Spatial correlations in ground motion intensity measuring from the 2023 Türkiye earthquake

When evaluating an area's seismic risk or resilience,it is necessary to use the spatial correlation to analyze the ground motion parameters of multiple sites together in an earthquake.These two large earthquakes in Türkiye provided the possibility for spatial correlation analysis of ground motion intensity measurements in this area.Based on the strong motion records provided by The Disaster and Emergency Management Authority of Türkiye(AFAD),this study uses the local ground motion prediction equation in Türkiye to give spatial correlation analysis of Intensity Measurements.This study gives an exponential model based on a semivariogram and compares it with the correlation model obtained from previous studies.

Spatial Correlation Module for Classification of Multi-Label Ocular Diseases Using Color Fundus Images

To prevent irreversible damage to one’s eyesight,ocular diseases(ODs)need to be recognized and treated immediately.Color fundus imaging(CFI)is a screening technology that is both effective and economical.According to CFIs,the early stages of the disease are characterized by a paucity of observable symptoms,which necessitates the prompt creation of automated and robust diagnostic algorithms.The traditional research focuses on image-level diagnostics that attend to the left and right eyes in isolation without making use of pertinent correlation data between the two sets of eyes.In addition,they usually only target one or a few different kinds of eye diseases at the same time.In this study,we design a patient-level multi-label OD(PLML_ODs)classification model that is based on a spatial correlation network(SCNet).This model takes into consideration the relevance of patient-level diagnosis combining bilateral eyes and multi-label ODs classification.PLML_ODs is made up of three parts:a backbone convolutional neural network(CNN)for feature extraction i.e.,DenseNet-169,a SCNet for feature correlation,and a classifier for the development of classification scores.The DenseNet-169 is responsible for retrieving two separate sets of attributes,one from each of the left and right CFI.After then,the SCNet will record the correlations between the two feature sets on a pixel-by-pixel basis.After the attributes have been analyzed,they are integrated to provide a representation at the patient level.Throughout the whole process of ODs categorization,the patient-level representation will be used.The efficacy of the PLML_ODs is examined using a soft margin loss on a dataset that is readily accessible to the public,and the results reveal that the classification performance is significantly improved when compared to several baseline approaches.

Spatial correlation of the high intensity zone in deep-water acoustic field

The spatial correlations of acoustic field have important implications for underwater target detection and other ap- plications in deep water. In this paper, the spatial correlations of the high intensity zone in the deep-water acoustic field are investigated by using the experimental data obtained in the South China Sea. The experimental results show that the structures of the spatial correlation coefficient at different ranges and depths are similar to the transmission loss structure in deep water. The main reason for this phenomenon is analyzed by combining the normal mode theory with the ray theory. It is shown that the received signals in the high intensity zone mainly include one or two main pulses which are contributed by the interference of a group of waterbome modes with similar phases. The horizontal-longitudinal correlations at the same receiver depth but in different high intensity zones are analyzed. At some positions, more pulses are received in the arrival structure of the signal due to bottom reflection and the horizontal-longitudinal correlation coefficient decreases accordingly. The multi-path arrival structure of receiving signal becomes more complex with increasing receiver depth.

Spatial correlation-based characterization of acoustic emission signal-cloud in a granite sample by a cube clustering approach

To extract more in-depth information of acoustic emission(AE)signal-cloud in rock failure under triaxial compression,the spatial correlation of scattering AE events in a granite sample is effectively described by the cube-cluster model.First,the complete connection of the fracture network is regarded as a critical state.Then,according to the Hoshen-Kopelman(HK)algorithm,the real-time estimation of fracture con-nection is effectively made and a dichotomy between cube size and pore fraction is suggested to solve such a challenge of the one-to-one match between complete connection and cluster size.After,the 3D cube clusters are decomposed into orthogonal layer clusters,which are then transformed into the ellip-soid models.Correspondingly,the anisotropy evolution of fracture network could be visualized by three orthogonal ellipsoids and quantitatively described by aspect ratio.Besides,the other three quantities of centroid axis length,porosity,and fracture angle are analyzed to evaluate the evolution of cube cluster.The result shows the sample dilatancy is strongly correlated to four quantities of aspect ratio,centroid axis length,and porosity as well as fracture angle.Besides,the cube cluster model shows a potential pos-sibility to predict the evolution of fracture angle.So,the cube cluster model provides an in-depth view of spatial correlation to describe the AE signal-cloud.

Low spatial correlation at base station uniform linear antennas

A spatial channel propagation model is presented. Consider a uniform linear antenna （ULA） at the base station （BS） and narrowband signals transmitted at the mobile. In two types of propagating environments： indoor and outdoor, performance of low spatial correlation is investigated and some results are provided, which are significant to an,3. lyze the performance of diversity systems and configuration of army. The results also show that the configuration of array with either smaller angular spread or bigger angle of arrival （AOA） dominates the impact on spatial correlation, and that increasing angular spread or decreasing AOA diminishes, or even eliminates this impact.

Single foggy image restoration based on spatial correlation analysis of dark channel prior

Focusing on the degradation of foggy images, a restora- tion approach from a single image based on spatial correlation of dark channel prior is proposed. Firstly, the transmission of each pixel is estimated by the spatial correlation of dark channel prior. Secondly, a degradation model is utilized to restore the foggy image. Thirdly, the final recovered image, with enhanced contrast, is obtained by performing a post-processing technique based on just-noticeable difference. Experimental results demonstrate that the information of a foggy image can be recovered perfectly by the proposed method, even in the case of the abrupt depth changing scene.

Horizontal-Longitudinal Spatial Correlation of Acoustic Field with Deep Receiver in the Direct Zone in Deep Water

The horizontal-longitudinal correlation of acoustic field for the receiver near the bottom is analyzed by using nu- merical modeling. An approximate analytical solution of horizontal-longitudinal correlation coefficient is derived based on the ray method. Combining the characteristic of Lloyd＇s mirror interference pattern, the variability of acoustic field and its effect on horizontal-longitudinal spatial correlation are discussed. The theoretical pre- diction agrees well with the numerical results. Experimental results confirm the validity of analytical solution. Finally, the applicability of the analytical solution is summarized. The conclusion is beneficial for the design of bottom-moored array and the estimation of integral time for moving source localization.

Pseudo-Channel Matrix Truncation Based Spatial Correlation Mitigation in Massive MIMO

Massive multiple-input multiple-output(MIMO),a technique that can greatly increase spectral efficiency(SE)of cellular networks,has attracted significant interests in recent years.One of the major limitations of massive MIMO systems is pilot contamination,which will deteriorate the SE.The superimposed pilot-based scheme has been proved to be a viable method for pilot contamination reduction.However,it cannot break through another limitation of massive MIMO,i.e.,spatial correlation.In addition,it will also lead to interference between the pilot and user data since they are imposed together.In this paper,we try to tackle these two issues,which will be described as follows.Firstly,a column-wise asymptotically orthogonal matrix,named as pseudo-channel matrix,is developed by orthogonalization of received signal.To recover the information about the large-scale fading(LSF)coefficients,the pseudo-channel matrix is truncated according to the cardinality of adjacent users set(CAUS).By this means,spatial correlation can be mitigated effectively.Secondly,robust independent component analysis(RobustICA)is used to reduce the interference caused by user data,and as a result the system performance can be further improved.Numerical simulation results demonstrate the effectiveness of the proposed method.

Spatial correlation properties and phase singularity annihilation of Gaussian Schell-model beams in the focal region

By using the generalized Debye diffraction integral, this paper studies the spatial correlation properties and phase singularity annihilation of apertured Gaussian Schell-model （GSM） beams in the focal region. It is shown that the width of the spectral degree of coherence can be larger, less than or equal to the corresponding width of spectral density, which depends not only on the scalar coherence length of the beams, but also on the truncation parameter. With a gradual increase of the truncation parameter, a pair of phase singularities of the spectral degree of coherence in the focal plane approaches each other, resulting in subwavelength structures. Finally, the annihilation of pairs of phase singularities takes place at a certain value of the truncation parameter. With increasing scalar coherence length, the annihilation occurs at the larger truncation parameter. However, the creation process of phase singularities outside the focal plane is not found for GSM beams.

Capacity and Spatial Correlation Measurements of Compact MIMO Antennas

The dual-port compact multiple-input multiple-output(MIMO)dipole antennas with close spacing d of 0.5λand 0.3λare designed,and some electromagnetic band gap(EBG)structures are inserted between them to reduce mutual coupling.Those MIMO antennas with d=0.5λand 0.3λ,and with different mutual couplings are fabricated and measured,the channel capacity and correlation coefficient(CC)are analyzed and compared in a rich multipath reverberation chamber(RC),an office and a conference room.Results show that if d is reduced from 0.5λto 0.3λ,in the RCs,channel capacities of all the antennas are very close to that of the i.i.d.Rayleigh channel,although the average CCs are increased from 0.168 in the nonlossy RC to 0.269 in the lossy RC.In the office and conference rooms,compared with the RC,the average capacities of those antennas get a slight reduction,however,in most cases,the capacity of d=0.5λis larger than that of d=0.3λ,and the antennas with EBG have a larger capacity compared with the antennas without EBG,with a corresponding reduction of CC.A non-line-of-sight(NLOS)scenario of through-the-wall is also investigated.

Spatial Correlation in Typical Binary Polycondensation Systems: An Essential Extension of the Kirkwood-Buff Theory

We present the isothermal susceptibility(XT)for the typical binary polycondensation system of Af-Bg type,and relate XT to the weight-average degree of polymerization in terms of the Kirkwood-Buff(KB)theory.The investigation is based on a new expression of XT for mixtures,which is still expressed by the KB integrals(KBIs)but endowed with an explicit physical interpretation.For polymerization systems,it is proposed that the KBIs can be further decomposed according to whether there exists a bond between particles when conversions(extents of reaction)of functional groups are incorporated into the KBIs.In this way,XT is directly decomposed into its relevant components as well.This is especially useful to reveal the relationship between local structures and average properties of various polymerization systems.As a consequence,the effect of polymerization on XT is greatly simplified in comparison with the free energy route.Therefore,we have provided a very simple method to carry out some thermodynamic properties of polymerization systems.

Spatial correlations between urbanization and river water pollution in the heavily polluted area of Taihu Lake Basin, China

Water pollution in the Taihu Lake Basin has been the focus of attention in China and abroad for a long time, due to its position in the forefront of urban development in China. Based on data gathering and processing from 84 monitoring sections in this heavily polluted area, this study first analyzes spatial patterns of urbanization and the distribution of river water pollution, and then uses the GeoDa bivariate spatial autocorrelation model to investigate the spatial correlation between urbanization and river water pollution at the scale of township units. The results show that urbanization has adverse impacts on water pollution, and the influence varies in different levels of development areas. The urban township units have the highest level of urbanization and highest pollution, but the best water quality; the suburban units have lower level of urbanization, but higher pollution and worse water quality; however the rural units have the lowest level of urbanization and lowest pollution, mainly affected by upstream pollution, but worst water quality. Lastly, urban and rural planning committees, while actively promoting the process of development in the region, should gradually resolve the issue of pollution control lagging behind urban life and urban develop- ment, giving priority to construction of centralized sewage treatment facilities and associated pipeline network coverage in the rural areas and suburban areas.

Potential Assessment of Spatial Correlation to Improve Maximum Distributed PV Hosting Capacity of Distribution Networks

Successful distributed photovoltaic (PV) planning now requires a hosting capacity assessment process that accounts for an appropriate model of PV output and its uncertainty. This paper explores how the PV hosting capacity of distribution networks can be increased by means of spatial correlation among distributed PV outputs. To achieve this, a novel PV hosting capacity assessment method is proposed to account for arbitrary geographically dispersed distributed PVs. In this method, the empirical relation between the spatial correlation coefficient and distance is fitted by historical data in one place and then applied to model the joint probability distribution of PV outputs at a neighboring location. To derive the PV hosting capacity at candidate locations, a stochastic PV hosting capacity assessment model that aims to maximize the PV hosting capacity under thermal and voltage constraints is proposed. Benders decomposition algorithm is also employed to reduce the computational cost associated with the numerous sampling scenarios. Finally, a rural 59-bus distribution network in Suzhou, China, is used to demonstrate the effectiveness of the proposed PV hosting capacity assessment methodology and the significant benefits obtained by increasing geographical distance.

The effect of a layer of varying density on spatial correlation of sea-bottom backscattering signal

The research is about the effect of a layer of varying density of sea-bottom sediments on spatial correlation of sea-bottom backscattering. The relationship between scattering cross section and spatial correlation is that backscattering cross section decreases quickly and the spatial correlation becomes stronger as the incident angle increases. Therefore, the density- depth profile is introduced into sea-bottom high-frequency backscattering echo model, which is used to simulate sea-bottom backscattering and calculate the function of spatial correlation. The influence of the density gradient on spatial correlation of sea-bottom backscattering is investigated by analyzing the relations between vertical gradient of density and the scattering cross section. As can be seen from the simulation results, the impact of the density gradient on the spatial correlation is found more significant. While the density gradient increases, the scattering cross-section and the radius of the spatial correlation broaden, the spatial correlation becomes stronger. At the same time, the scattering cross-section decreases more quickly as the incident angle increases.

Examining residual spatial correlation in variation partitioning of beta diversity in a subtropical forest

Aims The relative roles of ecological processes in structuring beta diver-sity are usually quantified by variation partitioning of beta diversity with respect to environmental and spatial variables or gamma di-versity.However,if important environmental or spatial factors are omitted,or a scale mismatch occurs in the analysis,unaccounted spatial correlation will appear in the residual errors and lead to re-sidual spatial correlation and problematic inferences.Methods Multi-scale ordination(MSO)partitions the canonical ordination results by distance into a set of empirical variograms which charac-terize the spatial structures of explanatory,conditional and residual variance against distance.Then these variance components can be used to diagnose residual spatial correlation by checking assump-tions related to geostatistics or regression analysis.In this paper,we first illustrate the performance of MSO using a simulated data set with known properties,thus making statistical issues explicit.We then test for significant residual spatial correlation in beta diversity analyses of the Gutianshan(GTS)24-ha subtropical forest plot in eastern China.Important Findings Even though we used up to 24 topographic and edaphic variables mapped at high resolution and spatial variables representing spa-tial structures at all scales,we still found significant residual spatial correlation at the 10 m×10 m quadrat scale.This invalidated the analysis and inferences at this scale.We also show that MSO pro-vides a complementary tool to test for significant residual spatial correlation in beta diversity analyses.Our results provided a strong argument supporting the need to test for significant residual spatial correlation before interpreting the results of beta diversity analyses.

Tomlinson-Harashima precoding minimizing total MSE with transmitter spatial correlation

This paper proposes a Tomlinson-Harashima precoding （THP） transceiver for multiple-input multiple-output （MIMO） system, where the spatial correlation information at the transmitter is included in the channel state information （CSI） model. It derives the total mean square error （MSE） and its lower bound as a function of precoding matrix. Then, a precoding matrix and the closed-form expression of minimum MSE lower bound are obtained by use of optimization and matrix theory. By right-multiplying a proper unitary matrix to the above precoding matrix, the paper develops the optimal precoding matrix, thus the optimal transceiver matrices are achieved. Simulation results show that the total MSE performance of the proposed method outperforms the existing linear method and the naive THP method.

The effect of ocean wave on the vertical spatial correlation of ocean ambient noise

The effect of the correlation function of noise sources derived from the ocean wave spectrum on the vertical spatial correlation of ocean ambient noise is investigated. The spatial correlation models of ocean ambient noise usually assume that the surface noise sources are uncorrelated. This assumption can be used to explain some physical phenomena, but it is not consistent with the real situation. Considering the relation between the ocean wave motion and the ambient noise generated by wind, the spectrum of ocean wave is introduced to calculate the vertical correlation of ocean ambient noise as the correlation function of noise sources by using the Kuperman-Ingenito （K/I） noise model. The comparison of the simulations and the experimental data shows that the simulations of vertical correlation of ambient noise have some differences with the experimental data by assuming the noise sources are uncorrelated and the simulations of vertical correlation of ambient noise have a good agreement with the experimental data by using the correlation function of noise sources derived from the ocean wave spectrum under the situation of high wind speed.

A theory on spatial correlation and vertical directivity of surface-generated ambient noise in the sea

A theoretical model of ambient sea noise including surface noise sources and stratified medium ocean is discussed. The noise sources are assumed to be statistically independent directional point sources distributed over the ocean surface, and the effects of ocean environment on ambient noise are studied. The normal-mode theory of surface-generated noise is developed, and the normal-mode formula of the directional density function suitable for small grazing angles is analytically continued for being suitable for great grazing angles and consistent with the ray formula. The unified formulae for calculating the intensities, spatial correlation and vertical directivity of ambient sea noise are presented.

Delayed response to the photovoltaic performance in a double quantum dots photocell with spatially correlated fluctuation

A viable strategy for enhancing photovoltaic performance is to comprehend the underlying quantum physical regime of charge transfer in a double quantum dots(DQD) photocell. This work explored the photovoltaic performance dependent spatially correlated fluctuation in a DQD photocell. The effects of spatially correlated fluctuation on charge transfer and output photovoltaic efficiency were explored in a proposed DQD photocell model. The results revealed that the charge transport process and the time to peak photovoltaic efficiency were both significantly delayed by the spatially correlated fluctuation, while the anti-spatially correlated fluctuation reduced the output peak photovoltaic efficiency. Further results revealed that the delayed response could be suppressed by gap difference and tunneling coefficient within two dots. Subsequent investigation demonstrated that the delayed response was caused by the spatial correlation fluctuation slowing the generative process of noise-induced coherence, which had previously been proven to improve the quantum photovoltaic performance in quantum photocells. And the reduced photovoltaic properties were verified by the damaged noise-induced coherence owing to the anti-spatial correlation fluctuation and a hotter thermal ambient environment. The discovery of delayed response generated by the spatially correlated fluctuations will deepen the understanding of quantum features of electron transfer, as well as promises to take our understanding even further concerning quantum techniques for high efficiency DQD solar cells.

Spatial distribution pattern of Picea schrenkiana population in the Middle Tianshan Mountains and the relationship with topographic attributes

The spatial distribution of plant populations is an important feature of population structure and it de- termines the population＇s ecological preferences, biological characteristics and relationships with environmental factors. The point pattern analysis method was adopted to study the distribution pattern of Picea schrenkiana indi- viduals of different size classes and the correlations between two size classes as well as the impact of topog- raphical attributes on the population distribution. With increasing diameter at breast height, the plant density of the P. schrenkiana population showed a declining trend. Old trees showed a random distribution at a small spatial scale （0-12 m）, whereas saplings, small trees and big trees all had an aggregated distribution at all scales. With the increase of tree age, the scales at which maximal aggregation occurred gradually increased and the aggregation strength decreased. At a small scale （0-16 m）, all size classes showed a negative correlation and the larger the difference between tree size, the more significant the negative correlation. The number of medium, big and old trees had a significantly positive correlation with elevations, whereas the number of saplings and small trees was not significantly correlated with elevations. The numbers of saplings, small and medium trees showed a significant positive correlation with slope gradient, whereas the number of big trees was not significantly correlated, and the number of old trees was negatively correlated with gradient. With the exception of old trees, saplings, small, me- dium and big trees showed negative correlations with convexity index. The study provides a theoretical basis for the conservation, rehabilitation and sustainable management of forest ecosystems in the Tianshan Mountains.