On the Issues of Spatial Modeling of Non-Standard Profiles by the Example of Electromagnetic Emission Measurement Data

This paper examines the possibility of the spatial modelling of the Earth’s natural pulsed-electromagnetic-field measured values, which form a closed profile without the data inside. This geophysical method allows us to map active tectonic movement which breaches the integrity of pipes. During the experiment, 4.5 km of profiles were measured in the Admiralteysky district of St. Petersburg, Russia. Regular electromotive force (EMF) values and anomalous EMF values were obtained, ranging from 0 to 900 µV and above 900 µV, respectively. The anomalous values are associated with tectonic faults in the bedrock. The data obtained are characterized by complex spatial anisotropy associated with the development of two groups of tectonic faults of different orientations. The authors have considered the problems of the spatial modeling of the data obtained. The main problems, the solutions to which should allow the obtaining of adequate models, have been identified. Based on the analysis of the measurement results, geological features of the studied areas, as well as variography, the following possible solutions were proposed: changing the measurement technique; dividing the data array according to the main directions of anisotropy; the need to introduce additional correction coefficients. The problem revealed in this article requires further research on the basis of the obtained results, which will reduce the cost and timing of such studies, and, as a result, give an opportunity to take into account active tectonic disturbances during the construction and scheduled maintenance of underground utilities, which is especially important within the framework of the concept of sustainable development.

Adaptive Critical Balance and Firehose Instability in an Expanding, Turbulent, Collisionless Plasma

Using a hybrid-kinetic particle-in-cell simulation, we study the evolution of an expanding, collisionless, magnetized plasma in which strong Alfvénic turbulence is persistently driven. Temperature anisotropy generated adiabatically by the plasma expansion (and consequent decrease in the mean magnetic-field strength) gradually reduces the effective elasticity of the field lines, causing reductions in the linear frequency and residual energy of the Alfvénic fluctuations. In response, these fluctuations modify their interactions and spatial anisotropy to maintain a scale-by-scale “critical balance” between their characteristic linear and nonlinear frequencies. Eventually the plasma becomes unstable to kinetic firehose instabilities, which excite rapidly growing magnetic fluctuations at ion-Larmor scales. The consequent pitch-angle scattering of particles maintains the temperature anisotropy near marginal stability, even as the turbulent plasma continues to expand. The resulting evolution of parallel and perpendicular temperatures does not satisfy double-adiabatic conservation laws, but is described accurately by a simple model that includes anomalous scattering. Our results have implications for understanding the complex interplay between macro- and microscale physics in various hot, dilute, astrophysical plasmas, and offer predictions concerning power spectra, residual energy, ion-Larmor-scale spectral breaks, and non-Maxwellian features in ion distribution functions that may be tested by measurements taken in high-beta regions of the solar wind.

Methods for analyzing continuous conformational variability of biomolecules in cryo electron subtomograms: HEMNMA-3D vs. traditional classification

Cryogenic electron tomography (cryo-ET) allows studying biological macromolecular complexes in cells by three-dimensional (3D) data analysis. The complexes continuously change their shapes (conformations) to achieve biological functions. The shape heterogeneity in the samples imaged in the cryo electron microscope is a bottleneck for comprehending biological mechanisms and developing drugs. Low signal-to-noise ratio and spatial anisotropy (missing wedge artefacts) make cryo-ET data particularly challenging for resolving the shape variability. Other shape variability analysis techniques simplify the problem by considering discrete rather than continuous conformational changes of complexes. Recently, HEMNMA-3D was introduced for cryo-ET continuous shape variability analysis, based on elastic and rigid-body 3D registration between simulated shapes and cryo-ET data. The simulated motions are obtained by normal mode analysis of a high- or low-resolution 3D reference model of the complex under study. The rigid-body alignment is achieved via fast rotational matching with missing wedge compensation. HEMNMA-3D provides a visual insight into molecular dynamics by grouping and averaging subtomograms of similar shapes and by animating movies of registered motions. This article reviews the method and compares it with existing literature on a simulated dataset for nucleosome shape variability.

Determination of the Spatial Anisotropy of the Surface MicroStructures of Different Implant Materials: An Atomic Force Microscopy Study

Many biomaterials’ surfaces exhibit directional properties, i.e., possess spatial anisotropy on a range of spatial scales spanning from the domain of the naked eye to the sub-micrometer level. Spatial anisotropy of surface can influence the mechanical, physicochemical, and morphological characteristics of the biomaterial, thus affecting its functional behavior in relation, for example, to the host tissue response in regenerative processes, or to the efficacy of spatially organized surface patterns in avoiding bacterial attachment. Despite the importance of the availability of quantitative data, a comprehensive characterization of anisotropic topographies is generally a hard task due to the proliferation of parameters and inherent formal complications. This fact has led so far to excessive simplification that has often prevented researchers from having comparable results. In an attempt to overcome these issues, in this work a systematic and multiscale approach to spatial anisotropy is adopted, based on the determination of only two statistical parameters of surface, namely the texture aspect ratio Str and the roughness exponent H, extracted from atomic force microscopy images of the surface. The validity on this approach is tested on four commercially available implant materials, namely titanium alloy, polyethylene, polyetheretherketone and polyurethane, characterized by textured surfaces obtained after different machining. It is found that the “two parameters” approach is effective in describing the anisotropy changes on surfaces with complex morphology, providing a simple quantitative route for characterization and design of natural and artificial textured surfaces at spatial scales relevant to a wide range of bio-oriented applications.

A Hybrid High-Order Vorticity-Based Eulerian and Lagrangian Vortex Particle Method, the 2-D Case

Hybrid Lagrangian-Eulerian solvers combine the convective and compactness advantages of vortex methods with the spatial anisotropy and boundary-resolving advantages of Eulerian methods to create flexible solvers capable of adequately capturing thin boundary layers while still maintaining wake vortex coherency for unsteady incompressible flow in complex geometries. The present paper details a new hybrid method which combines, in one open-source package, a novel, compact, high-order Eulerian scheme for vorticity transport to predict the flow in the near-boundary region with a grid-free, unremeshed, Lagrangian Vortex Particle Method (LVPM) for the off-boundary vorticity-containing region. This paper focuses on the hybridization of the two methods and demonstrates its effectiveness on two canonical benchmarks: flow in 2-D lid-driven cavity at Re = 1,000 and impulsively started flow over a circular cylinder at Re = 9,500. In each case, the hybrid method improves upon a pure LVPM and uses far fewer cells than a purely Eulerian scheme. In addition, the size of the associated Eulerian region is greatly reduced compared to previous hybrid methods.

PECAn, a pipeline for image processing and statistical analysis of complex mosaic 3D tissues

Investigating organ biology requires sophisticated methodologies to induce genetically distinct clones within a tissue. Microscopic analysis of such samples produces information-rich 3D images. However, the 3D nature and spatial anisotropy of clones makes sample analysis challenging and slow and limits the amount of information that can be extracted manually. Here we have developed a pipeline for image processing and statistical data analysis which automatically extracts sophisticated parameters from complex multi-genotype 3D images. The pipeline includes data handling, machine-learning-enabled segmentation, multivariant statistical analysis, and graph generation. This enables researchers to run rigorous analyses on images and videos at scale and in a fraction of the time, without requiring programming skills. We demonstrate the power of this pipeline by applying it to the study of Minute cell competition. We find an unappreciated sexual dimorphism in Minute competition and identify, by statistical regression analysis, tissue parameters that model and predict competitive death.