Residualton & neuronale Autokorrelation in Modellen der Tonhöhenwahrnehmung

Diese Arbeit beinhaltet einen Vergleich historischer und aktueller Erkenntnisse im psychoakustischen Forschungsgebiet der Tonhöhenwahrnehmung. Es wird ein Überblick über die historischen Ergebnisse von Wissenschaftern (u.a. Seebeck, Ohm, Helmholtz) gegeben und deren Einfluss auf die zukünftige Forschung beleuchtet. Der Aufbau des menschlichen Ohres wird geschildert, sowie die neurologischen Grundlagen des Gehörsinns. Anschließend werden die Entdeckung und charakteristische Eigenschaften des Residualtonhörens erläutert. Dieses Phänomen wurde erstmals von Schouten detailliert beschrieben und bezeichnet die Wahrnehmung eines physikalisch nicht vorhandenen Grundtons. Das bedeutet, dass im Frequenzspektrum des Klanges nur Obertöne auftreten. An die Stelle des Grundtones tritt beim Zuhören ein Residualton, deshalb ändert sich die Tonhöhenwahrnehmung durch den fehlenden Grundton nicht. Das Residualtonphänomen kann in Verbindung mit Lautsprechern, Telefonen oder tiefen Instrumenten (z.B. Fagott) beobachtet werden. Weiters werden die beiden grundlegenden Modelle der Tonhöhenwahrnehmung (Frequenz- vs. Zeitbereichanalyse) vorgestellt und ihre Fähigkeit, Phänomene des menschlichen Gehörs zu erklären, bewertet. Das Konzept der neuronalen Autokorrelation wird präsentiert und mathematische Eigenschaften gezeigt. Dieser Ansatz ist die Grundlage vieler Tonhöhenwahrnehmungsmodelle. Einige werden vorgestellt und die biologischen und theoretischen Hintergründe erklärt. Forscher (u.a. Langner) konnten nachweisen, dass im auditorischen Cortex des Menschen ein Autokorrelationsprozess stattfindet. Dies spricht für ein von Licklider formuliertes und später von anderen Wissenschaftern (u.a. Ebeling, Fricke) modifiziertes Modell der Tonhöhenwahrnehmung, das sowohl auf spektrale, als auch auf zeitliche Analyse basiert und Autokorrelation inkludiert. Die beiden vormals gegensätzlichen Theorien (Frequenz- vs. Zeitbereichanalyse) schaffen somit durch ihr Zusammenwirken ein neues Modell zur Beschreibung der Tonhöhenwahrnehmung, das erstmals eine biologisch fundierte Erklärung des Residualtonphänomens mittels neuronaler Autokorrelation darstellt.This paper describes recent and historical findings in the psychoacoustic field of pitch perception. An overview of historical research is given, where results of physicists (e.g. Seebeck, Ohm, Helmholtz) are summarized and their importance for future research work explained. The pitch perception phenomenon “missing fundamental” is introduced This phenomenon, first systematically described by Schouten, occurs when a listener hears a sound, which only consists of the overtone spectrum. The fundamental frequency is physically not present. However, the listener perceives the sound, as if the fundamental frequency were present. The missing fundamental concerns telephone communication, loudspeakers and instruments (e.g. bassoon). The two basic models of pitch perception (frequency vs. periodicity analysis) are explained, compared and their ability to account for particular pitch perception experiences is investigated. The idea of neural autocorrelation is explained and furthermore mathematical theorems for this concept. This approach is the underlying idea of many current pitch perception models. Some of them, including their theoretical and biological principles, are described. Langner et al. discovered biological evidence for an autocorrelation process in the auditory cortex of mammal and even human brains. This highly supports an autocorrelation model, first theoretically described by Licklider and later refined by other scientists (e.g. Fricke, Ebeling), as an explanation for pitch perception. The combination of the two former opposing theories (frequency vs. periodicity analysis) establishes a new, promising model for pitch perception, whose major advantage is the fact that this model by means of neural autocorrelation even accounts for the missing fundamental

MeGARA: Menu-based Game Abstraction and Abstraction Refinement of Markov Automata

Markov automata combine continuous time, probabilistic transitions, and nondeterminism in a single model. They represent an important and powerful way to model a wide range of complex real-life systems. However, such models tend to be large and difficult to handle, making abstraction and abstraction refinement necessary. In this paper we present an abstraction and abstraction refinement technique for Markov automata, based on the game-based and menu-based abstraction of probabilistic automata. First experiments show that a significant reduction in size is possible using abstraction.Comment: In Proceedings QAPL 2014, arXiv:1406.156

Modeling of leishmaniasis infection dynamics: novel application to the design of effective therapies

<p>Abstract</p> <p>Background</p> <p>The WHO considers leishmaniasis as one of the six most important tropical diseases worldwide. It is caused by parasites of the genus <it>Leishmania </it>that are passed on to humans and animals by the phlebotomine sandfly. Despite all of the research, there is still a lack of understanding on the metabolism of the parasite and the progression of the disease. In this study, a mathematical model of disease progression was developed based on experimental data of clinical symptoms, immunological responses, and parasite load for <it>Leishmania amazonensis </it>in <it>BALB/c </it>mice.</p> <p>Results</p> <p>Four biologically significant variables were chosen to develop a differential equation model based on the GMA power-law formalism. Parameters were determined to minimize error in the model dynamics and time series experimental data. Subsequently, the model robustness was tested and the model predictions were verified by comparing them with experimental observations made in different experimental conditions. The model obtained helps to quantify relationships between the selected variables, leads to a better understanding of disease progression, and aids in the identification of crucial points for introducing therapeutic methods.</p> <p>Conclusions</p> <p>Our model can be used to identify the biological factors that must be changed to minimize parasite load in the host body, and contributes to the design of effective therapies.</p

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics

Human Practice. Digital Ecologies. Our Future. : 14. Internationale Tagung Wirtschaftsinformatik (WI 2019) : Tagungsband

Erschienen bei: universi - Universitätsverlag Siegen. - ISBN: 978-3-96182-063-4Aus dem Inhalt: Track 1: Produktion & Cyber-Physische Systeme Requirements and a Meta Model for Exchanging Additive Manufacturing Capacities Service Systems, Smart Service Systems and Cyber- Physical Systems—What’s the difference? Towards a Unified Terminology Developing an Industrial IoT Platform – Trade-off between Horizontal and Vertical Approaches Machine Learning und Complex Event Processing: Effiziente Echtzeitauswertung am Beispiel Smart Factory Sensor retrofit for a coffee machine as condition monitoring and predictive maintenance use case Stakeholder-Analyse zum Einsatz IIoT-basierter Frischeinformationen in der Lebensmittelindustrie Towards a Framework for Predictive Maintenance Strategies in Mechanical Engineering - A Method-Oriented Literature Analysis Development of a matching platform for the requirement-oriented selection of cyber physical systems for SMEs Track 2: Logistic Analytics An Empirical Study of Customers’ Behavioral Intention to Use Ridepooling Services – An Extension of the Technology Acceptance Model Modeling Delay Propagation and Transmission in Railway Networks What is the impact of company specific adjustments on the acceptance and diffusion of logistic standards? Robust Route Planning in Intermodal Urban Traffic Track 3: Unternehmensmodellierung & Informationssystemgestaltung (Enterprise Modelling & Information Systems Design) Work System Modeling Method with Different Levels of Specificity and Rigor for Different Stakeholder Purposes Resolving Inconsistencies in Declarative Process Models based on Culpability Measurement Strategic Analysis in the Realm of Enterprise Modeling – On the Example of Blockchain-Based Initiatives for the Electricity Sector Zwischenbetriebliche Integration in der Möbelbranche: Konfigurationen und Einflussfaktoren Novices’ Quality Perceptions and the Acceptance of Process Modeling Grammars Entwicklung einer Definition für Social Business Objects (SBO) zur Modellierung von Unternehmensinformationen Designing a Reference Model for Digital Product Configurators Terminology for Evolving Design Artifacts Business Role-Object Specification: A Language for Behavior-aware Structural Modeling of Business Objects Generating Smart Glasses-based Information Systems with BPMN4SGA: A BPMN Extension for Smart Glasses Applications Using Blockchain in Peer-to-Peer Carsharing to Build Trust in the Sharing Economy Testing in Big Data: An Architecture Pattern for a Development Environment for Innovative, Integrated and Robust Applications Track 4: Lern- und Wissensmanagement (e-Learning and Knowledge Management) eGovernment Competences revisited – A Literature Review on necessary Competences in a Digitalized Public Sector Say Hello to Your New Automated Tutor – A Structured Literature Review on Pedagogical Conversational Agents Teaching the Digital Transformation of Business Processes: Design of a Simulation Game for Information Systems Education Conceptualizing Immersion for Individual Learning in Virtual Reality Designing a Flipped Classroom Course – a Process Model The Influence of Risk-Taking on Knowledge Exchange and Combination Gamified Feedback durch Avatare im Mobile Learning Alexa, Can You Help Me Solve That Problem? - Understanding the Value of Smart Personal Assistants as Tutors for Complex Problem Tasks Track 5: Data Science & Business Analytics Matching with Bundle Preferences: Tradeoff between Fairness and Truthfulness Applied image recognition: guidelines for using deep learning models in practice Yield Prognosis for the Agrarian Management of Vineyards using Deep Learning for Object Counting Reading Between the Lines of Qualitative Data – How to Detect Hidden Structure Based on Codes Online Auctions with Dual-Threshold Algorithms: An Experimental Study and Practical Evaluation Design Features of Non-Financial Reward Programs for Online Reviews: Evaluation based on Google Maps Data Topic Embeddings – A New Approach to Classify Very Short Documents Based on Predefined Topics Leveraging Unstructured Image Data for Product Quality Improvement Decision Support for Real Estate Investors: Improving Real Estate Valuation with 3D City Models and Points of Interest Knowledge Discovery from CVs: A Topic Modeling Procedure Online Product Descriptions – Boost for your Sales? Entscheidungsunterstützung durch historienbasierte Dienstreihenfolgeplanung mit Pattern A Semi-Automated Approach for Generating Online Review Templates Machine Learning goes Measure Management: Leveraging Anomaly Detection and Parts Search to Improve Product-Cost Optimization Bedeutung von Predictive Analytics für den theoretischen Erkenntnisgewinn in der IS-Forschung Track 6: Digitale Transformation und Dienstleistungen Heuristic Theorizing in Software Development: Deriving Design Principles for Smart Glasses-based Systems Mirroring E-service for Brick and Mortar Retail: An Assessment and Survey Taxonomy of Digital Platforms: A Platform Architecture Perspective Value of Star Players in the Digital Age Local Shopping Platforms – Harnessing Locational Advantages for the Digital Transformation of Local Retail Outlets: A Content Analysis A Socio-Technical Approach to Manage Analytics-as-a-Service – Results of an Action Design Research Project Characterizing Approaches to Digital Transformation: Development of a Taxonomy of Digital Units Expectations vs. Reality – Benefits of Smart Services in the Field of Tension between Industry and Science Innovation Networks and Digital Innovation: How Organizations Use Innovation Networks in a Digitized Environment Characterising Social Reading Platforms— A Taxonomy-Based Approach to Structure the Field Less Complex than Expected – What Really Drives IT Consulting Value Modularity Canvas – A Framework for Visualizing Potentials of Service Modularity Towards a Conceptualization of Capabilities for Innovating Business Models in the Industrial Internet of Things A Taxonomy of Barriers to Digital Transformation Ambidexterity in Service Innovation Research: A Systematic Literature Review Design and success factors of an online solution for cross-pillar pension information Track 7: IT-Management und -Strategie A Frugal Support Structure for New Software Implementations in SMEs How to Structure a Company-wide Adoption of Big Data Analytics The Changing Roles of Innovation Actors and Organizational Antecedents in the Digital Age Bewertung des Kundennutzens von Chatbots für den Einsatz im Servicedesk Understanding the Benefits of Agile Software Development in Regulated Environments Are Employees Following the Rules? On the Effectiveness of IT Consumerization Policies Agile and Attached: The Impact of Agile Practices on Agile Team Members’ Affective Organisational Commitment The Complexity Trap – Limits of IT Flexibility for Supporting Organizational Agility in Decentralized Organizations Platform Openness: A Systematic Literature Review and Avenues for Future Research Competence, Fashion and the Case of Blockchain The Digital Platform Otto.de: A Case Study of Growth, Complexity, and Generativity Track 8: eHealth & alternde Gesellschaft Security and Privacy of Personal Health Records in Cloud Computing Environments – An Experimental Exploration of the Impact of Storage Solutions and Data Breaches Patientenintegration durch Pfadsysteme Digitalisierung in der Stressprävention – eine qualitative Interviewstudie zu Nutzenpotenzialen User Dynamics in Mental Health Forums – A Sentiment Analysis Perspective Intent and the Use of Wearables in the Workplace – A Model Development Understanding Patient Pathways in the Context of Integrated Health Care Services - Implications from a Scoping Review Understanding the Habitual Use of Wearable Activity Trackers On the Fit in Fitness Apps: Studying the Interaction of Motivational Affordances and Users’ Goal Orientations in Affecting the Benefits Gained Gamification in Health Behavior Change Support Systems - A Synthesis of Unintended Side Effects Investigating the Influence of Information Incongruity on Trust-Relations within Trilateral Healthcare Settings Track 9: Krisen- und Kontinuitätsmanagement Potentiale von IKT beim Ausfall kritischer Infrastrukturen: Erwartungen, Informationsgewinnung und Mediennutzung der Zivilbevölkerung in Deutschland Fake News Perception in Germany: A Representative Study of People’s Attitudes and Approaches to Counteract Disinformation Analyzing the Potential of Graphical Building Information for Fire Emergency Responses: Findings from a Controlled Experiment Track 10: Human-Computer Interaction Towards a Taxonomy of Platforms for Conversational Agent Design Measuring Service Encounter Satisfaction with Customer Service Chatbots using Sentiment Analysis Self-Tracking and Gamification: Analyzing the Interplay of Motivations, Usage and Motivation Fulfillment Erfolgsfaktoren von Augmented-Reality-Applikationen: Analyse von Nutzerrezensionen mit dem Review-Mining-Verfahren Designing Dynamic Decision Support for Electronic Requirements Negotiations Who is Stressed by Using ICTs? A Qualitative Comparison Analysis with the Big Five Personality Traits to Understand Technostress Walking the Middle Path: How Medium Trade-Off Exposure Leads to Higher Consumer Satisfaction in Recommender Agents Theory-Based Affordances of Utilitarian, Hedonic and Dual-Purposed Technologies: A Literature Review Eliciting Customer Preferences for Shopping Companion Apps: A Service Quality Approach The Role of Early User Participation in Discovering Software – A Case Study from the Context of Smart Glasses The Fluidity of the Self-Concept as a Framework to Explain the Motivation to Play Video Games Heart over Heels? An Empirical Analysis of the Relationship between Emotions and Review Helpfulness for Experience and Credence Goods Track 11: Information Security and Information Privacy Unfolding Concerns about Augmented Reality Technologies: A Qualitative Analysis of User Perceptions To (Psychologically) Own Data is to Protect Data: How Psychological Ownership Determines Protective Behavior in a Work and Private Context Understanding Data Protection Regulations from a Data Management Perspective: A Capability-Based Approach to EU-GDPR On the Difficulties of Incentivizing Online Privacy through Transparency: A Qualitative Survey of the German Health Insurance Market What is Your Selfie Worth? A Field Study on Individuals’ Valuation of Personal Data Justification of Mass Surveillance: A Quantitative Study An Exploratory Study of Risk Perception for Data Disclosure to a Network of Firms Track 12: Umweltinformatik und nachhaltiges Wirtschaften Kommunikationsfäden im Nadelöhr – Fachliche Prozessmodellierung der Nachhaltigkeitskommunikation am Kapitalmarkt Potentiale und Herausforderungen der Materialflusskostenrechnung Computing Incentives for User-Based Relocation in Carsharing Sustainability’s Coming Home: Preliminary Design Principles for the Sustainable Smart District Substitution of hazardous chemical substances using Deep Learning and t-SNE A Hierarchy of DSMLs in Support of Product Life-Cycle Assessment A Survey of Smart Energy Services for Private Households Door-to-Door Mobility Integrators as Keystone Organizations of Smart Ecosystems: Resources and Value Co-Creation – A Literature Review Ein Entscheidungsunterstützungssystem zur ökonomischen Bewertung von Mieterstrom auf Basis der Clusteranalyse Discovering Blockchain for Sustainable Product-Service Systems to enhance the Circular Economy Digitale Rückverfolgbarkeit von Lebensmitteln: Eine verbraucherinformatische Studie Umweltbewusstsein durch audiovisuelles Content Marketing? Eine experimentelle Untersuchung zur Konsumentenbewertung nachhaltiger Smartphones Towards Predictive Energy Management in Information Systems: A Research Proposal A Web Browser-Based Application for Processing and Analyzing Material Flow Models using the MFCA Methodology Track 13: Digital Work - Social, mobile, smart On Conversational Agents in Information Systems Research: Analyzing the Past to Guide Future Work The Potential of Augmented Reality for Improving Occupational First Aid Prevent a Vicious Circle! The Role of Organizational IT-Capability in Attracting IT-affine Applicants Good, Bad, or Both? Conceptualization and Measurement of Ambivalent User Attitudes Towards AI A Case Study on Cross-Hierarchical Communication in Digital Work Environments ‘Show Me Your People Skills’ - Employing CEO Branding for Corporate Reputation Management in Social Media A Multiorganisational Study of the Drivers and Barriers of Enterprise Collaboration Systems-Enabled Change The More the Merrier? The Effect of Size of Core Team Subgroups on Success of Open Source Projects The Impact of Anthropomorphic and Functional Chatbot Design Features in Enterprise Collaboration Systems on User Acceptance Digital Feedback for Digital Work? Affordances and Constraints of a Feedback App at InsurCorp The Effect of Marker-less Augmented Reality on Task and Learning Performance Antecedents for Cyberloafing – A Literature Review Internal Crowd Work as a Source of Empowerment - An Empirical Analysis of the Perception of Employees in a Crowdtesting Project Track 14: Geschäftsmodelle und digitales Unternehmertum Dividing the ICO Jungle: Extracting and Evaluating Design Archetypes Capturing Value from Data: Exploring Factors Influencing Revenue Model Design for Data-Driven Services Understanding the Role of Data for Innovating Business Models: A System Dynamics Perspective Business Model Innovation and Stakeholder: Exploring Mechanisms and Outcomes of Value Creation and Destruction Business Models for Internet of Things Platforms: Empirical Development of a Taxonomy and Archetypes Revitalizing established Industrial Companies: State of the Art and Success Principles of Digital Corporate Incubators When 1+1 is Greater than 2: Concurrence of Additional Digital and Established Business Models within Companies Special Track 1: Student Track Investigating Personalized Price Discrimination of Textile-, Electronics- and General Stores in German Online Retail From Facets to a Universal Definition – An Analysis of IoT Usage in Retail Is the Technostress Creators Inventory Still an Up-To-Date Measurement Instrument? Results of a Large-Scale Interview Study Application of Media Synchronicity Theory to Creative Tasks in Virtual Teams Using the Example of Design Thinking TrustyTweet: An Indicator-based Browser-Plugin to Assist Users in Dealing with Fake News on Twitter Application of Process Mining Techniques to Support Maintenance-Related Objectives How Voice Can Change Customer Satisfaction: A Comparative Analysis between E-Commerce and Voice Commerce Business Process Compliance and Blockchain: How Does the Ethereum Blockchain Address Challenges of Business Process Compliance? Improving Business Model Configuration through a Question-based Approach The Influence of Situational Factors and Gamification on Intrinsic Motivation and Learning Evaluation von ITSM-Tools für Integration und Management von Cloud-Diensten am Beispiel von ServiceNow How Software Promotes the Integration of Sustainability in Business Process Management Criteria Catalog for Industrial IoT Platforms from the Perspective of the Machine Tool Industry Special Track 3: Demos & Prototyping Privacy-friendly User Location Tracking with Smart Devices: The BeaT Prototype Application-oriented robotics in nursing homes Augmented Reality for Set-up Processe Mixed Reality for supporting Remote-Meetings Gamification zur Motivationssteigerung von Werkern bei der Betriebsdatenerfassung Automatically Extracting and Analyzing Customer Needs from Twitter: A “Needmining” Prototype GaNEsHA: Opportunities for Sustainable Transportation in Smart Cities TUCANA: A platform for using local processing power of edge devices for building data-driven services Demonstrator zur Beschreibung und Visualisierung einer kritischen Infrastruktur Entwicklung einer alltagsnahen persuasiven App zur Bewegungsmotivation für ältere Nutzerinnen und Nutzer A browser-based modeling tool for studying the learning of conceptual modeling based on a multi-modal data collection approach Exergames & Dementia: An interactive System for People with Dementia and their Care-Network Workshops Workshop Ethics and Morality in Business Informatics (Workshop Ethik und Moral in der Wirtschaftsinformatik – EMoWI’19) Model-Based Compliance in Information Systems - Foundations, Case Description and Data Set of the MobIS-Challenge for Students and Doctoral Candidates Report of the Workshop on Concepts and Methods of Identifying Digital Potentials in Information Management Control of Systemic Risks in Global Networks - A Grand Challenge to Information Systems Research Die Mitarbeiter von morgen - Kompetenzen künftiger Mitarbeiter im Bereich Business Analytics Digitaler Konsum: Herausforderungen und Chancen der Verbraucherinformati

Effectiveness and safety of opicapone in Parkinson’s disease patients with motor fluctuations: the OPTIPARK open-label study

Background The efficacy and safety of opicapone, a once-daily catechol-O-methyltransferase inhibitor, have been established in two large randomized, placebo-controlled, multinational pivotal trials. Still, clinical evidence from routine practice is needed to complement the data from the pivotal trials. Methods OPTIPARK (NCT02847442) was a prospective, open-label, single-arm trial conducted in Germany and the UK under clinical practice conditions. Patients with Parkinson’s disease and motor fluctuations were treated with opicapone 50 mg for 3 (Germany) or 6 (UK) months in addition to their current levodopa and other antiparkinsonian treatments. The primary endpoint was the Clinician’s Global Impression of Change (CGI-C) after 3 months. Secondary assessments included Patient Global Impressions of Change (PGI-C), the Unified Parkinson’s Disease Rating Scale (UPDRS), Parkinson’s Disease Questionnaire (PDQ-8), and the Non-Motor Symptoms Scale (NMSS). Safety assessments included evaluation of treatment-emergent adverse events (TEAEs) and serious adverse events (SAEs). Results Of the 506 patients enrolled, 495 (97.8%) took at least one dose of opicapone. Of these, 393 (79.4%) patients completed 3 months of treatment. Overall, 71.3 and 76.9% of patients experienced any improvement on CGI-C and PGI-C after 3 months, respectively (full analysis set). At 6 months, for UK subgroup only (n = 95), 85.3% of patients were judged by investigators as improved since commencing treatment. UPDRS scores at 3 months showed statistically significant improvements in activities of daily living during OFF (mean ± SD change from baseline: − 3.0 ± 4.6, p < 0.0001) and motor scores during ON (− 4.6 ± 8.1, p < 0.0001). The mean ± SD improvements of − 3.4 ± 12.8 points for PDQ-8 and -6.8 ± 19.7 points for NMSS were statistically significant versus baseline (both p < 0.0001). Most of TEAEs (94.8% of events) were of mild or moderate intensity. TEAEs considered to be at least possibly related to opicapone were reported for 45.1% of patients, with dyskinesia (11.5%) and dry mouth (6.5%) being the most frequently reported. Serious TEAEs considered at least possibly related to opicapone were reported for 1.4% of patients. Conclusions Opicapone 50 mg was effective and generally well-tolerated in PD patients with motor fluctuations treated in clinical practice. Trial registration Registered in July 2016 at clinicaltrials.gov (NCT02847442)

Plasma lipid profiles discriminate bacterial from viral infection in febrile children

Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection ar

Ein Advektions-Diffusions-PDE Modell zu Seesterninvasionen in Muschelbänken im Limfjord - numerische Simulationen & analytische Ergebnisse

Abweichender Titel laut Übersetzung der Verfasserin/des VerfassersZsfassung in dt. SpracheDer Limfjord in Dänemark ist berühmt für seine Miesmuschelbänke, die von Fischern geerntet werden und eine beliebte Delikatesse darstellen. Immer wieder treten jedoch wellenartige Seesterninvasionen auf, die in die Muschelbänke einfallen und diese im Zuge ihrer Wanderung völlig abernten. Ziel dieser Diplomarbeit war die Entwicklung eines PDE-Modells zur Beschreibung und Analyse dieses Phänomens. In den numerischen Simulationen (Linienmethode) zeigte sich, dass ein Advektions-Diffusions-Ansatz mit geeigneter Diffusivitätsfunktion für die Fortbewegung der Seesterne und Erntefunktion für die Muschelbänke tatsächlich wellenartige Lösungen hervorbringt. Im Gegensatz zu den traveling waves aus der klassischen PDE-Theorie ändern diese Wellen jedoch im Laufe der Zeit Amplitude und Form. Die Daten aus den Simulationen wurden für eine gründliche Analyse der Wellengestalt verwendet, wobei sich herausstellte, dass einige Seesterne stets hinter der Wellenfront zurückblieben. Um dieses Phänomen mit einem powerlaw-Ansatz zu beschreiben, wurde Entropie als Maß verwendet. In Übereinstimmung mit den bisher erwähnten Resultaten ist der analytische Beweis, dass für das Modell in dieser Diplomarbeit keine echten traveling-wave-Lösungen existieren. Es ist daher naheliegend ein erweitertes Modell, das auch Muschelwachstum berücksichtigt, zu untersuchen. In einer linearen Stabilitätsanalyse zeigte sich, dass die Stabilität beim Übergang von einem Modell ohne zu einem mit Diffusion stets erhalten bleibt. Umgekehrt kann eine geeignet gewählte Diffusivitätsfunktion sogar ein instabiles System stabilisieren. Anschließend wurden die Ergebnisse noch mit den Erkenntnissen anderer Forscher verglichen, die in ähnlichen Modellen traveling-wave-Lösungen vorweisen konnten. Es stellte sich heraus, dass dies durch die Verwendung von Singularitäten (z.B. unstetige Diffusivitätsfunktion) möglich war und es sei angemerkt, dass die in diesen Modellen getroffenen Annahmen nicht unbedingt den biologischen Gegebenheiten entsprechen. Wurden die Parameter des Advektions-Diffusions-Modells an diese Szenarien angepasst, so zeigten sich ebenfalls traveling-wave-artige Lösungen in den Simulationen. Zum Abschluss wurde noch untersucht, wie sich eine nicht-homogene Anfangsbedingung, d.h. periodische Muschelanhäufungen am Meeresgrund, auf die Seesterninvasionswellen auswirkt. Es zeigte sich, dass die Simulation im Wesentlichen die gleichen Ergebnisse wie im homogenen Fall lieferte und daher die konkrete Form der Muschelbänke im Allgemeinen keinen großen Einfluss auf die Seesterninvasion hat. Zusammenfassend kann festgehalten werden, dass das entwickelte Modell die biologische Dynamik und die realen Gegebenheiten äußerst zufriedenstellend beschreibt. Vom mathematischen Standpunkt sind dabei besonders die auftretenden Wellen interessant und eine Gegenüberstellung bzw. mögliche Einordnung in die Theorie der travelingwave-Lösungen. Vom biologischen Standpunkt ist es erfreulich, dass mit diesem Modell Seesterninvasionen besser untersucht werden können und sich dadurch entscheidende Rückschlüsse auf das Abernten der Muschelbänke ziehen lassen.The Danish Limfjord is famous for its mussel beds, which are harvested by fishers and known to be a popular delicacy. However, it has been observed that starfish waves invade former untouched mussel beds and completely erase them during their progression. The aim of this master thesis was to develop a PDE model describing this phenomenon. During the numerical simulations (MOL), it turned out that an advective-diffusive approach with suitable functions to specify starfish diffusion and mussel harvesting, actually yields wavelike solutions. However, these waves are not traveling waves in the classical sense, since amplitude and speed change over time. Thus, the obtained data was used to analyze and study their characteristics and asymptotics. Of special interest is the observation that some starfish are not part of the wavefront, but rather stay behind. Entropy is used as a measure to describe this phenomenon with a powerlaw ansatz. In accordance with these results is the analytical proof that for the given PDE model traveling invasion waves cannot occur. A natural model extension would be to include mussel growth. At first glance, it is not clear if this could affect the system's stability. The calculations carried out in this thesis showed that a stable non-spatial system will remain stable, no matter which diffusivity function will be used to describe the spatial system. Further, it is actually possible to stabilize an unstable non-spatial system by adequately choosing the diffusivity function. A comparison to other scientists' results yielded that they were actually able to get traveling wave solutions in similar models by introducing singularities. Hence, in another simulation run the parameters were chosen to approximate their initial conditions and diffusivity functions. Indeed, this resulted in traveling waves. Although it has to be stated that the biological assumptions do not correspond to a realistic scenario. Finally, it was investigated how periodic mussel beds as initial condition affect the wavelike starfish invasion. It turned out that the results are quite similar to the case with homogenous mussel distribution. This means that the actual mussel bed shapes, be it heap-like or rather uniformly spread, are not of high significance. Summing up all those findings, one can conclude that the advection-diffusion PDE model is able to model starfish invasions in a quite satisfying manner. From a mathematical point of view, it is highly interesting to compare the starfish waves to traveling waves as known from PDE theory and develop ways to characterize them. From a biological point of view, it is of high value to learn about the starfish wavefront's characteristics as to have a better understanding how fast and intense the mussel harvesting progresses.8

Stochastic Bounded Model Checking: Bounded Rewards and Compositionality

We extend the available SAT/SMT-based methods for generating counterexamples of probabilistic systems in two ways: First, we propose bounded rewards, which are appropriate, e. g., to model the energy consumption of autonomous embedded systems, and show how to extend the SMT-based counterexample generation to handle such models. Second, we describe a compositional SAT encoding of the transition relation of Markov models, which exploits the system structure to obtain a more compact formula, which in turn can be solved more efficiently. Preliminary experiments show promising results in both cases