{{ECML} {PKDD} 2020 Workshops - Workshops of the European Conference on Machine Learning and Knowledge Discovery in Databases {(ECML} {PKDD} 2020): SoGood 2020, {PDFL} 2020, {MLCS} 2020, {NFMCP} 2020, {DINA} 2020, {EDML} 2020, {XKDD} 2020 and {INRA} 2020, Ghent, Belgium, September 14-18, 2020, Proceedings

Proceedings of ECML-PKDD workshop

{Search for direct production of GeV-scale resonances decaying to a pair of muons in proton-proton collisions at s \sqrt{s} = 13 TeV}

A search for direct production of low-mass dimuon resonances is performed using = 13 TeV proton-proton collision data collected by the CMS experiment during the 2017–2018 operation of the CERN LHC with an integrated luminosity of 96.6 fb−1. The search exploits a dedicated high-rate trigger stream that records events with two muons with transverse momenta as low as 3 GeV but does not include the full event information. The search is performed by looking for narrow peaks in the dimuon mass spectrum in the ranges of 1.1–2.6 GeV and 4.2–7.9 GeV. No significant excess of events above the expectation from the standard model background is observed. Model-independent limits on production rates of dimuon resonances within the experimental fiducial acceptance are set. Competitive or world’s best limits are set at 90% confidence level for a minimal dark photon model and for a scenario with two Higgs doublets and an extra complex scalar singlet (2HDM+S). Values of the squared kinetic mixing coefficient ε2 in the dark photon model above 10−6 are excluded over most of the mass range of the search. In the 2HDM+S, values of the mixing angle sin(θH) above 0.08 are excluded over most of the mass range of the search with a fixed ratio of the Higgs doublets vacuum expectation tan β = 0.5

The relationship between concentration of specific antibody at birth and subsequent response to primary immunization

Background and aims: Trans-placentally acquired antibodies can protect infants from infection in the first months of life. However, high concentrations of antibody at birth may impact the infant's own immune response to primary immunization. We examine the relationship between concentration of specific antibody to Bordetella pertussis, Haemophilus influenzae type b (Hib), tetanus toxoid and pneumococcal antigens at birth and following primary immunization. Methods: Healthy mother-infant pairs were recruited from a UK maternity unit. Peripheral blood samples were obtained at birth and 4 weeks after primary immunization. Specific antibody concentrations were determined using enzyme-linked immunosorbent assays. Pertussis antibody concentrations >50. IU/ml, Tetanus antibody levels >0.1. IU/ml and Hib antibody levels >0.15. mg/l were regarded as protective. Results: Following primary immunization, 35/36 (97%) infants had specific antibody concentrations associated with protection against Hib, 32/36 (89%) against pertussis and 36/36 (100%) against tetanus. Concentrations of all specific antibodies were significantly higher than at birth (p<0.0001), except anti-tetanus toxoid, p=0.41. However, there was an inverse correlation between infant antibody concentration at birth and fold-increase in antibody concentration post-immunization for tetanus: rs -0.86 (95%CI -0.93 to -0.74), p<0.0001; pneumococcus: rs -0.82 (95% CI -0.91 to -0.67), p<0.0001; pertussis: rs -0.77 (95% CI -0.89 to -0.58), p<0.0001 and Hib: rs -0.66 (95%CI -0.82 to -0.42), p<0.0001. The highest concentrations of specific IgG at birth were associated with lower concentrations post-immunization for tetanus (p=0.009) and pneumococcus (p=0.03). This association was not observed for Hib (p=0.88) or pertussis (p=0.14). Conclusion: Higher antibody concentration at birth appeared to inhibit the response to infant immunization for tetanus and pneumococcus; the effect was less marked for Hib and pertussis. However, the majority of infants achieved high antibody levels post-immunization. This supports maternal immunization, as high levels of maternally derived antibody at birth may not inhibit infants' immunization responses in a clinically relevant manner

Collaborative Speculations on Future Themes for Participatory Design in Germany

Participatory Design means recognizing that those who will be affected by a future technology should have an active say in its creation. Yet, despite continuous interest in involving people as future users and consumers into designing novel and innovative future technology, participatory approaches in technology design remain relatively underdeveloped in the German HCI community. This article brings together the diversity of voices, domains, perspectives, approaches, and methods that collectively shape Participatory Design in Germany. In the following, we (1) outline our understanding of participatory practice and how it is different from mere user involvement; (2) reflect current issues of participatory and fair technology design within the German Participatory Design community; and (3) discuss tensions relevant to the field, that we expect to arise in the future, and which we derived from our 2021 workshop through a speculative method. We contribute an introduction and an overview of current themes and a speculative outlook on future issues of Participatory Design in Germany. It is meant to inform, provoke, inspire and, ultimately, invite participation within the wider Computer Science community

Heimat in the Veld?

the depiction of Germans abroad by Stefan Manz as “extremely heterogeneous groups or individuals” is as applicable to South Africa as anywhere else. So is the apparent contradiction of self-proclaimed ‘Germanness’ alongside significant evidence of German- South Africans’ successful integration into local society. Keeping in mind, as Joan W. Scott summarises it, that identities are ascribed, embraced and rejected in complex discursive processes, and accepting the notion of culture as performance, I attempt to illustrate in this study how actors who would have been ascribed a ‘Germanness’ in South Africa in the first half of the twentieth century embodied different roles - at particular moments in time, as well as over time. I find the term “occasionalism”, coined by cultural historian Peter Burke, very productive: “on different occasions (moments, locales) or in different situations (in the presence of different people) the same person behaves in different ways.”http://www.vr-elibrary.de/loi/gegehb2016Visual Art

The initiation of cannabis use in adolescence is predicted by sex‐specific psychosocial and neurobiological features

Abstract Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants ( n  = 1,581) were cannabis‐naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group ( N  = 365, males n  = 207). Cannabis‐naïve participants at age 14 and 16 were included in the comparison group ( N  = 1,216, males n  = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross‐validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex‐ and drug‐specificity using post‐hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same‐sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex‐specific brain prognostic markers, which were likely to precede and influence cannabis initiation.National Institute of General Medical Sciences https://doi.org/10.13039/100000057Medical Research Council https://doi.org/10.13039/501100000265Wellcome Trust https://doi.org/10.13039/100004440National Institute for Health Research https://doi.org/10.13039/501100000272King’s College London https://doi.org/10.13039/100009360Bundesministerium für Bildung und Forschung https://doi.org/10.13039/501100002347Deutsche Forschungsgemeinschaft https://doi.org/10.13039/501100001659National Institute of Mental Health https://doi.org/10.13039/100000025National Institutes of Health https://doi.org/10.13039/100000002Bundesministerium für Bildung und Forschung https://doi.org/10.13039/50110000234

A community effort to optimize sequence-based deep learning models of gene regulation

A systematic evaluation of how model architectures and training strategies impact genomics model performance is needed. To address this gap, we held a DREAM Challenge where competitors trained models on a dataset of millions of random promoter DNA sequences and corresponding expression levels, experimentally determined in yeast. For a robust evaluation of the models, we designed a comprehensive suite of benchmarks encompassing various sequence types. All top-performing models used neural networks but diverged in architectures and training strategies. To dissect how architectural and training choices impact performance, we developed the Prix Fixe framework to divide models into modular building blocks. We tested all possible combinations for the top three models, further improving their performance. The DREAM Challenge models not only achieved state-of-the-art results on our comprehensive yeast dataset but also consistently surpassed existing benchmarks on Drosophila and human genomic datasets, demonstrating the progress that can be driven by gold-standard genomics datasets.</p