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.

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 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.

Cluster modeling of the short-range correlation of acoustically emitted scattering signals

As a widely used measurement technique in rock mechanics,spatial correlation modeling of acoustic emission(AE)scattering signals is attracting increasing focus for describing mechanical behavior quantitatively.Unlike the statistical description of the spatial distribution of randomly generated AE signals,spatial correlation modeling is based mainly on short-range correlation considering the interrelationship of adjacent signals.As a new idea from percolation models,the covering strategy is used to build the most representative cube cluster,which corresponds to the critical scale at peak stress.Its modeling process of critical cube cluster depends strongly on the full connection of the main fracture network,and the corresponding cube for coverage is termed the critical cube.The criticality pertains to not only the transition of local-to-whole connection of the fracture network but also the increasing-to-decreasing transition of the deviatoric stress with an obvious stress drop in the brittle failure of granite.Determining a reasonable critical cube guarantees the best observation scale for investigating the failure process.Besides,the topological connection induces the geometric criticality of three descriptors,namely anisotropy,pore fraction,and specific surface area,which are evaluated separately and effectively.The results show that cluster modeling based on the critical cube is effective and has criticality in both topology and geometry,as well as the triaxial behavior.Furthermore,the critical cube length presents a high confidence probability of being correlated to the mineral particle size.Besides,its pore fraction of cube cluster is influenced strongly by the critical cube length and confining pressure.

Quantitative assessment of the spatio-temporal correlations of seismic events induced by longwall coal mining

Rock failure process as a natural response to mining activities is associated with seismic events, which can pose a potential hazard to mine operators, equipment and infrastructures. Mining-induced seismicity has been found to be internally correlated in both time and space domains as a result of rock fracturing during progressive mining activities. Understanding the spatio-temporal(ST) correlation of mininginduced seismic events is an essential step to use seismic data for further analysis, such as rockburst prediction and caving assessment. However, there are no established methods to perform this critical task. Input parameters used for the prediction of seismic hazards, such as the time window of past data and effective prediction distance, are determined based on site-specific experience without statistical or physical reasons to support. Therefore, the accuracy of current seismic prediction methods is largely constrained, which can only be addressed by quantitively assessing the ST correlations of mininginduced seismicity. In this research, the ST correlation of seismic event energy collected from a study mine is quantitatively analysed using various statistical methods, including autocorrelation function(ACF), semivariogram and Moran’s I analysis. In addition, based on the integrated ST correlation assessment, seismic events are further classified into seven clusters, so as to assess the correlations within individual clusters. The correlation of seismic events is found to be quantitatively assessable, and their correlations may vary throughout the mineral extraction process.

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.

Study correlation vortices in the near-field of partially coherent vortex beams diffracted by an aperture

We have derived the analytical expression of the electric cross-spectral density in the near- field of partially coherent vortex beams diffracted by an aperture. Taking the Caussian Schell-model vortex beam as a typical example of partially coherent vortex beams, the spatial correlation properties and correlation vortices in the near-field of partially coherent vortex beams diffracted by a rectangle aperture are studied. It is shown that the off-axis displacement, spatial degree of coherence parameter, propagation distance, and the opening factor of the aperture affect the spectral degree of coherence and positions of correlation vortices. With the optimization algorithm, we obtain the symmetric distributing coherent vortex.

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.

Channel capacity of multiple-input multiple-output systems with transmit and receive correlation

In order to investigate the impact of channel model parameters on the channel capacity of a multipleinput multiple-output （MIMO） system, a novel method is proposed to explore the channel capacity under Rayleigh fiat fading with correlated transmit and receive antennas. The optimal transmitting direction which can achieve maximum channel capacity is derived using random matrices theory. In addition, the closed-form expression for the channel capacity of MIMO systems is given by utilizing the properties of Wishart distribution when SNR is high. Computer simulation results show that the channel capacity is maximized when the antenna spacing increases to a certain point, and furthermore, the larger the scattering angle is, the more quickly the channel capacity converges to its maximum. At high SNR （〉12 dB）, the estimation of capacity is close to its true wlue. And, when the same array configuration is adopted both at the transmitter and the receiver, the UCA yields higher channel capacity than ULA.

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.

Effect of spatially correlated noise on stochastic synchronization in globally coupled FitzHugh–Nagumo neuron systems

The phenomenon of stochastic synchronization in globally coupled FitzHugh–Nagumo（FHN） neuron system subjected to spatially correlated Gaussian noise is investigated based on dynamical mean-field approximation（DMA） and direct simulation（DS）. Results from DMA are in good quantitative or qualitative agreement with those from DS for weak noise intensity and larger system size. Whether the consisting single FHN neuron is staying at the resting state, subthreshold oscillatory regime, or the spiking state, our investigation shows that the synchronization ratio of the globally coupled system becomes higher as the noise correlation coefficient increases, and thus we conclude that spatial correlation has an active effect on stochastic synchronization, and the neurons can achieve complete synchronization in the sense of statistics when the noise correlation coefficient tends to one. Our investigation also discloses that the noise spatial correlation plays the same beneficial role as the global coupling strength in enhancing stochastic synchronization in the ensemble. The result might be useful in understanding the information coding mechanism in neural systems.

Spatio-temporal variations in trends of vegetation and drought changes in relation to climate variability from 1982 to 2019 based on remote sensing data from East Asia

Studying the significant impacts on vegetation of drought due to global warming is crucial in order to understand its dynamics and interrelationships with temperature,rainfall,and normalized difference vegetation index(NDVI).These factors are linked to excesses drought frequency and severity on the regional scale,and their effect on vegetation remains an important topic for climate change study.East Asia is very sensitive and susceptible to climate change.In this study,we examined the effect of drought on the seasonal variations of vegetation in relation to climate variability and determined which growing seasons are most vulnerable to drought risk;and then explored the spatio-temporal evolution of the trend in drought changes in East Asia from 1982 to 2019.The data were studied using a series of several drought indexes,and the data were then classified using a heat map,box and whisker plot analysis,and principal component analysis.The various drought indexes from January to August improved rapidly,except for vegetation health index(VHI)and temperature condition index(TCI).While these indices were constant in September,they increased again in October,but in December,they showed a descending trend.The seasonal and monthly analysis of the drought indexes and the heat map confirmed that the East Asian region suffered from extreme droughts in 1984,1993,2007,and 2012among the study years.The distribution of the trend in drought changes indicated that more severe drought occurred in the northwestern region than in the southeastern area of East Asia.The drought tendency slope was used to describe the changes in drought events during 1982–2019 in the study region.The correlations among monthly precipitation anomaly percentage(NAP),NDVI,TCI,vegetation condition index(VCI),temperature vegetation drought index(TVDI),and VHI indicated considerably positive correlations,while considerably negative correlations were found among the three pairs of NDVI and VHI,TVDI and VHI,and NDVI and TCI.This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within the East Asian region.This study is a step forward in monitoring the seasonal variation of vegetation and variations in drought dynamics within the East Asian region,which will serve and contribute to the better management of vegetation,disaster risk,and drought in the East Asian region.

Spatial correlations in time and frequency domains between chlorophyll-a concentration and environmental factors in the Bohai Sea

Based on the reconstructed MODIS data and ECMWF reanalysis data from 2003 to 2021,spatial correlations between chlorophyll a(Chl a)and sea surface temperature(SST),photosynthetically available radiation(PAR),aerosol optical thickness(AOT),and wind speed(WS)in the Bohai Sea were analyzed from the perspective of time domain and frequency domain.Results indicate that the frequency domain analysis was more conducive to revealing the correlations between Chl a and environmental factors.The spatial pattern of time-domain correlations was similar to the isobaths of the Bohai Sea,which was positive in shallow waters and negative in deep waters for SST,PAR,and AOT,and was reversed for WS.Frequency-domain correlations were obtained by performing Fourier Transform and were higher than correlations in time domain.The spatial distributions indicated that the effects of SST and PAR on Chl a were greater than AOT and WS in the Bohai Sea.Additionally,cross-spectrum analysis was applied to explore the response relationships.A depth-dependent pattern was shown in correlations and time lags,indicating that the influential mechanism of environmental factors on Chl-a concentration is related to seawater depth.

On the Ability of the Regional Climate Model RIEMS to Simulate the Present Climate over Asia

A continuous 10-year simulation in Asia for the period of 1 July 1988 to 31 December 1998 was conducted using the Regional Integrated Environmental Model System （RIEMS） with NCEP Reanalysis II data as the driving fields. The model processes include surface physics state package （BATS le）, a Holtslag explicit planetary boundary layer formulation, a Grell cumulus parameterization, and a modified radiation package （CCM3）. Model-produced surface temperature and precipitation axe compared with observations from 1001 meteorology stations distributed over Asia and with the 0.5° × 0.5° CRU gridded dataset. The analysis results show that： （1） RIEMS reproduces well the spatial pattern and the seasonal cycle of surface temperature and precipitation; （2） When regionally averaged, the seasonal mean temperature biases are within 1-2℃. For precipitation, the model tends to give better simulation in winter than in summer, and seasonal precipitation biases are mostly in the range of - 12%-50%; （3） Spatial correlation coefficients between observed and simulated seasonal precipitation are higher in north of the Yangtze River than in the south and higher in winter than in summer; （4） RIEMS can well reproduce the spatial pattern of seasonal mean sea level pressure. In winter, the model-simulated Siberian high is stronger than the observed. In summer, the simulated subtropical high is shifted northwestwards; （5） The temporal evolution of the East Asia summer monsoon rain belt, with steady phases separated by more rapid transitions, is reproduced.

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.