Testing the Potential of Deep Learning in Earthquake Forecasting

Reliable earthquake forecasting methods have long been sought after, and so the rise of modern data science techniques raises a new question: does deep learning have the potential to learn this pattern? In this study, we leverage the large amount of earthquakes reported via good seismic station coverage in the subduction zone of Japan. We pose earthquake forecasting as a classification problem and train a Deep Learning Network to decide, whether a timeseries of length greater than 2 years will end in an earthquake on the following day with magnitude greater than 5 or not. Our method is based on spatiotemporal b value data, on which we train an autoencoder to learn the normal seismic behaviour. We then take the pixel by pixel reconstruction error as input for a Convolutional Dilated Network classifier, whose model output could serve for earthquake forecasting. We develop a special progressive training method for this model to mimic real life use. The trained network is then evaluated over the actual dataseries of Japan from 2002 to 2020 to simulate a real life application scenario. The overall accuracy of the model is 72.3 percent. The accuracy of this classification is significantly above the baseline and can likely be improved with more data in the futur

Floresta Ombrófila Densa Altomontana: aspectos florísticos e estruturais de diferentes trechos na Serra do Mar, PR.

The floristic and the structure of the Upper Montane Rain Forest, on five different mountains, along Serra do Mar, PR, were evaluated. Primary fragments, always above 1.250 m above sea level, were measured, with 10 rectangular samples (5 x 10m) (GBH > 10 cm) for each site. There were registered 55 species (36 gen., 24 fam.). Including other author’s data, it was possible to reveal that Ilex microdonta is the most important species, followed by Drimys brasiliensis, Ocotea catharinensis, Blepharocalyx salicifolius and Gordonia fruticosa. It was observed the high arborous density, with more than 4.490 trees per hectare, which configures a single stratum, and medium height of 4 m. On cluster analysis the best results were obtained by using the Importance Value. The minor stand similarity was registered among the sites on “morro do Araçatuba” (1.610 m) and “morro do Vigia” (1.280 m), indicating that the altitude factor has a powerful influence on this aspect. Although the Jaccard´s index for all the sites revealed that despite of the structure significant differences, in relation to the floristic all of these were considered similar.Foram avaliadas a florística e a estrutura da Floresta Ombrófila Densa Altomontana, em cinco diferentes montanhas, ao longo da Serra do Mar, PR. Trechos primários, sempre acima dos 1.250 m, foram mensurados, com dez parcelas retangulares (5x10 m), em cada local. Foram registradas 55 espécies arbóreas, 36 gêneros e 24 famílias. Incluíndo dados de outros autores, foi possível revelar que Ilex microdonta é a espécie mais importante, seguida por Drimys brasiliensis, Ocotea catharinensis, Blepharocalyx salicifolius e Gordonia fruticosa. Constatou-se a elevada densidade arbórea, até 4.490 árvores por hectare (PAP > 10 cm), formando um estrato único, com altura média de 4 m. Na análise de agrupamentos, os melhores resultados foram obtidos adotando-se a variável Valor de Importância. A menor similaridade estrutural foi registrada entre os trechos dos morros Araçatuba (1.610 m s.n.m.) e Vigia (1.280 m s.n.m.), indicando que o fator altitude exerce grande influência nesse aspecto. Contudo, verificou-se, com base no índice de Jaccard, que, floristicamente, todos os trechos são similares, embora ocorram diferenças estruturais importantes entre eles

SAIPy: A Python Package for single station Earthquake Monitoring using Deep Learning

Seismology has witnessed significant advancements in recent years with the application of deep learning methods to address a broad range of problems. These techniques have demonstrated their remarkable ability to effectively extract statistical properties from extensive datasets, surpassing the capabilities of traditional approaches to an extent. In this study, we present SAIPy, an open source Python package specifically developed for fast data processing by implementing deep learning. SAIPy offers solutions for multiple seismological tasks, including earthquake detection, magnitude estimation, seismic phase picking, and polarity identification. We introduce upgraded versions of previously published models such as CREIMERT capable of identifying earthquakes with an accuracy above 99.8 percent and a root mean squared error of 0.38 unit in magnitude estimation. These upgraded models outperform state of the art approaches like the Vision Transformer network. SAIPy provides an API that simplifies the integration of these advanced models, including CREIMERT, DynaPickerv2, and PolarCAP, along with benchmark datasets. The package has the potential to be used for real time earthquake monitoring to enable timely actions to mitigate the impact of seismic events. Ongoing development efforts aim to enhance the performance of SAIPy and incorporate additional features that enhance exploration efforts, and it also would be interesting to approach the retraining of the whole package as a multi-task learning problem

Floristic cluster analysis in Araucaria Forest System Faxinal

Abstract This study aimed to generate floristic groups of trees in a fragment of Araucaria forest and determine the floristic associations and evaluate the horizontal structure and the floristic diversity of each formed group. The data were obtained from an experiment implemented in Faxinal Marmeleiros de Baixo locality in Rebouças - Parana. In an area of 509 ha, were installed 50 permanent sample plots of 500 m² (10 mx 50 m), distributed in a systematic way, where each individual tree with DBH less than 10 cm was measured and identified. Using multivariate analysis, the sample units with similarity in diversity indices for its species were grouped using cluster analysis. We obtained two floristic groups: Group 1, involving 38 sample units representing 64% of the area; Group 2, with 12 sample units representing 36% of the area. Through to sociological analysis were identified the species with the highest VI in each group, which were Curitiba prismatic (Group 1), Campomanesia xanthocarpa (Group 2). Group 1, present high number of species and most dominant, while group 2 has a higher species richness and most divercidade. Este estudo teve como objetivos gerar grupos florísticos da vegetação arbórea de um fragmento de Floresta Ombrófila Mista e determinar as associações florísticas e avaliar a estrutura horizontal e a diversidade florística de cada grupo formado. Os dados foram obtidos de um experimento implantado na localidade Faxinal Marmeleiros de Baixo, em Rebouças – Paraná. Em uma área de 509 ha, foram instaladas 50 unidades amostrais permanentes de 500 m² (10 m x 50 m), distribuídas de forma sistemática, onde cada indivíduo arbóreo com DAP igual ou superior a 10 cm foi medido e identificado. Utilizando técnicas de análise multivariada, as unidades amostrais com similaridade nos índices de diversidade de suas espécies foram agrupadas usando a análise de agrupamento. Foram obtidos 2 grupos florísticos: Grupo 1, envolvendo 38 unidades amostrais representando 64% da área; Grupo 2, com 12 unidades amostrais representando 36% da área. Por meio de análise fitossociológica foram identificadas, as espécies com maior VI em cada grupo, as quais foram Curitiba prismatica (Grupo 1), Campomanesia xanthocarpa (Grupo 2). O Grupo 1, apresentoumaior número de espécies e maior dominância, enquanto que o grupo 2 apresenta maior riqueza de espécies e maior divercidade.ResumenEste estudio tuvo como objetivo generar grupos florísticos de loa vegetación arbórea en un fragmento del bosque Ombrófila mista y determinar las asociaciones florísticas y evaluar la estructura horizontal y la diversidad florística de cada grupo formado. Los datos fueran obtenidos de un experimento conducido en la localidad de Faxinal Marmeleiros de baixo, Rebouças - Paraná. En un área de 509 hectáreas, se instaló 50 parcelas permanentes de 500 m² (10 m x 50 m), distribuidos de manera sistemática, donde cada individuo arbóreo con DAP igual o superior a 10 cm fue medido y identificado. Utilizando el análisis multivariado, se agruparon las unidades de muestreo con similitud en los índices de diversidad de sus especies mediante análisis de agrupamiento. Se obtuvieron 2 grupos florísticos: Grupo 1, con 38 unidades que representan el 64% del área; Grupo 2 con 12 unidades que representan 36% del área. A través de análisis fitosociológico se identificaron la especie con el mayor VI en cada grupo, las cuales fueran Curitiba prismática (Grupo 1), Campomanesia xanthocarpa (Grupo 2). El Grupo 1, presentó mayor número de especies y mayor predominio, mientras que el grupo 2 presenta una mayor riqueza de especies y superior diversidad.

Training in infectious diseases across Europe in 2021 - a survey on training delivery, content and assessment

Objectives: To define the status of infectious diseases (ID) as an approved specialty in Europe; to enumerate the number of specialists (in general and in relation to the overall population) and specialist trainees and describe the content, delivery and evaluation of postgraduate training in ID in different countries.Methods: Structured web-based questionnaire surveys in March 2021 of responsible national authorities, specialist societies and individual country representatives to the Section of Infectious Diseases of the European Union for Medical Specialties. Descriptive analysis of quantitative and qualitative responses.Results: In responses received from 33/35 (94.3%) countries, ID is recognized as a specialty in 24 and as a subspecialty of general internal medicine (GIM) in eight, but it is not recognized in Spain. The number of ID specialists per country varies from <5 per million inhabitants to 78 per million inhabitants. Median length of training is 5 years (interquartile range 4.0–6.0 years) with variable amounts of preceding and/or concurrent GIM. Only 21.2% of countries (7/33) provide the minimum recommended training of 6 months in microbiology and 30% cover competencies such as palliative care, team working and leadership, audit, and quality control. Training is monitored by personal logbook or e-portfolio in 75.8% (25/33) and assessed by final examinations in 69.7% (23/33) of countries, but yearly reviews with trainees only occur in 54.5% (18/33) of countries.Conclusions: There are substantial gaps in modernization of ID training in many countries to match current European training requirements. Joint training with clinical microbiology (CM) and in multidisciplinary team working should be extended. Training/monitoring trainers should find greater focus, together with regular feedback to trainees within many national training programmes.peer-reviewe

Global baryon number conservation encoded in net-proton fluctuations measured in Pb–Pb collisions at √sNN = 2.76 TeV

Experimental results are presented on event-by-event net-proton fluctuation measurements in Pb–Pb collisions at √SNN=2.76 TeV, recorded by the ALICE detector at the CERN LHC. These measurements have as their ultimate goal an experimental test of Lattice QCD (LQCD) predictions on second and higher order cumulants of net-baryon distributions to search for critical behavior near the QCD phase boundary. Before confronting them with LQCD predictions, account has to be taken of correlations stemming from baryon number conservation as well as fluctuations of participating nucleons. Both effects influence the experimental measurements and are usually not considered in theoretical calculations. For the first time, it is shown that event-by-event baryon number conservation leads to subtle long-range correlations arising from very early interactions in the collisions.publishedVersio

Pion-kaon femtoscopy and the lifetime of the hadronic phase in Pb-Pb collisions at root(S)(NN)=2.76 TeV

In this paper, the first femtoscopic analysis of pion-kaon correlations at the LHC is reported. The analysis was performed on the Pb-Pb collision data at root(S)(NN) = 2.76 TeV recorded with the ALICE detector. The non-identical particle correlations probe the spatio-temporal separation between sources of different particle species as well as the average source size of the emitting system. The sizes of the pion and kaon sources increase with centrality, and pions are emitted closer to the centre of the system and/or later than kaons. This is naturally expected in a system with strong radial flow and is qualitatively reproduced by hydrodynamic models. ALICE data on pion-kaon emission asymmetry are consistent with (3+1)-dimensional viscous hydrodynamics coupled to a statistical hadronisation model, resonance propagation, and decay code THERMINATOR 2 calculation, with an additional time delay between 1 and 2 fm/c for kaons. The delay can be interpreted as evidence for a significant hadronic rescattering phase in heavy-ion collisions at the LHC. (C) 2020 The Author. Published by Elsevier B.V.Peer reviewe