Structures Of Different Scales Research Articles

Investigations of equatorial plasma bubbles as observed in the OI 630 nm nightglow emissions over off-equatorial and low-latitudinal locations over Indian longitudes

Equatorial plasma bubbles (EPBs), generated over the dip-equator during the sunset time, get mapped over to the low-latitudes through the geomagnetic field lines and contribute to structures of different scales in the nighttime thermosphere-ionosphere system. In the present study, the EPBs are observed in the OI 630 nm nightglow emissions over Mt. Abu and Kolhapur using a High Throughput Imaging Echelle spectrograph (HiTIES) and All-Sky Imager (ASI), respectively. Similar periodicities obtained in these measurements consistently corroborate the presence of the EPBs at both these locations. The strength of the Pre-Reversal Enhancement (PRE) in the zonal electric field has been investigated using the ionosonde data over Trivandrum, a dip-equatorial location. The strength of PRE decides the latitudinal extent of the EPBs. The eastward movement of the EPBs has been estimated to be in the range of 190–90 ms−1, decreasing in magnitude from post-sunset to midnight. The wave number analysis carried out using the observed OI 630 nm emissions in the zonal direction has resulted in a contrasting behaviour during the presence/absence of the EPBs. Based on the analysis of around 1300 images of data, it is revealed that the scale sizes in the range of 250–300 km are omnipresent, whereas, shorter scale sizes (50–250 km) are present only during the presence of EPBs. It is inferred that these shorter scale size gravity waves played a significant role in the seeding the perturbation of the EPBs.

Sports Risk Analysis Based on Knowledge Discovery and Data Driven

Sports have gradually gained popularity, and the risks associated with them have risen as well. In today’s world, college students are a diverse population, and sports are very popular among them. The construction of sports risk assessment system in ordinary colleges is significant to improve physical quality of college students and ensure safety. College sports accidents have occurred on occasion in recent years, causing not only enormous pain to students and parents, but also casting a dark shadow over the sport. This work takes the risk analysis of college students’ sports as the background, and uses a data-driven neural network to conduct knowledge discovery of college sports threats. It evaluates the sports risks of college students’ physical education, and builds an index system of sports risk assessment in ordinary colleges and universities, which provides a certain basis for avoiding and reducing sports risks. This work studies an end-to-end one-dimensional convolutional neural network algorithm for risk assessment of college sports. In order to extract complementary structures in different scales, a multi-scale fusion framework is constructed using convolution kernels of diverse sizes. In this paper, the residual network structure is introduced to deepen and improve the network, and an attention module suitable for one-dimensional residual network is designed. It is embedded into the residual module to construct a multi-scale attention residual network (MSAR) model. Finally, validity and superiority of proposed model are verified by experimental data, which can effectively evaluate the sports risk of college students.

On the existence and formation of multi-scale particle streaks in turbulent channel flows

Direct numerical simulations of particle-laden turbulent channel flows at friction Reynolds number $Re_\tau$ from $600$ to $2000$ have been performed to examine the near-wall particle streaks. Different from the well-observed small-scale particle streaks in near-wall turbulence of low $Re_\tau$ , the present results show large-scale particle streaks through the computational domain formed for relatively high-inertia particles at high $Re_\tau$ . Transferred by large-scale sweep and ejection events ( $Q^-$ ), these high-inertia particles preferentially accumulate in near-wall regions beneath the large-scale low-speed flow streaks observed in the logarithmic region. The corresponding Stokes numbers are associated with the lifetime of large-scale $Q^-$ structures, which increases as the Reynolds number grows. The small-scale particle streaks with a typical Stokes number $St_\nu \approx 30$ are mainly driven by the $Q^-$ structures in the buffer layer, whose lifetime is approximately $30$ in viscous time unit. Therefore, we propose a new structure-based Stokes number normalized by the lifetime of $Q^-$ structures of different scales. The relevant flow scales that control the formation of the large-scale particle streaks are parameterized by the structure-based Stokes number. The small-scale (large-scale) particle streaks are most prominent when the buffer-layer (large-scale) structure-based Stokes number approaches unity. The present findings reveal that formation of near-wall particle streaks is governed by the $Q^-$ structures of different scales, and the particles with different inertia respond efficiently to the $Q^-$ structures of corresponding scales with respect to the particle translational motion.

ДОСЛІДЖЕННЯ ІСТОРИЧНО СФОРМОВАНОЇ СТРУКТУРИ ГРОМАДСЬКИХ ПРОСТОРІВ КУРОРТІВ НА ПРИКЛАДІ ЯРЕМЧЕ, ТАТАРОВА, ВОРОХТИ ІВАНО-ФРАНКІВСЬКОЇ ОБЛАСТІ

In this small-research study, the public spaces of the historical centres of three resorts of the Ivano-Frankivsk region (Yaremche, Tatariv, Vorokhta) were localized, their morphology and existing condition were analyzed, and architectural and town-planning elements were identified. Particular attention is paid to identifying the historically formed structure of spaces, their state of preservation, typology and uniqueness. All structural elements (existing ones and lost ones) were identified with the help of cartographic analysis, iconographic analysis and field surveys. The spatial organization of the researched resort areas represents a linear structure characteristic of mountain valleys. Following the terrain, the urban structure developed along the main road, which was laid along the Prut River. From the second half of the 19th century, this system was supplemented by the Transcarpathian railway. In the process of the field research, in addition to the inventory of discovered architectural objects, several historical spatial structures were localized, mostly neglected or lost today. During the research, two principle urban planning structures of different scales were identified: • the first is traced in the structure of historical public spaces of squares, streets, and promenades; • the second space was formed directly in the surroundings of significant complexes, sanatoriums, and boarding houses. The article examines the first planning structure in more detail. Theoretical models of public spaces for the identified three resorts were developed, in which the typological affinity and the presence of such basic architectural and town-planning elements as historical villa buildings, promenades, resort parks, beaches, etc. were recorded. All basic elements are grouped around one or more communication axes. It was defined that the development of public spaces of resort settlements can be adjusted in accordance with resort and recreation requirements, modern needs of users, taking into account their historical structure with the use of revalorization/revitalization methods.

Disparity Estimation of High-Resolution Remote Sensing Images with Dual-Scale Matching Network

As an essential task in remote sensing, disparity estimation of high-resolution stereo images is still confronted with intractable problems due to extremely complex scenes and dynamically changing disparities. Especially in areas containing texture-less regions, repetitive patterns, disparity discontinuities, and occlusions, stereo matching is difficult. Recently, convolutional neural networks have provided a new paradigm for disparity estimation, but it is difficult for current models to consider both accuracy and speed. This paper proposes a novel end-to-end network to overcome the aforementioned obstacles. The proposed network learns stereo matching at dual scales, in which the low one captures coarse-grained information while the high one captures fine-grained information, helpful for matching structures of different scales. Moreiver, we construct cost volumes from negative to positive values to make the network work well for both negative and nonnegative disparities since the disparity varies dramatically in remote sensing stereo images. A 3D encoder-decoder module formed by factorized 3D convolutions is introduced to adaptively learn cost aggregation, which is of high efficiency and able to alleviate the edge-fattening issue at disparity discontinuities and approximate the matching of occlusions. Besides, we use a refinement module that brings in shallow features as guidance to attain high-quality full-resolution disparity maps. The proposed network is compared with several typical models. Experimental results on a challenging dataset demonstrate that our network shows powerful learning and generalization abilities. It achieves convincing performance on both accuracy and efficiency, and improvements of stereo matching in these challenging areas are noteworthy.

The social topology of science in national and transnational contexts: the case of social sciences

The article explores the possibilities of application P. Bourdieu’s social topology in the studying of inequality in science in national and transnational contexts. It is argued that in the conditions of globalising science, discussions about its egalitarianism, which began approximately in the middle of the last century, are moving beyond national borders. For the purposes of studying global inequality in science, scholars often apply the theoretical frameworks of world-systems analysis, neo-institutionalism, and the theory of global governance. However, these theories often lead to reductionism which ignores the symbolic dimension of scientific activity. The article suggests reassessing the heuristic potentiality of P. Bourdieu’s social topology, which mitigates the mentioned drawback of other theories. The article aims to demonstrate the relevance of this theoretical framework for the study of inequality in different scales of scientific activity due to the fact that the French sociologist focused mainly on national academic systems. The article defines the general provisions of P. Bourdieu’s topological concept of the field and the units of the social order of the scientific field. It also demonstrates the role of various forms of capital in determining the structure of social space. Based on the case of social sciences, the article explores the formation of scientific fields, their interaction with other fields, and their structure in different scales. The structure of the scientific field on the national scale can be defined as a dichotomy of dominant – dominated or centre – periphery. On the transnational scale, this dichotomy is also relevant but it is represented by national fields. Among them, the dominant position is occupied by the United States and Great Britain, which have the largest amount of symbolic power. The structure of the transnational scientific space, however, is more complex and includes overlapping fields of national, regional and more global dimensions. The article argued that applying the theoretical framework of the field to the study of the transnational scientific field will remain tied to the definition and explanation of the peculiarities and the interaction of national scientific fields as long as national states keep their institutional boundaries in scientific activity.

A Study of Magnetic Conjugate Property in a Large Density Irregularity Structure Using Hilbert‐Huang Transform

AbstractA large density irregularity structure in latitudinal extent was observed by the sun‐synchronous orbiting FORMOSAT‐5 satellite at 720 km topside ionosphere in the South American sector on November 24, 2018 during a magnetically quiet time. The observed density irregularity structure has a latitudinal extent of ∼30° across the dip equator, and a longitudinal width of ∼6°. Unlike previously studied equatorial plasma bubble structures with the airglow images that indicate hemispheric magnetic conjugate similarity, the gross feature of this large density irregularity structure indicates a north‐south hemispheric asymmetry in density variation. We use the Hilbert‐Huang Transform analysis to study the irregularity structure in different scales of density variations. It is found that the amplitude of density variations in the scale sizes from 22.5 to 450 km all indicate the hemispheric asymmetry. However, the spectral property of density variations in the two hemispheres is almost identical to each other. This implies that the density irregularity structure which originates from the same Rayleigh‐Taylor (RT) instability process has preserved the spectral characteristics inside the magnetic flux tube. Therefore, the cause that fails to preserve the magnetic conjugate property in the density irregularity structure comes from the fact that the background ionospheric density distribution has a north‐south hemispherical asymmetry in the beginning of the RT instability process. This hemispheric asymmetrical density distribution is caused by the seasonal variation of density distributions in the two hemispheres and the prevailing inter‐hemispheric neutral wind during solstices in the South American sector.

Scale- and Slice-aware Net (S2 aNet) for 3D segmentation of organs and musculoskeletal structures in pelvic MRI.

MRI of organs and musculoskeletal structures in the female pelvis presents a unique display of pelvic anatomy. Automated segmentation of pelvic structures plays an important role in personalized diagnosis and treatment on pelvic structures disease. Pelvic organ systems are very complicated, and it is a challenging task for 3D segmentation of massive pelvic structures on MRI. A new Scale- and Slice-aware Net ( aNet) is presented for 3D dense segmentation of 54 organs and musculoskeletal structures in female pelvic MR images. A Scale-aware module is designed to capture the spatial and semantic information of different-scale structures. A Slice-aware module is introduced to model similar spatial relationships of consecutive slices in 3D data. Moreover, aNet leverages a weight-adaptive loss optimization strategy to reinforce the supervision with more discriminative capability on hard samples and categories. Experiments have been performed on a pelvic MRI cohort of 27 MR images from 27 patient cases. Across the cohort and 54 categories of organs and musculoskeletal structures manually delineated, aNet was shown to outperform the UNet framework and other state-of-the-art fully convolutional networks in terms of sensitivity, Dice similarity coefficient and relative volume difference. The experimental results on the pelvic 3D MR dataset show that the proposed aNet achieves excellent segmentation results compared to other state-of-the-art models. To our knowledge, aNet is the first model to achieve 3D dense segmentation for 54 musculoskeletal structures on pelvic MRI, which will be leveraged to the clinical application under the support of more cases in the future.

An Improved Universal Fusion Algorithm for Constructing 3D Multiscale Porous Media

AbstractVarious types of porous media materials inherently contain pore structures of different scales, ranging from nanoscale to millimeter scale. Due to the limitations of the existing imaging technology, it is challenging and intractable for any single method to obtain and characterize the multiscale pore structure features of porous media accurately and comprehensively. To address the issue, according to the inherent logical correspondence and mutual conversion relationship between different‐scale image pixels, we propose an improved universal fusion algorithm for constructing three‐dimensional (3D) multiscale porous media. We successfully applied this algorithm to the construction of multiscale pore structure model of carbonate rock, sandstone and coal, and subsequently made quantitative extractions and characterizations of their pore structure characteristics. In addition, the finite element method (FEM) was used to calculate their absolute permeability. The results show that the improved fusion algorithm can effectively solve the problem of pore bias of the existing algorithm, which reduces the porosity of the multiscale model to a certain extent, while maintaining good pore interconnectivity. Besides, the multiscale model obtained by the improved fusion algorithm has a wider pore size distribution interval than that of the existing algorithm, and the absolute permeability of the former, computed using the FEM, is closer to the laboratory‐measured value than that of the latter.

Minimal multi-scale dynamics of near-wall turbulence

Abstract

The effect of baffle on flow structures and dynamics stirred by pitch blade turbine

•In order for a better understanding of how baffle impacts on the flow field stirred by pitched blade turbine (PBT), the Particle Image Velocimetry (PIV) experiment was conducted in baffled and unbaffled tank, with time-averaged method, phase-resolved method and Proper Orthogonal Decomposition (POD) method applied to analyze the turbulent characteristics. The POD quadruple decomposition method was adopted to decompose the flow structures of different scales. As indicated by the experimental results, in the measured area, an independent circulation area develops under the impeller, thus forming a pattern of double circulation flow in the unbaffled tank. There is a relatively concentrated distribution of incoherent flow structures in the stirred flow field, and these small-scale flow structures hinder transfer to the whole stirred tank, which makes it easy for the difference in local concentration to arise. With the addition of baffle, the axial discharge of fluid is enhanced, and the independent circulation area under the turbine shows change, and the large-scale convection of main body develops. The stirring-induced incoherent flow structure shows a wider range of distribution, while the small-scale structure under the stirring tank creates a more favorable condition for the diffusion into the whole stirred tank.

A Visualization Framework for Multi-scale Coherent Structures in Taylor-Couette Turbulence.

Taylor-Couette flow (TCF) is the turbulent fluid motion created between two concentric and independently rotating cylinders. It has been heavily researched in fluid mechanics thanks to the various nonlinear dynamical phenomena that are exhibited in the flow. As many dense coherent structures overlap each other in TCF, it is challenging to isolate and visualize them, especially when the cylinder rotation ratio is changing. Previous approaches rely on 2D cross sections to study TCF due to its simplicity, which cannot provide the complete information of TCF. In the meantime, standard visualization techniques, such as volume rendering / iso-surfacing of certain attributes and the placement of integral curves/surfaces, usually produce cluttered visualization. To address this challenge and to support domain experts in the analysis of TCF, we developed a visualization framework to separate large-scale structures from the dense, small-scale structures and provide an effective visual representation of these structures. Instead of using a single physical attribute as the standard approach which cannot efficiently separate structures in different scales for TCF, we adapt the feature level-set method to combine multiple attributes and use them as a filter to separate large- and small-scale structures. To visualize these structures, we apply the iso-surface extraction on the kernel density estimate of the distance field generated from the feature level-set. The proposed methods successfully reveal 3D large-scale coherent structures of TCF with different control parameter settings, which are difficult to achieve with the conventional methods.

Modeling the wake dynamics of a marine hydrokinetic turbine using different actuator representations

Numerical models play a fundamental role in the development of marine hydrokinetic (MHK) turbines, as they can evaluate their performance and assess interactions with the local environment. Actuator representations that incorporate a force in the momentum equation of the flow are commonly used in numerical models to study the complex dynamics of wakes generated by the devices. However, the implications of adopting any of these approaches in simulations of turbulent wakes are not yet clear. To understand the effects produced by different approaches, we carry out simulations using a coherent-structure resolving turbulence model, for which we test three actuator representations: Actuator Disk, Blade-Element Momentum, and Actuator Lines. We reproduce an experiment with a horizontal-axis turbine and show the influence of each formulation on the mean flow and on the dynamics of the wake. In all three cases, unsteady large-scale vortices govern the flow statistics, but while the mean flow is captured reasonably well by all models, they produce structures of different scales and rotational features that control the details of wake recovery. These new insights can help define the most appropriate model for each specific flow and improve predictions at different spatial scales in future investigations.

Investigation of an optimal pulsed jet mixing and combustion in supersonic crossflow

The enhanced mixing and combustion mechanism of pulsed sonic jet with optimal frequency in supersonic crossflow with a 10° ramp has been investigated using Large Eddy Simulation (LES). The results show that the energetic structures from the barrel shock and shear vortex are further enlarged at the phase of 1/4T0 periodically due to the swing forward and backward effect of the bow shock. There coexists clockwise and counter-clockwise rotating shear layer vortex structures in the pulsed jet, while only counter-clockwise rotating shear layer vortex structure is found in the steady case. The mixing process and the flame distribution are significantly affected by these structures of different scales. The reflected shock waves in the transverse jet in supersonic crossflow have strong coupling effects with the heat release rate. The pulsed jet is also found to improve the non-premixed dominant heat release rate, but not the premixed one. The mechanism of enhanced mixing and combustion efficiency relevant to the optimal frequency of 50 kHz is studied with Power Spectral Density (PSD) and wavelet analysis, and it is interesting to notice that the optimal pulsed jet frequency has strong coupling effects with the bow shock swing back and forward frequency, the jet shear layer and barrel shock frequencies (i.e., 50 kHz). However, for the non-pulsed steady case, the bow shock characteristic frequency is found to be 40 kHz, which suggests the optimal pulsed jet frequency can be 40 kHz. In order to further validate it, Unsteady Reynolds Averaged Navier Stokes (URANS) simulations have been performed with the pulsed jet frequency of 40 kHz. It is optimising to see that the mixing and combustion efficiency are further improved.

The effect of vortices structures on the flow-induced vibration of three flexible tandem cylinders

Flow-induced vibration (FIV) is a phenomenon oftentimes occurring in practical situations where flexible cylinders are immersed in an oncoming flow. Understanding the FIV characteristics in different vortex structures plays an important role in vibration control and utilization of engineering structures, such as offshore stacks and bladeless wind turbines. A detailed investigation on FIV of flexible tandem cylinders in the atmospheric boundary layer (ABL) under various vortex structures through setting strakes were conducted experimentally and numerically. The typical FIV responses and dynamic vortex evolutions at two specific spans, 1.4 and 3.2, were obtained in Ur∈[2, 35] to demonstrate the effect of different vortices. At the small span, FIV of tandem cylinders depends on the shear layers interaction, which behave as a uncircular bluff body with a pivot point near the downstream cylinder. Under the irregular small-scale vortices generated by the disturbed shear layer, the second instability of FIV of tandem cylinders at Ur≥20 can be excited. At the moderate span, the fully developed wake interference predominates. Among the effect of three different vortex structures, FIV of tandem cylinders cannot be promoted by steady vortices; clear FIV responses at Ur<10 with larger amplitudes can be observed in periodic oscillating vortices; FIV response of downstream cylinders at small reduced velocities decreases but another instability with divergent FIV will re-occur at Ur≥20 in irregular oncoming small-scale vortices. Finally, the vortices structures in different scales are assessed through the turbulence kinetic viscosity, and the instabilities of aerodynamic forces affected by the small-scale vortices are discussed.

Two transitions in spatial modular networks

Understanding the resilience of infrastructures, such as a transportation network, has significant importance for our daily life. Recently, a homogeneous spatial network model was developed for studying spatial embedded networks with characteristic link length such as power-grids and the brain. However, although many real-world networks are spatially embedded and their links have characteristics length such as pipelines, power lines or ground transportation lines they are not homogeneous but rather heterogeneous. For example, density of links within cities are significantly higher than between cities. Here we develop and study numerically and analytically a similar realistic heterogeneous spatial modular model using percolation process to better understand the effect of heterogeneity on such networks. The model assumes that inside a city there are many lines connecting different locations, while long lines between the cities are sparse and usually directly connecting only a few nearest neighbours cities in a two dimensional plane. We find that our heterogeneous model experiences two distinct continuous transitions, one when the cities disconnect from each other and the second when each city breaks apart. This is in contrast to the homogeneous model where a single transition is found. Although the critical threshold for site percolation in 2D grid remains an open question we analytically find the critical threshold for site percolation in this model. In addition, it has been found that the homogeneous model experience a single transition having a unique phenomenon called critical stretching where a geometric crossover from random to spatial structure in different scales found to stretch non-linearly with the characteristic length at criticality. In marked contrast, we show here that the heterogeneous model does not experience such a phenomenon indicating that critical stretching strongly depends on the network structure.

Analysis of dynamic stall flow field of high bypass fan rotor based on airworthiness certification

In order to ensure flight safety, the stall test is one of the most important steps in the airworthiness certification phase of civil aircraft. The twisted-swept fan is one of the most important components of the high bypass ratio engine. The unsteady flow field of the fan rotor stall condition is obtained by numerical simulation. At the same time, the time series flow field data of the stall condition flow field is acquired. The modal analysis of the unsteady flow field at stall condition was performed using the dynamic mode decomposition and proper orthogonal decomposition methods. Through modal identification of a large number of unsteady flow field data, the eigenvalues and corresponding modal information about the unsteady flow field change process are obtained. Finally, the evolution process of the unsteady flow field of the fan rotor under stall condition is visually demonstrated, and the coherent structures of different scales in the complex flow field under stall condition are revealed.

Effets des exercices de stabilisation scapulaire sur l’activité musculaire de l’épaule et de l’avant-bras chez le violoniste

In this paper, we consider the problem of subspace clustering for image data under occlusion and gross spatially contiguous noise. The state of the art subspace clustering methods assume that the noise either follows independent Laplacian or Gaussian distributions. However, the realistic noise is much more complicated and exhibits different structures in different scales. To address this issue, we propose a multi-scale framework that extracts a clean self-expressive dictionary through an iterative approach and is capable of identifying probable corrupted elements in each sample. Using this information, not only we can estimate parameters of each subspace more accurately but also by optimizing a matrix completion problem based on group sparsity, we can recover corrupted regions more precisely and hence achieve higher clustering accuracy for corrupted samples. Numerical experiments on synthetic and real world data sets demonstrate the efficiency of our proposed framework in presence of occlusion and spatially contiguous noise.

Scaling features of price–volume cross correlation

Price without transaction makes no sense. Trading volume authenticates its corresponding price, so there exists mutual information and correlation between price and trading volume. We are curious about fractal features of this correlation and need to know how structures in different scales translate information. To explore the influence of investment size (trading volume), price-wise (gain/loss), and time-scale effects, we analyzed the price and trading volume and their coupling by applying the MF-DXA method. Our results imply that price, trading volume and price–volume coupling exhibit a power law and are also multifractal. Meanwhile, considering developed markets, the price–volume couplings are significantly negatively correlated. However, in emerging markets, price has less of a contribution in price–volume coupling. In emerging markets in comparison with the developed markets, trading volume and price are more independent.

Texture Smoothing Quality Assessment via Information Entropy

Image texture smoothing (ITS) aims at completely removing textures while preserving as much as possible different-scale structures of an image. However, few quality assessment metrics have been formulated to objectively evaluate the ITS results, due to the lack of ground-truth texture-free images. Considering both the smoothness of textures and the preservation of structures, we make the debut of objective evaluation of ITS results, and design an intuitive Texture Smoothness and Structural Similarity Index (T3SI) based on human perception. Specifically, we first intuitively select some patches which contain relatively more texture/structure information. We then employ the Edge Preservation Index and the Structural Similarity Index Measure to evaluate the texture smoothness and the structure similarity on the selected patches, respectively. We finally formulate the novel exponential entropy function to balance the texture smoothness and the structure similarity for the quality assessment of ITS. T3SI is objective, easy to use, simple to implement, and stable. An independent User Study is performed to verify our proposed T3SI, and large experiments show that T3SI competes successfully to the state-of-the-art metrics. Our code is publicly available.