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

A comparison between rate-and-state friction and microphysical models, based on numerical simulations of fault slip

Rate-and-state friction (RSF) is commonly used for the characterisation of laboratory friction experiments, such as velocity-step tests. However, the RSF framework provides little physical basis for the extrapolation of these results to the scales and conditions of natural fault systems, and so open questions remain regarding the applicability of the experimentally obtained RSF parameters for predicting seismic cycle transients. As an alternative to classical RSF, microphysics-based models offer means for interpreting laboratory and field observations, but are generally over-simplified with respect to heterogeneous natural systems. In order to bridge the temporal and spatial gap between the laboratory and nature, we have implemented existing microphysical model formulations into an earthquake cycle simulator. Through this numerical framework, we make a direct comparison between simulations exhibiting RSF-controlled fault rheology, and simulations in which the fault rheology is dictated by the microphysical model. Even though the input parameters for the RSF simulation are directly derived from the microphysical model, the microphysics-based simulations produce significantly smaller seismic event sizes than the RSF-based simulation, and suggest a more stable fault slip behaviour. Our results reveal fundamental limitations in using classical rate-and-state friction for the extrapolation of laboratory results. The microphysics-based approach offers a more complete framework in this respect, and may be used for a more detailed study of the seismic cycle in relation to material properties and fault zone pressure-temperature conditions

Cloning and functional characterization of a fructan 1-exohydrolase (1-FEH) in edible burdock (Arctium lappa L.)

<p>Abstract</p> <p>Background</p> <p>We have previously reported on the variation of total fructooligosaccharides (FOS), total inulooligosaccharides (IOS) and inulin in the roots of burdock stored at different temperatures. During storage at 0°C, an increase of FOS as a result of the hydrolysis of inulin was observed. Moreover, we suggested that an increase of IOS would likely be due to the synthesis of the IOS by fructosyltransfer from 1-kestose to accumulated fructose and elongated fructose oligomers which can act as acceptors for fructan:fructan 1-fructosyltransferase (1-FFT). However, enzymes such as inulinase or fructan 1-exohydorolase (1-FEH) involved in inulin degradation in burdock roots are still not known. Here, we report the isolation and functional analysis of a gene encoding burdock 1-FEH.</p> <p>Results</p> <p>A cDNA, named <it>aleh1</it>, was obtained by the RACE method following PCR with degenerate primers designed based on amino-acid sequences of FEHs from other plants. The <it>aleh1 </it>encoded a polypeptide of 581 amino acids. The relative molecular mass and isoelectric point (<it>pI</it>) of the deduced polypeptide were calculated to be 65,666 and 4.86. A recombinant protein of <it>aleh1 </it>was produced in <it>Pichia pastoris</it>, and was purified by ion exchange chromatography with DEAE-Sepharose CL-6B, hydrophobic chromatography with Toyopearl HW55S and gel filtration chromatography with Toyopearl HW55S. Purified recombinant protein showed hydrolyzing activity against β-2, 1 type fructans such as 1-kestose, nystose, fructosylnystose and inulin. On the other hand, sucrose, neokestose, 6-kestose and high DP levan were poor substrates.</p> <p>The purified recombinant protein released fructose from sugars extracted from burdock roots. These results indicated that <it>aleh1 </it>encoded 1-FEH.</p

A comparison between rate-and-state friction and microphysical models, based on numerical simulations of fault slip

Rate-and-state friction (RSF) is commonly used for the characterisation of laboratory friction experiments, such as velocity-step tests. However, the RSF framework provides little physical basis for the extrapolation of these results to the scales and conditions of natural fault systems, and so open questions remain regarding the applicability of the experimentally obtained RSF parameters for predicting seismic cycle transients. As an alternative to classical RSF, microphysics-based models offer means for interpreting laboratory and field observations, but are generally over-simplified with respect to heterogeneous natural systems. In order to bridge the temporal and spatial gap between the laboratory and nature, we have implemented existing microphysical model formulations into an earthquake cycle simulator. Through this numerical framework, we make a direct comparison between simulations exhibiting RSF-controlled fault rheology, and simulations in which the fault rheology is dictated by the microphysical model. Even though the input parameters for the RSF simulation are directly derived from the microphysical model, the microphysics-based simulations produce significantly smaller seismic event sizes than the RSF-based simulation, and suggest a more stable fault slip behaviour. Our results reveal fundamental limitations in using classical rate-and-state friction for the extrapolation of laboratory results. The microphysics-based approach offers a more complete framework in this respect, and may be used for a more detailed study of the seismic cycle in relation to material properties and fault zone pressure-temperature conditions

Are entrepreneurs' forecasts of economic indicators biased?

Insight into the investment behaviour of firms is central in understanding economic dynamics. A critical question, however, is whether firms provide sufficiently reliable data to enable them to make plausible forecasts at the meso (regional or sectoral) level. This paper analyses Dutch investment forecasts at different levels of aggregation. The central research question is whether entrepreneurs, individually or as a group, make systematic errors in their investment forecasts. A statistical test reveals that investment forecasts are not biased at the aggregated (regional and sectoral) level. At the micro level, however, there is a significant bias. Hence, using aggregated (regional and sectoral) data to test the lack of bias (unbiasedness) of forecasts may lead to the wrong conclusions. Moreover, aggregated investment forecasts may then be an inappropriate source for policy recommendations, despite their seemingly high reliability. This finding may in principle be valid for many European countries, since data collection on investment is organized in similar ways throughout Europe

Towards a better understanding of the generation of fructan structure diversity in plants: molecular and functional characterization of a sucrose:fructan 6-fructosyltransferase (6-SFT) cDNA from perennial ryegrass (Lolium perenne)

The main storage compounds in Lolium perenne are fructans with prevailing β(2–6) linkages. A cDNA library of L. perenne was screened using Poa secunda sucrose:fructan 6-fructosyltransferase (6-SFT) as a probe. A full-length Lp6-SFT clone was isolated as shown by heterologous expression in Pichia pastoris. High levels of Lp6-SFT transcription were found in the growth zone of elongating leaves and in mature leaf sheaths where fructans are synthesized. Upon fructan synthesis induction, Lp6-SFT transcription was high in mature leaf blades but with no concomitant accumulation of fructans. In vitro studies with the recombinant Lp6-SFT protein showed that both 1-kestotriose and 6G-kestotriose acted as fructosyl acceptors, producing 1- and 6-kestotetraose (bifurcose) and 6G,6-kestotetraose, respectively. Interestingly, bifurcose formation ceased and 6G,6-kestotetraose was formed instead, when recombinant fructan:fructan 6G-fructosyltransferase (6G-FFT) of L. perenne was introduced in the enzyme assay with sucrose and 1-kestotriose as substrates. The remarkable absence of bifurcose in L. perenne tissues might be explained by a higher affinity of 6G-FFT, as compared with 6-SFT, for 1-kestotriose, which is the first fructan formed. Surprisingly, recombinant 6-SFT from Hordeum vulgare, a plant devoid of fructans with internal glucosyl residues, also produced 6G,6-kestotetraose from sucrose and 6G-kestotriose. In the presence of recombinant L. perenne 6G-FFT, it produced 6G,6-kestotetraose from 1-kestotriose and sucrose, like L. perenne 6-SFT. Thus, we demonstrate that the two 6-SFTs have close catalytic properties and that the distinct fructans formed in L. perenne and H. vulgare can be explained by the presence of 6G-FFT activity in L. perenne and its absence in H. vulgare