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Proceedings of KogWis 2010 : 10th Biannual Meeting of the German Society for Cognitive Science
(2010)
As the latest biannual meeting of the German Society for Cognitive Science (Gesellschaft für Kognitionswissenschaft, GK), KogWis 2010 at Potsdam University reflects the current trends in a fascinating domain of research concerned with human and artificial cognition and the interaction of mind and brain. The Plenary talks provide a venue for questions of the numerical capacities and human arithmetic (Brian Butterworth), of the theoretical development of cognitive architectures and intelligent virtual agents (Pat Langley), of categorizations induced by linguistic constructions (Claudia Maienborn), and of a cross-level account of the “Self as a complex system“ (Paul Thagard). KogWis 2010 integrates a wealth of experimental research, cognitive modelling, and conceptual analysis in 5 invited symposia, over 150 individual talks, 6 symposia, and more than 40 poster contributions. Some of the invited symposia reflect local and regional strenghts of research in the Berlin-Brandenburg area: the two largests research fields of the university Cognitive Sciences Area of Excellence in Potsdam are represented by an invited symposium on “Information Structure” by the Special Research Area 632 (“Sonderforschungsbereich”, SFB) of the same name, of Potsdam University and Humboldt-University Berlin, and by a satellite conference of the research group “Mind and Brain Dynamics”. The Berlin School of Mind and Brain at Humboldt-University Berlin takes part with an invited symposium on “Decision Making” from a perspective of cognitive neuroscience and philosophy and the DFG Cluster of Excellence “Languages of Emotion” of Free University presents interdisciplinary research results in an invited symposium on “Symbolising Emotions”.
We establish elements of a new approach to ellipticity and parametrices within operator algebras on manifolds with higher singularities, only based on some general axiomatic requirements on parameter-dependent operators in suitable scales of spaes. The idea is to model an iterative process with new generations of parameter-dependent operator theories, together with new scales of spaces that satisfy analogous requirements as the original ones, now on a corresponding higher level. The "full" calculus involves two separate theories, one near the tip of the corner and another one at the conical exit to infinity. However, concerning the conical exit to infinity, we establish here a new concrete calculus of edge-degenerate operators which can be iterated to higher singularities.
In the present work, we study wave phenomena in strongly nonlinear lattices. Such lattices are characterized by the absence of classical linear waves. We demonstrate that compactons – strongly localized solitary waves with tails decaying faster than exponential – exist and that they play a major role in the dynamics of the system under consideration. We investigate compactons in different physical setups. One part deals with lattices of dispersively coupled limit cycle oscillators which find various applications in natural sciences such as Josephson junction arrays or coupled Ginzburg-Landau equations. Another part deals with Hamiltonian lattices. Here, a prominent example in which compactons can be found is the granular chain. In the third part, we study systems which are related to the discrete nonlinear Schrödinger equation describing, for example, coupled optical wave-guides or the dynamics of Bose-Einstein condensates in optical lattices. Our investigations are based on a numerical method to solve the traveling wave equation. This results in a quasi-exact solution (up to numerical errors) which is the compacton. Another ansatz which is employed throughout this work is the quasi-continuous approximation where the lattice is described by a continuous medium. Here, compactons are found analytically, but they are defined on a truly compact support. Remarkably, both ways give similar qualitative and quantitative results. Additionally, we study the dynamical properties of compactons by means of numerical simulation of the lattice equations. Especially, we concentrate on their emergence from physically realizable initial conditions as well as on their stability due to collisions. We show that the collisions are not exactly elastic but that a small part of the energy remains at the location of the collision. In finite lattices, this remaining part will then trigger a multiple scattering process resulting in a chaotic state.
In this paper we develop a spatial Cournot trade model with two unequally sized countries, using the geographical interpretation of the Hotelling line. We analyze the trade and welfare effects of international trade between these two countries. The welfare analysis indicates that in this framework the large country benefits from free trade and the small country may be hurt by opening to trade. This finding is contrary to the results of Shachmurove and Spiegel (1995) as well as Tharakan and Thisse (2002), who use related models to analyze size effects in international trade, where the small country usually gains from trade and the large country may lose.
In a very simplified view, the plant leaf growth can be reduced to two processes, cell division and cell expansion, accompanied by expansion of their surrounding cell walls. The vacuole, as being the largest compartment of the plant cell, plays a major role in controlling the water balance of the plant. This is achieved by regulating the osmotic pressure, through import and export of solutes over the vacuolar membrane (the tonoplast) and by controlling the water channels, the aquaporins. Together with the control of cell wall relaxation, vacuolar osmotic pressure regulation is thought to play an important role in cell expansion, directly by providing cell volume and indirectly by providing ion and pH homestasis for the cytosoplasm. In this thesis the role of tonoplast protein coding genes in cell expansion in the model plant Arabidopsis thaliana is studied and genes which play a putative role in growth are identified. Since there is, to date, no clearly identified protein localization signal for the tonoplast, there is no possibility to perform genome-wide prediction of proteins localized to this compartment. Thus, a series of recent proteomic studies of the tonoplast were used to compile a list of cross-membrane tonoplast protein coding genes (117 genes), and other growth-related genes from notably the growth regulating factor (GRF) and expansin families were included (26 genes). For these genes a platform for high-throughput reverse transcription quantitative real time polymerase chain reaction (RT-qPCR) was developed by selecting specific primer pairs. To this end, a software tool (called QuantPrime, see http://www.quantprime.de) was developed that automatically designs such primers and tests their specificity in silico against whole transcriptomes and genomes, to avoid cross-hybridizations causing unspecific amplification. The RT-qPCR platform was used in an expression study in order to identify candidate growth related genes. Here, a growth-associative spatio-temporal leaf sampling strategy was used, targeting growing regions at high expansion developmental stages and comparing them to samples taken from non-expanding regions or stages of low expansion. Candidate growth related genes were identified after applying a template-based scoring analysis on the expression data, ranking the genes according to their association with leaf expansion. To analyze the functional involvement of these genes in leaf growth on a macroscopic scale, knockout mutants of the candidate growth related genes were screened for growth phenotypes. To this end, a system for non-invasive automated leaf growth phenotyping was established, based on a commercially available image capture and analysis system. A software package was developed for detailed developmental stage annotation of the images captured with the system, and an analysis pipeline was constructed for automated data pre-processing and statistical testing, including modeling and graph generation, for various growth-related phenotypes. Using this system, 24 knockout mutant lines were analyzed, and significant growth phenotypes were found for five different genes.
Companies develop process models to explicitly describe their business operations. In the same time, business operations, business processes, must adhere to various types of compliance requirements. Regulations, e.g., Sarbanes Oxley Act of 2002, internal policies, best practices are just a few sources of compliance requirements. In some cases, non-adherence to compliance requirements makes the organization subject to legal punishment. In other cases, non-adherence to compliance leads to loss of competitive advantage and thus loss of market share. Unlike the classical domain-independent behavioral correctness of business processes, compliance requirements are domain-specific. Moreover, compliance requirements change over time. New requirements might appear due to change in laws and adoption of new policies. Compliance requirements are offered or enforced by different entities that have different objectives behind these requirements. Finally, compliance requirements might affect different aspects of business processes, e.g., control flow and data flow. As a result, it is infeasible to hard-code compliance checks in tools. Rather, a repeatable process of modeling compliance rules and checking them against business processes automatically is needed. This thesis provides a formal approach to support process design-time compliance checking. Using visual patterns, it is possible to model compliance requirements concerning control flow, data flow and conditional flow rules. Each pattern is mapped into a temporal logic formula. The thesis addresses the problem of consistency checking among various compliance requirements, as they might stem from divergent sources. Also, the thesis contributes to automatically check compliance requirements against process models using model checking. We show that extra domain knowledge, other than expressed in compliance rules, is needed to reach correct decisions. In case of violations, we are able to provide a useful feedback to the user. The feedback is in the form of parts of the process model whose execution causes the violation. In some cases, our approach is capable of providing automated remedy of the violation.
This professorial dissertation thesis collects several empirical studies on tax distribution and tax reform in Germany. Chapter 2 deals with two studies on effective income taxation, based on representative micro data sets from tax statistics. The first study analyses the effective income taxation at the individual level, in particular with respect to the top incomes. It is based on an integrated micro data file of household survey data and income tax statistics, which captures the entire income distribution up to the very top. Despite substantial tax base erosion and reductions of top tax rates, the German personal income tax has remained effectively progressive. The distribution of the tax burden is highly concentrated and the German economic elite is still taxed relatively heavily, even though the effective tax rate for this group has significantly declined. The second study of Chapter 2 highlights the effective income taxation of functional income sources, such as labor income, business and capital income, etc. Using income tax micro data and microsimulation models, we allocate the individual income tax liability to the respective income sources, according to different apportionment schemes accounting for losses. We find that the choice of the apportionment scheme markedly affects the tax shares of income sources and implicit tax rates, in particular those of capital income. Income types without significant losses such as labor income or transfer incomes show higher tax shares and implicit tax rates if we account for losses. The opposite is true for capital income, in particular for income from renting and leasing. Chapter 3 presents two studies on business taxation, based on representative micro data sets from tax statistics and the microsimulation model BizTax. The first part provides a study on fundamental reform options for the German local business tax. We find that today’s high concentration of local business tax revenues on corporations with high profits decreases if the tax base is broadened by integrating more taxpayers and by including more elements of business value added. The reform scenarios with a broader tax base distribute the local business tax revenue per capita more equally across regional categories. The second study of Chapter 3 discusses the macroeconomic performance of business taxation against the background of corporate income. A comparison of the tax base reported in tax statistics with the macroeconomic corporate income from national accounts gives hints to considerable tax base erosion. The average implicit tax rate on corporate income was around 20 percent since 2001, and thus falling considerably short of statutory tax rates and effective tax rates discussed in the literature. For lack of detailed accounting data it is hard to give precise reasons for the presumptive tax base erosion. Chapter 4 deals with several assessment studies on the ecological tax reform implemented in Germany as of 1999. First, we describe the scientific, ideological, and political background of the ecological tax reform. Further, we present the main findings of a first systematic impact analysis. We employ two macroeconomic models, an econometric input-output model and a recursive-dynamic computable general equilibrium (CGE) model. Both models show that Germany’s ecological tax reform helps to reduce energy consumption and CO2 emissions without having a substantial adverse effect on overall economic growth. It could have a slightly positive effect on employment. The reform’s impact on the business sector and the effects of special provisions granted to agriculture and the goods and materials sectors are outlined in a further study. The special provisions avoid higher tax burdens on the energy-intensive production. However, they widely reduce the marginal tax rates and thus the incentives to energy saving. Though the reform of special provisions 2003 increased the overall tax burden of the energy-intensive industry, the enlarged eligibility for tax rebates neutralizes the ecologic incentives. Based on the Income and Consumption Survey of 2003, we have analyzed the distributional impact of the ecological tax reform. The increased energy taxes show a clear regressive impact relative to disposable income. Families with children face a higher tax burden relative to household income. The reduction of pension contributions and the automatic adjustment of social security transfers widely mitigate this regressive impact. Households with low income or with many children nevertheless bear a slight increase in tax burden. Refunding the eco tax revenue by an eco bonus would make the reform clearly progressive.
Data obtained from foreign data sources often come with only superficial structural information, such as relation names and attribute names. Other types of metadata that are important for effective integration and meaningful querying of such data sets are missing. In particular, relationships among attributes, such as foreign keys, are crucial metadata for understanding the structure of an unknown database. The discovery of such relationships is difficult, because in principle for each pair of attributes in the database each pair of data values must be compared. A precondition for a foreign key is an inclusion dependency (IND) between the key and the foreign key attributes. We present with Spider an algorithm that efficiently finds all INDs in a given relational database. It leverages the sorting facilities of DBMS but performs the actual comparisons outside of the database to save computation. Spider analyzes very large databases up to an order of magnitude faster than previous approaches. We also evaluate in detail the effectiveness of several heuristics to reduce the number of necessary comparisons. Furthermore, we generalize Spider to find composite INDs covering multiple attributes, and partial INDs, which are true INDs for all but a certain number of values. This last type is particularly relevant when integrating dirty data as is often the case in the life sciences domain - our driving motivation.
Multi-color fluorescence imaging experiments of wave forming Dictyostelium cells have revealed that actin waves separate two domains of the cell cortex that differ in their actin structure and phosphoinositide composition. We propose a bistable model of actin dynamics to account for these experimental observation. The model is based on the simplifying assumption that the actin cytoskeleton is composed of two distinct network types, a dendritic and a bundled network. The two structurally different states that were observed in experiments correspond to the stable fixed points in the bistable regime of this model. Each fixed point is dominated by one of the two network types. The experimentally observed actin waves can be considered as trigger waves that propagate transitions between the two stable fixed points.