Automated Seismic Source Characterisation Using Deep Graph Neural Networks

Most seismological analysis methods require knowledge of the geographic location of the stations comprising a seismic network. However, common machine learning tools used in seismology do not account for this spatial information, and so there is an underutilised potential for improving the performance of machine learning models. In this work, we propose a Graph Neural Network (GNN) approach that explicitly incorporates and leverages spatial information for the task of seismic source characterisation (specifically, location and magnitude estimation), based on multi-station waveform recordings. Even using a modestly-sized GNN, we achieve model prediction accuracy that outperforms methods that are agnostic to station locations. Moreover, the proposed method is flexible to the number of seismic stations included in the analysis, and is invariant to the order in which the stations are arranged, which opens up new applications in the automation of seismological tasks and in earthquake early warning systems

Adsorptie, omzettingssnelheid en transport van carbendazim in twee bloembollengronden

Carbendazim is een fungicide dat diverse toepassingen kent in de bloembollenteelt en dat regelmatig in het oppervlaktewater wordt aangetroffen. Meer inzicht was nodig in de bijdrage van uitspoeling uit de bodem aan de emissie. De adsorptie van carbendazim aan twee bloembollengronden (humusarm zand) was matig. De omzetting bij 10 °C verliep verrassend snel, vermoedelijk door adaptatie van de micro-organismen in de gronden. Het gedrag van carbendazim in de bodem na toediening (begin december) van een restant ontsmettingsvloeistof aan twee bloembollenvelden werd gesimuleerd met het model PESTLA. De berekende concentraties in het drainagewater bleven ver beneden de bepalingsgrens van bijvoorbeeld 0,01 g/dm3. In scenario's met verhoogde bodembelasting, vertraging van de omzetting door een ander fungicide, slechts gedeeltelijke adaptatie, en een minder sterk gekromde adsorptie-isotherm bleef de berekende uitspoeling laag. Gezien de onzekerheden zijn enkele veldmetingen ter controle van de berekende resultaten gewenst. Extrapolatie naar gronden die niet regelmatig worden belast (minder adaptatie) is extra onzeker

How design can improve company performance

Emphasising design and including designers in product development teams contributes to new product success. Likewise, involving designers in developing websites and corporate visual identity helps to improve firm image. When taken together this can contribute to improved company performance. These are the main findings of research conducted in a survey of nearly 400 managers in Dutch firms from both manufacturing and service sectors

Characterizing the fluid-matrix affinity in an organogel from the growth dynamics of oil stains on blotting paper

Grease, as used for lubrication of rolling bearings, is a two-phase organogel that slowly releases oil from its gelator matrix. Because the rate of release determines the operation time of the bearing, we study this release process by measuring the amount of extracted oil as a function of time, while we use absorbing paper, to speed up the process. The oil concentration in the resulting stain is determined by measuring the attenuation of light transmitted through the paper, using a modified Lambert-Beer law. For grease the timescale for paper imbibition is typically 2 orders of magnitude larger than for a bare drop of the same base oil. This difference results from the high affinity, \it i.e. wetting energy per unit volume, of the oil for the grease matrix. To quantify this affinity, we developed a Washburn-like model describing the oil flow from the porous grease into the paper pores. The stain radius versus time curves for greases at various levels of oil content collapse onto a single master curve, which allows us to extract a characteristic spreading time and the corresponding oil-matrix affinity. Lowering the oil content results in a small increase of the oil-matrix affinity yet in a significant change in the spreading timescale. Even an affinity increase by a few per mill doubles the timescale

The relationship between cholesterol crystals, foamy macrophages and haemosiderin in odontogenic cysts

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