Acoustic impedance estimation from combined harmonic reconstruction and interval velocity

Low-frequency components of reflection seismic data are of paramount importance for acoustic impedance inversion, but they typically suffer from a poor signal-to-noise ratio. The estimation of low frequencies of the acoustic impedance can benefit from the combination of a harmonic reconstruction method (based on autoregressive models) and a seismic-derived interval velocity field. We propose the construction of a convex cost-function that accounts for the velocity field, together with geologic a priori information on acoustic impedance and its uncertainty, during the autoregressive reconstruction of the low frequencies. The minimization of this function allows one to reconstruct sensible estimates of low-frequency components of the subsurface reflectivity, which lead to an estimation of acoustic impedance model via a recursive formulation. In particular, the method is suited for an initial and computationally inexpensive assessment of the absolute value of acoustic impedance even when no well log data are available. We first tested the method on layered synthetic models, then we analyzed its applicability and limitations on a real marine seismic dataset that included tomographic velocity information. Despite a strong trace-to-trace variability in the results, which could partially be mitigated by multi-trace inversion, the method demonstrates its capability to highlight lateral variations of acoustic impedance that cannot be detected when the low frequencies only come from well log information

Merging gated Frequency-Modulated Continuous-Wave Mars2020 RIMFAX GPR data

The integration of GPR data at various frequencies, collected with different antennas or with the use of swept-frequency radars opens up interesting perspectives in the study of the subsurface at different resolutions. The proposed methodology is a semi-supervised DL algorithm based on Bi-Directional Long-Short Term Memory to automatically merge varying numbers of data sets at different frequencies. Neural Network training is done directly on the inference data by minimizing a custom loss function based on the L2 norm of all the input data, weighted on the custom merging area and the single output trace. The inference of the trained Neural Network is applied to the same data. The proposed algorithm is tested on synthetic data simulating the Mars conditions and on RIMFAX radar data collected in the Jezero crater during the Mars 2020 mission of Perseverance rover, showing successful performances and robustness

Plectoneme dynamics and statistics in braided polymers

Braids composed of two interwoven polymer chains exhibit a buckling transition whose origin has been explained through the onset of plectonemic structures. Here we study, by a combination of simulation and analytics, the dynamics of plectoneme formation and their statistics in steady state. The introduction of an order parameter, the plectonemic fraction, allows us to map out the phase boundary between the straight braid phase and the plectonemic one. We then monitor the formation and the growth of plectonemes, observing events typical of phase separation kinetics for liquid-gas systems (fusion, fission, 1D Ostwald ripening), but also of DNA supercoiling dynamics (plectonemic hopping). Finally, we propose a stochastic field theory for the coupled dynamics of twist and local writhe which explains the phenomenology found with Brownian dynamics simulations as well the power laws underlying the coarsening of plectonemes

Metaliteracy as Pedagogical Framework for Learner-Centered Design in Three MOOC Platforms: Connectivist, Coursera and Canvas

This article examines metaliteracy as a pedagogical model that leverages the assets of MOOC platforms to enhance self-regulated and self-empowered learning. Between 2013 and 2015, a collaborative teaching team within the State University of New York (SUNY) developed three MOOCs on three different platforms—connectivist, Coursera and Canvas—to engage with learners about metaliteracy. As a reframing of information literacy, metaliteracy envisions the learner as an active and metacognitive producer of digital information in online communities and social media environments (Mackey & Jacobson, 2011; 2014). This team of educators, which constitutes the core of the Metaliteracy Learning Collaborative, used metaliteracy as a lens for applied teaching and learning strategies in the development of a cMOOC and two xMOOCs. The metaliteracy MOOCs pushed against the dominant trends of lecture-based, automated MOOC design towards a more learner-centered pedagogy that aligns with key components of metaliteracy

Improved high-resolution GPR imaging and characterization of prehistoric archaeological features by means of attribute analysis

We propose a novel procedure for the analysis and interpretation of Ground-Penetrating Radar (GPR) data from archaeological data and we test the method in challenging conditions at a prehistoric settlement on the Stromboli Island (Italy). The main objective of the proposed procedure is to enhance the GPR capability of identifying and characterizing small-size and geometrically irregular archaeological remains buried beneath rough topographic surface conditions. After the basic GPR processing sequence, including topographic correction using a high-resolution Digital Elevation Model acquired from 3-D Laser Scanner, the procedure encompasses a multi-attribute analysis and iso-attribute surfaces calculation with different volume extraction solutions to emphasize vertical and lateral variations within GPR data cubes. The test was performed in cooperation with the archaeological team to calibrate the results and to provide detailed information about buried targets of potential archaeological interests to plan further excavations. The results gave evidence of localized buried remains and allowed detailed preexcavation planning. The archaeological excavations validated the results obtained from the GPR survey. The research demonstrates that the proposed GPR procedure enhances the ability to identify and characterize archaeological remains with high accuracy even in complex surface and subsurface conditions. Such logistical situation is very common, particularly in prehistoric sites, which are often characterized by discontinuous, small and irregular targets that cannot be identified by standard processing and analysis strategies

Metaliteracy as Pedagogical Framework for Learner-Centered Design in Three MOOC Platforms: Connectivist, Coursera and Canvas

This article examines metaliteracy as a pedagogical model that leverages the assets of MOOC platforms to enhance self-regulated and self-empowered learning. Between 2013 and 2015, a collaborative teaching team within the State University of New York (SUNY) developed three MOOCs on three different platforms—connectivist, Coursera and Canvas—to engage with learners about metaliteracy. As a reframing of information literacy, metaliteracy envisions the learner as an active and metacognitive producer of digital information in online communities and social media environments (Mackey & Jacobson, 2011; 2014). This team of educators, which constitutes the core of the Metaliteracy Learning Collaborative, used metaliteracy as a lens for applied teaching and learning strategies in the development of a cMOOC and two xMOOCs. The metaliteracy MOOCs pushed against the dominant trends of lecture-based, automated MOOC design towards a more learner-centered pedagogy that aligns with key components of metaliteracy

Thematic Analysis of the ‘Games' Students Play in Asynchronous Learning Environments

The dynamics of the student-student relationship within the asynchronous online classroom, as evidenced by conversations in an online discussion board, is one of a balancing act and are potentially more complex than those occurring in real-time. In order for learning to truly be considered effective, a collaborative, safe environment needs to exist among students within the online conversation (McDonald & Gibson, 1998). Conversations and postings made by students were examined by three raters using qualitative analysis. Thematic coding and member checking was conducted. Several prevalent themes emerged around the metaphor of playing a game. Students established rules for the game of asynchronous learning. They followed suit of the lead of player and formed team alliances while establishing who was ‘in’ and who was ‘out’ of the game. Based on these results, strategies have been identified to demonstrate techniques in how instructors can create a more effective learning environment for students, and what strategies can be used to examine and advance conversations, regardless of discipline. The techniques focus on creating awareness among students of potential issues of conflict in asynchronous student to student interactions, how to examine and engage a diversity of student perspectives, and ways to facilitate intellectual growth and advancement in the asynchronous online classroom

VIBRATION SIGNATURE ANALYSIS OF REAL AND VIRTUAL DAMAGED GEARS

ABSTRACT A high performance rig designed to test gears (materials and geometries) in extreme load and speed conditions as in aerospace applications was used to test diagnostic systems by the only vibration analysis. The authors of the present report have implemented, in addition to some standard signal analysis techniques, some advanced methodologies (e.g. NA4, NB4), which are applied to the synchronously averaged signal to detect the smallest fault related variations in the tested gear vibration signature. The different techniques have been tested and compared on the signals of a gear that underwent failure, showing the good performance of the latter approaches compared to the more conventional ones. A numerical simulation of the gear meshing was carried out to support the experimental campaign and the benchmarking of the diagnostic tools,. The stiffness computed by a FEM code was employed to simulate the gear system dynamic behavior with a lumped model, which was finally tuned using the experimental signals, to obtain indications on the crack evolution