Fast Simulation of 2.5D LWD Resistivity Tools

As a first step towards the fast inversion of geophysical data, in this work we focus on the rapid simulations of 2.5D logging-while-drilling (LWD) borehole resistivity measurements. Given a commercial logging instrument configuration, we calibrate the FE method offline with respect to (i) the element sizes via non-uniform tensor product grids; (ii) the arbitrary polynomial order of approximation on each element; and (iii) the interpolation of certain Fourier modes. This leads to the design of proper FE discretizations to simulate measurements acquired in an arbitrary 2D formation.Numerical results show that we accurately simulate on a sequential computer any field component at a rate faster than one second per logging position.The Marie Sklodowska-Curie grant agreement No 644602 MTM2013-40824-P SEV-2013-0323 BERC 2014-201

Source time reversal (STR) method for linear elasticity

We study the problem of source reconstruction for a linear elasticity problem applied to seismicity induced by mining. We assume the source is written as a variable separable function $\mathbf{f(x)}\>g(t)$ . We first present a simple proof a local decay result for elasticity in the case of homogeneous media. We then extend the source time reversal method, originally developed for acoustic waves, to an elastic system of waves. Additionally, we present a fast reconstruction implementation for large data sets. This is especially useful in the elastic case, in which the numerical cost is higher than in fluid acoustics. We complement this work with several 2D and 3D numerical experiments and an analysis of the resultsThis work was partially supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant No 644602 GEAGAM (Spain) and CONICYT, Chile - PIA/Concurso de Apoyo a Centros Científicos y Tecnológicos de Excelencia con Financiamiento Basal AFB170001. Additionally, the first author was supported by CONICYT Doctoral fellowship number (Chile), Fondecyt11161033 (Chile), ICMP09-015-F (Chile), and EQM140119. Jaime H. Ortega was partially supported by Fondecyt1111012 and 1171854 (Chile). Ángel Rodríguez-Rozas and David Pardo were partially funded by the Projects of the Spanish Ministry of Economy and Competitiveness with reference MTM2016-76329-R (AEI/FEDER, EU) and MTM2016-81697-ERC/AEI, the BCAM “Severo Ochoa” accreditation of excellence SEV-2017-0718, the Basque Government through the BERC 2018-2021 program, the Consolidated Research Group Grant IT649-13 on “Mathematical Modeling, Simulation, and Industrial Applications (M2SI)”. David Pardo has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 777778

Goal-Oriented p-Adaptivity using Unconventional Error Representations for a 1D Steady State Convection-Diffusion Problem

This work proposes the use of an alternative error representation for Goal-Oriented Adaptivity (GOA) in context of steady state convection dominated diffusion problems. It introduces an arbitrary operator for the computation of the error of an alternative dual problem. From the new representation, we derive element-wise estimators to drive the adaptive algorithm. The method is applied to a one dimensional (1D) steady state convection dominated diffusion problem with homogeneous Dirichlet boundary conditions. This problem exhibits a boundary layer that produces a loss of numerical stability. The new error representation delivers sharper error bounds. When applied to a $p$-GOA Finite Element Method (FEM), the alternative error representation captures earlier the boundary layer, despite the existing spurious numerical oscillations.Basque Government Consolidated Research Group Grant IT649-13 Spanish Ministry under Grant No. FPDI- 2013-17098 ICERMAR Project KK-2015/0000097 CYTED 2011 project 712RT0449 FONDECYT project 116077

Memory-Based Monte Carlo Integration for Solving Partial Differential Equations Using Neural Networks

Monte Carlo integration is a widely used quadrature rule to solve Partial Differential Equations with neural networks due to its ability to guarantee overfitting-free solutions and high-dimensional scalability. However, this stochastic method produces noisy losses and gradients during training, which hinders a proper convergence diagnosis. Typically, this is overcome using an immense (disproportionate) amount of integration points, which deteriorates the training performance. This work proposes a memory-based Monte Carlo integration method that produces accurate integral approximations without requiring the high computational costs of processing large samples during training

Ab initio study of the influence of nanoscale doping inhomogeneities in the phase separated state of La1−x_{1-x}Cax_{x}MnO3_3

The chemical influence in the phase separation phenomenon that occurs in perovskite manganites is discussed by means of ab initio calculations. Supercells have been used to simulate a phase separated state, that occurs at Ca concentrations close to the localized to itinerant crossover. We have first considered a model with two types of magnetic ordering coexisting within the same compound. This is not stable. However, a non-isotropic distribution of chemical dopants is found to be the ground state. This leads to regions in the system with different effective concentrations, that would always accompany the magnetic phase separation at the same nanometric scale, with hole-rich regions being more ferromagnetic in character and hole-poor regions being in the antiferromagnetic region of the phase diagram, as long as the system is close to a phase crossover.Comment: 8 pages, 7 figures, 1 tabl

Automated semantic annotation of rare disease cases: a case study

MOTIVATION: As the number of clinical reports in the peer-reviewed medical literature keeps growing, there is an increasing need for online search tools to find and analyze publications on patients with similar clinical characteristics. This problem is especially critical and challenging for rare diseases, where publications of large series are scarce. Through an applied example, we illustrate how to automatically identify new relevant cases and semantically annotate the relevant literature about patient case reports to capture the phenotype of a rare disease named cerebrotendinous xanthomatosis. RESULTS: Our results confirm that it is possible to automatically identify new relevant case reports with a high precision and to annotate them with a satisfactory quality (74% F-measure). Automated annotation with an emphasis to entirely describe all phenotypic abnormalities found in a disease may facilitate curation efforts by supplying phenotype retrieval and assessment of their frequency. Availability and Supplementary information: http://www.usc.es/keam/Phenotype Annotation/. Database URL: http://www.usc.es/keam/PhenotypeAnnotation

Goal-oriented adaptivity using unconventional error representations for the multi-dimensional Helmholtz equation

In goal‐oriented adaptivity, the error in the quantity of interest is represented using the error functions of the direct and adjoint problems. This error representation is subsequently bounded above by element‐wise error indicators that are used to drive optimal refinements. In this work, we propose to replace, in the error representation, the adjoint problem by an alternative operator. The main advantage of the proposed approach is that, when judiciously selecting such alternative operator, the corresponding upper bound of the error representation becomes sharper, leading to a more efficient goal‐oriented adaptivity. While the method can be applied to a variety of problems, we focus here on two‐ and three‐dimensional (2‐D and 3‐D) Helmholtz problems. We show via extensive numerical experimentation that the upper bounds provided by the alternative error representations are sharper than the classical ones and lead to a more robust p‐adaptive process. We also provide guidelines for finding operators delivering sharp error representation upper bounds. We further extend the results to a convection‐dominated diffusion problem as well as to problems with discontinuous material coefficients. Finally, we consider a sonic logging‐while‐drilling problem to illustrate the applicability of the proposed method.V. Darrigrand, A. Rodriguez-Rozas and D. Pardo were partially funded by the Projects of the Spanish Ministry of Economy and Competitiveness with reference MTM2013-40824-P, MTM2016-76329-R (AEI/FEDER, EU), MTM2016-81697-ERC and the Basque Government Consolidated Research Group Grant IT649- 13 on “Mathematical Modeling, Simulation, and Industrial Applications (M2SI)”. A. Rodriguez-Rozas and D.Pardo were also partially funded by the BCAM “Severo Ochoa” accreditation of excellence SEV-2013-0323 and the Basque Government through the BERC2014-2017 program. A. Rodriguez-Rozas acknowledges support from Spanish Ministry under Grant No. FPDI- 2013-17098. I. Muga was partially funded by the FONDECYT project 1160774. The first four authors were also partially funded by the European Union’s Horizon 2020, research and innovation program under the Marie Sklodowska-Curie grant agreement No 644202. Serge Prudhomme is grateful for the support by a Discovery Grant from the Natural Sciences and Engineering Research Council of Canada

A numerical 1.5D method for the rapid simulation of geophysical resistivity measurements

In some geological formations, borehole resistivity measurements can be simulated using a sequence of 1D models. By considering a 1D layered media, we can reduce the dimensionality of the problem from 3D to 1.5D via a Hankel transform. The resulting formulation is often solved via a semi-analytic method, mainly due to its high performance. However, semi-analytic methods have important limitations such as, for example, their inability to model piecewise linear variations on the resistivity. Herein, we develop a multi-scale finite element method (FEM) to solve the secondary field formulation. This numerical scheme overcomes the limitations of semi-analytic methods while still delivering high performance. We illustrate the performance of the method with numerical synthetic examples based on two symmetric logging-while-drilling (LWD) induction devices operating at 2 MHz and 500 KHz, respectively

Novel intravesical bacterial immunotherapy induces rejection of BCG-unresponsive established bladder tumors

Background Intravesical BCG is the gold-standard therapy for non-muscle invasive bladder cancer (NMIBC); however, it still fails in a significant proportion of patients, so improved treatment options are urgently needed. Methods Here, we compared BCG antitumoral efficacy with another live attenuated mycobacteria, MTBVAC, in an orthotopic mouse model of bladder cancer (BC). We aimed to identify both bacterial and host immunological factors to understand the antitumoral mechanisms behind effective bacterial immunotherapy for BC. Results We found that the expression of the BCG-absent proteins ESAT6/CFP10 by MTBVAC was determinant in mediating bladder colonization by the bacteria, which correlated with augmented antitumoral efficacy. We further analyzed the mechanism of action of bacterial immunotherapy and found that it critically relied on the adaptive cytotoxic response. MTBVAC enhanced both tumor antigen-specific CD4 + and CD8 + T-cell responses, in a process dependent on stimulation of type 1 conventional dendritic cells. Importantly, improved intravesical bacterial immunotherapy using MBTVAC induced eradication of fully established bladder tumors, both as a monotherapy and specially in combination with the immune checkpoint inhibitor antiprogrammed cell death ligand 1 (anti PD-L1). Conclusion These results contribute to the understanding of the mechanisms behind successful bacterial immunotherapy against BC and characterize a novel therapeutic approach for BCG-unresponsive NMIBC cases. © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ

First observations with CONDOR, a 1.5 THz heterodyne receiver

The THz atmospheric windows centered at roughly 1.3 and 1.5~THz, contain numerous spectral lines of astronomical importance, including three high-J CO lines, the N+ line at 205 microns, and the ground transition of para-H2D+. The CO lines are tracers of hot (several 100K), dense gas; N+ is a cooling line of diffuse, ionized gas; the H2D+ line is a non-depleting tracer of cold (~20K), dense gas. As the THz lines benefit the study of diverse phenomena (from high-mass star-forming regions to the WIM to cold prestellar cores), we have built the CO N+ Deuterium Observations Receiver (CONDOR) to further explore the THz windows by ground-based observations. CONDOR was designed to be used at the Atacama Pathfinder EXperiment (APEX) and Stratospheric Observatory For Infrared Astronomy (SOFIA). CONDOR was installed at the APEX telescope and test observations were made to characterize the instrument. The combination of CONDOR on APEX successfully detected THz radiation from astronomical sources. CONDOR operated with typical Trec=1600K and spectral Allan variance times of 30s. CONDOR's first light observations of CO 13-12 emission from the hot core Orion FIR4 (= OMC1 South) revealed a narrow line with T(MB) = 210K and delta(V)=5.4km/s. A search for N+ emission from the ionization front of the Orion Bar resulted in a non-detection. The successful deployment of CONDOR at APEX demonstrates the potential for making observations at THz frequencies from ground-based facilities.Comment: 4 pages + list of objects, 3 figures, to be published in A&A special APEX issu