We review previous approaches to nowcasting earthquakes and introduce new based on deep learning using three distinct models recurrent neural networks transformers. discuss different choices for observables measures presenting promising initial results a region of Southern California from 1950–2020. Earthquake activity is predicted as function 0.1-degree spatial bins time periods varying two we...

A large number of 2D models were originally developed as 1D for the calculation water levels along main course a river. Due to their development distributed models, majority have added precipitation source term. The can now be used quasi-2D hydrodynamic rainfall–runoff (‘HDRRM’). Within direct rainfall method (‘DRM’), there is an approach, referred ‘rain-on-grid’, in which input applied entire ...

This article reviews diagnostic criteria for nonalcoholic steatohepatitis (NASH), current grading and staging methodology, and diagnostic challenges and pitfalls in routine practice. Current practice guidelines and prognostic and treatment considerations are discussed. The clinical diagnosis of nonalcoholic fatty liver disease may represent stable disease without progressive liver damage, in th...

We pose the problem of computing approximate Nash equilibria in bimatrix games with two simultaneous criteria of optimization: minimization of the incentives to deviate from a strategy profile and maximization of a measure of quality of the strategy profile. We consider two natural measures of quality: the maximum and the minimum of the payoffs of the two players. Maximizing the former yields p...

Based on observed precipitation and runoff data, the monthly actual evapotranspiration (ETa) was calculated using hydrological budget balance method in three parallel river basins. The performance of complementary relationship methods, namely, nonlinear advection-aridity (non-AA) method, generalized (B2015), sigmoid function (H2018), for simulating ETa evaluated. evaluation results showed that ...

Abstract. Long short-term memory (LSTM) models are recurrent neural networks from the field of deep learning (DL) which have shown promise for time series modelling, especially in conditions when data abundant. Previous studies demonstrated applicability LSTM-based rainfall–runoff modelling; however, LSTMs not been tested on catchments Great Britain (GB). Moreover, opportunities exist to use sp...

background: nonalcoholic steatohepatitis (nash), a progressive stage of nonalcoholic fatty liver disease (nafld), is characterized by steatosis with inflammation. investigations have suggested that oxidative stress may play an important role in the progress of nafld to nash. to provide further insights into beneficial effects of antioxidants in nash prevention, we employed two manganese-superox...