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The objective of this thesis is to develop new methodologies for formal verification of nonlinear analog circuits. Therefore, new approaches to discrete modeling of analog circuits, specification of analog circuit properties and formal verification algorithms are introduced. Formal approaches to verification of analog circuits are not yet introduced into industrial design flows and still subject to research. Formal verification proves specification conformance for all possible input conditions and all possible internal states of a circuit. Automatically proving that a model of the circuit satisfies a declarative machine-readable property specification is referred to as model checking. Equivalence checking proves the equivalence of two circuit implementations. Starting from the state of the art in modeling analog circuits for simulation-based verification, discrete modeling of analog circuits for state space-based formal verification methodologies is motivated in this thesis. In order to improve the discrete modeling of analog circuits, a new trajectory-directed partitioning algorithm was developed in the scope of this thesis. This new approach determines the partitioning of the state space parallel or orthogonal to the trajectories of the state space dynamics. Therewith, a high accuracy of the successor relation is achieved in combination with a lower number of states necessary for a discrete model of equal accuracy compared to the state-of-the-art hyperbox-approach. The mapping of the partitioning to a discrete analog transition structure (DATS) enables the application of formal verification algorithms. By analyzing digital specification concepts and the existing approaches to analog property specification, the requirements for a new specification language for analog properties have been discussed in this thesis. On the one hand, it shall meet the requirements for formal specification of verification approaches applied to DATS models. On the other hand, the language syntax shall be oriented on natural language phrases. By synthesis of these requirements, the analog specification language (ASL) was developed in the scope of this thesis. The verification algorithms for model checking, that were developed in combination with ASL for application to DATS models generated with the new trajectory-directed approach, offer a significant enhancement compared to the state of the art. In order to prepare a transition of signal-based to state space-based verification methodologies, an approach to transfer transient simulation results from non-formal test bench simulation flows into a partial state space representation in form of a DATS has been developed in the scope of this thesis. As has been demonstrated by examples, the same ASL specification that was developed for formal model checking on complete discrete models could be evaluated without modifications on transient simulation waveforms. An approach to counterexample generation for the formal ASL model checking methodology offers to generate transition sequences from a defined starting state to a specification-violating state for inspection in transient simulation environments. Based on this counterexample generation, a new formal verification methodology using complete state space-covering input stimuli was developed. By conducting a transient simulation with these complete state space-covering input stimuli, the circuit adopts every state and transition that were visited during stimulus generation. An alternative formal verification methodology is given by retransferring the transient simulation responses to a DATS model and by applying the ASL verification algorithms in combination with an ASL property specification. Moreover, the complete state space-covering input stimuli can be applied to develop a formal equivalence checking methodology. Therewith, the equivalence of two implementations can be proven for every inner state of both systems by comparing the transient simulation responses to the complete-coverage stimuli of both circuits. In order to visually inspect the results of the newly introduced verification methodologies, an approach to dynamic state space visualization using multi-parallel particle simulation was developed. Due to the particles being randomly distributed over the complete state space and moving corresponding to the state space dynamics, another perspective to the system's behavior is provided that covers the state space and hence offers formal results. The prototypic implementations of the formal verification methodologies developed in the scope of this thesis have been applied to several example circuits. The acquired results for the new approaches to discrete modeling, specification and verification algorithms all demonstrate the capability of the new verification methodologies to be applied to complex circuit blocks and their properties.
Interview with Dario Azzellini, author of The Business of War and the new documentary film, Comuna Under Construction. What is it about Venezuela that is so interesting? Since 2003 I have practically lived in Venezuela. What motivates me is that I am interested in the social transformation process happening here. It’s a different type of revolution, a new left that draws from all the experiences of the 60s, 70s, 80s and 90s. ...
This thesis investigates the development of early cognition in infancy using neural network models. Fundamental events in visual perception such as caused motion, occlusion, object permanence, tracking of moving objects behind occluders, object unity perception and sequence learning are modeled in a unifying computational framework while staying close to experimental data in developmental psychology of infancy. In the first project, the development of causality and occlusion perception in infancy is modeled using a simple, three-layered, recurrent network trained with error backpropagation to predict future inputs (Elman network). The model unifies two infant studies on causality and occlusion perception. Subsequently, in the second project, the established framework is extended to a larger prediction network that models the development of object unity, object permanence and occlusion perception in infancy. It is shown that these different phenomena can be unified into a single theoretical framework thereby explaining experimental data from 14 infant studies. The framework shows that these developmental phenomena can be explained by accurately representing and predicting statistical regularities in the visual environment. The models assume (1) different neuronal populations processing different motion directions of visual stimuli in the visual cortex of the newborn infant which are supported by neuroscientific evidence and (2) available learning algorithms that are guided by the goal of predicting future events. Specifically, the models demonstrate that no innate force notions, motion analysis modules, common motion detectors, specific perceptual rules or abilities to "reason" about entities which have been widely postulated in the developmental literature are necessary for the explanation of the discussed phenomena. Since the prediction of future events turned out to be fruitful for theoretical explanation of various developmental phenomena and a guideline for learning in infancy, the third model addresses the development of visual expectations themselves. A self-organising, fully recurrent neural network model that forms internal representations of input sequences and maps them onto eye movements is proposed. The reinforcement learning architecture (RLA) of the model learns to perform anticipatory eye movements as observed in a range of infant studies. The model suggests that the goal of maximizing the looking time at interesting stimuli guides infants' looking behavior thereby explaining the occurrence and development of anticipatory eye movements and reaction times. In contrast to classical neural network modelling approaches in the developmental literature, the model uses local learning rules and contains several biologically plausible elements like excitatory and inhibitory spiking neurons, spike-timing dependent plasticity (STDP), intrinsic plasticity (IP) and synaptic scaling. It is also novel from the technical point of view as it uses a dynamic recurrent reservoir shaped by various plasticity mechanisms and combines it with reinforcement learning. The model accounts for twelve experimental studies and predicts among others anticipatory behavior for arbitrary sequences and facilitated reacquisition of already learned sequences. All models emphasize the development of the perception of the discussed phenomena thereby addressing the questions of how and why this developmental change takes place - questions that are difficult to be assessed experimentally. Despite the diversity of the discussed phenomena all three projects rely on the same principle: the prediction of future events. This principle suggests that cognitive development in infancy may largely be guided by building internal models and representations of the visual environment and using those models to predict its future development.
This thesis consists of four chapters. Each chapter covers a topic in international macroeconomics and monetary policy. The first chapter investigates the impact of unexpected monetary policy shocks on exchange rates in a multi-country econometric model. The second chapter examines the linkage between macroeconomic fundamentals and exchange rates through the monetary policy expectation channel. The third chapter focuses on the international transmission of bank and corporate distress. The last chapter unfolds the interest rate channel of monetary policy transmission in-an emerging economy-China, where regulations and market forces co-exist in this transmission.
The pathophysiology of schizophrenia is still poorly understood. Investigating the neurophysiological correlates of cognitive dysfunction with functional neuroimaging techniques such as electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) is widely considered to be a possible solution for this problem. Working memory impairment is one of the most prominent cognitive impairments found in schizophrenia. Working memory can be divided into a number of component processes, encoding, maintenance and retrieval. They appear to be differentially affected in schizophrenia, but little is known about the neurophysiological disturbances which contribute to deficits in these component processes. The aim of this dissertation was to elucidate the neurophysiological underpinnings of the component processes of working memory and their disturbance in schizophrenia. In the first study the the neurophysiological substrates of visual working memory capacity limitations were investigated during encoding, maintenance and retrieval in 12 healthy subjects using event-related fMRI. Subjects had to encode up to four abstract visual shapes and maintain them in working memory for 12 seconds. Afterwards a test stimulus was presented, which matched one of the previously shown shapes in fifty percent of the trials. A bilateral inverted U-shape pattern of BOLD activity with increasing memory load in areas closely linked with selective attention, i.e. the frontal eye fields and areas around the intraparietal sulcus, was observed already during encoding. The increase of the number of stored items from memory load three to memory load four in these regions was negatively correlated with the increase of BOLD activity from memory load three to memory load four. These results point to a crucial role of attentional processes for the limited capacity of working memory. In the second study, the contribution of early perceptual processing deficits during encoding and retrieval to working memory dysfunction was investigated in 17 patients with schizophrenia and 17 healthy control subjects using EEG and event-related fMRI. A slightly modified version of the working memory task used in the fist study was employed. Participants only had to encode and maintain up to three items. In patients the amplitude of the P1 event-related potential was significantly reduced already during encoding in all memory load conditions. Similarly, BOLD activity in early visual areas known to generate the P1 was significantly reduced in patients. In controls, a stronger P1 amplitude increase with increasing memory load predicted better performance. These findings indicate that in addition to later memory related processing stages early visual processing is disturbed in schizophrenia and contributes to working memory dysfunction by impairing the encoding of information. In the third study, which was based on the same data set as the second study, cortical activity and functional connectivity in 17 patients with schizophrenia and 17 to healthy control subjects during the working memory encoding, maintenance and retrieval was investigated using event-related fMRI. Patients had reduced working memory capacity. During encoding activation in the left ventrolateral prefrontal cortex and extrastriate visual cortex was reduced in patients but positively correlated with working memory capacity in controls. During early maintenance patients switched from hyper- to hypoactivation with increasing memory load in a fronto-parietal network which included left dorsolateral prefrontal cortex. During retrieval right ventrolateral prefrontal hyperactivation was correlated with encoding-related hypoactivation of left ventrolateral prefrontal cortex in patients. Cortical dysfunction in patients during encoding and retrieval was accompanied by abnormal functional connectivity between fronto-parietal and visual areas. These findings indicate a primary encoding deficit in patients caused by a dysfunction of prefrontal and visual areas. The findings of these studies suggest that isolating the component processes of working memory leads to more specific markers of cortical dysfunction in schizophrenia, which had been obscured in previous studies. This approach may help to identify more reliable biomarkers and endophenotypes of schizophrenia.
A framework for the analysis and visualization of multielectrode spike trains / von Ovidiu F. Jurjut
(2009)
The brain is a highly distributed system of constantly interacting neurons. Understanding how it gives rise to our subjective experiences and perceptions depends largely on understanding the neuronal mechanisms of information processing. These mechanisms are still poorly understood and a matter of ongoing debate remains the timescale on which the coding process evolves. Recently, multielectrode recordings of neuronal activity have begun to contribute substantially to elucidating how information coding is implemented in brain circuits. Unfortunately, analysis and interpretation of multielectrode data is often difficult because of their complexity and large volume. Here we propose a framework that enables the efficient analysis and visualization of multielectrode spiking data. First, using self-organizing maps, we identified reoccurring multi-neuronal spike patterns that evolve on various timescales. Second, we developed a color-based visualization technique for these patterns. They were mapped onto a three-dimensional color space based on their reciprocal similarities, i.e., similar patterns were assigned similar colors. This innovative representation enables a quick and comprehensive inspection of spiking data and provides a qualitative description of pattern distribution across entire datasets. Third, we quantified the observed pattern expression motifs and we investigated their contribution to the encoding of stimulus-related information. An emphasis was on the timescale on which patterns evolve, covering the temporal scales from synchrony up to mean firing rate. Using our multi-neuronal analysis framework, we investigated data recorded from the primary visual cortex of anesthetized cats. We found that cortical responses to dynamic stimuli are best described as successions of multi-neuronal activation patterns, i.e., trajectories in a multidimensional pattern space. Patterns that encode stimulus-specific information are not confined to a single timescale but can span a broad range of timescales, which are tightly related to the temporal dynamics of the stimuli. Therefore, the strict separation between synchrony and mean firing rate is somewhat artificial as these two represent only extreme cases of a continuum of timescales that are expressed in cortical dynamics. Results also indicate that timescales consistent with the time constants of neuronal membranes and fast synaptic transmission (~10-20 ms) appear to play a particularly salient role in coding, as patterns evolving on these timescales seem to be involved in the representation of stimuli with both slow and fast temporal dynamics.
The mTOR kinase inhibitor rapamycin (sirolimus) is a drug with potent immunosuppressive and antiproliferative properties. We found that rapamycin induces the TGF/Smad signaling cascade in rat mesangial cells (MC) as depicted by the nuclear translocation of phospho-Smads 2, -3 and Smad-4, respectively. Concomitantly rapamycin increases the nuclear DNA binding of receptor (R)- and co-Smad proteins to a cognate Smad-binding element (SBE) which in turn causes an increase in profibrotic gene expression as exemplified by the connective tissue growth factor (CTGF) and plasminogen activator inhibitor 1 (PAI-1). Using small interfering (si)RNA we demonstrate that Smad 2/3 activation by rapamycin depends on its endogenous receptor FK-binding protein 12 (FKBP12). Mechanistically, Smad induction by rapamycin is initiated by an increase in active TGF1 as shown by ELISA and by the inhibitory effects of a neutralizing TGF antibody. Using an activin receptor-like kinase (ALK)-5 inhibitor and by siRNA against the TGF type II receptor TGF-RII) we furthermore demonstrate a functional involvement of both types of TGF receptors. However, rapamycin did not compete with TGFfor TGF-receptor binding as found in radioligand-binding assay. Besides SB203580, a specific inhibitor of the p38 MAPK, the reactive oxygen species (ROS) scavenger N-acetyl-cysteine (NAC) and a cell-permeable superoxide dismutase (SOD) mimetic strongly abrogated the stimulatory effects of rapamycin on Smad 2 and 3 phosphorylation. Furthermore, the rapid increase in Dichlorofluorescein (DCF) formation implies that rapamycin mainly acts through ROS. In conclusion, activation of the profibrotic TGFSmad signaling cascade accompanies the immunosuppressive and antiproliferative actions of rapamycin. Keywords: FK506 binding protein; p38 MAP kinase; rapamycin; renal fibrosis; Smads; TGFβ
Ernst Bloch pointed out in a particularly emphatic way that the concept of human dignity featured centrally in historical struggles against different forms of unjustified rule, i.e. domination – to which one must add that it continues to do so to the present day. The “upright gait,” putting an end to humiliation and insult: this is the most powerful demand, in both political and rhetorical terms, that a “human rights-based” claim expresses. It marks the emergence of a radical, context-transcending reference point immanent to social conflicts which raises fundamental questions concerning the customary opposition between immanent and transcendent criticism. For within the idiom of demanding respect for human dignity, a right is invoked “here and now,” in a particular, context-specific form, which at its core is owed to every human being as a person. Thus Bloch is in one respect correct when he asserts that human rights are not a natural “birthright” but must be achieved through struggle; but in another respect this struggle can develop its social power only if it has a firm and in a certain sense “absolute” normative anchor. Properly understood, it becomes apparent that these social conflicts always affect “two worlds”: the social reality, on the one hand, which is criticized in part or radically in the light of an ideal normative dimension, on the other. For those who engage in this criticism there is no doubt that the normative dimension is no less real than the reality to which they refuse to resign themselves. Those who critically transcend reality always also live elsewhere.
The overvaluation hypothesis (Miller 1977) predicts that a) stocks are overvalued in the presence of short selling restrictions and that b) the overvaluation increases in the degree of divergence of opinion. We design an experiment that allows us to test these predictions in the laboratory. The results indicate that prices are higher with short selling constraints, but the overvaluation does not increase in the degree of divergence of opinion. We further find that trading volume is lower and bid-ask spreads are higher when short sale restrictions are imposed. JEL Classification: C92, G14 Keywords: Overvaluation Hypothesis , Short Selling Constraints , Divergence of Opinion