Apprendimento hebbiano in robotica: teoria e applicazione

Partendo dallo sviluppo della teoria dell'apprendimento Hebbiano, si delinea un percorso per la creazione di robot in grado di apprendere tramite architettura DAC e Value System.

Effect of mesh distortion on the accuracy of high order vorticity-velocity CFD approaches

The numerical solution of the incompressible Navier-Stokes equations offers an alternative to experimental analysis of fluid-structure interaction (FSI). We would save a lot of time and effort and help cut back on costs, if we are able to accurately model systems by these numerical solutions. These advantages are even more obvious when considering huge structures like bridges, high rise buildings or even wind turbine blades with diameters as large as 200 meters. The modeling of such processes, however, involves complex multiphysics problems along with complex geometries. This thesis focuses on a novel vorticity-velocity formulation called the Kinematic Laplacian Equation (KLE) to solve the incompressible Navier-stokes equations for such FSI problems. This scheme allows for the implementation of robust adaptive ordinary differential equations (ODE) time integration schemes, allowing us to tackle each problem as a separate module. The current algortihm for the KLE uses an unstructured quadrilateral mesh, formed by dividing each triangle of an unstructured triangular mesh into three quadrilaterals for spatial discretization. This research deals with determining a suitable measure of mesh quality based on the physics of the problems being tackled. This is followed by exploring methods to improve the quality of quadrilateral elements obtained from the triangles and thereby improving the overall mesh quality. A series of numerical experiments were designed and conducted for this purpose and the results obtained were tested on different geometries with varying degrees of mesh density.

Effect of high order interpolation in the stability and efficiency of the time-integration process in vorticity-velocity CFD algorithms

The numerical solution of the incompressible Navier-Stokes Equations offers an effective alternative to the experimental analysis of Fluid-Structure interaction i.e. dynamical coupling between a fluid and a solid which otherwise is very complex, time consuming and very expensive. To have a method which can accurately model these types of mechanical systems by numerical solutions becomes a great option, since these advantages are even more obvious when considering huge structures like bridges, high rise buildings, or even wind turbine blades with diameters as large as 200 meters. The modeling of such processes, however, involves complex multiphysics problems along with complex geometries. This thesis focuses on a novel vorticity-velocity formulation called the KLE to solve the incompressible Navier-stokes equations for such FSI problems. This scheme allows for the implementation of robust adaptive ODE time integration schemes and thus allows us to tackle the various multiphysics problems as separate modules. The current algorithm for KLE employs a structured or unstructured mesh for spatial discretization and it allows the use of a self-adaptive or fixed time step ODE solver while dealing with unsteady problems. This research deals with the analysis of the effects of the Courant-Friedrichs-Lewy (CFL) condition for KLE when applied to unsteady Stoke’s problem. The objective is to conduct a numerical analysis for stability and, hence, for convergence. Our results confirmthat the time step ∆t is constrained by the CFL-like condition ∆t ≤ const. hα, where h denotes the variable that represents spatial discretization.

Environmental change within the Balkan region during the past ca. 50 ka recorded in the sediments from lakes Prespa and Ohrid

Abstract. Lakes Prespa and Ohrid, in the Balkan region, are considered to be amongst the oldest lakes in Europe. Both lakes are hydraulically connected via karst aquifers. From Lake Ohrid, several sediment cores up to 15m long have been studied over the last few years. Here, we document the first long sediment record from nearby Lake Prespa to clarify the influence of Lake Prespa on Lake Ohrid and the environmental history of the region. Radiocarbon dating and dated tephra layers provide robust age control and indicate that the 10.5m long sediment record from Lake Prespa reaches back to 48 ka. Glacial sedimentation is characterized by low organic matter content and absence of carbonates in the sediments, which indicate oligotrophic conditions in both lakes. Holocene sedimentation is characterized by particularly high carbonate content in Lake Ohrid and by particularly high organic matter content in Lake Prespa, which indicates a shift towards more mesotrophic conditions in the latter. Long-term environmental change and short-term events, such as related to the Heinrich events during the Pleistocene or the 8.2 ka cooling event during the Holocene, are well recorded in both lakes, but are only evident in certain proxies. The comparison of the sediment cores from both lakes indicates that environmental change affects particularly the trophic state of Lake Prespa due to its lower volume and water depth.

NEW TOOLS FOR MONITORING GAMMA CAMERA UNIFORMITY

Detector uniformity is a fundamental performance characteristic of all modern gamma camera systems, and ensuring a stable, uniform detector response is critical for maintaining clinical images that are free of artifact. For these reasons, the assessment of detector uniformity is one of the most common activities associated with a successful clinical quality assurance program in gamma camera imaging. The evaluation of this parameter, however, is often unclear because it is highly dependent upon acquisition conditions, reviewer expertise, and the application of somewhat arbitrary limits that do not characterize the spatial location of the non-uniformities. Furthermore, as the goal of any robust quality control program is the determination of significant deviations from standard or baseline conditions, clinicians and vendors often neglect the temporal nature of detector degradation (1). This thesis describes the development and testing of new methods for monitoring detector uniformity. These techniques provide more quantitative, sensitive, and specific feedback to the reviewer so that he or she may be better equipped to identify performance degradation prior to its manifestation in clinical images. The methods exploit the temporal nature of detector degradation and spatially segment distinct regions-of-non-uniformity using multi-resolution decomposition. These techniques were tested on synthetic phantom data using different degradation functions, as well as on experimentally acquired time series floods with induced, progressively worsening defects present within the field-of-view. The sensitivity of conventional, global figures-of-merit for detecting changes in uniformity was evaluated and compared to these new image-space techniques. The image-space algorithms provide a reproducible means of detecting regions-of-non-uniformity prior to any single flood image’s having a NEMA uniformity value in excess of 5%. The sensitivity of these image-space algorithms was found to depend on the size and magnitude of the non-uniformities, as well as on the nature of the cause of the non-uniform region. A trend analysis of the conventional figures-of-merit demonstrated their sensitivity to shifts in detector uniformity. The image-space algorithms are computationally efficient. Therefore, the image-space algorithms should be used concomitantly with the trending of the global figures-of-merit in order to provide the reviewer with a richer assessment of gamma camera detector uniformity characteristics.

Proceedings of the 22nd Annual Biochemical Engineering Symposium

This is the twenty-second of a series of symposia devoted to talks and posters by students about their biochemical engineering research. The first, third, fifth, ninth, twelfth, sixteenth, and twenti~th were hosted by Kansas State University, the second and fourth by the University of Nebraska- Lincoln, the sixth, seventh, tenth, thirteenth, seventeenth, and twenty-second by Iowa State University, the eighth, fourteenth, and nineteenth by the University of Missouri-Columbia, the eleventh, fifteenth, and twenty-first by Colorado State University, and the eighteenth by the University of Colorado. Next year's symposium will be at the University of Oklahoma. Symposium proceedings are edited and issued by faculty of the host institution. Because final publication usually takes place in refereed journals, articles included here are brief and often cover work in progress. ContentsC. A. Baldwin, J.P. McDonald, and L. E. Erickson, Kansas State University. Effect of Hydrocarbon Phase on Kinetic and Transport Limitations for Bioremediation of Microporous Soil J. C. Wang, S. K. Banerji, and Rakesh Bajpai, University of Missouri-Columbia. Migration of PCP in Soil-Columns in Presence of a Second Organic Phase Cheng-Hsien Hsu and Roger G. Harrison, University of Oklahoma. Bacterial Leaching of Zinc and Copper from Mining Wastes James A. Searles, Paul Todd, and Dhinakar S. Kompala, University of Colorado. Suspension Culture of Chinese Hamster Ovary Cells Utilizing Inclined Sedimentation Ron Beyerinck and Eric H. Dunlop, Colorado State University. The Effect of Feed Zone Turbulence as Measured by Laser Doppler Velocimetry on Baker's Yeast Metabolism in a Chemostat Paul Li-Hong Yeh, GraceY. Sun, Gary A. Weisman, and Rakesh Bajpai, University of Missouri-Columbia. Effect of Medium Constituents upon Membrane Composition of Insect Cells R. Shane Gold, M. M. Meagher, R. Hutkins, and T. Conway, University of Nebraska-Lincoin. Ethanol Tolerance and Carbohydrate Metabolism in Lactobacilli John Sargantanis and M. N. Karim, Colorado State University. Application of Kalman Filter and Adaptive Control in Solid Substrate Fermentation D. Vrana, M. Meagher, and R. Hutkins, University of Nebraska-Lincoln. Product Recovery Optimization in the ABE Fermentation Kalyan R. Tadikonda and Robert H. Davis, University of Colorado. Cell Separations Using Targeted Monoclonal Antibodies Against Surface Proteins Meng H. Heng and Charles E. Glatz, Iowa State University. Charged Fusion for Selective Recovery of B-Galactosidase from Cell Extract Using Hollow Fiber Ion-Exchange Membrane Adsorption Hsiu-Mei Chen, Peter J. Reilly, and Clark Ford, Iowa State University. Site-Directed Mutagenesis to Enhance Thermostability of Glucoamylase from Aspergillus: A Rational Approach P. Tuitemwong, L. E. Erickson, and D. Y. C. Fung, Kansas State University. Applications of Enzymatic Hydrolysis and Fermentation on the Reduction of Flatulent Sugars in the Rapid Hydration Hydrothermal Cooked Soy Milk Sanjeev Redkar and Robert H. Davis, University of Colorado. Crossflow Microfiltration of Yeast Suspensions Linda Henk and James C. Linden, Colorado State University, and Irving C. Anderson, Iowa State University. Evaluation of Sorghum Ensilage as an Ethanol Feedstock Marc Lipovitch and James C. Linden, Colorado State University. Stability and Biomass Feedstock Pretreatability for Simultaneous Saccharification and Fermentation Ali Demirci, Anthony L. Pometto Ill, and Kenneth E. Johnson, Iowa State University. Application of Biofilm Reactors in Lactic Acid Fermentation Michael K. Dowd, Peter I. Reilly, and WalterS. Trahanovsky, Iowa State University. Low Molecular-Weight Organic Composition of Ethanol Stillage from Corn Craig E. Forney, Meng H. Heng, John R. Luther, Mark Q. Niederauer, and Charles E. Glatz, Iowa State University. Enhancement of Protein Separation Using Genetic Engineering J. F. Shimp, J. C. Tracy, E. Lee, L. C. Davis, and L. E. Erickson, Kansas State University. Modeling Contaminant Transport, Biodegradation and Uptake by Plants in the Rhizosphere Xiaoqing Yang, L. E. Erickson, and L. T. Fan, Kansas State University. Modeling of Dispersive-Convective Characteristics in Bioremediation of Contaminated Soil Jan Johansson and Rakesh Bajpai, University of Missouri-Columbia. Fouling of Membranes J. M. Wang, S. K. Banerji, and R. K. Bajpai, University of Missouri-Columbia. Migration of Sodium-Pentachorophenol (Na-PCP) in Unsaturated and Saturated Soil-Columns J. Sweeney and M. Meagher, University of Nebraska-Lincoln. The Purification of Alpha-D-Glucuronidase from Trichoderma reesei

Sedimentology and geochemistry on core Co1204

Lakes Prespa and Ohrid, in the Balkan region, are considered to be amongst the oldest lakes in Europe. Both lakes are hydraulically connected via karst aquifers. From Lake Ohrid, several sediment cores up to 15 m long have been studied over the last few years. Here, we document the first long sediment record from nearby Lake Prespa to clarify the influence of Lake Prespa on Lake Ohrid and the environmental history of the region. Radiocarbon dating and dated tephra layers provide robust age control and indicate that the 10.5 m long sediment record from Lake Prespa reaches back to 48 ka. Glacial sedimentation is characterized by low organic matter content and absence of carbonates in the sediments, which indicate oligotrophic conditions in both lakes. Holocene sedimentation is characterized by particularly high carbonate content in Lake Ohrid and by particularly high organic matter content in Lake Prespa, which indicates a shift towards more mesotrophic conditions in the latter. Long-term environmental change and short-term events, such as related to the Heinrich events during the Pleistocene or the 8.2 ka cooling event during the Holocene, are well recorded in both lakes, but are only evident in certain proxies. The comparison of the sediment cores from both lakes indicates that environmental change affects particularly the trophic state of Lake Prespa due to its lower volume and water depth.

Aerial Remote Sensing in Agriculture: A Practical Approach to Area Coverage and Path Planning for Fleets of Mini Aerial Robots

In this paper, a system that allows applying precision agriculture techniques is described. The application is based on the deployment of a team of unmanned aerial vehicles that are able to take georeferenced pictures in order to create a full map by applying mosaicking procedures for postprocessing. The main contribution of this work is practical experimentation with an integrated tool. Contributions in different fields are also reported. Among them is a new one-phase automatic task partitioning manager, which is based on negotiation among the aerial vehicles, considering their state and capabilities. Once the individual tasks are assigned, an optimal path planning algorithm is in charge of determining the best path for each vehicle to follow. Also, a robust flight control based on the use of a control law that improves the maneuverability of the quadrotors has been designed. A set of field tests was performed in order to analyze all the capabilities of the system, from task negotiations to final performance. These experiments also allowed testing control robustness under different weather conditions.

A general stability criterion for switched linear systems having stable and unstable subsystems

We report conditions on a switching signal that guarantee that solutions of a switched linear systems converge asymptotically to zero. These conditions are apply to continuous, discrete-time and hybrid switched linear systems, both those having stable subsystems and mixtures of stable and unstable subsystems.

Contributions to the Resilience Management in the Internet of Things

El auge del "Internet de las Cosas" (IoT, "Internet of Things") y sus tecnologías asociadas han permitido su aplicación en diversos dominios de la aplicación, entre los que se encuentran la monitorización de ecosistemas forestales, la gestión de catástrofes y emergencias, la domótica, la automatización industrial, los servicios para ciudades inteligentes, la eficiencia energética de edificios, la detección de intrusos, la gestión de desastres y emergencias o la monitorización de señales corporales, entre muchas otras. La desventaja de una red IoT es que una vez desplegada, ésta queda desatendida, es decir queda sujeta, entre otras cosas, a condiciones climáticas cambiantes y expuestas a catástrofes naturales, fallos de software o hardware, o ataques maliciosos de terceros, por lo que se puede considerar que dichas redes son propensas a fallos. El principal requisito de los nodos constituyentes de una red IoT es que estos deben ser capaces de seguir funcionando a pesar de sufrir errores en el propio sistema. La capacidad de la red para recuperarse ante fallos internos y externos inesperados es lo que se conoce actualmente como "Resiliencia" de la red. Por tanto, a la hora de diseñar y desplegar aplicaciones o servicios para IoT, se espera que la red sea tolerante a fallos, que sea auto-configurable, auto-adaptable, auto-optimizable con respecto a nuevas condiciones que puedan aparecer durante su ejecución. Esto lleva al análisis de un problema fundamental en el estudio de las redes IoT, el problema de la "Conectividad". Se dice que una red está conectada si todo par de nodos en la red son capaces de encontrar al menos un camino de comunicación entre ambos. Sin embargo, la red puede desconectarse debido a varias razones, como que se agote la batería, que un nodo sea destruido, etc. Por tanto, se hace necesario gestionar la resiliencia de la red con el objeto de mantener la conectividad entre sus nodos, de tal manera que cada nodo IoT sea capaz de proveer servicios continuos, a otros nodos, a otras redes o, a otros servicios y aplicaciones. En este contexto, el objetivo principal de esta tesis doctoral se centra en el estudio del problema de conectividad IoT, más concretamente en el desarrollo de modelos para el análisis y gestión de la Resiliencia, llevado a la práctica a través de las redes WSN, con el fin de mejorar la capacidad la tolerancia a fallos de los nodos que componen la red. Este reto se aborda teniendo en cuenta dos enfoques distintos, por una parte, a diferencia de otro tipo de redes de dispositivos convencionales, los nodos en una red IoT son propensos a perder la conexión, debido a que se despliegan en entornos aislados, o en entornos con condiciones extremas; por otra parte, los nodos suelen ser recursos con bajas capacidades en términos de procesamiento, almacenamiento y batería, entre otros, por lo que requiere que el diseño de la gestión de su resiliencia sea ligero, distribuido y energéticamente eficiente. En este sentido, esta tesis desarrolla técnicas auto-adaptativas que permiten a una red IoT, desde la perspectiva del control de su topología, ser resiliente ante fallos en sus nodos. Para ello, se utilizan técnicas basadas en lógica difusa y técnicas de control proporcional, integral y derivativa (PID - "proportional-integral-derivative"), con el objeto de mejorar la conectividad de la red, teniendo en cuenta que el consumo de energía debe preservarse tanto como sea posible. De igual manera, se ha tenido en cuenta que el algoritmo de control debe ser distribuido debido a que, en general, los enfoques centralizados no suelen ser factibles a despliegues a gran escala. El presente trabajo de tesis implica varios retos que conciernen a la conectividad de red, entre los que se incluyen: la creación y el análisis de modelos matemáticos que describan la red, una propuesta de sistema de control auto-adaptativo en respuesta a fallos en los nodos, la optimización de los parámetros del sistema de control, la validación mediante una implementación siguiendo un enfoque de ingeniería del software y finalmente la evaluación en una aplicación real. Atendiendo a los retos anteriormente mencionados, el presente trabajo justifica, mediante una análisis matemático, la relación existente entre el "grado de un nodo" (definido como el número de nodos en la vecindad del nodo en cuestión) y la conectividad de la red, y prueba la eficacia de varios tipos de controladores que permiten ajustar la potencia de trasmisión de los nodos de red en respuesta a eventuales fallos, teniendo en cuenta el consumo de energía como parte de los objetivos de control. Así mismo, este trabajo realiza una evaluación y comparación con otros algoritmos representativos; en donde se demuestra que el enfoque desarrollado es más tolerante a fallos aleatorios en los nodos de la red, así como en su eficiencia energética. Adicionalmente, el uso de algoritmos bioinspirados ha permitido la optimización de los parámetros de control de redes dinámicas de gran tamaño. Con respecto a la implementación en un sistema real, se han integrado las propuestas de esta tesis en un modelo de programación OSGi ("Open Services Gateway Initiative") con el objeto de crear un middleware auto-adaptativo que mejore la gestión de la resiliencia, especialmente la reconfiguración en tiempo de ejecución de componentes software cuando se ha producido un fallo. Como conclusión, los resultados de esta tesis doctoral contribuyen a la investigación teórica y, a la aplicación práctica del control resiliente de la topología en redes distribuidas de gran tamaño. Los diseños y algoritmos presentados pueden ser vistos como una prueba novedosa de algunas técnicas para la próxima era de IoT. A continuación, se enuncian de forma resumida las principales contribuciones de esta tesis: (1) Se han analizado matemáticamente propiedades relacionadas con la conectividad de la red. Se estudia, por ejemplo, cómo varía la probabilidad de conexión de la red al modificar el alcance de comunicación de los nodos, así como cuál es el mínimo número de nodos que hay que añadir al sistema desconectado para su re-conexión. (2) Se han propuesto sistemas de control basados en lógica difusa para alcanzar el grado de los nodos deseado, manteniendo la conectividad completa de la red. Se han evaluado diferentes tipos de controladores basados en lógica difusa mediante simulaciones, y los resultados se han comparado con otros algoritmos representativos. (3) Se ha investigado más a fondo, dando un enfoque más simple y aplicable, el sistema de control de doble bucle, y sus parámetros de control se han optimizado empleando algoritmos heurísticos como el método de la entropía cruzada (CE, "Cross Entropy"), la optimización por enjambre de partículas (PSO, "Particle Swarm Optimization"), y la evolución diferencial (DE, "Differential Evolution"). (4) Se han evaluado mediante simulación, la mayoría de los diseños aquí presentados; además, parte de los trabajos se han implementado y validado en una aplicación real combinando técnicas de software auto-adaptativo, como por ejemplo las de una arquitectura orientada a servicios (SOA, "Service-Oriented Architecture"). ABSTRACT The advent of the Internet of Things (IoT) enables a tremendous number of applications, such as forest monitoring, disaster management, home automation, factory automation, smart city, etc. However, various kinds of unexpected disturbances may cause node failure in the IoT, for example battery depletion, software/hardware malfunction issues and malicious attacks. So, it can be considered that the IoT is prone to failure. The ability of the network to recover from unexpected internal and external failures is known as "resilience" of the network. Resilience usually serves as an important non-functional requirement when designing IoT, which can further be broken down into "self-*" properties, such as self-adaptive, self-healing, self-configuring, self-optimization, etc. One of the consequences that node failure brings to the IoT is that some nodes may be disconnected from others, such that they are not capable of providing continuous services for other nodes, networks, and applications. In this sense, the main objective of this dissertation focuses on the IoT connectivity problem. A network is regarded as connected if any pair of different nodes can communicate with each other either directly or via a limited number of intermediate nodes. More specifically, this thesis focuses on the development of models for analysis and management of resilience, implemented through the Wireless Sensor Networks (WSNs), which is a challenging task. On the one hand, unlike other conventional network devices, nodes in the IoT are more likely to be disconnected from each other due to their deployment in a hostile or isolated environment. On the other hand, nodes are resource-constrained in terms of limited processing capability, storage and battery capacity, which requires that the design of the resilience management for IoT has to be lightweight, distributed and energy-efficient. In this context, the thesis presents self-adaptive techniques for IoT, with the aim of making the IoT resilient against node failures from the network topology control point of view. The fuzzy-logic and proportional-integral-derivative (PID) control techniques are leveraged to improve the network connectivity of the IoT in response to node failures, meanwhile taking into consideration that energy consumption must be preserved as much as possible. The control algorithm itself is designed to be distributed, because the centralized approaches are usually not feasible in large scale IoT deployments. The thesis involves various aspects concerning network connectivity, including: creation and analysis of mathematical models describing the network, proposing self-adaptive control systems in response to node failures, control system parameter optimization, implementation using the software engineering approach, and evaluation in a real application. This thesis also justifies the relations between the "node degree" (the number of neighbor(s) of a node) and network connectivity through mathematic analysis, and proves the effectiveness of various types of controllers that can adjust power transmission of the IoT nodes in response to node failures. The controllers also take into consideration the energy consumption as part of the control goals. The evaluation is performed and comparison is made with other representative algorithms. The simulation results show that the proposals in this thesis can tolerate more random node failures and save more energy when compared with those representative algorithms. Additionally, the simulations demonstrate that the use of the bio-inspired algorithms allows optimizing the parameters of the controller. With respect to the implementation in a real system, the programming model called OSGi (Open Service Gateway Initiative) is integrated with the proposals in order to create a self-adaptive middleware, especially reconfiguring the software components at runtime when failures occur. The outcomes of this thesis contribute to theoretic research and practical applications of resilient topology control for large and distributed networks. The presented controller designs and optimization algorithms can be viewed as novel trials of the control and optimization techniques for the coming era of the IoT. The contributions of this thesis can be summarized as follows: (1) Mathematically, the fault-tolerant probability of a large-scale stochastic network is analyzed. It is studied how the probability of network connectivity depends on the communication range of the nodes, and what is the minimum number of neighbors to be added for network re-connection. (2) A fuzzy-logic control system is proposed, which obtains the desired node degree and in turn maintains the network connectivity when it is subject to node failures. There are different types of fuzzy-logic controllers evaluated by simulations, and the results demonstrate the improvement of fault-tolerant capability as compared to some other representative algorithms. (3) A simpler but more applicable approach, the two-loop control system is further investigated, and its control parameters are optimized by using some heuristic algorithms such as Cross Entropy (CE), Particle Swarm Optimization (PSO), and Differential Evolution (DE). (4) Most of the designs are evaluated by means of simulations, but part of the proposals are implemented and tested in a real-world application by combining the self-adaptive software technique and the control algorithms which are presented in this thesis.

Dynamic characteristics and adaptability of mouse vestibulo-ocular and optokinetic response eye movements and the role of the flocculo-olivary system revealed by chemical lesions

The dynamic characteristics of reflex eye movements were measured in two strains of chronically prepared mice by using an infrared television camera system. The horizontal vestibulo-ocular reflex (HVOR) and horizontal optokinetic response (HOKR) were induced by sinusoidal oscillations of a turntable, in darkness, by 10° (peak to peak) at 0.11–0.50 Hz and of a checked-pattern screen, in light, by 5–20°at 0.11–0.17 Hz, respectively. The gains and phases of the HVOR and HOKR of the C57BL/6 mice were nearly equivalent to those of rabbits and rats, whereas the 129/Sv mice exhibited very low gains in the HVOR and moderate phase lags in the HOKR, suggesting an inherent sensory-motor anomaly. Adaptability of the HOKR was examined in C57BL/6 mice by sustained screen oscillation. When the screen was oscillated by 10° at 0.17 Hz, which induced sufficient retinal slips, the gain of the HOKR increased by 0.08 in 1 h on average, whereas the stimuli that induced relatively small or no retinal slips affected the gain very little. Lesions of the flocculi induced by local applications of 0.1% ibotenic acid and lesions of the inferior olivary nuclei induced by i.p. injection of 3-acetylpyridine in C57BL/6 mice little affected the dynamic characteristics of the HVOR and HOKR, but abolished the adaptation of the HOKR. These results indicate that the olivo-floccular system plays an essential role in the adaptive control of the ocular reflex in mice, as suggested in other animal species. The data presented provide the basis for analyzing the reflex eye movements of genetically engineered mice.

Most central nervous system D2 dopamine receptors are coupled to their effectors by Go

We reported previously that Go-deficient mice develop severe neurological defects that include hyperalgesia, a generalized tremor, lack of coordination, and a turning syndrome somewhat reminiscent of unilateral lesions of the dopaminergic nigro-striatal pathway. By using frozen coronal sections of serially sectioned brains of normal and Go-deficient mice, we studied the ability of several G protein coupled receptors to promote binding of GTPγS to G proteins and the ability of GTP to promote a shift in the affinity of D2 dopamine receptor for its physiologic agonist dopamine. We found a generalized, but not abolished reduction in agonist-stimulated binding of GTPγS to frozen brain sections, with no significant left–right differences. Unexpectedly, the ability of GTP to regulate the binding affinity of dopamine to D2 receptors (as seen in in situ [35S]sulpiride displacement curves) that was robust in control mice, was absent in Go-deficient mice. The data suggest that most of the effects of the Gi/Go-coupled D2 receptors in the central nervous system are mediated by Go instead of Gi1, Gi2, or Gi3. In agreement with this, the effect of GTP on dopamine binding to D2 receptors in double Gi1 plus Gi2- and Gi1 plus Gi3-deficient mice was essentially unaffected.

FROG (formulation of a robot organization that generalizes) : a hardwardware [sic] experiment in machine cognition /

Vita.

Binomial leap methods for simulating stochastic chemical kinetics

This paper discusses efficient simulation methods for stochastic chemical kinetics. Based on the tau-leap and midpoint tau-leap methods of Gillespie [D. T. Gillespie, J. Chem. Phys. 115, 1716 (2001)], binomial random variables are used in these leap methods rather than Poisson random variables. The motivation for this approach is to improve the efficiency of the Poisson leap methods by using larger stepsizes. Unlike Poisson random variables whose range of sample values is from zero to infinity, binomial random variables have a finite range of sample values. This probabilistic property has been used to restrict possible reaction numbers and to avoid negative molecular numbers in stochastic simulations when larger stepsize is used. In this approach a binomial random variable is defined for a single reaction channel in order to keep the reaction number of this channel below the numbers of molecules that undergo this reaction channel. A sampling technique is also designed for the total reaction number of a reactant species that undergoes two or more reaction channels. Samples for the total reaction number are not greater than the molecular number of this species. In addition, probability properties of the binomial random variables provide stepsize conditions for restricting reaction numbers in a chosen time interval. These stepsize conditions are important properties of robust leap control strategies. Numerical results indicate that the proposed binomial leap methods can be applied to a wide range of chemical reaction systems with very good accuracy and significant improvement on efficiency over existing approaches. (C) 2004 American Institute of Physics.

区分服务网络中主动队列管理算法

现有区分服务网络的保证转发服务可提供稳定的带宽保证,但缺乏保证时延和分组丢失性能的有效方案.基于对RIO队列的稳态性能分析,提出两种自适应调整控制策略的主动队列管理算法(ARIO-D和ARIO-L).仿真结果表明,这两种算法在保持RIO算法带宽保证能力的同时,还可以提供稳定的和可区分的时延和分组丢失性能.采用ARIO-D和ARIO-L的保证转发服务可以为多媒体流量提供多种服务质量的定量保证. Current assured forwarding (AF) service in differentiated services (DiffServ) networks can provide stable guarantees in throughput, but is lacking of efficient schemes in ensuring queuing delay and loss ratio. By analyzing the steady state operating point of RIO, this paper proposes two active queue management algorithms with adaptive control policy, namely ARIO-D and ARIO-L. These two algorithms can provide differentiated performance in, respectively, queuing delay and loss ratio, in addition to throughput guarantee. By deploying ARIO-D and ARIO-L, AF service can provide quantitative guarantees for multimedia traffic with multiple QoS metrics.