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Kijko et al. (2016) present various methods to estimate parameters that are relevant for probabilistic seismic-hazard assessment. One of these parameters, although not the most influential, is the maximum possible earthquake magnitude m(max). I show that the proposed estimation of m(max) is based on an erroneous equation related to a misuse of the estimator in Cooke (1979) and leads to unstable results. So far, reported finite estimations of m(max) arise from data selection, because the estimator in Kijko et al. (2016) diverges with finite probability. This finding is independent of the assumed distribution of earthquake magnitudes. For the specific choice of the doubly truncated Gutenberg-Richter distribution, I illustrate the problems by deriving explicit equations. Finally, I conclude that point estimators are generally not a suitable approach to constrain m(max).
Data limitations can lead to unrealistic fits of predictive species distribution models (SDMs) and spurious extrapolation to novel environments. Here, we want to draw attention to novel combinations of environmental predictors that are within the sampled range of individual predictors but are nevertheless outside the sample space. These tend to be overlooked when visualizing model behaviour. They may be a cause of differing model transferability and environmental change predictions between methods, a problem described in some studies but generally not well understood. We here use a simple simulated data example to illustrate the problem and provide new and complementary visualization techniques to explore model behaviour and predictions to novel environments. We then apply these in a more complex real-world example. Our results underscore the necessity of scrutinizing model fits, ecological theory and environmental novelty.
Domain-specific physical activity patterns and cardiorespiratory fitness among adults in Germany
(2019)
Background Studies show that occupational physical activity (OPA) has less health-enhancing effects than leisure-time physical activity (LTPA). The spare data available suggests that OPA rarely includes aerobic PAs with little or no enhancing effects on cardiorespiratory fitness (CRF) as a possible explanation. This study aims to investigate the associations between patterns of OPA and LTPA and CRF among adults in Germany. Methods 1,204 men and 1,303 women (18-64 years), who participated in the German Health Interview and Examination Survey 2008-2011, completed a standardized sub-maximal cycle ergometer test to estimate maximal oxygen consumption (VO2max). Job positions were coded according to the level of physical effort to construct an occupational PA index and categorized as low vs. high OPA. LTPA was assessed via questionnaires and dichotomized in no vs. any LTPA participation. A combined LTPA/OPA variable was used (high OPA/ LTPA, low OPA/LTPA, high OPA/no LTPA, low OPA/no LTPA). Information on potential confounders was obtained via questionnaires (e.g., smoking and education) or physical measurements (e.g., waist circumference). Multi-variable logistic regression was used to analyze associations between OPA/LTPA patterns and VO2max. Results Preliminary analyses showed that less-active men were more likely to have a low VO2max with odds ratios (ORs) of 0.80 for low OPA/LTPA, 1.84 for high OPA/no LTPA and 3.46 for low OPA/no LTPA compared to high OPA/LTPA. The corresponding ORs for women were 1.11 for low OPA/LTPA, 3.99 for high OPA/no LTPA and 2.44 for low OPA/no LTPA, indicating the highest likelihood of low fitness for women working in physically demanding jobs and not engaging in LTPA. Conclusions Findings confirm a strong association between LTPA and CRF and suggest an interaction between OPA and LTPA patterns on CRF within the workforce in Germany. Women without LTPA are at high risk of having a low CRF, especially if they work in physically demanding jobs. Key messages Women not practicing leisure-time physical activity are at risk of having a low cardiorespiratory fitness, especially if they work in physically demanding jobs. Different impact of domains of physical activity should be considered when planning interventions to enhance fitness among the adult population.
Zero-shot learning in Language & Vision is the task of correctly labelling (or naming) objects of novel categories. Another strand of work in L&V aims at pragmatically informative rather than "correct" object descriptions, e.g. in reference games. We combine these lines of research and model zero-shot reference games, where a speaker needs to successfully refer to a novel object in an image. Inspired by models of "rational speech acts", we extend a neural generator to become a pragmatic speaker reasoning about uncertain object categories. As a result of this reasoning, the generator produces fewer nouns and names of distractor categories as compared to a literal speaker. We show that this conversational strategy for dealing with novel objects often improves communicative success, in terms of resolution accuracy of an automatic listener.