in the hippocampus following stress, it is difficult to pinpoint the pertinent contributing pathophysiological factors. Here we directly assess the impact of a reduction in tonic GABAergic inhibition of dentate gyrus granule cells on learning and memory using a mouse model with a decrease in GABAA R δ subunit expression specifically in dentate gyrus granule cells (Gabrd/Pomc mice). Reduced GABAA R δ subunit expression and function in dentate gyrus granule cells is sufficient to induce deficits in learning and memory. Collectively, these findings suggest that the reduction in GABAA R δ subunit-mediated tonic inhibition
Hooper, Andrew; Maguire, Jamie
2016-01-01
It is well established that stress impacts the underlying processes of learning and memory. The effects of stress on memory are thought to involve, at least in part, effects on the hippocampus, which is particularly vulnerable to stress. Chronic stress induces hippocampal alterations, including but not limited to dendritic atrophy and decreased neurogenesis, which are thought to contribute to chronic stress-induced hippocampal dysfunction and deficits in learning and memory. Changes in synaptic transmission, including changes in GABAergic inhibition, have been documented following chronic stress. Recently, our laboratory demonstrated shifts in EGABA in CA1 pyramidal neurons following chronic stress, compromising GABAergic transmission and increasing excitability of these neurons. Interestingly, here we demonstrate that these alterations are unique to CA1 pyramidal neurons, since we do not observe shifts in EGABA following chronic stress in dentate gyrus granule cells. Following chronic stress, there is a decrease in the expression of the GABAA receptor (GABAAR) δ subunit and tonic GABAergic inhibition in dentate gyrus granule cells; whereas, there is an increase in the phasic component of GABAergic inhibition, evident by an increase in the peak amplitude of spontaneous inhibitory postsynaptic currents (sIPSCs). Given the numerous changes observed in the hippocampus following stress, it is difficult to pinpoint the pertinent contributing pathophysiological factors. Here we directly assess the impact of a reduction in tonic GABAergic inhibition of dentate gyrus granule cells on learning and memory using a mouse model with a decrease in GABAAR δ subunit expression specifically in dentate gyrus granule cells (Gabrd/Pomc mice). Reduced GABAAR δ subunit expression and function in dentate gyrus granule cells is sufficient to induce deficits in learning and memory. Collectively, these findings suggest that the reduction in GABAAR δ subunit-mediated tonic inhibition in
Vogel, S.; Klumpers, F.; Navarro Schröder, T.; Oplaat, K.T.; Krugers, H.J.; Oitzl, M.S.; Joëls, M.; Doeller, C.F.; Fernández, G.
2017-01-01
Stress is assumed to cause a shift from flexible 'cognitive' memory to more rigid 'habit' memory. In the spatial memory domain, stress impairs place learning depending on the hippocampus whereas stimulus-response learning based on the striatum appears to be improved. While the neural basis of this
Vogel, S.; Klumpers, F.; Navarro Schröder, T.; Oplaat, K.T.; Krugers, H.J.; Oitzl, M.S.; Joëls, M.; Doeller, C.F.; Fernandez, G.
2017-01-01
Stress is assumed to cause a shift from flexible 'cognitive' memory to more rigid 'habit' memory. In the spatial memory domain, stress impairs place learning depending on the hippocampus whereas stimulus-response learning based on the striatum appears to be improved. While the neural basis of this
Vogel, Susanne; Klumpers, Floris; Schroeder, Tobias Navarro; Oplaat, Krista T.; Krugers, Harm J.; Oitzl, Melly S.; Joels, Marian; Doeller, Christian F.; Fernandez, Guillen
Stress is assumed to cause a shift from flexible 'cognitive' memory to more rigid 'habit' memory. In the spatial memory domain, stress impairs place learning depending on the hippocampus whereas stimulus-response learning based on the striatum appears to be improved. While the neural basis of this
Effective lagrangian description on discrete gauge symmetries
International Nuclear Information System (INIS)
Banks, T.
1989-01-01
We exhibit a simple low-energy lagrangian which describes a system with a discrete remnant of a spontaneously broken continuous gauge symmetry. The lagrangian gives a simple description of the effects ascribed to such systems by Krauss and Wilczek: black holes carry discrete hair and interact with cosmic strings, and wormholes cannot lead to violation of discrete gauge symmetries. (orig.)
Discrete port-Hamiltonian systems : mixed interconnections
Talasila, Viswanath; Clemente-Gallardo, J.; Schaft, A.J. van der
2005-01-01
Either from a control theoretic viewpoint or from an analysis viewpoint it is necessary to convert smooth systems to discrete systems, which can then be implemented on computers for numerical simulations. Discrete models can be obtained either by discretizing a smooth model, or by directly modeling
Discrete fractional solutions of a Legendre equation
Yılmazer, Resat
2018-01-01
One of the most popular research interests of science and engineering is the fractional calculus theory in recent times. Discrete fractional calculus has also an important position in fractional calculus. In this work, we acquire new discrete fractional solutions of the homogeneous and non homogeneous Legendre differential equation by using discrete fractional nabla operator.
From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.
De Meo, Rosanna; Bourquin, Nathalie M-P; Knebel, Jean-François; Murray, Micah M; Clarke, Stephanie
2015-09-01
Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra
Tadi, Monika; Allaman, Igor; Lengacher, Sylvain; Grenningloh, Gabriele; Magistretti, Pierre J.
2015-01-01
We examined the expression of genes related to brain energy metabolism and particularly those encoding glia (astrocyte)-specific functions in the dorsal hippocampus subsequent to learning. Context-dependent avoidance behavior was tested in mice using the step-through Inhibitory Avoidance (IA) paradigm. Animals were sacrificed 3, 9, 24, or 72 hours after training or 3 hours after retention testing. The quantitative determination of mRNA levels revealed learning-induced changes in the expression of genes thought to be involved in astrocyte-neuron metabolic coupling in a time dependent manner. Twenty four hours following IA training, an enhanced gene expression was seen, particularly for genes encoding monocarboxylate transporters 1 and 4 (MCT1, MCT4), alpha2 subunit of the Na/K-ATPase and glucose transporter type 1. To assess the functional role for one of these genes in learning, we studied MCT1 deficient mice and found that they exhibit impaired memory in the inhibitory avoidance task. Together, these observations indicate that neuron-glia metabolic coupling undergoes metabolic adaptations following learning as indicated by the change in expression of key metabolic genes.
Hu, Lili; Han, Bo; Zhao, Xiaoge; Mi, Lihua; Song, Qiang; Wang, Jue; Song, Tusheng; Huang, Chen
2016-04-13
Chronic scream sounds during adulthood affect spatial learning and memory, both of which are sexually dimorphic. The long-term effects of chronic early postnatal scream sound stress (SSS) during postnatal days 1-21 (P1-P21) on spatial learning and memory in adult mice as well as whether or not these effects are sexually dimorphic are unknown. Therefore, the present study examines the performance of adult male and female mice in the Morris water maze following exposure to chronic early postnatal SSS. Hippocampal NR2A and NR2B levels as well as NR2A/NR2B subunit ratios were tested using immunohistochemistry. In the Morris water maze, stress males showed greater impairment in spatial learning and memory than background males; by contrast, stress and background females performed equally well. NR2B levels in CA1 and CA3 were upregulated, whereas NR2A/NR2B ratios were downregulated in stressed males, but not in females. These data suggest that chronic early postnatal SSS influences spatial learning and memory ability, levels of hippocampal NR2B, and NR2A/NR2B ratios in adult males. Moreover, chronic early stress-induced alterations exert long-lasting effects and appear to affect performance in a sex-specific manner.
Directory of Open Access Journals (Sweden)
Monika Tadi
Full Text Available We examined the expression of genes related to brain energy metabolism and particularly those encoding glia (astrocyte-specific functions in the dorsal hippocampus subsequent to learning. Context-dependent avoidance behavior was tested in mice using the step-through Inhibitory Avoidance (IA paradigm. Animals were sacrificed 3, 9, 24, or 72 hours after training or 3 hours after retention testing. The quantitative determination of mRNA levels revealed learning-induced changes in the expression of genes thought to be involved in astrocyte-neuron metabolic coupling in a time dependent manner. Twenty four hours following IA training, an enhanced gene expression was seen, particularly for genes encoding monocarboxylate transporters 1 and 4 (MCT1, MCT4, alpha2 subunit of the Na/K-ATPase and glucose transporter type 1. To assess the functional role for one of these genes in learning, we studied MCT1 deficient mice and found that they exhibit impaired memory in the inhibitory avoidance task. Together, these observations indicate that neuron-glia metabolic coupling undergoes metabolic adaptations following learning as indicated by the change in expression of key metabolic genes.
Tadi, Monika
2015-10-29
We examined the expression of genes related to brain energy metabolism and particularly those encoding glia (astrocyte)-specific functions in the dorsal hippocampus subsequent to learning. Context-dependent avoidance behavior was tested in mice using the step-through Inhibitory Avoidance (IA) paradigm. Animals were sacrificed 3, 9, 24, or 72 hours after training or 3 hours after retention testing. The quantitative determination of mRNA levels revealed learning-induced changes in the expression of genes thought to be involved in astrocyte-neuron metabolic coupling in a time dependent manner. Twenty four hours following IA training, an enhanced gene expression was seen, particularly for genes encoding monocarboxylate transporters 1 and 4 (MCT1, MCT4), alpha2 subunit of the Na/K-ATPase and glucose transporter type 1. To assess the functional role for one of these genes in learning, we studied MCT1 deficient mice and found that they exhibit impaired memory in the inhibitory avoidance task. Together, these observations indicate that neuron-glia metabolic coupling undergoes metabolic adaptations following learning as indicated by the change in expression of key metabolic genes.
Continuous versus discrete structures II -- Discrete Hamiltonian systems and Helmholtz conditions
Cresson, Jacky; Pierret, Frédéric
2015-01-01
We define discrete Hamiltonian systems in the framework of discrete embeddings. An explicit comparison with previous attempts is given. We then solve the discrete Helmholtz's inverse problem for the discrete calculus of variation in the Hamiltonian setting. Several applications are discussed.
Asymptotic behavior of discrete holomorphic maps z^c, log(z) and discrete Painleve transcedents
Agafonov, S. I.
2005-01-01
It is shown that discrete analogs of z^c and log(z) have the same asymptotic behavior as their smooth counterparts. These discrete maps are described in terms of special solutions of discrete Painleve-II equations, asymptotics of these solutions providing the behaviour of discrete z^c and log(z) at infinity.
International Nuclear Information System (INIS)
Zhang Yufeng; Fan Engui; Zhang Yongqing
2006-01-01
With the help of two semi-direct sum Lie algebras, an efficient way to construct discrete integrable couplings is proposed. As its applications, the discrete integrable couplings of the Toda-type lattice equations are obtained. The approach can be devoted to establishing other discrete integrable couplings of the discrete lattice integrable hierarchies of evolution equations
Zechendorf, Elisabeth; Vaßen, Phillip; Zhang, Jieyi; Hallawa, Ahmed; Martincuks, Antons; Krenkel, Oliver; Müller-Newen, Gerhard; Schuerholz, Tobias; Simon, Tim-Philipp; Marx, Gernot; Ascheid, Gerd; Schmeink, Anke; Dartmann, Guido; Thiemermann, Christoph; Martin, Lukas
2018-01-01
Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical- In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p machine learning algorithms.
Thaut, Michael H; Peterson, David A; McIntosh, Gerald C; Hoemberg, Volker
2014-01-01
Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during music-assisted learning. Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG) in alpha and beta frequency bands in 54 patients with MS. The study sample was randomly divided into two groups, either hearing a spoken or a musical (sung) presentation of Rey's auditory verbal learning test. We defined the "learning-related synchronization" (LRS) as the percent change in EEG spectral power from the first time the word was presented to the average of the subsequent word encoding trials. LRS differed significantly between the music and the spoken conditions in low alpha and upper beta bands. Patients in the music condition showed overall better word memory and better word order memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. The evidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization in prefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicit in musical stimuli enhances "deep encoding" during verbal learning and sharpens the timing of neural dynamics in brain networks degraded by demyelination in MS.
Directory of Open Access Journals (Sweden)
Michael eThaut
2014-06-01
Full Text Available Recent research in music and brain function has suggested that the temporal pattern structure in music andrhythm can enhance cognitive functions. To further elucidate this question specifically for memory weinvestigated if a musical template can enhance verbal learning in patients with multiple sclerosis and ifmusic assisted learning will also influence short-term, system-level brain plasticity. We measuredsystems-level brain activity with oscillatory network synchronization during music assisted learning.Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG in alpha andbeta frequency bands in 54 patients with multiple sclerosis (MS. The study sample was randomlydivided into 2 groups, either hearing a spoken or musical (sung presentation of Rey’s Auditory VerbalLearning Test (RAVLT. We defined the learning-related synchronization (LRS as the percent changein EEG spectral power from the first time the word was presented to the average of the subsequent wordencoding trials. LRS differed significantly between the music and spoken conditions in low alpha andupper beta bands. Patients in the music condition showed overall better word memory and better wordorder memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. Theevidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization inprefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicitin musical stimuli enhances ‘deep encoding’ during verbal learning and sharpens the timing of neuraldynamics in brain networks degraded by demyelination in MS
Cuspidal discrete series for projective hyperbolic spaces
DEFF Research Database (Denmark)
Andersen, Nils Byrial; Flensted-Jensen, Mogens
2013-01-01
Abstract. We have in [1] proposed a definition of cusp forms on semisimple symmetric spaces G/H, involving the notion of a Radon transform and a related Abel transform. For the real non-Riemannian hyperbolic spaces, we showed that there exists an infinite number of cuspidal discrete series......, and at most finitely many non-cuspidal discrete series, including in particular the spherical discrete series. For the projective spaces, the spherical discrete series are the only non-cuspidal discrete series. Below, we extend these results to the other hyperbolic spaces, and we also study the question...
Space-Time Discrete KPZ Equation
Cannizzaro, G.; Matetski, K.
2018-03-01
We study a general family of space-time discretizations of the KPZ equation and show that they converge to its solution. The approach we follow makes use of basic elements of the theory of regularity structures (Hairer in Invent Math 198(2):269-504, 2014) as well as its discrete counterpart (Hairer and Matetski in Discretizations of rough stochastic PDEs, 2015. arXiv:1511.06937). Since the discretization is in both space and time and we allow non-standard discretization for the product, the methods mentioned above have to be suitably modified in order to accommodate the structure of the models under study.
Pintana, Hiranya; Apaijai, Nattayaporn; Pratchayasakul, Wasana; Chattipakorn, Nipon; Chattipakorn, Siriporn C
2012-10-05
Metformin is a first line drug for the treatment of type 2 diabetes mellitus (T2DM). Our previous study reported that high-fat diet (HFD) consumption caused not only peripheral and neuronal insulin resistance, but also induced brain mitochondrial dysfunction as well as learning impairment. However, the effects of metformin on learning behavior and brain mitochondrial functions in HFD-induced insulin resistant rats have never been investigated. Thirty-two male Wistar rats were divided into two groups to receive either a normal diet (ND) or a high-fat diet (HFD) for 12weeks. Then, rats in each group were divided into two treatment groups to receive either vehicle or metformin (15mg/kg BW twice daily) for 21days. All rats were tested for cognitive behaviors using the Morris water maze (MWM) test, and blood samples were collected for the determination of glucose, insulin, and malondialdehyde. At the end of the study, animals were euthanized and the brain was removed for studying brain mitochondrial function and brain oxidative stress. We found that in the HFD group, metformin significantly attenuated the insulin resistant condition by improving metabolic parameters, decreasing peripheral and brain oxidative stress levels, and improving learning behavior, compared to the vehicle-treated group. Furthermore, metformin completely prevented brain mitochondrial dysfunction caused by long-term HFD consumption. Our findings suggest that metformin effectively improves peripheral insulin sensitivity, prevents brain mitochondrial dysfunction, and completely restores learning behavior, which were all impaired by long-term HFD consumption. Copyright © 2012 Elsevier Inc. All rights reserved.
Modeling Anti-Air Warfare With Discrete Event Simulation and Analyzing Naval Convoy Operations
2016-06-01
W., & Scheaffer, R. L. (2008). Mathematical statistics with applications . Belmont, CA: Cengage Learning. 118 THIS PAGE INTENTIONALLY LEFT BLANK...WARFARE WITH DISCRETE EVENT SIMULATION AND ANALYZING NAVAL CONVOY OPERATIONS by Ali E. Opcin June 2016 Thesis Advisor: Arnold H. Buss Co...REPORT DATE June 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE MODELING ANTI-AIR WARFARE WITH DISCRETE EVENT
Integrable discretizations of the short pulse equation
International Nuclear Information System (INIS)
Feng Baofeng; Maruno, Ken-ichi; Ohta, Yasuhiro
2010-01-01
In this paper, we propose integrable semi-discrete and full-discrete analogues of the short pulse (SP) equation. The key construction is the bilinear form and determinant structure of solutions of the SP equation. We also give the determinant formulas of N-soliton solutions of the semi-discrete and full-discrete analogues of the SP equations, from which the multi-loop and multi-breather solutions can be generated. In the continuous limit, the full-discrete SP equation converges to the semi-discrete SP equation, and then to the continuous SP equation. Based on the semi-discrete SP equation, an integrable numerical scheme, i.e. a self-adaptive moving mesh scheme, is proposed and used for the numerical computation of the short pulse equation.
Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker
2014-01-01
Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during ...
Directory of Open Access Journals (Sweden)
Yusuke Furukawa
2016-07-01
Full Text Available Gamma-aminobutyric acid (GABA, the major inhibitory neurotransmitter in the mammalian central nervous system, is also known to be important for brain development. Therefore, disturbances of GABA receptor (GABA-R mediated signaling (GABA-R signal during brain development may influence normal brain maturation and cause late-onset brain malfunctions. In this study, we examined whether the temporal stimulation of the GABA-R signal during brain development induces late-onset adverse effects on the brain in adult male mice. To stimulate the GABA-R signal, we used either the benzodiazepine sleep-inducing drug triazolam (TZ or the non-benzodiazepine drug zolpidem (ZP. We detected deficits in learning and memory in mice treated with TZ during the juvenile period, as seen in the fear conditioning test. On the other hand, ZP administration during the juvenile period had little effect. In addition, decreased protein expression of GluR1 and GluR4, which are excitatory neurotransmitter receptors, was detected in the hippocampi of mice treated with TZ during the juvenile period. We measured mRNA expression of the immediate early genes (IEGs, which are neuronal activity markers, in the hippocampus shortly after the administration of TZ or ZP to juvenile mice. Decreased IEG expression was detected in mice with juvenile TZ administration, but not in mice with juvenile ZP administration. Our findings demonstrate that TZ administration during the juvenile period can induce irreversible brain dysfunction in adult mice. It may need to take an extra care for the prescription of benzodiazepine sleep-inducing drugs to juveniles because it might cause late onset learning and memory defects.
Suzuki, Ayumi; Iinuma, Mitsuo; Hayashi, Sakurako; Sato, Yuichi; Azuma, Kagaku; Kubo, Kin-Ya
2016-11-15
Maternal chewing during prenatal stress attenuates both the development of stress-induced learning deficits and decreased cell proliferation in mouse hippocampal dentate gyrus. Hippocampal myelination affects spatial memory and the synaptic structure is a key mediator of neuronal communication. We investigated whether maternal chewing during prenatal stress ameliorates stress-induced alterations of hippocampal myelin and synapses, and impaired development of spatial memory in adult offspring. Pregnant mice were divided into control, stress, and stress/chewing groups. Stress was induced by placing mice in a ventilated restraint tube, and was initiated on day 12 of pregnancy and continued until delivery. Mice in the stress/chewing group were given a wooden stick to chew during restraint. In 1-month-old pups, spatial memory was assessed in the Morris water maze, and hippocampal oligodendrocytes and synapses in CA1 were assayed by immunohistochemistry and electron microscopy. Prenatal stress led to impaired learning ability, and decreased immunoreactivity of myelin basic protein (MBP) and 2',3'-cyclic nucleotide 3'-phosphodiesterase (CNPase) in the hippocampal CA1 in adult offspring. Numerous myelin sheath abnormalities were observed. The G-ratio [axonal diameter to axonal fiber diameter (axon plus myelin sheath)] was increased and postsynaptic density length was decreased in the hippocampal CA1 region. Maternal chewing during stress attenuated the prenatal stress-induced impairment of spatial memory, and the decreased MBP and CNPase immunoreactivity, increased G-ratios, and decreased postsynaptic-density length in the hippocampal CA1 region. These findings suggest that chewing during prenatal stress in dams could be an effective coping strategy to prevent hippocampal behavioral and morphologic impairments in their offspring. Copyright © 2016 Elsevier B.V. All rights reserved.
Discrete geometric structures for architecture
Pottmann, Helmut
2010-06-13
The emergence of freeform structures in contemporary architecture raises numerous challenging research problems, most of which are related to the actual fabrication and are a rich source of research topics in geometry and geometric computing. The talk will provide an overview of recent progress in this field, with a particular focus on discrete geometric structures. Most of these result from practical requirements on segmenting a freeform shape into planar panels and on the physical realization of supporting beams and nodes. A study of quadrilateral meshes with planar faces reveals beautiful relations to discrete differential geometry. In particular, we discuss meshes which discretize the network of principal curvature lines. Conical meshes are among these meshes; they possess conical offset meshes at a constant face/face distance, which in turn leads to a supporting beam layout with so-called torsion free nodes. This work can be generalized to a variety of multilayer structures and laid the ground for an adapted curvature theory for these meshes. There are also efforts on segmenting surfaces into planar hexagonal panels. Though these are less constrained than planar quadrilateral panels, this problem is still waiting for an elegant solution. Inspired by freeform designs in architecture which involve circles and spheres, we present a new kind of triangle mesh whose faces\\' in-circles form a packing, i.e., the in-circles of two triangles with a common edge have the same contact point on that edge. These "circle packing (CP) meshes" exhibit an aesthetic balance of shape and size of their faces. They are closely tied to sphere packings on surfaces and to various remarkable structures and patterns which are of interest in art, architecture, and design. CP meshes constitute a new link between architectural freeform design and computational conformal geometry. Recently, certain timber structures motivated us to study discrete patterns of geodesics on surfaces. This
Radiative transfer on discrete spaces
Preisendorfer, Rudolph W; Stark, M; Ulam, S
1965-01-01
Pure and Applied Mathematics, Volume 74: Radiative Transfer on Discrete Spaces presents the geometrical structure of natural light fields. This book describes in detail with mathematical precision the radiometric interactions of light-scattering media in terms of a few well established principles.Organized into four parts encompassing 15 chapters, this volume begins with an overview of the derivations of the practical formulas and the arrangement of formulas leading to numerical solution procedures of radiative transfer problems in plane-parallel media. This text then constructs radiative tran
Thaut, Michael H.; Peterson, David A.; McIntosh, Gerald C.; Hoemberg, Volker
2014-01-01
Recent research on music and brain function has suggested that the temporal pattern structure in music and rhythm can enhance cognitive functions. To further elucidate this question specifically for memory, we investigated if a musical template can enhance verbal learning in patients with multiple sclerosis (MS) and if music-assisted learning will also influence short-term, system-level brain plasticity. We measured systems-level brain activity with oscillatory network synchronization during music-assisted learning. Specifically, we measured the spectral power of 128-channel electroencephalogram (EEG) in alpha and beta frequency bands in 54 patients with MS. The study sample was randomly divided into two groups, either hearing a spoken or a musical (sung) presentation of Rey’s auditory verbal learning test. We defined the “learning-related synchronization” (LRS) as the percent change in EEG spectral power from the first time the word was presented to the average of the subsequent word encoding trials. LRS differed significantly between the music and the spoken conditions in low alpha and upper beta bands. Patients in the music condition showed overall better word memory and better word order memory and stronger bilateral frontal alpha LRS than patients in the spoken condition. The evidence suggests that a musical mnemonic recruits stronger oscillatory network synchronization in prefrontal areas in MS patients during word learning. It is suggested that the temporal structure implicit in musical stimuli enhances “deep encoding” during verbal learning and sharpens the timing of neural dynamics in brain networks degraded by demyelination in MS. PMID:24982626
Gentine, P.; Alemohammad, S. H.
2018-04-01
Solar-induced fluorescence (SIF) observations from space have resulted in major advancements in estimating gross primary productivity (GPP). However, current SIF observations remain spatially coarse, infrequent, and noisy. Here we develop a machine learning approach using surface reflectances from Moderate Resolution Imaging Spectroradiometer (MODIS) channels to reproduce SIF normalized by clear sky surface irradiance from the Global Ozone Monitoring Experiment-2 (GOME-2). The resulting product is a proxy for ecosystem photosynthetically active radiation absorbed by chlorophyll (fAPARCh). Multiplying this new product with a MODIS estimate of photosynthetically active radiation provides a new MODIS-only reconstruction of SIF called Reconstructed SIF (RSIF). RSIF exhibits much higher seasonal and interannual correlation than the original SIF when compared with eddy covariance estimates of GPP and two reference global GPP products, especially in dry and cold regions. RSIF also reproduces intense productivity regions such as the U.S. Corn Belt contrary to typical vegetation indices and similarly to SIF.
Li, Hong-Shi; Ke, Jie; Zhao, Gui-Zhi; Wu, Li-An; Kou, Jun-Ping; Liu, Hong-Chen
2015-07-20
. Astrocytes activation showed the opposite trend in hippocampus dentate gyrus (DG). Treatment with DSS could restore the impaired abilities on ETM-induced decrease of learning and memory behavior. The decreased spines density in the hippocampus and astrocytes activation in DG of hippocampus in the ETM group rats may be related with the decline of the ability of learning and memory. The ability to change the synaptic plasticity in hippocampus after DSS administration may be correlated with the alleviation of impairment of learn and memory after ETM treatment.
Institute of Scientific and Technical Information of China (English)
Hong-Shi Li; Jie Ke; Gui-Zhi Zhao; Li-An Wu; Jun-Ping Kou; Hong-Chen Liu
2015-01-01
.Astrocytes activation showed the opposite trend in hippocampus dentate gyrus (DG).Conclusions:Treatment with DSS could restore the impaired abilities on ETM-induced decrease of learning and memory behavior.The decreased spines density in the hippocampus and astrocytes activation in DG of hippocampus in the ETM group rats may be related with the decline of the ability of learning and memory.The ability to change the synaptic plasticity in hippocampus after DSS administration may be correlated with the alleviation of impairment of learn and memory after ETM treatment.
Directory of Open Access Journals (Sweden)
Mohsen Laabidi
2014-01-01
Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.
3-D discrete analytical ridgelet transform.
Helbert, David; Carré, Philippe; Andres, Eric
2006-12-01
In this paper, we propose an implementation of the 3-D Ridgelet transform: the 3-D discrete analytical Ridgelet transform (3-D DART). This transform uses the Fourier strategy for the computation of the associated 3-D discrete Radon transform. The innovative step is the definition of a discrete 3-D transform with the discrete analytical geometry theory by the construction of 3-D discrete analytical lines in the Fourier domain. We propose two types of 3-D discrete lines: 3-D discrete radial lines going through the origin defined from their orthogonal projections and 3-D planes covered with 2-D discrete line segments. These discrete analytical lines have a parameter called arithmetical thickness, allowing us to define a 3-D DART adapted to a specific application. Indeed, the 3-D DART representation is not orthogonal, It is associated with a flexible redundancy factor. The 3-D DART has a very simple forward/inverse algorithm that provides an exact reconstruction without any iterative method. In order to illustrate the potentiality of this new discrete transform, we apply the 3-D DART and its extension to the Local-DART (with smooth windowing) to the denoising of 3-D image and color video. These experimental results show that the simple thresholding of the 3-D DART coefficients is efficient.
Matrix metalloproteinase (MMP) 9 transcription in mouse brain induced by fear learning.
Ganguly, Krishnendu; Rejmak, Emilia; Mikosz, Marta; Nikolaev, Evgeni; Knapska, Ewelina; Kaczmarek, Leszek
2013-07-19
Memory formation requires learning-based molecular and structural changes in neurons, whereas matrix metalloproteinase (MMP) 9 is involved in the synaptic plasticity by cleaving extracellular matrix proteins and, thus, is associated with learning processes in the mammalian brain. Because the mechanisms of MMP-9 transcription in the brain are poorly understood, this study aimed to elucidate regulation of MMP-9 gene expression in the mouse brain after fear learning. We show here that contextual fear conditioning markedly increases MMP-9 transcription, followed by enhanced enzymatic levels in the three major brain structures implicated in fear learning, i.e. the amygdala, hippocampus, and prefrontal cortex. To reveal the role of AP-1 transcription factor in MMP-9 gene expression, we have used reporter gene constructs with specifically mutated AP-1 gene promoter sites. The constructs were introduced into the medial prefrontal cortex of neonatal mouse pups by electroporation, and the regulation of MMP-9 transcription was studied after contextual fear conditioning in the adult animals. Specifically, -42/-50- and -478/-486-bp AP-1 binding motifs of the mouse MMP-9 promoter sequence have been found to play a major role in MMP-9 gene activation. Furthermore, increases in MMP-9 gene promoter binding by the AP-1 transcription factor proteins c-Fos and c-Jun have been demonstrated in all three brain structures under investigation. Hence, our results suggest that AP-1 acts as a positive regulator of MMP-9 transcription in the brain following fear learning.
Motor learning induces plastic changes in Purkinje cell dendritic spines in the rat cerebellum.
González-Tapia, D; González-Ramírez, M M; Vázquez-Hernández, N; González-Burgos, I
2017-12-14
The paramedian lobule of the cerebellum is involved in learning to correctly perform motor skills through practice. Dendritic spines are dynamic structures that regulate excitatory synaptic stimulation. We studied plastic changes occurring in the dendritic spines of Purkinje cells from the paramedian lobule of rats during motor learning. Adult male rats were trained over a 6-day period using an acrobatic motor learning paradigm; the density and type of dendritic spines were determined every day during the study period using a modified version of the Golgi method. The learning curve reflected a considerable decrease in the number of errors made by rats as the training period progressed. We observed more dendritic spines on days 2 and 6, particularly more thin spines on days 1, 3, and 6, fewer mushroom spines on day 3, fewer stubby spines on day 1, and more thick spines on days 4 and 6. The initial stage of motor learning may be associated with fast processing of the underlying synaptic information combined with an apparent "silencing" of memory consolidation processes, based on the regulation of the neuronal excitability. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.
Toward Optimal Manifold Hashing via Discrete Locally Linear Embedding.
Rongrong Ji; Hong Liu; Liujuan Cao; Di Liu; Yongjian Wu; Feiyue Huang
2017-11-01
Binary code learning, also known as hashing, has received increasing attention in large-scale visual search. By transforming high-dimensional features to binary codes, the original Euclidean distance is approximated via Hamming distance. More recently, it is advocated that it is the manifold distance, rather than the Euclidean distance, that should be preserved in the Hamming space. However, it retains as an open problem to directly preserve the manifold structure by hashing. In particular, it first needs to build the local linear embedding in the original feature space, and then quantize such embedding to binary codes. Such a two-step coding is problematic and less optimized. Besides, the off-line learning is extremely time and memory consuming, which needs to calculate the similarity matrix of the original data. In this paper, we propose a novel hashing algorithm, termed discrete locality linear embedding hashing (DLLH), which well addresses the above challenges. The DLLH directly reconstructs the manifold structure in the Hamming space, which learns optimal hash codes to maintain the local linear relationship of data points. To learn discrete locally linear embeddingcodes, we further propose a discrete optimization algorithm with an iterative parameters updating scheme. Moreover, an anchor-based acceleration scheme, termed Anchor-DLLH, is further introduced, which approximates the large similarity matrix by the product of two low-rank matrices. Experimental results on three widely used benchmark data sets, i.e., CIFAR10, NUS-WIDE, and YouTube Face, have shown superior performance of the proposed DLLH over the state-of-the-art approaches.
K-theory for discrete subgroups of the Lorentz groups
International Nuclear Information System (INIS)
Schwalbe, D.A.
1986-01-01
In the thesis, a conjecture on the structure of the topological K theory groups associated to an action of a discrete group on a manifold is verified in the special case when the group is a closed discrete subgroup of a Lorentz group. The K theory is the topological K theory of the reduced crossed product C algebra arising from the action of a countable discrete group acting by diffeomorphisms on a smooth, Hausdorf, and second and countable manifold. The proof uses the geometric K theory of Baum and Connes. In this situation, they have developed a geometrically realized K theory which they conjecture to be isomorphic to the analytic K theory. Work of Kasparov is used to show the geometric K groups and the analytic K groups are isomorphic for actions of the Lorentz groups on a manifold. Work of Marc Rieffel on Morita equivalence of C/sup */ algebras, shows the analytic K theory for a closed discrete subgroup of a Lie group acting on a manifold is isomorphic to the K theory of the Lie group itself, acting on an induced manifold
Baydas, Giyasettin; Koz, Sema T; Tuzcu, Mehmet; Nedzvetsky, Victor S; Etem, Ebru
2007-05-01
In this study, we suggest that chronic maternal hyperhomocysteinemia results in learning deficits in the offspring due to delayed brain maturation and altered expression pattern of neural cell adhesion molecule. Although the deleterious effects of hyperhomocysteinemia were extensively investigated in the adults, there is no clear evidence suggesting its action on the developing fetal rat brain and cognitive functions of the offspring. Therefore, in the present work we aimed to investigate effects of maternal hyperhomocysteinemia on the fetal brain development and on the behavior of the offspring. A group of pregnant rats received daily methionine (1 g/kg body weight) dissolved in drinking water to induce maternal hyperhomocysteinemia, starting in the beginning of gestational day 0. The levels of glial fibrillary acidic protein, S100B protein, and neural cell adhesion molecule were determined in the tissue samples from the pups. Learning and memory performances of the young-adult offsprings were tested using Morris water maze test. There were significant reductions in the expressions of glial fibrillary acidic protein and S100B protein in the brains of maternally hyperhomocysteinemic pups on postnatal day 1, suggesting that hyperhomocysteinemia delays brain maturation. In conclusion, maternal hyperhomocysteinemia changes the expression pattern of neural cell adhesion molecule and therefore leads to an impairment in the learning performance of the offspring.
Han, Huili; Peng, Yan; Dong, Zhifang
2015-06-01
It is well known that bidirectional glia-neuron interactions play important roles in the neurophysiological and neuropathological processes. It is reported that impairing glial functions with sodium fluoroacetate (FAC) impaired hippocampal long-term depression (LTD) and spatial memory retrieval. However, it remains unknown whether FAC impairs hippocampal long-term potentiation (LTP) and learning and/or memory, and if so, whether pharmacological treatment with exogenous d-serine can recuse the impairment. Here, we reported that systemic administration of FAC (3mg/kg, i.p.) before training resulted in dramatic impairments of spatial learning and memory in water maze and fear memory in contextual fear conditioning. Furthermore, the behavioral deficits were accompanied by impaired LTP induction in the hippocampal CA1 area of brain slices. More importantly, exogenous d-serine treatment succeeded in recusing the deficits of hippocampal LTP and learning and memory induced by FAC. Together, these results suggest that astrocytic d-serine may be essential for hippocampal synaptic plasticity and memory, and that alteration of its levels may be relevant to the induction and potentially treatment of psychiatric and neurological disorders. Copyright © 2015 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Parisa Hasanein
2010-04-01
Full Text Available "n Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Background: Ascorbic acid improves cognitive impairments in several experimental models. Diabetes causes learning and memory deficits. In this study we hypothesized that chronic treatment with ascorbic acid (100mg/kg, p.o would affect on the passive avoidance learning (PAL and memory in control and streptozocin-induced diabetic rats."n"nMethods: Diabetes was induced by a single i.p. injection of STZ (60mg/kg. The rats were considered diabetic if plasma glucose levels exceeded 250mg/dl on three days after STZ injection. Treatment was begun at the onset of hyperglycemia. PAL was assessed 30 days later. Retention test was done 24 h after training. At the end, animals were weighted and blood samples were drawn for plasma glucose measurement."n"nResults: Diabetes caused impairment in acquisition and retrieval processes of PAL and memory in rats. Ascorbic acid treatment improved learning and memory in control rats and reversed learning and memory deficits in diabetic rats. Ascorbic acid administration also improved the body weight loss and hyperglycemia of diabetics. Hypoglycemic and antioxidant properties of the vitamin may be involved in the memory improving effects of such treatment."n"nConclusion: These results show that
Zhao, H; Ji, Z-H; Liu, C; Yu, X-Y
2015-04-02
Studies demonstrated that chronic high-dose homocysteine administration induced learning and memory impairment in animals. Atractylenolide III (Aen-III), a neuroprotective constituent of Atractylodis macrocephalae Koidz, was isolated in our previous study. In this study, we investigated potential benefits of Aen-III in preventing learning and memory impairment following chronic high-dose homocysteine administration in rats. Results showed that administration of Aen-III significantly ameliorated learning and memory impairment induced by chronic high-dose homocysteine administration in rats, decreased homocysteine-induced reactive oxygen species (ROS) formation and restored homocysteine-induced decrease of phosphorylated protein kinase C expression level. Moreover, Aen-III protected primary cultured neurons from apoptotic death induced by homocysteine treatment. This study provides the first evidence for the neuroprotective effect of Aen-III in preventing learning and impairment induced by chronic administration of homocysteine. Aen-III may have therapeutic potential in treating homocysteine-mediated cognitive impairment and neuronal injury. Copyright © 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
Meng, Qinghe; Lian, Yuzheng; Jiang, Jianjun; Wang, Wei; Hou, Xiaohong; Pan, Yao; Chu, Hongqian; Shang, Lanqin; Wei, Xuetao; Hao, Weidong
2018-04-18
Ambient light has a vital impact on mood and cognitive functions. Blue light has been previously reported to play a salient role in the antidepressant effect via melanopsin. Whether blue light filtered white light (BFW) affects mood and cognitive functions remains unclear. The present study aimed to investigate whether BFW led to depression-like symptoms and cognitive deficits including spatial learning and memory abilities in rats, and whether they were associated with the light-responsive function in retinal explants. Male Sprague-Dawley albino rats were randomly divided into 2 groups (n = 10) and treated with a white light-emitting diode (LED) light source and BFW light source, respectively, under a standard 12 : 12 h L/D condition over 30 days. The sucrose consumption test, forced swim test (FST) and the level of plasma corticosterone (CORT) were employed to evaluate depression-like symptoms in rats. Cognitive functions were assessed by the Morris water maze (MWM) test. A multi-electrode array (MEA) system was utilized to measure electro-retinogram (ERG) responses induced by white or BFW flashes. The effect of BFW over 30 days on depression-like responses in rats was indicated by decreased sucrose consumption in the sucrose consumption test, an increased immobility time in the FST and an elevated level of plasma CORT. BFW led to temporary spatial learning deficits in rats, which was evidenced by prolonged escape latency and swimming distances in the spatial navigation test. However, no changes were observed in the short memory ability of rats treated with BFW. The micro-ERG results showed a delayed implicit time and reduced amplitudes evoked by BFW flashes compared to the white flash group. BFW induces depression-like symptoms and temporary spatial learning deficits in rats, which might be closely related to the impairment of light-evoked output signals in the retina.
Effects of Wuling capsule on learning and memory disorder induced by post-stroke depression in rats
Directory of Open Access Journals (Sweden)
Zhong-chun LI
2011-06-01
Full Text Available Objective To evaluate the effects of Wuling capsule on learning and memory disorder induced by post-troke depression(PSD in rats,and examine the relationship between the changes in cognitive function and the expression of brain-derived neurotrophic factor(BDNF in hippocampus.Methods Forty male adult SD rats were randomly divided into four groups(10 each: untreated control group,model group,escitalopram treatment group and Wuling treatment group.All rats,except those in the untreated control group,underwent a paradigm of 3-week consecutive chronic unpredictable mild stress(CMS followed by selective right middle cerebral artery embolism to induce PSD.The sucrose preference was introduced to evaluate the level of depression and the spatial learning,and memory functions were detected using Morris water maze test.The expression of BDNF was analyzed by Western blotting.Results The cognitive function and hippocampal BDNF expression were significantly lower in model rats than in the untreated control group and the two treatment groups(P < 0.05.When escitalopram was administered once daily to the model rats at a dose of 0.2mg/(kg·d for 21 days along with the procedure of CMS,the depressed behavior was improved with BDNF protein expression rose from 0.41±0.07 to 0.86±0.09.Similar effects were found after treatment with Wuling capsule [100mg/(kg·d],except that the lower BDNF expression was not changed.Conclusion Wuling capsule can improve the learning and memory function in PSD rats,bat this effect is not related to the changes in BDNF expression in hippocampus.
Error-Induced Learning as a Resource-Adaptive Process in Young and Elderly Individuals
Ferdinand, Nicola K.; Weiten, Anja; Mecklinger, Axel; Kray, Jutta
Thorndike described in his law of effect [44] that actions followed by positive events are more likely to be repeated in the future, whereas actions that are followed by negative outcomes are less likely to be repeated. This implies that behavior is evaluated in the light of its potential consequences, and non-reward events (i.e., errors) must be detected for reinforcement learning to take place. In short, humans have to monitor their performance in order to detect and correct errors, and this allows them to successfully adapt their behavior to changing environmental demands and acquire new behavior, i.e., to learn.
Developing Enterprise E-Learning at Kodak.
Gold, Martha
2003-01-01
The third in a five-part series of case studies on enterprisewide electronic learning describes how Kodak's approach to a global learning management system integrated 80 discrete human resource systems into one. (JOW)
Ouchi, Hirofumi; Ono, Kazuya; Murakami, Yukihisa; Matsumoto, Kinzo
2013-02-01
Social isolation of rodents (SI) elicits a variety of stress responses such as increased aggressiveness, hyper-locomotion, and reduced susceptibility to pentobarbital. To obtain a better understanding of the relevance of SI-induced behavioral abnormalities to psychiatric disorders, we examined the effect of SI on latent learning as an index of spatial attention, and discussed the availability of SI as an epigenetic model of attention deficit hyperactivity disorder (ADHD). Except in specially stated cases, 4-week-old male mice were housed in a group or socially isolated for 3-70 days before experiments. The animals socially isolated for 1 week or more exhibited spatial attention deficit in the water-finding test. Re-socialized rearing for 5 weeks after 1-week SI failed to attenuate the spatial attention deficit. The effect of SI on spatial attention showed no gender difference or correlation with increased aggressive behavior. Moreover, SI had no effect on cognitive performance elucidated in a modified Y-maze or an object recognition test, but it significantly impaired contextual and conditional fear memory elucidated in the fear-conditioning test. Drugs used for ADHD therapy, methylphenidate (1-10 mg/kg, i.p.) and caffeine (0.5-1 mg/kg, i.p.), improved SI-induced latent learning deficit in a manner reversible with cholinergic but not dopaminergic antagonists. Considering the behavioral features of SI mice together with their susceptibility to ADHD drugs, the present findings suggest that SI provides an epigenetic animal model of ADHD and that central cholinergic systems play a role in the effect of methylphenidate on SI-induced spatial attention deficit. Copyright © 2012 Elsevier B.V. All rights reserved.
Learning Visual Forward Models to Compensate for Self-Induced Image Motion.
Ghadirzadeh, A.; Kootstra, G.W.; Maki, A.; Björkman, M.
2014-01-01
Predicting the sensory consequences of an agent's own actions is considered an important skill for intelligent behavior. In terms of vision, so-called visual forward models can be applied to learn such predictions. This is no trivial task given the high-dimensionality of sensory data and complex
Demographically Induced Variation in Students' Beliefs about Learning and Studying German.
Chavez, Monika
1995-01-01
Examines how the demographic values of foreign travel, previous foreign-language learning, major field of study, and other factors affect students' beliefs about the study of German. The article focuses on student-perceived improvement in the four skills and cultural knowledge, student motivation, and the expected contributions of teachers and…
Integrating Machine Learning into a Crowdsourced Model for Earthquake-Induced Damage Assessment
Rebbapragada, Umaa; Oommen, Thomas
2011-01-01
On January 12th, 2010, a catastrophic 7.0M earthquake devastated the country of Haiti. In the aftermath of an earthquake, it is important to rapidly assess damaged areas in order to mobilize the appropriate resources. The Haiti damage assessment effort introduced a promising model that uses crowdsourcing to map damaged areas in freely available remotely-sensed data. This paper proposes the application of machine learning methods to improve this model. Specifically, we apply work on learning from multiple, imperfect experts to the assessment of volunteer reliability, and propose the use of image segmentation to automate the detection of damaged areas. We wrap both tasks in an active learning framework in order to shift volunteer effort from mapping a full catalog of images to the generation of high-quality training data. We hypothesize that the integration of machine learning into this model improves its reliability, maintains the speed of damage assessment, and allows the model to scale to higher data volumes.
Induced lexical categories enhance cross-situational learning of word meanings
Alishahi, A.; Chrupala, Grzegorz
2014-01-01
In this paper we bring together two sources of information that have been proposed as clues used by children acquiring word meanings. One mechanism is cross-situational learning which exploits co-occurrences between words and their referents in perceptual context accompanying utterances. The other
Inevitable randomness in discrete mathematics
Beck, Jozsef
2009-01-01
Mathematics has been called the science of order. The subject is remarkably good for generalizing specific cases to create abstract theories. However, mathematics has little to say when faced with highly complex systems, where disorder reigns. This disorder can be found in pure mathematical arenas, such as the distribution of primes, the 3n+1 conjecture, and class field theory. The purpose of this book is to provide examples--and rigorous proofs--of the complexity law: (1) discrete systems are either simple or they exhibit advanced pseudorandomness; (2) a priori probabilities often exist even when there is no intrinsic symmetry. Part of the difficulty in achieving this purpose is in trying to clarify these vague statements. The examples turn out to be fascinating instances of deep or mysterious results in number theory and combinatorics. This book considers randomness and complexity. The traditional approach to complexity--computational complexity theory--is to study very general complexity classes, such as P...
Quantum evolution by discrete measurements
International Nuclear Information System (INIS)
Roa, L; Guevara, M L Ladron de; Delgado, A; Olivares-RenterIa, G; Klimov, A B
2007-01-01
In this article we review two ways of driving a quantum system to a known pure state via a sequence discrete of von Neumann measurements. The first of them assumes that the initial state of the system is unknown, and the evolution is attained only with the help of two non-commuting observables. For this method, the overall success probability is maximized when the eigentstates of the involved observables constitute mutually unbiased bases. The second method assumes the initial state is known and it uses N observables which are consecutively measured to make the state of the system approach the target state. The probability of success of this procedure converges to 1 as the number of observables increases
Quantum evolution by discrete measurements
Energy Technology Data Exchange (ETDEWEB)
Roa, L [Center for Quantum Optics and Quantum Information, Departamento de Fisica, Universidad de Concepcion, Casilla 160-C, Concepcion (Chile); Guevara, M L Ladron de [Departamento de Fisica, Universidad Catolica del Norte, Casilla 1280, Antofagasta (Chile); Delgado, A [Center for Quantum Optics and Quantum Information, Departamento de Fisica, Universidad de Concepcion, Casilla 160-C, Concepcion (Chile); Olivares-RenterIa, G [Center for Quantum Optics and Quantum Information, Departamento de Fisica, Universidad de Concepcion, Casilla 160-C, Concepcion (Chile); Klimov, A B [Departamento de Fisica, Universidad de Guadalajara, Revolucion 1500, 44420 Guadalajara, Jalisco (Mexico)
2007-10-15
In this article we review two ways of driving a quantum system to a known pure state via a sequence discrete of von Neumann measurements. The first of them assumes that the initial state of the system is unknown, and the evolution is attained only with the help of two non-commuting observables. For this method, the overall success probability is maximized when the eigentstates of the involved observables constitute mutually unbiased bases. The second method assumes the initial state is known and it uses N observables which are consecutively measured to make the state of the system approach the target state. The probability of success of this procedure converges to 1 as the number of observables increases.
Discrete stochastic processes and applications
Collet, Jean-François
2018-01-01
This unique text for beginning graduate students gives a self-contained introduction to the mathematical properties of stochastics and presents their applications to Markov processes, coding theory, population dynamics, and search engine design. The book is ideal for a newly designed course in an introduction to probability and information theory. Prerequisites include working knowledge of linear algebra, calculus, and probability theory. The first part of the text focuses on the rigorous theory of Markov processes on countable spaces (Markov chains) and provides the basis to developing solid probabilistic intuition without the need for a course in measure theory. The approach taken is gradual beginning with the case of discrete time and moving on to that of continuous time. The second part of this text is more applied; its core introduces various uses of convexity in probability and presents a nice treatment of entropy.
Discrete calculus methods for counting
Mariconda, Carlo
2016-01-01
This book provides an introduction to combinatorics, finite calculus, formal series, recurrences, and approximations of sums. Readers will find not only coverage of the basic elements of the subjects but also deep insights into a range of less common topics rarely considered within a single book, such as counting with occupancy constraints, a clear distinction between algebraic and analytical properties of formal power series, an introduction to discrete dynamical systems with a thorough description of Sarkovskii’s theorem, symbolic calculus, and a complete description of the Euler-Maclaurin formulas and their applications. Although several books touch on one or more of these aspects, precious few cover all of them. The authors, both pure mathematicians, have attempted to develop methods that will allow the student to formulate a given problem in a precise mathematical framework. The aim is to equip readers with a sound strategy for classifying and solving problems by pursuing a mathematically rigorous yet ...
Modeling discrete competitive facility location
Karakitsiou, Athanasia
2015-01-01
This book presents an up-to-date review of modeling and optimization approaches for location problems along with a new bi-level programming methodology which captures the effect of competition of both producers and customers on facility location decisions. While many optimization approaches simplify location problems by assuming decision making in isolation, this monograph focuses on models which take into account the competitive environment in which such decisions are made. New insights in modeling, algorithmic and theoretical possibilities are opened by this approach and new applications are possible. Competition on equal term plus competition between market leader and followers are considered in this study, consequently bi-level optimization methodology is emphasized and further developed. This book provides insights regarding modeling complexity and algorithmic approaches to discrete competitive location problems. In traditional location modeling, assignment of customer demands to supply sources are made ...
Discrete modelling of drapery systems
Thoeni, Klaus; Giacomini, Anna
2016-04-01
Drapery systems are an efficient and cost-effective measure in preventing and controlling rockfall hazards on rock slopes. The simplest form consists of a row of ground anchors along the top of the slope connected to a horizontal support cable from which a wire mesh is suspended down the face of the slope. Such systems are generally referred to as simple or unsecured draperies (Badger and Duffy 2012). Variations such as secured draperies, where a pattern of ground anchors is incorporated within the field of the mesh, and hybrid systems, where the upper part of an unsecured drapery is elevated to intercept rockfalls originating upslope of the installation, are becoming more and more popular. This work presents a discrete element framework for simulation of unsecured drapery systems and its variations. The numerical model is based on the classical discrete element method (DEM) and implemented into the open-source framework YADE (Šmilauer et al., 2010). The model takes all relevant interactions between block, drapery and slope into account (Thoeni et al., 2014) and was calibrated and validated based on full-scale experiments (Giacomini et al., 2012).The block is modelled as a rigid clump made of spherical particles which allows any shape to be approximated. The drapery is represented by a set of spherical particle with remote interactions. The behaviour of the remote interactions is governed by the constitutive behaviour of the wire and generally corresponds to a piecewise linear stress-strain relation (Thoeni et al., 2013). The same concept is used to model wire ropes. The rock slope is represented by rigid triangular elements where material properties (e.g., normal coefficient of restitution, friction angle) are assigned to each triangle. The capabilities of the developed model to simulate drapery systems and estimate the residual hazard involved with such systems is shown. References Badger, T.C., Duffy, J.D. (2012) Drapery systems. In: Turner, A.K., Schuster R
Learnings from the Monitoring of Induced Seismicity in Western Canada over the Past Three Years
Yenier, E.; Moores, A. O.; Baturan, D.; Spriggs, N.
2017-12-01
In response to induced seismicity observed in western Canada, existing public networks have been densified and a number of private networks have been deployed to closely monitor the earthquakes induced by hydraulic fracturing operations in the region. These networks have produced an unprecedented volume of seismic data, which can be used to map pre-existing geological structures and understand their activation mechanisms. Here, we present insights gained over the past three years from induced seismicity monitoring (ISM) for some of the most active operators in Canada. First, we discuss the benefits of high-quality ISM data sets for making operational decisions and how their value largely depends on choice of instrumentation, seismic network design and data processing techniques. Using examples from recent research studies, we illustrate the key role of robust modeling of regional source, attenuation and site attributes on the accuracy of event magnitudes, ground motion estimates and induced seismicity hazard assessment. Finally, acknowledging that the ultimate goal of ISM networks is assisting operators to manage induced seismic risk, we share some examples of how ISM data products can be integrated into existing protocols for developing effective risk management strategies.
Brus, Maïna; Trouillet, Anne-Charlotte; Hellier, Vincent; Bakker, Julie
2016-08-01
Odors processed by the main and accessory olfactory bulbs (MOB, AOB) are important for sexual behavior. Interestingly, both structures continue to receive new neurons during adulthood. A role for olfactory neurogenesis in sexual behavior in female mice has recently been shown and gonadal hormones such as estradiol can modulate adult neurogenesis. Therefore, we wanted to determine the role of estradiol in learning the odors of sexual partners and in the adult neurogenesis of female aromatase knockout mice (ArKO), unable to produce estradiol. Female wild-type (WT) and ArKO mice were exposed to male odors during 7 days, and olfactory preferences, cell proliferation, cell survival and functional involvement of newborn neurons were analyzed, using BrdU injections, in combination with a marker of cell activation (Zif268) and neuronal fate (doublecortin, NeuN). Behavioral tasks indicated that both WT and ArKO females were able to discriminate between the odors of two different males, but ArKO mice failed to learn the familiar male odor. Proliferation of newborn cells was reduced in ArKO mice only in the dentate gyrus of the hippocampus. Olfactory exposure decreased cell survival in the AOB in WT females, suggesting a role for estradiol in a structure involved in sexual behavior. Finally, newborn neurons do not seem to be functionally involved in the AOB of ArKO mice compared with WT, when females were exposed to the odor of a familiar male, suggesting that estradiol-induced neurogenesis in the AOB is required for the learning of the male odor in female mice. Aromatase knockout mice (ArKO) presented deficits in olfactory preferences without affecting their olfactory discrimination abilities, and showed no functional involvement of newborn neurons in the accessory olfactory bulb (AOB) in response to the odor of a familiar male. These results suggest that estradiol-induced neurogenesis in the female AOB is required for the learning of the male odor. © 2016 International
Zhang, Lei; Zhao, Qi; Chen, Chun-Hai; Qin, Qi-Zhong; Zhou, Zhou; Yu, Zheng-Ping
2014-09-01
This study aimed to investigate the protective effect of rutin against trimethyltin-induced spatial learning and memory impairment in mice. This study focused on the role of synaptophysin, growth-associated protein 43 and the action of the dopaminergic system in mechanisms associated with rutin protection and trimethyltin-induced spatial learning and memory impairment. Cognitive learning and memory was measured by Morris Water Maze. The expression of synaptophysin and growth-associated protein 43 in hippocampus was analyzed by western blot. The concentrations of dopamine, homovanillic acid, and dihyroxyphenylacetic acid in hippocampus were detected using reversed phase high-performance liquid chromatography with electrochemical detection. Trimethyltin-induced spatial learning impairment showed a dose-dependent mode. Synaptophysin but not growth-associated protein 43 was decreased in the hippocampus after trimethyltin administration. The concentration of dopamine decreased, while homovanillic acid increased in the hippocampus after trimethyltin administration. Mice pretreated with 20 mg/kg of rutin for 7 consecutive days exhibited improved water maze performance. Moreover, rutin pretreatment reversed the decrease of synaptophysin expression and dopamine alteration. These results suggest that rutin may protect against spatial memory impairment induced by trimethyltin. Synaptophysin and the dopaminergic system may be involved in trimethyltin-induced neuronal damage in hippocampus.
Experimentally-induced learned helplessness in adolescents with type 1 diabetes.
McLaughlin, Elizabeth; Lefaivre, Marie-josée; Cummings, Elizabeth
2010-05-01
To determine whether adolescents with type 1 diabetes are more at risk for learned helplessness than their healthy peers. Twenty-three adolescents with diabetes and 25 controls completed a solvable or unsolvable concept formation task. All completed pre- and post-task performance and attribution ratings, and later completed an anagram-solving task to determine if perceived helplessness on the first task would negatively impact performance on the second. Participants in the unsolvable condition solved fewer anagrams; those with diabetes did not show weaker performance than controls. Participants in the solvable condition (diabetes and controls) showed an increase in internal attributions from before the concept formation task to after. In the unsolvable condition, only participants with diabetes made more external attributions for their failure. Contrary to the only other controlled study to use this paradigm in youth with chronic illness, adolescents with diabetes were not more susceptible to learned helplessness.
Diuk, Carlos; Tsai, Karin; Wallis, Jonathan; Botvinick, Matthew; Niv, Yael
2013-03-27
Studies suggest that dopaminergic neurons report a unitary, global reward prediction error signal. However, learning in complex real-life tasks, in particular tasks that show hierarchical structure, requires multiple prediction errors that may coincide in time. We used functional neuroimaging to measure prediction error signals in humans performing such a hierarchical task involving simultaneous, uncorrelated prediction errors. Analysis of signals in a priori anatomical regions of interest in the ventral striatum and the ventral tegmental area indeed evidenced two simultaneous, but separable, prediction error signals corresponding to the two levels of hierarchy in the task. This result suggests that suitably designed tasks may reveal a more intricate pattern of firing in dopaminergic neurons. Moreover, the need for downstream separation of these signals implies possible limitations on the number of different task levels that we can learn about simultaneously.
Enhancing Decision-Making in STSE Education by Inducing Reflection and Self-Regulated Learning
Gresch, Helge; Hasselhorn, Marcus; Bögeholz, Susanne
2017-02-01
Thoughtful decision-making to resolve socioscientific issues is central to science, technology, society, and environment (STSE) education. One approach for attaining this goal involves fostering students' decision-making processes. Thus, the present study explores whether the application of decision-making strategies, combined with reflections on the decision-making processes of others, enhances decision-making competence. In addition, this study examines whether this process is supported by elements of self-regulated learning, i.e., self-reflection regarding one's own performance and the setting of goals for subsequent tasks. A computer-based training program which involves the resolution of socioscientific issues related to sustainable development was developed in two versions: with and without elements of self-regulated learning. Its effects on decision-making competence were analyzed using a pre test-post test follow-up control-group design ( N = 242 high school students). Decision-making competence was assessed using an open-ended questionnaire that focused on three facets: consideration of advantages and disadvantages, metadecision aspects, and reflection on the decision-making processes of others. The findings suggest that students in both training groups incorporated aspects of metadecision into their statements more often than students in the control group. Furthermore, both training groups were more successful in reflecting on the decision-making processes of others. The students who received additional training in self-regulated learning showed greater benefits in terms of metadecision aspects and reflection, and these effects remained significant two months later. Overall, our findings demonstrate that the application of decision-making strategies, combined with reflections on the decision-making process and elements of self-regulated learning, is a fruitful approach in STSE education.
Leuner, Benedetta; Waddell, Jaylyn; Gould, Elizabeth; Shors, Tracey J.
2012-01-01
Some, but not all, types of learning and memory can influence neurogenesis in the adult hippocampus. Trace eyeblink conditioning has been shown to enhance the survival of new neurons, whereas delay eyeblink conditioning has no such effect. The key difference between the two training procedures is that the conditioning stimuli are separated in time during trace but not delay conditioning. These findings raise the question of whether temporal discontiguity is necessary for enhancing the survival of new neurons. Here we used two approaches to test this hypothesis. First, we examined the influence of a delay conditioning task in which the duration of the conditioned stimulus (CS) was increased nearly twofold, a procedure that critically engages the hippocampus. Although the CS and unconditioned stimulus are contiguous, this very long delay conditioning procedure increased the number of new neurons that survived. Second, we examined the influence of learning the trace conditioned response (CR) after having acquired the CR during delay conditioning, a procedure that renders trace conditioning hippocampal-independent. In this case, trace conditioning did not enhance the survival of new neurons. Together, these results demonstrate that associative learning increases the survival of new neurons in the adult hippocampus, regardless of temporal contiguity. PMID:17192426
Directory of Open Access Journals (Sweden)
Ming Xiong
2014-05-01
Full Text Available Propofol is a general anesthetic widely used in surgical procedures, including those in pregnant women. Preclinical studies suggest that propofol may cause neuronal injury to the offspring of primates if it is administered during pregnancy. However, it is unknown whether those neuronal changes would lead to long-term behavioral deficits in the offspring. In this study, propofol (0.4 mg/kg/min, IV, 2 h, saline, or intralipid solution was administered to pregnant rats on gestational day 18. We detected increased levels of cleaved caspase-3 in fetal brain at 6 h after propofol exposure. The neuronal density of the hippocampus of offspring was reduced significantly on postnatal day 10 (P10 and P28. Synaptophysin levels were also significantly reduced on P28. Furthermore, exploratory and learning behaviors of offspring rats (started at P28 were assessed in open-field trial and eight-arm radial maze. The offspring from propofol-treated dams showed significantly less exploratory activity in the open-field test and less spatial learning in the eight-arm radial maze. Thus, this study suggested that propofol exposure during pregnancy in rat increased cleaved caspsase-3 levels in fetal brain, deletion of neurons, reduced synaptophysin levels in the hippocampal region, and persistent learning deficits in the offspring.
Directory of Open Access Journals (Sweden)
Lin Lin
2018-03-01
Full Text Available DPP6 is well known as an auxiliary subunit of Kv4-containing, A-type K+ channels which regulate dendritic excitability in hippocampal CA1 pyramidal neurons. We have recently reported, however, a novel role for DPP6 in regulating dendritic filopodia formation and stability, affecting synaptic development and function. These results are notable considering recent clinical findings associating DPP6 with neurodevelopmental and intellectual disorders. Here we assessed the behavioral consequences of DPP6 loss. We found that DPP6 knockout (DPP6-KO mice are impaired in hippocampus-dependent learning and memory. Results from the Morris water maze and T-maze tasks showed that DPP6-KO mice exhibit slower learning and reduced memory performance. DPP6 mouse brain weight is reduced throughout development compared with WT, and in vitro imaging results indicated that DPP6 loss affects synaptic structure and motility. Taken together, these results show impaired synaptic development along with spatial learning and memory deficiencies in DPP6-KO mice.
Nonlinear wave propagation in discrete and continuous systems
Rothos, V. M.
2016-09-01
In this review we try to capture some of the recent excitement induced by a large volume of theoretical and computational studies addressing nonlinear Schrödinger models (discrete and continuous) and the localized structures that they support. We focus on some prototypical structures, namely the breather solutions and solitary waves. In particular, we investigate the bifurcation of travelling wave solution in Discrete NLS system applying dynamical systems methods. Next, we examine the combined effects of cubic and quintic terms of the long range type in the dynamics of a double well potential. The relevant bifurcations, the stability of the branches and their dynamical implications are examined both in the reduced (ODE) and in the full (PDE) setting. We also offer an outlook on interesting possibilities for future work on this theme.
A Discrete Spectral Problem and Related Hierarchy of Discrete Hamiltonian Lattice Equations
International Nuclear Information System (INIS)
Xu Xixiang; Cao Weili
2007-01-01
Staring from a discrete matrix spectral problem, a hierarchy of lattice soliton equations is presented though discrete zero curvature representation. The resulting lattice soliton equations possess non-local Lax pairs. The Hamiltonian structures are established for the resulting hierarchy by the discrete trace identity. Liouville integrability of resulting hierarchy is demonstrated.
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.
Directory of Open Access Journals (Sweden)
Miriam Annika Vogt
2014-11-01
Full Text Available The cyclic AMP (cAMP-response element binding protein (CREB is an activity-dependent transcription factor playing a role in synaptic plasticity, learning and memory, and emotional behavior. However, the impact of Creb ablation on rodent behavior is vague as e.g. memory performance of different Creb mutant mice depends on the specific type of mutation per se but additionally on the background and learning protocol differences. Here we present the first targeted ablation of CREB induced during adulthood selectively in principal forebrain neurons in a pure background strain of C57BL/6 mice. All hippocampal principal neurons exhibited lack of CREB expression. Mutant mice showed a severe anxiety phenotype in the openfield and novel object exploration test as well as in the Dark-Light Box Test, but unaltered hippocampus-dependent long-term memory in the Morris water maze and in context dependent fear conditioning. On the molecular level, CREB ablation led to CREM up regulation in the hippocampus and frontal cortex which may at least in part compensate for the loss of CREB. BDNF, a postulated CREB target gene, was down regulated in the frontal lobe but not in the hippocampus; neurogenesis remained unaltered. Our data indicate that in the adult mouse forebrain the late onset of CREB ablation can, in case of memory functionality, be compensated for and is not essential for memory consolidation and retrieval during adulthood. In contrast, the presence of CREB protein during adulthood seems to be pivotal for the regulation of emotional behavior.
Geometry and Hamiltonian mechanics on discrete spaces
International Nuclear Information System (INIS)
Talasila, V; Clemente-Gallardo, J; Schaft, A J van der
2004-01-01
Numerical simulation is often crucial for analysing the behaviour of many complex systems which do not admit analytic solutions. To this end, one either converts a 'smooth' model into a discrete (in space and time) model, or models systems directly at a discrete level. The goal of this paper is to provide a discrete analogue of differential geometry, and to define on these discrete models a formal discrete Hamiltonian structure-in doing so we try to bring together various fundamental concepts from numerical analysis, differential geometry, algebraic geometry, simplicial homology and classical Hamiltonian mechanics. For example, the concept of a twisted derivation is borrowed from algebraic geometry for developing a discrete calculus. The theory is applied to a nonlinear pendulum and we compare the dynamics obtained through a discrete modelling approach with the dynamics obtained via the usual discretization procedures. Also an example of an energy-conserving algorithm on a simple harmonic oscillator is presented, and its effect on the Poisson structure is discussed
Cuspidal discrete series for semisimple symmetric spaces
DEFF Research Database (Denmark)
Andersen, Nils Byrial; Flensted-Jensen, Mogens; Schlichtkrull, Henrik
2012-01-01
We propose a notion of cusp forms on semisimple symmetric spaces. We then study the real hyperbolic spaces in detail, and show that there exists both cuspidal and non-cuspidal discrete series. In particular, we show that all the spherical discrete series are non-cuspidal. (C) 2012 Elsevier Inc. All...
Discrete Riccati equation solutions: Distributed algorithms
Directory of Open Access Journals (Sweden)
D. G. Lainiotis
1996-01-01
Full Text Available In this paper new distributed algorithms for the solution of the discrete Riccati equation are introduced. The algorithms are used to provide robust and computational efficient solutions to the discrete Riccati equation. The proposed distributed algorithms are theoretically interesting and computationally attractive.
Painleve test and discrete Boltzmann equations
International Nuclear Information System (INIS)
Euler, N.; Steeb, W.H.
1989-01-01
The Painleve test for various discrete Boltzmann equations is performed. The connection with integrability is discussed. Furthermore the Lie symmetry vector fields are derived and group-theoretical reduction of the discrete Boltzmann equations to ordinary differentiable equations is performed. Lie Backlund transformations are gained by performing the Painleve analysis for the ordinary differential equations. 16 refs
Variance Swap Replication: Discrete or Continuous?
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Fabien Le Floc’h
2018-02-01
Full Text Available The popular replication formula to price variance swaps assumes continuity of traded option strikes. In practice, however, there is only a discrete set of option strikes traded on the market. We present here different discrete replication strategies and explain why the continuous replication price is more relevant.
Discretization vs. Rounding Error in Euler's Method
Borges, Carlos F.
2011-01-01
Euler's method for solving initial value problems is an excellent vehicle for observing the relationship between discretization error and rounding error in numerical computation. Reductions in stepsize, in order to decrease discretization error, necessarily increase the number of steps and so introduce additional rounding error. The problem is…
Discrete/PWM Ballast-Resistor Controller
King, Roger J.
1994-01-01
Circuit offers low switching loss and automatic compensation for failure of ballast resistor. Discrete/PWM ballast-resistor controller improved shunt voltage-regulator circuit designed to supply power from high-resistance source to low-impedance bus. Provides both coarse discrete voltage levels (by switching of ballast resistors) and continuous fine control of voltage via pulse-width modulation.
Current Density and Continuity in Discretized Models
Boykin, Timothy B.; Luisier, Mathieu; Klimeck, Gerhard
2010-01-01
Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schrodinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying…
Geometry and Hamiltonian mechanics on discrete spaces
Talasila, V.; Clemente-Gallardo, J.; Schaft, A.J. van der
2004-01-01
Numerical simulation is often crucial for analysing the behaviour of many complex systems which do not admit analytic solutions. To this end, one either converts a ‘smooth’ model into a discrete (in space and time) model, or models systems directly at a discrete level. The goal of this paper is to
Geometry and Hamiltonian mechanics on discrete spaces
Talasila, V.; Clemente Gallardo, J.J.; Clemente-Gallardo, J.; van der Schaft, Arjan
2004-01-01
Numerical simulation is often crucial for analysing the behaviour of many complex systems which do not admit analytic solutions. To this end, one either converts a 'smooth' model into a discrete (in space and time) model, or models systems directly at a discrete level. The goal of this paper is to
Discrete mathematics in the high school curriculum
Anderson, I.; Asch, van A.G.; van Lint, J.H.
2004-01-01
In this paper we present some topics from the field of discrete mathematics which might be suitable for the high school curriculum. These topics yield both easy to understand challenging problems and important applications of discrete mathematics. We choose elements from number theory and various
Discrete Fourier analysis of multigrid algorithms
van der Vegt, Jacobus J.W.; Rhebergen, Sander
2011-01-01
The main topic of this report is a detailed discussion of the discrete Fourier multilevel analysis of multigrid algorithms. First, a brief overview of multigrid methods is given for discretizations of both linear and nonlinear partial differential equations. Special attention is given to the
Directory of Open Access Journals (Sweden)
Takenobu Katagiri, PhD
2015-05-01
Full Text Available Bone morphogenetic protein (BMP was originally discovered by Marshall Urist a half century ago following the observation of a unique activity that induced heterotopic bone formation in skeletal muscle tissue. The molecular mechanisms underlying the induction of heterotopic bone formation in skeletal muscle by BMPs were elucidated through the purification and molecular cloning of BMPs and identification of their functional receptors and downstream effectors, as well as from genetic disorders related to BMP activity. BMPs are important regulators of not only skeletal development and regeneration but also the homeostasis of normal skeletal muscle mass. There is still much to learn about the physiology and pathology at the interface of BMPs and skeletal muscle.
Involvement of nitrergic system of CA1in harmane induced learning and memory deficits.
Nasehi, Mohammad; Piri, Morteza; Abdollahian, Mojgan; Zarrindast, Mohammad Reza
2013-01-17
Harmane (HA) is a β-carboline alkaloid derived from the Peganum harmala plant which induces memory impairment. On the other hand some of the investigations showed that β-carboline alkaloids inhibit NO production. Thus, the aim of the present study was to investigate the role of nitrergic system of the dorsal hippocampus (CA1) in HA-induced amnesia in male adult mice. One-trial step-down passive avoidance and hole-board apparatuses were used for the assessment of memory retrieval and exploratory behaviors respectively. The data indicated that pre-training intraperitoneal (i.p.) administration of HA (12 and 16 mg/kg) decreased memory acquisition. Sole pre-training or pre-testing administration of L-NAME, a nitric oxide synthesis inhibitor (5, 10 and 15 μg/mice, intra-CA1) did not alter memory retrieval. On the other hand, pre-training (10 and 15 μg/mice, intra-CA1) and pre-testing (5, 10 μg/mice, intra-CA1) injections of L-NAME restored HA-induced amnesia (16 mg/kg, i.p.). Furthermore, neither sole pre-training nor pre-testing administration of l-arginine, a NO precursor (3, 6 and 9 μg/mice, intra-CA1), altered memory retrieval. In addition, pre-testing (6 and 9 μg/mice, intra-CA1), but not pre-training, injection of l-arginine increased HA-induced amnesia (16 mg/kg, i.p.). These results suggest that the nitrergic system of CA1 is involved in HA-induced amnesia. Copyright © 2012 Elsevier Inc. All rights reserved.
Directory of Open Access Journals (Sweden)
Takashi Ochiai
Full Text Available BACKGROUND: Coordinated movement in social animal groups via social learning facilitates foraging activity. Few studies have examined the behavioral cause-and-effect between group members that mediates this social learning. METHODOLOGY/PRINCIPAL FINDINGS: We first established a behavioral paradigm for visual food learning using medaka fish and demonstrated that a single fish can learn to associate a visual cue with a food reward. Grouped medaka fish (6 fish learn to respond to the visual cue more rapidly than a single fish, indicating that medaka fish undergo social learning. We then established a data-mining method based on Kullback-Leibler divergence (KLD to search for candidate behaviors that induce alignment and found that high-speed movement of a focal fish tended to induce alignment of the other members locally and transiently under free-swimming conditions without presentation of a visual cue. The high-speed movement of the informed and trained fish during visual cue presentation appeared to facilitate the alignment of naïve fish in response to some visual cues, thereby mediating social learning. Compared with naïve fish, the informed fish had a higher tendency to induce alignment of other naïve fish under free-swimming conditions without visual cue presentation, suggesting the involvement of individual recognition in social learning. CONCLUSIONS/SIGNIFICANCE: Behavioral cause-and-effect studies of the high-speed movement between fish group members will contribute to our understanding of the dynamics of social behaviors. The data-mining method used in the present study is a powerful method to search for candidates factors associated with inter-individual interactions using a dataset for time-series coordinate data of individuals.
Handbook on modelling for discrete optimization
Pitsoulis, Leonidas; Williams, H
2006-01-01
The primary objective underlying the Handbook on Modelling for Discrete Optimization is to demonstrate and detail the pervasive nature of Discrete Optimization. While its applications cut across an incredibly wide range of activities, many of the applications are only known to specialists. It is the aim of this handbook to correct this. It has long been recognized that "modelling" is a critically important mathematical activity in designing algorithms for solving these discrete optimization problems. Nevertheless solving the resultant models is also often far from straightforward. In recent years it has become possible to solve many large-scale discrete optimization problems. However, some problems remain a challenge, even though advances in mathematical methods, hardware, and software technology have pushed the frontiers forward. This handbook couples the difficult, critical-thinking aspects of mathematical modeling with the hot area of discrete optimization. It will be done in an academic handbook treatment...
Discrete elements method of neutral particle transport
International Nuclear Information System (INIS)
Mathews, K.A.
1983-01-01
A new discrete elements (L/sub N/) transport method is derived and compared to the discrete ordinates S/sub N/ method, theoretically and by numerical experimentation. The discrete elements method is more accurate than discrete ordinates and strongly ameliorates ray effects for the practical problems studied. The discrete elements method is shown to be more cost effective, in terms of execution time with comparable storage to attain the same accuracy, for a one-dimensional test case using linear characteristic spatial quadrature. In a two-dimensional test case, a vacuum duct in a shield, L/sub N/ is more consistently convergent toward a Monte Carlo benchmark solution than S/sub N/, using step characteristic spatial quadrature. An analysis of the interaction of angular and spatial quadrature in xy-geometry indicates the desirability of using linear characteristic spatial quadrature with the L/sub N/ method
Spatially localized, temporally quasiperiodic, discrete nonlinear excitations
International Nuclear Information System (INIS)
Cai, D.; Bishop, A.R.; Gronbech-Jensen, N.
1995-01-01
In contrast to the commonly discussed discrete breather, which is a spatially localized, time-periodic solution, we present an exact solution of a discrete nonlinear Schroedinger breather which is a spatially localized, temporally quasiperiodic nonlinear coherent excitation. This breather is a multiple-soliton solution in the sense of the inverse scattering transform. A discrete breather of multiple frequencies is conceptually important in studies of nonlinear lattice systems. We point out that, for this breather, the incommensurability of its frequencies is a discrete lattice effect and these frequencies become commensurate in the continuum limit. To understand the dynamical properties of the breather, we also discuss its stability and its behavior in the presence of an external potential. Finally, we indicate how to obtain an exact N-soliton breather as a discrete generalization of the continuum multiple-soliton solution
Discrete breathers in graphane: Effect of temperature
Energy Technology Data Exchange (ETDEWEB)
Baimova, J. A., E-mail: julia.a.baimova@gmail.com [Russian Academy of Sciences, Institute of Metal Physics, Ural Branch (Russian Federation); Murzaev, R. T.; Lobzenko, I. P.; Dmitriev, S. V. [Russian Academy of Sciences, Institute for Metals Superplasticity Problems (Russian Federation); Zhou, Kun [Nanyang Technological University, School of Mechanical and Aerospace Engineering (Singapore)
2016-05-15
The discrete breathers in graphane in thermodynamic equilibrium in the temperature range 50–600 K are studied by molecular dynamics simulation. A discrete breather is a hydrogen atom vibrating along the normal to a sheet of graphane at a high amplitude. As was found earlier, the lifetime of a discrete breather at zero temperature corresponds to several tens of thousands of vibrations. The effect of temperature on the decay time of discrete breathers and the probability of their detachment from a sheet of graphane are studied in this work. It is shown that closely spaced breathers can exchange energy with each other at zero temperature. The data obtained suggest that thermally activated discrete breathers can be involved in the dehydrogenation of graphane, which is important for hydrogen energetics.
International Nuclear Information System (INIS)
Vazquez, Adrinel; Pena de Ortiz, Sandra
2004-01-01
The long-term storage of information in the brain known as long-term memory (LTM) depends on a variety of intracellular signaling cascades utilizing calcium (Ca 2+ ) and cyclic adenosine monophosphate as second messengers. In particular, Ca +2 /phospholipid-dependent protein kinase C (PKC) activity has been proposed to be necessary for the transition from short-term memory to LTM. Because the neurobehavioral toxicity of lead (Pb +2 ) has been associated to its interference with normal Ca +2 signaling in neurons, we studied its effects on spatial learning and memory using a hippocampal-dependent discrimination task. Adult rats received microinfusions of either Na + or Pb +2 acetate in the CA1 hippocampal subregion before each one of four training sessions. A retention test was given 7 days later to examine LTM. Results suggest that intrahippocampal Pb +2 did not affect learning of the task, but significantly impaired retention. The effects of Pb +2 selectively impaired reference memory measured in the retention test, but had no effect on the general performance because it did not affect the latency to complete the task during the test. Finally, we examined the effects of Pb +2 on the induction of hippocampal Ca +2 /phospholipid-dependent PKC activity during acquisition training. The results showed that Pb +2 interfered with the learning-induced activation of Ca +2 /phospholipid-dependent PKC on day 3 of acquisition. Overall, our results indicate that Pb +2 causes cognitive impairments in adult rats and that such effects might be subserved by interference with Ca +2 -related signaling mechanisms required for normal LTM
International Nuclear Information System (INIS)
Ding Qing
2007-01-01
We prove that the integrable-nonintegrable discrete nonlinear Schroedinger equation (AL-DNLS) introduced by Cai, Bishop and Gronbech-Jensen (Phys. Rev. Lett. 72 591(1994)) is the discrete gauge equivalent to an integrable-nonintegrable discrete Heisenberg model from the geometric point of view. Then we study whether the transmission and bifurcation properties of the AL-DNLS equation are preserved under the action of discrete gauge transformations. Our results reveal that the transmission property of the AL-DNLS equation is completely preserved and the bifurcation property is conditionally preserved to those of the integrable-nonintegrable discrete Heisenberg model
DEFF Research Database (Denmark)
Karemore, Gopal Raghunath; Mascarenhas, Kim Komal; Patil, Choudhary
2008-01-01
In the present work we discuss the potential of recently developed classification algorithm, Learning Vector Quantization (LVQ), for the analysis of Laser Induced Fluorescence (LIF) Spectra, recorded from normal and malignant bladder tissue samples. The algorithm is prototype based and inherently...
International Nuclear Information System (INIS)
Rabin, B.M.; Hunt, W.A.; Lee, J.
1987-01-01
Three experiments were run to assess the role of the area postrema in taste aversion learning resulting from combined treatment with subthreshold unconditioned stimuli and in the acquisition of an amphetamine-induced taste aversion. In the first experiment, it was shown that combined treatment with subthreshold radiation (15 rad) and subthreshold amphetamine (0.5 mg/kg, IP) resulted in the acquisition of a taste aversion. The second experiment showed that lesions of the area postrema blocked taste aversion learning produced by two subthreshold doses of amphetamine. In the third experiment, which looked at the dose-response curve for amphetamine-induced taste aversion learning in intact rats and rats with area postrema lesions, it was shown that both groups of rats acquired taste aversions following injection of amphetamine, although the rats with lesions showed a less severe aversion than the intact rats. The results are interpreted as indicating that amphetamine-induced taste aversion learning may involve area postrema-mediated mechanisms, particularly at the lower doses, but that an intact area postrema is not a necessary condition for the acquisition of an amphetamine-induced taste aversion
Memory enhancement by a semantically unrelated emotional arousal source induced after learning.
Nielson, Kristy A; Yee, Douglas; Erickson, Kirk I
2005-07-01
It has been well established that moderate physiological or emotional arousal modulates memory. However, there is some controversy about whether the source of arousal must be semantically related to the information to be remembered. To test this idea, 35 healthy young adult participants learned a list of common nouns and afterward viewed a semantically unrelated, neutral or emotionally arousing videotape. The tape was shown after learning to prevent arousal effects on encoding or attention, instead influencing memory consolidation. Heart rate increase was significantly greater in the arousal group, and negative affect was significantly less reported in the non-arousal group after the video. The arousal group remembered significantly more words than the non-arousal group at both 30 min and 24 h delays, despite comparable group memory performance prior to the arousal manipulation. These results demonstrate that emotional arousal, even from an unrelated source, is capable of modulating memory consolidation. Potential reasons for contradictory findings in some previous studies, such as the timing of "delayed" memory tests, are discussed.
Wang, Jian; Zhang, Xiangming; Wang, Ping; Wang, Xiang; Farris, Alton B; Wang, Ya
2016-06-01
Unlike terrestrial ionizing radiation, space radiation, especially galactic cosmic rays (GCR), contains high energy charged (HZE) particles with high linear energy transfer (LET). Due to a lack of epidemiologic data for high-LET radiation exposure, it is highly uncertain how high the carcinogenesis risk is for astronauts following exposure to space radiation during space missions. Therefore, using mouse models is necessary to evaluate the risk of space radiation-induced tumorigenesis; however, which mouse model is better for these studies remains uncertain. Since lung tumorigenesis is the leading cause of cancer death among both men and women, and low-LET radiation exposure increases human lung carcinogenesis, evaluating space radiation-induced lung tumorigenesis is critical to enable safe Mars missions. Here, by comparing lung tumorigenesis obtained from different mouse strains, as well as miR-21 in lung tissue/tumors and serum, we believe that wild type mice with a low spontaneous tumorigenesis background are ideal for evaluating the risk of space radiation-induced lung tumorigenesis, and circulating miR-21 from such mice model might be used as a biomarker for predicting the risk. Copyright © 2016 The Committee on Space Research (COSPAR). Published by Elsevier Ltd. All rights reserved.
Wang, Jian; Zhang, Xiangming; Wang, Ping; Wang, Xiang; Farris, Alton B.; Wang, Ya
2016-06-01
Unlike terrestrial ionizing radiation, space radiation, especially galactic cosmic rays (GCR), contains high energy charged (HZE) particles with high linear energy transfer (LET). Due to a lack of epidemiologic data for high-LET radiation exposure, it is highly uncertain how high the carcinogenesis risk is for astronauts following exposure to space radiation during space missions. Therefore, using mouse models is necessary to evaluate the risk of space radiation-induced tumorigenesis; however, which mouse model is better for these studies remains uncertain. Since lung tumorigenesis is the leading cause of cancer death among both men and women, and low-LET radiation exposure increases human lung carcinogenesis, evaluating space radiation-induced lung tumorigenesis is critical to enable safe Mars missions. Here, by comparing lung tumorigenesis obtained from different mouse strains, as well as miR-21 in lung tissue/tumors and serum, we believe that wild type mice with a low spontaneous tumorigenesis background are ideal for evaluating the risk of space radiation-induced lung tumorigenesis, and circulating miR-21 from such mice model might be used as a biomarker for predicting the risk.
Compatible Spatial Discretizations for Partial Differential Equations
Energy Technology Data Exchange (ETDEWEB)
Arnold, Douglas, N, ed.
2004-11-25
From May 11--15, 2004, the Institute for Mathematics and its Applications held a hot topics workshop on Compatible Spatial Discretizations for Partial Differential Equations. The numerical solution of partial differential equations (PDE) is a fundamental task in science and engineering. The goal of the workshop was to bring together a spectrum of scientists at the forefront of the research in the numerical solution of PDEs to discuss compatible spatial discretizations. We define compatible spatial discretizations as those that inherit or mimic fundamental properties of the PDE such as topology, conservation, symmetries, and positivity structures and maximum principles. A wide variety of discretization methods applied across a wide range of scientific and engineering applications have been designed to or found to inherit or mimic intrinsic spatial structure and reproduce fundamental properties of the solution of the continuous PDE model at the finite dimensional level. A profusion of such methods and concepts relevant to understanding them have been developed and explored: mixed finite element methods, mimetic finite differences, support operator methods, control volume methods, discrete differential forms, Whitney forms, conservative differencing, discrete Hodge operators, discrete Helmholtz decomposition, finite integration techniques, staggered grid and dual grid methods, etc. This workshop seeks to foster communication among the diverse groups of researchers designing, applying, and studying such methods as well as researchers involved in practical solution of large scale problems that may benefit from advancements in such discretizations; to help elucidate the relations between the different methods and concepts; and to generally advance our understanding in the area of compatible spatial discretization methods for PDE. Particular points of emphasis included: + Identification of intrinsic properties of PDE models that are critical for the fidelity of numerical
Rei, Damien; Mason, Xenos; Seo, Jinsoo; Gräff, Johannes; Rudenko, Andrii; Wang, Jun; Rueda, Richard; Siegert, Sandra; Cho, Sukhee; Canter, Rebecca G; Mungenast, Alison E; Deisseroth, Karl; Tsai, Li-Huei
2015-06-09
Repeated stress has been suggested to underlie learning and memory deficits via the basolateral amygdala (BLA) and the hippocampus; however, the functional contribution of BLA inputs to the hippocampus and their molecular repercussions are not well understood. Here we show that repeated stress is accompanied by generation of the Cdk5 (cyclin-dependent kinase 5)-activator p25, up-regulation and phosphorylation of glucocorticoid receptors, increased HDAC2 expression, and reduced expression of memory-related genes in the hippocampus. A combination of optogenetic and pharmacosynthetic approaches shows that BLA activation is both necessary and sufficient for stress-associated molecular changes and memory impairments. Furthermore, we show that this effect relies on direct glutamatergic projections from the BLA to the dorsal hippocampus. Finally, we show that p25 generation is necessary for the stress-induced memory dysfunction. Taken together, our data provide a neural circuit model for stress-induced hippocampal memory deficits through BLA activity-dependent p25 generation.
Kim, Hyun-Bum; Lee, Seok; Hwang, Eun-Sang; Maeng, Sungho; Park, Ji-Ho
2017-10-21
Due to the improvement of medical level, life expectancy increased. But the increased incidence of cognitive disorders is an emerging social problem. Current drugs for dementia treatment can only delay the progress rather than cure. p-Coumaric acid is a phenylpropanoic acid derived from aromatic amino acids and known as a precursor for flavonoids such as resveratrol and naringenin. It was shown to reduce oxidative stress, inhibit genotoxicity and exert neuroprotection. Based on these findings, we evaluated whether p-coumaric acid can protect scopolamine induced learning and memory impairment by measuring LTP in organotypic hippocampal slice and cognitive behaviors in rats. p-Coumaric acid dose-dependently increased the total activity of fEPSP after high frequency stimulation and attenuated scopolamine-induced blockade of fEPSP in the hippocampal CA1 area. In addition, while scopolamine shortened the step-through latency in the passive avoidance test and prolonged the latency as well as reduced the latency in the target quadrant in the Morris water maze test, co-treatment of p-coumaric acid improved avoidance memory and long-term retention of spatial memory in behavioral tests. Since p-coumaric acid improved electrophysiological and cognitive functional deterioration by scopolamine, it may have regulatory effects on central cholinergic synapses and is expected to improve cognitive problems caused by abnormality of the cholinergic nervous system. Copyright © 2017 Elsevier Inc. All rights reserved.
Rei, Damien; Mason, Xenos; Seo, Jinsoo; Gräff, Johannes; Rudenko, Andrii; Wang, Jun; Rueda, Richard; Siegert, Sandra; Cho, Sukhee; Canter, Rebecca G.; Mungenast, Alison E.; Deisseroth, Karl; Tsai, Li-Huei
2015-01-01
Repeated stress has been suggested to underlie learning and memory deficits via the basolateral amygdala (BLA) and the hippocampus; however, the functional contribution of BLA inputs to the hippocampus and their molecular repercussions are not well understood. Here we show that repeated stress is accompanied by generation of the Cdk5 (cyclin-dependent kinase 5)-activator p25, up-regulation and phosphorylation of glucocorticoid receptors, increased HDAC2 expression, and reduced expression of memory-related genes in the hippocampus. A combination of optogenetic and pharmacosynthetic approaches shows that BLA activation is both necessary and sufficient for stress-associated molecular changes and memory impairments. Furthermore, we show that this effect relies on direct glutamatergic projections from the BLA to the dorsal hippocampus. Finally, we show that p25 generation is necessary for the stress-induced memory dysfunction. Taken together, our data provide a neural circuit model for stress-induced hippocampal memory deficits through BLA activity-dependent p25 generation. PMID:25995364
Institute of Scientific and Technical Information of China (English)
YANG Zheng-qin; YANG Su-fen; YANG Jun-qing; ZHOU Qi-xin; LI Shao-lin
2007-01-01
Objective:To observe the effect of total coptis alkaloids (TCA) on β-amyloid peptide (Aβ 25-35) induced learning and memory dysfunction in rats,and to explore its mechanism.Methods:Forty male Wistar rats were randomly divided into four groups:the control group,the model group,the TCA low dose (60 mg/kg) group and the TCA high dose (120 mg/kg) group,10 in each.Aβ 25-35 (5μl,2μg/μl) was injected into bilateral hippocampi of each rat to induce learning and memory dysfunction.TCA were administered through intragavage for consecutive 15 days.Morris Water Maze test was used to assess the impairment of learning and memory;concentration of malondialdehyde (MDA) in cerebral cortex was determined by thiobarbituric acid reactive substance to indicate the level of lipid peroxidation in brain tissues;activity of manganese-superoxide dismutase (Mn-SOD) in cerebral cortex was determined by xanthine-oxidase to indicate the activity of the enzyme;and NF-κB protein expression in cerebral cortex was measured by SP immunohistochemistry.Results:(1)Morris Water Maze test showed that,during the 4 consecutive days of acquisition trials,the rats in the model group took longer latency and searching distance than those in the control group (P＜0.01),which could be shortened by high dose TCA (P＜0.05);during the spatial probe trial on the fifth day,the rats in the model group took shorter searching time and distance on the previous flat area than those in the control group (P＜O.01),which could be prolonged after TCA treatment (for low dose group,P＜0.05;for high dose group,P＜0.01).(2)Analysis of cerebral cortical tissues showed that,compared with the control group,MDA level got significantly increased and Mn-SOD activity decreased in the model group (both P＜0.01).After having been treated with TCA,the MDA level got significantly decreased (P＜0.05 and P＜O.01 respectively for low and high dose group),while relative increase of Mn-SOD activity only appeared in high dose group
Liu, Chao; Min, Su; Wei, Ke; Liu, Dong; Dong, Jun; Luo, Jie; Liu, Xiao-Bin
2012-08-25
This study explored the effect of the excitatory amino acid receptor antagonists on the impairment of learning-memory and the hyperphosphorylation of Tau protein induced by electroconvulsive shock (ECT) in depressed rats, in order to provide experimental evidence for the study on neuropsychological mechanisms improving learning and memory impairment and the clinical intervention treatment. The analysis of variance of factorial design set up two intervention factors which were the electroconvulsive shock (two level: no disposition; a course of ECT) and the excitatory amino acid receptor antagonists (three level: iv saline; iv NMDA receptor antagonist MK-801; iv AMPA receptor antagonist DNQX). Forty-eight adult Wistar-Kyoto (WKY) rats (an animal model for depressive behavior) were randomly divided into six experimental groups (n = 8 in each group): saline (iv 2 mL saline through the tail veins of WKY rats ); MK-801 (iv 2 mL 5 mg/kg MK-801 through the tail veins of WKY rats) ; DNQX (iv 2 mL 5 mg/kg DNQX through the tail veins of WKY rats ); saline + ECT (iv 2 mL saline through the tail veins of WKY rats and giving a course of ECT); MK-801 + ECT (iv 2 mL 5 mg/kg MK-801 through the tail veins of WKY rats and giving a course of ECT); DNQX + ECT (iv 2 mL 5 mg/kg DNQX through the tail veins of WKY rats and giving a course of ECT). The Morris water maze test started within 1 day after the finish of the course of ECT to evaluate learning and memory. The hippocampus was removed from rats within 1 day after the finish of Morris water maze test. The content of glutamate in the hippocampus of rats was detected by high performance liquid chromatography. The contents of Tau protein which included Tau5 (total Tau protein), p-PHF1(Ser396/404), p-AT8(Ser199/202) and p-12E8(Ser262) in the hippocampus of rats were detected by immunohistochemistry staining (SP) and Western blot. The results showed that ECT and the glutamate ionic receptor blockers (NMDA receptor antagonist MK-801 and
Zhang, Jianbin; Cai, Tongjian; Zhao, Fang; Yao, Ting; Chen, Yaoming; Liu, Xinqin; Luo, Wenjing; Chen, Jingyuan
2012-01-01
Lead (Pb) is a well-known heavy metal in nature. Pb can cause pathophysiological changes in several organ systems including central nervous system. Especially, Pb can affect intelligence development and the ability of learning and memory of children. However, the toxic effects and mechanisms of Pb on learning and memory are still unclear. To clarify the mechanisms of Pb-induced neurotoxicity in hippocampus, and its effect on learning and memory, we chose Sprague-Dawley rats (SD-rats) as experimental subjects. We used Morris water maze to verify the ability of learning and memory after Pb treatment. We used immunohistofluorescence and Western blotting to detect the level of tau phosphorylation, accumulation of α-synuclein, autophagy and related signaling molecules in hippocampus. We demonstrated that Pb can cause abnormally hyperphosphorylation of tau and accumulation of α-synuclein, and these can induce hippocampal injury and the ability of learning and memory damage. To provide the new insight into the underlying mechanisms, we showed that Grp78, ATF4, caspase-3, autophagy-related proteins were induced and highly expressed following Pb-exposure. But mTOR signaling pathway was suppressed in Pb-exposed groups. Our results showed that Pb could cause hyperphosphorylation of tau and accumulation of α-synuclein, which could induce ER stress and suppress mTOR signal pathway. These can enhance type II program death (autophgy) and type I program death (apoptosis) in hippocampus, and impair the ability of learning and memory of rats. This is the first evidence showing the novel role of autophagy in the neurotoxicity of Pb.
From discrete-time models to continuous-time, asynchronous modeling of financial markets
Boer, Katalin; Kaymak, Uzay; Spiering, Jaap
2007-01-01
Most agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modeling of financial markets. We study the behavior of a learning market maker in a market with information
From Discrete-Time Models to Continuous-Time, Asynchronous Models of Financial Markets
K. Boer-Sorban (Katalin); U. Kaymak (Uzay); J. Spiering (Jaap)
2006-01-01
textabstractMost agent-based simulation models of financial markets are discrete-time in nature. In this paper, we investigate to what degree such models are extensible to continuous-time, asynchronous modelling of financial markets. We study the behaviour of a learning market maker in a market with
Directory of Open Access Journals (Sweden)
Lluís eFortes-Marco
2015-10-01
Full Text Available Chemosignals mediate both intra- and inter-specific communication in most mammals. Pheromones elicit stereotyped reactions in conspecifics, whereas kairomones provoke a reaction in an allospecific animal. For instance, predator kairomones elicit anticipated defensive responses in preys. The aim of this work was to test the behavioral responses of female mice to two chemosignals: 2-heptanone (2-HP, a putative alarm pheromone, and 2,4,5-trimethylthiazoline (TMT, a fox-derived putative kairomone, widely used to investigate fear and anxiety in rodents. The banana-like odorant isoamyl acetate (IA, unlikely to act as a chemosignal, served as a control odorant. We first presented increasing amounts of these odorants in consecutive days, in a test box in which mice could explore or avoid them. Female mice avoided the highest amounts of all three compounds, with TMT and IA eliciting avoidance at lower amounts (3.8 pmol and 0.35 μmol, respectively than 2-HP (35 μmol. All three compounds induced minimal effects in global locomotion and immobility in this set up. Further, mice detected 3.5 pmol of TMT and IA in a habituation-dishabituation test, so avoidance of IA started well beyond the detection threshold. Finally, both TMT and IA, but not 2-HP, induced conditioned place avoidance and increased immobility in the neutral compartment during a contextual memory test. These data suggest that intense odors can induce contextual learning irrespective of their putative biological significance. Our results support that synthetic predator-related compounds (like TMT or other intense odorants are useful to investigate the neurobiological basis of emotional behaviors in rodents. Since intense odorants unlikely to act as chemosignals can elicit similar behavioral reactions than chemosignals, we stress the importance of using behavioral measures in combination with other physiological (e.g. hormonal levels or neural measures (e.g. immediate early gene expression to
Fortes-Marco, Lluís; Lanuza, Enrique; Martínez-García, Fernando; Agustín-Pavón, Carmen
2015-01-01
Chemosignals mediate both intra- and inter-specific communication in most mammals. Pheromones elicit stereotyped reactions in conspecifics, whereas kairomones provoke a reaction in an allospecific animal. For instance, predator kairomones elicit anticipated defensive responses in preys. The aim of this work was to test the behavioral responses of female mice to two chemosignals: 2-heptanone (2-HP), a putative alarm pheromone, and 2,4,5-trimethylthiazoline (TMT), a fox-derived putative kairomone, widely used to investigate fear and anxiety in rodents. The banana-like odorant isoamyl acetate (IA), unlikely to act as a chemosignal, served as a control odorant. We first presented increasing amounts of these odorants in consecutive days, in a test box in which mice could explore or avoid them. Female mice avoided the highest amounts of all three compounds, with TMT and IA eliciting avoidance at lower amounts (3.8 pmol and 0.35 μmol, respectively) than 2-HP (35 μmol). All three compounds induced minimal effects in global locomotion and immobility in this set up. Further, mice detected 3.5 pmol of TMT and IA in a habituation-dishabituation test, so avoidance of IA started well beyond the detection threshold. Finally, both TMT and IA, but not 2-HP, induced conditioned place avoidance and increased immobility in the neutral compartment during a contextual memory test. These data suggest that intense odors can induce contextual learning irrespective of their putative biological significance. Our results support that synthetic predator-related compounds (like TMT) or other intense odorants are useful to investigate the neurobiological basis of emotional behaviors in rodents. Since intense odorants unlikely to act as chemosignals can elicit similar behavioral reactions than chemosignals, we stress the importance of using behavioral measures in combination with other physiological (e.g., hormonal levels) or neural measures (e.g., immediate early gene expression) to establish
2015-01-01
Positive allosteric modulators (PAMs) of the M4 muscarinic acetylcholine receptor (mAChR) represent a novel approach for the treatment of psychotic symptoms associated with schizophrenia and other neuropsychiatric disorders. We recently reported that the selective M4 PAM VU0152100 produced an antipsychotic drug-like profile in rodents after amphetamine challenge. Previous studies suggest that enhanced cholinergic activity may also improve cognitive function and reverse deficits observed with reduced signaling through the N-methyl-d-aspartate subtype of the glutamate receptor (NMDAR) in the central nervous system. Prior to this study, the M1 mAChR subtype was viewed as the primary candidate for these actions relative to the other mAChR subtypes. Here we describe the discovery of a novel M4 PAM, VU0467154, with enhanced in vitro potency and improved pharmacokinetic properties relative to other M4 PAMs, enabling a more extensive characterization of M4 actions in rodent models. We used VU0467154 to test the hypothesis that selective potentiation of M4 receptor signaling could ameliorate the behavioral, cognitive, and neurochemical impairments induced by the noncompetitive NMDAR antagonist MK-801. VU0467154 produced a robust dose-dependent reversal of MK-801-induced hyperlocomotion and deficits in preclinical models of associative learning and memory functions, including the touchscreen pairwise visual discrimination task in wild-type mice, but failed to reverse these stimulant-induced deficits in M4 KO mice. VU0467154 also enhanced the acquisition of both contextual and cue-mediated fear conditioning when administered alone in wild-type mice. These novel findings suggest that M4 PAMs may provide a strategy for addressing the more complex affective and cognitive disruptions associated with schizophrenia and other neuropsychiatric disorders. PMID:25137629
Wei, Jun; Jiang, Guo-Qing; Liu, Xin
2017-09-01
This study proposed three algorithms that can potentially be used to provide sea surface temperature (SST) conditions for typhoon prediction models. Different from traditional data assimilation approaches, which provide prescribed initial/boundary conditions, our proposed algorithms aim to resolve a flow-dependent SST feedback between growing typhoons and oceans in the future time. Two of these algorithms are based on linear temperature equations (TE-based), and the other is based on an innovative technique involving machine learning (ML-based). The algorithms are then implemented into a Weather Research and Forecasting model for the simulation of typhoon to assess their effectiveness, and the results show significant improvement in simulated storm intensities by including ocean cooling feedback. The TE-based algorithm I considers wind-induced ocean vertical mixing and upwelling processes only, and thus obtained a synoptic and relatively smooth sea surface temperature cooling. The TE-based algorithm II incorporates not only typhoon winds but also ocean information, and thus resolves more cooling features. The ML-based algorithm is based on a neural network, consisting of multiple layers of input variables and neurons, and produces the best estimate of the cooling structure, in terms of its amplitude and position. Sensitivity analysis indicated that the typhoon-induced ocean cooling is a nonlinear process involving interactions of multiple atmospheric and oceanic variables. Therefore, with an appropriate selection of input variables and neuron sizes, the ML-based algorithm appears to be more efficient in prognosing the typhoon-induced ocean cooling and in predicting typhoon intensity than those algorithms based on linear regression methods.
Perfect discretization of reparametrization invariant path integrals
International Nuclear Information System (INIS)
Bahr, Benjamin; Dittrich, Bianca; Steinhaus, Sebastian
2011-01-01
To obtain a well-defined path integral one often employs discretizations. In the case of gravity and reparametrization-invariant systems, the latter of which we consider here as a toy example, discretizations generically break diffeomorphism and reparametrization symmetry, respectively. This has severe implications, as these symmetries determine the dynamics of the corresponding system. Indeed we will show that a discretized path integral with reparametrization-invariance is necessarily also discretization independent and therefore uniquely determined by the corresponding continuum quantum mechanical propagator. We use this insight to develop an iterative method for constructing such a discretized path integral, akin to a Wilsonian RG flow. This allows us to address the problem of discretization ambiguities and of an anomaly-free path integral measure for such systems. The latter is needed to obtain a path integral, that can act as a projector onto the physical states, satisfying the quantum constraints. We will comment on implications for discrete quantum gravity models, such as spin foams.
Perfect discretization of reparametrization invariant path integrals
Bahr, Benjamin; Dittrich, Bianca; Steinhaus, Sebastian
2011-05-01
To obtain a well-defined path integral one often employs discretizations. In the case of gravity and reparametrization-invariant systems, the latter of which we consider here as a toy example, discretizations generically break diffeomorphism and reparametrization symmetry, respectively. This has severe implications, as these symmetries determine the dynamics of the corresponding system. Indeed we will show that a discretized path integral with reparametrization-invariance is necessarily also discretization independent and therefore uniquely determined by the corresponding continuum quantum mechanical propagator. We use this insight to develop an iterative method for constructing such a discretized path integral, akin to a Wilsonian RG flow. This allows us to address the problem of discretization ambiguities and of an anomaly-free path integral measure for such systems. The latter is needed to obtain a path integral, that can act as a projector onto the physical states, satisfying the quantum constraints. We will comment on implications for discrete quantum gravity models, such as spin foams.
Kooshki, Razieh; Abbasnejad, Mehdi; Esmaeili-Mahani, Saeed; Raoof, Maryam
2016-04-01
It is widely accepted that the spinal trigeminal nuclear complex, especially the subnucleus caudalis (Vc), receives input from orofacial structures. The neuropeptides orexin-A and -B are expressed in multiple neuronal systems. Orexin signaling has been implicated in pain-modulating system as well as learning and memory processes. Orexin 1 receptor (OX1R) has been reported in trigeminal nucleus caudalis. However, its roles in trigeminal pain modulation have not been elucidated so far. This study was designed to investigate the role of Vc OX1R in the modulation of orofacial pain as well as pain-induced learning and memory deficits. Orofacial pain was induced by subcutaneous injection of capsaicin in the right upper lip of the rats. OX1R agonist (orexin-A) and antagonist (SB-334867-A) were microinjected into Vc prior capsaicin administration. After recording nociceptive times, learning and memory was investigated using Morris water maze (MWM) test. The results indicated that, orexin-A (150 pM/rat) significantly reduced the nociceptive times, while SB334867-A (80 nM/rat) exaggerated nociceptive behavior in response to capsaicin injection. In MWM test, capsaicin-treated rats showed a significant learning and memory impairment. Moreover, SB-334867-A (80 nM/rat) significantly exaggerated learning and memory impairment in capsaicin-treated rats. However, administration of orexin-A (100 pM/rat) prevented learning and memory deficits. Taken together, these results indicate that Vc OX1R was at least in part involved in orofacial pain transmission and orexin-A has also a beneficial inhibitory effect on orofacial pain-induced deficits in abilities of spatial learning and memory. Copyright © 2016 Elsevier Inc. All rights reserved.
Zhong, Yu; Chen, Jing; Li, Li; Qin, Yi; Wei, Yi; Pan, Shining; Jiang, Yage; Chen, Jialin; Xie, Yubo
2018-04-20
Studies have found that propofol can induce widespread neuroapoptosis in developing brains, which leads to cause long-term learning and memory abnormalities. However, the specific cellular and molecular mechanisms underlying propofol-induced neuroapoptosis remain elusive. The aim of the present study was to explore the role of PKA-CREB-BDNF signaling pathway in propofol-induced long-term learning and memory impairment during brain development. Seven-day-old rats were randomly assigned to control, intralipid and three treatment groups (n = 5). Rats in control group received no treatment. Intralipid (10%, 10 mL/kg) for vehicle control and different dosage of propofol for three treatment groups (50, 100 and 200 mg/kg) were administered intraperitoneally. FJB staining, immunohistochemistry analysis for neuronal nuclei antigen and transmission electron microscopy were used to detect neuronal apoptosis and structure changes. MWM test examines the long-term spatial learning and memory impairment. The expression of PKA, pCREB and BDNF was quantified using western blots. Propofol induced significant increase of FJB-positive cells and decrease of PKA, pCREB and BDNF protein levels in the immature brain of P7 rats. Using the MWM test, propofol-treated rats demonstrated long-term spatial learning and memory impairment. Moreover, hippocampal NeuN-positive cell loss, long-lasting ultrastructural abnormalities of the neurons and synapses, and long-term down-regulation of PKA, pCREB and BDNF protein expression in adult hippocampus were also found. Our results indicated that neonatal propofol exposure can significantly result in long-term learning and memory impairment in adulthood. The possible mechanism involved in the propofol-induced neuroapoptosis was related to down-regulation of PKA-CREB-BDNF signaling pathway. Copyright © 2018. Published by Elsevier B.V.
E-Learning 2.0: Learning Redefined
Kumar, Rupesh
2009-01-01
The conventional e-learning approach emphasizes a learning system more than a learning environment. While traditional e-learning systems continue to be significant, there is a new set of services emerging, embracing the philosophy of Web 2.0. Known as e-learning 2.0, it aims to create a personalized learning environment. E-learning 2.0 combines the use of discrete but complementary tools and web services to support the creation of ad-hoc learning communities. This paper discusses the influenc...
Falcone, Brian; Wada, Atsushi; Parasuraman, Raja
2018-01-01
Transcranial direct current stimulation (tDCS) has been shown to enhance cognitive performance on a variety of tasks. It is hypothesized that tDCS enhances performance by affecting task related cortical excitability changes in networks underlying or connected to the site of stimulation facilitating long term potentiation. However, many recent studies have called into question the reliability and efficacy of tDCS to induce modulatory changes in brain activity. In this study, our goal is to investigate the individual differences in tDCS induced modulatory effects on brain activity related to the degree of enhancement in performance, providing insight into this lack of reliability. In accomplishing this goal, we used functional magnetic resonance imaging (fMRI) concurrently with tDCS stimulation (1 mA, 30 minutes duration) using a visual search task simulating real world conditions. The experiment consisted of three fMRI sessions: pre-training (no performance feedback), training (performance feedback which included response accuracy and target location and either real tDCS or sham stimulation given), and post-training (no performance feedback). The right posterior parietal cortex was selected as the site of anodal tDCS based on its known role in visual search and spatial attention processing. Our results identified a region in the right precentral gyrus, known to be involved with visual spatial attention and orienting, that showed tDCS induced task related changes in cortical excitability that were associated with individual differences in improved performance. This same region showed greater activity during the training session for target feedback of incorrect (target-error feedback) over correct trials for the tDCS stim over sham group indicating greater attention to target features during training feedback when trials were incorrect. These results give important insight into the nature of neural excitability induced by tDCS as it relates to variability in
What can we learn from Raman Spectroscopy on irradiation-induced defects in UO2?
International Nuclear Information System (INIS)
Desgranges, L.; Martin, Ph.; Simon, P.; Guimbretiere, G.; Baldinozzi, G.
2014-01-01
Recent results on irradiated UO 2 by Raman spectroscopy evidenced Raman lines that are characteristic of irradiation-induced defects. Three main mechanisms are identified to explain their origin: resonant Raman, formation of new molecular entities, or breakdown in symmetry. Arguments are given to consider breakdown in symmetry as the predominant mechanism. A tentative description of the defects at the origin of this symmetry breakdown is proposed in terms of coordination polyhedrons of uranium. This discussion led us to consider that the Raman defect modes could be related to area with different stoichiometry. (authors)
Higher dimensional discrete Cheeger inequalities
Directory of Open Access Journals (Sweden)
Anna Gundert
2015-01-01
Full Text Available For graphs there exists a strong connection between spectral and combinatorial expansion properties. This is expressed, e.g., by the discrete Cheeger inequality, the lower bound of which states that $\\lambda(G \\leq h(G$, where $\\lambda(G$ is the second smallest eigenvalue of the Laplacian of a graph $G$ and $h(G$ is the Cheeger constant measuring the edge expansion of $G$. We are interested in generalizations of expansion properties to finite simplicial complexes of higher dimension (or uniform hypergraphs. Whereas higher dimensional Laplacians were introduced already in 1945 by Eckmann, the generalization of edge expansion to simplicial complexes is not straightforward. Recently, a topologically motivated notion analogous to edge expansion that is based on $\\mathbb{Z}_2$-cohomology was introduced by Gromov and independently by Linial, Meshulam and Wallach. It is known that for this generalization there is no direct higher dimensional analogue of the lower bound of the Cheeger inequality. A different, combinatorially motivated generalization of the Cheeger constant, denoted by $h(X$, was studied by Parzanchevski, Rosenthal and Tessler. They showed that indeed $\\lambda(X \\leq h(X$, where $\\lambda(X$ is the smallest non-trivial eigenvalue of the ($(k-1$-dimensional upper Laplacian, for the case of $k$-dimensional simplicial complexes $X$ with complete $(k-1$-skeleton. Whether this inequality also holds for $k$-dimensional complexes with non-com\\-plete$(k-1$-skeleton has been an open question.We give two proofs of the inequality for arbitrary complexes. The proofs differ strongly in the methods and structures employed,and each allows for a different kind of additional strengthening of the original result.
International Nuclear Information System (INIS)
Maruno, Ken-ichi; Biondini, Gino
2004-01-01
We present a class of solutions of the two-dimensional Toda lattice equation, its fully discrete analogue and its ultra-discrete limit. These solutions demonstrate the existence of soliton resonance and web-like structure in discrete integrable systems such as differential-difference equations, difference equations and cellular automata (ultra-discrete equations)
Hairs of discrete symmetries and gravity
Energy Technology Data Exchange (ETDEWEB)
Choi, Kang Sin [Scranton Honors Program, Ewha Womans University, Seodaemun-Gu, Seoul 03760 (Korea, Republic of); Center for Fields, Gravity and Strings, CTPU, Institute for Basic Sciences, Yuseong-Gu, Daejeon 34047 (Korea, Republic of); Kim, Jihn E., E-mail: jihnekim@gmail.com [Department of Physics, Kyung Hee University, 26 Gyungheedaero, Dongdaemun-Gu, Seoul 02447 (Korea, Republic of); Center for Axion and Precision Physics Research (IBS), 291 Daehakro, Yuseong-Gu, Daejeon 34141 (Korea, Republic of); Kyae, Bumseok [Department of Physics, Pusan National University, 2 Busandaehakro-63-Gil, Geumjeong-Gu, Busan 46241 (Korea, Republic of); Nam, Soonkeon [Department of Physics, Kyung Hee University, 26 Gyungheedaero, Dongdaemun-Gu, Seoul 02447 (Korea, Republic of)
2017-06-10
Gauge symmetries are known to be respected by gravity because gauge charges carry flux lines, but global charges do not carry flux lines and are not conserved by gravitational interaction. For discrete symmetries, they are spontaneously broken in the Universe, forming domain walls. Since the realization of discrete symmetries in the Universe must involve the vacuum expectation values of Higgs fields, a string-like configuration (hair) at the intersection of domain walls in the Higgs vacua can be realized. Therefore, we argue that discrete charges are also respected by gravity.
Hairs of discrete symmetries and gravity
Directory of Open Access Journals (Sweden)
Kang Sin Choi
2017-06-01
Full Text Available Gauge symmetries are known to be respected by gravity because gauge charges carry flux lines, but global charges do not carry flux lines and are not conserved by gravitational interaction. For discrete symmetries, they are spontaneously broken in the Universe, forming domain walls. Since the realization of discrete symmetries in the Universe must involve the vacuum expectation values of Higgs fields, a string-like configuration (hair at the intersection of domain walls in the Higgs vacua can be realized. Therefore, we argue that discrete charges are also respected by gravity.
Discrete Morse functions for graph configuration spaces
International Nuclear Information System (INIS)
Sawicki, A
2012-01-01
We present an alternative application of discrete Morse theory for two-particle graph configuration spaces. In contrast to previous constructions, which are based on discrete Morse vector fields, our approach is through Morse functions, which have a nice physical interpretation as two-body potentials constructed from one-body potentials. We also give a brief introduction to discrete Morse theory. Our motivation comes from the problem of quantum statistics for particles on networks, for which generalized versions of anyon statistics can appear. (paper)
Discrete Tomography and Imaging of Polycrystalline Structures
DEFF Research Database (Denmark)
Alpers, Andreas
High resolution transmission electron microscopy is commonly considered as the standard application for discrete tomography. While this has yet to be technically realized, new applications with a similar flavor have emerged in materials science. In our group at Ris� DTU (Denmark's National...... Laboratory for Sustainable Energy), for instance, we study polycrystalline materials via synchrotron X-ray diffraction. Several reconstruction problems arise, most of them exhibit inherently discrete aspects. In this talk I want to give a concise mathematical introduction to some of these reconstruction...... problems. Special focus is on their relationship to classical discrete tomography. Several open mathematical questions will be mentioned along the way....
Ensemble simulations with discrete classical dynamics
DEFF Research Database (Denmark)
Toxværd, Søren
2013-01-01
For discrete classical Molecular dynamics (MD) obtained by the "Verlet" algorithm (VA) with the time increment $h$ there exist a shadow Hamiltonian $\\tilde{H}$ with energy $\\tilde{E}(h)$, for which the discrete particle positions lie on the analytic trajectories for $\\tilde{H}$. $\\tilde......{E}(h)$ is employed to determine the relation with the corresponding energy, $E$ for the analytic dynamics with $h=0$ and the zero-order estimate $E_0(h)$ of the energy for discrete dynamics, appearing in the literature for MD with VA. We derive a corresponding time reversible VA algorithm for canonical dynamics...
Stochastic Kuramoto oscillators with discrete phase states
Jörg, David J.
2017-09-01
We present a generalization of the Kuramoto phase oscillator model in which phases advance in discrete phase increments through Poisson processes, rendering both intrinsic oscillations and coupling inherently stochastic. We study the effects of phase discretization on the synchronization and precision properties of the coupled system both analytically and numerically. Remarkably, many key observables such as the steady-state synchrony and the quality of oscillations show distinct extrema while converging to the classical Kuramoto model in the limit of a continuous phase. The phase-discretized model provides a general framework for coupled oscillations in a Markov chain setting.
Stochastic Kuramoto oscillators with discrete phase states.
Jörg, David J
2017-09-01
We present a generalization of the Kuramoto phase oscillator model in which phases advance in discrete phase increments through Poisson processes, rendering both intrinsic oscillations and coupling inherently stochastic. We study the effects of phase discretization on the synchronization and precision properties of the coupled system both analytically and numerically. Remarkably, many key observables such as the steady-state synchrony and the quality of oscillations show distinct extrema while converging to the classical Kuramoto model in the limit of a continuous phase. The phase-discretized model provides a general framework for coupled oscillations in a Markov chain setting.
Discrete-Time Biomedical Signal Encryption
Directory of Open Access Journals (Sweden)
Victor Grigoraş
2017-12-01
Full Text Available Chaotic modulation is a strong method of improving communication security. Analog and discrete chaotic systems are presented in actual literature. Due to the expansion of digital communication, discrete-time systems become more efficient and closer to actual technology. The present contribution offers an in-depth analysis of the effects chaos encryption produce on 1D and 2D biomedical signals. The performed simulations show that modulating signals are precisely recovered by the synchronizing receiver if discrete systems are digitally implemented and the coefficients precisely correspond. Channel noise is also applied and its effects on biomedical signal demodulation are highlighted.
Discrete symmetries and de Sitter spacetime
Energy Technology Data Exchange (ETDEWEB)
Cotăescu, Ion I., E-mail: gpascu@physics.uvt.ro; Pascu, Gabriel, E-mail: gpascu@physics.uvt.ro [West University of Timişoara, V. Pârvan Ave. 4, RO-300223 Timişoara (Romania)
2014-11-24
Aspects of the ambiguity in defining quantum modes on de Sitter spacetime using a commuting system composed only of differential operators are discussed. Discrete symmetries and their actions on the wavefunction in commonly used coordinate charts are reviewed. It is argued that the system of commuting operators can be supplemented by requiring the invariance of the wavefunction to combined discrete symmetries- a criterion which selects a single state out of the α-vacuum family. Two such members of this family are singled out by particular combined discrete symmetries- states between which exists a well-known thermality relation.
Sampling rare fluctuations of discrete-time Markov chains
Whitelam, Stephen
2018-03-01
We describe a simple method that can be used to sample the rare fluctuations of discrete-time Markov chains. We focus on the case of Markov chains with well-defined steady-state measures, and derive expressions for the large-deviation rate functions (and upper bounds on such functions) for dynamical quantities extensive in the length of the Markov chain. We illustrate the method using a series of simple examples, and use it to study the fluctuations of a lattice-based model of active matter that can undergo motility-induced phase separation.
On mixing property in set-valued discrete systems
International Nuclear Information System (INIS)
Gu Rongbao; Guo Wenjing
2006-01-01
Let (X,d) be a compact metric space and f:X->X be a continuous map. Let (K(X),H) be the space of all non-empty compact subsets of X endowed with the Hausdorff metric induced by d and f-bar :K(X)->K(X) be the map defined by f-bar (A):{f(a):a-bar A}. In this paper we investigate the relationships between the mixing property of (K(X),f-bar ) and the mixing property of (X,f). In addition, we discuss specification for the set-valued discrete dynamical system (K(X),f-bar )
Exterior difference systems and invariance properties of discrete mechanics
International Nuclear Information System (INIS)
Xie Zheng; Xie Duanqiang; Li Hongbo
2008-01-01
Invariance properties describe the fundamental physical laws in discrete mechanics. Can those properties be described in a geometric way? We investigate an exterior difference system called the discrete Euler-Lagrange system, whose solution has one-to-one correspondence with solutions of discrete Euler-Lagrange equations, and use it to define the first integrals. The preservation of the discrete symplectic form along the discrete Hamilton phase flows and the discrete Noether's theorem is also described in the language of difference forms
On organizing principles of discrete differential geometry. Geometry of spheres
International Nuclear Information System (INIS)
Bobenko, Alexander I; Suris, Yury B
2007-01-01
Discrete differential geometry aims to develop discrete equivalents of the geometric notions and methods of classical differential geometry. This survey contains a discussion of the following two fundamental discretization principles: the transformation group principle (smooth geometric objects and their discretizations are invariant with respect to the same transformation group) and the consistency principle (discretizations of smooth parametrized geometries can be extended to multidimensional consistent nets). The main concrete geometric problem treated here is discretization of curvature-line parametrized surfaces in Lie geometry. Systematic use of the discretization principles leads to a discretization of curvature-line parametrization which unifies circular and conical nets.
New lessons learned from disease modeling with induced Pluripotent Stem Cells
Onder, Tamer T.; Daley, George Q.
2012-01-01
Cellular reprogramming and generation of induced pluripotent stem cells (iPSCs) from adult cell types has enabled the creation of patient-specific stem cells for use in disease modeling. To date, many iPSC lines have been generated from a variety of disorders, which have then been differentiated into disease-relevant cell types. When a disease-specific phenotype is detectable in such differentiated cells, the reprogramming technology provides a new opportunity to identify aberrant disease-associated pathways and drugs that can block them. Here, we highlight recent progress as well as limitations in the use of iPSCs to recapitulate disease phenotypes and to screen for therapeutics in vitro. PMID:22749051
Can time be a discrete dynamical variable
International Nuclear Information System (INIS)
Lee, T.D.
1983-01-01
The possibility that time can be regarded as a discrete dynamical variable is examined through all phases of mechanics: from classical mechanics to nonrelativistic quantum mechanics, and to relativistic quantum field theories. (orig.)
Local discrete symmetries from superstring derived models
International Nuclear Information System (INIS)
Faraggi, A.E.
1996-10-01
Discrete and global symmetries play an essential role in many extensions of the Standard Model, for example, to preserve the proton lifetime, to prevent flavor changing neutral currents, etc. An important question is how can such symmetries survive in a theory of quantum gravity, like superstring theory. In a specific string model the author illustrates how local discrete symmetries may arise in string models and play an important role in preventing fast proton decay and flavor changing neutral currents. The local discrete symmetry arises due to the breaking of the non-Abelian gauge symmetries by Wilson lines in the superstring models and forbids, for example dimension five operators which mediate rapid proton decay, to all orders of nonrenormalizable terms. In the context of models of unification of the gauge and gravitational interactions, it is precisely this type of local discrete symmetries that must be found in order to insure that a given model is not in conflict with experimental observations
Breatherlike impurity modes in discrete nonlinear lattices
DEFF Research Database (Denmark)
Hennig, D.; Rasmussen, Kim; Tsironis, G. P.
1995-01-01
We investigate the properties of a disordered generalized discrete nonlinear Schrodinger equation, containing both diagonal and nondiagonal nonlinear terms. The equation models a Linear host lattice doped with nonlinear impurities. We find different types of impurity states that form itinerant...
Inferring gene networks from discrete expression data
Zhang, L.; Mallick, B. K.
2013-01-01
graphical models applied to continuous data, which give a closedformmarginal likelihood. In this paper,we extend network modeling to discrete data, specifically data from serial analysis of gene expression, and RNA-sequencing experiments, both of which
A discrete control model of PLANT
Mitchell, C. M.
1985-01-01
A model of the PLANT system using the discrete control modeling techniques developed by Miller is described. Discrete control models attempt to represent in a mathematical form how a human operator might decompose a complex system into simpler parts and how the control actions and system configuration are coordinated so that acceptable overall system performance is achieved. Basic questions include knowledge representation, information flow, and decision making in complex systems. The structure of the model is a general hierarchical/heterarchical scheme which structurally accounts for coordination and dynamic focus of attention. Mathematically, the discrete control model is defined in terms of a network of finite state systems. Specifically, the discrete control model accounts for how specific control actions are selected from information about the controlled system, the environment, and the context of the situation. The objective is to provide a plausible and empirically testable accounting and, if possible, explanation of control behavior.
Running Parallel Discrete Event Simulators on Sierra
Energy Technology Data Exchange (ETDEWEB)
Barnes, P. D. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Jefferson, D. R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2015-12-03
In this proposal we consider porting the ROSS/Charm++ simulator and the discrete event models that run under its control so that they run on the Sierra architecture and make efficient use of the Volta GPUs.
Effective Hamiltonian for travelling discrete breathers
MacKay, Robert S.; Sepulchre, Jacques-Alexandre
2002-05-01
Hamiltonian chains of oscillators in general probably do not sustain exact travelling discrete breathers. However solutions which look like moving discrete breathers for some time are not difficult to observe in numerics. In this paper we propose an abstract framework for the description of approximate travelling discrete breathers in Hamiltonian chains of oscillators. The method is based on the construction of an effective Hamiltonian enabling one to describe the dynamics of the translation degree of freedom of moving breathers. Error estimate on the approximate dynamics is also studied. The concept of the Peierls-Nabarro barrier can be made clear in this framework. We illustrate the method with two simple examples, namely the Salerno model which interpolates between the Ablowitz-Ladik lattice and the discrete nonlinear Schrödinger system, and the Fermi-Pasta-Ulam chain.
Comparing the Discrete and Continuous Logistic Models
Gordon, Sheldon P.
2008-01-01
The solutions of the discrete logistic growth model based on a difference equation and the continuous logistic growth model based on a differential equation are compared and contrasted. The investigation is conducted using a dynamic interactive spreadsheet. (Contains 5 figures.)
Discrete-time nonlinear sliding mode controller
African Journals Online (AJOL)
user
Keywords: Discrete-time delay system, Sliding mode control, nonlinear sliding ... of engineering systems such as chemical process control, delay in the actuator ...... instrumentation from Motilal Nehru National Institute of Technology (MNNIT),.
Rich dynamics of discrete delay ecological models
International Nuclear Information System (INIS)
Peng Mingshu
2005-01-01
We study multiple bifurcations and chaotic behavior of a discrete delay ecological model. New form of chaos for the 2-D map is observed: the combination of potential period doubling and reverse period-doubling leads to cascading bubbles
Discrete and Continuous Models for Partitioning Problems
Lellmann, Jan; Lellmann, Bjö rn; Widmann, Florian; Schnö rr, Christoph
2013-01-01
-based techniques. This work is concerned with the sources of such artifacts. We discuss the importance of differentiating between artifacts caused by discretization and those caused by relaxation and provide supporting numerical examples. Moreover, we consider
Memorized discrete systems and time-delay
Luo, Albert C J
2017-01-01
This book examines discrete dynamical systems with memory—nonlinear systems that exist extensively in biological organisms and financial and economic organizations, and time-delay systems that can be discretized into the memorized, discrete dynamical systems. It book further discusses stability and bifurcations of time-delay dynamical systems that can be investigated through memorized dynamical systems as well as bifurcations of memorized nonlinear dynamical systems, discretization methods of time-delay systems, and periodic motions to chaos in nonlinear time-delay systems. The book helps readers find analytical solutions of MDS, change traditional perturbation analysis in time-delay systems, detect motion complexity and singularity in MDS; and determine stability, bifurcation, and chaos in any time-delay system.
Electrophysiological correlates of learning-induced modulation of visual motion processing in humans
Directory of Open Access Journals (Sweden)
Viktor Gál
2010-01-01
Full Text Available Training on a visual task leads to increased perceptual and neural responses to visual features that were attended during training as well as decreased responses to neglected distractor features. However, the time course of these attention-based modulations of neural sensitivity for visual features has not been investigated before. Here we measured event related potentials (ERP in response to motion stimuli with different coherence levels before and after training on a speed discrimination task requiring object-based attentional selection of one of the two competing motion stimuli. We found that two peaks on the ERP waveform were modulated by the strength of the coherent motion signal; the response amplitude associated with motion directions that were neglected during training was smaller than the response amplitude associated with motion directions that were attended during training. The first peak of motion coherence-dependent modulation of the ERP responses was at 300 ms after stimulus onset and it was most pronounced over the occipitotemporal cortex. The second peak was around 500 ms and was focused over the parietal cortex. A control experiment suggests that the earlier motion coherence-related response modulation reflects the extraction of the coherent motion signal whereas the later peak might index accumulation and readout of motion signals by parietal decision mechanisms. These findings suggest that attention-based learning affects neural responses both at the sensory and decision processing stages.
Learning-induced Dependence of Neuronal Activity in Primary Motor Cortex on Motor Task Condition.
Cai, X; Shimansky, Y; He, Jiping
2005-01-01
A brain-computer interface (BCI) system such as a cortically controlled robotic arm must have a capacity of adjusting its function to a specific environmental condition. We studied this capacity in non-human primates based on chronic multi-electrode recording from the primary motor cortex of a monkey during the animal's performance of a center-out 3D reaching task and adaptation to external force perturbations. The main condition-related feature of motor cortical activity observed before the onset of force perturbation was a phasic raise of activity immediately before the perturbation onset. This feature was observed during a series of perturbation trials, but were absent under no perturbations. After adaptation has been completed, it usually was taking the subject only one trial to recognize a change in the condition to switch the neuronal activity accordingly. These condition-dependent features of neuronal activity can be used by a BCI for recognizing a change in the environmental condition and making corresponding adjustments, which requires that the BCI-based control system possess such advanced properties of the neural motor control system as capacity to learn and adapt.
Santos Monteiro, Thiago; Beets, Iseult A M; Boisgontier, Matthieu P; Gooijers, Jolien; Pauwels, Lisa; Chalavi, Sima; King, Brad; Albouy, Geneviève; Swinnen, Stephan P
2017-10-01
To study age-related differences in neural activation during motor learning, functional magnetic resonance imaging scans were acquired from 25 young (mean 21.5-year old) and 18 older adults (mean 68.6-year old) while performing a bimanual coordination task before (pretest) and after (posttest) a 2-week training intervention on the task. We studied whether task-related brain activity and training-induced brain activation changes differed between age groups, particularly with respect to the hyperactivation typically observed in older adults. Findings revealed that older adults showed lower performance levels than younger adults but similar learning capability. At the cerebral level, the task-related hyperactivation in parietofrontal areas and underactivation in subcortical areas observed in older adults were not differentially modulated by the training intervention. However, brain activity related to task planning and execution decreased from pretest to posttest in temporo-parieto-frontal areas and subcortical areas in both age groups, suggesting similar processes of enhanced activation efficiency with advanced skill level. Furthermore, older adults who displayed higher activity in prefrontal regions at pretest demonstrated larger training-induced performance gains. In conclusion, in spite of prominent age-related brain activation differences during movement planning and execution, the mechanisms of learning-related reduction of brain activation appear to be similar in both groups. Importantly, cerebral activity during early learning can differentially predict the amplitude of the training-induced performance benefit between young and older adults. Copyright © 2017 Elsevier Inc. All rights reserved.
Quadratic Term Structure Models in Discrete Time
Marco Realdon
2006-01-01
This paper extends the results on quadratic term structure models in continuos time to the discrete time setting. The continuos time setting can be seen as a special case of the discrete time one. Recursive closed form solutions for zero coupon bonds are provided even in the presence of multiple correlated underlying factors. Pricing bond options requires simple integration. Model parameters may well be time dependent without scuppering such tractability. Model estimation does not require a r...
Symmetries in discrete-time mechanics
International Nuclear Information System (INIS)
Khorrami, M.
1996-01-01
Based on a general formulation for discrete-time quantum mechanics, introduced by M. Khorrami (Annals Phys. 224 (1995), 101), symmetries in discrete-time quantum mechanics are investigated. It is shown that any classical continuous symmetry leads to a conserved quantity in classical mechanics, as well as quantum mechanics. The transformed wave function, however, has the correct evolution if and only if the symmetry is nonanomalous. Copyright copyright 1996 Academic Press, Inc
Nonlinear integrodifferential equations as discrete systems
Tamizhmani, K. M.; Satsuma, J.; Grammaticos, B.; Ramani, A.
1999-06-01
We analyse a class of integrodifferential equations of the `intermediate long wave' (ILW) type. We show that these equations can be formally interpreted as discrete, differential-difference systems. This allows us to link equations of this type with previous results of ours involving differential-delay equations and, on the basis of this, propose new integrable equations of ILW type. Finally, we extend this approach to pure difference equations and propose ILW forms for the discrete lattice KdV equation.
Definable maximal discrete sets in forcing extensions
DEFF Research Database (Denmark)
Törnquist, Asger Dag; Schrittesser, David
2018-01-01
Let be a Σ11 binary relation, and recall that a set A is -discrete if no two elements of A are related by . We show that in the Sacks and Miller forcing extensions of L there is a Δ12 maximal -discrete set. We use this to answer in the negative the main question posed in [5] by showing...
Application of multivariate splines to discrete mathematics
Xu, Zhiqiang
2005-01-01
Using methods developed in multivariate splines, we present an explicit formula for discrete truncated powers, which are defined as the number of non-negative integer solutions of linear Diophantine equations. We further use the formula to study some classical problems in discrete mathematics as follows. First, we extend the partition function of integers in number theory. Second, we exploit the relation between the relative volume of convex polytopes and multivariate truncated powers and giv...
Discrete symmetries and solar neutrino mixing
Energy Technology Data Exchange (ETDEWEB)
Kapetanakis, D.; Mayr, P.; Nilles, H.P. (Physik Dept., Technische Univ. Muenchen, Garching (Germany) Max-Planck-Inst. fuer Physik, Werner-Heisenberg-Inst., Muenchen (Germany))
1992-05-21
We study the question of resonant solar neutrino mixing in the framework of the supersymmetric extension of the standard model. Discrete symmetries that are consistent with solar neutrino mixing and proton stability are classified. In the minimal model they are shown to lead to two distinct patterns of allowed dimension-four operators. Imposing anomaly freedom, only three different discrete Z{sub N}-symmetries (with N=2, 3, 6) are found to be phenomenologically acceptable. (orig.).
Discrete symmetries and solar neutrino mixing
International Nuclear Information System (INIS)
Kapetanakis, D.; Mayr, P.; Nilles, H.P.
1992-01-01
We study the question of resonant solar neutrino mixing in the framework of the supersymmetric extension of the standard model. Discrete symmetries that are consistent with solar neutrino mixing and proton stability are classified. In the minimal model they are shown to lead to two distinct patterns of allowed dimension-four operators. Imposing anomaly freedom, only three different discrete Z N -symmetries (with N=2, 3, 6) are found to be phenomenologically acceptable. (orig.)
Discrete symmetries and coset space dimensional reduction
International Nuclear Information System (INIS)
Kapetanakis, D.; Zoupanos, G.
1989-01-01
We consider the discrete symmetries of all the six-dimensional coset spaces and we apply them in gauge theories defined in ten dimensions which are dimensionally reduced over these homogeneous spaces. Particular emphasis is given in the consequences of the discrete symmetries on the particle content as well as on the symmetry breaking a la Hosotani of the resulting four-dimensional theory. (orig.)
On discrete models of space-time
International Nuclear Information System (INIS)
Horzela, A.; Kempczynski, J.; Kapuscik, E.; Georgia Univ., Athens, GA; Uzes, Ch.
1992-02-01
Analyzing the Einstein radiolocation method we come to the conclusion that results of any measurement of space-time coordinates should be expressed in terms of rational numbers. We show that this property is Lorentz invariant and may be used in the construction of discrete models of space-time different from the models of the lattice type constructed in the process of discretization of continuous models. (author)
Discrete approximations to vector spin models
Energy Technology Data Exchange (ETDEWEB)
Van Enter, Aernout C D [University of Groningen, Johann Bernoulli Institute of Mathematics and Computing Science, Postbus 407, 9700 AK Groningen (Netherlands); Kuelske, Christof [Ruhr-Universitaet Bochum, Fakultaet fuer Mathematik, D44801 Bochum (Germany); Opoku, Alex A, E-mail: A.C.D.v.Enter@math.rug.nl, E-mail: Christof.Kuelske@ruhr-uni-bochum.de, E-mail: opoku@math.leidenuniv.nl [Mathematisch Instituut, Universiteit Leiden, Postbus 9512, 2300 RA, Leiden (Netherlands)
2011-11-25
We strengthen a result from Kuelske and Opoku (2008 Electron. J. Probab. 13 1307-44) on the existence of effective interactions for discretized continuous-spin models. We also point out that such an interaction cannot exist at very low temperatures. Moreover, we compare two ways of discretizing continuous-spin models, and show that except for very low temperatures, they behave similarly in two dimensions. We also discuss some possibilities in higher dimensions. (paper)
Discrete approximations to vector spin models
International Nuclear Information System (INIS)
Van Enter, Aernout C D; Külske, Christof; Opoku, Alex A
2011-01-01
We strengthen a result from Külske and Opoku (2008 Electron. J. Probab. 13 1307–44) on the existence of effective interactions for discretized continuous-spin models. We also point out that such an interaction cannot exist at very low temperatures. Moreover, we compare two ways of discretizing continuous-spin models, and show that except for very low temperatures, they behave similarly in two dimensions. We also discuss some possibilities in higher dimensions. (paper)
A study of discrete nonlinear systems
International Nuclear Information System (INIS)
Dhillon, H.S.
2001-04-01
An investigation of various spatially discrete time-independent nonlinear models was undertaken. These models are generically applicable to many different physical systems including electron-phonon interactions in solids, magnetic multilayers, layered superconductors and classical lattice systems. To characterise the possible magnetic structures created on magnetic multilayers a model has been formulated and studied. The Euler-Lagrange equation for this model is a discrete version of the Sine-Gordon equation. Solutions of this equation are generated by applying the methods of Chaotic Dynamics - treating the space variable associated with the layer number as a discrete time variable. The states found indicate periodic, quasiperiodic and chaotic structures. Analytic solutions to the discrete nonlinear Schroedinger Equation (DNSE) with cubic nonlinearity are presented in the strong coupling limit. Using these as a starting point, a procedure is developed to determine the wave function and the energy eigenvalue for moderate coupling. The energy eigenvalues of the different structures of the wave function are found to be in excellent agreement with the exact strong coupling result. The solutions to the DNSE indicate commensurate and incommensurate spatial structures associated with different localisation patterns of the wave function. The states which arise may be fractal, periodic, quasiperiodic or chaotic. This work is then extended to solve a first order discrete nonlinear equation. The exact solutions for both the first and second order discrete nonlinear equations with cubic nonlinearity suggests that this method of studying discrete nonlinear equations may be applied to solve discrete equations with any order difference and cubic nonlinearity. (author)
Mohamed, Mamdouh S.
2016-02-11
A conservative discretization of incompressible Navier–Stokes equations is developed based on discrete exterior calculus (DEC). A distinguishing feature of our method is the use of an algebraic discretization of the interior product operator and a combinatorial discretization of the wedge product. The governing equations are first rewritten using the exterior calculus notation, replacing vector calculus differential operators by the exterior derivative, Hodge star and wedge product operators. The discretization is then carried out by substituting with the corresponding discrete operators based on the DEC framework. Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy for otherwise unstructured meshes. By construction, the method is conservative in that both mass and vorticity are conserved up to machine precision. The relative error in kinetic energy for inviscid flow test cases converges in a second order fashion with both the mesh size and the time step.
Mohamed, Mamdouh S.; Hirani, Anil N.; Samtaney, Ravi
2016-05-01
A conservative discretization of incompressible Navier-Stokes equations is developed based on discrete exterior calculus (DEC). A distinguishing feature of our method is the use of an algebraic discretization of the interior product operator and a combinatorial discretization of the wedge product. The governing equations are first rewritten using the exterior calculus notation, replacing vector calculus differential operators by the exterior derivative, Hodge star and wedge product operators. The discretization is then carried out by substituting with the corresponding discrete operators based on the DEC framework. Numerical experiments for flows over surfaces reveal a second order accuracy for the developed scheme when using structured-triangular meshes, and first order accuracy for otherwise unstructured meshes. By construction, the method is conservative in that both mass and vorticity are conserved up to machine precision. The relative error in kinetic energy for inviscid flow test cases converges in a second order fashion with both the mesh size and the time step.
Taati, Majid; Moghaddasi, Mehrnoush; Esmaeili, Masoumeh; Pourkhodadad, Soheila; Nayebzadeh, Hassan
2014-10-31
While it is well known that exercise can improve cognitive performance, the underlying mechanisms are not fully understood. There is now evidence that histamine can modulate learning and memory in different types of behavioral tasks. The present study was designed to examine the possible role of central histamine H1 and H2 receptors in forced treadmill running-induced enhancement of learning and memory in rats. For this purpose the animals received intracerebroventricularly chlorpheniramine (H1 receptor blocker) and cimetidine (H2 receptor blocker) before each day of fifteen consecutive days of exercise. Then their learning and memory were tested on the water maze task using a four-trial-per-day for 4 consecutive days. A probe trial was performed after the last training day. Our data showed that cimetidine reversed the exercise-induced improvement in learning and memory in rats; however, this was not the case regarding chlorpheniramine. Our findings indicate that central histamine H2 receptors play an important role in mediating the beneficial effects of forced exercise on learning and memory. Copyright © 2014 Elsevier B.V. All rights reserved.
Explicit solutions to the semi-discrete modified KdV equation and motion of discrete plane curves
International Nuclear Information System (INIS)
Inoguchi, Jun-ichi; Kajiwara, Kenji; Matsuura, Nozomu; Ohta, Yasuhiro
2012-01-01
We construct explicit solutions to continuous motion of discrete plane curves described by a semi-discrete potential modified KdV equation. Explicit formulas in terms of the τ function are presented. Bäcklund transformations of the discrete curves are also discussed. We finally consider the continuous limit of discrete motion of discrete plane curves described by the discrete potential modified KdV equation to motion of smooth plane curves characterized by the potential modified KdV equation. (paper)
Discrete modeling considerations in multiphase fluid dynamics
International Nuclear Information System (INIS)
Ransom, V.H.; Ramshaw, J.D.
1988-01-01
The modeling of multiphase flows play a fundamental role in light water reactor safety. The main ingredients in our discrete modeling Weltanschauung are the following considerations: (1) Any physical model must be cast into discrete form for a digital computer. (2) The usual approach of formulating models in differential form and then discretizing them is potentially hazardous. It may be preferable to formulate the model in discrete terms from the outset. (3) Computer time and storage constraints limit the resolution that can be employed in practical calculations. These limits effectively define the physical phenomena, length scales, and time scales which cannot be directly represented in the calculation and therefore must be modeled. This information should be injected into the model formulation process at an early stage. (4) Practical resolution limits are generally so coarse that traditional convergence and truncation-error analyses become irrelevant. (5) A discrete model constitutes a reduced description of a physical system, from which fine-scale details are eliminated. This elimination creates a statistical closure problem. Methods from statistical physics may therefore be useful in the formulation of discrete models. In the present paper we elaborate on these themes and illustrate them with simple examples. 48 refs
Theoretical Basics of Teaching Discrete Mathematics
Directory of Open Access Journals (Sweden)
Y. A. Perminov
2012-01-01
Full Text Available The paper deals with the research findings concerning the process of mastering the theoretical basics of discrete mathematics by the students of vocational pedagogic profile. The methodological analysis is based on the subject and functions of the modern discrete mathematics and its role in mathematical modeling and computing. The modern discrete mathematics (i.e. mathematics of the finite type structures plays the important role in modernization of vocational training. It is especially rele- vant to training students for vocational pedagogic qualifications, as in the future they will be responsible for training the middle and the senior level specialists in engineer- ing and technical spheres. Nowadays in different industries, there arise the problems which require for their solving both continual – based on the classical mathematical methods – and discrete modeling. The teaching course of discrete mathematics for the future vocational teachers should be relevant to the target qualification and aimed at mastering the mathematical modeling, systems of computer mathematics and computer technologies. The author emphasizes the fundamental role of mastering the language of algebraic and serial structures, as well as the logical, algorithmic, combinatory schemes dominating in dis- crete mathematics. The guidelines for selecting the content of the course in discrete mathematics are specified. The theoretical findings of the research can be put into practice whilst developing curricula and working programs for bachelors and masters’ training.
Current density and continuity in discretized models
International Nuclear Information System (INIS)
Boykin, Timothy B; Luisier, Mathieu; Klimeck, Gerhard
2010-01-01
Discrete approaches have long been used in numerical modelling of physical systems in both research and teaching. Discrete versions of the Schroedinger equation employing either one or several basis functions per mesh point are often used by senior undergraduates and beginning graduate students in computational physics projects. In studying discrete models, students can encounter conceptual difficulties with the representation of the current and its divergence because different finite-difference expressions, all of which reduce to the current density in the continuous limit, measure different physical quantities. Understanding these different discrete currents is essential and requires a careful analysis of the current operator, the divergence of the current and the continuity equation. Here we develop point forms of the current and its divergence valid for an arbitrary mesh and basis. We show that in discrete models currents exist only along lines joining atomic sites (or mesh points). Using these results, we derive a discrete analogue of the divergence theorem and demonstrate probability conservation in a purely localized-basis approach.
Discrete Calculus as a Bridge between Scales
Degiuli, Eric; McElwaine, Jim
2012-02-01
Understanding how continuum descriptions of disordered media emerge from the microscopic scale is a fundamental challenge in condensed matter physics. In many systems, it is necessary to coarse-grain balance equations at the microscopic scale to obtain macroscopic equations. We report development of an exact, discrete calculus, which allows identification of discrete microscopic equations with their continuum equivalent [1]. This allows the application of powerful techniques of calculus, such as the Helmholtz decomposition, the Divergence Theorem, and Stokes' Theorem. We illustrate our results with granular materials. In particular, we show how Newton's laws for a single grain reproduce their continuum equivalent in the calculus. This allows introduction of a discrete Airy stress function, exactly as in the continuum. As an application of the formalism, we show how these results give the natural mean-field variation of discrete quantities, in agreement with numerical simulations. The discrete calculus thus acts as a bridge between discrete microscale quantities and continuous macroscale quantities. [4pt] [1] E. DeGiuli & J. McElwaine, PRE 2011. doi: 10.1103/PhysRevE.84.041310
Recent developments in discrete ordinates electron transport
International Nuclear Information System (INIS)
Morel, J.E.; Lorence, L.J. Jr.
1986-01-01
The discrete ordinates method is a deterministic method for numerically solving the Boltzmann equation. It was originally developed for neutron transport calculations, but is routinely used for photon and coupled neutron-photon transport calculations as well. The computational state of the art for coupled electron-photon transport (CEPT) calculations is not as developed as that for neutron transport calculations. The only production codes currently available for CEPT calculations are condensed-history Monte Carlo codes such as the ETRAN and ITS codes. A deterministic capability for production calculations is clearly needed. In response to this need, we have begun the development of a production discrete ordinates code for CEPT calculations. The purpose of this paper is to describe the basic approach we are taking, discuss the current status of the project, and present some new computational results. Although further characterization of the coupled electron-photon discrete ordinates method remains to be done, the results to date indicate that the discrete ordinates method can be just as accurate and from 10 to 100 times faster than the Monte Carlo method for a wide variety of problems. We stress that these results are obtained with standard discrete ordinates codes such as ONETRAN. It is clear that even greater efficiency can be obtained by developing a new generation of production discrete ordinates codes specifically designed to solve the Boltzmann-Fokker-Planck equation. However, the prospects for such development in the near future appear to be remote
Discrete symmetries and their stringy origin
International Nuclear Information System (INIS)
Mayorga Pena, Damian Kaloni
2014-05-01
Discrete symmetries have proven to be very useful in controlling the phenomenology of theories beyond the standard model. In this work we explore how these symmetries emerge from string compactifications. Our approach is twofold: On the one hand, we consider the heterotic string on orbifold backgrounds. In this case the discrete symmetries can be derived from the orbifold conformal field theory, and it can be shown that they are in close relation with the orbifold geometry. We devote special attention to R-symmetries, which arise from discrete remnants of the Lorentz group in compact space. Further we discuss the physical implications of these symmetries both in the heterotic mini-landscape and in newly constructed models based on the Z 2 x Z 4 orbifold. In both cases we observe that the discrete symmetries favor particular locations in the orbifold where the particles of standard model should live. On the other hand we consider a class of F-theory models exhibiting an SU(5) gauge group, times additional U(1) symmetries. In this case, the smooth compactification background does not permit us to track the discrete symmetries as transparently as in orbifold models. Hence, we follow a different approach and search for discrete subgroups emerging after the U(1)s are broken. We observe that in this approach it is possible to obtain the standard Z 2 matter parity of the MSSM.
Hasanein, Parisa; Felehgari, Zhila; Emamjomeh, Abbasali
2016-05-27
Learning and memory impairment occurs in diabetes. Salvia officinalis L. (SO) has been used in Iranian traditional medicine as a remedy against diabetes. We hypothesized that chronic administration of SO (400, 600 and 800mg/kg, p.o.) and its principal constituent, rosmarinic acid, would affect on passive avoidance learning (PAL) and memory in streptozocin-induced diabetic and non-diabetic rats. We also explored hypoglycemic and antioxidant activities of SO as the possible mechanisms. Treatments were begun at the onset of hyperglycemia. PAL was assessed 30days later. Retention test was done 24h after training. At the end, animals were weighed and blood samples were drawn for further analyzing of glucose and oxidant/antioxidant markers. Diabetes induced deficits in acquisition and retrieval processes. SO (600 and 800mg/kg) and rosmarinic acid reversed learning and memory deficits induced by diabetes and improved cognition of healthy rats. While the dose of 400mg/kg had no effect, the higher doses and rosmarinic acid inhibited hyperglycemia and lipid peroxidation as well as enhanced the activity of antioxidant enzymes superoxide dismutase and catalase. SO prevented diabetes-induced acquisition and memory deficits through inhibiting hyperglycemia, lipid peroxidation as well as enhancing antioxidant defense systems. Therefore, SO and its principal constituent rosmarinic acid represent a potential therapeutic option against diabetic memory impairment which deserves consideration and further examination. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Discrete integrable systems and deformations of associative algebras
International Nuclear Information System (INIS)
Konopelchenko, B G
2009-01-01
Interrelations between discrete deformations of the structure constants for associative algebras and discrete integrable systems are reviewed. Theory of deformations for associative algebras is presented. Closed left ideal generated by the elements representing the multiplication table plays a central role in this theory. Deformations of the structure constants are generated by the deformation driving algebra and governed by the central system of equations. It is demonstrated that many discrete equations such as discrete Boussinesq equation, discrete WDVV equation, discrete Schwarzian KP and BKP equations, discrete Hirota-Miwa equations for KP and BKP hierarchies are particular realizations of the central system. An interaction between the theories of discrete integrable systems and discrete deformations of associative algebras is reciprocal and fruitful. An interpretation of the Menelaus relation (discrete Schwarzian KP equation), discrete Hirota-Miwa equation for KP hierarchy, consistency around the cube as the associativity conditions and the concept of gauge equivalence, for instance, between the Menelaus and KP configurations are particular examples.
International Nuclear Information System (INIS)
Shi, Ying; Zhang, Da-jun; Nimmo, Jonathan J C
2014-01-01
The Hirota–Miwa equation can be written in ‘nonlinear’ form in two ways: the discrete KP equation and, by using a compatible continuous variable, the discrete potential KP equation. For both systems, we consider the Darboux and binary Darboux transformations, expressed in terms of the continuous variable, and obtain exact solutions in Wronskian and Grammian form. We discuss reductions of both systems to the discrete KdV and discrete potential KdV equation, respectively, and exploit this connection to find the Darboux and binary Darboux transformations and exact solutions of these equations. (paper)
Simulating and Detecting Radiation-Induced Errors for Onboard Machine Learning
Wagstaff, Kiri L.; Bornstein, Benjamin; Granat, Robert; Tang, Benyang; Turmon, Michael
2009-01-01
Spacecraft processors and memory are subjected to high radiation doses and therefore employ radiation-hardened components. However, these components are orders of magnitude more expensive than typical desktop components, and they lag years behind in terms of speed and size. We have integrated algorithm-based fault tolerance (ABFT) methods into onboard data analysis algorithms to detect radiation-induced errors, which ultimately may permit the use of spacecraft memory that need not be fully hardened, reducing cost and increasing capability at the same time. We have also developed a lightweight software radiation simulator, BITFLIPS, that permits evaluation of error detection strategies in a controlled fashion, including the specification of the radiation rate and selective exposure of individual data structures. Using BITFLIPS, we evaluated our error detection methods when using a support vector machine to analyze data collected by the Mars Odyssey spacecraft. We found ABFT error detection for matrix multiplication is very successful, while error detection for Gaussian kernel computation still has room for improvement.
Learning Bayesian Dependence Model for Student Modelling
Directory of Open Access Journals (Sweden)
Adina COCU
2008-12-01
Full Text Available Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.
Learning conditional Gaussian networks
DEFF Research Database (Denmark)
Bøttcher, Susanne Gammelgaard
This paper considers conditional Gaussian networks. The parameters in the network are learned by using conjugate Bayesian analysis. As conjugate local priors, we apply the Dirichlet distribution for discrete variables and the Gaussian-inverse gamma distribution for continuous variables, given...... a configuration of the discrete parents. We assume parameter independence and complete data. Further, to learn the structure of the network, the network score is deduced. We then develop a local master prior procedure, for deriving parameter priors in these networks. This procedure satisfies parameter...... independence, parameter modularity and likelihood equivalence. Bayes factors to be used in model search are introduced. Finally the methods derived are illustrated by a simple example....
Moros, J; Serrano, J; Gallego, F J; Macías, J; Laserna, J J
2013-06-15
During recent years laser-induced breakdown spectroscopy (LIBS) has been considered one of the techniques with larger ability for trace detection of explosives. However, despite of the high sensitivity exhibited for this application, LIBS suffers from a limited selectivity due to difficulties in assigning the molecular origin of the spectral emissions observed. This circumstance makes the recognition of fingerprints a latent challenging problem. In the present manuscript the sorting of six explosives (chloratite, ammonal, DNT, TNT, RDX and PETN) against a broad list of potential harmless interferents (butter, fuel oil, hand cream, olive oil, …), all of them in the form of fingerprints deposited on the surfaces of objects for courier services, has been carried out. When LIBS information is processed through a multi-stage architecture algorithm built from a suitable combination of 3 learning classifiers, an unknown fingerprint may be labeled into a particular class. Neural network classifiers trained by the Levenberg-Marquardt rule were decided within 3D scatter plots projected onto the subspace of the most useful features extracted from the LIBS spectra. Experimental results demonstrate that the presented algorithm sorts fingerprints according to their hazardous character, although its spectral information is virtually identical in appearance, with rates of false negatives and false positives not beyond of 10%. These reported achievements mean a step forward in the technology readiness level of LIBS for this complex application related to defense, homeland security and force protection. Copyright © 2013 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Xiuwen Yi
2015-01-01
Full Text Available Background. Isoflurane disrupts brain development of neonatal mice, but its mechanism is unclear. We explored whether isoflurane damaged developing hippocampi through FASL-FAS signaling pathway, which is a well-known pathway of apoptosis. Method. Wild type and FAS- or FASL-gene-knockout mice aged 7 days were exposed to either isoflurane or pure oxygen. We used western blotting to study expressions of caspase-3, FAS (CD95, and FAS ligand (FASL or CD95L proteins, TUNEL staining to count apoptotic cells in hippocampus, and Morris water maze (MWM to evaluate learning and memory. Result. Isoflurane increased expression of FAS and FASL proteins in wild type mice. Compared to isoflurane-treated FAS- and FASL-knockout mice, isoflurane-treated wild type mice had higher expression of caspase-3 and more TUNEL-positive hippocampal cells. Expression of caspase-3 in wild isoflurane group, wild control group, FAS/FASL-gene-knockout control group, and FAS/FASL-gene-knockout isoflurane group showed FAS or FASL gene knockout might attenuate increase of caspase-3 caused by isoflurane. MWM showed isoflurane treatment of wild type mice significantly prolonged escape latency and reduced platform crossing times compared with gene-knockout isoflurane-treated groups. Conclusion. Isoflurane induces apoptosis in developing hippocampi of wild type mice but not in FAS- and FASL-knockout mice and damages brain development through FASL-FAS signaling.
Institute of Scientific and Technical Information of China (English)
Feng Zhang; Jiguo Zhang; Lihua Wang; Dexiang Mao
2008-01-01
BACKGROUND: Learning and memory processes are accompanied by complex neuropathological and biochemical changes. Free radicals play an important role in learning and memory damage. OBJECTIVE: To observe the effects of polygonatum sibiricum polysaccharide (PSP) in comparison with vitamin E on inhibiting free radical damage, as well as improving the degree of cerebral ischemia and learning and memory in a scopolamine-induced mouse model of dementia.DESIGN: Randomized controlled animal study.SETTINGS: Department of Pharmacology, Taishan Medical College; Shandong Jewim Pharmaceutical Co., Ltd.MATERIALS: A total of 105 healthy Kunming mice, comprising 90 males and 15 females that were clean grade, were provided by the Animal Center of Taishan Medical College. PSP (extracted and purified by Huangjing, Taishan) was provided by the Department of Traditional Chinese Medicine, Taishan Medical College (purity of 79.6% by using a phenol-concentrated sulphate acid method), and hydrogen bromine acid scopolamine injection solution (SCO) by Shanghai Hefeng Pharmaceutical Co., Ltd.METHODS: This study was performed at the Pharmacological Laboratory of Taishan Medical College from March to June 2007. ① A total of 75 healthy Kunming male mice of clean grade were randomly divided into a normal control group, positive control group, and low-dosage and high-dosage PSP groups, with 15 mice in each group. Mice in both the low-dosage and high-dosage PSP groups were intragastrically administered 0.5 g/kg and 2.0 g/kg PSP, respectively. Mice in the positive control group were intragastrically administered 0.5 g/kg vitamin E. In addition, mice in both the normal control group and model group were intragastrically administered the same volume of saline, respectively, once a day for 7 consecutive days. One hour after the final administration on day 6, mice in the positive control group, model group, low-dosage and high-dosage PSP groups were subcutaneously injected with 3.0 mg/kg SCO, while
Directory of Open Access Journals (Sweden)
Lešinskis Aloizs
2017-08-01
Full Text Available Aircraft crew training corresponds to the interactive learning models of sensorimotor skill acquisition, and the dynamics of skill acquirement can be approximated by the exponential trend. A model of 5-grade assessment of separate exercises is offered. It helps to calculate a resulting evaluation, in accordance with which the progress level of a discrete exercise is evaluated. Such an evaluation forms one of the points for the analytical construction of a learning curve using the Gaussian method. Possible applications of the learning curve are covered.
A Continuum of Learning: From Rote Memorization to Meaningful Learning in Organic Chemistry
Grove, Nathaniel P.; Bretz, Stacey Lowery
2012-01-01
The Assimilation Theory of Ausubel and Novak has typically been used in the research literature to describe two extremes to learning chemistry: meaningful learning "versus" rote memorization. It is unlikely, however, that such discrete categories of learning exist. Rote and meaningful learning, rather, are endpoints along a continuum of…
Convergence of posteriors for discretized log Gaussian Cox processes
DEFF Research Database (Denmark)
Waagepetersen, Rasmus Plenge
2004-01-01
In Markov chain Monte Carlo posterior computation for log Gaussian Cox processes (LGCPs) a discretization of the continuously indexed Gaussian field is required. It is demonstrated that approximate posterior expectations computed from discretized LGCPs converge to the exact posterior expectations...... when the cell sizes of the discretization tends to zero. The effect of discretization is studied in a data example....
Active Affordance Learning in Continuous State and Action Spaces
Wang, C.; Hindriks, K.V.; Babuska, R.
2014-01-01
Learning object affordances and manipulation skills is essential for developing cognitive service robots. We propose an active affordance learning approach in continuous state and action spaces without manual discretization of states or exploratory motor primitives. During exploration in the action
International Nuclear Information System (INIS)
Zazula, J.M.
1983-01-01
The general purpose code BALTORO was written for coupling the three-dimensional Monte-Carlo /MC/ with the one-dimensional Discrete Ordinates /DO/ radiation transport calculations. The quantity of a radiation-induced /neutrons or gamma-rays/ nuclear effect or the score from a radiation-yielding nuclear effect can be analysed in this way. (author)
Institute of Scientific and Technical Information of China (English)
YANGSu-Fen; YANGZheng-Qin; LiYu; WuQin; HUANGXie-Nan; SUNAn-Sheng; ZHOUQi-Xin; SHIJing-Shan
2004-01-01
Objective: To explore the mechanism of Ecdysterone (ECR) in prevention of learning and memory dysfunction of the rats induced by β-amyloid peptide ( Aβ25-35 ). Methods: Ninety Wistar male rats were randomly divided into five groups, the control group, the model group, the treated groups (ECR 4mg·kg-1 and ECR 8mg·kg-1 and Nimodipine
Discrete stochastic analogs of Erlang epidemic models.
Getz, Wayne M; Dougherty, Eric R
2018-12-01
Erlang differential equation models of epidemic processes provide more realistic disease-class transition dynamics from susceptible (S) to exposed (E) to infectious (I) and removed (R) categories than the ubiquitous SEIR model. The latter is itself is at one end of the spectrum of Erlang SE[Formula: see text]I[Formula: see text]R models with [Formula: see text] concatenated E compartments and [Formula: see text] concatenated I compartments. Discrete-time models, however, are computationally much simpler to simulate and fit to epidemic outbreak data than continuous-time differential equations, and are also much more readily extended to include demographic and other types of stochasticity. Here we formulate discrete-time deterministic analogs of the Erlang models, and their stochastic extension, based on a time-to-go distributional principle. Depending on which distributions are used (e.g. discretized Erlang, Gamma, Beta, or Uniform distributions), we demonstrate that our formulation represents both a discretization of Erlang epidemic models and generalizations thereof. We consider the challenges of fitting SE[Formula: see text]I[Formula: see text]R models and our discrete-time analog to data (the recent outbreak of Ebola in Liberia). We demonstrate that the latter performs much better than the former; although confining fits to strict SEIR formulations reduces the numerical challenges, but sacrifices best-fit likelihood scores by at least 7%.
Positivity for Convective Semi-discretizations
Fekete, Imre
2017-04-19
We propose a technique for investigating stability properties like positivity and forward invariance of an interval for method-of-lines discretizations, and apply the technique to study positivity preservation for a class of TVD semi-discretizations of 1D scalar hyperbolic conservation laws. This technique is a generalization of the approach suggested in Khalsaraei (J Comput Appl Math 235(1): 137–143, 2010). We give more relaxed conditions on the time-step for positivity preservation for slope-limited semi-discretizations integrated in time with explicit Runge–Kutta methods. We show that the step-size restrictions derived are sharp in a certain sense, and that many higher-order explicit Runge–Kutta methods, including the classical 4th-order method and all non-confluent methods with a negative Butcher coefficient, cannot generally maintain positivity for these semi-discretizations under any positive step size. We also apply the proposed technique to centered finite difference discretizations of scalar hyperbolic and parabolic problems.
Noether symmetries of discrete mechanico–electrical systems
International Nuclear Information System (INIS)
Fu Jingli; Xie Fengping; Chen Benyong
2008-01-01
This paper focuses on studying Noether symmetries and conservation laws of the discrete mechanico-electrical systems with the nonconservative and the dissipative forces. Based on the invariance of discrete Hamilton action of the systems under the infinitesimal transformation with respect to the generalized coordinates, the generalized electrical quantities and time, it presents the discrete analogue of variational principle, the discrete analogue of Lagrange–Maxwell equations, the discrete analogue of Noether theorems for Lagrange–Maxwell and Lagrange mechanico-electrical systems. Also, the discrete Noether operator identity and the discrete Noether-type conservation laws are obtained for these systems. An actual example is given to illustrate these results. (general)
Discrete breathers for a discrete nonlinear Schrödinger ring coupled to a central site.
Jason, Peter; Johansson, Magnus
2016-01-01
We examine the existence and properties of certain discrete breathers for a discrete nonlinear Schrödinger model where all but one site are placed in a ring and coupled to the additional central site. The discrete breathers we focus on are stationary solutions mainly localized on one or a few of the ring sites and possibly also the central site. By numerical methods, we trace out and study the continuous families the discrete breathers belong to. Our main result is the discovery of a split bifurcation at a critical value of the coupling between neighboring ring sites. Below this critical value, families form closed loops in a certain parameter space, implying that discrete breathers with and without central-site occupation belong to the same family. Above the split bifurcation the families split up into several separate ones, which bifurcate with solutions with constant ring amplitudes. For symmetry reasons, the families have different properties below the split bifurcation for even and odd numbers of sites. It is also determined under which conditions the discrete breathers are linearly stable. The dynamics of some simpler initial conditions that approximate the discrete breathers are also studied and the parameter regimes where the dynamics remain localized close to the initially excited ring site are related to the linear stability of the exact discrete breathers.
Discrete Localized States and Localization Dynamics in Discrete Nonlinear Schrödinger Equations
DEFF Research Database (Denmark)
Christiansen, Peter Leth; Gaididei, Yu.B.; Mezentsev, V.K.
1996-01-01
Dynamics of two-dimensional discrete structures is studied in the framework of the generalized two-dimensional discrete nonlinear Schrodinger equation. The nonlinear coupling in the form of the Ablowitz-Ladik nonlinearity is taken into account. Stability properties of the stationary solutions...
Rosenstein, Joseph G., Ed.; Franzblau, Deborah S., Ed.; Roberts, Fred S., Ed.
This book is a collection of articles by experienced educators and explains why and how discrete mathematics should be taught in K-12 classrooms. It includes evidence for "why" and practical guidance for "how" and also discusses how discrete mathematics can be used as a vehicle for achieving the broader goals of the major…
Stochastic Synapses Enable Efficient Brain-Inspired Learning Machines
Neftci, Emre O.; Pedroni, Bruno U.; Joshi, Siddharth; Al-Shedivat, Maruan; Cauwenberghs, Gert
2016-01-01
Recent studies have shown that synaptic unreliability is a robust and sufficient mechanism for inducing the stochasticity observed in cortex. Here, we introduce Synaptic Sampling Machines (S2Ms), a class of neural network models that uses synaptic stochasticity as a means to Monte Carlo sampling and unsupervised learning. Similar to the original formulation of Boltzmann machines, these models can be viewed as a stochastic counterpart of Hopfield networks, but where stochasticity is induced by a random mask over the connections. Synaptic stochasticity plays the dual role of an efficient mechanism for sampling, and a regularizer during learning akin to DropConnect. A local synaptic plasticity rule implementing an event-driven form of contrastive divergence enables the learning of generative models in an on-line fashion. S2Ms perform equally well using discrete-timed artificial units (as in Hopfield networks) or continuous-timed leaky integrate and fire neurons. The learned representations are remarkably sparse and robust to reductions in bit precision and synapse pruning: removal of more than 75% of the weakest connections followed by cursory re-learning causes a negligible performance loss on benchmark classification tasks. The spiking neuron-based S2Ms outperform existing spike-based unsupervised learners, while potentially offering substantial advantages in terms of power and complexity, and are thus promising models for on-line learning in brain-inspired hardware. PMID:27445650
Directory of Open Access Journals (Sweden)
Nagi F Idris
2009-06-01
Full Text Available Recent studies in our laboratory have shown that PCP (phencyclidine and d-amphetamine induce a cognitive deficit in rats, in a paradigm of potential relevance for the pathology of schizophrenia. Atypical, but not classical antipsychotics and the anticonvulsant, lamotrigine have been shown to prevent a selective reversal learning deficit induced by PCP. In contrast, only haloperidol reversed the d-amphetamine-induced deficit. The present study aimed to explore the ability of two anticonvulsants with differing mechanism of action, valproate and phenytoin to attenuate the cognitive deficits induced by PCP and d-amphetamine in the reversal learning paradigm. PCP at 1.5mg/kg and d-amphetamine at 0.5mg/kg both produced a selective and significant reduction in performance of the reversal phase with no effect on the initial phase of the task in female-hooded Lister rats. Valproate (25-200mg/kg and phenytoin (25-50mg/kg had no effect on performance when administered alone. Valproate (100-200mg/kg, whose principle action is thought to be the enhancement of GABA transmission, was unable to prevent the cognitive deficit induced by either PCP or d-amphetamine. Conversely, phenytoin (50mg/kg, a use-dependent sodium channel inhibitor, significantly prevented the deficit induced by PCP, but not d-amphetamine. These results add to our earlier work with lamotrigine, and suggest that sodium channel blockade may be a mechanism by which some anticonvulsant drugs can prevent the PCP-induced deficit. These data have implications for the use of anticonvulsant drugs in the treatment of cognitive or psychotic disorders.
Limit sets for the discrete spectrum of complex Jacobi matrices
International Nuclear Information System (INIS)
Golinskii, L B; Egorova, I E
2005-01-01
The discrete spectrum of complex Jacobi matrices that are compact perturbations of the discrete Laplacian is studied. The precise stabilization rate (in the sense of order) of the matrix elements ensuring the finiteness of the discrete spectrum is found. An example of a Jacobi matrix with discrete spectrum having a unique limit point is constructed. These results are discrete analogues of Pavlov's well-known results on Schroedinger operators with complex potential on a half-axis.
Euler-Poincare reduction for discrete field theories
International Nuclear Information System (INIS)
Vankerschaver, Joris
2007-01-01
In this note, we develop a theory of Euler-Poincare reduction for discrete Lagrangian field theories. We introduce the concept of Euler-Poincare equations for discrete field theories, as well as a natural extension of the Moser-Veselov scheme, and show that both are equivalent. The resulting discrete field equations are interpreted in terms of discrete differential geometry. An application to the theory of discrete harmonic mappings is also briefly discussed
Integrals of Motion for Discrete-Time Optimal Control Problems
Torres, Delfim F. M.
2003-01-01
We obtain a discrete time analog of E. Noether's theorem in Optimal Control, asserting that integrals of motion associated to the discrete time Pontryagin Maximum Principle can be computed from the quasi-invariance properties of the discrete time Lagrangian and discrete time control system. As corollaries, results for first-order and higher-order discrete problems of the calculus of variations are obtained.
The ultimatum game: Discrete vs. continuous offers
Dishon-Berkovits, Miriam; Berkovits, Richard
2014-09-01
In many experimental setups in social-sciences, psychology and economy the subjects are requested to accept or dispense monetary compensation which is usually given in discrete units. Using computer and mathematical modeling we show that in the framework of studying the dynamics of acceptance of proposals in the ultimatum game, the long time dynamics of acceptance of offers in the game are completely different for discrete vs. continuous offers. For discrete values the dynamics follow an exponential behavior. However, for continuous offers the dynamics are described by a power-law. This is shown using an agent based computer simulation as well as by utilizing an analytical solution of a mean-field equation describing the model. These findings have implications to the design and interpretation of socio-economical experiments beyond the ultimatum game.
Symmetric, discrete fractional splines and Gabor systems
DEFF Research Database (Denmark)
Søndergaard, Peter Lempel
2006-01-01
In this paper we consider fractional splines as windows for Gabor frames. We introduce two new types of symmetric, fractional splines in addition to one found by Unser and Blu. For the finite, discrete case we present two families of splines: One is created by sampling and periodizing the continu......In this paper we consider fractional splines as windows for Gabor frames. We introduce two new types of symmetric, fractional splines in addition to one found by Unser and Blu. For the finite, discrete case we present two families of splines: One is created by sampling and periodizing...... the continuous splines, and one is a truly finite, discrete construction. We discuss the properties of these splines and their usefulness as windows for Gabor frames and Wilson bases....
Sputtering calculations with the discrete ordinated method
International Nuclear Information System (INIS)
Hoffman, T.J.; Dodds, H.L. Jr.; Robinson, M.T.; Holmes, D.K.
1977-01-01
The purpose of this work is to investigate the applicability of the discrete ordinates (S/sub N/) method to light ion sputtering problems. In particular, the neutral particle discrete ordinates computer code, ANISN, was used to calculate sputtering yields. No modifications to this code were necessary to treat charged particle transport. However, a cross section processing code was written for the generation of multigroup cross sections; these cross sections include a modification to the total macroscopic cross section to account for electronic interactions and small-scattering-angle elastic interactions. The discrete ordinates approach enables calculation of the sputtering yield as functions of incident energy and angle and of many related quantities such as ion reflection coefficients, angular and energy distributions of sputtering particles, the behavior of beams penetrating thin foils, etc. The results of several sputtering problems as calculated with ANISN are presented
Modeling discrete time-to-event data
Tutz, Gerhard
2016-01-01
This book focuses on statistical methods for the analysis of discrete failure times. Failure time analysis is one of the most important fields in statistical research, with applications affecting a wide range of disciplines, in particular, demography, econometrics, epidemiology and clinical research. Although there are a large variety of statistical methods for failure time analysis, many techniques are designed for failure times that are measured on a continuous scale. In empirical studies, however, failure times are often discrete, either because they have been measured in intervals (e.g., quarterly or yearly) or because they have been rounded or grouped. The book covers well-established methods like life-table analysis and discrete hazard regression models, but also introduces state-of-the art techniques for model evaluation, nonparametric estimation and variable selection. Throughout, the methods are illustrated by real life applications, and relationships to survival analysis in continuous time are expla...
Direct Discrete Method for Neutronic Calculations
International Nuclear Information System (INIS)
Vosoughi, Naser; Akbar Salehi, Ali; Shahriari, Majid
2002-01-01
The objective of this paper is to introduce a new direct method for neutronic calculations. This method which is named Direct Discrete Method, is simpler than the neutron Transport equation and also more compatible with physical meaning of problems. This method is based on physic of problem and with meshing of the desired geometry, writing the balance equation for each mesh intervals and with notice to the conjunction between these mesh intervals, produce the final discrete equations series without production of neutron transport differential equation and mandatory passing from differential equation bridge. We have produced neutron discrete equations for a cylindrical shape with two boundary conditions in one group energy. The correction of the results from this method are tested with MCNP-4B code execution. (authors)
An algebra of discrete event processes
Heymann, Michael; Meyer, George
1991-01-01
This report deals with an algebraic framework for modeling and control of discrete event processes. The report consists of two parts. The first part is introductory, and consists of a tutorial survey of the theory of concurrency in the spirit of Hoare's CSP, and an examination of the suitability of such an algebraic framework for dealing with various aspects of discrete event control. To this end a new concurrency operator is introduced and it is shown how the resulting framework can be applied. It is further shown that a suitable theory that deals with the new concurrency operator must be developed. In the second part of the report the formal algebra of discrete event control is developed. At the present time the second part of the report is still an incomplete and occasionally tentative working paper.
Is Fitts' law continuous in discrete aiming?
Directory of Open Access Journals (Sweden)
Rita Sleimen-Malkoun
Full Text Available The lawful continuous linear relation between movement time and task difficulty (i.e., index of difficulty; ID in a goal-directed rapid aiming task (Fitts' law has been recently challenged in reciprocal performance. Specifically, a discontinuity was observed at critical ID and was attributed to a transition between two distinct dynamic regimes that occurs with increasing difficulty. In the present paper, we show that such a discontinuity is also present in discrete aiming when ID is manipulated via target width (experiment 1 but not via target distance (experiment 2. Fitts' law's discontinuity appears, therefore, to be a suitable indicator of the underlying functional adaptations of the neuro-muscular-skeletal system to task properties/requirements, independently of reciprocal or discrete nature of the task. These findings open new perspectives to the study of dynamic regimes involved in discrete aiming and sensori-motor mechanisms underlying the speed-accuracy trade-off.
Acceleration techniques for the discrete ordinate method
International Nuclear Information System (INIS)
Efremenko, Dmitry; Doicu, Adrian; Loyola, Diego; Trautmann, Thomas
2013-01-01
In this paper we analyze several acceleration techniques for the discrete ordinate method with matrix exponential and the small-angle modification of the radiative transfer equation. These techniques include the left eigenvectors matrix approach for computing the inverse of the right eigenvectors matrix, the telescoping technique, and the method of false discrete ordinate. The numerical simulations have shown that on average, the relative speedup of the left eigenvector matrix approach and the telescoping technique are of about 15% and 30%, respectively. -- Highlights: ► We presented the left eigenvector matrix approach. ► We analyzed the method of false discrete ordinate. ► The telescoping technique is applied for matrix operator method. ► Considered techniques accelerate the computations by 20% in average.
Discrete quantum geometries and their effective dimension
International Nuclear Information System (INIS)
Thuerigen, Johannes
2015-01-01
In several approaches towards a quantum theory of gravity, such as group field theory and loop quantum gravity, quantum states and histories of the geometric degrees of freedom turn out to be based on discrete spacetime. The most pressing issue is then how the smooth geometries of general relativity, expressed in terms of suitable geometric observables, arise from such discrete quantum geometries in some semiclassical and continuum limit. In this thesis I tackle the question of suitable observables focusing on the effective dimension of discrete quantum geometries. For this purpose I give a purely combinatorial description of the discrete structures which these geometries have support on. As a side topic, this allows to present an extension of group field theory to cover the combinatorially larger kinematical state space of loop quantum gravity. Moreover, I introduce a discrete calculus for fields on such fundamentally discrete geometries with a particular focus on the Laplacian. This permits to define the effective-dimension observables for quantum geometries. Analysing various classes of quantum geometries, I find as a general result that the spectral dimension is more sensitive to the underlying combinatorial structure than to the details of the additional geometric data thereon. Semiclassical states in loop quantum gravity approximate the classical geometries they are peaking on rather well and there are no indications for stronger quantum effects. On the other hand, in the context of a more general model of states which are superposition over a large number of complexes, based on analytic solutions, there is a flow of the spectral dimension from the topological dimension d on low energy scales to a real number between 0 and d on high energy scales. In the particular case of 1 these results allow to understand the quantum geometry as effectively fractal.
Synchronization Of Parallel Discrete Event Simulations
Steinman, Jeffrey S.
1992-01-01
Adaptive, parallel, discrete-event-simulation-synchronization algorithm, Breathing Time Buckets, developed in Synchronous Parallel Environment for Emulation and Discrete Event Simulation (SPEEDES) operating system. Algorithm allows parallel simulations to process events optimistically in fluctuating time cycles that naturally adapt while simulation in progress. Combines best of optimistic and conservative synchronization strategies while avoiding major disadvantages. Algorithm processes events optimistically in time cycles adapting while simulation in progress. Well suited for modeling communication networks, for large-scale war games, for simulated flights of aircraft, for simulations of computer equipment, for mathematical modeling, for interactive engineering simulations, and for depictions of flows of information.
Speeding Up Network Simulations Using Discrete Time
Lucas, Aaron; Armbruster, Benjamin
2013-01-01
We develop a way of simulating disease spread in networks faster at the cost of some accuracy. Instead of a discrete event simulation (DES) we use a discrete time simulation. This aggregates events into time periods. We prove a bound on the accuracy attained. We also discuss the choice of step size and do an analytical comparison of the computational costs. Our error bound concept comes from the theory of numerical methods for SDEs and the basic proof structure comes from the theory of numeri...
PHASE CHAOS IN THE DISCRETE KURAMOTO MODEL
DEFF Research Database (Denmark)
Maistrenko, V.; Vasylenko, A.; Maistrenko, Y.
2010-01-01
The paper describes the appearance of a novel, high-dimensional chaotic regime, called phase chaos, in a time-discrete Kuramoto model of globally coupled phase oscillators. This type of chaos is observed at small and intermediate values of the coupling strength. It arises from the nonlinear...... interaction among the oscillators, while the individual oscillators behave periodically when left uncoupled. For the four-dimensional time-discrete Kuramoto model, we outline the region of phase chaos in the parameter plane and determine the regions where phase chaos coexists with different periodic...
A Low Complexity Discrete Radiosity Method
Chatelier , Pierre Yves; Malgouyres , Rémy
2006-01-01
International audience; Rather than using Monte Carlo sampling techniques or patch projections to compute radiosity, it is possible to use a discretization of a scene into voxels and perform some discrete geometry calculus to quickly compute visibility information. In such a framework , the radiosity method may be as precise as a patch-based radiosity using hemicube computation for form-factors, but it lowers the overall theoretical complexity to an O(N log N) + O(N), where the O(N) is largel...
Modeling and simulation of discrete event systems
Choi, Byoung Kyu
2013-01-01
Computer modeling and simulation (M&S) allows engineers to study and analyze complex systems. Discrete-event system (DES)-M&S is used in modern management, industrial engineering, computer science, and the military. As computer speeds and memory capacity increase, so DES-M&S tools become more powerful and more widely used in solving real-life problems. Based on over 20 years of evolution within a classroom environment, as well as on decades-long experience in developing simulation-based solutions for high-tech industries, Modeling and Simulation of Discrete-Event Systems is the only book on
Logic and discrete mathematics a concise introduction
Conradie, Willem
2015-01-01
A concise yet rigorous introduction to logic and discrete mathematics. This book features a unique combination of comprehensive coverage of logic with a solid exposition of the most important fields of discrete mathematics, presenting material that has been tested and refined by the authors in university courses taught over more than a decade. The chapters on logic - propositional and first-order - provide a robust toolkit for logical reasoning, emphasizing the conceptual understanding of the language and the semantics of classical logic as well as practical applications through the easy
Semiclassical expanding discrete space-times
International Nuclear Information System (INIS)
Cobb, W.K.; Smalley, L.L.
1981-01-01
Given the close ties between general relativity and geometry one might reasonably expect that quantum effects associated with gravitation might also be tied to the geometry of space-time, namely, to some sort of discreteness in space-time itself. In particular it is supposed that space-time consists of a discrete lattice of points rather than the usual continuum. Since astronomical evidence seems to suggest that the universe is expanding, the lattice must also expand. Some of the implications of such a model are that the proton should presently be stable, and the universe should be closed although the mechanism for closure is quantum mechanical. (author)
Systematization of Accurate Discrete Optimization Methods
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V. A. Ovchinnikov
2015-01-01
Full Text Available The object of study of this paper is to define accurate methods for solving combinatorial optimization problems of structural synthesis. The aim of the work is to systemize the exact methods of discrete optimization and define their applicability to solve practical problems.The article presents the analysis, generalization and systematization of classical methods and algorithms described in the educational and scientific literature.As a result of research a systematic presentation of combinatorial methods for discrete optimization described in various sources is given, their capabilities are described and properties of the tasks to be solved using the appropriate methods are specified.