Entanglement dynamics in open two-qubit systems via diffusive quantum trajectories

We use quantum diffusive trajectories to prove that the time evolution of two-qubit entanglement under spontaneous emission can be fully characterized by optimal continuous monitoring. We analytically determine this optimal unraveling and derive a deterministic evolution equation for the system's concurrence. Furthermore, we propose an experiment to monitor the entanglement dynamics in bipartite two-level systems and to determine the disentanglement time from a single trajectory.Comment: 4 pages, 2 figures, changed title, abstract and fig. 2, corrected typo

Improve Your Modeling Skills with the Help of Your Peers – Developing and Introducing a Digital Case Study and Peer Feedback App in an Information Systems Class

The overall goal of this research study is to improve students’ modeling skills in large-scale educational settings by providing video-based case studies and introducing a formative peer feedback process to enable asynchronous, anonymous collaboration among the students. To this aim, we designed a learning concept and implemented an app that supports the provision of video-based case studies and the conduction of a double-blind peer feedback process. Our results from introducing the digital learning concept in an introductory course targeting information systems students indicate that the students’ motivation and reflection on the learning content could be fostered, and their modeling skills could be improved. Overall, we contribute with insights into how to conduct video-based case studies combined with peer feedback processes in information systems education

The influence of the layer sizes on the conversion regimes realizing at layered composite synthesis

The composite materials with different structure find a variety of applications. However, the peculiarities of the propagation of chemical reactions between structural elements during composite material synthesis are poorly studied. This paper suggests a model describing the conjugation of structure composite elements using a solid phase reaction at the ignition from a free surface. It was established that depending on the relation between layer sizes, various conversion regimes between inert materials are observed. The regimes differ in temperature values in the reaction zone, heterogeneities of temperature field and reaction zone thickness. Relation between thermophysical properties and thicknesses of layers can both promote reaction and retard it

Hamburger Mathematikabitur im Kreuzfeuer der Kritik

Das Hamburger Mathematikabitur war in den letzten Monaten im Kreuzfeuer der Kritik, insbesondere auch auf politischer Ebene. So haben einige Abgeordnete der Hamburger Bürgerschaft unter Bezug auf die steigende Abiturientenquote in Hamburg am 27. 11. 2013 eine Große Anfrage an den Hamburger Senat zum Niveau des Hamburger Abiturs gestellt, in der sie folgendes fragen: Vor diesem Hintergrund muss man sich die Frage stellen, ob ein derartiger Anstieg der Abiturientenquote, wie er in Hamburg und anderen Großstädten zu beobachten ist, nur über eine Veränderung der Leistungsansprüche erklärbar ist. Ist das Niveau des Abiturs in Hamburg in den vergangenen Jahren gesunken? (Drucksache 20/10116 der Bürgerschaft der Freien und Hansestadt Hamburg – 20. Wahlperiode

Professional knowledge of (prospective) Mathematics Teachers – Its structure and development

Recent research on the professional knowledge of mathematics teachers, which has been carried out in the last decade, is in the focus of this paper. Building on the international IEA Teacher Education and Development Study – Learning to Teach Mathematics (TEDS-M), this paper describes a more situated way of evaluating the professional knowledge of teachers. The theoretical framework of the follow-up study of TEDS-M takes up the novice-expert framework andanalyses via video-based assessment instruments the structure and development of the professional knowledge of mathematics teachers. More recent concepts on noticing and interpreting classroom situations and students’ activities are also incorporated into the analysis. Connecting the results of the study TEDS-FU with the study TEDS-M gives insight into the development of the professional knowledge of mathematics teachers

Professional knowledge of (prospective) Mathematics Teachers – Its structure and development

Recent research on the professional knowledge of mathematics teachers, which has been carried out in the last decade, is in the focus of this paper. Building on the international IEA Teacher Education and Development Study – Learning to Teach Mathematics (TEDS-M), this paper describes a more situated way of evaluating the professional knowledge of teachers. The theoretical framework of the follow-up study of TEDS-M takes up the novice-expert framework andanalyses via video-based assessment instruments the structure and development of the professional knowledge of mathematics teachers. More recent concepts on noticing and interpreting classroom situations and students’ activities are also incorporated into the analysis. Connecting the results of the study TEDS-FU with the study TEDS-M gives insight into the development of the professional knowledge of mathematics teachers

Different sample types in pigs challenged with Haemophilus parasuis following two treatment schemes with tulathromycin

This study aimed to test the efficacy of samplings for the detection of Haemophilus parasuis after metaphylactic treatment and subsequent challenge using an established model for Glässer’s disease. In this model, 36 piglets were equally assigned to a negative control, a positive control, and two trial groups receiving tulathromycin 7 or 4 days prior to challenge. The piglets of three groups were challenged intratracheally with H. parasuis serovar 5. As a result, four pigs in each challenged group died or had to be euthanised within 10 days post challenge. The remaining 15 pigs of these challenged groups survived until termination of the experiment (days 14–15). All pigs were necropsied and collective swabs of serosal surfaces were tested by bacterial culture and PCR. Samples of tarsal synovial fluid and joint capsule, cerebrospinal fluid (CSF) and brain swabs were tested by PCR. A total of 22 out of the 27 challenged animals had macroscopically detectable polyserositis and all of them tested positive in the collective swab samples. Haemophilus parasuis was more frequently detected in pigs that died within the first 10 days compared to those surviving until days 14–15 (P < 0.001), and those that succumbed within 10 days showed higher positivity rates in the brain and CSF. All pigs which were positive in the CSF had detectable meningitis. At days 14–15, joint samples from 5 of the remaining 15 pigs tested positive for H. parasuis. Four of these five animals did not show any macroscopic or histological lesions in the joints. In conclusion, collective swabs were the best sample material in acute cases, whereas samples from the joints gave the best results in chronic cases. In this challenge model it was not possible to prove the metaphylactic effect of tulathromycin administered 4 and 7 days prior to infection with H. parasuis

Road pavement crack detection using deep learning with synthetic data

The improvement of road system quality is a critical task. The mechanism to address such important issue is close monitoring of road pavement condition. Traditional approach requires manual identification of damages. Taking into account considerable length of road system it is essential to create an effective automatic pavement defects detection tool. This approach will extremely reduce time for monitoring of current road state. In this paper global experience in solution of detection issues of road pavement's distress is reviewed. The article includes information about the existing datasets of road defects, which are commonly used for detection and segmentation. The present work is based on deep learning approach with the use of synthetic generated training data for segmentation of cracks in driver-view image. The novelty of the approach lies in creating synthetic dataset for training state-of-the-art deep learning frameworks. The relevance of the research is emphasized by processing of wide-view images in which heterogeneous pixel intensity, complex crack topology, different illumination condition and complexity of background make the task challenging