Static Region Research Articles

4D dynamic spatial brain networks at rest linked to cognition show atypical variability and coupling in schizophrenia.

Despite increasing interest in the dynamics of functional brain networks, most studies focus on the changing relationships over time between spatially static networks or regions. Here we propose an approach to study dynamic spatial brain networks in human resting state functional magnetic resonance imaging (rsfMRI) data and evaluate the temporal changes in the volumes of these 4D networks. Our results show significant volumetric coupling (i.e., synchronized shrinkage and growth) between networks during the scan, that we refer to as dynamic spatial network connectivity (dSNC). We find that several features of such dynamic spatial brain networks are associated with cognition, with higher dynamic variability in these networks and higher volumetric coupling between network pairs positively associated with cognitive performance. We show that these networks are modulated differently in individuals with schizophrenia versus typical controls, resulting in network growth or shrinkage, as well as altered focus of activity within a network. Schizophrenia also shows lower spatial dynamical variability in several networks, and lower volumetric coupling between pairs of networks, thus upholding the role of dynamic spatial brain networks in cognitive impairment seen in schizophrenia. Our data show evidence for the importance of studying the typically overlooked voxel-wise changes within and between brain networks.

YPL-SLAM: A Simultaneous Localization and Mapping Algorithm for Point-line Fusion in Dynamic Environments.

Simultaneous Localization and Mapping (SLAM) is one of the key technologies with which to address the autonomous navigation of mobile robots, utilizing environmental features to determine a robot's position and create a map of its surroundings. Currently, visual SLAM algorithms typically yield precise and dependable outcomes in static environments, and many algorithms opt to filter out the feature points in dynamic regions. However, when there is an increase in the number of dynamic objects within the camera's view, this approach might result in decreased accuracy or tracking failures. Therefore, this study proposes a solution called YPL-SLAM based on ORB-SLAM2. The solution adds a target recognition and region segmentation module to determine the dynamic region, potential dynamic region, and static region; determines the state of the potential dynamic region using the RANSAC method with polar geometric constraints; and removes the dynamic feature points. It then extracts the line features of the non-dynamic region and finally performs the point-line fusion optimization process using a weighted fusion strategy, considering the image dynamic score and the number of successful feature point-line matches, thus ensuring the system's robustness and accuracy. A large number of experiments have been conducted using the publicly available TUM dataset to compare YPL-SLAM with globally leading SLAM algorithms. The results demonstrate that the new algorithm surpasses ORB-SLAM2 in terms of accuracy (with a maximum improvement of 96.1%) while also exhibiting a significantly enhanced operating speed compared to Dyna-SLAM.

A Static Security Region Analysis of New Power Systems Based on Improved Stochastic–Batch Gradient Pile Descent

The uncertainty in the new power system has increased, leading to limitations in traditional stability analysis methods. Therefore, considering the perspective of the three-dimensional static security region (SSR), we propose a novel approach for system static stability analysis. To address the slow training speed of traditional deep learning algorithms using batch gradient descent (BGD), we introduce an improved stochastic–batch gradient descent (S-BGD) search method that combines the advantages of stochastic gradient descent (SGD) in fast training. This method ensures both speed and precision in parameter training. Moreover, to tackle the problem of getting trapped in local optima and saddle points during parameter training, we draw inspiration from kinematic theory and propose a gradient pile (GP) training method. By utilizing accumulated gradients as parameter corrections, this method effectively avoids getting stuck in local optima and saddle points, thereby enhancing precision. Finally, we apply the proposed methods to construct the static security region for the IEEE-118 new power system using its data as samples, demonstrating the effectiveness of our approach.

Geometrical method for a fast practical static stability region evaluation of a smart microgrid

This paper introduces an innovative approach to the offline Static Security Assessment (SSA) of smart MicroGrids (MG). By defining a specific region in the operating hyperspace, the stability of a MG is evaluated in a practical way, through the study of violations of voltage limits settled by protection relays. This method determines whether operating points, generated by Economic Dispatch algorithms, are feasible or not. Unlike traditional methods, it doesn't require continuous training on large datasets if the system topology doesn’t change. The method proactively explores the operating region offline, enabling quick assessment of operational security. By analyzing the feasibility region in the hyperspace from a geometrical perspective, it provides rapid insights of the system security status. This eliminates the need for computationally expensive trajectory studies involving complex equations and online iterative procedures, as applied in energy function approaches and conventional methods like the continuation load flow. The methodology is tested by simulation on a case study reproducing a subset of the experimental MG installed at the PrInCE Laboratory of the Polytechnic University of Bari.

Numerical Investigation of the Influence of Different Suction and Discharge Ports on Scroll Expander Performance

Background: With the rapid consumption of non-renewable energy such as coal, oil and natural gas, the growing demand for environmental protection, the re-utilization of low-grade waste heat energy has become an important approach to improve energy utilization efficiency. As a new technology, organic Rankine cycle (ORC) power generation technology can make full use of and convert heat waste. Objective: Both the suction and discharge pressures of the scroll expander have a certain influence on the output and motion characteristics of the orbiting scroll. By studying the position and arrangement of the suction and discharge ports of the expander, a theoretical basis can be provided for the design of these ports. Methods: For the scroll expander using working fluid R134a, establishing the geometrical and three-dimensional models of the suction and discharge ports of the scroll expander with different positions and structures, based on the Computational Fluid Dynamics (CFD) method. Results/Discussion: Through comprehensive comparison, it was found that the structure of the original suction pipe outperformed any of the other structures; the fluid flow in the original discharge pipe was more complicated, and the simplified model of the commonly used scroll mechanical discharge pipe had the optimal performance. Conclusion: Compared with the original prototype SEI2, the suction port area is increased, and the suction port pulsation intensity coefficient and the suction pressure loss coefficient of the prototype SEI4 are reduced by 34.833% and 5.264% respectively, which can make the suction process of the expander more stable. Since the unilateral discharge ports Outlet3 and Outlet5 are located in the moving and static regions, respectively, there is a difference in the perturbation of the outlet fluid by the movable scroll, so that the gas pulsation intensity at Outlet3 is nearly double that of Outlet5.

Complex Rupture Features and Triggering during the 2022 Chishang Earthquake Sequence in Eastern Taiwan Estimated by InSAR, GPS, Strong Motion, and Teleseismic Waveform Evidence

Abstract The most recent 2022 Chishang earthquake sequence broke a long-time seismic quiescence on the Central Range fault (CRF), attracting lots of attention to the seismic behaviors and fault interactions of the Longitudinal Valley zone (LVZ), eastern Taiwan orogeny. However, detailed rupture features of both the foreshock and mainshock are still scarce. Here, available static displacements (i.e., Interferometric Synthetic Aperture Radar [InSAR], Global Positioning System [GPS], and strong motion [SM]) and kinematic waveform evidence (i.e., high-frequency GPS, strong motion, and teleseismic data) are used to delineate the rupture behaviors of both the foreshock and mainshock in this sequence. Our results indicate that the static displacements derived from strong-motion sites rival the high precision of GPS observations, replenishing the near-field constraints on the hanging wall together with InSAR and GPS. The optimal uniform slip models exhibit that both the foreshock and mainshock generally ruptured the west-dipping CRF along the south-southwest-striking direction with a steep dip angle >65°. The slip distribution models revealed that the rupture of foreshock and mainshock nearly ruptured a total length of CRF within 65 km from the Guanshan to Ruisui at a depth of above 14 km, and their slips are concentrated within one asperity and two asperities, respectively. The spatial evolution of this sequence’s ruptures exhibits a discontinued and separated pattern, and is well consistent with the local seismicity. Considering that the mainshock was initialed in a weak slip and negative static Coulomb stress region caused by the foreshock, the 2022 sequence occurrence is in favor of a preslip triggering mechanism. The rupture region of the 2022 sequence filled the “seismic gap” along the western flank of the LVZ and will promote the potential seismic hazard in this region.

Conformal geodesics and the evolution of spacetimes with positive Cosmological constant.

This article provides a discussion on the construction of conformal Gaussian gauge systems to study the evolution of solutions to the Einstein field equations with positive Cosmological constant. This is done by means of a gauge based on the properties of conformal geodesics. The use of this gauge, combined with the extended conformal Einstein field equations, yields evolution equations in the form of a symmetric hyperbolic system for which standard Cauchy stability results can be employed. This strategy is used to study the global properties of de Sitter-like spacetimes with constant negative scalar curvature. It is then adapted to study the evolution of the Schwarzschild-de Sitter spacetime in the static region near the conformal boundary. This review is based on Minucci et al. 2021 Class. Quantum Grav. 38, 145026. (doi:10.1088/1361-6382/ac0356) and Minucci et al. 2023 Class. Quantum Grav. 40, 145005. (doi:10.1088/1361-6382/acdb3f). This article is part of a discussion meeting issue 'At the interface of asymptotics, conformal methods and analysis in general relativity'.

Geometrizing the partial entanglement entropy: from PEE threads to bit threads

We give a scheme to geometrize the partial entanglement entropy (PEE) for holographic CFT in the context of AdS/CFT. More explicitly, given a point x we geometrize the two-point PEEs between x and any other points in terms of the bulk geodesics connecting these two points. We refer to these geodesics as the PEE threads, which can be naturally regarded as the integral curves of a divergenceless vector field Vxμ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {V}_{\ extbf{x}}^{\\mu } $$\\end{document}, which we call PEE thread flow. The norm of Vxμ\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ {V}_{\ extbf{x}}^{\\mu } $$\\end{document} that characterizes the density of the PEE threads can be determined by some physical requirements of the PEE. We show that, for any static interval or spherical region A, a unique bit thread configuration can be generated from the PEE thread configuration determined by the state. Hence, the non-intrinsic bit threads are emergent from the intrinsic PEE threads. For static disconnected intervals, the vector fields describing a divergenceless flow is no longer suitable to reproduce the RT formula. We weight a PEE thread with the number of times it intersects with any homologous surface. Instead, the RT formula is perfectly reformulated by the minimization of the summation of PEE threads with all possible assignment of weights.

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

In an integrated electricity-gas system (IEGS), load fluctuations affect not only the voltage in the power system but also the gas pressure in the natural gas system. The static voltage stability region (SVSR) method is a tool for analyzing the overall static voltage stability in a power system. However, in an IEGS, the SVSR boundary may be overly optimistic because the gas pressure may collapse before the voltage collapses. Thus, the SVSR method cannot be directly applied to an IEGS. In this paper, the concept of the SVSR is extended to the IEGS-static stability region (SSR) while considering voltage and gas pressure. First, criteria for static gas pressure stability in a natural gas system are proposed, based on the static voltage stability criteria in a power system. Then, the IEGS-SSR is defined as a set of active power injections that satisfies multi-energy flow (MEF) equations and static voltage and gas pressure stability constraints in the active power injection space of natural gas-fired generator units (NGUs). To determine the IEGS-SSR, a continuation MEF (CMEF) method is employed to trace the boundary point in one specific NGU scheduling direction. A multidimensional hyperplane sampling method is also proposed to sample the NGU scheduling directions evenly. The obtained boundary points are further used to form the IEGS-SSR in three-dimensional (3D) space via a Delaunay triangulation hypersurface fitting method. Finally, the numerical results of typical case studies are presented to demonstrate that the proposed method can effectively form the IEGS-SSR, providing a tool for IEGS online monitoring and dispatching.

Influence of Geomagnetic Storms on Power System Static Voltage Security

The adverse effects of geomagnetic storms on power systems have been confirmed by numerous examples and observations. However, there remains a dearth of research on the quantitative assessment of the safety risks of a system under extreme geomagnetic storm conditions. Accordingly, in this study, we developed a risk assessment model for magnetic storm disasters based on the static voltage security region theory from the global perspective of power grid security. First, we determined the boundary shape of the static security region of a system under magnetic storm conditions and analyzed its influence on the voltage stability of the system from a regional perspective. Subsequently, a static safe-distance index was proposed to characterize the influence of a magnetic storm disaster on the system voltage. Considering the uncertainty in the injected power during a magnetic storm, we calculated the static voltage instability probability of the system. Through probability index analysis, a probabilistic safety assessment of the system under magnetic storm conditions was performed, and its overall static voltage safety level was measured. Finally, a simulation analysis based on the UIUC 150 node showed the proposed method to be reasonable and effective.

Evaluating influences of deposition direction and state-dependence on large deformation processes of granular column collapse

This paper examines the impacts of deposition direction and density of granular soils on their large deformation behavior encapsulated by column collapse processes. We combine a critical state-based, anisotropic constitutive model for sand and material point method (MPM). The constitutive model includes state- and fabric-dependent dilatancy and hardening, thus accounting for the effects of density and deposition direction on the mechanical behavior of soils. The MPM model is first validated against experimental results. We then investigate the fundamental connections between local constitutive properties of soils (e.g., friction and dilation) and global column collapse response. Based on these correlations, this work further studies how material density and deposition direction influence collapse behavior, including run-out distance, residual height, and slope angle of the static region. Results indicate that run-out distance is relatively insensitive to initial soil density but can be significantly altered by the deposition direction of soils. Peak run-out distance is observed as the deposition direction is aligned with sliding band formed within the granular column. Moreover, a higher density or a smaller inclination of deposit direction leads to a greater residual height and a steeper slope of the static region. The mechanisms of above effects from soil properties perspectives are discussed.

Risk-Aware Operating Regions for PV-Rich Distribution Networks Considering Irradiance Variability

This paper proposes a framework to identify, visualize, and quantify risk of potential over/under voltage due to annual energy consumption and PV generation growth. The stochastic modeling considers the following: (i) Active and reactive power profiles for distribution transformers, dependent on annual energy consumption and activity in the serviced areas. (ii) Variable solar irradiance profiles that allow a broader range of PV generation scenarios for sunny, overcast, and cloudy days. The proposed framework uses multivariate- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$t$</tex-math></inline-formula> copulas to model temporal correlations between random variables to generate synthetic scenarios. A probabilistic power flow is computed using the generated scenarios to define critical static operating regions. Results show that classical approaches may underestimate the maximum PV capacity of distribution networks when local irradiance conditions are not considered. Moreover, it is found that including annual energy consumption growth is critical to establishing realistic PV installation capacity limits. Finally, a sensitivity analysis shows that taking a 5% of overvoltage risk could increase up to 15% of the PV installed capacity limits.

Optimization of 3D dynamic speech MRI: Poisson-disc undersampling and locally higher-rank reconstruction through partial separability model with regional optimized temporal basis.

To improve the spatiotemporal qualities of images and dynamics of speech MRI through an improved data sampling and image reconstruction approach. For data acquisition, we used a Poisson-disc random under sampling scheme that reduced the undersampling coherence. For image reconstruction, we proposed a novel locally higher-rank partial separability model. This reconstruction model represented the oral and static regions using separate low-rank subspaces, therefore, preserving their distinct temporal signal characteristics. Regional optimized temporal basis was determined from the regional-optimized virtual coil approach. Overall, we achieved a better spatiotemporal image reconstruction quality with the potential of reducing total acquisition time by 50%. The proposed method was demonstrated through several 2-mm isotropic, 64 mm total thickness, dynamic acquisitions with 40 frames per second and compared to the previous approach using a global subspace model along with other k-space sampling patterns. Individual timeframe images and temporal profiles of speech samples were shown to illustrate the ability of the Poisson-disc under sampling pattern in reducing total acquisition time. Temporal information of sagittal and coronal directions was also shown to illustrate the effectiveness of the locally higher-rank operator and regional optimized temporal basis. To compare the reconstruction qualities of different regions, voxel-wise temporal SNR analysis were performed. Poisson-disc sampling combined with a locally higher-rank model and a regional-optimized temporal basis can drastically improve the spatiotemporal image quality and provide a 50% reduction in overall acquisition time.

Heart rate estimation by leveraging static and dynamic region weights

Heart rate estimation by leveraging static and dynamic region weights

Dynamic and heterogeneity-sensitive urban network partitioning: a data-driven technique

Information of Connected Vehicles (CVs) could describe vehicular dynamics in much greater detail, enhancing the effectiveness of traffic control systems. One important such system is perimeter control, which can achieve better performance by incorporating the evolution of congestion into the identification of protected regions through a dynamic approach. However, little attention has been given to identifying such dynamic regions by developing CV-based network partitioning models in a spatiotemporal dimension. To address this gap, this paper proposes a three-module framework that (1) collects the relevant information of CVs, (2) performs initial partitioning based on some rational considerations, and (3) identifies the optimal protected regions through a partitioning evaluation, improvement, and iteration algorithm. The carried-out comparisons between perimeter control systems employing the resulting protected regions and those using static regions confirm that the proposed framework enhances the efficiency of perimeter control, even for CVs' penetration rates that are as low as 15%.

Feature selection based on the self-calibration of binocular camera extrinsic parameters

The accuracy of feature-based vision algorithms, including the self-calibration of binocular camera extrinsic parameters used in autonomous driving environment perception techniques relies heavily on the quality of the features extracted from the images. This study investigates the influence of the depth distance between objects and the camera, the feature points in different object regions, and the feature points in dynamic object regions on the self-calibration of binocular camera extrinsic parameters. To achieve this, the study first filters out different types of objects in the image through semantic segmentation. Then, it identifies the areas of dynamic objects and extracts the feature points in the static object region for the self-calibration of binocular camera extrinsic parameters. By calculating the baseline error of the binocular camera and the row alignment error of the matching feature points, this study evaluates the influence of feature points in dynamic object regions, feature points in different object regions, and feature points at different distances on the self-calibration algorithm. The experimental results demonstrate that feature points at static objects close to the camera are beneficial for the self-calibration of extrinsic parameters of binocular camera.

Multi-objective random-fuzzy optimal power flow of transmission-distribution interaction considering security region constraints

In order to deal with the static voltage stability region problem of the power system caused by the penetration of distributed energy resources, this paper presents an interactive random-fuzzy optimal power flow method for transmission-distribution network considering security region constraints. Firstly, based on the random-fuzzy theory, the output of wind power and multi-energy coupling energy hub connected to transmission-distribution network are obtained. On this basis, the security region model of transmission-distribution network is established. As the interaction and cooperation between multiple distribution networks and transmission network throughout the system are described, the global random-fuzzy model of transmission-distribution interaction is established. Then, the security domain opportunity constraints are incorporated into the multi-objective optimization model of transmission-distribution network. Finally, based on the improved IEEE30 bus transmission system and IEEE33 bus distribution system, the power flow of transmission-distribution interactive network under the proposed model is calculated. The simulation results validate the effectiveness of the proposed model and algorithm. The safe operation distance of the power grid system can be improved and the active power network loss and power generation cost can be reduced.

Heat flux characteristics of a single droplet splashing on the liquid film obtained with a thermal lattice Boltzmann method

The double-distribution-function thermal lattice Boltzmann method is employed to investigate the heat flux characteristics of single droplet impact on a liquid film above a heated wall. The effects of impact velocity, liquid film thickness, droplet radius, and viscosity coefficient on the average and instant heat flux distribution are analyzed. The droplet impact first breaks the steady-state thermal boundary layer in the impact region, causing the heat flux in the wall impact region to increase. This is because the temperature gradient between the liquid film and the wall increases as the droplet dives downward and expands. The velocity discontinuity at the liquid jet sheet prevents the transfer of the transverse velocity in the liquid film to the static region, yielding a transition region. Convective heat transfer is dominant in the impact and transition regions, while conductive heat transfer is dominant in the static region. Moreover, a large impact velocity promotes the synergy between the temperature and flow velocity fields, enhancing the heat transfer efficiency. The kinetic energy consumption of the droplet increases with the liquid film thickness, which causes the heat flux to decrease. The effect of droplet radius on the heat flux at the wall is minimal. Furthermore, an increased liquid viscosity is not beneficial for wall heat dissipation.

Algorithm for biological second messenger analysis with dynamic regions of interest.

Physiological function is regulated through cellular communication that is facilitated by multiple signaling molecules such as second messengers. Analysis of signal dynamics obtained from cell and tissue imaging is difficult because of intricate spatially and temporally distinct signals. Signal analysis tools based on static region of interest analysis may under- or overestimate signals in relation to region of interest size and location. Therefore, we developed an algorithm for biological signal detection and analysis based on dynamic regions of interest, where time-dependent polygonal regions of interest are automatically assigned to the changing perimeter of detected and segmented signals. This approach allows signal profiles to be rigorously and precisely tracked over time, eliminating the signal distortion observed with static methods. Integration of our approach with state-of-the-art image processing and particle tracking pipelines enabled the isolation of dynamic cellular signaling events and characterization of biological signaling patterns with distinct combinations of parameters including amplitude, duration, and spatial spread. Our algorithm was validated using synthetically generated datasets and compared with other available methods. Application of the algorithm to volumetric time-lapse hyperspectral images of cyclic adenosine monophosphate measurements in rat microvascular endothelial cells revealed distinct signal heterogeneity with respect to cell depth, confirming the utility of our approach for analysis of 5-dimensional data. In human tibial arteries, our approach allowed the identification of distinct calcium signal patterns associated with atherosclerosis. Our algorithm for automated detection and analysis of second messenger signals enables the decoding of signaling patterns in diverse tissues and identification of pathologic cellular responses.

Quench-Probe Setup as Analyzer of Fractionalized Entanglement Spreading.

We propose a novel spatially inhomogeneous setup for revealing quench-induced fractionalized excitations in entanglement dynamics. In this quench-probe setting, the region undergoing a quantum quench is tunnel coupled to a static region, the probe. Subsequently, the time-dependent entanglement signatures of a tunable subset of excitations propagating to the probe are monitored by energy selectivity. We exemplify the power of this generic approach by identifying a unique dynamical signature associated with the presence of an isolated Majorana zero mode in the postquench Hamiltonian. In this case excitations emitted from the topological part of the system give rise to a fractionalized jump of log(2)/2 in the entanglement entropy of the probe. This dynamical effect is highly sensitive to the localized nature of the Majorana zero mode, but does not require the preparation of a topological initial state.