Population Growth Research Articles

Quantification of Green Carbon Changes in Relation with LULC Changes using Remote Sensing - GIS Technology in Kuantan River Basin

Land use land cover changes (LULCC) is a process that is influenced by anthropogenic effect. The growth of population is increasing, which leads to a demand on metropolitan regions. However, these urbanization and development are significant contributors to the expansion of LULCC conflict at an alarming rate to fulfil the human needs. LULCC has derived huge effects towards the environment which is biomass and green carbon changes. LULCC has caused vegetation covers of the land being degraded which reducing the total biomass of the area and implemented to that, the carbon stock for the area is increasing causing climate change and global warming. Therefore, the estimation of total carbon is important to be conducted. The existing map of LULCC is not update, the inventories information about the total carbon in Kuantan is not well covered, people in this region are lack of awareness about the harmful of carbon in the air, and conventional method is hard to be applied for carbon estimation are the problems that have derived for this study to be conducted. This study is focused on quantification of total carbon in Kuantan district to raise the awareness towards the local communities about the danger of high amount of carbon. The objective of this study is to classify LULC types in Kuantan district using geospatial artificial intelligent (GeoAI) approach on satellite images, to relate soil types, vegetation index and satellite – based total biomass in Kuantan River basin and to map green carbon changes in Kuantan based on quantified biomass using remote sensing – GIS technology. Therefore, this study is focused on Kuantan district to quantify the total biomass and carbon in this area by using selected multispectral satellites images with high spatial resolution Landsat 8 OLI, and Landsat 5 TM.

Assessing and anticipating environmental challenges in Lahore, Pakistan: future implications of air pollution on sustainable development and environmental governance.

Urban environment and air quality are changing primarily due to land use land cover (LULC) changes, economic activity, and urbanization. Air pollution has been increasingly acknowledged as a major issue for cities due to its extensive effects on health and well-being. As the second most populous city in the country, Lahorefaces alarming levels of air pollutants, whichinduced this study to focus on the pervasive issue of air pollution in Lahore. For this, the study collected air pollutants data from the Environmental Protection Department of Punjab and analyzed them using the ARIMA model. In the research results, both the observed data and predictive models uncovered concerning trends in pollutant concentrations, ultimatelyportraying a concerning picture for air quality management. Carbon monoxide (CO) levels show a consistent rise, surpassing Pakistan's environmental standards by 2025. Similarly, nitrogen dioxide (NO2) concentrations escalate, exceeding prescribed standards. Ground-level ozone (O3) also demonstrates a substantial increase, surpassing standards by 2025. Both PM2.5 and PM10 exhibit marked upward trends, projected to exceed recommended limits, particularly PM10 throughout the study year. The Air Quality Index exhibits an observable upward trend, fluctuating between 70 and 442 from 2015 to 2020. Similarly, a positive correlation was found between population growth and land use conversion into residential areas. Projections suggest a continuous increase, potentially hitting a severe level of 500 during winter by 2025. These findings point to an impending air pollution crisis, demanding urgent action to address the hazardous situation in the city. The study recommends that urban air pollution should be reduced, and the negative health effects of air pollution should be minimized using vegetation barriers, screens, and greening initiatives. Strict regulations and monitoring initiatives need to be put in place in big cities to monitor pollution and vegetation.

Predictors of Medical and Dental Clinic Closure by Machine Learning Methods: Cross-Sectional Study Using Empirical Data.

Small clinics are important in providing health care in local communities. Accurately predicting their closure would help manage health care resource allocation. There have been few studies on the prediction of clinic closure using machine learning techniques. This study aims to test the feasibility of predicting the closure of medical and dental clinics (MCs and DCs, respectively) and investigate important factors associated with their closure using machine running techniques. The units of analysis were MCs and DCs. This study used health insurance administrative data. The participants of this study ran and closed clinics between January 1, 2020, and December 31, 2021. Using all closed clinics, closed and run clinics were selected at a ratio of 1:2 based on the locality of study participants using the propensity matching score of logistic regression. This study used 23 and 19 variables to predict the closure of MCs and DCs, respectively. Key variables were extracted using permutation importance and the sequential feature selection technique. Finally, this study used 5 and 6 variables of MCs and DCs, respectively, for model learning. Furthermore, four machine learning techniques were used: (1) logistic regression, (2) support vector machine, (3) random forest (RF), and (4) Extreme Gradient Boost. This study evaluated the modeling accuracy using the area under curve (AUC) method and presented important factors critically affecting closures. This study used SAS (version 9.4; SAS Institute Inc) and Python (version 3.7.9; Python Software Foundation). The best-fit model for the closure of MCs with cross-validation was the support vector machine (AUC 0.762, 95% CI 0.746-0.777; P<.001) followed by RF (AUC 0.736, 95% CI 0.720-0.752; P<.001). The best-fit model for DCs was Extreme Gradient Boost (AUC 0.700, 95% CI 0.675-0.725; P<.001) followed by RF (AUC 0.687, 95% CI 0.661-0.712; P<.001). The most significant factor associated with the closure of MCs was years of operation, followed by population growth, population, and percentage of medical specialties. In contrast, the main factor affecting the closure of DCs was the number of patients, followed by annual variation in the number of patients, year of operation, and percentage of dental specialists. This study showed that machine running methods are useful tools for predicting the closure of small medical facilities with a moderate level of accuracy. Essential factors affecting medical facility closure also differed between MCs and DCs. Developing good models would prevent unnecessary medical facility closures at the national level.

Developmental regulators in promoting genetic transformation efficiency in maize and other plants

Given global agricultural challenges such as population growth, climate change, and limitations on resources and the environment, as well as increasing diversity in breeding goals, relying on traditional breeding methods is inadequate to provide food security requirements and promote sustainable development. Genetic transformation technology has become an effective tool for performing functional genomics research and molecular breeding. In this study, we conducted an in-depth analysis of 1669 literary works to investigate the potential of developmental regulators (DRs) in enhancing the efficiency of plant genetic transformation, with a concentration on their use in maize. Through multi-omics data analysis, we identified 12 homologous DRs from various species that are potentially applicable to maize. We identified a total of 41 possible disease resistances (DRs) for maize genetic transformation. Further experimental verification of ZmWIND1, a novel regulator belonging to the ERF/AP2 transcription factor (TF) family, showed that it significantly improved the efficiency of plant regeneration and transformation efficiency in maize. Specifically, compared to the control group, the callus induction rates for the pG3GB411-ZmWIND1 vector increased to 60.22 % and 47.85 % in Xiang249 and Zheng58, respectively. Transformation efficiency increased to 37.5 % in Xiang249 and 16.56 % in Zheng58, both significantly surpassing the control group. These findings have the potential to broaden the range of transformable maize varieties and lines, as well as introduce new genetic transformation methods in agricultural biotechnology, underscoring the immense potential to enhance genetic transformation efficiency through systematic exploration and application of DRs in maize.

Carbon emissions from global impervious surface expansion between 1985 and 2020

Impervious surface expansion (ISE) refers to the phenomenon that natural surfaces are covered by artificial materials, such as cement, asphalt, bricks, etc., usually due to human activities. Over recent decades, the rapid growth of the global population, economic development, and continuous urbanization have contributed to extensive ISE, which caused significant losses in terrestrial ecosystem carbon pools. A global assessment effort is lacking because of limited comprehensive data on carbon pools and uncertainties surrounding the extent of ISE. In this study, we aimed to quantify the carbon emissions resulting from global ISE between 1985 and 2020, following the method provided by the Intergovernmental Panel on Climate Change (IPCC) Guidelines. We first divided global land into 87 fine geographical zones by overlaying continental boundary information with an ecological zone map. Then, multiple time-series impervious surface data products, land cover dynamic monitoring product, global biomass data, and topsoil organic carbon (TSOC) information were integrated to build a lookup table (LUT) of biomass and TSOC density for these fine geographical zones. Last, we employed the IPCC method to estimate carbon emissions from ISE between 1985 and 2020. Our findings indicated a global ISE encompassing a total area of 58.12 Mha, with cropland encroachment accounting for 67.30 %. Over the past 35 years, cumulative committed carbon emissions from global ISE reached 1.14 ± 0.38 PgC, with TSOC representing 54.55 % and biomass carbon contributing 45.45 %.

Global prevalence and disability-adjusted life years of hypertensive heart disease: A trend analysis from the Global Burden of Disease Study 2019.

As hypertensive heart disease (HHD) presents a significant public health challenge globally, we analysed its global, regional, and national burdens and trends from 1990 to 2019. We used data from the Global Burden of Disease (GBD) 2019 study, focussing on the age-standardised prevalence rates (ASPRs) of HHD prevalence, age-standardised disability-adjusted life year (DALY) rates, average annual percentage change (AAPC), and risk factor attributions. We compared the HHD burden across sociodemographic index (SDI) strata, gender, age groups, and 204 countries and territories. In 2019, the global prevalence of HHD was estimated at 18 598 thousand cases, with DALYs reaching 21 508 thousand. From 1990 to 2019, the ASPRs increased (AAPC = 0.21; 95% confidence interval (CI) = 0.17, 0.24), while the age-standardised DALY rates decreased (AAPC = -0.45; 95% CI = -1.23, -0.93). We observed the highest increase in ASPRs in high-middle SDI quantile countries, and an overall negative correlation between age-standardised DALY rates and SDI. Individuals above 70 years of age were the most affected, particularly elderly women. There has been a significant increase in HHD burden attributed to high body mass index (BMI) since 1990. The burden of HHD is concentrated in the middle SDI quintile, with population ageing and growth being major drivers for the increase in DALYs. We identified opportunities for reducing age-standardised DALY rates in the middle SDI quintile or lower. Despite a declining trend in the age-standardised DALY rates, the ASPRs of HHD continue to rise, especially in high-middle SDI regions. Meanwhile, countries in middle and lower SDI quintiles face a higher burden of age-standardised DALY rates. Targeted attention towards elderly women and controlling high BMI, alongside enhancing hypertension and HHD management awareness, is crucial for reducing the global burden of HHD.

Critical areas for &lt;i&gt;Brettanomyces bruxellensis&lt;/i&gt; contamination and biofilm formation in the cellar: on the origin of wine spoilage

The cellar environment harbours a consortium of microorganisms on the material surfaces and in the air. Among these microorganisms, the spoilage yeast Brettanomyces bruxellensis can colonise surfaces due to its specific bioadhesive properties. In this study, air and surface samples were collected in several wineries during the winter period. B. bruxellensis was detected in the cellar environment either in the air or on the surfaces of various materials, including in tartaric acid precipitates. Difficult-to-clean tank equipment (taps, wall angles, valves) were identified as critical areas where B. bruxellensis was frequently detected. To confirm that surfaces contaminated by B. bruxellensis could be involved in wine contamination, yeast growth and volatile phenol production were monitored in wine in contact with stainless steel harbouring biofilms. The presence of bioadherent cells and biofilms in contact with the wine resulted in significant cell release into the wine, leading to population growth and the production of volatile phenols at concentrations above the olfactory detection threshold. This study demonstrates the possibility of wine spoilage by resident and adherent populations of B. bruxellensis and confirms the need to pay special attention to the hygiene of hard-to-reach areas such as valves.

High among‐species variability in the context dependence of herbivory across disturbance, weather and topoedaphic gradients

Abstract Species interaction effects on populations can vary in both magnitude (i.e. strong vs. weak) and sign (positive, negative, or no effect). Context‐dependent effects of species interactions occur when the sign or strength of the interaction's effect on population growth rate changes across abiotic gradients. We know that species can vary substantially in the degree of context dependence they exhibit, even across similar abiotic gradients. However, few studies have characterised context dependence of co‐occurring species, limiting our ability to understand the implications of context dependence for species interaction effects on community composition. Using over three decades of data collected for 13 tallgrass prairie forbs at the Konza Prairie Biological Station, we parameterise density structured population models that predict population dynamics as functions of abiotic conditions and bison herbivory. We use these models to estimate the degree of context dependence in responses to bison herbivory for 13 species across three abiotic gradients: weather, fire frequency and soil type. All species showed significant context dependence for fire frequency in the same direction, though with variable magnitude, such that herbivory increased cover with more frequent fires. Context dependence with weather and soil type varied dramatically across species in both direction and magnitude. For example, herbivory effects on 3/13 species were stronger in wet conditions, but herbivory effects on 5/13 species were stronger in dry conditions. Thus, context dependence exhibited by individual species, as opposed to effects of abiotic conditions on the relative abundances of species, could generate much of the weather‐dependent effects of herbivory on community composition. Synthesis: Our work suggests that species can vary dramatically in the presence, direction and magnitude of context dependence, even when occurring in the same community and when considering the same species interaction (i.e. response to a herbivore). In addition, we find that context dependence could drive substantial variation in the effect of species interactions on community characteristics (e.g. composition) across multiple abiotic gradients.

Application of a Multi-Layer Perceptron and Markov Chain Analysis-Based Hybrid Approach for Predicting and Monitoring LULCC Patterns Using Random Forest Classification in Jhelum District, Punjab, Pakistan.

Land-use and land-cover change (LULCC) is a critical environmental issue that has significant effects on biodiversity, ecosystem services, and climate change. This study examines the land-use and land-cover (LULC) spatiotemporal dynamics across a three-decade period (1998-2023) in a district area. In order to forecast the LULCC patterns, this study suggests a hybrid strategy that combines the random forest method with multi-layer perceptron (MLP) and Markov chain analysis. To predict the dynamics of LULC changes for the year 2035, a hybrid technique based on multi-layer perceptron and Markov chain model analysis (MLP-MCA) was employed. The area of developed land has increased significantly, while the amount of bare land, vegetation, and forest cover have all decreased. This is because the principal land types have changed due to population growth and economic expansion. This study also discovered that between 1998 and 2023, the built-up area increased by 468 km2 as a result of the replacement of natural resources. It is estimated that 25.04% of the study area's urbanization will increase by 2035. The performance of the model was confirmed with an overall accuracy of 90% and a kappa coefficient of around 0.89. It is important to use advanced predictive models to guide sustainable urban development strategies. The model provides valuable insights for policymakers, land managers, and researchers to support sustainable land-use planning, conservation efforts, and climate change mitigation strategies.

Water resources management under climate change and anthropogenic pressure in the upper Bandama catchment in Northern Côte d'Ivoire

ABSTRACT The upper Bandama basin at Badikaha in the North of Côte d'Ivoire, subject to climate change, has recorded a rapid population growth that significantly affects water availability. This study applies the water evaluation and planning (WEAP) system model to explore how the water resources available currently can meet people's needs in the future, mainly for irrigation, mine activities, rural and urban water supply and cattle breeding. The outputs from two regional climate models RACMO 22T and CCLM 4-8-17 under representative concentration pathway (RCP) 4.5 and RCP 8.5 scenarios were used for the climate change impact assessment. Results predict an increase in mean annual temperature by 1.5°C while precipitation could decrease by 21% by 2090. The climate model outputs coupled with the WEAP model show that unmet water demand estimated to 50 million m3 in 2020 could reach 115 million m3 in 2050. Nevertheless, climate change mitigation scenarios by the WEAP model, including the implementation of dams, boreholes and the hydraulics infrastructure improvement reveal that water scarcity could be reduced significantly in the catchment.

The Influence of Population and Economic Growth on Capital Expenditures through Original Regional Income of East Kalimantan Province 2018-2022

Understanding the degree of regional autonomy in funding development and government operations by raising the possibility of regional revenue is a crucial component of putting regional autonomy authority into practice. The degree of regional financial independence indicates how well the regional government has been able to boost local financial capability and lessen reliance on financial aid from the federal government. In order to determine the direct and indirect impacts between variables, this study used the route analysis data analysis method (route Analysis) with SPSS (Statistical Product and Service Solutions) software version 29. Path analysis is chosen in this study because it enables testing of the theoretical applicability of the methodology employed, which is the causal relationship approach. Path analysis is a useful tool for analyzing more complex models than multiple linear regression can handle. The government is projected to be able to implement strategic policy initiatives in an effort to raise Regional Original Income, which serves as a source of funding for capital expenditures.

Analyzing Lamprey Population Growth and Sex Ratio Evolution Through Cellular Automata and Impact of Predation Efficiency and Sex Ratio on Lamprey Populations

Analyzing Lamprey Population Growth and Sex Ratio Evolution Through Cellular Automata and Impact of Predation Efficiency and Sex Ratio on Lamprey Populations

The effect of a warmed enema during ovum pick-up on subsequent in vitro oocyte maturation in Southern white rhinoceros (Ceratotherium simum simum).

Rhinoceros are currently one of the most threatened mammal species globally. Slow population growth, increased poaching and habitat destruction have led to increased conservation efforts for each species. Assisted reproductive technologies (ART) have been implemented in an attempt to aid reproductive outputs for the conservation of these endangered species. Developing species-specific ART programmes for wildlife have been challenging. Temperature control during oocyte recovery is essential for ensuring in vitro success. This study is the first to investigate the effect of enema warming prior to trans-rectal ovum pick-up (OPU) on in vitro oocyte maturation in Southern white rhinoceros (Ceratotherium simum simum). OPUs were performed on 20 rhinoceros cows from three different game farms in South Africa; oocytes were transported to one of two in vitro fertilisation laboratories for culture. The enema fluid was either warmed to 32 °C or not warmed prior to the OPU. Location of the farm, the different laboratories, ambient temperature, season, aspiration probe temperature, media type and enema temperature were investigated as predictor variables for oocyte maturation success. After considering all other potential covariates, warming of the enema fluid was the only independent predictor of in vitro oocyte maturation success during this study. Oocytes retrieved from rhinoceros cows that received an enema warmed to 32 °C were 2.3 times more likely to mature in vitro compared to oocytes from cows that received an unwarmed enema; the findings can be implemented in other rhinoceros ART programmes and in conservation efforts of other endangered mammalian species.

Internal tension or external pressure? Study on the influencing factors of the diffusion of education policies for older adults in China – Based on the analysis of China’s provincial panel data from 2016 to 2023

ABSTRACT The development of education for older adults through policy measures has become an important means for governments to actively cope with population aging. Taking the number of education policies for older adults adopted in 31 provinces of China from 2016 to 2023 as an example, this study empirically analyzes the factors influencing the diffusion of education policies from dimensions of internal tension and external pressure. The results showed that the level of economic development, natural population growth rate, older adults dependency ratio, child dependency ratio, illiterate population over 15 years old, number of local libraries inside the province and the adoption of education policies for older adults in adjacent provinces significantly affected the adoption of education policies for older adults in each province. After the introduction of regional variables, it is found that there are significant differences in the adoption of education policies for older adults by provincial governments in different regions of China. The policy responsiveness of eastern provinces is the best, followed by the central, and the western is the worst. The above results indicate that provincial governments in China are not only affected by the supply level of education services for older adults and their service demand within the province, but also affected by the adoption behavior of other provinces when making decisions, which is the result of rational thinking and competitive pressure. The above results provide China’s experience for the diffusion and implementation of education policies for older adults in a wider range.

Analysis of the medical and demographic situation in the central region of Russia in the pre-pandemic period

Introduction. According to Federal State Statistics Service (Rosstat) , in 2021, the Vladimir Region took 69th place among all subjects of the Russian Federation in terms of natural population growth (loss). In terms of the frequency of general morbidity over 2010, the region was the most disadvantaged in the Central Federal District; in 2017, it was at the second place. The purpose of the study is to analyze the medical and demographic situation in the Vladimir region during the pre‒pandemic period. Materials and methods. The official statistical data of the Federal State Statistics Service and collections of the medical information and analytical center of the Vladimir region for 2001–2019 were used. The analysis of the main demographic indicators, as well as data on the general morbidity in children, adolescents, and adults in sixteen classes of diseases of the WHO classification (ICD-10) was carried out. Results. The population of the Vladimir Region has decreased by 192,247 people since 2001. A significant differentiation of morbidity values is shown both by different age groups and by administrative districts. Limitations of the study are usually related to the lack of access to detailed statistical information within administrative territories. The peculiarities of collecting and presenting statistical information on morbidity do not allow implementing a more detailed analysis within each age group, limited to three contingents. Conclusion. For the first time, a study of the medical and demographic situation in the Vladimir region, which developed over a nineteen-year pre-pandemic period, made it possible to establish risk territories with characteristic features of their health status.

Screening Urban Tree Species for Air Quality Enhancement: A Review

Air pollution poses a significant global challenge, particularly in urban areas, due to factors like industrialization, urbanization, increased vehicular traffic, and high energy consumption. In India, vehicle emissions, industrial activities, and power plants are major contributors to deteriorating air quality, with vehicles alone responsible for substantial carbon monoxide and hydrocarbon emissions. Unplanned urbanization and population growth further exacerbate pollution levels. Urban air pollution is linked to millions of deaths and respiratory illnesses annually, especially in developing countries. Vegetation plays a crucial role in mitigating air pollution by absorbing gaseous pollutants and particulate matter through leaves. Plants also act as bioindicators, displaying characteristic responses to specific pollutants. They employ mechanisms like leaf absorption, particulate deposition, and fallout on the leeward side to cleanse the atmosphere. Bio-monitoring with plants is a cost-effective method to assess environmental pollution impacts, highlighting the vital role of urban green spaces in improving air quality and public health. In summary, the screening of trees for pollution abatement is essential in urban planning. The APTI, coupled with assessing the dust-capturing capacity and emission reduction of trees, aids in categorizing them as sensitive indicators or effective pollution sinks.

Anthropometric measurements of children with neurofibromatosis type I: impact of plexiform neurofibroma volume and treatment.

In children and adolescents/young adults (CAYA) with neurofibromatosis type I (NF1), associations between anthropometric measurements, plexiform neurofibroma (pNF) tumor volume (TV), and treatment history are unknown. We retrospectively investigated anthropometrics in CAYA on the National Cancer Institute (NCI) NF1 Natural History Study who had pNF TV assessed by imaging (n = 106). We determined CDC height/weight percentiles and estimated Preece-Baines (PB) height growth curve parameters. We evaluated variables that could impact height/weight including: (1) pNF volume, (2) pNF directed therapy, and (3) serum IGF-1. 23% of males and 20% of females had height <5th percentile; 13% of males had weight <5th percentile. Estimated median final adult height for males was 171.6 cm (CDC 23rd percentile) and for females was 156.2 cm (CDC 14th percentile). Inverse associations between height and weight percentiles and pNF volume were observed (Spearman's r = -0.277, -0.216, respectively). Estimated median final height was not meaningfully affected by patients who received pNF-directed treatment with MEK inhibitor. 52% of low serum IGF-1 measurements were concurrent with a height percentile <5th. Greater than expected percentages of patients had height/weight <5th percentile, and median final adult heights were <CDC 25th percentile. pNF volume was inversely associated with height/weight percentiles. Children and adolescents/young adults with neurofibromatosis type I (NF1) seen at a research hospital have lower height and weight percentiles than normative populations. Growth percentiles are inversely associated with plexiform neurofibroma tumor volumes and impacted little by MEKi treatment history in this subset of patients. These findings align with prior investigations of growth in the NF1 population but are the first to examine the association with tumor burden.

The mediating effects of resilience in the relationship between social support and posttraumatic growth in patients with acute coronary syndrome in China.

Posttraumatic growth has a positive impact on patients diagnosed with acute coronary syndrome (ACS). Patients with acute coronary syndrome in China report low to moderate levels of posttraumatic growth. Additionally, there is a dearth of research exploring the associations between resilience, social support, and posttraumatic growth in this specific patient population. This study examined whether resilience serves as a mediator between social support and posttraumatic growth in patients with acute coronary syndrome who had been discharged for 1 to 6 months and were being followed up in clinics. A descriptive correlational study design was utilized. A systematic sampling technique was used to recruit 121 patients with acute coronary syndrome who had been discharged for 1 to 6 months from cardiovascular clinics of a tertiary care hospital in Jiangsu Province, China. The research instruments included the demographic characteristics questionnaire, the Connor-Davidson Resilience Scale, the Multidimensional Scale of Perceived Social Support, and the Posttraumatic Growth Inventory. The data were collected between August 2022 and November 2022 and were analyzed using descriptive statistics and regression analyses to determine the mediating effects. The level of posttraumatic growth among patients with acute coronary syndrome attending follow-up clinic visits was moderate (Mean = 60.58, SD = 14.13). Resilience had a direct and positive impact on posttraumatic growth (β = 0.361, p <0.001). Moreover, resilience fully mediated the relationship between social support and posttraumatic growth (indirect effect = 0.203, 95% CI [0.076, 0.331]; direct effect = 0.162, p = 0.101). Patients with acute coronary syndrome in China experience moderate posttraumatic growth after discharge. Resilience mediates the relationship between social support and posttraumatic growth. Therefore, nursing interventions focusing on promoting social support and resilience should be developed to encourage posttraumatic growth in patients with acute coronary syndrome.

Methodological proposal for measuring economic efficiency in regional transportation networks

This article seeks to improve the understanding and efficiency of transportation within and between metropolitan areas. Efficient transportation infrastructure and services are essential for achieving sustainable development, fostering economic growth, and minimizing environmental impacts. In metropolitan regions, where urbanization and population growth are concentrated, the significance of transportation efficiency becomes even more critical. To address this issue, the study proposes a methodology that combines graph theory and centrality measures to analyze regional hierarchies and their influence on transportation efficiency. By representing the regional road network, cities, and toll plazas as a graph with attributes linked to quantitative data of urban economies, this approach provides a concise and replicable method for examining network hierarchy in urban economies.

Nutrition, health benefits, and processing of sand rice (Agriophyllum squarrosum): Comparisons with quinoa and buckwheat

AbstractThe dual pressures of climate change and population growth have made the development of new grains a necessity. Agriophyllum squarrosum (sand rice) has high adaptability to harsh environments and does not occupy agricultural land. It is widely cultivated and consumed in Central Asia. Sand rice, together with quinoa and buckwheat, belongs to the same pseudocereals group with rich nutritional value and gluten‐free properties; however, its nutritional composition and health benefits differ from those of quinoa and buckwheat. Sand rice seeds are a rich source of nutrients and bioactive compounds, including proteins, amino acids, unsaturated fatty acids, and crude fiber, which are similar to those in buckwheat and quinoa; however, their starch content is relatively low. Sand rice seeds also possess phenolic acids and flavonoids, which exhibit antioxidant, anticancer, anti‐diabetes, and anti‐inflammatory properties. Furthermore, sand rice extracts are considered suitable for treating some chronic diseases. Overall, sand rice is considered a good plant‐based food that can be used to develop various functional foods and beverages or mixed with other grains in different recipes. However, advancements in the processing technology of sand rice‐based foods are required to fully exploit the potential of sand rice in the food industry to improve human health. This review analyzes the current understanding of the nutritional content of sand rice by comparing it with that of quinoa and buckwheat. Furthermore, its potential medicinal activity and feasibility as a functional ingredient to improve food quality is discussed.