Monitoring multicountry macroeconomic risk

We propose a multicountry quantile factor augmeneted vector autoregression (QFAVAR) to model heterogeneities both across countries and across characteristics of the distributions of macroeconomic time series. The presence of quantile factors allows for summarizing these two heterogeneities in a parsimonious way. We develop two algorithms for posterior inference that feature varying level of trade-off between estimation precision and computational speed. Using monthly data for the euro area, we establish the good empirical properties of the QFAVAR as a tool for assessing the e ects of global shocks on country-level macroeconomic risks. In particular, QFAVAR short-run tail forecasts are more accurate compared to a FAVAR with symmetric Gaussian errors, as well as univariate quantile autoregressions that ignore comovements among quantiles of macroeconomic variables. We also illustrate how quantile impulse response functions and quantile connectedness measures, resulting from the new model, can be used to implemennt joint risk scenario analysis.publishedVersio

Probabilistic quantile factor analysis

This paper extends quantile factor analysis to a probabilistic variant that incorporates regularization and computationally efficient variational approximations. By means of synthetic and real data experiments it is established that the proposed estimator can achieve, in many cases, better accuracy than a recently proposed loss-based estimator. We contribute to the literature on measuring uncertainty by extracting new indexes of low, medium and high economic policy uncertainty, using the probabilistic quantile factor methodology. Medium and high indexes have clear contractionary effects, while the low index is benign for the economy, showing that not all manifestations of uncertainty are the same

A surrogate model for data-driven magnetic stray field calculations

In this contribution we propose a data-driven surrogate model for the prediction of magnetic stray fields in two-dimensional random micro-heterogeneous materials. Since data driven models require thousands of training data sets, FEM simulations appear to be too time consuming. Hence, a stochastic model based on Brownian motion, which utilizes an efficient evaluation of stochastic transition matrices, is applied for the training data generation. For the encoding of the microstructure and the optimization of the surrogate model, two architectures are compared, i.e. the so-called UResNet model and the Fourier Convolutional neural network (FCNN). Here we analyze two FCNNs, one based on the discrete cosine transformation and one based on the complex-valued discrete Fourier transformation. Finally, we compare the magnetic stray fields for independent microstructures (not used in the training set) with results from the FE$^2$ method, a numerical homogenization scheme, to demonstrate the efficiency of the proposed surrogate model

Impaired Autonomic Responses to Emotional Stimuli in Autoimmune Limbic Encephalitis

Limbic encephalitis (LE) is an autoimmune-mediated disorder that affects structures of the limbic system, in particular the amygdala. The amygdala constitutes a brain area substantial for processing of emotional, especially fear-related signals. The amygdala is also involved in neuroendocrine and autonomic functions, including skin conductance responses (SCRs) to emotionally arousing stimuli. This study investigates behavioral and autonomic responses to discrete emotion-evoking and neutral film clips in a patient suffering from LE associated with contactin-associated protein-2 (CASPR2)-antibodies as compared to a healthy control group. Results show a lack of SCRs in the patient while watching the film clips, with significant differences compared to healthy controls in the case of fear-inducing videos. There was no comparable impairment in behavioral data (emotion report, valence and arousal ratings). The results point to a defective modulation of sympathetic responses during emotional stimulation in patients with LE, probably due to impaired functioning of the amygdala

Peer review analysis in the field of radiation oncology: results from a web-based survey of the Young DEGRO working group

PURPOSE To evaluate the reviewing behaviour in the German-speaking countries in order to provide recommendations to increase the attractiveness of reviewing activity in the field of radiation oncology. METHODS In November 2019, a survey was conducted by the Young DEGRO working group (jDEGRO) using the online platform “eSurveyCreator”. The questionnaire consisted of 29 items examining a~broad range of factors that influence reviewing motivation and performance. RESULTS A total of 281 responses were received. Of these, 154 (55%) were completed and included in the evaluation. The most important factors for journal selection criteria and peer review performance in the field of radiation oncology are the scientific background of the manuscript (85%), reputation of the journal (59%) and a~high impact factor (IF; 40%). Reasons for declining an invitation to review include the scientific background of the article (60%), assumed effort (55%) and a low IF (27%). A~double-blind review process is preferred by 70% of respondents to a single-blind (16%) or an open review process (14%). If compensation was offered, 59% of participants would review articles more often. Only 12% of the participants have received compensation for their reviewing activities so far. As compensation for the effort of reviewing, 55% of the respondents would prefer free access to the journal's articles, 45% a discount for their own manuscripts, 40% reduced congress fees and 39% compensation for expenses. CONCLUSION The scientific content of the manuscript, reputation of the journal and a~high IF determine the attractiveness for peer reviewing in the field of radiation oncology. The majority of participants prefer a~double-blind peer review process and would conduct more reviews if compensation was available. Free access to journal articles, discounts for publication costs or congress fees, or an expense allowance were identified to increase attractiveness of the review process

Does the time of the day affect multiple trauma care in hospitals? A retrospective analysis of data from the TraumaRegister DGU®

Results Fewer patients were admitted during the night (6.00 pm-11.59 pm: 18.8% of the patients, 0.00-5.59 am: 4.6% of the patients) than during the day. Patients who arrived between 0.00 am-5.59 am were younger (49.4 ± 22.8 years) and had a higher injury severity score (ISS) (21.4 ± 11.5) and lower Glasgow Coma Scale (GCS) score (11.6 ± 4.4) than those admitted during the day (12.00 pm-05.59 pm; age: 55.3 ± 21.6 years, ISS: 20.6 ± 11.4, GCS: 12.6 ± 4.0). Time in the trauma department and time to an emergency operation were only marginally different. Time to imaging was slightly prolonged during the night (0.00 am-5.59 am: X-ray 16.2 ± 19.8 min; CT scan 24.3 ± 18.1 min versus 12.00 pm- 5.59 pm: X-ray 15.4 ± 19.7 min; CT scan 22.5 ± 17.8 min), but the delay did not affect the outcome. The outcome was also not affected by level of the trauma center. There was no relevant difference in the Revised Injury Severity Classification II (RISC II) score or mortality rate between patients admitted during the day and at night. There were no differences in RISC II scores or mortality rates according to time period. Admission at night was not a predictor of a higher mortality rate. Conclusion The patient population and injury severity vary between the day and night with regard to age, injury pattern and trauma mechanism. Despite the differences in these factors, arrival at night did not have a negative effect on the outcome