RESUMEN
Building accurate acoustic subsurface velocity models is essential for successful industrial exploration projects. Traditional inversion methods from field-recorded seismograms struggle in regions with complex geology. While deep learning (DL) presents a promising alternative, its robustness using field data in these complicated regions has not been sufficiently explored. In this study, we present a thorough analysis of DL's capability to harness labeled seismograms, whether field-recorded or synthetically generated, for accurate velocity model recovery in a challenging region of the Gulf of Mexico. Our evaluation centers on the impact of training data selection and data augmentation techniques on the DL model's ability to recover velocity profiles. Models trained on field data produced superior results to data obtained using quantitative metrics like Mean Squared Error (MSE), Structural Similarity Index Measure (SSIM), and R2 (R-squared). They also yielded more geologically plausible predictions and sharper geophysical migration images. Conversely, models trained on synthetic data, while less precise, highlighted the potential utility of synthetic training data, especially when labeled field data are scarce. Our work shows that the efficacy of synthetic data-driven models largely depends on bridging the domain gap between training and test data through the use of advanced wave equation solvers and geologic priors. Our results underscore DL's potential to advance velocity model-building workflows in industrial settings using previously labeled field-recorded seismograms. They also highlight the indispensable role of earth scientists' domain expertise in curating synthetic data when field data are lacking.
RESUMEN
Paint and varnish removers constitute a major potential source of organic solvent exposure to contractors and home improvement enthusiasts. Unfortunately, the leading paint remover formulations have traditionally contained, as major ingredients, chemicals classified as probable human carcinogens (eg, methylene chloride) or reproductive toxicants (eg, N-methylpyrrolidone). In addition, because of its unique toxicology (ie, hepatic conversion to carbon monoxide compounding generic solvent narcosis and arrythmogenesis), high volatility, and rigorous requirements for personal protective equipment, methylene chloride exposures from paint removers have been linked to numerous deaths involving both occupational and consumer usage. The aim of this review is to summarize the known toxicology of solvent-based paint remover constituents (including those found in substitute formulations) in order to provide health risk information to regulators, chemical formulators, and end-users of this class of products, and to highlight any data gaps that may exist.
Asunto(s)
Carcinógenos/toxicidad , Exposición a Riesgos Ambientales/efectos adversos , Exposición Profesional/efectos adversos , Pintura/toxicidad , Solventes/toxicidad , Compuestos Orgánicos Volátiles/toxicidad , Adulto , Femenino , Humanos , Masculino , Persona de Mediana EdadRESUMEN
OBJECTIVE: To ascertain whether reverse transcriptase polymerase chain reaction (RT-PCR) cycle amplifications until detection, the cycle threshold (Ct), could help inform return to work (RTW) strategies for health care workers (HCWs) recovering from COVID-19 infection. METHODS: Sequential Ct data from COVID-19 nasal pharyngeal (NP) RT-PCR testing in all COVID-19 positive HCWs at a single institution. Analysis of Ct in relation to time until negative testing for RTW clearance. RESULTS: Data for 12 employees showed that time elapsed until RT-PCR test-based RTW clearance ranged from 7 to 57 days (median, 34.5 days). Lower initial Ct correlated with the total time elapsed until clearance (râ=â-0.80; Pâ=â0.002). CONCLUSION: Considering the RT-PCR Ct, which correlates with the estimated viral load, may help inform RTW planning and decision making beyond solely relying on dichotomized positive/negative results.
Asunto(s)
Betacoronavirus , Técnicas de Laboratorio Clínico , Infecciones por Coronavirus/diagnóstico , Personal de Salud , Neumonía Viral/diagnóstico , Reinserción al Trabajo , COVID-19 , Prueba de COVID-19 , Estudios de Cohortes , Femenino , Humanos , Masculino , Pandemias , SARS-CoV-2 , Sensibilidad y Especificidad , Carga ViralRESUMEN
A 25-year-old man, who was an active duty US Navy sailor, went to his ship's medical department complaining of a mild cough that he'd had for 2 days. He denied having any fevers, chills, night sweats, angina, or dyspnea. He said he hadn't experienced any exertional fatigue or difficulty completing the rigorous physical tasks of his occupation as an engineman on the ship. The patient had no medical or surgical history of significance, and he wasn't taking any medications or supplements. On exam, he was not in acute distress and his vital signs were within normal limits. Auscultation revealed mild wheezing throughout the upper lung fields and loud heart sounds throughout his chest that were audible even with gentle contact of the stethoscope diaphragm. He had no discernible murmurs, rubs, or gallops. In light of the unusually loud heart sounds heard on exam, we performed an electrocardiogram. The EKG revealed a normal sinus rhythm, slight right axis deviation indicated by tall R-waves in V1 (also suggestive of right ventricular hypertrophy), an incomplete right bundle branch block, and a crochetage sign (a notch in the R-waves of the inferior leads). A chest x-ray revealed a normal-sized heart and dilated pulmonary vasculature suggestive of pulmonary hypertension.