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.

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.

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.

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 Analysis of the Aging Population and Socio-economic Factors of China:Global and Local Perspectives

Population aging has become an inevitable trend and exerted profound influences on socio-economic development in China.In this study,we utilized data from national population census and statistical yearbooks in 2010 and 2020 to explore spatio-temporal patterns of aging population and its coupling correlations with socio-economic factors from both global and local perspectives.The results from Local Indicators of Spatial Association(LISA)uncover notable spatial disparities in aging population rates,with higher rates concentrated in the eastern regions and lower rates in the western areas of the Chinese mainland.The results from the global correlation analysis with the changes in aging population rates show significant positive correlations with government interventions and industrial structures,but negatively correlated with economic development,social consumption,and medical facilities.From a local perspective,a Geographically Weighted(GW)correlation analysis is employed to uncover local correlations between aging trends and socio-economic factors.The insights gained from this technique not only underscore the complexity and diversity of economic implications stemming from population aging,but also provide invaluable guidance for crafting region-specific economic policies tailored to various stages of population aging.

Optimal training sequences for MIMO systems under correlated fading

The optimal design of training sequences for channel estimation in multiple-input multiple-output （MIMO） systems under spatially correlated fading is considered. The channel is assumed to be a block-fading model with spatial correlation known at both the transmitter and the receiver. To minimize the channel estimation error, optimal training sequences are designed to exploit full information of the spatial correlation under the criterion of minimum mean square error （MMSE）. It is investigated that the spatial correlation is helpful to decrease the estimation error and the proposed training sequences have good performance via simulations.

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 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 Characteristics and Change for Tree Species (Genera) Along Northeast China Transect (NECT)

The 16 tree species on Northeast China Transect (NECT) were analyzed from the change of geographical distribution, frequency and dominance pattern and the spatial correlation at landscape scale in 1986 and 1994. Pinus koraiensis Sieb. et Zucc. and Fraxinus rhynchophylla Hemsl. had spread rapidly towards west and east, respectively. The frontier form of species had close relation with its movement. The patch size of Pinus koraiensis , Populus davidiana Dode., Phellodendron amurense Rupr., Juglans mandshurica Maxim., Fraxinus mandshurica Rupr., Betula dahurica Pall., Picea koraiensis Nakai, Abies nephrolepis Maxim. and Larix olgeusis var. koreana Nakai decreased, however, Quercus mongolica Fisch., Betula costata Trautv., Acer mono Maxim., Tilia spp., Ulmus spp., Betula platyphylla Suk. and Fraxinus rhynchophylla increased. The frequency pattern of Populus davidiana , Betula platyphylla , Fraxinus rhynchophylla and Betula dahurica changed significantly. The dominance pattern of Populus davidiana , Tilia spp., Juglans mandshurica , Betula platyphylla , Betula dahurica and Abies nephrolepis changed significantly. The spatial correlation between Quercus mongolica and Betula dahurica , Betula costata and Picea spp., Betula costata and Abies nephrolepis , Picea spp. and Abies nephrolepis declined, however, the spatial correlation between Larix spp. and Betula platyphylla , Acer mono and Ulmus spp. increased.

Why Well Spread Probability Samples Are Balanced

When sampling from a finite population there is often auxiliary information available on unit level. Such information can be used to improve the estimation of the target parameter. We show that probability samples that are well spread in the auxiliary space are balanced, or approximately balanced, on the auxiliary variables. A consequence of this balancing effect is that the Horvitz-Thompson estimator will be a very good estimator for any target variable that can be well approximated by a Lipschitz continuous function of the auxiliary variables. Hence we give a theoretical motivation for use of well spread probability samples. Our conclusions imply that well spread samples, combined with the Horvitz- Thompson estimator, is a good strategy in a varsity of situations.

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.

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.

Spatial Correlation and Ecological Characteristics Analysis of Man-agement Area for Biodiversity Conservation and Relevant Regionalization

Formulation of different ecological zone plans according to the corresponding protection targets and the necessity of proper conservation policy is one of the measures to achieve the goal of ecological conservation in China.In order to clarify the interrelation among key ecological zone plans,this paper carried out the research on spatial relation of priority areas of biodiversity conservation and three key ecological areas(key ecological function areas,key regions of ecological service function,national nature reserves)and the research on ecological conditions,based on multi-scale ecological spatial theme information,which incorporates elements like ecological quality and type,and by the aid of spatial information analysis and GIS modeling.The results showed a contrastively fine spatial consistency with 68.8%of priority areas of biodiversity conservation overlapping with three key ecological areas.Although the environment in priority areas of biodiversity conservation were in good conditions,protection pressure is also increasing,powerful supervision and protection should not be ignored.The environmental conditions in the overlapping areas,as a whole,were superior to those in the non-overlapping areas.Since two areas have different characteristics,targeted protection measures should be formulated based on this difference,which will be very important for biodiversity conservation in priority areas of biodiversity conservation.

Spatial pattern dynamics among co-dominant populations in early secondary forests in Southwest China

The canopy of subtropical natural forests usually consists of several co-dominant populations(CDPs),which play a crucial role in forest structure,formation of the forest environment,and ecological function.However,little attention has been given to changes in spatial patterns in CDPs during natural succession.Cyclobalanopsis glauca(Thunb.)Oerst.,Quercus variabilis Blume,and Pinus yunnanensis var.tenuifolia W.C.Cheng & Y.W.Law are canopy species that form CDPs in zonal forests along the Nanpan River in southwest China.We used the g(r) function and its bivariate distribution model,g_(12)(r),which is based on distances between pairs of points,to explore the dynamics of the three CDP species with respect to distribution patterns and spatial correlations in two secondary forests(one 30-year-old forest [30-YF] and one 57-year-old forest [57-YF]).The following key results were obtained:(1) there was a clumped pattern in the 30-YF,but the intensity of aggregation varied among populations and life stages.The distribution pattern gradually shifted to become random with longer succes sion time(i.e.,30-YF vs.57-YF),expansion of the observation scale(r=0-20 m),and at later life stages.(2) Aside from the mid-sized C.glauca trees and large P.yunnanensis trees,the trees repulsed each other at certain scales(r=0-2,5-6,11-12,14-16 m) in the 30-YF.Almost all of the life stages in the CDPs were independently correlated.This independent correlation was exacerbated by a longer succession time.(3) An increase in life stages and longer succession also promoted independent changes in intraspecific correlations.(4) Intraspecific correlations were stronger than interspecific correlations.Our results showed that reducing exclusive competition is essential to coexistence in CDPs.Inter-and intra-specific repulsion may occur at the same time,but intraspecific repulsion was the main driving force behind the random distributions and independent correlations.

Is the “One Province One Rate” premium policy reasonable for Chinese crop insurance? The case in Jilin Province

Crop insurance in China is currently adopting the premium pricing strategy of "One Province One Rate", which appears to be in line with the systematic risk characteristics within crop insurance. This research aims to investigate the theoretical rationalization of this pricing strategy and its implications using the spatial lag model and the county-level data from the 45 corn plant counties of Jilin Province, China. Results corroborate that:(1) the spatial spillover effect of the corn yield risk is significant in Jilin but decreases rapidly when the risk unit includes more than eight counties; and(2) separating Jilin Province into eight risk zones for corn insurance will significantly reduce the high cross-subsidy phenomenon arising from the "One Province One Rate" strategy and shall benefit poor peasants in the region as well. This paper not only proves the existence of a systematic risk of crop insurance but also reveals that the spatial correlation and systemic features of the crop yield risk do not create a solid foundation for the current pricing strategy of "One Province One Rate". These conclusions will undoubtedly provide important references and empirical evidence for the role of China’s crop insurance in poverty alleviation.

Wavelet Denoising of Flight Flutter Testing Data for Improvement of Parameter Identification

The accuracy of modal parameter estimation plays a crucial role in flutter boundary prediction. A new wavelet denoising method is introduced for flight flutter testing data, which can improve the estimation of frequency domain identification algorithms. In this method, the testing data is first preprocessed with a gradient inverse weighted filter to initially lower the noise. The redundant wavelet transform is then used to decompose the signal into several levels. A “clean” input is recovered from the noisy data by level dependent thresholding approach, and the noise of output is reduced by a modified spatially selective noise filtration technique. The advantage of the wavelet denoising is illustrated by means of simulated and real data.

A geometric Model for the Spatial Correlation of an Acoustic Vector Field in Surface-generated Noise

Spatial correlation of sound pressure and particle velocity of the surface noise in horizontally stratified media was demonstrated, with directional noise sources uniformly distributed on the ocean surface. In the evaluation of particle velocity, plane wave approximation was applied to each incident ray. Due to the equivalence of the sound source correlation property and its directivity, solutions for the spatial correlation of the field were transformed into the integration of the coherent function generated by a single directional source. As a typical horizontally stratified media, surface noise in a perfect waveguide was investigated. Correlation coefficients given by normal mode and geometric models show satisfactory agreement. Also, the normalized covariance between sound pressure and the vertical component of particle velocity is proportional to acoustic absorption coefficient, while that of the surface noise in semi-infinitely homogeneous space is zero.

SPATIAL CORRELATION ANALYSIS OF CROP YIELD IN THE MIDDLE AND WEST OF JILIN PROVINCE

In this paper,spatial correlation of crop yield in the middle and west of Jilin Province is analyzed by us-ing the method of geostatistics semivariogram,taking the NDVI of NOAA/AVHRR spectrum data as the regionalized vari-able,aiming to provide theory and practical basis for field sampling of crop yield estimation using remote sensing.The ratio of nugget variance and sill of semivariograms are 21.1% and 9.7% in the west and middle regions in Jilin Province respectively.This shows that the crop yields are spatially correlated.The degree and range of correlation are far different in the different situations.In the west test region,the range is 49.9 km and the sill is 0.00019.In the middle testre-gion,the range is 16.5 km and the sill is0.00453.The dissimilarity in the western test region is larger than that in the middle one.The range in which the correlation existed of the former is far larger than the later.Different character is tics of spatial correlation of crop yield are decided by the environmental factors.Samples for crop yield estimation should be extracted according to the characteristic of spatial distribution of crop yield to promote the efficiency of sampling.