Exploratory Data Analysis Methods Research Articles

Development and Analysis of a Reconnaissance-Technique Knowledge Graph

Penetration testing involves the use of many tools and techniques. The first stage of penetration testing involves conducting reconnaissance on a target organization. In the reconnaissance phase, adversaries use tools to find network data, people data, company/organization data, and attack data to generate a risk assessment about a target to determine where initial weaknesses may be. Although a small number of tools can be used to conduct many of reconnaissance tasks, including Shodan, Nmap, Recon-ng, Maltego, Metasploit, Google and more, each tool holds an abundance of specific techniques that can be used. Furthermore, each technique uses unique syntax. For example, Nmap holds over 600 scripts that make up its Nmap Scripting Engine. Depending on the type of device targeted, Nmap scripts can scan for ports, operating systems, IP addresses, hostnames and more. As another example, Maltego operates over 150 transforms or modules that collect data on organizations, files and people. Understanding which reconnaissance tool, techniques within those tools, and the syntax for each technique represents a highly complex task. MITRE ATT&CK, a widely accepted framework, models tactics and techniques within the tactics to help users make sense of adversarial behaviours. The tactic of reconnaissance is modelled in ATT&CK as well as its techniques. However, the explicit links between reconnaissance techniques are not modelled. Our research focused on the development of an ontology called Recontology to model the domain of reconnaissance. Recontology was then used to form Reconnaissance-Technique Graph (RT-Graph) to model 102 reconnaissance techniques and the directional links between the techniques. We used exploratory data analysis (EDA) methods including a graph spatial-layout algorithm and several graph-statistical algorithms to examine RT-Graph. We also used EDA to find critical techniques within the graph. Patterns across the results are discussed as well as implications for real-world uses of RT-Graph.

Design of Fe36.29Cr28.9Ni26.15Cu4.17Ti1.67V2.48C0.46 HEA using a new criterion based on VEC: Microstructural study and multiscale mechanical response

The present work updated empirical parameter ranges with a high adjustment to the experimental results as obtained by the means of the exploratory data analysis (EDA) method. A new high entropy alloy with FCC structure reinforced by precipitation of intermetallic phases fabricated by vacuum-argon induction melting was designed and modeled. The main results showed that the valence electron concentration (VEC) is the predominant empirical phase prediction parameter in high entropy alloys and that the lattice packing factor is necessary to determine the presence of intermetallic phases effectively. Phase stability ranges based on VEC associated with the base crystal structures and the presence of intermetallics corroborated computationally by CALPHAD and experimentally were reported. The interdendritic zone proved to be a preferential precipitation zone with precipitates of σ, TiC, and γ' phases. The γ' phase showed a size difference between the dendritic and interdendritic zone associated with diffusive Ti mechanisms. The nanoscale mechanical response determined that dislocation creep and reinforcement in the interdendritic zone are predominant creep mechanisms that obtained an effective entanglement of the dislocations increasing the strain hardening coefficient. The mechanical response of the alloy obtained is superior to the average of the alloys with FCC structure. It maintains a high ductility that allows reaching an energy absorption and damage tolerance of 43.56 GPa% showing severe plastic slip lines being in the range of use for aerospace applications and hydrogen tanks.

ICT Usage in Enterprises in the Years 2010–2019 – Poland in Comparison with Other European Union Countries

As Eurostat’s glossary explains, the term Information and Communication Technologies (ICT): ‘covers all technical means used to handle information and aid communication. This includes both computer and network hardware, as well as their software.’ In both local and global perspective, the ICT impact on modern economies and societies is undeniable. Moreover, it is growing, as the usability and technical capabilities are expanding. The researchers recognised that the ICT expansion in enterprises is a stimulant for economic development, as it strengthens competitiveness and innovation. Its impact on labour markets is significant, and constantly increasing demand for digital competences and ICT specialists can be observed. In both global and local perspective, the ICT sector is growing dynamically along with its value share in GDP. Monitoring the development of ICT usage as well as analysing how it stimulates socio‑economic transformations and growth are crucial for global leaders, governments and local authorities all over the world in order to formulate policy at all levels. Also, it plays a significant role in modern businesses expansion, as it strengthens innovativeness and competitiveness. The main objective of the paper is to study the ICT usage development in Poland against other EU countries from the enterprises’ perspective in the years 2010–2019 (before the COVID–19 pandemic and Brexit). The research presented was based on Eurostat data. The variables were selected on the basis of the literature review on ICT usage, as well as the criterion of data availability and comprehensiveness. The exploratory data analysis methods dealing with three‑way data structures, i.e. the between and within‑class principal component analysis, were used, and the presentation of the results was supported by factorial maps (scatterplots and biplots). In the analysed period, enterprises in all the European Union Member States intensified their ICT usage. Despite the positive trend from 2010 to 2019, Poland remained far behind the leading countries, and more precisely, was in the group of the least developed ones.

Coupling Coordination Relationship and Dynamic Response between Urbanization and Urban Resilience: Case of Yangtze River Delta

In the context of rapid urbanization, urban resilience, as a new way of thinking to seek solutions to urban risk crises, has become an important direction and a new development trend in the continued acceleration of urbanization. This study takes the Yangtze River Delta (YRD) as the study object, establishes a comprehensive evaluation index system of urbanization and urban resilience from a multi-dimensional perspective based on the improved entropy value method, and uses the coupling coordination degree (CCD) model, the kernel density estimation method, and the exploratory spatial data analysis (ESDA) method to investigate the spatio-temporal evolution trends of the CCD level of urbanization and urban resilience. Further, the dynamic response relationship of the coupling between the two systems is revealed by the PVAR model. The study results are shown as follows: (1) The urbanization level and the urban resilience level show a box-shaped clustering of overall urbanization values and urban resilience values, with a widening absolute gap between extreme value cities. (2) The kernel density estimates of CCD values for urbanization and urban resilience show an upward trend in the overall level of CCD, with regional integration replacing multi-level differentiation. (3) The level of CCD shows a continuous upward trend in terms of the spatial distribution characteristics of CCD, and the high-class area shows regional integration. (4) The spatial agglomeration trend of CCD continues to develop, reaching a region-wide hot spot agglomeration. (5) The PVAR model indicates that there is a dynamic response relationship between the urbanization system and the urban resilience system. Finally, based on the above research results, this study gives policy recommendations for the coordination and sustainable development of the urbanization system and the urban resilience system, providing some academic references for the relevant departments in the YRD to accelerate urbanization, enhance the urban resilience level, and promote regional integration.

Evaluation and Spatial Correlation Analysis of Green Economic Growth Efficiency in Yangtze River Delta Urban Agglomeration

The Yangtze River Delta urban agglomeration has an extremely important strategic location in the national regional development pattern, is the engine of China’s green economic development, and plays an important role in promoting the green transformation of the national economy. It is important to clarify the region’s current situation and the space–time characteristics of green economic growth. This study uses a super-efficiency dynamic Slacks-Based Measure (SBM) model to measure the green economic growth efficiency (GEGE) of 41 cities in the Yangtze River Delta urban agglomeration. Based on this, the exploratory spatial data analysis (ESDA) method is used to analyze the spatial correlation of the GEGE. Differently from previous studies, this paper evaluates the GEGE based on a dynamic perspective, considering the intertemporal role of capital. At the same time, the space–time analysis of regional systems (STARS) is used to explore the long-term development pattern and transition path of the GEGE in the Yangtze River Delta urban agglomeration. The results show the following: (1) The GEGE in the Yangtze River Delta urban agglomeration shows a fluctuating downward trend. The efficiency values of the Shanghai, Jiangsu, Zhejiang, and Anhui are significantly different, showing the distribution law of “high in the east and low in the west”. (2) The global spatial autocorrelation has weakened, but the characteristics of local agglomeration are obvious. (3) The space–time transitions show high spatial stability and path dependence. The findings highlight that the economic development of the Yangtze River Delta urban agglomeration is undergoing a difficult period of transition. Despite a decline in the GEGE, the overall regional linkage shows a positive trend. The conclusions can provide a reference for enhancing the green economic development of the Yangtze River Delta urban agglomeration. The implications of this research are important for the implementation of a regional integration strategy and the early achievement of the emission peak and carbon neutrality goals.

Spatial-temporal characteristics of corrected total phosphorus pollution loads from agricultural non-point sources in Tuojiang River watershed, Sichuan Province of southwestern China.

Traditional method of estimating pollution loads may neglect the internal spatial heterogeneity of socio-economic driving factors, which can result in overestimate and underestimate of pollution loads. In this study, the corrected approach to estimating total phosphorus (TP) pollution load was proposed to explore its future variation to develop effective phosphorus pollution control strategies for water environment management. As the first-class tributary of the Yangtze River, the TP out of limits in the Tuojiang River is serious. Thus, based on the presently related basic datasets related to TP pollution load estimation, we firstly adopted the GM (1,1) model to predict their varied trends from 2021 to 2025. We then used the pollution emission coefficient method to calculate the TP pollution load. Moreover, considering the temporal and spatial heterogeneity of the pollutant generation coefficient, we further introduced population and GDP factors to further modify the pollutant generation coefficient to correct TP pollution load. Finally, we employed the exploratory spatial data analysis (ESDA) method to explore spatial distribution characteristics and spatial autocorrelation of TP pollution load from diverse pollution sources in 2025. The results showed that the total TP pollution load from diverse pollution sources will increase from 12,194.92 t in 2021 to 12,461.26 t in 2025, an increase of 2.18%. More concretely, the TP pollution load from rural domestic sewage, rural domestic waste and livestock, and poultry pollution sources will separately decrease by 94.24 t, 77.9 t, and 86.52 t. However, the TP pollution load from agricultural runoff and agricultural solid wastes pollution sources will increase by 74.52 t and 451.49 t, respectively. The contribution of TP pollution load from diverse pollution sources to total TP pollution load will be as follows: livestock and poultry (63.49%) > agricultural solid wastes (16.72%) > agricultural runoff (12.26%) > rural domestic sewage (4.12%) > rural domestic waste (3.41%). The difference in the spatial distribution of TP pollution load from diverse pollution sources in 2025 will be prominent. TP pollution from rural domestic sewage and rural domestic waste pollution sources is more serious in the Xindu and Longquanyi districts, and that from agricultural runoff and agricultural solid wastes pollution sources is more prominent in the midstream and downstream. TP pollution load from livestock and poultry pollution source is higher in the Renshou, Anyue, Rongxian, Luxian counties, and Jiangyang district. Additionally, TP pollution load from rural domestic sewage, rural domestic waste, agricultural runoff, and agricultural solid wastes pollution sources in 2025 will show a clear spatial correlation, but the spatial correlation of TP pollution load from livestock and poultry pollution source will be weak. The study is effective to eliminate the influence of temporal and spatial variation of pollutants generates coefficients on TP pollution load estimation. The method can reflect the actual condition of pollution loads in watersheds more objectively, which can be applied to estimate other pollution loads of similar watersheds with intensive socio-economic activities. The findings in this study can provide a critical reference for the stakeholders to balance water environment conservation and socio-economic development.

Heterogeneity and optimization of ecological security pattern on a mountain town: A case of Tianzhu County in the Hexi Corridor, China

As a primary concern in the ecosystem, understanding the impact of spatial heterogeneity of ecological networks on the development of environmental sustainability has overarching significance. The Tibetan Plateau’s edge is a vital contribution to the study of the plateau’s ecological network. However, there are few studies and explorations on the county-level ecological network in the arid region. This study aimed to evaluate ecological network spatial patterns in Tianzhu County and establish an ecological security evaluation index system. We used the minimum cumulative resistance (MCR) model and built an ecological resistance surface model from the exploratory spatial data analysis (ESDA) method. Then, by identifying ecological corridors and ecological nodes from the gravity model, we analyzed the ecological security pattern and proposed specific plans for optimizing the situation. The results showed that 1) county ecological security overall has been lower, and its values showed spatial heterogeneity in each direction, and 2) the Z-Score of the ecological security evaluation index was 70.1893, which shows ecological vulnerability in the arid region has significant spatial autocorrelation. The study identified 156 ecological corridors and 112 ecological nodes, which formed an ecological spatial pattern of “one belt and three zones.” Our analytical framework offers a valuable tool for constructing ecological security patterns in Tianzhu County and selecting “sources” at the regional scale, which can be applied to landscapes and geographical contexts for sustainable development in arid regions.

Coordinated Development of Farmland Transfer and Labor Migration in China: Spatio-Temporal Evolution and Driving Factors

The coordinated development of farmland transfer (FT) and labor migration (LM) is of great efficiency significance to facilitate the development of rural economy and implement the rural revitalization strategy. The study used socioeconomic data from 30 provinces/autonomous regions/municipalities (hereafter referred to as provinces) in China to measure the coupling coordination degree (CCD) of FT and LM. It adopted the coupling coordination degree model (CCDM), exploratory spatial data analysis method (ESDA), and gray relational analysis model (GARM) to investigate the spatial differences in the CCD and its influencing factors. The results indicate the following: (1) Regional differences are evident despite the fact that the comprehensive evaluation level of FT and LM in the various provinces is relatively low and displaying a rising trend. (2) The CCD of FT and LM exhibits a fluctuating upward trend and is at the primary coupling coordination stage, with a significant difference in coupling coordination levels between regions, and a spatial distribution pattern of central region > eastern region > northeast region > western region. (3) The CCD shows a strong global spatial positive correlation with clear fluctuations, demonstrating the agglomeration dispersion development tendency over time; the local spatial agglomeration state emerges and stabilizes. According to the distribution pattern, the Western region exhibits weak agglomeration type, whereas the eastern and central regions exhibit strong agglomeration type. (4) There are significant variations between provinces in terms of the intensity of the CCD of FT and LM, as well as the level of concurrent employment business, the level of non-agricultural industry development, the level of urbanization, the level of agricultural equipment, and the land approval.

An Overview on the Application of Chemometrics Tools in Food Authenticity and Traceability.

The use of advanced chemometrics tools in food authenticity research is crucial for managing the huge amount of data that is generated by applying state-of-the-art analytical methods such as chromatographic, spectroscopic, and non-targeted fingerprinting approaches. Thus, this review article provides description, classification, and comparison of the most important statistical techniques that are commonly employed in food authentication and traceability, including methods for exploratory data analysis, discrimination, and classification, as well as for regression and prediction. This literature revision is not intended to be exhaustive, but rather to provide a general overview to non-expert readers in the use of chemometrics in food science. Overall, the available literature suggests that the selection of the most appropriate statistical technique is dependent on the characteristics of the data matrix, but combining complementary tools is usually needed for properly handling data complexity. In that way, chemometrics has become a powerful ally in facilitating the detection of frauds and ensuring the authenticity and traceability of foods.

The Spatial-Temporal Transition and Influencing Factors of Green and Low-Carbon Utilization Efficiency of Urban Land in China under the Goal of Carbon Neutralization

Urban-land development and utilization is one of the main sources of carbon emissions. Improving the green and low-carbon utilization efficiency of urban land (GLUEUL) under the goal of carbon neutrality is crucial to the low-carbon transition and green development of China's economy. Combining the concept of green and low-carbon development in urban land use, carbon emissions and industrial-pollution emissions are incorporated into the unexpected outputs of the GLUEUL evaluation system. The super-efficient slacks-based measure (SBM) model, Exploratory Spatial-Temporal Data Analysis (ESTDA) method and Geographically and Temporally Weighted Regression (GTWR) model were used to analyze the spatial-temporal transition and the influencing factors of GLUEUL in 282 cities in China from 2005 to 2020. The result shows that: (1) From 2005 to 2020, the green and low-carbon land-utilization efficiency of Chinese cities shows an increasing temporal-evolution trend, but the gap between cities is gradually widening. (2) From the spatial-temporal dynamic characteristics of Local Indicators of Spatial Association (LISA), regions with the highest GLUEUL have strong dynamics and instability, while cities at the lowest level have a relatively stable spatial structure. On the whole, the local-spatial-transfer direction of GLUEUL of each city is stable, with certain path-dependent characteristics. (3) There are differences in the degree of influence and direction of action of different factors on GLUEUL. The economic development level, industrial-structure upgrading, financial support, wealth level, and green-technology-innovation ability have positive effects on overall GLUEUL, with industrial-structure upgrading promoting GLUEUL the most, while urban population size, foreign-investment scale, and financial-development level play a negative role. This study can provide some empirical and theoretical references for the improvement of GLUEUL.

The Coupling Coordination Degree and Spatial Correlation Analysis of the Digital Economy and Sports Industry in China

Driven by a new round of scientific and technological revolution and industrial transformation, the interactive and integrated development of the digital economy and the sports industry has become the objective demand of current economic development. In order to explore the coupling coordination relationship between the digital economy and the sports industry, this paper uses the coupling coordination degree model and exploratory spatial data analysis method to analyze the coupling coordination degree and spatial correlation of the integrated development of China’s digital economy and its sports industry. It does this by taking the statistical data of 30 provinces, autonomous regions and municipalities in China from 2015 to 2019 as observation samples. The results show that the coupling coordination degree of China’s digital economy and sports industry is low, showing an unbalanced development trend of “low in the west, high in the east, low in the north and high in the south”. There is a significant positive clustering in spatial integration of the two, and the degree of clustering increases year by year. It is necessary to establish a regional coordinated development mechanism, define the stage of regional integration, optimize the spatial pattern of coupled development, and promote the balanced development of digital economy and sports industry.

Global performance strategies in leading Japanese automotive organisations

The purpose of this paper is to examine the correlation between the evaluation of performance strategies in leading automotive organisations located in Japan during four economically significant periods. Furthermore, the article aims to determine key performance factors that have had an influence on automotive organisations in the most recent and current period. The sample group includes 14 large and very large corporations. This paper draws on both theoretical and empirical research. A questionnaire was created as part of the research and was pre-tested in order to increase its internal validity. The actual survey was conducted through semi-structured interviews with managers at the top management level. To address the aim, non-parametric statistical methods have been used (Kruskal-Wallis test and Spearman correlation), mainly due to the relatively small testing sample of companies and the Shapiro-Wilk test failing at the five percent level of significance. Additionally, exploratory data analysis methods have been applied. Despite the noticeable deviation in the period of economic recession, the results indicate an increase in the significance of the individual factors in the periods in question. Another interesting finding is the growing power of factors oriented at innovation and the future environment. This means that, for the companies, measuring these factors will be crucial henceforth.

Spatial Relationship between the Residential Land Price and the Land Intensive use in Hebei Province

Using the exploratory spatial data analysis method to analyze the level of residential land price, and calculate the use level of urban land intensive use based on the PSR model, exploring the differences between the urban residential land price and land intensive spatial in the city of Hebei Province in 2019 and make relevant suggestions. The result shows (1) The land price level of urban housing is characterized by spatial differentiation of circle structure with Langfang city as the center and decreasing outward. (2) The overall level of urban land intensive use shows the spatial differentiation characteristics of high in the southeast and low in the northwest. (3) The spatial distribution of urban residential land price level is different from that of land intensive use level, and there is a situation that the land price level is high and the urban land intensive use level is low. (4) Because of the shortcomings in the development of land price and intensive land use, some suggestions are put forward from the overall perspective of the whole province and the specific situation of each city.

The Space–Time Evolution of the Coupling and Coordinated Development of Public Cultural Services and Cultural Industries: A Case Study of 31 Regions in China

The coordinated development of public cultural services (PCS) and cultural industries (CI) is conducive to sustainable regional development. Few studies focus on the coordinated development of PCS and CI. This study builds an evaluation index system for the coordinated development of PCS and CI and uses the entropy weight method, synchronous development model, coupling coordination model, and exploratory spatial data analysis method on 31 regions in China. It evaluates the synchronous development levels, coupling coordination levels, and spatial evolution characteristics of the coordinated development of PCS and CI from 2011 to 2020. The results are as follows: (1) The coordinated development level of PCS and CI has risen steadily. The leading type is dominant in space, with the leading type > synchronous type > lagging type. (2) The overall coupling degree is high. The high-level coupling in space is dominant. (3) The degree of coupling coordination has improved. Regions with good spatial and high-quality coordination are concentrated in the eastern, central, and coastal areas. (4) The coordinated development of PCS and CI shows positive spatial correlation agglomeration. The degree of agglomeration is increasing, mainly high high, forming an important growth region in the Yangtze River Delta economic region and its surroundings. Finally, we propose policy recommendations for the coordinated development of PCS and CI, and provide new ideas for the collaborative development of PCS and CI in China.

The contribution of tourism mobility to tourism economic growth in China.

Mobility is the key factor in promoting tourism economic growth (TEG), and the transportation infrastructure has essential functions for maintaining an orderly flow of tourists. Based on the theory of fluid mechanics, we put forward the indicator of tourism mobility (TM). This study is the first to measure the level of TM in China and analyze the spatiotemporal evolution characteristics of TM. Applying the Exploratory Spatial Data Analysis method, we analyze the global and local spatial correlation characteristics of TM. Moreover, we further estimate the contribution of TM to TEG by econometric models and the LMDI method. The results show that (1) the TM in China has maintained rapid growth for a long time. However, there are differences in the rate of growth in different regions. The TM in each region only showed a significant positive spatial correlation in 2016-2018. The space-time pattern is constantly changing over time. The local spatial autocorrelation results of TM are stable, and various agglomeration states are stably distributed in some provinces. (2) The regression results of the traditional panel data model and spatial panel data model both show that TM has a significant positive effect on TEG. Moreover, TM has a negative spatial spillover effect on neighboring regions. (3) The result from the decomposition of LMDI shows that the overall contribution of TM to TEG is 15.76%. This shows that improving TM is a crucial way to promote the economic growth of tourism.

The Image Data Explorer: Interactive exploration of image-derived data.

Many bioimage analysis projects produce quantitative descriptors of regions of interest in images. Associating these descriptors with visual characteristics of the objects they describe is a key step in understanding the data at hand. However, as many bioimage data and their analysis workflows are moving to the cloud, addressing interactive data exploration in remote environments has become a pressing issue. To address it, we developed the Image Data Explorer (IDE) as a web application that integrates interactive linked visualization of images and derived data points with exploratory data analysis methods, annotation, classification and feature selection functionalities. The IDE is written in R using the shiny framework. It can be easily deployed on a remote server or on a local computer. The IDE is available at https://git.embl.de/heriche/image-data-explorer and a cloud deployment is accessible at https://shiny-portal.embl.de/shinyapps/app/01_image-data-explorer.

Spatio-Temporal Characteristics and Influencing Factors of Basic Public Service Levels in the Yangtze River Delta Region, China

Basic public services are essential to ensure regional social equity and promote regional integrated development. As the Yangtze River Delta region (YRDR) is an example of integrated regional development in China, the integration of basic public services plays a crucial role in promoting regions’ integrated development. However, little studies provide evidence of the characteristics and influencing factors of basic public services in the YRDR. Taking the YRDR as the study area, this paper constructed a comprehensive evaluation index system for the basic public services level (BPSL) in the YRDR from 2010 to 2020. Then, it measured and analyzed its spatio-temporal dynamic evolution characteristics using entropy-weighted TOPSIS and exploratory spatial data analysis methods, as well as analyzed the spatio-temporal heterogeneity of its influencing factors using a geographically and temporally weighted regression model. The results show that: (1) The BPSL in the YRDR generally improved during the study period. There was a huge variation within and between provinces in the BPSL. Over time, the BPSL gradually transitions from unipolar polarization to multipolar differentiation and a flattening trend. (2) Spatial differentiation of the BPSL was evident, with a decreasing gradient from east to west with an inverted U-shape distribution in the north–south direction. The overall spatial circle structure was characterized as being high in the east and low in the west, high in the center, and low in the north and south, forming a spatial distribution pattern of high-level and higher-level grades mainly in Shanghai, southern Jiangsu, and northern Zhejiang. The global spatial correlation characteristics became increasingly significant with time, while the local spatial correlation showed the trend of “spatial club convergence”. (3) Various factors influenced the spatial and temporal evolution of the BPSL, including the urbanization level, the economic development level, the industrial structure level, the degree of external openness, the government action capacity, and the regional population size, each of which had evident spatial and temporal heterogeneity.

Temporal and spatial differentiation characteristics of ecosystem service values based on the ecogeographical division of China: a case study in the Yellow River Basin, China.

The identification of spatiotemporal changes in ecosystem service values (ESVs) and their drivers is the basis for ecosystem service administration and decision-making. This research focuses on the Yellow River Basin (YRB). With a multitemporal land use and land cover (LULC) dataset (1995-2018), the equivalence coefficient method with spatiotemporal dynamic correction and exploratory spatial data analysis methods were used to evaluate ESV changes due to LULC changes and their spatial characteristics. The contributions of the ESV driving factors and their mutual effects were also investigated via geographic detectors. The results revealed that (1) the land use structure of the YRB, mainly grassland and cultivated land, was stable from 1995 to 2018. However, the transition between land use types was dramatic, including urban expansion accompanied by losses of farmland, grassland, and unused land; increased forestland; and significant increases in water bodies and wetland areas. (2) During the study period, the overall ESV of the YRB increased, and hydrological regulation and climate regulation services dominated the change in the ESVs in the study area. The ESV exhibited obvious ecogeographical pattern differentiation and evident positive spatial autocorrelation. High values were concentrated in the southern part of the study area, including the southeastern part of the Qinghai-Tibet Plateau region and the central part of the East Asian monsoon region. Low values were concentrated in the northwestern arid zone, dominated by desert and grassland ecosystems. (3) Because of the fragility of the regional ecological background, the spatial differentiation of the ESVs in the YRB is dependent on natural factors; however, anthropogenic factors such as the degree of land use and the human activity intensity also lead to ESV differentiation. The synergistic effects of human activities, landscape pattern changes, and natural factors result in the spatial differentiation of the ESVs in the research region. Therefore, human activities affecting the ecological environment should be controlled, nature-based solutions should be advocated, patch diversity should be increased, landscape fragmentation should be reduced, LULC ecosystem service functions should be improved, and the relationship among economic, social, and ecological landscape resources should be coordinated.

Leadership and power sharing in Nigerian federalism: issues and perspectives

Federalism is a practical political cum constitutional design for managing complex governmental problems usually associated with ethno-religious and cultural diversity. The abysmal performance of the Nigerian state in the area of development and national integration since independence in 1960 has been attributed mainly to the quality, nature, and character of the nation's leaders. The paper examines the impact of leadership and power-sharing on Nigeria's Federalism, focusing on the issues and perspectives. Exploratory research design, documentary sources, and qualitative descriptive data gathering and analysis methods were adopted. Anchoring our discourse on the Self-Reliance theory, findings amongst others revealed that; the attitudes of Nigeria's political class in their intra-class struggle for political power to consolidate on their primitive accumulation of wealth developed a penchant for aggravating existing cleavages by interpreting politics in terms of survival of ethnic or regional entities. This explains the reasons for the agitation by every region/ethnic group to produce a president or governor at the federal and state levels. The paper recommends, amongst others, that; there should be an emergence of leaders with nationalist appeal who would be more interested in building a nation out of the diverse ethnic and religious nationalities as found presently in Nigeria.

Spatial Differentiation and Dynamic Evolution of Agricultural Carbon Emissions in Fujian Province of China

The previous literatures have insufficient content on spatial dependence and heterogeneity of agricultural carbon emissions (ACEs), which is inconsistent with the actual situation, weakening the practical significance of research conclusions. To fill this knowledge gap, this study attempts to explore the spatial evolution pattern of ACEs at the city-scale in the Fujian Province of China from spatio-temporal latitudes and adopts the exploratory spatial data analysis method (ESDA) to analyze the spatial correlation effects of ACEs. The findings revealed that ACEs in Fujian show a downtrend as a whole. From the perspective of carbon sources of ACEs, agricultural materials and livestock breeding caused the largest emissions, accounting for 73.82% of the total ACEs, while rice growth led to the smallest carbon emissions, accounting for 26.18% of the total ACEs. We also found that there is obvious non-equilibrium in the spatial distribution of ACEs and their intensity, showing a strong spatial correlation; and although a relatively obvious clustering area has been formed, the spatial autocorrelation of most regions is not significant. Accordingly, we suggest that exploring the “carbon compensation mechanism”, is conducive to stimulating the low-carbon agricultural production behavior with positive externalities, to reduce agricultural carbon emissions.