Neighboring Areas Research Articles

THE IMPACT OF THE AGRICULTURAL PRODUCTIVE SERVICE INDUSTRY ON THE INCOME GAP BETWEEN URBAN AND RURAL RESIDENTS: EVIDENCE FROM 276 CHINESE PREFECTURE-LEVEL CITIES

Based on the panel data of 276 prefecture-level cities in China from 2009 to 2018, this paper explores the impact of the agricultural productive service industry on the income gap between urban and rural residents by constructing the spatial econometric model and threshold regression model. The results show that the development of the agricultural productive service industry has a significant spatial spillover effect, which has a significant restraining effect on widening the income gap between urban and rural residents in the neighboring areas. Developing the agricultural productive service industry in the eastern and central regions significantly narrows the income gap between urban and rural residents. There is a significant urbanization threshold effect on the impact of the agricultural productive service industry on the income gap between urban and rural residents. When the urbanization level crosses the threshold of 3.7469, the role of the agricultural productive service industry in reducing the income gap between urban and rural residents increases significantly. Therefore, this paper proposes accelerating the development of the agricultural productive service industry, improving the urban–rural integration mechanism, strengthening the coordinated development between regions and playing the external effects of the agricultural productive service industry.

The Joint Clean Air Actions and air quality spillovers in China

ABSTRACT Facing severe air pollution in its North Plain, the central government of China initiated the Joint Clean Air Action (JCAA) in 2017 to facilitate pollution mitigation efforts across the region. While quite a few studies investigated the effectiveness of this regulation, much less attention is paid to the pollution spillover effects. We empirically examine the effects, and show that 1) air quality in the east of the target cities has been improved due to positive spillover of improved air quality under the JCAA; 2) the beneficiary spillover lasts for two seasons and disappeared in autumn and winter; 3) air quality in the north, south and west directions are almost not changed; 4) wind direction and topography, two determinants of atmospheric transport, have a considerable influence over the spillover effects. Our study provides a fresh perspective to understand the impacts of the JCAA policy and underlines the necessity of taking both pollution and air quality spillover effects into the cost-benefit analysis. Implications: Pollution regulations in one place may increase pollution in other places, as production and emissions are re-allocated under the incentives induced by regional-specific regulations. This phenomenon has long been recognized in the literature as pollution spillover. However, if the relevant production and emissions are not re-allocated, at least not re-allocated in large quantities, local air quality improvement induced by regulations may also benefit the neighboring areas. We call this effect air quality spillover. Both spillover effects should be rigorously evaluated, which is of scientific interest by itself and also contributes to a comprehensive cost-benefit analysis of environmental regulations.

Dynamic evolution and impact mechanism of human capital mismatch in strategic emerging industries: Evidence from the Yangtze River Delta region of China

China's “demographic dividend” has gradually disappeared since 2013, but the problem of human capital mismatch prevails in various industries and sectors, and improving human capital mismatch and optimizing the allocation of human capital has become an important measure for high-quality economic development. This study uses panel data at the provincial level in the Yangtze River Delta region from 2012 to 2021 and employs spatial econometric models to quantitatively analyze the index of human capital mismatch, the impact mechanism, and spatial interaction effects in strategic emerging industries. The results show that the spatial agglomeration and dependence of human capital mismatch decreased in the Yangtze River Delta region, and the index of human capital mismatch in strategic emerging industries is generally insufficient. The shortage of talent supply within industries is particularly severe in high-end equipment manufacturing and biotechnology industries. Second, fiscal subsidies have exacerbated human capital mismatches in both local and neighboring areas, with significant spatial spillover effects. Urbanization has exacerbated local human capital mismatches but has improved the degree of human capital mismatch in neighboring areas. The index of industrial structural adjustment is generally conducive to alleviating human capital mismatches. Distorted markets and financial levels have accelerated human capital mismatches by distorting the efficiency of human capital allocation. Third, regional heterogeneity significantly influences the spatial interaction effects of human capital mismatches. This study contributes to improving the situation of human capital mismatch in strategic emerging industries in the Yangtze River Delta and provides theoretical and policy recommendations for local governments.

Bidirectional Collaborative Mentoring Network for Marine Organism Detection and Beyond

Organism detection plays a vital role in marine resource exploitation and marine economy. How to accurately locate the target organism object within the camouflaged and dark light oceanic scene has recently drawn great attention in the research community. Existing learning-based works usually leverage local texture details within a neighboring area, with few methods explicitly exploring the usage of contextualized awareness for accurate object detection. From a novel perspective, we in this work present a Bidirectional Collaborative Mentoring Network (BCMNet) which fully explores both texture and context clues during the encoding and decoding stages, making the cross-paradigm interaction bidirectional and improving the scene understanding at all stages. Specifically, we first extract texture and context features through a dual-branch encoder and attentively fuse them through our adjacent feature fusion (AFF) block. Then, we propose a structure-aware module (SAM) and a detail-enhanced module (DEM) to form our two-stage decoding pipeline. On the one hand, our SAM leverages both local and global clues to preserve morphological integrity and generate an initial prediction of the target object. On the other hand, the DEM explicitly explores long-range dependencies to refine the initially predicted object mask further. The combination of SAM and DEM enables better extracting, preserving, and enhancing the object morphology, making it easier to segment the target object from the camouflaged background with sharp contour. Extensive experiments on three benchmark datasets show that our proposed BCMNet performs favorably over state-of-the-art models. The code will be made available at https://github.com/chasecjg/BCMNet.

Reducing the Highway Networks Energy Bills using Renewable Energy System

Jordan has significant renewable energy potential due to its remarkable geographical location and climate conditions. This potential elevates engaging several innovative renewable alternatives in energy development, which may efficiently minimize the excessive import of traditional energy sources. The objective of this research is to study the potential of utilizing clean and affordable solar energy along roadways such as Jordan’s Desert Highway-15 to be in line with the United Nations Sustainable Development Goals (UN-SDG’s) by installing selected solar panels that possess adequate friction and the ability to allow solar radiation to reach the solar cells, in addition to allowing the load to be bypassed around the cells. The shoulder of the highway, with a length of 315 km and a width of 3.0 meters, has been exploited in order to supply the neighboring areas with energy for those roads, particularly those paved roads, which are poorly lit at night. Furthermore, this study provides direction and guidance concerning the structural performance of non-traditional pavement materials, which are a form of subgrade or pavement reinforcement. The performance of a prototype board on a variety of structural bases has also been evaluated. Overall, this paper found that it is possible to design a solar road panel to withstand traffic loading and that the concrete structural base allows for a significant improvement of the analyzed prototype design, especially in countries with limited energy sources and dependent on imports such as Jordan. Doi: 10.28991/CEJ-2023-09-11-019 Full Text: PDF

The impact of environmental tournament on CO2 emissions from the perspective of synergizing the reduction of pollution and carbon emissions

Synergizing the reduction of pollution and carbon emissions is the essential way for the construction of ecological civilization in the new era. Based on the panel data of 278 Chinese cities from 2006 to 2020, we study the effect of environmental tournament on carbon dioxide (CO2) emissions. The results show that environmental tournaments have both effectiveness and limitations. The effectiveness is reflected in the fact that the environmental tournament is beneficial for the reduction of the pollution and CO2 emissions, and possesses a long-term effect. Green technology innovation, official promotion and foreign investment are identified as the main channels of influence. Moreover, the carbon reduction of the environmental tournament involves a positive spatial spillover effect, which means that the CO2 reduction can be radiated to the neighboring areas. However, environmental tournaments also have limitations. The results of the environmental tournament in the last year could bring pressure on cities to reduce pollution in the current year. The present study reveals a positive U-shaped relationship between the pollution reduction pressure and CO2 emissions. The pressure is beneficial to CO2 emissions reduction as the pollution reduction pressure is less than the extreme point; otherwise, CO2 emissions increase. The government's environmental attention strengthens the internal motivation of local participation in the environmental championship through policy orientation, and alleviates the negative impact caused by the limited nature of the environmental championship. The results of this study provide new ideas for improving China's environmental governance policy system and improving the governance efficiency of local governments.

Analysis of the impact of local government debt policy on the financial ecological environment-based on debt level and debt structure perspectives

This paper employs panel data from 227 prefecture-level cities in China spanning the period from 2000 to 2020 to investigate the effects and influences of local government debt policies on the financial ecological environment. Considering regional economic foundation, financial development, government governance, and the construction of the social credit system, our analysis reveals the following outcomes regarding debt level and debt structure: Firstly, we find that higher debt levels and an increased proportion of hidden debt at the local government level have impacts on various dimensions of the financial ecological environment. Specifically, debt expansion facilitates regional economic foundations and financial development but hampers government governance and the construction of the social credit system, leading to a deterioration in the development of the financial ecological environment. Furthermore, employing a threshold regression model, we have not identified a significant nonlinear relationship in this context. Secondly, local government debt exhibits a reverse spatial spillover effect on the financial ecological environment of surrounding regions, contrasting with the effects observed within the local area. This effect manifests as the enhancement of the financial ecological environment in neighboring areas.

Spatial Spillover Effect of Water Environment Pollution Control in Basins—Based on Environmental Regulations

The basin economy is essential in China’s high-quality development, which brings prodigious economic and social benefits. However, high industrialization and urbanization led to a significant escalation in water pollution within basins. The achievement of synergistic control of water environment pollution at the basin scale has emerged as a primary goal for governmental departments in developing environmental policies. This study constructs a “four-in-one” basin’s water environment regulation system comprising four categories: total, quality, project, and governance. Further, the spatial spillover effects of water environment pollution control in 27 Chinese provincial-level administrative regions spanning key river basins were analyzed. This study aims to provide evidence from China on the transfer of water pollution in basins worldwide. The results indicate the following conclusions: (1) A consistent upward trend in the environmental regulations and water environment pollution indexes across all provinces in the basin. Compared to 2006, in 2018, the mean value of the basin environmental regulation index was 0.21, which is an increase of 23.5%, and the mean value of the water environmental pollution index was 0.83, which is an increase of 29.7%. (2) Whether in the basin’s upper, middle, or lower reaches, the relationship between environmental regulations and water pollution follows a “U”-shaped pattern, with thresholds of 0.318, 0.331, and 0.390, respectively. (3) Under the neighbor weight matrix and water flow distance weight matrix, the impact coefficient of the water environment pollution index on the surrounding areas is significantly positive, implying that the implementation of local environmental policies will radiate to the neighboring areas in the short term and bring positive governance effects. (4) Regarding the time-lag effect, it is observed that the lag term associated with the water environment pollution index exhibits a statistically significant positive relationship. This finding suggests that the pollution of the water environment within the basin follows a cumulative and continuous pattern. (5) It is noted that long-term environmental regulation measures do not contribute favorably to the amelioration of water pollution in the neighboring regions. This implies the presence of a characteristic neighboring avoidance effect.

Influence of Root Reinforcement on Shallow Landslide Distribution: A Case Study in Garfagnana (Northern Tuscany, Italy)

In this work, we evaluated the influence of root structure on shallow landslide distribution. Root density measurements were acquired in the field and the corresponding root cohesion was estimated. Data were acquired from 150 hillslope deposit trenches dug in areas either devoid or affected by shallow landslides within the Garfagnana Valley (northern Tuscany, Italy). Results highlighted a correlation between the root reinforcement and the location of measurement sites. Namely, lower root density was detected within shallow landslides, with respect to neighboring areas. Root area ratio (RAR) data allowed us to estimate root cohesion by the application of the revised version of the Wu and Waldron Model. Then, we propose a new method for the assimilation of the lateral root reinforcement into the infinite slope model and the limit equilibrium approach by introducing the equivalent root cohesion parameter. The results fall within the range of root cohesion values adopted in most of the physically based shallow landslide susceptibility models known in the literature (mean values ranging between ca. 2 and 3 kPa). Moreover, the results are in line with the scientific literature that has demonstrated the link between root mechanical properties, spatial variability of root reinforcement, and shallow landslide locations.

Identification Of Leading Sectors As The Growth Pole Of Ambon City

A growth pole is an area experiencing rapid expansion and is seen as a hub for development, with the potential to influence the development of neighboring areas. This research aims to identify key sectors that can serve as the economic driving force in Ambon city. The study utilized historical data, specifically time series data from the gross regional domestic product (GRDP) in 2010 constant prices. The research methodology employed several techniques, including Location Quotient (LQ) analysis, Dynamic Location Quotient (DLQ) analysis, and Klassen Typology analysis, to assess the prominent sectors in Ambon city. Additionally, the Shift-Share Analysis (SSA) approach was used to estimate the impact of these leading sectors on the city's economic growth. The LQ analysis revealed the existence of ten leading sectors in Ambon city. Furthermore, the Klassen Typology analysis categorized these sectors into five developed, five stagnant, five developing, and two underdeveloped sectors. The SSA analysis indicated that four sectors had the highest share value in the province's share component, four sectors showed positive values in the proportional shift component, and eleven sectors exhibited positive values in the differential shift component. The cumulative effect of these three components illustrates the significant impact of these sectors on Ambon city's economic growth.

Analysis and forecast of passenger flows in public transport - the case of Poland

Public transportation provides its services to both urban centers and neighboring areas in the immediate vicinity of the city. The problem of urban transportation is evident, the number of people willing to use public transportation has decreased. Therefore, there is a need to delve into the issue and conduct an analysis of the demand for urban transportation in Poland in 2000-2030, this will allow us to assess in what direction urban transportation is heading, whether there is an increase in the number of people using it, or whether there is a downward trend (Zielińska 2018). Based on CSO statistics from 2009-2020 for the analysis of demand for public transportation in Poland, a forecast of people using public transportation was conducted using Statistica software for 2021-2030. Due to the situation with the COVID-19 pandemic, the study was conducted in 2 ways – with and without 2020. Public transportation will make less and less profit and even losses for the next few years through rising gasoline and energy prices. Virtually in each of the provinces, and likewise throughout Poland, a decline in the number of people willing to use public transportation is evident. conclusions. On the basis of the surveys carried out, there is a general trend that shows the current state of public transport. In most of the cases studied, a similar conclusion emerges, namely that public transport will experience a marked decline in the coming years. The number of people who want to use public transport will decrease, mainly due to the COVID-19 pandemic and people’s fears for their own safety.

Biomechanical explanation of W-plasty effectiveness using a finite element method approach

The finite element method has often been used to assist analyzing local flaps in terms of deformation and stress measurements as it takes into account complex skin properties. We, herein, present an isotropic two-dimensional finite element skin model applied to the W-plasty method to demonstrate that the good outcomes of W-plasty should be attributed to the geometry itself, as it generates lower stresses. The skin was modeled as a two-dimensional (2D) planar geometry. The model was created and solved as a plane stress problem. The model was based on simulation of the loading and stitching of W-plasties of various angles. Each central triangular flap was segmented in nine triangular elements. The stitching was modeled with one suture at the top of each triangular flap with the center of the opposite corner. X- and Y-axis stresses and shearing stresses Txy in the elements involved in the broken stitching line, show lower stresses than the elements behind the stitching line. Interestingly, in the triangular flaps, the stresses were clearly lower than those of their neighboring areas. The maximum compressive stresses in the 2D model we used, correspond to the dog ears. We conclude that the effectiveness of W-plasty should be attributed not only to the scar orientation in relation to the relaxed tension skin lines but also to the special design of the triangular flaps used. This finding assists the general understanding of the method and should be taken into account by the clinician during flap designing.

How do R&D capital market distortions affect innovation efficiency in China? Some evidence about spatial interaction and spillover effects

Improving innovation efficiency (IE) and refining capital market distortions are important considerations for promoting national innovation strategies. This study uses the dynamic spatial Durbin model and mechanism tests to explore the direct impacts, spatial effects, and influencing mechanisms of R&D capital market distortions on IE based on Chinese provincial panel data from 2009 to 2019. The main results can be summarized as follows. First, China’s IE is characterized by temporal inertia and spatial agglomeration. In both the spatial and temporal dimensions, IE in neighboring areas in the previous period can inhibit local IE in the current period. Second, R&D capital market distortions have a weakening effect on IE in the short- and long-term. Third, R&D capital market distortions have significant spatial interaction and persistent positive spatial spillover effects on IE. Finally, R&D capital mismatch and technology lock-in effects are essential mechanisms related to R&D capital market distortions that can inhibit IE. Based on these results, policy recommendations have been proposed to improve IE.

THE IMPACT OF DIGITAL ECONOMY DEVELOPMENT ON CARBON EMISSION INTENSITY REDUCTION: EVIDENCE FROM CHINA

Digital economy development is important for promoting industrial upgrades and high-quality economic growth. As excessive carbon emissions are a threat to sustainable economic growth, whether digital economy development contributes to reducing carbon emission intensity has gained attention. This study employs the fixed effects model and spatial Dubin model to examine the effect of digital economy development in 275 cities in China on the reduction of carbon emissions intensity. The results show effectiveness in reducing carbon intensity with a spatial spillover effect to neighboring areas. Urban economic primacy plays a positive modulating role in carbon reduction. Policy implications are discussed.

Empowering rural human Settlement:Digital Economy's path to progress

Digital economy development (DED) empowers rural habitat (RH) improvement and promotes the construction of harmonious villages. Based on a panel data of 30 provinces in China from 2013 to 2019, this paper empirically tests the impact of DED on RH and its endogenous mechanism in multiple dimensions using panel fixed effects model and spatial Durbin model. The results show that DED significantly improves RH, which remains robust after a series of robustness tests and dealing with endogeneity issues. The mechanism analysis shows that DED helps to bring into play the rural resource allocation effect, the innovation and entrepreneurship effect, and the carbon emission reduction effect, and improves the RH through these three effects. Further study finds that the digital application divide and regional divide are the main barriers to digital technology enabling RH improvement, there is a spatial spillover effect of DED, which helps to promote the improvement of RH in neighboring areas. The results of the study can provide theoretical support and decision-making reference for the construction of digital villages and the balanced regional development of RH in China.

The Impact of Agricultural Insurance on Urban–Rural Income Gap: Empirical Evidence from China

Based on the panel data of 31 provinces in China from 2005 to 2020, this paper analyzes the mechanism and spatial spillover effect of agricultural insurance on the urban–rural income gap using a fixed effect model, an intermediary effect model, and a two-stage least square method. The results show that agricultural insurance has a significant inhibitory effect on the income gap between urban and rural areas. This inhibitory effect is realized through the path of “improving the development level of agricultural insurance-improving agricultural total factor productivity-reducing the income gap between urban and rural areas”, in which the intermediary effect of agricultural total factor productivity accounts for 19.74% of the total effect. At the same time, the income gap between urban and rural areas in China exhibits typical spatial agglomeration characteristics. The western region has always been the region with the largest income gap between urban and rural areas, while the eastern region is the region with the smallest income gap between urban and rural areas. The development of agricultural insurance has had a spatial spillover effect on the income gap between urban and rural areas, and the development of agricultural insurance in neighboring areas expands the income gap between urban and rural areas in this region. In order to prevent the siphon effect, agricultural insurance investment should be increased in the neighboring regions. The results of this paper support the view of the resource flow model. Finally, we put forward some suggestions for the development of agricultural insurance, improvement in agricultural total factor productivity, and the narrowing of the income gap between urban and rural areas.

Groundwater potentiality in hard-rock terrain of southern Saudi Arabia using electrical resistivity tomography approach

To detect groundwater-bearing zones in southern Saudi Arabia, 10 profiles of 2D electrical have been constructed resistivity tomography at five selected sites. The collected data were corrected and processed using the RES2DINV software. The results demonstrated that site-1 contains two groundwater-bearing zones; the first zone is situated 13 m beneath the ground surface, while the depth of the second zone varies from 4 m to 15 m. A promising 15-m-deep groundwater-bearing zone was identified at site 2. The groundwater-bearing zones exhibit depths of 40, 10, and 10 m at sites 3, 4, and 5, respectively. The detected groundwater-bearing zones are notably shallow, with a depth of 20 m below the ground surface and with lateral extension up to 200 m. These aquifers prevail in the alluvial deposits, where the weathered/fractured or fresh basement rocks underlying these aquifers. Moreover, rainfall recharges these unconfined aquifers, as evidenced by the increasing water levels along the main Wadi channels flow during rainy seasons. Sites 2, 3, and 5 are considered as groundwater-bearing sources with high potential. Because this unconfined aquifer can be swiftly replenished by the 300–360 mm of annual rainfall in the southern Saudi lowlands, it is a promising area for groundwater supply for future urbanization plans and agricultural projects in neighboring areas.

Tempnet: A graph convolutional network for temperature field prediction of fire-damaged concrete

Determining the damage level of the fire-damaged concrete structure is critical for the structural assessment and repair of buildings after fire. Existing methods assess the damage levels of concrete by measuring the remaining mechanical performance in a traditional manner, where they either have limited accuracy or efficiency due to the need of heavy machines and experienced laborers. In contrast with these methods, we propose a deep learning based approach called Tempnet to promote the efficiency and effectiveness of damage level assessment for concrete after fire. Tempnet incorporates a graph convolutional layer and a conventional convolutional layer to encode the temperature interdependency between neighboring areas in the images of fire-affected concrete to capture the exposed temperature fields of the concrete. Three closely related application scenarios together with their corresponding datasets have been proposed to evaluate the performance of Tempnet. Extensive comparative experiments and ablation studies have validated the model design, the high efficiency, and the robust performance of Tempnet, with a performance metric F1 value higher than 0.97 in all applications. Case studies were conducted further to provide insightful illustration of Tempnet’s impressive performance. It is envisioned that the Tempnet can contribute to the efficient maintenance of concrete structures following fire accidents for construction applications.

Assessment of spatio-temporal evolution trends and driving factors of green development in Harbin-Changchun urban agglomeration

As China has entered a new stage of high-quality development, clarifying the mechanism and spatial characteristics of green development for urban agglomerations are critical to sustainable development. Based on the data of 11 major cities in the Harbin-Changchun urban agglomeration (HCUA) from 2010 to 2020, this study constructs an evaluation system of green development index (GDI) is composed of four dimensions, i.e. urban green construction (UGC), industrial green development (IGD), resource and environmental carrying capacity (RECC), and technological innovation support (TIS). Furthermore, using the entropy weight method to obtain the weights of evaluation indicators. And then, the comprehensive index calculation is used to evaluate the GDI. The driving factors of each level of GDI are determined by the Pearson correlation coefficient. The results infer some novel findings as follows: (1) the overall tendency of the GDI of the HCUA has gradually increased from 0.358 in 2010 to 0.379 in 2020 which is at the average level. The dimension of TIS shows the highest rate of contribution while IGD and RECC show a fluctuating trend over the time window. (2) The GDI in the HCUA exhibits a patchy clustering differentiation feature that spreads from the central area to the surrounding areas with a “high in the south and low in the north” pattern. Specifically, Changchun, Harbin, and Daqing form an “inverted triangle” structure in geographical location to drive the green development of neighboring areas. (3) The core cities of the HCUA, Changchun, and Harbin, show a much higher level than the other cities. Jilin and Daqing are at the average level, and besides, the rest of the cities of GDI are at the poor level with significant fluctuations in ranking. (4) There are different driving factors between each level of GDI. For cities with good and average levels should focus on protecting resources and the environment. Meanwhile, cities with poor level of GDI need to improve IGD to optimize the urban green structure. Thus, it is suggested to strengthen the flow of factors and implement differentiated strategies to promote coordinated development and spatial clustering.

SARS-CoV-2 Infection Dynamics in the Pittsburgh Zoo Wild Felids with Two Viral Variants (Delta and Alpha) during the 2021-2022 Pandemic in the United States.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been reported in multiple animal species besides humans. The goal of this study was to report clinical signs, infection progression, virus detection and antibody response in a group of wild felids housed in adjacent but neighboring areas at the Pittsburgh Zoo. Initially, five African lions (Panthera leo krugeri) housed together exhibited respiratory clinical signs with viral shedding in their feces in March of 2021 coinciding with infection of an animal keeper. During the second infection wave in December 2021, four Amur tigers (Panthera tigris altaica) and a Canadian lynx (Lynx canadensis) showed clinical signs and tested positive for viral RNA in feces. In infected animals, viral shedding in feces was variable lasting up to 5 weeks and clinical signs were observed for up to 4 weeks. Despite mounting an antibody response to initial exposure, lions exhibited respiratory clinical signs during the second infection wave, but none shed the virus in their feces. The lions were positive for alpha variant (B.1.1.7 lineage) during the first wave and the tiger and lynx were positive for delta variant (AY.25.1. lineage) during the second wave. The viruses recovered from felids were closely related to variants circulating in human populations at the time of the infection. Cheetahs (Acinonyx jubatus) in the park did not show either the clinical signs or the antibody response.