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Graph repair, restoring consistency of a graph, plays a prominent role in several areas of computer science and beyond: For example, in model-driven engineering, the abstract syntax of models is usually encoded using graphs. Flexible edit operations temporarily create inconsistent graphs not representing a valid model, thus requiring graph repair. Similarly, in graph databases—managing the storage and manipulation of graph data—updates may cause that a given database does not satisfy some integrity constraints, requiring also graph repair. We present a logic-based incremental approach to graph repair, generating a sound and complete (upon termination) overview of least-changing repairs. In our context, we formalize consistency by so-called graph conditions being equivalent to first-order logic on graphs. We present two kind of repair algorithms: State-based repair restores consistency independent of the graph update history, whereas deltabased (or incremental) repair takes this history explicitly into account. Technically, our algorithms rely on an existing model generation algorithm for graph conditions implemented in AutoGraph. Moreover, the delta-based approach uses the new concept of satisfaction (ST) trees for encoding if and how a graph satisfies a graph condition. We then demonstrate how to manipulate these STs incrementally with respect to a graph update.
Graph repair, restoring consistency of a graph, plays a prominent role in several areas of computer science and beyond: For example, in model-driven engineering, the abstract syntax of models is usually encoded using graphs. Flexible edit operations temporarily create inconsistent graphs not representing a valid model, thus requiring graph repair. Similarly, in graph databases—managing the storage and manipulation of graph data—updates may cause that a given database does not satisfy some integrity constraints, requiring also graph repair.
We present a logic-based incremental approach to graph repair, generating a sound and complete (upon termination) overview of least-changing repairs. In our context, we formalize consistency by so-called graph conditions being equivalent to first-order logic on graphs. We present two kind of repair algorithms: State-based repair restores consistency independent of the graph update history, whereas deltabased (or incremental) repair takes this history explicitly into account. Technically, our algorithms rely on an existing model generation algorithm for graph conditions implemented in AutoGraph. Moreover, the delta-based approach uses the new concept of satisfaction (ST) trees for encoding if and how a graph satisfies a graph condition. We then demonstrate how to manipulate these STs incrementally with respect to a graph update.
In daily life, we automatically form impressions of other individuals on basis of subtle facial features that convey trustworthiness. Because these face-based judgements influence current and future social interactions, we investigated how perceived trustworthiness of faces affects long-term memory using event-related potentials (ERPs). In the current study, participants incidentally viewed 60 neutral faces differing in trustworthiness, and one week later, performed a surprise recognition memory task, in which the same old faces were presented intermixed with novel ones. We found that after one week untrustworthy faces were better recognized than trustworthy faces and that untrustworthy faces prompted early (350–550 ms) enhanced frontal ERP old/new differences (larger positivity for correctly remembered old faces, compared to novel ones) during recognition. Our findings point toward an enhanced long-lasting, likely familiarity-based, memory for untrustworthy faces. Even when trust judgments about a person do not necessarily need to be accurate, a fast access to memories predicting potential harm may be important to guide social behaviour in daily life.
Verwaltungswissenschaft
(2019)
Das Werk ist im ersten Teil Grundlagen und Querschnittsfragen der Verwaltungswissenschaft gewidmet. Zunächst stellt der Verfasser die Erkenntnisobjekte "Verwaltungswissenschaft" und "Öffentliche Verwaltung" vor. Sodann vermittelt er dem Leser Aufgaben, Kulturen, Reformen und die Kontrolle der Verwaltung. Im zweiten Teil werden Verwaltungsbehörden als Organisationen und Handlungssysteme näher beleuchtet. Die betreffenden Kapitel behandeln die Aufbauorganisation, das Personal, die Koordination, das Verfahren und die Entscheidung.
This paper challenges the solely rational view of the scenario technique as a strategy and foresight tool designed to cope with uncertainty by considering multiple possible future states. The paper employs an affordance-based view that allows for the identification and structuring of hidden, emergent attributes of the scenario technique beyond the intended ones. The suggested framework distinguishes between affordances (1) that are intended by the organization and relate to its goals, (2) that emergently generate organizational benefits, and (3) that do not relate to organizational but individual interests. Also, constraints in the use of scenarios are discussed. Affordance theory’s specific lens shows that the emergence of such attributes depends on the users’ specific intentions.
In the scenario of the narrow escape problem (NEP) a particle diffuses in a finite container and eventually leaves it through a small 'escape window' in the otherwise impermeable boundary, once it arrives to this window and crosses an entropic barrier at the entrance to it. This generic problem is mathematically identical to that of a diffusion-mediated reaction with a partially-reactive site on the container's boundary. Considerable knowledge is available on the dependence of the mean first-reaction time (FRT) on the pertinent parameters. We here go a distinct step further and derive the full FRT distribution for the NEP. We demonstrate that typical FRTs may be orders of magnitude shorter than the mean one, thus resulting in a strong defocusing of characteristic temporal scales. We unveil the geometry-control of the typical times, emphasising the role of the initial distance to the target as a decisive parameter. A crucial finding is the further FRT defocusing due to the barrier, necessitating repeated escape or reaction attempts interspersed with bulk excursions. These results add new perspectives and offer a broad comprehension of various features of the by-now classical NEP that are relevant for numerous biological and technological systems.
Relationship quality between teachers and their students is a critical aspect for well-being and effective learning in school. Accordingly, teacher training should promote competencies for creating and maintaining positive relationships in the classroom. The Helga Breuninger Foundation developed a video-based online training (Intus³) that intends to focus on student teachers' interpersonal competencies by reflecting on staged videos. Although this training is well-designed, there is only little empirical evidence in general and so far no experimental research investigating the effects of Intus³. Accordingly, we investigated whether this program is able to improve the capacities of student teachers' interpersonal competencies, affective well-being, and affective attitudes toward challenging students. We conducted two randomized experimental studies (n1 = 132, n2 = 242) within lectures in teacher education at the University of Potsdam, introducing the basics of inclusive education in two consecutive semesters. We compared groups first working with Intus³ to waiting control groups that wrote an expository text based on empirical research discussing the relevance of teacher–student relationships with a longitudinal design with four measurement points. Latent change models showed that prior work with Intus³ showed few effects but complex effects in comparison to the prior text work groups. In the larger and extended study 2, an increase of empathic concern was significant after the prior work with Intus³. The results will be discussed with the perspective of the potential of further development of online training courses for affective learning for teachers and teacher students.
Ultrafast magnetisation dynamics have been investigated intensely for two decades. The recovery process after demagnetisation, however, was rarely studied experimentally and discussed in detail. The focus of this work lies on the investigation of the magnetisation on long timescales after laser excitation. It combines two ultrafast time resolved methods to study the relaxation of the magnetic and lattice system after excitation with a high fluence ultrashort laser pulse. The magnetic system is investigated by time resolved measurements of the magneto-optical Kerr effect. The experimental setup has been implemented in the scope of this work. The lattice dynamics were obtained with ultrafast X-ray diffraction. The combination of both techniques leads to a better understanding of the mechanisms involved in magnetisation recovery from a non-equilibrium condition. Three different groups of samples are investigated in this work: Thin Nickel layers capped with nonmagnetic materials, a continuous sample of the ordered L10 phase of Iron Platinum and a sample consisting of Iron Platinum nanoparticles embedded in a carbon matrix. The study of the remagnetisation reveals a general trend for all of the samples: The remagnetisation process can be described by two time dependences. A first exponential recovery that slows down with an increasing amount of energy absorbed in the system until an approximately linear time dependence is observed. This is followed by a second exponential recovery. In case of low fluence excitation, the first recovery is faster than the second. With increasing fluence the first recovery is slowed down and can be described as a linear function. If the pump-induced temperature increase in the sample is sufficiently high, a phase transition to a paramagnetic state is observed. In the remagnetisation process, the transition into the ferromagnetic state is characterised by a distinct transition between the linear and exponential recovery. From the combination of the transient lattice temperature Tp(t) obtained from ultrafast X-ray measurements and magnetisation M(t) gained from magneto-optical measurements we construct the transient magnetisation versus temperature relations M(Tp). If the lattice temperature remains below the Curie temperature the remagnetisation curve M(Tp) is linear and stays below the M(T) curve in equilibrium in the continuous transition metal layers. When the sample is heated above phase transition, the remagnetisation converges towards the static temperature dependence. For the granular Iron Platinum sample the M(Tp) curves for different fluences coincide, i.e. the remagnetisation follows a similar path irrespective of the initial laser-induced temperature jump.
In the era of social networks, internet of things and location-based services, many online services produce a huge amount of data that have valuable objective information, such as geographic coordinates and date time. These characteristics (parameters) in the combination with a textual parameter bring the challenge for the discovery of geospatiotemporal knowledge. This challenge requires efficient methods for clustering and pattern mining in spatial, temporal and textual spaces.
In this thesis, we address the challenge of providing methods and frameworks for geospatiotemporal data analytics. As an initial step, we address the challenges of geospatial data processing: data gathering, normalization, geolocation, and storage. That initial step is the basement to tackle the next challenge -- geospatial clustering challenge. The first step of this challenge is to design the method for online clustering of georeferenced data. This algorithm can be used as a server-side clustering algorithm for online maps that visualize massive georeferenced data. As the second step, we develop the extension of this method that considers, additionally, the temporal aspect of data. For that, we propose the density and intensity-based geospatiotemporal clustering algorithm with fixed distance and time radius.
Each version of the clustering algorithm has its own use case that we show in the thesis.
In the next chapter of the thesis, we look at the spatiotemporal analytics from the perspective of the sequential rule mining challenge. We design and implement the framework that transfers data into textual geospatiotemporal data - data that contain geographic coordinates, time and textual parameters. By this way, we address the challenge of applying pattern/rule mining algorithms in geospatiotemporal space. As the applicable use case study, we propose spatiotemporal crime analytics -- discovery spatiotemporal patterns of crimes in publicly available crime data.
The second part of the thesis, we dedicate to the application part and use case studies. We design and implement the application that uses the proposed clustering algorithms to discover knowledge in data. Jointly with the application, we propose the use case studies for analysis of georeferenced data in terms of situational and public safety awareness.
Due to advances in science and technology towards smaller and more powerful processing units, the fabrication of micrometer sized machines for different tasks becomes more and more possible. Such micro-robots could revolutionize medical treatment of diseases and shall support to work on other small machines. Nevertheless, scaling down robots and other devices is a challenging task and will probably remain limited in near future. Over the past decade the concept of bio-hybrid systems has proved to be a promising approach in order to advance the further development of micro-robots. Bio-hybrid systems combine biological cells with artificial components, thereby benefiting from the functionality of living biological cells. Cell-driven micro-transport is one of the most prominent applications in the emerging field of these systems. So far, micrometer sized cargo has been successfully transported by means of swimming bacterial cells. The potential of motile adherent cells as transport systems has largely remained unexplored.
This thesis concentrates on the social amoeba Dictyostelium discoideum as a potential candidate for an amoeboid bio-hybrid transport system. The use of this model organism comes with several advantages. Due to the unspecific properties of Dictyostelium adhesion, a wide range of different cargo materials can be used for transport. As amoeboid cells exceed bacterial cells in size by one order of magnitude, also the size of an object carried by a single cell can also be much larger for an amoeba. Finally it is possible to guide the cell-driven transport based on the chemotactic behavior of the amoeba. Since cells undergo a developmentally induced chemotactic aggregation, cargo could be assembled in a self-organized manner into a cluster. It is also possible to impose an external chemical gradient to guide the amoeboid transport system to a desired location.
To establish Dictyostelium discoideum as a possible candidate for bio-hybrid transport systems, this thesis will first investigate the movement of single cells. Secondly, the interaction of cargo and cells will be studied. Eventually, a conceptional proof will be conducted, that the cheomtactic behavior can be exploited either to transport a cargo self-organized or through an external chemical source.