Interpreting neural network models for toxicity prediction by extracting learned chemical features

Neural network models have become a popular machine learning technique for toxicity prediction of chemicals. However, due to their complex structure, it is difficult to understand predictions made by these models which limits confidence. Current techniques to tackle this problem such as SHAP or integrated gradients provide insights by attributing importance to input features of individual compounds. While these methods have produced promising results in some cases, they do not shed light on how representations of compounds are transformed in hidden layers, which constitutes how neural networks learn. We present a novel technique to interpret neural networks which identifies chemical substructures in training data found to be responsible for the activation of hidden neurons. For individual test compounds, the importance of hidden neurons is determined, and the associated substructures are leveraged to explain the model prediction. Using structural alerts for mutagenicity from the Derek Nexus expert system as a ground truth, we demonstrate the validity of the approach and show that model explanations in some cases are complementary to explanations obtained from an established feature attribution method

Religious perspectives on the use of psychopharmaceuticals as an enhancement technology

The use of psychopharmaceuticals as an enhancement technology has been the focus of attention in the bioethics literature. However, there has been little examination of the challenges that this practice creates for religious traditions that place importance on questions of being, authenticity and identity. We asked expert commentators from six major world religions to consider the issues raised by psychopharmaceuticals as an enhancement technology. These commentaries reveal that in assessing the appropriate place of medical therapies, religious traditions, like secular perspectives, rely upon ideas about health and disease and about normal human behavior. But unlike secular perspectives, faith traditions explicitly concern themselves with ways in which medicine should or should not be used to live a ‘good life’. KEYWORDS: Enhancement; bioethics, psychopharmacology, religio

Can filesharers be triggered by economic incentives? Results of an experiment

Illegal filesharing on the internet leads to considerable financial losses for artists and copyright owners as well as producers and sellers of music. Thus far, measures to contain this phenomenon have been rather restrictive. However, there are still a considerable number of illegal systems, and users are able to decide quite freely between legal and illegal downloads because the latter are still difficult to sanction. Recent economic approaches account for the improved bargaining position of users. They are based on the idea of revenue-splitting between professional sellers and peers. In order to test such an innovative business model, the study reported in this article carried out an experiment with 100 undergraduate students, forming five small peer-to-peer networks.The networks were confronted with different economic conditions.The results indicate that even experienced filesharers hold favourable attitudes towards revenue-splitting.They seem to be willing to adjust their behaviour to different economic conditions

Derivative corrections to the Born-Infeld action through beta-function calculations in N=2 boundary superspace

We calculate the beta-functions for an open string sigma-model in the presence of a U(1) background. Passing to N=2 boundary superspace, in which the background is fully characterized by a scalar potential, significantly facilitates the calculation. Performing the calculation through three loops yields the equations of motion up to five derivatives on the fieldstrengths, which upon integration gives the bosonic sector of the effective action for a single D-brane in trivial bulk background fields through four derivatives and to all orders in alpha'. Finally, the present calculation shows that demanding ultra-violet finiteness of the non-linear sigma-model can be reformulated as the requirement that the background is a deformed stable holomorphic U(1) bundle.Comment: 25 pages, numerous figure

High-throughput field imaging and basic image analysis in a wheat breeding programme

Visual assessment of colour-based traits plays a key role within field-crop breeding programmes, though the process is subjective and time-consuming. Digital image analysis has previously been investigated as an objective alternative to visual assessment for a limited number of traits, showing suitability and slight improvement to throughput over visual assessment. However, easily adoptable, field-based high-throughput methods are still lacking. The aim of the current study was to produce a high-throughput digital imaging and analysis pipeline for the assessment of colour-based traits within a wheat breeding programme. This was achieved through the steps of (i) a proof-of-concept study demonstrating basic image analysis methods in a greenhouse, (ii) application of these methods to field trials using hand-held imaging, and (iii) developing a field-based high-throughput imaging infrastructure for data collection. The proof of concept study showed a strong correlation (r = 0.95) between visual and digital assessments of wheat physiological yellowing (PY) in a greenhouse environment, with both scores having similar heritability (H2 = 0.85 and 0.76, respectively). Digital assessment of hand-held field images showed strong correlations to visual scores for PY (r = 0.61 and 0.78), senescence (r = 0.74 and 0.75) and Septoria tritici blotch (STB; r = 0.76), with greater heritability of digital scores, excluding STB. Development of the high-throughput imaging infrastructure allowed for images of field plots to be collected at a rate of 7,400 plots per hour. Images of an advanced breeding trial collected with this system were analysed for canopy cover at two time-points, with digital scores correlating strongly to visual scores (r = 0.88 and 0.86) and having similar or greater heritability. This study details how high-throughput digital phenotyping can be applied to colour-based traits within field trials of a wheat breeding programme. It discusses the logistics of implementing such systems with minimal disruption to the programme, provides a detailed methodology for the basic image analysis methods utilized, and has potential for application to other field-crop breeding or research programmes.James Walter, James Edwards, Jinhai Cai, Glenn McDonald, Stanley J. Miklavcic, and Haydn Kuche