Temperature and Salinity Inverted for a Mediterranean Eddy Captured With Seismic Data, Using a Spatially Iterative Markov Chain Monte Carlo Approach

Ocean submesoscale dynamics are thought to play a key role in both the climate system and ocean productivity, however, subsurface observations at these scales remain rare. Seismic oceanography, an established acoustic imaging method, provides a unique tool for capturing oceanic structure throughout the water column with spatial resolutions of tens of meters. A drawback to the seismic method is that temperature and salinity are not measured directly, limiting the quantitative interpretation of imaged features. The Markov Chain Monte Carlo (MCMC) inversion approach has been used to invert for temperature and salinity from seismic data, with spatially quantified uncertainties. However, the requisite prior model used in previous studies relied upon highly continuous acoustic reflection horizons rarely present in real oceanic environments due to instabilities and turbulence. Here we adapt the MCMC inversion approach with an iteratively updated prior model based on hydrographic data, sidestepping the necessity of continuous reflection horizons. Furthermore, uncertainties introduced by the starting model thermohaline fields as well as those from the MCMC inversion itself are accounted for. The impact on uncertainties of varying the resolution of hydrographic data used to produce the inversion starting model is also investigated. The inversion is applied to a mid-depth Mediterranean water eddy (or meddy) captured with seismic imaging in the Gulf of Cadiz in 2007. The meddy boundary exhibits regions of disrupted seismic reflectivity and rapid horizontal changes of temperature and salinity. Inverted temperature and salinity values typically have uncertainties of 0.16°C and 0.055 psu, respectively, and agree well with direct measurements. Uncertainties of inverted results are found to be highly dependent on the resolution of the hydrographic data used to produce the prior model, particularly in regions where background temperature and salinity vary rapidly, such as at the edge of the meddy. This further advancement of inversion techniques to extract temperature and salinity from seismic data will help expand the use of ocean acoustics for understanding the mesoscale to finescale structure of the interior ocean.

Building FWI starting model from wells with dynamic time warping and convolutional neural networks

Full waveform inversion (FWI) needs a feasible starting model, because otherwise it might converge to a local minimum and the inversion result might suffer from detrimental artifacts. We built a feasible starting model from wells by applying dynamic time warping (DTW) localized rewarp and convolutional neural network (CNN) methods alternatively. We used the DTW localized rewarp method to extrapolate the velocities at well locations to the non-well locations in the model space. Rewarping is conducted based on the local structural coherence which is extracted from a migration image of an initial infeasible model. The extraction uses the DTW method. The purpose of velocity extrapolation is to provide sufficient training samples to train a CNN, which maps local spatial features on the migration image into the velocity quantities of each layer. We further designed an interactive workflow to reject inaccurate network predictions and to improve CNN prediction accuracy by incorporating the Monte Carlo dropout method. We demonstrated that the proposed method is robust against the kinematic incorrectness in the migration velocity model, and is capable to produce a feasible FWI starting model.

Multiscale modeling of bio-nano interactions of zero-valent silver nanoparticles.

Understanding the specifics of interaction between protein and nanomaterial is crucial for designing efficient, safe, and selective nanoplatforms, such as biosensor or nanocarrier systems. Routing experimental screening for the most suitable complementary pair of biomolecule and nanomaterial used in such nanoplatforms might be a resource-intensive task. While a variety of computational tools is available for pre-screening libraries of small drug molecules interacting with proteins, options for high-throughput screening of protein libraries for binding affinities to new and existing nanomaterials are limited. In the current work, we present the results of a systematic computational study of protein interaction with zero-valent silver nanoparticles using a multiscale approach. A variety of blood plasma and dietary proteins, namely, bovine and human serum albumins, bovine and human hemoglobin, papain, bromelain, lysozyme, and bovine lactoferrin, were examined. Selected combinations of nanomaterial and proteins can serve as a starting model for developing noble metal-based nanocarriers and biosensors. The computed binding (adsorption) characteristics for selected proteins were validated by experimental data reported in the literature. An advanced in silico nano-QSAR/QSPR interfacial descriptor 〖log⁡P〗^NM was also introduced to characterize the relative hydrophobicity/hydrophilicity of the nanomaterial.

Molecular Dynamics Study of Escherichia coli Thymidine Phosphorylase in a Complex with 3'-Azidothymidine Inhibitor and Phosphate

Abstract— Using a molecular dynamics method, the state of the dimeric thymidine phosphorylase molecule from Escherichia coli in a complex with noncompetitive enzyme inhibitor 3'-azidothymidine and phosphate ion was studied on a trajectory of 50 ns. Previously obtained atomic coordinates of a complex of thymidine phosphorylase with azidothymidine and sulfate at a resolution of 1.52 Å were used as a starting model. It was demonstrated that both subunits of a dimeric enzyme molecule function asynchronously in a given time interval; moreover, each subunit maintains an open conformation. It was found that the nature of ligand at the nucleoside center affects the binding strength of phosphate in the phosphate center. In a complex with an inhibitor, both ligands over the entire time interval remain bound to the enzyme, while the release of phosphate from the active center is observed when simulating the behavior of thymidine phosphorylase in the presence of phosphate and thymidine substrate. The stabilizing effect of azidothymidine on phosphate binding is consistent with the behavior of azidothymidine as a noncompetitive inhibitor of thymidine phosphorylase.

A Novel Biologging Tag that Minimizes the Hydrodynamic Loading on Marine Animals

Although biologging tags, which are externally attached sensor packages deployed on marine animals, have become essential conservation tools, a core issue with current tag designs is that they are rarely tested for hydrodynamics and may generate substantial hydrodynamic loading (drag and lift forces) on animals. This may cause tags to impede animal physiology, give rise to injuries at the site of attachment, and cause tags to relay unrepresentative data. This study aims to design a new biologging tag form that houses the DTAG3 electronics and reduces the total drag and lift induced on marine animals. One starting model (GPS Phone Tag referred to as Model 0), three iterations, and the final design (Model D), were constructed using CAD software. They were tested with Computational Fluid Dynamics (CFD) simulations to obtain and analyze the drag and lift force. All models were tested at speeds between 1-5 m/s, with 400 trials. The Model D includes a narrow elliptical shape to maintain laminar boundary layers, a pointed tail shape to avoid flow separation, canards for frontal downforce, tabs to reduce form drag, streamlined hydrophones, and dimples to delay flow separation. The CFD simulation results demonstrated that Model D reduced drag by up to 56% and lift by upto 86% compared to Model 0. These results show the potential benefit of this design in reducing the impact of biologging tags on the behavior and energetics of marine animals, and in providing an unbiased and holistic view of the animal behavior for conservation management actions.

Agent-Based Learning Model for the Obesity Paradox in RCC

A recent study on the immunotherapy treatment of renal cell carcinoma reveals better outcomes in obese patients compared to lean subjects. This enigmatic contradiction has been explained, in the context of the debated obesity paradox, as the effect produced by the cell-cell interaction network on the tumor microenvironment during the immune response. To better understand this hypothesis, we provide a computational framework for the in silico study of the tumor behavior. The starting model of the tumor, based on the cell-cell interaction network, has been described as a multiagent system, whose simulation generates the hypothesized effects on the tumor microenvironment. The medical needs in the immunotherapy design meet the capabilities of a multiagent simulator to reproduce the dynamics of the cell-cell interaction network, meaning a reaction to environmental changes introduced through the experimental data.

Predicting Big Data Adoption in Companies With an Explanatory and Predictive Model

The purpose of this paper is to identify the factors that affect the intention to use Big Data Applications in companies. Research into Big Data usage intention and adoption is scarce and much less from the perspective of the use of these techniques in companies. That is why this research focuses on analyzing the adoption of Big Data Applications by companies. Further to a review of the literature, it is proposed to use a UTAUT model as a starting model with the update and incorporation of other variables such as resistance to use and perceived risk, and then to perform a neural network to predict this adoption. With respect to this non-parametric technique, we found that the multilayer perceptron model (MLP) for the use of Big Data Applications in companies obtains higher AUC values, and a better confusion matrix. This paper is a pioneering study using this hybrid methodology on the intention to use Big Data Applications. The result of this research has important implications for the theory and practice of adopting Big Data Applications.

Improved interpretation of SAGEEP 2011 blind refraction data using Frequency-Dependent Traveltime Tomography

<p>We demonstrate improved resolution in P-wave velocity tomograms obtained by inversion of the synthetic SAGEEP 2011 refraction traveltime data (Zelt 2010) using Wavepath-Eikonal Traveltime Inversion (WET; Schuster 1993) and Wavelength-Dependent Velocity Smoothing (WDVS; Zelt and Chen 2016). We use a multiscale inversion approach and a Conjugate-Gradient based search method. Our default starting model is a 1D-gradient model obtained directly from the traveltime first arrivals assuming diving waves (Sheehan, 2005). As a second approach, we map the first breaks to assumed refractors and obtain a layered starting model using the Plus-Minus refraction method (Hagedoorn, 1959). We compare tomograms obtained using WDVS to smooth the current velocity model grid before forward modeling traveltimes vs. tomograms obtained without WDVS. Results show that WET images velocity layer boundaries more sharply when engaging WDVS. We determine the optimum WDVS frequency iteratively by trial-and-error. We observe that the lower the used WDVS frequency, the stronger the imaged velocity contrast at the top-of-basement. Using a WDVS frequency that is too low makes WDVS based WET inversion unstable exhibiting increasing RMS error, too high modeled velocity contrast and too shallow imaged top-of-basement. To speed up WDVS, we regard each nth node only when scanning the velocity along straight scan lines radiating from the current velocity grid node. Scanned velocities are weighted with a Cosine-Squared function as described by (Zelt and Chen, 2016). We observe that activating WDVS allows decreasing WET regularization (smoothing and damping) to a higher degree than without WDVS.</p><p>References:</p><p><span>Hagedoorn, J.G., 1959, </span><span>The Plus-Minus method of interpreting seismic refraction sections, Geophysical Prospecting</span><span>, Volume 7, 158-182.</span></p><p><span>Rohdewald, S.R.C., 2021, SAGEEP11 data interpretation, https://rayfract.com/tutorials/sageep11_16.pdf.</span></p><p>Schuster, G.T., Quintus-Bosz, A., 1993, <span>Wavepath eikonal traveltime inversion: Theory</span>. Geophysics, Volume 58, 1314-1323.</p><p><span>Sheehan, J.R., Doll, W.E., Mandell, W., 2005, </span><span>An evaluation of methods and available software for seismic refraction tomography analysis</span><span>, JEEG, Volume 10(1), 21-34.</span></p><p>Shewchuk, J.R., 1994, An Introduction to the Conjugate Gradient Method Without the Agonizing Pain, <span>http://www.cs.cmu.edu/~quake-papers/painless-conjugate-gradient.pdf</span><span>. </span></p><p>Zelt, C.A., 2010, Seismic refraction shootout: blind test of methods for obtaining velocity models from first-arrival travel times, <span>http://terra.rice.edu/department/faculty/zelt/sageep2011</span>.</p><p><span>Zelt, C.A., Haines, S., Powers, M.H. et al. 2013, </span><span>Blind Test of Methods for Obtaining 2-D Near-Surface Seismic Velocity Models from First-Arrival Traveltimes</span><span>, JEEG, Volume 18(3), 183-194. </span></p><p><span>Zelt, C.A., Chen, J., 2016, </span><span>Frequency-dependent traveltime tomography for near-surface seismic refraction data</span><span>, Geophys. J. Int., Volume 207, 72-88. </span></p>

Model digitalnog reflektivnog portfolija za strani jezik struke

In the conditions of online teaching and working in digital environment, digital portfolio is one of important tools in the process of improving the quality of teaching and the implementation of the student-oriented model of university teaching. The aim of this paper is to create a model of a reflective digital portfolio for foreign languages for specific purposes at the Teacher Education Faculty, University of Belgrade, with the aim of raising the level of language and digital literacy in the conditions of hybrid and online teaching. In addition to the modeling method, a case study was used which included students attending the academic course of Educational Technology at the Teacher Education Faculty, with a focus on interdisciplinary connections with foreign languages for specific purposes. The paper discusses the theoretical starting points, the possibilities and challenges of using a digital portfolio teaching foreign languages for specific purposes. The review and analysis concluded that a hybrid model is a starting model for an efficient digital portfolio development, and that the digital portfolio can be successfully used in both formative and summative evaluation of student achievement, with horizontal and vertical interdisciplinary connections playing a key role.