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Der Tagungsbericht fasst die Vorträge, Workshops und Ergebnisse der Abschlusstagung des BMBF-Projektes PODMAN: „Forschung + Datenmanagement = Forschungsdatenmanagement – Wann geht die Gleichung auf?“ vom 27. und 28. März 2019 an der Universität Trier zusammen. Ihm sind die Vortragsfolien, die Präsentationen der Workshops sowie die zugehörige Fotodokumentation der Arbeitsgruppen im Anhang beigefügt.
Die Beschäftigung mit dem Luxemburgischen unter phraseologischem Gesichtspunkt ist ein Phänomen der jüngsten Forschungen, das erst im Laufe der letzten beiden Jahrzehnte vermehrt Aufmerksam gefunden hat. Trotz einer bereits soliden Grundsteinlegung bietet die Phraseologie des Luxemburgischen noch reichlich Untersuchungsfläche. Die Dissertation "Formelhafte Sprache in der Chambre des Députés: Eine empirische Untersuchung der Phrasemverwendung im Luxemburgischen anhand der öffentlichen Sitzungsprotokolle der Abgeordnetenkammer" befasst sich mit dem Gebrauch des Luxemburgischen in politischen Reden, mit Schwerpunkt auf formelhafter Sprache, sogenannten Phraseologismen, wie etwa Routineformeln (z. B.: Dir Dammen an Dir Hären…; wéi scho gesot…), Sprichwörter (z. B.: Déi aarm Leit kache mat Waasser; Wie schnell geet, geet duebel), Paarformeln (z. B.: de Sënn an den Zweck; ëmmer an iwwerall), komparative Phraseologismen (z. B.: eppes läit engem um Mo wéi eng Zill) und andere vorgefertigte Sprachelemente, die meistens in einer verfestigten Form vorkommen und häufig dazu dienen, bestimmte Kommunikationssituationen zu bewältigen. In diesen Reden spielen Phraseologismen unbestreitbar eine wichtige Rolle, seien es bewusst eingesetzte Wortverbindungen, die rhetorisch überzeugen sollen oder unbewusst vorkommende Phraseologismen, die den Redefluss und die Formulierung erleichtern. Zudem zeigt die Formelhaftigkeit sich in dieser Textsorte umso stärker, weil es in den Sitzungen der Abgeordnetenkammer, ebenso wie in anderen Parlamenten auch, eine Fülle von fest vorgeschriebenen Abläufen und festgelegte Rollen mit eigenen ritualisierten Redeanteilen gibt. Die in den stenographischen Protokollen aufgezeichneten Reden und Debatten aus dem luxemburgischen Parlament bilden also die Grundlage der Untersuchung. Im Vorfeld wurde ein Untersuchungkorpus zusammengestellt, indem die betreffenden Sprachelemente (Phraseme) manuell exzerpiert wurden. Diese wurden in eine Datenbank eingetragen, nach mehreren Kriterien klassifiziert und mit zusätzlichen Metainformationen angereichert. Der Hauptteil der Untersuchung besteht in der Analyse der im Textkorpus vorkommenden Phraseme innerhalb ihres Kontextes in den Abgeordnetenreden, um die unterschiedlichen (stilistischen, rhetorischen, etc.) Funktionen und Effekte herauszuarbeiten, die sie in den jeweiligen Redestellen erfüllen. Dieses Vorgehen ist von großer Bedeutung, um zu erkennen, wie wichtig solche verfestigten Ausdrücke und formelhaften Elemente für die Sprache sind und welche zentrale Rolle sie in den untersuchten Reden und im Luxemburgischen im Allgemeinen spielen. Daneben werden auch quantitative Aspekte untersucht (z. B. allgemeine Phraseologismenfrequenz; Verteilung auf unterschiedliche Phraseologismusklassen; Phrasemvorkommen in unterschiedlichen Zeitschnitten), damit die ausgewählten Texte auch mit anderen Textsorten oder mit Parlamentsreden aus anderen Sprachen vergleichbar sind hinsichtlich des Gebrauchs von formelhaften/phraseologischen Elementen.
Formation et marché du travail transfrontalier : Quelles pistes face aux déséquilibres croissants ?
(2022)
L’objet de ce document est d’alimenter la réflexion sur le rôle de la formation sur le marché du travail transfrontalier, en mobilisant les débats engagés à la fois dans les différents Cahiers de la Grande Ré-gion et lors d’une conférencedébat organisée en ligne le 1er décembre 2020 sur le thème « Inadéquations, Compétences, et formation : Quelles équations pour le marché du travail transfrontalier ? ». Plus précisément, cette contribution vise à répondre à la question suivante : comment la formation et ses différentes pratiques dans les domaines professionnels, mais aussi dans l’enseignement scolaire et universitaire peuvent atténuer les déséquilibres qui se font jour sur le marché du travail de la Grande Région ? Le document propose ainsi quelques pistes de réflexions pour la coopération transfrontalière en matière de formation.
This thesis centers on formal tree languages and on their learnability by algorithmic methods in abstractions of several learning settings. After a general introduction, we present a survey of relevant definitions for the formal tree concept as well as special cases (strings) and refinements (multi-dimensional trees) thereof. In Chapter 3 we discuss the theoretical foundations of algorithmic learning in a specific type of setting of particular interest in the area of Grammatical Inference where the task consists in deriving a correct formal description for an unknown target language from various information sources (queries and/or finite samples) in a polynomial number of steps. We develop a parameterized meta-algorithm that incorporates several prominent learning algorithms from the literature in order to highlight the basic routines which regardless of the nature of the information sources have to be run through by all those algorithms alike. In this framework, the intended target descriptions are deterministic finite-state tree automata. We discuss the limited transferability of this approach to another class of descriptions, residual finite-state tree automata, for which we propose several learning algorithms as well. The learnable class by these techniques corresponds to the class of regular tree languages. In Chapter 4we outline a recent range of attempts in Grammatical Inference to extend the learnable language classes beyond regularity and even beyond context-freeness by techniques based on syntactic observations which can be subsumed under the term 'distributional learning', and we describe learning algorithms in several settings for the tree case taking this approach. We conclude with some general reflections on the notion of learning from structural information.
In der kleinen ostfriesischen Kirchengemeinde W. hat sich im Jahr 1969 ein plötzlicher Todesfall ereignet. Fremdverschulden wird ausgeschlossen. Jemand, der die Hintergründe des Todesfalls aufklären will, stößt allenthalben auf – bisweilen gar aggressives – Schweigen. Eine Geschichte über individuelle und kollektive Schuld, lutherische Kirchenmusik und den Wert, den wir der Kultur und der Tradition beimessen.
Ausgezeichnet mit dem Borsla-Preis 2019.
Although it has been demonstrated that nociceptive processing can be modulated by heterotopically and concurrently applied noxious stimuli, the nature of brain processes involved in this percept modulation in healthy subjects remains elusive. Using functional magnetic resonance imaging (fMRI) we investigated the effect of noxious counter-stimulation on pain processing. FMRI scans (1.5 T; block-design) were performed in 34 healthy subjects (median age: 23.5 years; range: 20-31 yrs.) during combined and single application (duration: 15 s; ISI=36 s incl. 6 s rating time) of noxious interdigital-web pinching (intensity range: 6-15 N) and contact-heat (45-49 -°C) presented in pseudo-randomized order during two runs separated by approx. 15 min with individually adjusted equi-intense stimuli. In order to control for attention artifacts, subjects were instructed to maintain their focus either on the mechanical or on the thermal pain stimulus. Changes in subjective pain intensity were computed as percent differences (∆%) in pain ratings between single and heterotopic stimulation for both fMRI runs, resulting in two subgroups showing a relative pain increase (subgroup P-IN, N=10) vs. decrease (subgroup P-DE, N=12). Second level and Region of Interest analysis conducted for both subgroups separately revealed that during heterotopic noxious counter-stimulation, subjects with relative pain decrease showed stronger and more widespread brain activations compared to subjects with relative pain increase in pain processing regions as well as a fronto-parietal network. Median-split regression analyses revealed a modulatory effect of prefrontal activation on connectivity between the thalamus and midbrain/pons, supporting the proposed involvement of prefrontal cortex regions in pain modulation. Furthermore, the mid-sagittal size of the total corpus callosum and five of its subareas were measured from the in vivo magnetic resonance imaging (MRI) recordings. A significantly larger relative truncus size (P=.04) was identified in participants reporting a relative decrease of subjective pain intensity during counter-stimulation, when compared to subjects experiencing a relative pain increase. The above subgroup differences observed in functional and structural imaging data are discussed with consideration of potential differences in cognitive and emotional aspects of pain modulation.
The microbial enzyme alkaline phosphatase contributes to the removal of organic phosphorus compounds from wastewaters. To cope with regulatory threshold values for permitted maximum phosphor concentrations in treated wastewaters, a high activity of this enzyme in the biological treatment stage, e.g., the activated sludge process, is required. To investigate the reaction dynamics of this enzyme, to analyze substrate selectivities, and to identify potential inhibitors, the determination of enzyme kinetics is necessary. A method based on the application of the synthetic fluorogenic substrate 4-methylumbelliferyl phosphate is proven for soils, but not for activated sludges. Here, we adapt this procedure to the latter. The adapted method offers the additional benefit to determine inhibition kinetics. In contrast to conventional photometric assays, no particle removal, e.g., of sludge pellets, is required enabling the analysis of the whole sludge suspension as well as of specific sludge fractions. The high sensitivity of fluorescence detection allows the selection of a wide substrate concentration range for sound modeling of kinetic functions.
- Fluorescence array technique for fast and sensitive analysis of high sample numbers
- No need for particle separation – analysis of the whole (diluted) sludge suspension
- Simultaneous determination of standard and inhibition kinetics
Traditional workflow management systems support process participants in fulfilling business tasks through guidance along a predefined workflow model.
Flexibility has gained a lot of attention in recent decades through a shift from mass production to customization. Various approaches to workflow flexibility exist that either require extensive knowledge acquisition and modelling effort or an active intervention during execution and re-modelling of deviating behaviour. The pursuit of flexibility by deviation is to compensate both of these disadvantages through allowing alternative unforeseen execution paths at run time without demanding the process participant to adapt the workflow model. However, the implementation of this approach has been little researched so far.
This work proposes a novel approach to flexibility by deviation. The approach aims at supporting process participants during the execution of a workflow through suggesting work items based on predefined strategies or experiential knowledge even in case of deviations. The developed concepts combine two renowned methods from the field of artificial intelligence - constraint satisfaction problem solving with process-oriented case-based reasoning. This mainly consists of a constraint-based workflow engine in combination with a case-based deviation management. The declarative representation of workflows through constraints allows for implicit flexibility and a simple possibility to restore consistency in case of deviations. Furthermore, the combined model, integrating procedural with declarative structures through a transformation function, increases the capabilities for flexibility. For an adequate handling of deviations the methodology of case-based reasoning fits perfectly, through its approach that similar problems have similar solutions. Thus, previous made experiences are transferred to currently regarded problems, under the assumption that a similar deviation has been handled successfully in the past.
Necessary foundations from the field of workflow management with a focus on flexibility are presented first.
As formal foundation, a constraint-based workflow model was developed that allows for a declarative specification of foremost sequential dependencies of tasks. Procedural and declarative models can be combined in the approach, as a transformation function was specified that converts procedural workflow models to declarative constraints.
One main component of the approach is the constraint-based workflow engine that utilizes this declarative model as input for a constraint solving algorithm. This algorithm computes the worklist, which is proposed to the process participant during workflow execution. With predefined deviation handling strategies that determine how the constraint model is modified in order to restore consistency, the support is continuous even in case of deviations.
The second major component of the proposed approach constitutes the case-based deviation management, which aims at improving the support of process participants on the basis of experiential knowledge. For the retrieve phase, a sophisticated similarity measure was developed that integrates specific characteristics of deviating workflows and combines several sequence similarity measures. Two alternative methods for the reuse phase were developed, a null adaptation and a generative adaptation. The null adaptation simply proposes tasks from the most similar workflow as work items, whereas the generative adaptation modifies the constraint-based workflow model based on the most similar workflow in order to re-enable the constraint-based workflow engine to suggest work items.
The experimental evaluation of the approach consisted of a simulation of several types of process participants in the exemplary domain of deficiency management in construction. The results showed high utility values and a promising potential for an investigation of the transfer on other domains and the applicability in practice, which is part of future work.
Concluding, the contributions are summarized and research perspectives are pointed out.
A basic assumption of standard small area models is that the statistic of interest can be modelled through a linear mixed model with common model parameters for all areas in the study. The model can then be used to stabilize estimation. In some applications, however, there may be different subgroups of areas, with specific relationships between the response variable and auxiliary information. In this case, using a distinct model for each subgroup would be more appropriate than employing one model for all observations. If no suitable natural clustering variable exists, finite mixture regression models may represent a solution that „lets the data decide“ how to partition areas into subgroups. In this framework, a set of two or more different models is specified, and the estimation of subgroup-specific model parameters is performed simultaneously to estimating subgroup identity, or the probability of subgroup identity, for each area. Finite mixture models thus offer a fexible approach to accounting for unobserved heterogeneity. Therefore, in this thesis, finite mixtures of small area models are proposed to account for the existence of latent subgroups of areas in small area estimation. More specifically, it is assumed that the statistic of interest is appropriately modelled by a mixture of K linear mixed models. Both mixtures of standard unit-level and standard area-level models are considered as special cases. The estimation of mixing proportions, area-specific probabilities of subgroup identity and the K sets of model parameters via the EM algorithm for mixtures of mixed models is described. Eventually, a finite mixture small area estimator is formulated as a weighted mean of predictions from model 1 to K, with weights given by the area-specific probabilities of subgroup identity.
Finding behavioral parameterization for a 1-D water balance model by multi-criteria evaluation
(2019)
Evapotranspiration is often estimated by numerical simulation. However, to produce accurate simulations, these models usually require on-site measurements for parameterization or calibration. We have to make sure that the model realistically reproduces both, the temporal patterns of soil moisture and evapotranspiration. In this study, we combine three sources of information: (i) measurements of sap velocities; (ii) soil moisture; and (iii) expert knowledge on local runoff generation and water balance to define constraints for a “behavioral” forest stand water balance model. Aiming for a behavioral model, we adjusted soil moisture at saturation, bulk resistance parameters and the parameters of the water retention curve (WRC). We found that the shape of the WRC influences substantially the behavior of the simulation model. Here, only one model realization could be referred to as “behavioral”. All other realizations failed for a least one of our evaluation criteria: Not only transpiration and soil moisture are simulated consistently with our observations, but also total water balance and runoff generation processes. The introduction of a multi-criteria evaluation scheme for the detection of unrealistic outputs made it possible to identify a well performing parameter set. Our findings indicate that measurement of different fluxes and state variables instead of just one and expert knowledge concerning runoff generation facilitate the parameterization of a hydrological model.