Spatial Effects Research Articles

Exploring the influence of natural and cultural environments on tourism demand: a spatial analysis

ABSTRACT This study integrates natural and cultural environmental factors within a unified framework, exploring their specific effects on tourism demand in China. To more effectively account for spatial dependence and variable heterogeneity in tourism demand, we utilize the spatial Durbin model in analyzing provincial-level data spanning from 2007 to 2019. Research findings reveal: (1) Both domestic and inbound tourism display significant spatial association. (2) Natural and cultural factors exhibit spatial spillover effects on domestic tourism demand, exemplified by sulfur dioxide generation and intangible cultural heritage quantity. (3) The impact factors or mechanisms of natural and cultural environment on domestic and inbound tourism share some similarities, but differences still exist. For instance, intangible cultural heritage prosperity stimulates regional domestic tourism but only affects local inbound tourism. This study, using China as a case, offers a practical approach and theoretical perspective for probing into the emergent growth poles in tourism demand.

The impact of European Cohesion Policy: a spatial perspective

Abstract Cohesion Policy is one of the core policy areas of the European Union and one of the largest expenditure items in its budget. Its impact is the subject of intense academic and policy debate, but its effectiveness is an empirical question still open. This article contributes to this debate by performing a region-specific investigation of the direct and indirect impact of Structural Funds expenditure. We employ a heterogeneous panel data model, which accommodates the spatial dependence in a heterogeneous setting and measures heterogeneous spatial spillover effects, both inward and outward. We also consider different channels of spatial spillovers with respect to standard geographical closeness. In particular, the introduction of new measures of proximity that explicitly consider economic linkages between regions is a novel contribution to the literature. The results clearly indicate that the impact of the Cohesion Policy, while positive overall, is highly heterogeneous and the Structural Funds expenditure generates substantial heterogeneous spatial spillovers: the positive effects do not remain confined to the target regions. Finally, strong spillover effects are channelled by value-added trade connections, particularly in regions belonging to the so-called ‘Central European Manufacturing Core’.

Direct angiographic comparison of different velocity-selective saturation, inversion, and DANTE labeling modules on cerebral arteries.

This study evaluated the velocity-selective (VS) MRA with different VS labeling modules, including double refocused hyperbolic tangent, eight-segment B1-insensitive rotation, delay alternating with nutation for tailored excitation, Fourier transform-based VS saturation, and Fourier transform-based inversion. These five VS labeling modules were evaluated first through Bloch simulations, and then using VSMRA directly on various cerebral arteries of healthy subjects. The relative signal ratios from arterial ROIs and surrounding tissues as well as relative arteria-tissue contrast ratios of different methods were compared. Double refocused hyperbolic tangent and eight-segment B1-insensitive rotation showed very similar labeling effects. Delay alternating with nutation for tailored excitation yielded high arterial signal but with residual tissue signal due to the spatial banding effect. Fourier transform-based VS saturation with half the time of other techniques serves as an efficient nonsubtractive VSMRA method, but the remaining tissue signal still obscured some small distal arteries that were delineated by other subtraction-based VSMRA, allowing more complete cancelation of static tissue. Fourier transform-based inversion produced the highest arterial signal in VSMRA with minimal tissue background. This is the first study that angiographically compared five different VS labeling modules. Their labeling characteristics on arteries and tissue and implications for VSMRA and VS arterial spin labeling are discussed.

Experimentally Closing the Balance of Progress of Reaction in Premixed Turbulent Combustion in the Thin Flame Regime

We investigate the possibility of determining the local turbulent flame speed by measuring the individual terms in the balance of a mean progress of reaction variable for the case of a low turbulence methane-air Bunsen flame in the thin flame regime. Velocity distributions and flame edge positions were measured by particle image velocimetry techniques at 3 kHz for a flame stabilized by a surrounding pilot of the same stoichiometry, for a turbulent Reynolds number around 66 and Karlovitz numbers of the order of 4. The conservation equation for mean progress variable was analyzed along different streamlines as a balance of terms expressed as velocities, including terms for convection, turbulent diffusion, mean reaction, and turbulent and molecular diffusion. Each term was estimated from local velocities and flame locations using a thin flame approximation, and their uncertainty was evaluated based on propagation of experimentally measured statistical correlations. The largest terms were the convective and reaction terms, as expected, with smaller roles for turbulent and molecular diffusion across the flame brush. Countergradient diffusion and transition to gradient diffusion were observed across the flame brush. Closure of the balance of terms in the conservation equations using independently measured terms was not consistently achieved across the flame brush within the reckoned uncertainties, arriving at a balance within 20–30% of the absolute value. Testable hypotheses are offered for the possible reasons for the mismatch, including the role of spatial filtering and 3D effects on the reaction rate term. Finally, the experiments identify the inaccuracies in measuring a true local turbulent flame speed, and suggest a consistent methodology to reduce errors in such estimations. This is the first time such a detailed experimental closure is attempted for any configuration. The results suggest that the significant improvements in spatial resolution are necessary for a full closure.

Analysis of the impact factors of industrial structure upgrading on green total factor productivity from the perspective of spatial spillover effects

Green development has already been a vital part of China's high-quality economic progress in the future, and accelerating the restructuring and improvement of the industrial structure plays a crucial roll in promoting a regional green economy. In this article, based on the data of 278 prefecture-level cities in China from 2011 to 2020, the SBM directional distance function and Malmquist-Luenberger (ML) index are used to gauge regional green total factor productivity (GTFP). The spatial Durbin model is also introduced to investigate the spatial spillover mechanism of GTFP and its influencing factors under the optimized and upgraded industrial structure. The study indicates that the optimization of the industrial structure have an important effect in promoting the growth of GTFP. Specifically, industrial structure integration has a greater bearing on the increase in GTFP, while there is a difference in the effectiveness of industrial structural advancement and rationalization of GTFP. Economic growth level inhibits the enhancement of GTFP, and urbanization level and industrial agglomeration have a significant negative impact on the enhancement of GTFP in the spatial dimension. On a different hand, foreign investment degree and government intervention level have a significant positive affect on regional GTFP. In addition, this study fills the research gap of the regional industrial structure upgrading influence on GTFP, which has great theory and practice value for promoting China's high quality growth of green economy.

Integration effect of shipping network based on shipping alliances

ABSTRACT Shipping alliances and shipping lines are one major research field concerning marine management. This paper examines the role played by shipping lines in shaping the global container shipping network, and focuses on the significant impact of shipping alliances on the global shipping market. The scientific evaluation of the effects of shipping alliances construction and reorganization on network integration remains inadequate. To bridge this gap, our study uses AIS big data to construct a comprehensive model of the container shipping network from the perspective of multilayer, focusing on two levels: shipping alliances and shipping lines. Our findings show that while shipping lines have been competing for shipping markets fiercely, the construction of shipping alliances eases the competition among them and promotes their cooperation. The three alliances have formed a new oligopoly pattern, combining to build a complete and mature network with increased efficiency, density, and stability. Shipping alliances promote spatial complementarity, expand network coverage, and develop branches. We also identify distinct spatial patterns for each alliance, with differentiated complementary structures. This study sheds light on the spatial effect of shipping network integration, offering a new perspective and method for understanding the organization of the global shipping network.

Digital financial inclusion and upgrading of consumption structure: Evidence from rural China

Based on the perspective of spatial economy, this paper focuses on the primary effects and spatial characteristics of Digital Financial Inclusion (DFI) on the upgrading of rural consumption structure (URCS) in China, conducting a literature review and theoretical analysis. It then uses statistical data collected over the years and the Digital Financial Inclusion Index (DFII) of Peking University to prepare panel data for 31 provinces in China (aside from Hong Kong, Macao, and Taiwan) from 2011 to 2020 for empirical testing. The results are as follows: DFI can considerably boost URCS, and there is a strong spatial neighbor impact, that is, it is affected by random shocks in surrounding provinces via its spatial effect; DFI has nonlinear characteristics in the process of fostering URCS, with the threshold variables of income level and family sizes; the impact of DFI on URCS is spatially heterogeneous, and the promotion of the eastern region is better than other zones. These results can inform policymakers about rural development and provide valuable references to push forward rural vitalization.

The impact of different transportation infrastructures on urban carbon emissions: Evidence from China

Transport infrastructure is an important source of carbon emissions, and different transport infrastructure have varying impacts on urban carbon emissions, which has been lacking in previous research. This study selects 273 cities in China from 2005 to 2020 and applied the spatial Durbin model and mediation effect model to empirically examine the direct impact effects, spatial spillover effects, scale and regional heterogeneity, and indirect pathways of highways, high-speed railways, and urban rail on urban carbon emissions. The results shows that: (1) Overall, high-speed railways have a significant reducing effect on carbon emissions, while highways and urban rail have the opposite effect. (2) Considering spatial spillover effects, highways and high-speed railways can promote carbon emissions reduction in neighboring areas, while urban rail has the opposite effect. (3) For scale heterogeneity, urban rail can reduce carbon emissions in mega-cities, while highways and high-speed railways have the opposite effect. For regional heterogeneity, all three types of transport infrastructure can reduce carbon emissions in western cities, but increase urban carbon emissions in eastern and central regions. (4) Industrial upgrading, technological progress, and population agglomeration are all pathways through which transport infrastructure indirectly affects carbon emissions, but their effects vary for different transport infrastructure.

Assessing territorial space conflicts in the coastal zone of Wenzhou, China: A land-sea interaction perspective

Territorial space conflicts (TSCs) in coastal zones stem from the intricate interaction between the land-sea dual system, significantly impacting the sustainable development of these areas. To accurately identify TSCs, our study proposed a theoretical framework based on a land-sea interaction perspective. We also assessed TSCs using the territorial space conflicts index and a social network analysis model. We demonstrated the proposed spatial conflicts assessment methodology through a case study of Wenzhou, a typical city on the east coast of China. Our results indicate that the distribution of TSCs gradually decreased from the coastal zone to the inland zone, with significant variation in the distribution of different conflict types across different zones. The findings also reveal that territorial space use had diverse impacts on the space conflict network, making it urgent to take targeted measures. In the future, it is crucial to comprehensively consider the overall pattern and distribution characteristics of current TSCs, as well as the spatial spillover effect of the overall network, to develop targeted coping strategies and regulation mechanisms that promote the integration and high-quality development of coastal territorial space systems. To maintain a sustainable coastal zone process, we proposed a set of optimization paths for alleviating TSCs and promoting the coordinated development of land and sea regions in China based on our study.

Improving full-waveform inversion based on sparse regularization for geophysical data

Abstract Full-waveform inversion (FWI) is an advanced geophysical inversion technique. FWI provides images of subsurface structures with higher resolution in fields such as oil exploration and geology. The conventional algorithm minimizes the misfit error by calculating the least squares of the wavefield solutions between observed data and simulated data, followed by gradient direction and model update increment. Since the gradient is calculated by forward and backward wavefields, the high-accuracy model update relies on accurate forward and backward wavefield modelling. However, the quality of wavefield solutions obtained in practical situations could be poor and does not meet the requirements of high-resolution FWI. Specifically, the low-frequency wavefield is easily affected by noise and downsampling, which influences data quality, whereas the high-frequency wavefield is susceptible to spatial aliasing effects that produce imaging artefacts. Therefore, we propose using an algorithm called sparse relaxation regularized regression to optimize the wavefield solution in frequency-domain FWI, which is the forward and backward wavefield obtained from the Helmholtz equation, thus improving FWI's accuracy. The sparse relaxation regularized regression algorithm combines sparsity and regularization, allowing the broadband FWI to reduce the effects of noise and outliers, which can provide data supplementation in the low-frequency band and anti-aliasing in the high-frequency band. Our numerical examples demonstrate the wavefield optimization effect of the sparse relaxation regularized regression-based algorithm in various cases. The improved algorithm's accuracy and stability are verified compared to the Tikhonov regularization algorithm.

The Impact of Data Agglomeration on Export Structure Upgrading in Cities: A Factor Mobility Perspective

The digital economy and export upgrading are important topics of common concern for policymakers and academics during the period of high-quality economic development. From the perspective of factor mobility, this paper constructs the two-way fixed effect, mediation effect, and spatial Durbin models to analyze the impacts of data agglomeration on urban export structure upgrading. Using panel data of 280 cities at the prefecture level and above in China from 2005 to 2018, the empirical analysis reveals a positive impact of data agglomeration on urban export structure upgrading, with capital transfer and technology diffusion further reinforcing this impact. Additionally, data agglomeration promotes urban export structure upgrading by optimizing innovation resource allocation and exhibits a spatial spillover effect on urban export structure upgrading. Finally, the facilitating effect on urban export structure upgrading is heterogeneous. Consequently, it is imperative to expedite the construction of new digital infrastructure, foster the integration and symbiotic evolution of data and traditional production factors, and implement distinct innovation development pathways based on regional comparative advantages.

The impact of air pollution on regional innovation: empirical evidence based on 267 cities in China.

Based on the spatially correlated effects of air pollution on regional innovation, theoretical hypotheses are proposed, and this paper employs a spatial Durbin model to conduct empirical tests using panel data from 267 Chinese cities from 2003 to 2019, and investigates the mediating effect of human capital. Research has shown that (1) air pollution significantly reduces regional innovation output and has a negative spatial spillover effect significantly in the short term; (2) in the process of regional innovation impacted by air pollution, human capital acts as a mediator role; and (3) analysis of heterogeneity reveals that, from the regional perspective, air pollution has significantly damaged regional innovation in eastern and middle cities, but not significantly influences western cities, and in terms of innovation types, there is a stronger detrimental effect on invention patents exerted by air pollution compared to non-innovation patents. The study's findings provide theoretical and empirical evidence to strengthenenvironmental governance, enhance regional innovation and promote the coordinated development of regional innovation.

Towards green governance and real economy development: how digital technology affects health human resource allocation?

ABSTRACT The adoption and integration of digital technology have profoundly reshaped societal and environmental governance within the healthcare sector. This study aims to explore the influence of digital technology development on the allocation of healthcare human resources, intending to contribute to the net-zero carbon process. Utilizing panel data from 30 provinces and cities across mainland China during the period 2011 to 2020, we computed three unique indices for health resource density. Employing the spatial Durbin model, our analysis unveiled a gradual augmentation in the overall level of healthcare human resource allocation in China due to the spatial impact of digital technology development. Robustness tests substantiated a noteworthy positive spatial spillover effect of digital technology, contributing to the augmentation of healthcare human resource allocation at the regional level. Heterogeneity results revealed a notably more pronounced promotional effect in the eastern region, contrasting with the central and western regions. From the perspective of sustainable development, the development of digital technology can contribute to the advancement of environmentally friendly healthcare by optimizing the allocation of healthcare human resources. In conclusion, this study offers valuable insights for China to formulate effective policies for healthcare human resource allocation, contributing to the attainment of sustainable development goals.

Accounting for Greenhouse Gas Emissions in the Agricultural System of China Based on the Life Cycle Assessment Method

Agricultural systems contribute nearly one-third of global anthropogenic GHG emissions and are an important source of GHGs globally. The clarification of the GHG emission pattern from agriculture is of paramount importance in the establishment of an agricultural emission reduction mechanism and the realization of China’s dual-carbon target. Based on the life cycle assessment method (LCA), this paper comprehensively quantifies the greenhouse gas emissions from the agricultural system in China, encompassing rice, wheat, and corn cultivation as well as animal husbandry including cows, horses, donkeys, mules, camels, pigs, and sheep. The analysis covers the period 2000–2020 and examines the spatial distribution, temporal trends, and structural changes in the greenhouse gas emissions within China’s agriculture sector. The main results are as follows: (1) from 2000 to 2020, China witnessed a consistent upward trajectory in its total agricultural GHG emissions, exhibiting an average annual growth rate of 0.73%. Notably, methane (CH4) emissions emerged as the largest contributor, displaying an overall fluctuating pattern. Carbon dioxide (CO2) emissions demonstrated intermittent increases with a noteworthy annual growth rate of 3%, signifying the most rapid expansion within this context. Conversely, nitrous oxide (N2O) emissions experienced decline over the specified period. (2) GHG emissions from cultivation demonstrate an upward trajectory, primarily driven by the CH4 emissions originating from rice cultivation and CO2 resulting from straw incineration. Conversely, GHG emissions stemming from animal husbandry declined, with the primary source being CH4 emissions arising from animal enteric fermentation. Agricultural N2O emissions predominantly arise due to manure management and nitrogen fertilizer application. (3) Agricultural greenhouse gas emissions exhibit significant variations in spatial distribution, gradually concentrating towards the North China Plain, the middle and lower reaches of the Yangtze River, and the northeast. Specifically, agricultural CH4 emissions are progressively concentrated in China’s pivotal rice-growing regions, encompassing the middle and lower reaches of the Yangtze River Plain, as well as livestock breeding areas like Inner Mongolia. Agricultural CO2 emissions primarily concentrate in dryland crop production zones such as North China and Northeast China. Meanwhile, Agricultural N2O emissions predominantly occur in Inner Mongolia and the North China Plain. China’s agricultural greenhouse gas emissions in 2020 show a significant spatial clustering effect, with hotspots primarily concentrated in Shandong, Anhui, Henan, and other regions and cold spots focused in the western and southern areas. The emission patterns of agricultural GHGs are closely intertwined with farming practices, regional development levels, and national policy; hence, tailored measures for emission reduction should be formulated based on specific crop types, livestock categories, agricultural production activities, and regional development characteristics.

Prosperity or futility? Effects of micro-regeneration on neighborhood commercial vitality

PurposeMicro-regeneration can effectively enhance a neighborhood’s commercial vitality and serve as a viable approach to boost economic benefits. However, the small scale of micro-regeneration efforts and the fragmented nature of information currently limit the availability of strong empirical evidence demonstrating its impact on neighborhood commercial vitality. The aim of the study was to examine the link between micro-regeneration and neighborhood commercial vitality, focusing on the average, time-lag, spatial spillover, and spatial heterogeneity effects.Design/methodology/approachUsing the panel data set of 1,755 neighborhoods in Chongqing from 2016 to 2021 as the research sample, the difference-in-differences (DID) method was employed in this study to explore the impact micro-regeneration has on neighborhood commercial vitality.FindingsThe results illustrate that: (1) micro-regeneration can promote neighborhood commercial vitality in terms of the number and types of local consumption amenities by 27.76 and 5.89%, respectively, with no time-lag effect; (2) the positive spillovers can exist within the range of 5,000 meters–5,500 meters of regenerated neighborhoods; and (3) the effect of micro-regeneration on neighborhood commercial vitality can be greater in peripheral areas than in core areas of the city.Originality/valueThe findings fill the knowledge gap on the relationship between micro-regeneration and neighborhood commercial vitality. Additionally, the results on the time-lag effect, spatial spillover effects, and spatial heterogeneity provide practical implications that can support the government and private sector in developing temporal and spatial arrangements for micro-regeneration projects.

A dual-core 3D DNA nanomachine based on DNAzyme positive feedback loop for highly sensitive MicroRNA imaging in living cells

A double 3D DNA walker nanomachine by DNAzyme self-driven positive feedback loop amplification for the detection of miRNA was constructed. This method uses two gold nanoparticles as the reaction core, and because of the spatial confinement effect the local concentration of the reactants increase the collision efficiency was greatly improved. Meanwhile, the introduction of positive feedback loop promotes the conversion efficiency. In presence of miRNA-21, a large amount of DNAzyme was released and hydrolyze the reporter probe, resulting the recovery of fluorescence signal. The linear range for miRNA-21 is 0.5–60 pmol/L, and the detection limit is 0.41 pmol/L (S/N = 3). This nanomachine has been successfully used for accurate detection of miRNA-21 expression levels in cell lysates. At the same time, it can enter cells for intracellular miRNA-21 fluorescence imaging, distinguishing tumor cells from normal cells. This combination of in vitro detection and imaging analysis of living cells can achieve the goal of jointly detecting cancer markers through multiple pathways, providing new ideas for early diagnosis and screening of diseases.

Impact of Tea Tree Cultivation on Soil Microbiota, Soil Organic Matter, and Nitrogen Cycling in Mountainous Plantations

This study focused on examining the early stages of tea cultivation (1, 3, and 5 years) in mountainous tea plantations. It specifically aimed to investigate the changes in soil micro-ecology at different locations (inter-row, terrace surfaces, and terrace walls). It was revealed that as tea tree cultivation progressed over the years, bacterial diversity and co-occurrence networks annually decreased in different locations. The results of soil physicochemical index analysis showed that the soil’s available nutrients and the activities of cellulase and protease increased. Furthermore, the amplitude of variation of these indexes in the inter-row soil was significantly higher than that on the terrace surfaces and the terrace walls (p < 0.05). Alterations occurred in the soil microbial community structure, with an enrichment of bacterial genera such as Sinomonas, Granulicella, and Sphingomonas, as well as fungal genera such as Trichoderma, Penicillium, and Talaromyces; an increase in the proportion of plant pathogenic fungi (Cladosporium, Fusarium, and Curvularia) was observed in the inter-row soil. The results of soil microbial function prediction showed that nitrification and nitrogen fixation decreased, but denitrification increased (p < 0.05). In conclusion, cultivating tea trees in mountainous terraced plantations significantly impacted the soil microbial community, accelerated the metabolism of soil organic matter, disrupted soil nitrogen cycling functions, and increased the presence of plant pathogenic fungal pathogens. Moreover, the changes in the structure and functions of the soil microbial community demonstrate a spatial distance effect across different terrace locations.

Spatiotemporal modeling of under-five mortality and associated risk factors in Ethiopia using 2000–2016 EDHS data

BackgroundThe under-five mortality rate serves as a key indicator of the performance of a country’s healthcare system. Despite a minor decline, Ethiopia continues to face a persistently high under-five mortality rate across different zones. Thus, this study aimed to identify the risk factors of under-five mortality and the spatiotemporal variation in Ethiopian administrative zones.MethodThis study used the 2000–2016 Ethiopian Demographic and Health Survey (EDHS) data which were collected using a two-stage sampling method. A total of 43,029 (10,873 in 2000, 9,861 in 2005, 11,654 in 2011, and 10,641 in 2016) weighted sample under-five child mortality were used. The space-time dynamic model was employed to account for spatial and time effects in 65 administrative zones in Ethiopia.ResultsFrom the result of a general nesting spatial-temporal dynamic model, there was a significant space-time interaction effect [γ = -0.1444, 95% CI(-0.6680, -0.1355)] for under-five mortality. The increase in the percentages of mothers illiteracy [β = 0.4501, 95% CI (0.2442, 0.6559)], not vaccinated[β= 0.7681, 95% CI (0.5683, 0.9678)], unimproved water[β= 0.5801, CI (0.3793, 0.7808)] were increased death rates for under five children while increased percentage of contraceptive use [β= -0.6609, 95% CI (-0.8636, -0.4582)] and antenatal care unit visit > 4 times [β= -0.1585, 95% CI(-0.1812, -0.1357)] were contributed to the decreased under-five mortality rate at the zone in Ethiopia.ConclusionsEven though the mortality rate for children under five has decreased over time, still there is higher in different zones of Ethiopia. There exists spatial and temporal variation in under-five mortality among zones. Therefore, it is very important to consider spatial neighborhood’s and temporal context when aiming to avoid under-five mortality.

Analysis and implementation of volume reflection gratings in photorefractive lithium niobate for edge enhancement.

Diffraction from volume reflection gratings written in bulk photorefractive lithium niobate is modeled for the case of longitudinally varying index modulation depths. Numerical solutions to the Helmholtz equation are found in the spatial frequency domain, leading to transfer functions for the volume reflection grating. These transfer functions are then used to show the spatial frequency filtering effect of the volume reflection grating on input light fields containing 2D spatial information. It is shown, first through simulations and then by experiment, that the 0th order transmitted beam undergoes a 2D edge enhancement.

Spatial spillover effect of green finance on urban-rural income gap

ABSTRACT This paper constructs a spatial panel data model and establishes the Green Finance Index of China’s provinces with the entropy value method to empirically test the impact of green finance on China’s urban-rural income gap. The results of the study show that green finance not only reduces the local urban-rural income gap but also has an obvious inhibitory effect on the urban-rural income gap in the surrounding areas. In terms of regional analysis, green finance has limited inhibitory effects in developed regions and significant inhibitory effects in developing regions.