Prebiotic Aggregates (Tissues) Emerging from Reaction–Diffusion: Formation Time, Configuration Entropy and Optimal Spatial Dimension

For the formation of a proto-tissue, rather than a protocell, the use of reactant dynamics in a finite spatial region is considered. The framework is established on the basic concepts of replication, diversity, and heredity. Heredity, in the sense of the continuity of information and alike traits, is characterized by the number of equivalent patterns conferring viability against selection processes. In the case of structural parameters and the diffusion coefficient of ribonucleic acid, the formation time ranges between a few years to some decades, depending on the spatial dimension (fractional or not). As long as equivalent patterns exist, the configuration entropy of proto-tissues can be defined and used as a practical tool. Consequently, the maximal diversity and weak fluctuations, for which proto-tissues can develop, occur at the spatial dimension 2.5.

Weighted Group Sparsity-Constrained Tensor Factorization for Hyperspectral Unmixing

Recently, unmixing methods based on nonnegative tensor factorization have played an important role in the decomposition of hyperspectral mixed pixels. According to the spatial prior knowledge, there are many regularizations designed to improve the performance of unmixing algorithms, such as the total variation (TV) regularization. However, these methods mostly ignore the similar characteristics among different spectral bands. To solve this problem, this paper proposes a group sparse regularization that uses the weighted constraint of the L2,1 norm, which can not only explore the similar characteristics of the hyperspectral image in the spectral dimension, but also keep the data smooth characteristics in the spatial dimension. In summary, a non-negative tensor factorization framework based on weighted group sparsity constraint is proposed for hyperspectral images. In addition, an effective alternating direction method of multipliers (ADMM) algorithm is used to solve the algorithm proposed in this paper. Compared with the existing popular methods, experiments conducted on three real datasets fully demonstrate the effectiveness and advancement of the proposed method.

Measuring Spatial Distribution in the Banking System in Hungary

Over the past decade, due in part to the global economic crisis, a significant part of the bank branches have been closed in the European banking system, but in Hungary this proportion has been significantly higher than the European average. Therefore, the aim of the present study is to explore what aspects of commercial banks are taken into account when deciding where to be present within bank branches. This will also reveal the spatial dimension of public access to financial services. The present study seeks to answer the question of which socio-economic factors and in what form they affect the spatial structure of bank branches. The settlement-level examination can also provide additional indication of which settlements may be affected by further bank branch closures. Linear regression based on Ordinary Least Squares (OLS) parameter estimation was used to explore the factors influencing the location of bank branches. In addition, the possible clustering of bank branches was observed, i.e., whether spatial autocorrelation was present at certain stages of the analysis. Geographically Weighted Regression (GWR) was also estimated in the present study. Based on the results of the research, the resident population, the proportion of enterprises per capita, the average income, the number of neighbouring bank branches and the type of settlement all proved to be significant factors that may encourage decision-makers to establish a bank branch.

A parametric and feasibility study for data sampling of the dynamic mode decomposition: range, resolution, and universal convergence states

Scientific research and engineering practice often require the modeling and decomposition of nonlinear systems. The dynamic mode decomposition (DMD) is a novel Koopman-based technique that effectively dissects high-dimensional nonlinear systems into periodically distinct constituents on reduced-order subspaces. As a novel mathematical hatchling, the DMD bears vast potentials yet an equal degree of unknown. This effort investigates the nuances of DMD sampling with an engineering-oriented emphasis. It aimed at elucidating how sampling range and resolution affect the convergence of DMD modes. We employed the most classical nonlinear system in fluid mechanics as the test subject—the turbulent free-shear flow over a prism—for optimal pertinency. We numerically simulated the flow by the dynamic-stress Large-Eddies Simulation with Near-Wall Resolution. With the large-quantity, high-fidelity data, we parametrized and identified four global convergence states: Initialization, Transition, Stabilization, and Divergence with increasing sampling range. Results showed that Stabilization is the optimal state for modal convergence, in which DMD output becomes independent of the sampling range. The Initialization state also yields sufficient accuracy for most system reconstruction tasks. Moreover, defying popular beliefs, over-sampling causes algorithmic instability: as the temporal dimension, n, approaches and transcends the spatial dimension, m (i.e., m < n), the output diverges and becomes meaningless. Additionally, the convergence of the sampling resolution depends on the mode-specific dynamics, such that the resolution of 15 frames per cycle for target activities is suggested for most engineering implementations. Finally, a bi-parametric study revealed that the convergence of the sampling range and resolution are mutually independent.

Case-Crossover Spatial Lag Grid Differences Between Aerosol Optical Depth-PM2.5 and Respiratory-Cardiovascular Emergency Department Visits and Inpatient Hospitalizations in Baltimore, Maryland, USA: Identification of Homogeneous Spatial Areas

Optimal use of aerosol optical depth (AOD)-PM2.5 fused surfaces in epidemiologic studies requires homogeneous temporal and spatial fused surfaces. No analytic method is currently available to evaluate the spatial dimension. The temporal case-crossover design was modified to assess the association between Community Multiscale Air Quality (CMAQ) lag grids and four respiratory-cardiovascular hospital events. The maximum number of adjacent lag grids with the expo-sure-health outcome association determined the size of the homogeneous spatial area. The largest homogeneous spatial area included 5 grids (720 km2) and the smallest 2 grids (288 km2). PMC and PMCK analyses of ED asthma, IP asthma, IP MI, and IP HF were significantly higher in rural grids without air monitors than in urban with air monitors at lag grids 0, 1, and 01. Grids without air monitors had higher AOD-PM2.5 concentration levels, poverty percent, population density, and environmental hazards than grids with air monitors. ED asthma, IP MI, and HF PMCK ORs were significantly higher during the warm season than during the cold season at lag grids 0, 1, 01, and 04. The possibility of elevated fine PM and other demographic and environmental risk factors contributing to elevated respiratory-cardiovascular diseases in persons residing in rural areas was discussed.

Toggle-like current-induced Bloch point dynamics of 3D skyrmion strings in a room-temperature nanowire

Research into practical applications of magnetic skyrmions, nanoscale solitons with interesting topological and transport properties [1,2], has traditionally focused on two dimensional (2D) thin-film systems[3,4]. However, the recent observation of novel three dimensional (3D) skyrmion-like structures, such as hopfions [5], skyrmion strings (SkS) [6-9], skyrmion bundles [11] and skyrmion braids [12], motivates the investigation of new designs, aiming to exploit the third spatial dimension for more compact and higher performance spintronic devices in 3D or curvilinear geometries [13-15]. A crucial requirement of such device schemes is the control of the 3D magnetic structures via charge or spin currents, which has yet to be experimentally observed. In this work, we utilise real-space imaging to investigate the dynamics of a 3D SkS within a nanowire of Co8Zn9Mn3 at room temperature. Utilising single, nanoscale current pulses, we demonstrate current-induced nucleation of a single SkS, and a toggle-like positional switching of an individual Bloch point at the end of a SkS. The observations highlight the possibility to locally manipulate 3D topological spin textures, opening up a range of design concepts for future 3D spintronic devices.

Possibilities of Developing Sustainable World by Introducing Bioeconomy: Global Perspective

At the time of the study, the world economy is attempting to form a resource-efficient policy. The purpose of this study is to investigate the evolution of the development of strategies and tactics of bioeconomic policy in the international space. The study substantiated the specific features of the implementation of special state and regional programmes of the advanced countries of the world, which differ in socio-economic ideas and prospects for their implementation. The comparative review of strategies identified similarities and differences between them, which allowed to differentiate strategic documents for the implementation of bioeconomic policy in certain areas. The study provides graphic visualisation of distribution of the countries according to the established orientation. The authors of the study proved the convergent difference of bioeconomic policy within each of the above areas by development goals, key objectives, and means of achieving them in a certain spatial dimension.

Development Importance of The Regional Development Program (Comparative Study Between Babylon and Maysan Provinces For 2019)

In this research, the relationship between the regional development program and achieving spatial development goals (a comparative study between Babylon and Maysan provinces for 2019) will be discussed, as well as the factors that lead to a kind of moderation in the development of the provinces, and whether these factors help to distribute the spatial budget between administrative units, based on the application of development fundamentals and in accordance with planning standards in order to achieve the development goals of the regional program. Distributed (100) forms divided into (n=50 samples of executives and administrators from Babylon province, n=50 samples of executives and administrators from Maysan province) who are employees working in different administrative units in both provinces. Applied the statistical package program for social sciences( statistical package for social science(SPSS) v.2 Through it, the link tool was used Correlation In applying this questionnaire, it was found that there is a correlation between the dimensions of the predictive variable program of the development of the regions and they are (institutional dimension, economic dimension, urban social dimension, environmental dimension), and also that there is a correlation between the dimensions of the predictive variable program of regional development and (spatial dimension) of the variable achieving the objectives of spatial development for the province of Babylon and Maysan. Based on the above, we have found that the improvement in the dimensions of the predictive variable program of the development of the provinces leads to the achievement of the objectives of spatial development and in accordance with the planning standards of the province of Babylon and Maysan, either weakness in the axes or dimensions of the predictive variable leads to weakness or failure to achieve development goals in the provinces of Babylon and Maysan.

The Spatial Dimension in Social Media Analysis

In the data revolution era, the availability of “voluntary” and “derived from social media” geographic information allowed the spatial dimension to gain attention in digital and web studies. The purpose of this work is to recognize the impact of this research stream on some methodological and theoretical issues. The first regards “critical algorithm studies” in order to understand what algorithms are used. The second concerns how these works conceive the space. The last two issues concern the disciplinary areas in which these researches take place and which are the ecological units taken into account. The authors answer these questions by analyzing, through a content analysis, the researches extracted with the PRISMA methodology that have used Twitter as a data source. The application of this procedure allows the authors to classify the analysis material, moving simultaneously on the four defined dimensions.

Multi-scale 3D-convolutional neural network for hyperspectral image classification

Deep Learning methods are state-of-the-art approaches for pixel-based hyperspectral images (HSI) classification. High classification accuracy has been achieved by extracting deep features from both spatial-spectral channels. However, the efficiency of such spatial-spectral approaches depends on the spatial dimension of each patch and there is no theoretically valid approach to find the optimum spatial dimension to be considered. It is more valid to extract spatial features by considering varying neighborhood scales in spatial dimensions. In this regard, this article proposes a deep convolutional neural network (CNN) model wherein three different multi-scale spatial-spectral patches are used to extract the features in both the spatial and spectral channels. In order to extract these potential features, the proposed deep learning architecture takes three patches various scales in spatial dimension. 3D convolution is performed on each selected patch and the process runs through entire image. The proposed is named as multi-scale three-dimensional convolutional neural network (MS-3DCNN). The efficiency of the proposed model is being verified through the experimental studies on three publicly available benchmark datasets including Pavia University, Indian Pines, and Salinas. It is empirically proved that the classification accuracy of the proposed model is improved when compared with the remaining state-of-the-art methods.