Regional Characteristics Research Articles

Determination of biomass energy potential based on regional characteristics using adaptive clustering method

Determining the energy potential of biomass is the first step in selecting the most suitable and efficient energy conversion technology based on regional characteristics. The approach to estimating and determining biomass potential generally uses geospatial technology related to collecting and processing data about mapping an area. Unfortunately, this method is inadequate for simulating the interaction between variables, nor can it provide accurate predictions for the biomass supply chain. As a result, the results obtained from this method tend to be biased and macro, particularly in regions experiencing rapid land-use development. In this paper, the author has developed a clustering methodology with a fuzzy c-means (FCM) algorithm to determine biomass energy potential based on regional characteristics to produce data clusters with high accuracy. Grouping the characteristics of clustering-based areas involves grouping physical or abstract objects into classes or similar objects.

The influence of depression on esophageal cancer outcomes: Using the National Inpatient Sample (NIS) 2021.

338 Background: Esophageal cancer (EC) remains a challenging malignancy with high morbidity and mortality rates. Depression is prevalent among cancer patients and has been shown to affect various clinical outcomes. This study aims to evaluate the impact of depression on mortality, length of stay (LOS), and hospitalization charges in patients with esophageal cancer using data from the NIS. Methods: We conducted a retrospective, population-based study using the NIS data to analyze patients diagnosed with esophageal cancer. Depression was the primary exposure variable using the appropriate ICD-10 code. We applied survey-weighted descriptive statistics, logistic regression, and linear regression models to assess outcomes, adjusting for demographic and clinical factors, including age, sex, race, comorbidities (Charlson Comorbidity Index), hospital teaching status, and regional characteristics. Results: A total of 40,855 patients with esophageal cancer were included, with 11.4% (n = 4,855) having a concurrent diagnosis of depression. The unadjusted mortality rate for the cohort was 9.18%, with depressed patients showing a lower mortality rate (6.45% vs. 9.53%, p = 0.0018). After adjusting for covariates, depression was associated with significantly lower in-hospital mortality (adjusted OR 0.63, 95% CI 0.48–0.83, p = 0.001). While the unadjusted mean length of stay (LOS) was slightly higher in depressed patients (7.66 vs. 7.25 days, p = 0.132), adjusted models showed no significant difference (β = 0.42 days, p = 0.132). Depression was associated with lower unadjusted total hospitalization charges ($92,321 vs. $104,156, p = 0.023), and in adjusted analyses, depressed patients incurred significantly lower costs (β = -$10,327, 95% CI -$19,233 to -$1,421, p = 0.023). Significant predictors of increased hospitalization charges included teaching hospital status (β = $34,029, p < 0.0001) and large hospital size (β = $38,481, p < 0.0001). Conclusions: Depression, while common among patients with esophageal cancer, was unexpectedly associated with lower in-hospital mortality, despite a longer length of stay and higher comorbidity burden. This suggests that depressed patients may receive more comprehensive or prolonged care, which could contribute to their reduced mortality risk. Additionally, despite extended hospital stays, these patients incurred significantly lower hospitalization costs, indicating possible differences in resource utilization or treatment intensity. These findings highlight the complex relationship between mental health and cancer outcomes, emphasizing the need for further research to explore the mechanisms behind these associations and to better tailor care for esophageal cancer patients with depression.

Evaluating the regional geological characteristics of the St. Peter Sandstone and Everton Formation for CO2 storage in Southern Illinois: A case study on site-specific injection feasibility in Washington County, Illinois

Evaluating the regional geological characteristics of the St. Peter Sandstone and Everton Formation for CO2 storage in Southern Illinois: A case study on site-specific injection feasibility in Washington County, Illinois

Realtime Accent Translation

Abstract: Accent Translation in Real-Time is one of the very first projects meant to overcome the barriers erected by regional accents in spoken languages. It uses the state-of-the-art research on speech recognition, NLP, and speech synthesis while translating speech from a source accent into a neutral or target accent in real-time. Accent detection and modification may include the use of deep learning models, like RNNs or transformers. In addition to the regional phonetic features, audio inputs on words with contextual meanings allow the reconstruction of the speech to conserve a desirable accent and continue giving the speaker their identity. Global communication, educational, and accessible applications would cultivate effective, comforting communication, where care for lingual background goes by the board. Project scope: low latency processing and scalabilitywhich should be able to support many languages and varieties of accents that might make it extremely practical yet quite an effective tool in this increasing world. Keywords— Real-Time Accent Translation, Speech Recognition, Natural Language Processing (NLP), Speech Synthesis, Deep Learning, Transformers, Multilingual Support, Low Latency Processing, Accent Identification, Phonetic Mapping, Seq2SeqModels, Voice Synthesis, Ethical Considerations, Global Communication, Accessibility

Global, regional, and national burdens of type 1 and type 2 diabetes mellitus in adolescents from 1990 to 2021, with forecasts to 2030: a systematic analysis of the global burden of disease study 2021

BackgroundAdolescent diabetes is one of the major public health problems worldwide. This study aims to estimate the burden of type 1 diabetes mellitus (T1DM) and type 2 diabetes mellitus (T2DM) in adolescents from 1990 to 2021, and to predict diabetes prevalence through 2030.MethodsWe extracted epidemiologic data from the Global Burden of Disease (GBD) on T1DM and T2DM among adolescents aged 10–24 years in 204 countries and territories worldwide. This study calculated the age-standardized prevalence rate (ASPR) and age-standardized DALY rate (ASDR) in adolescents based on the world standard population for cross-country comparisons. Average annual percentage changes (AAPC) in age-standardized rate were calculated by linkage point regression. Correlation analyses were used to identify the relationship between age-standardized rate and sociodemographic index (SDI). The Bayesian age-period-cohort (BAPC) model was used to predict changes in the diabetes prevalence among adolescents from 2022 to 2030.ResultsIn 2021, 3.4 million adolescents were living with T1DM, with an ASPR of 180.96 (95% CI 180.77–181.15), and 14.6 million were living with T2DM, with ASPR of 1190.73 (1190.13–1191.34). As national and territory SDI levels rise, the prevalence rate of T1DM increases (r = 0.44, p < 0.01), and the prevalence rate of T2DM decreases (r = − 0.18, p < 0.01). Compared with males, females had a greater age-standardized prevalence of T1DM (185.49 [185.21–185.76] vs. 176.66 [176.39–176.92]), whereas males had a greater ASPR of T2DM than females did (1241.45 [1240.58–1242.31] vs. 1138.24 [1137.40–1139.09]). This study found a negative correlation between the SDI and the ASDR for both T1DM (r = − 0.51, p < 0.01) and T2DM (r = − 0.62, p < 0.01) in adolescents. For T2DM patients, 32.84% of DALYs were attributed to high BMI, which increased by 40.78% during the study period. By 2030, 3.7 million people are projected to have T1DM, and 14.6 million are projected to have T2DM.ConclusionsAmong adolescents, the burden of T1DM and T2DM is increasing and varies by region, sex, and SDI. Therefore, targeted interventions based on regional features are needed to prevent and control adolescent diabetes. Moreover, more efforts are needed to control climate change and obesity to reduce the adolescent diabetes burden.

Density-Refine: Patent Image Retrieval by Density based Region Extraction and Feature Fusion

Density-Refine: Patent Image Retrieval by Density based Region Extraction and Feature Fusion

Determinants of future anxiety across individual, household, and regional levels in South Korea using a social ecological model

This study is the first to examine the determinants of future anxiety in South Korea using the Social Ecological Model (SEM). It aimed to show that, beyond individual factors, mezzo- and macro-level aspects, particularly those related to housing, may influence anxiety. Utilizing 2018 data from the Korean Health Panel Survey, we employed a three-level multilevel analysis to investigate how these factors contribute to the perception of future anxiety among Koreans. Our findings reveal that future anxiety is influenced by a complex interplay of demographic and socio-economic factors, including gender, age, health status, economic stability, living conditions, and regional socio-economic indicators. Notably, the study highlights the significant role of household-level factors, such as income and housing status, in shaping individuals’ anxieties about the future. Additionally, regional characteristics like housing vacancy rates and suicide rates are found to have an impact, suggesting the importance of broader socio-economic and cultural contexts in understanding future anxiety. Given South Korea’s socio-economic challenges, including the real estate crisis and demographic shifts, our study underscores the need for targeted policies to alleviate future anxiety, enhance mental well-being, and promote a more equitable society.

Measurement and spatiotemporal evolution characteristics of dietary diversity among Chinese residents

PurposeThe purpose of this paper is to measure the dietary diversity and to analyze the regional characteristics, differences, and evolutionary trends of dietary diversity among Chinese residents.MethodsIn this paper, the dietary diversity among Chinese residents was measured using the Shannon index based on the provincial-level food consumption data from 1995 to 2021. On this basis, the paper employs analysis methods such as kernel density estimation, spatial correlation test, and Dagum’s Gini coefficient to analyze the regional characteristics, differences, and trends of change in dietary diversity.ResultsDuring the study period, the dietary diversity among Chinese residents showed an increasing trend. Among the four major geographic regions, the dietary diversity was highest in the southern region, followed by the northern region, northwest region, and Qinghai-Tibet region. Among the three major economic regions, the dietary diversity was highest in the eastern region, followed by the central region and western region. There was a significant positive spatial correlation in the dietary diversity among Chinese residents, and both high-high agglomeration and low-low agglomeration phenomena were strengthened. In terms of the trend of regional differences, whether overall differences, interregional differences, or intraregional differences, they all showed a shrinking trend. However, interregional differences were the main source of overall differences in dietary diversity among Chinese residents.ConclusionThe dietary diversity among Chinese residents shows an overall increasing trend, and there are regional differences in dietary diversity from the perspectives of economic and geographic regions, which have been narrowing over time.

Identifying Suitable Dam Locations in Al Dinder: Integrating GIS, Remote Sensing, and Hydrological Factors

This study evaluates the suitability of dam site locations in the Al Dinder region of Sudan using a GIS-based approach and weighted overlay analysis. Five key criteria were assessed: Stream Order, Slope, Soil Type, Precipitation, and Land Cover. Each criterion was analyzed to determine its impact on selecting optimal sites for dam construction. The results reveal that fourth-order streams offer the highest suitability due to their larger flow capacity, covering 11.4% of the area, while first-order streams, accounting for 48.9%, are less suitable. Slope analysis shows that 99.52% of the region features gentle slopes (0-5°), which are ideal for dam construction. Soil type analysis identifies Gleysols as the most favorable for dam foundations, covering 86.1% of the area. Precipitation levels, particularly in areas receiving 1200-2200 mm of rainfall, are deemed highly suitable for dam operations. The study further reveals that 96% of the land cover consists of barren land, which is advantageous for construction due to minimal land-use conflicts. A detailed cross-sectional profile analysis of six proposed dam sites identified Dam 5 as the most suitable location, offering stable terrain, a consistent cross-section, and favorable hydrological conditions. Other sites, such as Dam 1 and Dam 6, show promise but require additional engineering modifications. The study’s findings contribute valuable insights into sustainable water resource management and infrastructure development in regions with similar environmental conditions. Key recommendations include further feasibility assessments, environmental impact analyses, and consideration of the social and economic benefits of dam construction.

Insights from Optimized Non-Landslide Sampling and SHAP Explainability for Landslide Susceptibility Prediction

The quality of sampling data critically influences landslide susceptibility prediction accuracy. Current studies commonly use a 1:1 ratio of landslide to non-landslide samples, failing to reflect natural geographical variability. This study develops a region-specific framework by integrating SHAP (SHapley Additive exPlanation) analysis with twelve landslide conditioning factors (LCFs) and three progressive sampling strategies, aiming to create adaptive non-landslide point selection criteria tailored to unique environmental and geological characteristics. The strategies include (1) multi-ratio random sampling (1:1 to 1:200), (2) susceptibility-based sampling adjustments derived from pre-susceptibility analysis, and (3) LCF-based correction using the NDVI threshold identified through SHAP analysis. Results show that LCF-based correction achieved the highest performance, while a 1:5 ratio proved optimal in random sampling, aligning with regional characteristics. This framework demonstrates the importance of region-specific sampling strategies in improving landslide susceptibility prediction.

Using Integrated Geodetic Data for Enhanced Monitoring of Drought Characteristics Across Four Provinces and Municipalities in Southwest China

This paper presents an analysis of regional terrestrial water storage (TWS) changes and drought characteristics in Southwest China, encompassing Sichuan Province, Chongqing Municipality, Yunnan Province, and Guizhou Province. Existing geodetic datasets, such as those from the Gravity Recovery and Climate Experiment (GRACE) and its successor satellites (GRACE Follow-On), as well as Global Navigation Satellite System (GNSS) data, face significant challenges related to limited spatial resolution and insufficient station distribution. To address these issues, we propose a novel inversion method that integrates GNSS and GRACE/GFO data by establishing virtual stations for GRACE/GFO data and determining the weight values between GNSS and GRACE/GFO using the Akaike Bayesian Information Criterion (ABIC). This method allows for estimating the TWS changes from December 2010 to June 2023 and monitoring drought conditions in conjunction with hydrometeorological data (precipitation, evapotranspiration, and runoff). The results show strong correlations between TWS changes from the joint inversion and GNSS (0.98) and GRACE/GFO (0.69). The Joint Drought Severity Index (Joint-DSI) indicates five major drought events, with the most severe occurring from July 2022 to June 2023, with an average deficit of 86.133 km³. Extreme drought primarily impacts Sichuan and Yunnan, driven by abnormal precipitation deficits. The joint inversion methodology presented in this study provides a practical approach for monitoring TWS changes and assessing drought characteristics in Southwest China. This paper leverages the complementary strengths of GNSS and GRACE/GFO data and offers new insights into regional water resource management and drought detection.

Real-Time Detection of Smoke and Fire in the Wild Using Unmanned Aerial Vehicle Remote Sensing Imagery

Detecting wildfires and smoke is essential for safeguarding forest ecosystems and offers critical information for the early evaluation and prevention of such incidents. The advancement of unmanned aerial vehicle (UAV) remote sensing has further enhanced the detection of wildfires and smoke, which enables rapid and accurate identification. This paper presents an integrated one-stage object detection framework designed for the simultaneous identification of wildfires and smoke in UAV imagery. By leveraging mixed data augmentation techniques, the framework enriches the dataset with small targets to enhance its detection performance for small wildfires and smoke targets. A novel backbone enhancement strategy, integrating region convolution and feature refinement modules, is developed to facilitate the ability to localize smoke features with high transparency within complex backgrounds. By integrating the shape aware loss function, the proposed framework enables the effective capture of irregularly shaped smoke and fire targets with complex edges, facilitating the accurate identification and localization of wildfires and smoke. Experiments conducted on a UAV remote sensing dataset demonstrate that the proposed framework achieves a promising detection performance in terms of both accuracy and speed. The proposed framework attains a mean Average Precision (mAP) of 79.28%, an F1 score of 76.14%, and a processing speed of 8.98 frames per second (FPS). These results reflect increases of 4.27%, 1.96%, and 0.16 FPS compared to the YOLOv10 model. Ablation studies further validate that the incorporation of mixed data augmentation, feature refinement models, and shape aware loss results in substantial improvements over the YOLOv10 model. The findings highlight the framework’s capability to rapidly and effectively identify wildfires and smoke using UAV imagery, thereby providing a valuable foundation for proactive forest fire prevention measures.

Japanese Konbini Minimarkets: Unique and Universal Character, Regional Characteristics

Based on the analysis of statistical and information sources, academic publications, and the authors’ personal experience, the article analyzes the peculiarities of Japanese minimarkets that rank among amazing Japanese inventions, creations, and practices and have become an integral part of the Japanese way of life and a trademark of the country. In the academic literature, there have been no comprehensive works focused on this phenomenon so far, and their regional peculiarities, especially the geography of stores operated by different chains, are almost completely neglected. The purpose of this article is to highlight the key academic discourse, to characterize the unique character and universality, which, in fact, constitute the phenomenon of konbini, as well as to identify their regional features.The study clearly shows that these stores, which came to Japan from the United States in 1973, have been completely transformed and are constantly evolving, changing the store concept and presenting a globally unique phenomenon. It describes the characteristics of the leading chains of these stores in their endeavor to gain even greater popularity among consumers and the innovations that have emerged in recent years, including those caused by the COVID-19 pandemic. Studying the phenomenon of konbini, the authors, on the one hand, note their transformation into an important element of social infrastructure, that meets the needs of modern society and is especially necessary in the context of rapidly progressing aging of the population, and, on the other hand, their certain negative impact, especially on the younger generation.The paper features an analysis of the regional characteristics of these stores and the cartographic material illustrating them. It is revealed that, within prefectures, the location of konbini correlates with the number of inhabitants (the number of stores is proportional to the population of municipalities), and each of the 20 konbini chains operating in Japan is located in its own specific area. The authors conclude that konbini facilitate the development of the country’s regions as a whole, and their role in Japanese society cannot be overemphasized. The Japanese experience can be relevant to other countries, including Russian chain stores.

Comparing the cost-benefit of breast cancer screening programs in rural and urban areas across four economic zones in China: a Markov modeling analysis

BackgroundThis study assessed the effectiveness and cost-effectiveness of breast cancer screening across rural and urban regions in China’s four economic zones.MethodsUsing a decision-analytic Markov model, we evaluated 5,280 scenarios involving different ages and screening technologies. The model followed individuals from birth through 100 yearly cycles in eight settings. Model parameters, such as incidence, transition rate, attendance and compliance rate, screening accuracy, utility, and mortality, were based on Chinese research and international data. Screening costs were calculated using median medical costs in the respective zones. The main outcome measured was incremental net benefit (INB) and incremental cost-effectiveness ratio (ICER), with sensitivity analyses to assess uncertainty.ResultsUsing a willingness-to-pay threshold of three times the local per capita Gross domestic product (GDP), the recommended strategies varied across regions. However, annual screening of individuals aged 30–70 years with a combination of mammography (MAM) and computed tomography laser mammography (CTL) was the most cost-effective strategy for most regions. The incremental cost-effectiveness ratios (ICERs) of the most cost-effective strategies, compared to no intervention and status quo in China, ranged from US$5,173.31/QALY to US$18,551.27/QALY, and from US$-3,872.28 to US$17,804.59, respectively. Except for the rural central region, where the cost-effective strategy had suboptimal outcomes compared to status quo, the recommended strategies in the other seven regions could prevent 41.12–58.80% and 8.08–35.39% of advanced breast cancer cases, and 18.83–29.27% and 2.71–14.06% of breast cancer deaths, when compared to no screening and status quo, respectively. Sensitivity analysis indicated that the results were robust.ConclusionOur study identified cost-effective breast cancer screening strategies suitable for the rural and urban areas in China’s four major economic zones. These findings highlight the necessity of universal screening and the importance of optimizing strategies based on regional economic development and epidemiological characteristics. These insights are crucial for improving national breast cancer screening policies.

The Level of Green Development in China and Influencing Factors—A Case Study of the Huai River Ecological Economic Belt

ABSTRACTEnvironmental issues are significant challenges for China's growth, with green development being crucial. The Huai He River Ecological and Economic Belt (EEB), a vital north–south economic corridor, plays a key role in demonstrating ecological civilization and regional coordinated development, essential for China's eco‐progress. This study uses the super‐SBM‐DEA model to measure the green development efficiency (GDE) of the EEB from 2005 to 2020, introducing innovative input–output indicators like technological innovation, industrial, environmental, and social gains. It analyzes the GDE from multiple angles using the Malmquist index, Moran index, and Durbin model, examining the temporal and spatial evolution and influencing factors of the EEB. Four key findings emerge: (1) The EEB's green development level trends upward, with western urban areas showing superior sustainable growth and environmental efficiency compared with the east. (2) Technological progress is the primary driver for improving the green level in the EEB. (3) The spatial agglomeration of green development levels is increasing. (4) Technological innovation significantly influences the EEB's GDE, while the digital economy level and environmental regulation promote it. Conversely, a single energy structure, urbanization, and foreign investment negatively impact the GDE, whereas economic growth and industrial structure enhancement positively affect the region's GDE but may adversely affect neighboring areas. The study recommends strategies to advance the premium quality evolution of the EEB, tailored to its regional characteristics.

VOCATIONAL EDUCATION IN PEREYASLAV IN THE EARLY TWENTIETH CENTURY: CONTENT AND MAIN ACTIVITIES IN THE CONTEXT OF THE DEVELOPMENT OF NATIONAL EDUCATION

A retrospective analysis of professional education development and formation of Pereiaslav at the beginning XX century was made in this article; the development of commercial school of Pereiaslav at the beginning XX century, vocational technical training was studied on the archive recording and egghead paperback research and analysis ground. Descriptive information: history, professional education, Maecenas. The history of professional education development and formation is an essential part of national history.Taking into account modern educational reforms in Ukraine the interest in analyzing the background and development of vocational technical training increased. A huge majority of scientists` works concerning branch education and research affairs issues can serve as evidence.Pererva V., Seiko N., Berezivska L., Kazmyrchuk G., Kazmyrchuk M. and others are engaged in problems of foundation and direction of commercial education in Ukraine. Sikorcriy M., Filonenko N., Gozkalo G., Nabok L., Troncko T. and others are engaged in problems of foundation and direction of commercial education in Pereiaslav at the beginning XX century.At the second part of XIX century after the abolition of serfage the developing industry was requiring skilled workers; and a lot of forward-minded people from different sections of the community were realizing the necessity in training of an educated man. The development ofcapitalism stimulated increasing of the commercial schools. Different ministries were opening their educational establishments: the Ministry of Local Education was opening teachers` seminaries, the Ministry of Agriculture was opening veterinary schools, and the Ministry of War was opening cadet corps, military specialized schools, and academies. The handicraft classes were opened in rural schools. Special handicraft schools were organizing.At the second part of XIX century some positive changes came into formation of commercial education: the foundation of professional education was laid, the secondary school teaching no classics was created, and the number of special education establishments was opened. The educational establishments existed thanks to money of private individuals, because state educational support was not enough. Representatives of Pereiaslav elite and industrialists paid a lot of attention to the development of the commercial education system. The best features of former entrepreneurial elite were embodied in their public activities.The study of the origins of the historical experience of the development of education at the regional level has not only scientific and cognitive, but also applied significance. The analysis of regional features of the development of national education provides an opportunity to understand the processes and phenomena that occur today in the educational environment and are caused by changes in the social and economic life of our country.

Research on the Pattern and Evolution Characteristics of Global Dry Bulk Shipping Network Driven by Big Data

The dry bulk shipping network is an important carrier of global bulk commodity flow. To better understand the structural characteristics and future development trends of the global dry bulk shipping network (GDBSN), this study proposes a framework for characteristics analysis and link prediction based on complex network theory. The study integrates large-scale heterogeneous data, including automatic identification system data and port geographic information, to construct the GDBSN. The findings reveal that the network exhibits small-world properties, with the Port of Singapore identified as the most influential node. Link prediction results indicate that many potential new shipping routes exist within regions or between neighboring countries, exhibiting clear regional clustering characteristics. The added links mainly influence the local structure, with minimal impact on the overall network topology. This study provides valuable insights for shipping companies in route planning and for port authorities in developing strategic plans.

Genetic Structure of Hereditary Forms of Diabetes Mellitus in Russia.

Analyzing the genetic architecture of hereditary forms of diabetes in different populations is a critical step toward optimizing diagnostic and preventive algorithms. This requires consideration of regional and population-specific characteristics, including the spectrum and frequency of pathogenic variants in targeted genes. As part of this study, we used a custom-designed NGS panel to screen for mutations in 28 genes associated with the pathogenesis of hereditary diabetes mellitus in 506 unrelated patients from Russia. The study identified 180 pathogenic or likely pathogenic variants across 13 genes (GCK, HNF1A, HNF1B, HNF4A, ABCC8, INS, INSR, KCNJ11, PAX4, PDX1, ZFP57, BLK, WFS1), representing 46.44% of the analyzed cohort (235 individuals). The glucokinase gene (GCK) had the highest number of identified variants, with 111 variants detected in 161 patients, 20 of which were identified for the first time. In the tissue-specific transcription factor genes HNF1A, HNF4A, and HNF1B, 34 variants were found in 38 patients, including 13 that were previously unreported. Seventeen variants were identified in the ABCC8 gene, which encodes the ATP-binding cassette transporter 8 of subfamily C, each found in a different patient; four of these were novel discoveries. Nine pathogenic or likely pathogenic variants were identified in the insulin gene (INS) and its receptor gene (INSR), including four previously unreported variants. Additionally, we identified 10 previously unreported variants in six other genes among 11 patients. Variants in the genes GCK, HNF1A, HNF1B, HNF4A, ABCC8, INS, and INSR were the main contributors to the genetic pathogenesis of hereditary diabetes mellitus in the Russian cohort. These findings enhance our understanding of the molecular mechanisms underlying the disease and provide a solid basis for future studies aimed at improving diagnostic accuracy and advancing personalized therapeutic strategies. This knowledge provides a foundation for developing region-specific genetic testing algorithms and personalized therapeutic strategies, which are critical for future initiatives in precision medicine.

Chemical and Physical Analysis of Different Types of Soil in India

This study examines the chemical and physical properties of soils across various regions of India, focusing on their agricultural production and environmental sustainability. Chemical testing revealed notable variations in soil pH and nutrient content. Phosphorus ran from 15 to 47 ppm; potassium from 180 to 270 ppm; nitrogen from 12 to 22 ppm; and pH from 5.4 to 6.8. Revealing the intricate interactions among several components improves correlation analysis and offers important information for the development of concentrated soil management strategies. The soil structure determines water retention capacity and nutrient availability regardless of loam, sand, or clayey. Studies of heavy metals revealed varying degrees of mercury, cadmium, arsenic, and lead all around India. Since it shows the changes in easily available water over time, the moisture content of the soil is vital for irrigation planning and agriculture. Emphasising the need of soil porosity (28.45% to 40.17%) and permeability (7.83 to 11.23 cm/hr) for water movement and root penetration is absolutely vital. These findings support informed decision-making in soil management, promoting sustainable agricultural practices tailored to regional soil characteristics.

Vegetation Quality Assessment of the Shaanxi Section of the Yellow River Basin Based on NDVI and Rain-Use Efficiency

The Yellow River Basin is a critical region for ecological environment protection and social and economic development in China. It is of great significance to study vegetation dynamics for the high-quality development of the Yellow River Basin. In this study, based on the data of NDVI and precipitation datasets in the growing season (June to September) from 2000 to 2019, we used a Sen+Mann–Kendall trend analysis and other methods to study the spatial and temporal evolution characteristics of precipitation and vegetation cover in the Shaanxi section of the Yellow River Basin and to assess the regional vegetation quality change characteristics based on estimating the rain-use efficiency (RUE). The results show the following: (1) The precipitation in the study area showed a spatial distribution pattern of more in the south and less in the north, in which Yulin City had the lowest precipitation overall, but it was an area with significant increasing precipitation. (2) The NDVI value of the Shaanxi section of the Yellow River Basin showed an overall upward trend from 2000 to 2019, with a growth rate of 0.327/10a. The vegetation cover showed the spatial characteristics of high in the south and low in the north, which showed that the vegetation growth condition was poor in the wind-sand grassland area at the southern edge of the Mu Us Sandland in the northwestern part of Yulin City and the construction areas in the Guanzhong Plain. Meanwhile, the vegetation grew well in Yan’an City and the area close to the Qinba Mountains. Moreover, the NDVI of the study area increased with the increase in precipitation. (3) The vegetation quality in the study area showed fluctuating interannual changes and a weak upward trend. More than 80% of the vegetation in the study area was in a state of improvement, and the areas with more significant improvement were mainly located in the northern part of the study area, while the vegetation was degraded in the urban and urban suburb areas in the Guanzhong Plain. The results of this study are of great practical significance for promoting the socio-economic development of the Yellow River Basin in coordination with ecological environmental protection.