East Central Region Research Articles

Delineating the drought vulnerability zones in Bangladesh

The research aims to explore the vulnerability of Bangladesh to drought by considering a comprehensive set of twenty-four factors, classified into four major categories: meteorological, hydrological, agricultural, and socioeconomic vulnerability. To achieve this, the study utilized a knowledge-based multi-criteria method known as the Analytic Hierarchy Process (AHP) to delineate drought vulnerability zones across the country. Weight estimation was accomplished by creating pairwise comparison matrices for factors and different types of droughts, drawing on relevant literature, field experience, and expert opinions. Additionally, online-based interviews and group discussions were conducted with 30 national and foreign professionals, researchers, and academics specializing in drought-related issues in Bangladesh. Results from overall drought vulnerability map shows that the eastern hills region displays a notably high vulnerability rate of 56.85% and an extreme low vulnerability rate of 0.03%. The north central region shows substantial vulnerability at high levels (35.85%), while the north east exhibits a significant proportion (41.68%) classified as low vulnerability. The north west region stands out with a vulnerability rate of 40.39%, emphasizing its importance for drought management strategies. The River and Estuary region displays a modest vulnerability percentage (38.44%), suggesting a balanced susceptibility distribution. The south central and south east regions show significant vulnerabilities (18.99% and 39.60%, respectively), while the south west region exhibits notable vulnerability of 41.06%. The resulting model achieved an acceptable level of performance, as indicated by an area under the curve value of 0.819. Policymakers and administrators equipped with a comprehensive vulnerability map can utilize it to develop and implement effective drought mitigation strategies, thereby minimizing the losses associated with drought.

Orthohantavirus diversity in Central-East Argentina: Insights from complete genomic sequencing on phylogenetics, Geographic patterns and transmission scenarios.

Hantavirus Pulmonary Syndrome (HPS), characterized by its high fatality rate, poses a significant public health concern in Argentina due to the increasing evidence of person-to-person transmission of Andes virus. Several orthohantaviruses were described in the country, but their phylogenetic relationships were inferred from partial genomic sequences. The objectives of this work were to assess the viral diversity of the most prevalent orthohantaviruses associated with HPS cases in the Central-East (CE) region of Argentina, elucidate the geographic patterns of distribution of each variant and reconstruct comprehensive phylogenetic relationships utilizing complete genomic sequencing. To accomplish this, a detailed analysis was conducted of the geographic distribution of reported cases within the most impacted province of the region. A representative sample of cases was then selected to generate a geographic map illustrating the distribution of viral variants. Complete viral genomes were obtained from HPS cases reported in the region, including some from epidemiologically linked cases. The phylogenetic analysis based on complete genomes defined two separate clades in Argentina: Andes virus in the Southwestern region and Andes-like viruses in other parts of the country. In the CE region, Buenos Aires virus and Lechiguanas virus clearly segregate in two subclades. Complete genomes were useful to distinguish person-to-person transmission from environmental co-exposure to rodent population. This study enhances the understanding of the genetic diversity, geographical spread, and transmission dynamics of orthohantaviruses in Central Argentina and prompt to consider the inclusion of Buenos Aires virus and Lechiguanas virus in the species Orthohantavirus andesense, as named viruses.

Analysis of Gyimes Csango population samples on a high-resolution genome-wide basis

BackgroundThe Csangos are an East-Central European ethnographic group living mainly in east of Transylvania in Romania. Traditionally, ethnography distinguishes three Csango subpopulations, the Moldavian, Gyimes and Burzenland Csangos. In our previous study we found that the Moldavian Csangos have East Asian/Siberian Turkic ancestry components that might be unique in the East-Central European region and might help to better understand the history of Hungarian speaking ethnic groups of the area. Since then, we obtained further Csango samples from Moldavia and from a distinct region of Gyimes, which two Csango subgroups are traditionally different since they live in a degree of isolation not only from other people but also from each other. Here we present the first genomic analysis of Gyimes Csangos, which intended to compare the genetic makeup of these two Csango subgroups using both allele-frequency and haplotype-based methods. The main goal of the study was to investigate the genetic isolation of the Csangos on a genome-wide SNP basis and to assess the isolation of Gyimes Csangos, which in contrast to the Moldavians was not yet studied.ResultsOur results show that these two Csango groups show slight differences from each other. We confirmed the genetic isolation of Moldavian Csangos and revealed that Gyimes Csangos have a similar, but detectably weaker isolation. In the case of Gyimes Csangos we detected also a stronger East European or presumably Asian derived ancestry.ConclusionThe Gyimes Csangos show a degree of genetic isolation comparable to that of the Moldavians. The Asian ancestry that differentiates the Moldavian Csango people from the other East-Central European populations may be present in the Gyimes Csangos in an even higher degree, since Gyimes Csango individuals show a more significant share from that ancestry component.

Quaternary environment and climate change reconstruction from geochemical and geoarchaeological evidences of paleosols in east-central Barind, NW Bangladesh

This research focuses on analyzing paleosols, major and trace element geochemistry, organic carbon levels, and geo-archaeological aspects of Quaternary deposits investigated in two sedimentary successions located in the east-central Barind region of NW Bangladesh. Several factors that influence the paleosol development can be used to decipher the paleoenvironment and paleoclimatic conditions of the study area. Sedimentary succession of the studied sections have been grouped into two broad categories i.e., Gray unit/Newer Alluvium (NA) of Late Holocene and Red unit/Older Alluvium (OA) of Early Pleistocene age. Some geoarchaeological evidences have been found at the bottom of the gray unit and the top of the red unit in Durgadaha (DD) section indicating the existence of paleo-settlement at about ∼1300 years BP. The age is determined by the relative dating of several artifacts found at the paleo-settlement surface. Interpretation of several field characteristics and geochemical parameters i.e., clayeyness, salinization, base loss, calcification, leaching (Ba/Sr), aeolian input (Zr/Al), CIA, CIW, CIA-K, etc. revealed that the paleosols in gray unit are weakly developed; whereas, paleosols in red unit are relatively moderate, strong to very strongly developed. In the red unit, the MAP and MAT range from 1000 ± 181 mm to 1478 ± 181 mm and 9° ± 4.4°–14° ± 4.4 °C respectively. On the other hand, MAT ranges from 23.1° ± 0.6 °C to 28.3° ± 0.6 °C in gray unit paleosols. Depending on the depositional pattern and estimated MAT, five short-term climatic cycles (i.e., alternating phases of dry and wet) have been recognized in gray/newer alluvium units during the last 1300 years. The demise of paleo settlement (1300 years BP) due to the abrupt climatic change towards a dry and cooler phase where the MAT was estimated as 23.1° ± 0.6° which is at least 3 °C lower than the present. This study also revealed that the estimated MAP and MAT are more analogous to paleoclimatic records of the Asian regions.

Long-range transport impact of a severe dust storm over the Yangtze River Basin region and its modeling sensitivity to dust emission scheme

Dust storms frequently occur in the spring over East Asia, affecting southern Mongolia and northeast China. An exceptionally powerful dust storm occurred in East Asia from March 14th to March 18th, 2021. To investigate the ability of climate models to simulate severe dust storms, we employed the Weather Research Forecast model coupled with chemistry (WRF-Chem) with Goddard Chemistry Aerosol Radiation and Transport (GOCART), SHAO and KOK dust emission schemes to simulate the evolution of this event and to characterize dust aerosols long-range transport. Results showed that this storm was caused by a Mongolian cyclone depicted at 850 hPa with a cold front, which swept dust aerosols southeastward across southern Mongolia to northeast China. Model evaluation with satellite-retrieved Aerosol Optical Depth (AOD) and observational PM10 concentrations revealed that the SHAO dust emission scheme performed better in simulating spatial and temporal distribution of AOD over the Gobi Desert (GD) but overestimated them over Taklimakan Desert (TD). In contrast, the GOCART dust emission scheme underestimated AOD over most areas except the Taklimakan Desert; the KOK dust emission scheme overestimated them over both TD and GD. Overall, the SHAO dust emission scheme had good performance in simulating the surface PM10 concentrations over the Yangtze River Basin (YRB) and depicted an increase in PM10 concentrations, which denoted the transport of dust aerosols over YRB. As a better description of the physical process of dust emission flux over the eastern region of the Gobi Desert, the SHAO dust emission scheme depicted well the spatial and temporal evolution of dust plume episodes, especially over northeast China and YRB. The significant differences in dust emission fluxes between the three dust emission schemes were attributed to the sensitivity of threshold friction velocity and erodibility factor. Thereunto, the SHAO dust emission scheme incorporated well soil particle size distribution and threshold velocity to produce the dust emission flux, which allowed higher dust emission flux over the eastern GD and under strong southwesterly transported dust aerosols to East Central China's region of North China Plain (NCP) and YRB. This study will help further the simulation of extreme dust events more accurately and the exploration of climate change's effect on dust events over East Asia.

Three-dimensional model and environmental fragility in the Guarani Aquifer system, SE-Brazil

The Guarani Aquifer System (GAS) is a vast transboundary continental sedimentary basin in southern South America, encompassing sedimentary rocks and basalt flows across Uruguay, Paraguay, Argentina, and Brazil. It serves as a crucial water resource for urban supply and irrigation. This study aims to propose geophysical, geometric, and fragility models of the GAS in a critical exploitation area, utilizing geological data, geophysical logs, geomorphometry, and information from tubular wells. The models define distinct geophysical ranges for each formation and identify contacts between sedimentary and basaltic rocks. Integration of horizontal and vertical spatial distributions of geophysical and geological data forms a 3D model, revealing basaltic flows and intrusions distribution in fragile areas between formations, and potentially connecting aquifer layers. Natural fragility zones, characterized by high fracture densities, are observed in the central-east region, while outcrop and recharge areas of the main aquifer hydrofacies are found in the north. The 3D model highlights similarities between the topography of the Botucatu Formation (KJb – eolian sandstones) and the potentiometry of GAS at local scales, and overexploitation zones in Ribeirão Preto's city center. The assessment prioritizes areas at risk and conservation strategies for sedimentary aquifers, emphasizing interactions between surface and groundwater and addressing issues of overexploitation, identifying high-impact risks on GAS hydrodynamics and water quality.

Nexus among government digital development, resource dependence, and carbon emissions in China

Government digital development uses data technology to empower data for economic and social benefits, making social governance more scientific and efficient. Using unbalanced panel data of Chinese cities from 2006 to 2019, this paper explores the relationship between government digital development, fossil energy dependence, and urban carbon emissions. The results show that government digital development can effectively curb urban carbon emissions. The " carbon curse " phenomenon does exist at the city level in China, and government digital development is an effective way to break the "carbon curse." Heterogeneity analyses show that the digitalization of government significantly reduces the carbon emissions of cities in the East-Central region and the Yangtze River Economic Belt. Promoting government digital development in large cities can effectively break the "carbon curse." In addition, government digital development can also curb urban carbon emissions through structural, innovation, and resource allocation effects. Therefore, due attention should be paid to the digital development of government, which in turn will leverage digital advantages and eliminate the adverse effects of fossil energy dependence. This is of profound theoretical and practical significance for curbing urban carbon emissions and promoting green economic development.

Spatial Vulnerability Assessment for Mountain Cities Based on the GA-BP Neural Network: A Case Study in Linzhou, Henan, China

Mountain cities with complex topographies have always been highly vulnerable areas to global environmental change, prone to geological hazards, climate change, and human activities. Exploring and analyzing the vulnerability of coupling systems in mountain cities is highly important for improving regional resilience and promoting sustainable regional development. Therefore, a comprehensive framework for assessing the spatial vulnerability of mountain cities is proposed. A vulnerability assessment index system is constructed using three functional systems, ecological protection, agricultural production, and urban construction. Subsequently, the BP neural network and the genetic algorithm (GA) are combined to establish a vulnerability assessment model, and geographically weighted regression (GWR) is introduced to analyze the spatial influence of one-dimensional systems on the coupling system. Linzhou, a typical mountain city at the boundary between China’s second- and third-step terrains, was selected as a case study to demonstrate the feasibility of the framework. The results showed that the vulnerability of the ecological protection system was highly aggregated in the east–central region, that of the agricultural production system was high in the west, and that of the urban construction system was low in the central region and high in the northwestern region. The coupling system vulnerability was characterized by multispatial distribution. The complex topography and geomorphology and the resulting natural hazards are the underlying causes of the vulnerability results. The impact of ecological and urban systems on the coupling system vulnerability is more prominent. The proposed framework can serve as a reference for vulnerability assessments of other similar mountain cities with stepped topographies to support the formulation of sustainable development strategies.

Coupling and interaction mechanism between green urbanization and tourism competitiveness based an empirical study in the Yellow River Basin of China

Exploring the spatial coupling relationship and interaction mechanism between green urbanization (GU) and tourism competitiveness (TC) is of great significance for promoting urban sustainable development. However, the lack of research on the interaction mechanism between GU and TC limits the formulation of effective environmental management policy and urban planning. Taking 734 counties in the Yellow River Basin (YRB) as the study area, this paper analyzes the spatial coupling relationship between GU and TC on the basis of comprehensive evaluation of GU and TC. Then, the interactive mechanism between GU and TC is systematically discussed, and the synergistic development strategy of the two is proposed. The results show that the GU level presents a multicore circle structure, with provincial capitals, prefecture-level urban districts and economically developed counties in east-central regions as high-value centers. The TC at county scale presents a multi-center spatial structure. Additionally, there is a significant positive spatial coupling between GU and TC in the YRB. The analysis further reveals that green urbanization level, social progress, population development, infrastructure construction, economic development quality, and eco-environmental protection has a observably influence on TC. Tourism competitiveness, service competitiveness, location competitiveness, resource competitiveness, market competitiveness, environmental influence, and talent competitiveness has a observably influence on GU. TC can promote GU, and the improvement of green urbanization level can support the development of tourism competitiveness. According to the spatial zoning method, 734 counties are divided into 6 categories, and the coordinated development strategy of GU and TC for each type of district is proposed.

Changes in climate attributes and harvest area structures jointly determined spatial-temporal variations in water footprint of maize in the Beijing-Tianjin-Hebei region

Irrigation contributes significantly to boosting crop yield and ensuring food security. However, in the Beijing-Tianjin-Hebei (BTH) region, unsustainable irrigation practices have led to serious outcomes on freshwater resources. Balancing irrigation with crop productivity in this region, currently facing complex challenge, requires a comprehensive understanding of its spatial pattern and thus to seeking for potential optimization of current crop structures. In this study, we employed the concept of water footprint (WFP) to assess the spatial-temporal patterns of water footprint for maize in BTH region at the county level for the years 2005, 2010, 2015, and 2020, untangled the relative impacts on WFP from climate attributes and harvest area structures. Our results showed significant regional heterogeneities in both blue water requirement and green water requirement, ranging from 64.6 mm to 290.7 mm. Yearly anomalies of climate attributes and maize harvest jointly influenced water footprints, with the highest value of 1.06 × 1011 m3 occurring in the year 2015. The green water footprints, linked to precipitation, dominated the total water footprint compared to the blue water footprint associated with irrigation. Additionally, we observed an increasing influence of maize harvest area on the temporal changes in water footprints, with these changes becoming more concentrated in the east-central region over time. Our findings underscore the respective contributions of annual climate attribute changes and harvest area variations at the county level, highlighting regions where urgent interventions are required to enhance the sustainability of water usage for agriculture.

Individual and community-level factors associated with repeat induced abortion among women in Ghana: a multivariable complex sample logistic regression analysis of 2017 Ghana maternal health survey

BackgroundRepeat induced abortion is a serious public health issue that has been linked to adverse maternal health outcomes. However, knowledge about repeat induced abortion and its associated factors among reproductive age women in Ghana is very scarce. The objective of this study is to examine individual and community factors associated with repeat induced abortion in Ghana which would be helpful to design appropriate programmes and policies targeted at improving the sexual and reproductive health of women.MethodsWe used secondary cross-sectional data from the 2017 Ghana Maternal Health Survey. The study included a weighted sample of 4917 women aged 15–49 years with a history of induced abortion. A multivariable complex sample logistic regression analysis was used to investigate individual and community factors associated with repeat induced abortion among women in Ghana. Adjusted odds ratios (AOR) with 95% confidence intervals (CI) was used to measure the association of variables.ResultsOf the 4917 reproductive women with a history of abortion, 34.7% have repeat induced abortion. We find that, compared to women who experience single induced abortion, women who experience repeat abortion are age 25–34 years (AOR:2.16;95%CI = 1.66–2.79) or 35–49 years (AOR:2.95;95%CI:2.18–3.99), have Middle/JHS education (AOR:1.69;95%CI = 1.25–12.27), use contraceptive at the time of conception (AOR:1.48: 95%CI = 1.03–2.14), had sexual debut before 18 years (AOR:1.57; 95%CI: 1.33–1.85) and reside in urban areas (AOR:1.29;95%CI = 1.07–1.57). On the other hand, women who reside in Central (AOR:0.68;95%CI: 0.49–0.93), Northern (AOR:0.46;95%CI:0.24–0.88), Upper West (AOR:0.24; 95%CI: 0.12–0.50) and Upper East (AOR:0.49; 95%CI = 0.24–0.99) regions were less likely to have repeat induced abortion.ConclusionThe study showed that both individual and community level determinants were significantly associated with repeat induced abortion. Based on the findings, it is recommended to promote sexual and reproductive health education and more emphasis should be given to adult, those with early sexual debut, those with Middle/JHS education and those who live in urban centers.

Research on the impact of digital economic development level on ecological environment

PurposeExploring the intrinsic connection between the ecological environment and the digital economy and empirically testing how the level of digital economic development affects the ecological environment. Using the entropy weighting method to analyze the weights of the indicators in the digital economic development level and ecological environment system to explore the factors that have the greatest impact on the ecological environment in the indicator system of the digital economic development level so as to deepen the theoretical understanding of the relationship between the level of development of the digital economy and the ecological environment. Explore the regional heterogeneity of the level of development of the digital economy to promote the healthy development of China’s ecological environment proving the difference in the level of development of the digital economy in the east west and central regions of China and the difference in the effect on the ecological environment.Design/methodology/approachBased on the panel data of 30 provinces in China from 2013 to 2021 this paper fits the index system of digital economy development level with three factors. A digital infrastructure digital industry and digital application combines environmental pollution and energy consumption to construct ecological environment indicators and explored the impact of digital economy development level on the ecological environment by using the entropy weight method and the random effect model.FindingsThe findings indicate that the degree of digital economic development has a positive and significant impact on promoting the healthy development of the ecological environment, in which the digital industry has the greatest impact on the ecological environment. Meanwhile, the improvement of industrial structure also has a positive effect on the improvement of the ecological environment, whereas the level of human capital inhibits the healthy development of the ecological environment, and the governmental support fails to effectively and significantly promote the improvement of the ecological environment. Furthermore, the empirical research indicates that the level of digital economy development has obvious regional heterogeneity on the healthy development of the ecological environment: the eastern and central regions have a significant effect, while the western region has a less significant effect.Originality/valueAlthough domestic and foreign scholars and experts have conducted sufficient studies on the ecological environment and the development level of digital economy respectively, there are few studies on the empirical analysis of the positive significance and regional heterogeneity of the impact of the development level of digital economy on the ecological environment, which can be supplemented and referred to in this study. At the same time, it also provides intellectual support for our country to achieve high-quality development of digital economy and efficient governance of ecological environment.

Digital economy, data resources and enterprise green technology innovation: Evidence from A-listed Chinese Firms

The digital economy provides a framework for leveraging data resources to enhance enterprise green technology innovation. By harnessing digital tools and analytics, businesses can optimize resource use, streamline operations, and develop eco-friendly products and services. This synergy between the digital economy, data resources, and green technology innovation underscores the transformative potential of technology in addressing environmental challenges and fostering sustainable development. Against this backdrop, this study examines whether the digital economy promotes green technological innovation and uses a two-way fixed effect based on the data of A-share listed companies in Shanghai and Shenzhen from 2011 to 2020. The mediation effect model and threshold model are used to explore the possible mechanism played by data resources. The study shows that the development of the digital economy significantly promotes enterprises' green technology innovation. This positive effect is especially prominent in the east-central region, second-tier cities, and non-resource cities. In contrast, the digital economy inhibits firms' green technology innovation in Tier 4 and Tier 5 cities and resource-based cities. Mechanism analysis shows that the digital economy can further promote enterprise green technology innovation by developing data resources. The threshold effect indicates a double threshold variable for data resources. The digital economy has differentiated effects on enterprise green technology innovation in different digital resource intervals. It provides a new perspective for understanding green technology innovation in the context of the digital economy and data resources.

Housing Rent Control at the Micro Level: Perspectives from Southeast and East Central Europe, 1918–1924

This paper presents both statistical and qualitative analyses examining the micro-level repercussions of state intervention, specifically the implementation of rent control systems and requisitioning in the housing rental markets of Southeast- and East-Central European regions in the aftermath of the First World War. The numerical assessment relies on the calculation of the residual postwar purchasing power parity of prewar rents, while the qualitative analysis endeavors to reconstruct the daily dynamics of coexistence among conflicting parties, encompassing instances of extreme intimidation and violence.

Temporal analysis of land degradation and urban expansion in central Yunnan Province using remote sensing for supporting sustainable development goals 11/15

Monitoring land degradation and urban expansion is crucial for sustainable development and environmental stewardship. It helps protect arable land, ensure food security, mitigate climate change impacts, and guide urban growth while minimizing environmental harm, thus advancing the Sustainable Development Goals (SDG).This study focuses on the application of the Trends.Earth tool, following the UN-SDG indicator framework, to assess land changes, urban expansion, and drought vulnerability in the central east region of Yunnan Province, China, during the period 2000 to 2020.The analysis reveals significant trends in land transformation and urban growth. Notably, the central Yunnan region demonstrated a positive trajectory, with 69.58% experiencing land improvement and 8.55% undergoing degradation. Urban areas expanded dramatically, with Kunming City growing threefold from 2000 to 2015 raising concerns about sustainable land management. Drought vulnerability assessments unveil the temporal variation and the extent of impact on the population.This research underscores the importance of remote sensing and its role in achieving the SDGs. By providing a comprehensive assessment of land dynamics, urbanization patterns, and environmental vulnerability. As Yunnan Province grapples with both developmental aspirations and ecological conservation imperatives, this study serves as a foundation for informed decision-making to balance economic growth and environmental protection.

Spatio-Temporal Analysis and Clinical-Epidemiological Characterization of Visceral Leishmaniasis in Maranhão, Brazil, from 2009 to 2020.

This study was carried out to identify the spatial distribution and characterize the clinical-epidemiological profile of Visceral Leishmaniasis (VL) in Maranhão state, Brazil, from 2009 to 2020. This descriptive ecological study collected sociodemographic and clinical data of VL cases from the Brazilian Notifiable Diseases Information System database. A spatial autocorrelation analysis (Moran statistics) was performed. From 2009 to 2020, 5699 cases of VL were reported, with incidence of 6.5 cases/100,000 and prevalence of 7.1 cases/100,000. The temporal analysis showed a significant growth in incidence from 2009 to 2018, followed by a significant decrease between 2019 and 2020. The Moran map shows hotspots of high values in the central-west and central-east regions, and hotspots of low values in the northern region of Maranhão. The profile of patients affected by VL comprises males (OR = 1.8; IC95% = 1.72-1.92), aged under 14 years, brown, and with incomplete elementary schooling. The main symptoms reported were fever, fatigue, and edema. The main diagnostic method was laboratory. The mortality rate was 6.8%, and co-infection with HIV was reported by 8.5% of patients. The results of this study indicated the increase in incidence and lethality, as well as the expansion, of leishmaniasis in the state of Maranhão.

Demographic and social differences in autonomous vehicle technology acceptance in Hungary

Progress in automation has resulted in a growing number of autonomous vehicles (AVs). However, demographic and social differences behind the acceptance of AV technology are an emerging topic in the East-Central European region. These countries (e.g., Poland, Slovakia, Romania) move on a similar technological development path, and the social and economic conditions are alike; thus, Hungary represents this region well. This study contributes to fill this niche. We used quantitative research methods (factor analysis, Kruskal-Wallis H test, Pearson-correlation) to analyze with a snowball (non-probability) sampling. The Hungarian respondents (N=949) selected in the sample were interviewed through a face-to-face and online quantitative questionnaire. The results show that gender and age influence mostly the acceptance; residence and occupation have only partial influence. The propensity to take risks is significantly differentiated in almost all demographic segments. The results facilitate differentiation of users based on their demographic characteristics in AV adoption. Furthermore, the integration of risk propensity into the analysis helps to identify which potential user groups are more likely to overcome any fears of novelty or which clusters are more likely to adopt the current framework of safe transport without driver control. The outcomes are of interest to engineers, manufacturers and policy-makers who can adapt their products, services and taking measures to meet the mobility needs of potential users and introduce effective incentives to increase public acceptance of AVs.

Formal urbanisation in East-Central Europe

The East-Central European region has undergone a unique urbanisation process during socialist and postsocialist periods. These peculiarities result from social and economic development delays, which the statehas tried to remedy through massive interventions. One such intervention is urban reclassification, where the state promotes certain places it deems crucial, granting them urban status, often without actual developmentor urban characteristics. Due to its artificial character, this intervention is called formal urbanisation in our approach being a specific local feature of the urbanisation process. The visible result is the growth of the urbanpopulation, often only by administrative causes, with the reclassification of villages as towns. The emergence of numerous small towns, which we refer to as newest towns, has significantly influenced urbanisation, alteredthe concept of towns and cities3, and generated significant debates. In this paper, we compare the formal urbanisation of the socialist and post-socialist eras, trying to estimate the added value of formal urbanisation inthe latter period. We compare the administrative backgrounds of formal urbanisation in selected ECE countries for similarities and differences. Throughout the research, we analyse their formal urbanisation involvingapproximately 800 municipalities promoted since 1990 in Poland, Czechia, Hungary, and Romania, trying to identify common and unique features in the processes. Based on historical determination, modernisation, and integration into new spatial processes, considering demographic and functional changes, we developedtypes of formal urbanisation. Our research has revealed several common factors in the reclassification process, such as local initiatives, while we have also identified disparities between principles and practices and varyinglevels of control from regional and national actors. The study has also led to a deeper understanding of formal urbanisation in the context of the urbanisation process as a whole.

Colorectal cancer survival disparities in the five regions of Georgia.

The objective of this study was to examine 5-year colorectal cancer survival rates. We also determined whether demographics, tumor characteristics, and treatment modality were associated with 5-year CRC survival in the Clayton, West Central, East Central, Southeast, and Northeast Georgia regions because the significant higher CRC mortality rates in these regions in comparison to the overall rates in the State of Georgia. We conducted a retrospective cohort analysis using data from the 1975-2016 Surveillance, Epidemiology, and End Results program aggregated CRC patients to these five regions. Five-year CRC survival was calculated and stratified by the five regions of Georgia, using the Kaplan-Meier method with log-rank test. Cox proportional hazard regression was used to examine the mentioned association in these five regions. Among 11,023 CRC patients, 5-year CRC survival was lowest in Clayton (65.9%) compared to the West Central (69.0%), East Central (68.2%), Southeast (70.5%), and Northeast regions (69.5%) (p-value = 0.02). In multivariable analysis, greater risk of CRC death was found in the Clayton region compared to the West Central (HR, 1.12; 95%, 1.00-1.25) region when adjusting for demographics, tumor characteristics, and treatment modality. Among Clayton Georgians, age of 75+ years (HR, 2.13; 95%, 1.56-2.89), grade 3 & 4 tumors (HR, 2.22; 95%, 1.64-3.00), and distant stage (HR, 20.95; 95%, 15.99-27.45) were negatively associated with CRC survival. We observed place-based differences in CRC survival with significantly lower survival rates in the Clayton region. Factors associated with higher risk of CRC death include older age at diagnosis, high-grade tumors, and distant stage CRC among Clayton Georgians. Our study provides important evidence to all relevant stakeholders in furthering the development of culturally tailored CRC screening interventions aimed at CRC early detection and improved outcomes.

Mitigating effect of digital payments on the micro-enterprises’ financing constraints

Breaking the financing constraint is the focus of stimulating the innovation of micro-enterprises. Based on the 2020–2022 Chinese micro-enterprises’ survey data, the effect of data payment on the financing constraints of micro-enterprises is empirically examined. It is found that digital payment can significantly alleviate the financing constraints of micro-enterprises. The results of the heterogeneity test show that the mitigating effect of digital payments on the financing constraints of micro-enterprises in the western region is significantly stronger than that in the east-central region, and the mitigating effect on the financing constraints of micro-enterprises in the growth period is significantly stronger than that of micro-enterprises in the non-growth period. In addition, the level of financial marketization helps to strengthen the mitigating effect of digital payment on the financing constraints of micro-enterprises.