Spatio-Temporal Analysis of Drought in the North-Eastern Coastal Region of Vietnam Using the Standardized Precipitation Index (SPI)

Spatio-temporal analysis of drought provides valuable information for drought management and damage mitigation. In this study, the Standardized Precipitation Index at the time scale of 6 months (SPI-6) is selected to reflect drought conditions in the North-Eastern coastal region of Vietnam. The drought events and their characteristics from 1981 to 2019 are detected at 9 meteorological stations and 10 Chirps rainfall stations. The spatio-temporal variation of drought in the study region is analyzed on the basis of the number, duration, severity, intensity, and peak of the detected drought events at the 19 stations. The results show that from 1981 to 2019 the drought events mainly occurred with 1-season duration and moderate intensity and peak. The number, duration, severity, and peak of the drought events were the greatest in the period 2001-2010 and were the smallest in the period 2011-2019. Among the 19 stations, the drought duration tends to decrease at 11 stations, increase at 7 stations, and has a slight variant at 1 station;the drought severity tends to decrease at 14 stations, increase at 4 stations, and has not a significant trend at 1 station;the drought intensity tends to decrease at 17 stations, increase at 1 station, and has a slight variant at 1 station;and the drought peak tends to decrease at 18 stations and increase at 1 station.

Spatio-Temporal Change of Dispersal Areas of Greater Kudu (Tragelaphus strepsiceros) in Lake Bogoria Landscape, Kenya

Decline in wildlife populations is manifest globally, regionally and locally. A wildlife decline of 68% has been reported in Kenya’s rangelands with Baringo County experiencing more than 85% wildlife loss in the last four decades. Greater Kudu (Tragelaphus strepsiceros) is endemic to Lake Bogoria landscape in Baringo County and constitutes a major tourist attraction for the region necessitating use of its photo on the County’s logo and thus a flagship species. Tourism plays a central role in Baringo County’s economy and is a major source of potential growth and employment creation. The study was carried out to assess spatio-temporal change of dispersal areas of Greater Kudu (GK) in Lake Bogoria landscape in the last four years for enhanced adaptive management and improved livelihoods. GK population distribution primary data collected in December 2022 and secondary data acquired from Lake Bogoria National Game Reserve (LBNGR) for 2019 and 2020 were digitized using in a Geographic Information System (GIS). Measures of dispersion and point pattern analysis (PPA) were used to analyze dispersal of GK population using GIS. Spatio-temporal change of GK dispersal in LBNR was evident thus the null hypothesis was rejected. It is recommended that anthropogenic activities contributing to GK’s habitat degradation be curbed by providing alternative livelihood sources and promoting community adoption of sustainable technologies for improved livelihoods.

Gas monitoring data anomaly identification based on spatio-temporal correlativity analysis

Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed. The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided. By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity, the correlative coefficient values range of eight kinds of data anomaly is obtained. Then the gas moni- toring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented. In order to improve the efficiency of analysis, the gas sensors code rules which can express the spatial topological relations are sug- gested. The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.

Modeling and Analysis of Production Logistics Spatio-Temporal Graph Network Driven by Digital Twin

In the process of logistics distribution of manufacturing enterprises, the automatic scheduling method based on the algorithm model has the advantages of accurate calculation and stable operation, but it excessively relies on the results of data calculation, ignores historical information and empirical data in the solving process, and has the bottleneck of low processing dimension and small processing scale. Therefore, in the digital twin(DT) system based on virtual and real fusion, a modeling and analysis method of production logistics spatio-temporal graph network model is proposed, considering the characteristics of road network topology and time-varying data. In the DT system, the temporal graph network model of the production logistics task is established and combined with the network topology, and the historical scheduling information about logistics elements is stored in the nodes. When the dynamic task arrives, a multi-stage links probability prediction method is adopted to predict the possibility of loading, driving, and other link relationships between task-related entity nodes at each stage. Several experiments are carried out, and the prediction accuracy of the digital twin-based temporal graph network(DTGN) model trained by historical scheduling information reaches 99.2% when the appropriate batch size is selected. Through logistics simulation experiments, the feasibility and the effectiveness of production logistics spatio-temporal graph network analysis methods based on historical scheduling information are verified.

Spatio-temporal analysis of the incidence of colorectal cancer in Guangzhou,2010-2014

Introduction: Colorectal cancer(CRC) is a common type of neoplasm. This study examined the spatio?temporal distribution of the CRC incidence in Guangzhou during 2010–2014.Methods: Colorectal cancer incidence data were obtained from the Guangzhou Cancer Registry System. Spatial autocorrelation analysis and a retrospective spatio?temporal scan were used to assess the spatio?temporal cluster distribution of CRC cases.Results: A total of 14,618 CRC cases were registered in Guangzhou during 2010–2014, with a crude incidence of 35.56/100,000 and an age?standardized rate of incidence by the world standard population(ASRIW) of 23.58/100,000. The crude incidence increased by 19.70% from 2010(32.88/100,000) to 2014(39.36/100,000) with an average annual percentage change(AAPC) of 4.33%. The AAPC of ASRIW was not statistically significant. The spatial autocorrelation analysis revealed a CRC incidence hot spot in central urban areas in Guangzhou City, which included 25 streets in southwestern Baiyun District, northwestern Haizhu District, and the border region between Liwan and Yuexiu Dis?tricts. Three high? and five low?incidence clusters were identified according to spatio?temporal scan of CRC incidence clusters. The high?incidence clusters were located in central urban areas including the border regions between Bai?yun, Haizhu, Liwan, and Yuexiu Districts.Conclusions: This study revealed the spatio?temporal cluster pattern of the incidence of CRC in Guangzhou. This information can inform allocation of health resources for CRC screening.

Spatio-temporal analysis of the melt onset dates over Arctic sea ice from 1979 to 2017

The melt onset dates(MOD)over Arctic sea ice plays an important role in the seasonal cycle of sea ice surface properties,which impacts Arctic surface solar radiation absorbed by the ice-ocean system.Monitoring interannual variations in MOD is valuable for understanding climate change.In this study,we investigated the spatio-temporal variability of MOD over Arctic sea ice and 14 Arctic sub-regions in the period of 1979 to 2017 from passive microwave satellite data.A set of mathematical and statistical methods,including the Sen’s slope and Mann-Kendall mutation tests,were used to comprehensively assess the variation trend and abrupt points of MOD during the past 39 years for different Arctic sub-regions.Additionally,the correlation between Arctic Oscillation(AO)and MOD was analyzed.The results indicate that:(1)all Arctic sub-regions show a trend toward earlier MOD except the Bering Sea and St.Lawrence Gulf.The East Siberian Sea exhibits a significantly earlier trend,with the highest rate of-9.45 d/decade;(2)the temporal variability and statistical significance of MOD trend exhibit large interannual differences with different time windows for most regions in the Arctic;(3)during the past 39 years,the MOD changed abruptly in different years for different sub-regions;(4)the seasonal AO has more influence on MOD than monthly AO.The findings in this study can improve our knowledge of MOD changes and are beneficial for further Arctic climate change study.

Implementing geostatistical analysis to study spatio-temporal distribution patterns of swimming crabs(Portunus trituberculatus)

This study attempted to compare the performance of local polynomial interpolation,inverse distance weighted interpolation,and ordinary kriging in studying distribution patterns of swimming crabs.Cross-validation was used to select the optimum method to get distribution results,and kriging was used for making spatial variability analysis.Data were collected from 87 sampling stations in November of 2015(autumn)and February(winter),May(spring)and August(summer)of 2016.Results indicate that swimming crabs widely distributed in autumn and summer:in the summer,they were more spatially independent,and resources in each sampling station varied a lot;in the winter and spring,the abundance of crabs was much lower,but the individual crab size was bigger,and they showed the patchy and more concentrative distribution pattern,which means they were more spatially dependent.Distribution patterns were in accordance with ecological migration features of swimming crabs,which were affected by the changing marine environment.This study could infer that it is applicable to study crab fishery or even other crustacean species using geostatistical analysis.It not only helps practitioners have a better understanding of how swimming crabs migrate from season to season,but also assists researchers in carrying out a more comprehensive assessment of the fishery.Therefore,it may facilitate advancing the implementation in the pilot quota management program of swimming crabs in northern Zhejiang fishing grounds.

Hotshots of Spatio-temporal Behavior of Chinese Residents in the Context of Big Data:Visual Analysis Based on CiteSpace

By using CiteSpace software to create a knowledge map of authors,institutions and keywords,the literature on the spatio-temporal behavior of Chinese residents based on big data in the architectural planning discipline published in the China Academic Network Publishing Database(CNKI)was analyzed and discussed.It is found that there was a lack of communication and cooperation among research institutions and scholars;the research hotspots involved four main areas,including“application in tourism research”,“application in traffic travel research”,“application in work-housing relationship research”,and“application in personal family life research”.

Study and application of an improved four-dimensional variational assimilation system based on the physical-space statistical analysis for the South China Sea

The four-dimensional variational assimilation(4D-Var)has been widely used in meteorological and oceanographic data assimilation.This method is usually implemented in the model space,known as primal approach(P4D-Var).Alternatively,physical space analysis system(4D-PSAS)is proposed to reduce the computation cost,in which the 4D-Var problem is solved in physical space(i.e.,observation space).In this study,the conjugate gradient(CG)algorithm,implemented in the 4D-PSAS system is evaluated and it is found that the non-monotonic change of the gradient norm of 4D-PSAS cost function causes artificial oscillations of cost function in the iteration process.The reason of non-monotonic variation of gradient norm in 4D-PSAS is then analyzed.In order to overcome the non-monotonic variation of gradient norm,a new algorithm,Minimum Residual(MINRES)algorithm,is implemented in the process of assimilation iteration in this study.Our experimental results show that the improved 4D-PSAS with the MINRES algorithm guarantees the monotonic reduction of gradient norm of cost function,greatly improves the convergence properties of 4D-PSAS as well,and significantly restrains the numerical noises associated with the traditional 4D-PSAS system.

Gonorrhea cluster detection in Manitoba,Canada:Spatial,temporal,and spatio-temporal analysis

In Canada,Gonorrhea infection ranks as the second most prevalent sexually transmitted infection.In 2018,Manitoba reported an incidence rate three times greater than the national average.This study aims to investigate the spatial,temporal,and spatio-temporal patterns of Gonorrhea infection in Manitoba,using individual-level laboratory-confirmed administrative data provided by Manitoba Health from 2000 to 2016.Age and sex patterns indicate that females are affected by infections at younger ages compared to males.Moreover,there is an increase in repeated infections in 2016,accounting for 16%of the total infections.Spatial analysis at the 96 Manitoba regional health authority districts highlights significant positive spatial autocorrelation,demonstrating a clustered distribution of the infection.Northern districts of Manitoba and central Winnipeg were identified as significant clusters.Temporal analysis shows seasonal patterns,with higher infections in late summer and fall.Additionally,spatio-temporal analysis reveals clusters during high-risk periods,with the most likely cluster in the northern districts of Manitoba from January 2006 to June 2014,and a secondary cluster in central Winnipeg from June 2004 to November 2012.This study identifies that Gonorrhea infection transmission in Manitoba has temporal,spatial,and spatio-temporal variations.The findings provide vital insights for public health and Manitoba Health by revealing high-risk clusters and emphasizing the need for focused and localized prevention,control measures,and resource allocation.

Spatio-temporal analysis of Permian-Cretaceous magmatic activities in the Tengchong block:Implications for tectono-magmatic evolution

Understanding the tectono-magmatic evolution history of the Tengchong block is crucial for elucidating the formation of the Eastern Tethys tectonic domain.However,the correlation and evolution of the Tengchong block with the Sibumasu and Lhasa blocks is controversial during the Permian and Cretaceous.This study explores the information contained within magmatic rocks using big data and spatio-temporal analysis,providing quantitative constraints for the discussion of the tectonomagmatic evolution of the Tengchong block.To more accurately assess true magma activities and reduce errors caused by preservation and sampling processes,we utilized local singularity analysis to obtain the singularity index time-series.Correlation analysis of zircon ages and eHf(t)(correlation coefficient0.5)values indicates that the Tengchong block is more similar to the Sibumasu block.Results from timelagged cross-correlation analysis indicate that the Tengchong block and Sibumasu block exhibit a shorter lag in magmatic activities(3 Myr).Wavelet analysis reveals similar periods of collision-related magmatic activities(57 Myr and 43 Myr).Integrating evidence from paleontology and ophiolite belts,we propose that the Tengchong block co-evolved more closely with the Sibumasu block than with the Lhasa block,suggesting similar tectonic processes during the Early Permian to Early Cretaceous.Approximately 250–236 Ma,in the western Tengchong block,partial melting of the lower crust occurs due to crustal thickening.Around 219–213 Ma and 198–180 Ma,after the Tengchong block collided with the Eurasian continent,the subduction of the Meso-Tethys Ocean commenced.Around 130–111 Ma,the overall tectonic feature was a scissor-like closure of the Meso-Tethys Ocean from north to south.

Knowledge-embedded spatio-temporal analysis for euploidy embryos identification in couples with chromosomal rearrangements

Background:The goal of the assisted reproductive treatment is to transfer one euploid blastocyst and to help infertile women giving birth one healthy neonate.Some algorithms have been used to assess the ploidy status of embryos derived from couples with normal chromosome,who subjected to preimplantation genetic testing for aneuploidy(PGT-A)treatment.However,it is currently unknown whether artificial intelligence model can be used to assess the euploidy status of blastocyst derived from populations with chromosomal rearrangement.Methods:From February 2020 to May 2021,we collected the whole raw time-lapse videos at multiple focal planes from in vitro cultured embryos,the clinical information of couples,and the comprehensive chromosome screening results of those blastocysts that had received PGT treatment.Initially,we developed a novel deep learning model called the Attentive Multi-Focus Selection Network(AMSNet)to analyze time-lapse videos in real time and predict blastocyst formation.Building upon AMSNet,we integrated additional clinically predictive variables and created a second deep learning model,the Attentive Multi-Focus Video and Clinical Information Fusion Network(AMCFNet),to assess the euploidy status of embryos.The efficacy of the AMCFNet was further tested in embryos with parental chromosomal rearrangements.The receiver operating characteristic curve(ROC)was used to evaluate the superiority of the model.Results:A total of 4112 embryos with complete time-lapse videos were enrolled for the blastocyst formation prediction task,and 1422 qualified blastocysts received PGT-A(n=589)or PGT for chromosomal structural rearrangement(PGT-SR,n=833)were enrolled for the euploidy assessment task in this study.The AMSNet model using seven focal raw time-lapse videos has the best real-time accuracy.The real-time accuracy for AMSNet to predict blastocyst formation reached above 70%on the day 2 of embryo culture,and then increased to 80%on the day 4 of embryo culture.Combing with 4 clinical features of couples,the AUC of AMCFNet with 7 focal points increased to 0.729 in blastocysts derived from couples with chromosomal rearrangement.Conclusion:Integrating seven focal raw time-lapse images of embryos and parental clinical information,AMCFNet model have the capability of assessing euploidy status in blastocysts derived from couples with chromosomal rearrangement.

Land use change in Bohai Rim: a spatial-temporal analysis

Based on RS and GIS methods, land use information for 1985 and 1995 was acquired from TM images and analyzed. Then on both spatial and temporal aspects, this paper analyzes land use change in three provinces of Hebei, Shandong and Liaoning and two municipalities of Beijing and Tianjin in the Bohai Rim covering the period of 1985 to 1995. The extent, rate, areal difference and trend of various types of land use changes in the region, as well as spatial changes of major types of land use, their distribution characteristics and regional orientation are revealed. The regional characteristics of land use are elaborated, so as to provide effective policy support for sustainable land use in the area around the Bohai Bay.

Spatiotemporal Property Analysis of Birth Defects in Wuxi,China

Objective To describe the temporal trends and spatial patterns of birth defects occurring in Wuxi, a developed region of China. Methods Wavelet analysis was used to decompose the temporal trends of birth defect prevalence based on the birth defect rates over the past 16 years. Birth defect cases with detailed personal and family information were geo-coded and the relative risk in each village was calculated. General G statistic was used to test the spatial property with different scales. Results Wavelet analysis showed an increasing temporal trend of birth defects in this region. Clustering analysis revealed that changes continued in the spatial patterns with different scales. Conclusion Wuxi is confronted with severe challenges to reduce birth defect prevalence. The risk factors are stable and show no change with spatial scale but an increasing temporal trend. Interventions should be focused on villages with a higher prevalence of birth defects.

Characteristics and Cause Analysis of Variations in Light Precipitation Events in the Central and Eastern Tibetan Plateau,China,During 1961–2019

The Tibetan Plateau(TP)is one of the most sensitive areas and is more susceptible to climate change than other regions in China.The TP also experiences extremely frequent light precipitation events compared to precipitation of other intensities.However,the definition,influencing factors,and characteristics of light precipitation in the TP have not been accurately explained.This study investigated the variation characteristics of light precipitation with intensities(Pre)of 0.1-10.0 mm/d based on climate data from 53 meteorological stations over the central and eastern TP from 1961 to 2019.For detailed analysis,light precipitation events were classified into five grades:G1[0.1-2.0 mm/d),G2[2.0-4.0 mm/d),G3[4.0-6.0 mm/d),G4[6.0-8.0 mm/d),and G5[8.0-10.0 mm/d).The results showed that both the amount of precipitation and number of precipitation days had increased significantly at rates of 4.0-6.0 mm/10 yr and 2.0-4.0 d/10 yr,respectively,and most precipitation events were of low intensity(0.1≤Pre<2.0 mm/d).Light precipitation events mainly occurred in the southeast of the study area,and it showed an increasing trend from the northwest to the southeast.Abrupt changes in light precipitation primarily occurred in the 1980 s.A comprehensive time series analysis using the Mann-Kendall test and Morlet wavelet was performed to characterize the abrupt changes and cycles of light precipitation.During the study period,the main periods of light precipitation corresponded to the 6 yr cycle,with obvious periodic oscillation characteristics,and this cycle coexisted with cycles of other scales.Significant correlations were observed between the amount of light precipitation and temperature over the study area.The findings will enhance our understanding of changes in light precipitation in the TP and provide Scientific basis for the definition of light precipitation in the future.

Video Analysis Based on Volumetric Event Detection

During the past decade, feature extraction and knowledge acquisition based on video analysis have been extensively researched and tested on many applications such as closed-circuit television （CCTV） data analysis, large-scale public event control, and other daily security monitoring and surveillance operations with various degrees of success. However, since the actual video process is a multi-phased one and encompasses extensive theories and techniques ranging from fundamental image processing, computational geometry and graphics, and machine vision, to advanced artificial intelligence, pattern analysis, and even cognitive science, there are still many important problems to resolve before it can be widely applied. Among them, video event identification and detection are two prominent ones. Comparing with the most popular frame-to-frame processing mode of most of today＇s approaches and systems, this project reorganizes video data as a 3D volume structure that provides the hybrid spatial and temporal information in a unified space. This paper reports an innovative technique to transform original video frames to 3D volume structures denoted by spatial and temporal features. It then highlights the volume array structure in a so-called ＂pre-suspicion＂ mechanism for a later process. The focus of this report is the development of an effective and efficient voxel-based segmentation technique suitable to the volumetric nature of video events and ready for deployment in 3D clustering operations. The paper is concluded with a performance evaluation of the devised technique and discussion on the future work for accelerating the pre-processing of the original video data.

Spatio-temporal Changes and Associated Uncertainties of CENTURYmodelled SOC for Chinese Upland Soils, 1980-2010

Detailed information on the spatio-temporal changes of cropland soil organic carbon(SOC) can significantly contribute to the improvement of soil fertility and mitigate climate change. Nonetheless, information and knowledge on the national scale spatio-temporal changes and the corresponding uncertainties of SOC in Chinese upland soils remain limited. The CENTURY model was used to estimate the SOC storages and their changes in Chinese uplands from 1980 to 2010. With the Monte Carlo method, the uncertainties of CENTURY-modelled SOC dynamics associated with the spatial heterogeneous model inputs were quantified. Results revealed that the SOC storage in Chinese uplands increased from 3.03(1.59 to 4.78) Pg C in 1980 to 3.40(2.39 to 4.62) Pg C in 2010. Increment of SOC storage during this period was 370 Tg C, with an uncertainty interval of –440 to 1110 Tg C. The regional disparities of SOC changes reached a significant level, with considerable SOC accumulation in the Huang-Huai-Hai Plain of China and SOC loss in the northeastern China. The SOC lost from Meadow soils, Black soils and Chernozems was most severe, whilst SOC accumulation in Fluvo-aquic soils, Cinnamon soils and Purplish soils was most significant. In modelling large-scale SOC dynamics, the initial soil properties were major sources of uncertainty. Hence, more detailed information concerning the soil properties must be collected. The SOC stock of Chinese uplands in 2010 was still relatively low, manifesting that recommended agricultural management practices in conjunction with effectively economic and policy incentives to farmers for soil fertility improvement were indispensable for future carbon sequestration in these regions.

Wi-Fi Positioning Dataset with Multiusers and Multidevices Considering Spatio-Temporal Variations

Precise information on indoor positioning provides a foundation for position-related customer services.Despite the emergence of several indoor positioning technologies such as ultrawideband,infrared,radio frequency identification,Bluetooth beacons,pedestrian dead reckoning,and magnetic field,Wi-Fi is one of the most widely used technologies.Predominantly,Wi-Fi fingerprinting is the most popular method and has been researched over the past two decades.Wi-Fi positioning faces three core problems:device heterogeneity,robustness to signal changes caused by human mobility,and device attitude,i.e.,varying orientations.The existing methods do not cover these aspects owing to the unavailability of publicly available datasets.This study introduces a dataset that includes the Wi-Fi received signal strength(RSS)gathered using four different devices,namely Samsung Galaxy S8,S9,A8,LG G6,and LG G7,operated by three surveyors,including a female and two males.In addition,three orientations of the smartphones are used for the data collection and include multiple buildings with a multifloor environment.Various levels of human mobility have been considered in dynamic environments.To analyze the time-related impact on Wi-Fi RSS,data over 3 years have been considered.

A Spatio-Temporal Odyssey Around the Concepts of Sustainable Development and Corporate Social Responsibility： Boundaries to Be Determined？

The aim of this research is to analyze the emergence of the concepts of sustainable development （SD） and corporate social responsibility （CSR） in companies in time and space. A spatio-temporal reading will indicate the most important socio-political and environmental events that have emerged with these two concepts. In order to complete the odyssey, a spatio-temporal analysis has retraced the epistemological evolution of these latter, whilst at the same time remarking the appropriation that has been made by the different institutional and organizational actors. The historical and epistemological reviews tell us that these two concepts, which came into existence almost 80 years, have indefinite outlines; one can be substituted for the other. However, thanks to this odyssey, we have reduced the boundaries even further between sustainable development and social responsibility and shown their theoretic and historical association. The perspective adopted shows that the concept of corporate social responsibility is closely connected to that of sustainable development. This connection means that researchers in management science are faced with more new problem issues reaching further than the simple lack of conceptual consensuses.

Application of the Distance to Natural (D2N) Index and Statistical Analysis of Different Anthropic Uses of the Río Grande De Comitán Watershed, Chiapas, México

The intensification of anthropic uses (i.e., increase of the hemerobic condition) threatens the remnants of native vegetation due to the reduction of its self-regulation capacity. In this research, the Distance to Nature (D2N) index for land use and land cover was applied in the Río Grande de Comitán watershed (Southern Mexico) to answer the following questions: 1) What were the land use dynamics observed in the Rio Grande de Comitán watershed in the trajectory through 1999, 2009 and 2019? 2) Does the subcategorization of the D2N allow one to identify which anthropic uses influence more the territorial expression of the watershed? To answer these questions, we performed a supervised classification of land use and land cover was performed in this watershed, and for the D2N index, the classification was simplified to three-category scale for the subcategorization of the anthropic component. Through Principal Component Analysis (PCA), we identified that agricultural anthropogenic use had the greatest influence on territorial expression. The reported scenario indicates a trend of gradual and continuous reduction of naturalness over the last 20 years. Additionally, the D2N index proved to be a useful tool to demonstrate both the anthropic impact, with the simplified scale, and the component that most influences the territory, by subcategorizing the anthropic scale.