Autocorrelation Analysis Research Articles

Possibilities of Using Geoinformation Technologies in Epidemiological Surveillance of COVID-19 Infection at the Regional Level

Relevance. The spread of the new coronavirus infection throughout the world has led to expressed interest in studying, among other things, the patterns of territorial distribution of cases of the disease. Aim. To investigate the spatial distribution of cases of COVID-19 infection and develop proposals for the use of GIS technologies in the epidemiological supervision system for the new coronavirus infection at the regional level. Materials and methods. The study was conducted on the territory of the closed administrative- territorial entity of Zelenogorsk, Krasnoyarsk Territory. 4176 cases of COVID-19 infection were reported during the study period of 57 weeks (04/12/2020 to 06/18/2021). Each case of the disease was geocoded by the residence of the sick person using a projection coordinate system from the open data of the Open Street Map resource. The spatial distribution of COVID-19 cases was studied with geographic information system QGIS Desktop version 3.28.0. Spatial autocorrelation analysis was carried out using the Getis-Ord index. Results. During the application of GIS technologies, the density of distribution of COVID-19 infection cases was estimated, six zones with an average core density were discovered, the outbreaks in the northern part of the city had the greatest epidemiological significance. When assessing the clustering of cases within the specified territorial zones, eleven clusters were identified, three of which were characterized by the highest density of cases - 1210.1 cases per 1 sq. km, 1155.9 and 1116.7 cases per 1 sq. km. The Getis-Ord index value ranged from 0.00 to 2.576, the majority of cases was recorded in territorial clusters located in the northern part of the city. Conclusions. New knowledge obtained on the basis of modern GIS technologies about the presence of “hot spots” or clusters in the administrative territory will make the adjustment of preventive measures in micro-areas with a high prevalence of infection possible and develop strategies for more effective control of COVID-19 infection.

Geospatial Patterns of Non-Melanoma Skin Cancer in Relation to Climate Changes in Iran.

The purpose of this study is to examine the impact of climate change factors on the incidence of skin cancer in Iran. The statistical population for this study comprises skin cancer patients in Iran. All other data used in this research were extracted from Remote Sensing imagery, including Ultraviolet ray, Relative humidity, Cloud cover, incoming short-wave flux, elevation, and total hours of sunshine. Initially, spatial autocorrelation analysis and cluster patterns were calculated using General G and Moran's I indices. Subsequently, a Geographically Weighted Regression Model was used to establish a regression relationship between the climate change data and the detection and forecasting rate of skin cancer. Finally, the model's accuracy was evaluated by estimating the detection coefficient between the reality map and the forecasting map. The study found that UV radiation and relative humidity exhibit the highest positive and negative correlation, respectively, with the skin cancer rate in Iran. Geostatistical analysis revealed a clustered spatial distribution of skin cancer rates, and the proposed GWR model demonstrated high accuracy in predicting the skin cancer rate. The results indicate the highest positive correlation (+0.51) for UV ray and the most negative correlation (-0.43) for relative humidity. The Geostatistical analysis reveals spatial autocorrelation, cluster patterns, and non-randomness of the data. The detection rate of skin cancer increases from north to south and from west to east.

Linking wilderness mapping and ecosystem services: Identifying integrated wilderness and ecological indicators to quantify ecosystem services of wilderness

Wilderness has proven to provide a wide range of ecosystem services (ES). Wilderness have been shown to play an important role in preserving biodiversity and providing ES, which is indispensable to both nature and people. It is essential to integrate ES quantification into wilderness conservation and management. This study presents a method that combines the wilderness mapping and ecological indicators to measure ES of wilderness. The method was applied in 155,800 km2 of Shandong province in China, across 23 types of land use. First, relative wilderness value (RWV) and ecosystem service capability (ESC) were quantified according to Weighted Linear Combination (WLC). Then, spatial autocorrelation between RWV and ESC were tested and analyzed using GeoDa software. Finally, the Redundancy analysis was used to investigate the primary drivers of RWV and ESC in different landscape types. The findings showed that, there were 27,263 km2 of wilderness in Shandong province, of which 6,294 km2 were high-quality wilderness. The region with the highest RWV was the Yellow River Delta (RWV = 0.82), and the area with the highest ESC was Laoshan Mountain (ESC = 0.76). Spatial autocorrelation analysis showed a positive correlation between RWV and ESC (Pearson’s r = 0.637), both of which had significant spatial relevance (Moran’s I = 0.589, P < 0.005). The RWV and ESC high-high clusters were found to cover 5,223 km2 of high-quality wilderness areas. Regression analysis (R2 = 0.744) showed that RWV can quantify ESC of urban area reliably. Population density (Explaining 33.9 %-49.3 %) was found to be a key indicator of RWV and ESC changes through the Redundancy analysis. In addition, we discussed key drivers of RWV and ESC of high-quality wilderness according to different landscape types. This approach can be used and adopted to support planning decisions dealing with wilderness conservation and management.

Difference in the Contribution of Driving Factors to Nitrogen Loss With Surface Runoff Between the Hill and Plain Agricultural Watersheds

AbstractIdentifying the factors and quantifying their contributions to nitrogen (N) loss associated with surface runoff is of great significance to the control of non‐point source N pollution. However, the distinct geographical units, such as hills and plains, may lead to great differences in the contribution of these driving factors, which has been rarely investigated. This study developed an effective framework, which simulated the N loss with surface runoff in hills and plains by SWAT and NDP, and analyzed their spatial distribution variations by spatial autocorrelation analysis, and distinguished the contribution of their driving factors by multi‐scenario simulation and partial redundancy analysis (pRDA). The framework was instantiated in a hill and a plain agricultural watershed, respectively, in the upper Taihu Lake Basin, China. We found the contribution of fertilization to N loss with surface runoff in the hills (10.4%) was greater than that in the plains (6.4%), which may be due to the N increment effect of paddy land. The contribution of rainfall to N loss with surface runoff in the plains (93.2%) was greater than that in the hills (74.3%), which may be due to the N increment effect of urban land. The developed framework could provide a viable way to study the environmental impacts of natural and anthropogenic drivers in different types of agricultural watersheds, thus offer scientific references for nutrient control measures.

Is Poverty Concentrated in Shanghai? Spatial Patterns in Social Housing and Their Implications for Social Equality in Chinese Cities

It is of general concern how poverty concentrates in cities, due to its close association with social equality issues. This research explores this topic at a citywide level. Spatial data of social housing regarding 2008 to 2020 in Shanghai are utilized to examine how the concentration patterns for low-to-moderate-income groups have changed. Multiple methods including spatial autocorrelation analysis, location quotient (LQ), and Mann–Whitney U test were employed to assess the spatial distribution of, and concentration patterns in, social housing, as well as investigating whether the spatial distribution of urban resources was equitable for residents in social housing. We found that the low-to-moderate-income groups were previously concentrated at the boundary of central city and then gradually deconcentrated into a relatively even pattern. However, it is important to note that this process has not effectively facilitated social equality due to the unequitable distribution of urban resources. Consequently, we recommend that policy makers in developing countries pay particular attention to site selection for social housing and the distribution of urban amenities in the future.

Spatial analysis of rabies-transmitting animal bite cases in North Tapanuli Regency, North Sumatera Province in 2016-2020

Purpose: Rabies is a priority strategic disease because it has an impact on socio-economic and public health. This study aims to describe the incidence of rabies-transmitting animal bite cases in North Tapanuli Regency in 2016-2020, contribute to understanding the dynamics of cases, and provide effective information in controlling cases of animal bites that transmit rabies.&#x0D; Methods: Ecological study using aggregated data. The data was collected from monthly reports of rabies cases at the North Tapanuli Regency Health Service in 2016-2020. As a unit analysis, all districts are used. QGIS and GeoDA software are used for data analysis. Through GeOda software, spatial autocorrelation analysis was carried out globally using Moran's I test and locally using the LISA test.&#x0D; Results: Rabies-transmitting animal bite cases had a dispersed pattern in 2016 (I&lt;E[I]) and a clustered pattern (I&gt;E[I]). Globally, there is positive spatial autocorrelation in rabies-transmitting animal bite cases between districts in North Tapanuli Regency in 2017 and 2020 (p-value &lt; 0.05). Moran's cluster map shows that locally in 2016-2020, the districts in the quadrant I (High-High) are Siborongborong and Sipoholon. Quadrant II (Low-High) is Adiankoting and Pagaran. Quadrant III (Low-Low) is Pangaribuan, and quadrant IV (High-Low) is Pahae Jae and Pangaribuan.&#x0D; Conclusion: Globally, cases of animal bites that transmit rabies in North Tapanuli Regency occur in clusters. It means that the number of bite cases in one area is related to the number of cases in other nearby areas. Therefore, rabies control program interventions in areas with high observation values must be prioritized so they do not spread to areas with low observation values.

Toward tuberculosis elimination by understanding epidemiologic characteristics and risk factors in Hainan Province, China

BackgroundThe disease burden of tuberculosis (TB) was heavy in Hainan Province, China, and the information on transmission patterns was limited with few studies. This atudy aims to further explore the epidemiological characteristics and influencing factors of TB in Hainan Province, and thereby contribute valuable scientific evidences for TB elimination in Hainan Province.MethodsThe TB notification data in Hainan Province from 2013 to 2022 were collected from the Chinese National Disease Control Information System Tuberculosis Surveillance System, along with socio-economic data. The spatial–temporal and population distributions were analyzed, and spatial autocorrelation analysis was conducted to explore TB notification rate clustering. In addition, the epidemiological characteristics of the cases among in-country migrants were described, and the delay pattern in seeking medical care was investigated. Finally, a geographically and temporally weighted regression (GTWR) model was adopted to analyze the relationship between TB notification rate and socio-economic indicators. The tailored control suggestions in different regions for TB elimination was provided by understanding epidemiological characteristics and risk factors obtained by GTWR.ResultsFrom 2013 to 2022, 64,042 cases of TB were notified in Hainan Province. The estimated annual percentage change of TB notification rate in Hainan Province from 2013 to 2020 was − 6.88% [95% confidence interval (CI): − 5.30%, − 3.69%], with higher rates in central and southern regions. The majority of patients were males (76.33%) and farmers (67.80%). Cases among in-country migrants primarily originated from Sichuan (369 cases), Heilongjiang (267 cases), Hunan (236 cases), Guangdong (174 cases), and Guangxi (139 cases), accounting for 53%. The majority (98.83%) of TB cases were notified through passive case finding approaches, with delay in seeking care. The GTWR analysis showed that gross domestic product per capita, the number of medical institutions and health personnel per 10,000 people were main factors affecting the high TB notification rates in some regions in Hainan Province. Different regional tailored measures such as more TB specialized hospitals were proposed based on the characteristics of each region.ConclusionsThe notification rate of TB in Hainan Province has been declining overall but still remained high in central and southern regions. Particular attention should be paid to the prevalence of TB among males, farmers, and out-of-province migrant populations. The notification rate was also influenced by economic development and medical conditions, indicating the need of more TB specialized hospitals, active surveillance and other tailored prevention and control measures to promote the progress of TB elimination in Hainan Province.

The moist halo region around shallow cumulus clouds in large eddy simulations

AbstractIn this study, the moist buffering halo region of shallow maritime cumulus clouds is systematically investigated using large eddy simulations with various grid resolutions and numerical choices. Autocorrelation analyses of cloud liquid water and relative humidity suggest a converged size of 200–300 m for moist patches outside clouds when the model resolution is below 50 m, but may overestimate this size due to noncloudy moist regions. Based on a composite analysis, the structure of the moist halo immediately outside individual clouds is examined. It is found that, regardless of model resolution, the distribution of relative humidity in the halo region does not depend on cloud size, but on the real distance away from the cloud boundary, indicating some size‐independent length scales are responsible for the halo formation. The relative humidity decays with distance more quickly with finer horizontal resolution, which is possibly related to the model resolution dependence of the cloud spectrum. The halo size near the cloud base is larger than that within the cloud layer and this feature is robust across all simulations. Further analyses of backward and forward Lagrangian trajectories originating from the moist halo region reveal the possible role for subcloud coherent structures in cloud‐base halo formation. Possible mechanisms explaining cloud halo sizes and associated length scales are discussed.

Method for phase space reconstruction to estimate the short-term future behavior of pressure signals in pipelines

In this study, we propose a method based on phase space reconstruction to estimate the short-term future behavior of pressure signals in pipelines. The pressure time series data were obtained from an IoT experimental model conducted in the laboratory. The proposed hydraulic system demonstrated the presence of traces of weak chaos in the time series of the pressure signal. Fractal dimension analysis revealed a complex fractal structure in the data, indicating the existence of nonlinear dynamics. Similarly, Lyapunov coefficients, divergent trajectories, and autocorrelation analysis confirmed the presence of weak chaos in the time series. The results demonstrated the existence of apparently chaotic patterns that follow the theory proposed by Kolmogorov for deterministic dynamic systems that exhibit apparently random behaviors. Phase space reconstruction allowed us to show the dynamic characteristics of the signal so that short-term predictions were stable. Finally, the study of strange attractors in pipeline pressure time series can have significant contributions to anomaly detection.•A methodology is proposed for the reconstruction of the phase space to estimate the short-term future behavior of pressure signals in pipelines in real time.•The analysis of the proposed hydraulic system revealed some indications of weak chaos in the time series of the pressure signal obtained experimentally.•The methodology implemented and the results of this study showed that the short-term predictions were very accurate and consistent; Chaotic patterns were also identified that support the theory proposed by Kolmogorov.

Spatial Assessment of Groundwater Salinity and Its Impact on Vegetation Cover Conditions in the Agricultural Lands of Al-Ahsa Oasis, Saudi Arabia

This study investigated the complex relationship among groundwater salinity, soil texture, and vegetation health in Al-Ahsa Oasis, Saudi Arabia. Utilizing vegetation condition index data from 5 years of satellite imagery, alongside ground measurements of groundwater salinity and soil analysis, the study unveiled significant spatial heterogeneity. The vegetation health and groundwater salinity in the study area ranged from 27 to 70% and from 1.7 to 9.6 dS m−1, respectively, and exhibited contrasting patterns, with a high vegetation condition index (healthy vegetation) in the north and east versus high salinity in the southwest. The applied cross-tabulation statistics revealed a strong negative correlation between the vegetation condition index and salinity, with “good” and “normal” vegetation health primarily coinciding with “slightly saline” groundwater. Soil texture further modulated the vegetation response, as “Silt loam” soils corresponded with “good” VCI, while “silty clay loam” only supported “dry” and “normal” conditions. The applied spatial autocorrelation analysis confirmed this, showing low vegetation clustering with “silt” texture and high salinity in the mid-west of the study area (p &lt; 0.05). Outlier districts hint at local factors beyond simple salinity–vegetation health relationships. Finally, a conditional plot, applied as a spatial statistical approach, revealed that low vegetation health spatially correlates with high groundwater salinity (&gt;5 dS m−1) on “silt loam” in the mid-west, while a higher vegetation condition index aligned with lower groundwater salinity in the east and north. These findings highlight the critical role of spatial variability and the need for advanced modeling and data integration to understand and predict the responses of vegetation to environmental challenges, and will be crucial for optimizing water management to ensure the long-term sustainability of Al-Ahsa Oasis.

Study on the spatiotemporal evolution of coupled and coordinated digital economic resilience and efficiency

The coordinated development of resilience and efficiency in the digital economy guarantees a sustainable and efficient growth model. We used panel data from 30 provinces and regions in China from 2013 to 2021 to evaluate the resilience and efficiency levels of the digital economy. We calculated their coordinated development levels using kernel density estimation, spatial autocorrelation, and Markov chain analysis to explore the spatiotemporal evolution characteristics of their coordinated development. The results indicate that (1) the resilience level of the digital economy is on the rise, while efficiency fluctuations are decreasing. Resilience exhibits an “east high–west low” spatial pattern with the “Hu Huanyong Line” as a boundary, while efficiency shows a “collapse in the central and northern regions” trend. (2) The overall level of coordinated development between resilience and efficiency has decreased; however, the differences in coordination between different regions have reduced, gradually forming a spatial pattern of “high in the east, low in the west, low in the south, and high in the north.” (3) A significant positive spatial correlation exists between the development levels of digital economic resilience and efficiency, which continues to strengthen over time. This finding reveals a spatial pattern of high-level concentration centered around Beijing–Tianjin, Jiangsu–Zhejiang–Shanghai, and low-level concentration centered around the central and western regions. (4) Coordinated development shows a “club convergence” effect, indicating stability in maintaining the existing state.

Spatial and temporal distribution characteristics and influencing factors of tourism eco-efficiency in the Yellow River Basin based on the geographical and temporal weighted regression model.

With economic progression in China, Yellow River Basin serves as a critical economic belt, which has also been recognized as a cradle of Chinese culture. A watershed is a complex structure of social, economic, and natural factors, and the diversity of its components determines its complexity. Studies on the spatiotemporal distribution characteristics and factors influencing the tourism eco-efficiency at the watershed scale are crucial for the sustainable regional socio-economic development, maintaining a virtuous cycle of various ecosystems, and comprehensively considering the utilization and coordinated development of various elements. Based on tourism eco-efficiency, the coordination degree of regional human-land system and the sustainable development levels can be accurately measured. With the tourism eco-efficiency in the Yellow River Basin from 2009 to 2019, the present study considers 63 cities in the Yellow River Basin as the research area by adopting the super-efficiency slacks-based measure (Super-SBM) model. Methods such as trend surface analysis, spatial autocorrelation analysis, elliptic standard deviation analysis, and hot spot analysis were used to explore their spatiotemporal distribution and evolution characteristics. The geographical and temporal weighted regression (GTWR) model was used to determine the factors influencing the tourism eco-efficiency value. The findings are as follows: ①The level of tourism eco-efficiency in the Yellow River Basin is not high, exhibiting a fluctuating upward trend. ②The tourism eco-efficiency in the Yellow River Basin shows significant spatial interdependence and agglomeration. Furthermore, the track of the center of gravity moves from northeast to southwest. ③ The tourism eco-efficiency in the Yellow River Basin is affected by various factors, with the economic development level having the greatest influence.

Spatial coupling coordination and interactive response between green finance and green total factor productivity: geographical analysis based on Chinese provinces, 2010-2020.

Based on the panel data of 30 provinces in China from 2010 to 2020, this study uses the coupling coordination degree model (CCDM), spatial autocorrelation analysis, and the panel vector autoregression (PVAR) model to quantitatively examine the dynamic coordination and interactive response of green finance (GF) and green total factor productivity (GTFP). The results show that the coupling coordination degree (CCD) between GF and GTFP during the study period shows an overall increasing trend and significant regional differentiation and remains at the medium level, indicating large room for improvement. The CCDs of provinces fluctuate between the low and high types. The distribution gradually shifts from a "high in the south and low in the north" pattern to a "high in the east and low in the west" configuration. The spatial difference of coupling development continues to expand and presents a significant spatial positive correlation. In addition, GF and GTFP in China exhibit significant self-reinforcing characteristics, but the reinforcing effect gradually decreases. There is only a unidirectional interaction relationship between GF and GTFP, which is GF actively fosters the advancement of GTFP, while the influence of GTFP on GF appears less pronounced. This research provides comprehensive insights into the dynamic interaction between GF and GTFP.

Bridging the gap: coordinating equity and efficiency in older people care resource allocation in China

BackgroundWith the increasing global aging population, how to allocate older people care resources reasonably has become an increasingly urgent international issue. China, as the largest developing country, has made many efforts to actively respond to the challenges of an aging population. However, there are still problems with uneven allocation of older people care resources and low efficiency of allocation. Therefore, this study evaluates the regional differences and dynamic evolution of the equity and efficiency of older people care resource allocation in China from 2009 to 2020, and explores ways to change the current situation.MethodsThe data used in this study were derived from the “China Statistical Yearbook” and the “China Civil Affairs Statistical Yearbook” for the period of 2010–2021. Firstly, the equity of older people care resource allocation was measured using the Gini coefficient, the Theil index, the Older People Care Resource Density Index, and the Older People Care Resource Agglomeration Degree. Secondly, the dynamic Slack-Based Measure data envelopment analysis method was adopted to evaluate efficiency. Lastly, the Z-score is used to normalize the equity index and perform classification matching with the efficiency value. Spatial autocorrelation analysis and hotspot analysis were conducted using GIS technology to examine the dynamic evolution process of older people care resource allocation equity and efficiency, as well as their spatial distribution patterns and coordination across provinces from 2009 to 2020.ResultsThe equity analysis showed that the spatial distribution of various types of older people care resources was uneven, and the differences were mainly due to internal differences within each region, with the largest equity differences observed in western provinces. Currently, older people care resources are mainly concentrated in eastern regions, while the total amount of older people care resources in western regions and some central regions is relatively small, which cannot meet the older people care needs of residents. The efficiency analysis results showed that the efficiency of older people care resource allocation has been improving over the past 12 years, and in 2020, 77.42% of provinces were located on the efficiency frontier with an average efficiency value of 0.9396. Finally, the coordination analysis results showed that there were significant spatiotemporal differences in the equity and efficiency of older people care resources allocation.ConclusionWith the development of society and economy, the total amount and service capacity of older people care resources in China have greatly improved. However, there are still significant spatiotemporal differences in the equity and efficiency of older people care resource allocation. The development of older people care services in central and eastern provinces is unbalanced, and there is a polarization trend in terms of equity and efficiency of older people care resource allocation. Most provinces in western regions face the dual dilemma of inadequate older people care resources and low utilization efficiency. It is recommended that policymakers comprehensively consider population and geographic factors in different provinces, establish relevant allocation standards according to local conditions, improve the redistribution system, and focus on increasing the total amount of older people care resources in underdeveloped provinces while promoting resource flow.

Efficient similar waveform search using short binary codes obtained through a deep hashing technique

Summary A similar waveform search plays a crucial role in seismology for detecting seismic events, such as small earthquakes and low-frequency events. However, the high computational costs associated with waveform cross-correlation calculations represent bottlenecks during the analysis of long, continuous records obtained from numerous stations. In this study, we developed a deep-learning network to obtain 64-bit hash codes containing information on seismic waveforms. Using this network, we performed a similar waveform search for ∼35 million moving windows developed for the 30 min waveforms recorded continuously at 10 MHz sampling rates using 16 acoustic emission transducers during a laboratory hydraulic fracturing experiment. The sampling points of each channel corresponded to those of the 5.8-year records obtained from typical seismic observations at 100 Hz sampling rates. Of the 35 million windows, we searched for windows with small average Hamming distances among the hash codes of 16 channel waveforms against template hash codes of 6057 events that were catalogued using conventional autoprocessing techniques. The calculation of average Hamming distances is 1430–1530 times faster than that of the corresponding network correlation. This hashing-based template matching enabled the detection of 23,462 additional events. We also demonstrated the feasibility of the hashing-based autocorrelation analysis, where similar event pairs were extracted without templates, by calculating the average Hamming distances for all possible pairs of the ∼35 million windows. This calculation required only 15.5 h under 120 thread parallelisation. This deep hashing approach significantly reduced the required memory compared with locality-sensitive hashing approaches based on random permutations, enabling similar waveform searching on a large-scale dataset.

Epidemiological and spatial-temporal clustering characteristics of pertussis in Hebei Province from 2013 to 2022

Objective: To analyze the spatial-temporal epidemiological characteristics of pertussis from 2013 to 2022 in Hebei Province and to provide a reference for improving prevention and control measures. Methods: Based on the data of pertussis reported in Hebei Province during 2013-2022 to analyze the popular characteristic, the ArcGIS 10.8 software was used to construct a ring map and to perform spatial autocorrelation analysis; the SaTScan 10.1 software was used for spatial-temporal scan statistics. Results: There were 6 715 cases of the cumulative report in Hebei Province from 2013 to 2022 without death. The annual report incidence was 0.90/100 000. The overall incidence rate showed an upward trend from 2013 to 2019, and during 2020-2021, it showed a sharp decline, but in 2022, it showed a sharp increase. Summer and autumn are the peak seasons of the epidemic. The incidence was highest in age group <1 year (48.67%), and the lowest age group in age group ≥15 years (0.45%) and mainly scattered children (78.03%); the incidence about men is higher than women. Spatial autocorrelation analysis showed that the onset of pertussis has spatial clustering, and high-high clusters were found in Langfang, Baoding, and Cangzhou, the top three countries with reported incidence. The area covered by a low-low cluster was consistent with the distribution of the corresponding low-incidence areas in this study. Space-time scan detects five statistically significant areas, and three zones were concentrated in 2022. Conclusions: The incidence of pertussis in Hebei had obvious season, population, and area-specific differences. There was obvious spatiotemporal and clustering, so the control of key areas should target the characteristics of time and space.

Epidemiological characteristics of typhoid fever in Fujian Province, 2011-2022

Objective: To analyze the incidence trend and epidemiological characteristics of typhoid fever in Fujian Province from 2011 to 2022, and understand the high-incidence population and hotspot areas, and provide evidences to develop more targeted prevention and control measures. Methods: The surveillance data of typhoid fever during 2011-2022 in Fujian Province were obtained from the National Disease Reporting Information System and analyzed with SAS 9.4. The spatial autocorrelation analysis of typhoid fever incidence at county/district levels was performed with ArcGlS 10.8. Results: A total of 5 126 cases of typhoid fever were reported in Fujian Province from 2011 to 2022, with an average annual incidence rate of 1.10/100 000. The average annual incidence rate was 0.96/100 000 from 2011 to 2015, 1.49/100 000 from 2016 to 2019, and 0.81/100 000 from 2020 to 2022. The disease occurred all the year round, with high epidemic season from May to September. A total of 23.59% (1 209/5 126) of the cases occurred at the age of 0-4, and 9.62% (493/5 126) at the age of 5-9. The male to female ratio of the cases was 0.97∶1 (2 524∶2 602) for the whole population, 1.19∶1 (925∶777) for people under 10 years old, 0.75∶1 (1 060∶1 404) for people between 10 and 54 years old, and 1.28∶1 (539∶421) for people over 55 years old. Cases in Ningde City accounted for 30.65% (1 571/5 126) of the total cases. Most hotspots were occurred in Ningde City. Recurrent and clustered cases were found in family members. Conclusions: Typhoid fever was prevalent at a low level in Fujian Province during 2011-2022, indicating that strengthening the prevention and control measures should target key areas and populations. The incidence of typhoid fever in Fujian Province showed spatial aggregation phenomenon, and most cases gathered in Ningde City. Intensive study for the influencing factors of spatial clustering should be conducted.

Spatiotemporal Analysis of the Impacts of Land Use Change on Ecosystem Service Value: A Case from Guiyang, China

The significance of ecosystem services and land use for human well-being and sustainable development cannot be understated. Scientifically assessing the ecosystem service value (ESV) and studying the relationship between land use change and the ESV can provide a theoretical groundwork for land use planning and ecological administration in Guiyang. In this study, gradient analysis was utilized to explore the changes of ESV at district level of Guiyang. Then, the synergistic relationship and the strength of the interaction between land use intensity (LUI) and ESV were explored by using a coupled coordination model and spatial autocorrelation analysis. Furthermore, polynomial fitting was carried out for the LUI index and its linked coordination index in relation to the ESV. The results showed that (1) the areas of farmland, forest, grassland, and unused land in Guiyang decreased from 2000 to 2020, while the areas of construction land and water body increased conversely. (2) The expansion of the construction land and water body was the main cause of the ESV change pattern in Guiyang, which first moved downward and then upward. (3) The ESV and LUI had a low overall coupling coordination degree (CCD). Spatial autocorrelation studies showed that low–to–low aggregation and high–to–high aggregation dominated the spatial patterns of essential regions. (4) The LUI and CCD indexes exhibited an inverted U-shaped curve correlation.

Research on the Evaluation and Influencing Factors of China’s Provincial Employment Quality Based on Principal Tensor Analysis

The research on the quality of employment in China holds immense significance for attaining high-quality employment development. Firstly, enhancing the quality of employment facilitates the optimization of labor resource allocation and enhances economic efficiency. Secondly, high-quality employment serves as a fundamental pillar for social equity and stability. Lastly, continual enhancement of employment quality caters to the requirements of social development and plays a crucial role in promoting economic transformation and achieving sustainable development. However, what is the current situation of employment quality in China? How can we scientifically measure employment quality? What are the key factors for the development of employment quality? This study aimed to use spatiotemporal tensor data to measure the level of employment quality in China’s provinces and analyzed the magnitude and direction of its influencing factors in the spatiotemporal dimension. Taking thirty provinces, autonomous regions, and municipalities directly under the central government in China from 2011 to 2020 as the research objects, the employment quality evaluation system was constructed from six dimensions: employment environment, employment status, employability, labor remuneration, social security, and labor relations. The employment quality index data were expressed in the form of three-order, high-dimensional tensor spatiotemporal data, and the employment quality of China’s provinces was measured from the spatiotemporal perspective by using principal tensor analysis. Then, the visual analysis of the development and change process of employment quality was carried out. The spatial autocorrelation analysis of employment quality was carried out, and the time–space dual-fixed-effect model of the spatial Durbin model was selected to analyze the direction and magnitude of the influence factors of employment quality on the selected and neighboring provinces. The research showed that: (1) The overall level of employment quality in China was not high, the employment quality varied greatly among provinces, and the employment quality development gap among provinces showed a trend of widening. (2) The development of employment quality in western China was relatively fast, while the development of employment quality in central China showed insufficient stamina. (3) Sichuan Province had a strong radiation effect on the development of employment quality in neighboring provinces, and Beijing and Tianjin had a strong siphon effect on the development of employment quality in neighboring provinces. (4) The level of industrialization and informatization promoted the development of employment quality in China’s provinces, while the industrial structure had a significant negative effect on the development of employment quality. According to the research findings, the following policy recommendations are proposed: (1) strengthen inter-provincial cooperation and exchange, (2) emphasize support for the central and western regions, (3) fully leverage the radiation effect of Sichuan while optimizing the siphon effect of Beijing and Tianjin, and (4) enhance industrialization and information technology levels, as well as adjust the industrial structure.

An adaptive enhanced envelope spectrum technique for bearing fault detection in conditions characterized by strong noise

Rolling bearings are widely used in rotating machinery and have a high failure rate. Regrettably, the task of ensuring dependable bearing fault detection presents a formidable challenge, especially when the bearing fault-related characteristics are non-stationary or even affected by strong noise. In response to this challenge, a novel adaptive enhanced envelope spectrum (AEES) technique is proposed in this study. Firstly, it generates representative intrinsic mode functions (IMFs) using the variational mode decomposition algorithm. Then, based on the analysis of the envelope spectrum normalized mutual information and time-domain fuzzy entropy, a new IMF selection and integration strategy combining time- and frequency-domain metrics is suggested to reconstruct the most informative analytical signal. An adaptive filter is employed to post-process the reconfigured signal to reinforce fault-related impulsive characteristics, the optimal length of which is ascertained through the proposed variable step-size search technique based on unbiased autocorrelation analysis. The efficacy of the AEES technique has been validated through a sequence of experiments conducted under diverse bearing conditions. Its robustness and distinct advantages under strong noise conditions are tested using a publicly available dataset. The validation results show that the AEES technique can effectively identify the health conditions of bearings under high noise conditions (signal-to-noise ratios between 1 dB and 3 dB). Compared with two relevant techniques in the existing literature and a classical method, the proposed AEES technique can achieve signal processing results with fewer interference components and more prominent characteristic frequency information and has a unique ability to identify fault features in some challenging situations.