On the Parameterized Complexity of Learning Monadic Second-Order Formulas

Within the model-theoretic framework for supervised learning introduced by Grohe and Tur\'an (TOCS 2004), we study the parameterized complexity of learning concepts definable in monadic second-order logic (MSO). We show that the problem of learning a consistent MSO-formula is fixed-parameter tractable on structures of bounded tree-width and on graphs of bounded clique-width in the 1-dimensional case, that is, if the instances are single vertices (and not tuples of vertices). This generalizes previous results on strings and on trees. Moreover, in the agnostic PAC-learning setting, we show that the result also holds in higher dimensions. Finally, via a reduction to the MSO-model-checking problem, we show that learning a consistent MSO-formula is para-NP-hard on general structures

inD Dataset Python Tools

The goal of this repo is to make the inD dataset as easy to use as possible. For this purpose we provide source code in Python, which allows the import and visualization of the dataset

Impact of the COVID-19 pandemic on cardiovascular mortality and catherization activity during the lockdown in central Germany: an observational study

Aims!#!During the COVID-19 pandemic, hospital admissions for cardiac care have declined. However, effects on mortality are unclear. Thus, we sought to evaluate the impact of the lockdown period in central Germany on overall and cardiovascular deaths. Simultaneously we looked at catheterization activities in the same region.!##!Methods and results!#!Data from 22 of 24 public health-authorities in central Germany were aggregated during the pandemic related lockdown period and compared to the same time period in 2019. Information on the total number of deaths and causes of death, including cardiovascular mortality, were collected. Additionally, we compared rates of hospitalization (n = 5178) for chronic coronary syndrome (CCS), acute coronary syndrome (ACS), and out of hospital cardiac arrest (OHCA) in 26 hospitals in this area. Data on 5,984 deaths occurring between March 23, 2020 and April 26, 2020 were evaluated. In comparison to the reference non-pandemic period in 2019 (deaths: n = 5832), there was a non-significant increase in all-cause mortality of 2.6% [incidence rate ratio (IRR) 1.03, 95% confidence interval (CI) 0.99-1.06; p = 0.16]. Cardiovascular and cardiac mortality increased significantly by 7.6% (IRR 1.08, 95%-CI 1.01-1.14; p = 0.02) and by 11.8% (IRR 1.12, 95%-CI 1.05-1.19; p < 0.001), respectively. During the same period, our data revealed a drop in cardiac catherization procedures.!##!Conclusion!#!During the COVID-19-related lockdown a significant increase in cardiovascular mortality was observed in central Germany, whereas catherization activities were reduced. The mechanisms underlying both of these observations should be investigated further in order to better understand the effects of a pandemic-related lockdown and social-distancing restrictions on cardiovascular care and mortality