Money-based interest rate rules: lessons from German data

The paper derives the monetary policy reaction function implied by money growth targeting. It consists of an interest rate response to deviations of the inflation rate from target, to the change in the output gap, to money demand shocks and to the lagged interest rate. In the second part, it is shown that this type of inertial interest rate rule characterises the Bundesbank's monetary policy from 1979 to 1998 quite well. This result is robust to the use of real-time or ex post data and to the consideration of serially correlated errors. The main lesson is that, in addition to anchoring long-term inflation expectations, monetary targeting introduces inertia and history-dependence into the monetary policy rule. This is advantageous when private agents have forward-looking expectations and when the level of the output gap is subject to persistent measurement errors. --Monetary policy,Taylor rule,money growth targets,history dependence

Intergenerational Coresidence and Female Labour Supply

We examine the role of family structure, specifically of co-residence with parents in-law, for female labour supply. To account for the endogeneity of co-residence, we exploit a tradition in Central Asia, namely that the youngest son of a family usually lives with his parents. Using data from Kyrgyzstan, we therefore instrument co-residence with being married to a youngest son. We find that the effect of co-residence on female labour supply - though insignificant - tends to be negative

Interest rate rules and monetary targeting: What are the links?

The paper derives the monetary policy reaction function implied by money growth targeting. It consists of an interest rate response to deviations of the inflation rate from target, to the change in the output gap, to money demand shocks and to the lagged interest rate. We show that this type of inertial interest rate rule characterises the Bundesbank's monetary policy from 1979 to 1998 quite well. This result is robust to the use of real-time or ex post data. The main lesson is that, in addition to anchoring long term inflation expectations, monetary targeting introduces inertia and history-dependence into the monetary policy rule. This is advantageous when private agents have forward-looking expectations and when the level of the output gap is subject to persistent measurement errors

PYRO-NN: Python Reconstruction Operators in Neural Networks

Purpose: Recently, several attempts were conducted to transfer deep learning to medical image reconstruction. An increasingly number of publications follow the concept of embedding the CT reconstruction as a known operator into a neural network. However, most of the approaches presented lack an efficient CT reconstruction framework fully integrated into deep learning environments. As a result, many approaches are forced to use workarounds for mathematically unambiguously solvable problems. Methods: PYRO-NN is a generalized framework to embed known operators into the prevalent deep learning framework Tensorflow. The current status includes state-of-the-art parallel-, fan- and cone-beam projectors and back-projectors accelerated with CUDA provided as Tensorflow layers. On top, the framework provides a high level Python API to conduct FBP and iterative reconstruction experiments with data from real CT systems. Results: The framework provides all necessary algorithms and tools to design end-to-end neural network pipelines with integrated CT reconstruction algorithms. The high level Python API allows a simple use of the layers as known from Tensorflow. To demonstrate the capabilities of the layers, the framework comes with three baseline experiments showing a cone-beam short scan FDK reconstruction, a CT reconstruction filter learning setup, and a TV regularized iterative reconstruction. All algorithms and tools are referenced to a scientific publication and are compared to existing non deep learning reconstruction frameworks. The framework is available as open-source software at \url{https://github.com/csyben/PYRO-NN}. Conclusions: PYRO-NN comes with the prevalent deep learning framework Tensorflow and allows to setup end-to-end trainable neural networks in the medical image reconstruction context. We believe that the framework will be a step towards reproducible researchComment: V1: Submitted to Medical Physics, 11 pages, 7 figure

Gas-induced segregation in Pt-Rh alloy nanoparticles observed by in-situ Bragg coherent diffraction imaging

Bimetallic catalysts can undergo segregation or redistribution of the metals driven by oxidizing and reducing environments. Bragg coherent diffraction imaging (BCDI) was used to relate displacement fields to compositional distributions in crystalline Pt-Rh alloy nanoparticles. 3D images of internal composition showed that the radial distribution of compositions reverses partially between the surface shell and the core when gas flow changes between O2 and H2. Our observation suggests that the elemental segregation of nanoparticle catalysts should be highly active during heterogeneous catalysis and can be a controlling factor in synthesis of electrocatalysts. In addition, our study exemplifies applications of BCDI for in situ 3D imaging of internal equilibrium compositions in other bimetallic alloy nanoparticles

Increasing the Interactivity in Software Engineering MOOCs - A Case Study

MOOCs differ from traditional university courses: instructors do not know the learners who have a diverse background and cannot talk to them in person due to the worldwide distribution. This has a decisive influence on the interactivity of teaching and the learning success in online courses. While typical online exercises such as multiple choice quizzes are interactive, they only stimulate basic cognitive skills and do not reflect software engineering working practices such as programming or testing. However, the application of knowledge in practical and realistic exercises is especially important in software engineering education. In this paper, we present an approach to increase the interactivity in software engineering MOOCs. Our interactive learning approach focuses on a variety of practical and realistic exercises, such as analyzing, designing, modeling, programming, testing, and delivering software stimulating all cognitive skills. Semi-automatic feedback provides guidance and allows reflection on the learned theory. We applied this approach in the MOOC software engineering essentials SEECx on the edX platform. Since the beginning of the course, more than 15,000 learners from more than 160 countries have enrolled. We describe the design of the course and explain how its interactivity affects the learning success

Recommendations for the Transition to Open Access in Austria

Based on 16 recommendations, efforts should be made to achieve the following goal: By 2025, a large part of all scholarly publication activity in Austria should be Open Access. In other words, the final versions of most scholarly publications (in particular all refereed journal articles and conference proceedings) resulting from the support of public resources must be freely accessible on the Internet without delay (Gold Open Access). This goal should be pursued by taking into account the different disciplinary practices and under consideration of the different disciplinary priorisations of Open Access. The resources required to meet this obligation shall be provided to the authors, or the cost of the publication venues shall be borne directly by the research organisations. The necessary funding must be brought in line with the overall funding priorities for research

Effects of different acute stressors on the regulation of appetite genes in the carp (Cyprinus carpio L.) brain

Our understanding of the timing of stress responses and specific roles of different regulatory pathways that drive stress responses is incomplete. In particular, the regulation of appetite genes as a consequence of exposure to different stressors has not been studied in sufficient detail in fish. Therefore, a stress trial was conducted with koi carp, aiming at identifying typical effects of stress on regulation of appetite genes. The stressors tank manipulation, air exposure and feed rewarding were chosen. The responses to these stressors were evaluated 10, 30 and 60 min after the stressors were applied. Orexigenic and anorexigenic genes were investigated in four different brain regions (telencephalon, hypothalamus, optic tectum and rhombencephalon). The results show that, apart from the typical appetite regulation in the hypothalamus, the different brain regions also display pronounced responses of appetite genes to the different stressors. In addition, several genes in the serotonergic, dopaminergic and gaba-related pathways were investigated. These genes revealed that rearing in pairs of two and opening of the tank lid affected anorexigenic genes, such as cart and cck, which were not changed by air exposure or feed rewarding. Moreover, distress and eustress led to limited, but distinguishable gene expression pattern changes in the investigated brain regions