Error Control and Loss Functions for the Deep Learning Inversion of Borehole Resistivity Measurements

Deep learning (DL) is a numerical method that approximates functions. Recently, its use has become attractive for the simulation and inversion of multiple problems in computational mechanics, including the inversion of borehole logging measurements for oil and gas applications. In this context, DL methods exhibit two key attractive features: a) once trained, they enable to solve an inverse problem in a fraction of a second, which is convenient for borehole geosteering operations as well as in other real-time inversion applications. b) DL methods exhibit a superior capability for approximating highly-complex functions across different areas of knowledge. Nevertheless, as it occurs with most numerical methods, DL also relies on expert design decisions that are problem specific to achieve reliable and robust results. Herein, we investigate two key aspects of deep neural networks (DNNs) when applied to the inversion of borehole resistivity measurements: error control and adequate selection of the loss function. As we illustrate via theoretical considerations and extensive numerical experiments, these interrelated aspects are critical to recover accurate inversion results

Comparative Live-Cell Imaging Analyses of SPA-2, BUD-6 and BNI-1 in Neurospora crassa Reveal Novel Features of the Filamentous Fungal Polarisome

A key multiprotein complex involved in regulating the actin cytoskeleton and secretory machinery required for polarized growth in fungi, is the polarisome. Recognized core constituents in budding yeast are the proteins Spa2, Pea2, Aip3/Bud6, and the key effector Bni1. Multicellular fungi display a more complex polarized morphogenesis than yeasts, suggesting that the filamentous fungal polarisome might fulfill additional functions. In this study, we compared the subcellular organization and dynamics of the putative polarisome components BUD-6 and BNI-1 with those of the bona fide polarisome marker SPA-2 at various developmental stages of Neurospora crassa. All three proteins exhibited a yeast-like polarisome configuration during polarized germ tube growth, cell fusion, septal pore plugging and tip repolarization. However, the localization patterns of all three proteins showed spatiotemporally distinct characteristics during the establishment of new polar axes, septum formation and cytokinesis, and maintained hyphal tip growth. Most notably, in vegetative hyphal tips BUD-6 accumulated as a subapical cloud excluded from the Spitzenkörper (Spk), whereas BNI-1 and SPA-2 partially colocalized with the Spk and the tip apex. Novel roles during septal plugging and cytokinesis, connected to the reinitiation of tip growth upon physical injury and conidial maturation, were identified for BUD-6 and BNI-1, respectively. Phenotypic analyses of gene deletion mutants revealed additional functions for BUD-6 and BNI-1 in cell fusion regulation, and the maintenance of Spk integrity. Considered together, our findings reveal novel polarisome-independent functions of BUD-6 and BNI-1 in Neurospora, but also suggest that all three proteins cooperate at plugged septal pores, and their complex arrangement within the apical dome of mature hypha might represent a novel aspect of filamentous fungal polarisome architecture

Interview no. 1058

Mr. Verdín recalls growing up in Purísima del Rincón, Guanajuato, México, and working with his father in the fields; he remembers receiving formal education up to the fifth grade; he joined the Bracero Program in 1959, and relates his experience during the hiring process; additionally, he discusses how he was chosen to be a cook in the bracero camps, and what his life was like as a bracero; he also worked in Arizona and California picking cotton; these activities he did until 1967; after the Bracero Program ended, he returned to the United States as an undocumented worker; he describes how he crossed the border and the work he did in the U.S.; furthermore, he concludes by stating that he has lived in Austin, Texas since 1971 with his family, and that he took advantage of the amnesty offered in 1985

Efficiency of Software Testing Techniques: A Controlled Experiment Replication and Network Meta-analysis

Background: Common approaches to software verification include static testing techniques, such as code reading, and dynamic testing techniques, such as black-box and white-box testing. Objective: With the aim of gaining a~better understanding of software testing techniques, a~controlled experiment replication and the synthesis of previous experiments which examine the efficiency of code reading, black-box and white-box testing techniques were conducted. Method: The replication reported here is composed of four experiments in which instrumented programs were used. Participants randomly applied one of the techniques to one of the instrumented programs. The outcomes were synthesized with seven experiments using the method of network meta-analysis (NMA). Results: No significant differences in the efficiency of the techniques were observed. However, it was discovered the instrumented programs had a~significant effect on the efficiency. The NMA results suggest that the black-box and white-box techniques behave alike; and the efficiency of code reading seems to be sensitive to other factors. Conclusion: Taking into account these findings, the Authors suggest that prior to carrying out software verification activities, software engineers should have a~clear understanding of the software product to be verified; they can apply either black-box or white-box testing techniques as they yield similar defect detection rates

Uncertainty Quantification on the Inversion of Geosteering Measurements using Deep Learning

We propose the use of a Deep Learning (DL) algorithm for the real-time inversion of electromagnetic measurements acquired during geosteering operations. Moreover, we show that when the DL algorithm is equipped with a properly designed two-step loss function without regularization, it is possible to recover an uncertainty quantification map by analyzing certain cross-plots. We illustrate these ideas with a synthetic example based on piecewise 1D earth models. The resulting uncertainty quantification map could be used to design better measurement acquisition systems for geosteering operations

Low Flow Veno-Venous ECMO: An Experimental Study

Clinical use of extracorporeal membrane oxygenation (ECMO) and carbon dioxide removal (ECCO2R) have become well established techniques for the treatment of severe respiratory failure; however they require full cardiopulmonary bypass, representing major procedures with high morbidity. We theorized the possibility of an efficient low flow venavenous extracorporeal membrane gas exchange method. Four mongrel 12kg dogs were submitted to vena-venous extracorporeal membrane gas exchange via a jugular dialysis catheter using a low flow (10 ml/min) roller pump and a membrane oxygenator for a period of four hours. Respiratory rate was set at 4 breaths/min with a FiO2 of 21% and ventilatory dead space was increased. Adequate gas exchange was obtained (pO2 139, pCO2 24, Sat 99.4%), without major hemodynamic changes or hematuria. Our results demonstrate the feasibility of a low flow, less aggressive system. Further research should be considered