DispersioNET: Joint Inversion of Rayleigh-Wave Multimode Phase Velocity Dispersion Curves using Convolutional Neural Networks

Rayleigh wave dispersion curves have been widely used in near-surface studies, and are primarily inverted for the shear wave (S-wave) velocity profiles. However, the inverse problem is ill-posed, non-unique and nonlinear. Here, we introduce DispersioNET, a deep learning model based on convolution neural networks (CNN) to perform the joint inversion of Rayleigh wave fundamental and higher order mode phase velocity dispersion curves. DispersioNET is trained and tested on both noise-free and noisy dispersion curve datasets and predicts S-wave velocity profiles that match closely with the true velocities. The architecture is agnostic to variations in S-wave velocity profiles such as increasing velocity with depth and intermediate low-velocity layers, while also ensuring that the output remains independent of the number of layers.Comment: Preprint of the paper submitted to the 2nd Indian Near Surface Geophysics Conference & Exhibition by AF Academy and the European Association of Geoscientists & Engineers (EAGE

GSU Scheduling System

The main agenda of this project is scheduling student project sessions for a particular semester. In this system we going to develop a web based application where students who are been registered for this particular section can directly select their slot and time when they want to give Presentation of their project and also they can directly submit their abstract online and also they can get updates as a messages and e-mails which are been send to their personal contact numbers and email address regarding their project and where as advisor can add the students and manage the schedule of the project selected by the student

Isolation, identification and molecular characterization of Ralstonia solanacerum isolates collected from Southern Karnataka

Bacterial wilt caused by Ralstonia solanacearum, is the major threat to tomato cultivation in all tomato growing areas of Karnataka.  R. solanacearum was isolated from the infected host plants collected from different locations of southern Karnataka. The identity of the isolates was established using morphological, biochemical, and molecular analysis using species specific PCR primers. The race and biovar specificity of pathogen was determined through pathogenicity test on different host plants and the ability of isolates to use carbohydrates, respectively. Phylotype classification was done by phylotype specific multiplex PCR using phylotype specific primers. All the bacterial isolates showed the characteristic creamy white fluidal growth with pink centre on the Tetrazolium chloride medium. Further, the isolates amplified at 280 bp, which confirmed the identity of pathogen as Ralstonia solanacearum. Our results showed that all isolates belonged to Race 1 of the pathogen. Among different isolates obtained, four isolates each were identified to be Biovar III and Biovar IIIA, repectively, while two isolates were identified as Biovar IIIB. All the ten isolates were affiliated to Phylotype I of Ralstonia solanaceraum species complex. These findings may help in devising the management practices for bacterial wilt of tomato in southern Karnataka

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570

Modeling, evaluation, and asymptotic analysis of attenuation anisotropy

Seismic attenuation is sensitive to the physical properties of the subsurface, which makes attenuation analysis a useful tool for reservoir characterization. In this thesis, I present algorithms for estimating directionally dependent attenuation coefficients and perform asymptotic and numerical analysis of wave propagation in attenuative anisotropic media. First, I introduce a methodology to estimate the S-wave interval attenuation coefficient by extending the layer-stripping method of Behura and Tsvankin (2009) to mode-converted (PS) waves. Kinematic reconstruction of pure shear (SS) events in the target layer and the overburden is performed by combining velocity-independent layer stripping with the PP+PS=SS method. Then, application of the spectral-ratio method and the dynamic version of velocity-independent layer stripping to the constructed SS reflections yields the S-wave interval attenuation coefficient in the target layer. The attenuation coefficient estimated for a range of source-receiver offsets can be inverted for the interval attenuation-anisotropy parameters. The method is tested on synthetic data generated with the anisotropic reflectivity method for layered VTI (transversely isotropic with a vertical symmetry axis) media and vertical symmetry planes of orthorhombic media. Then, I analyze a cross-hole data set generated by perforation shots set off in a horizontal borehole to induce hydraulic fracturing in a tight gas reservoir. The spectral-ratio method is applied to pairs of traces to set up a system of equations for directionally-dependent effective attenuation. Although the inversion provides clear evidence of attenuation anisotropy, the narrow range of propagation directions impairs the accuracy of anisotropy analysis. The observed variations of the attenuation coefficient between different perforation stages appear to be related to changes in the medium due to hydraulic fracturing and stimulation. Important insights into point-source radiation in attenuative anisotropic media can be gained by applying asymptotic methods. I derive the asymptotic Green's function in homogeneous, attenuative, arbitrarily anisotropic media using the steepest-descent method. The saddle-point condition helps describe the behavior of the far field slowness and group-velocity vectors and evaluate the inhomogeneity angle (the angle between the real and imaginary parts of the slowness vector). The results from the asymptotic analysis are compared with those from the ray-perturbation method for P-waves in TI media. Finally, I address the problem of efficient viscoelastic modeling in heterogeneous anisotropic media. The Kirchhoff scattering integral is employed to generate reflected P-waves, with the required Green's functions computed by summation of Gaussian beams. The influence of attenuation on the Gaussian beams is incorporated using ray-perturbation theory. The method is applied to generate synthetic data from a highly attenuative VTI medium above a horizontal reflector and a structurally complex acoustic model with a salt body