Trends In Distribution Research Articles

Optimizing School Management through Genetic Algorithm-Driven Pattern Mining for Educational Process Enhancement

Improving school administration procedures is a crucial goal in the constantly changing field of education. Genetic algorithms (GA), influenced by natural selection, repeatedly examine possible solutions, assess their suitability, and progress towards the best patterns. In educational settings, this repeated improvement process enables the identification of concealed patterns in various datasets, such as student performance statistics, resource distribution trends, and administrative procedures. By using genetic algorithms, policymakers and educators have access to an advanced set of tools for making decisions based on data and improving processes. This paper introduces an Educational Optimization Genetic Algorithm (EOGA), a new approach for pattern mining to enhance school management operations. The suggested method deals with the changing nature of educational leadership by providing flexibility to adapt to different situations and developing priorities. Genetic algorithms help continuously improve and optimize school administration procedures, allowing institutions to adjust to new challenges and possibilities. By using genetic algorithm-based pattern mining, educators and others can discover detailed insights that standard analytical methods could miss. These understandings help administrators make educated decisions about resource distribution, curriculum improvement, and student assistance, leading to better educational results and organizational efficiency. By adopting a data-focused method, schools can go beyond conventional thinking and make ongoing enhancements in several aspects of school administration. Incorporating genetic algorithms into educational practices significantly promotes creativity, effectiveness, and high quality in education.

Mechanical response and numerical simulation of liquid soil abutment backfill

The application of a new liquid soil material and the treatment effect of backfilling an underpass tunnel in an airport are studied. The deformation and mechanical properties of liquid soil and conventional soil under load are comprehensively compared and analyzed via a numerical simulation with finite element software. The effects of the buried depth of overlying fill, tunnel height, and traffic load on the backfilling of liquid soil abutment are analyzed. The research results show that under the action of load, the overall deformation and stress distribution of the liquid soil and conventional soil show similar laws. However, liquid soil backfilling has great advantages over conventional soil backfilling in all aspects. Liquid soil backfilling can reduce the deformation and the compressive stress at the corner of the backfilling area by approximately 13% and 15%, respectively. The overburden buried depth has a great impact on the subgrade deformation. In the actual construction, the overburden buried depth should be 1.5 m. Overburden depth has a greater impact on the vertical deformation of the road, the self-weight of the overburden will act as an additional load on the overall roadbed, compared to conventional soil backfill, the overburden depth of 2.0 m conventional soil backfill overall deformation of the overburden depth is about equal to the overburden depth of 1.5 m liquid soil backfill, the use of liquid soil backfill is equivalent to the overburden fill to reduce the additional load of 0.5 m. The height of the box culvert has a greater impact on the stress, but this change is not linear, the actual construction in the case of meeting the specific requirements of use, should try to control in the vicinity of 8.4 m, and at the same time the use of liquid soil backfill can reduce the compressive stress of about 14%. The compressive stress increases first and then decreases with the increase in liquid soil modulus. The liquid soil modulus should be controlled to 180 MPa. Moreover, liquid soil backfilling can reduce the compressive stress in the backfilling area by approximately 25%. The trapezoidal slope of the backfill area is proportional to the deformation amount. Although an obvious correlation with compressive stress exists, the regularity is not strong. Thus, the trapezoidal slope should be set to 1:1 during construction. Traffic load slightly affects the overall deformation and compressive stress of the road. However, the distribution trend of deformation and stress changes obviously under the action of aircraft load. In the actual design, only one load form of aircraft load should be considered.

On the event-based extreme precipitation in the Xiangjiang River Basin, China: temporal-spatial distribution and future trends

On the event-based extreme precipitation in the Xiangjiang River Basin, China: temporal-spatial distribution and future trends

Field detection of indoor fire threat situation based on LSTM-Kriging network

Obtaining the fire development information quickly and accurately is an important part of indoor fire emergency evacuation and rescue. However, at present, buildings only use fire sensors to monitor whether a fire is occurring, and there is a lack of means to obtain real-time threat situation information on the development of fires. An LSTM-Kriging neural network model is proposed in this paper, which can quickly generate an indoor fire threat field using the temporal data of fire sensors when an indoor fire occurs. Firstly, the Kriging algorithm was improved by replacing the Euclidean distance used in the variational function with the nearest passable distance to obtain a more accurate representation of the indoor threat distribution trend, and combined it with the Long Short-Term Memory (LSTM) network to construct the LSTM-Kriging network. Secondly, indoor fire scenarios were constructed in PyroSim, and fire parameters were simulated randomly. After data augmentation, the indoor fire threat situation dataset was generated. Finally, the optimized LSTM-Kriging model was trained and compared with Transformer, LSTM, and Recurrent Neural Network (RNN) on the indoor fire hazardous situation dataset. The experimental results show that LSTM-Kriging is the most effective model compared with several models mentioned above and the prediction of threatening situation reaches an accuracy of 97.8 %, with an average computation time of 0.19s on the GPU, which can meet the requirement of real-time fire situation monitoring. The indoor fire threat situation field detection method proposed in this paper achieves intelligent indoor fire detection and improves the building fire safety.

Uropathogenic distribution and antibiotic resistance patterns according to multidrug-resistant bacteria colonization status in patients with stroke.

Urinary tract infections (UTI) are common in patients with stroke. The colonization of multidrug-resistant organisms (MDR) has recently become a global issue, and infection with MDR is associated with a poorer prognosis. This study aimed to investigate the uropathogenic distribution in stroke patients according to MDR colonization and investigate the infection risk and antibiotic resistance of each uropathogen to help determine initial antibiotic treatment. This study is a retrospective study conducted on patients who underwent inpatient treatment for stroke at Kosin University Gospel Hospital in 2019 to 2021. The participants were classified into Group VRE if vancomycin-resistant Enterococcus (VRE) colonization was confirmed, Group CRE if carbapenem-resistant Enterobacteriaceae (CRE) colonization was confirmed, and Group Negative if no MDR colonization was confirmed. Urine culture was performed if symptomatic UTI was suspected. Uropathogenic distribution, antibiotic resistance patterns were assessed by one-way analysis of variance, independent t-test, and Pearson chi-square test. And the infection risk factors for each uropathogen were assessed by multinomial logistic regression analysis. Six hundred thirty-three participants were enrolled. The mean age of all participants was 69.77 ± 14.91, with 305 males and 328 females, including 344 hemorrhagic strokes and 289 ischemic strokes. No growth in urine culture was the most common finding (n = 281), followed by Escherichia coli (E.coli) (n = 141), and Enterococcus spp. (n = 80). Group Negative had significantly more cases of no growth in urine culture than Group VRE (Odds ratio [OR], 11.698; 95% confidence interval [CI], 3.566-38.375; P < .001) and than Group CRE (OR, 11.381; 95% CI, 2.665-48.611; P < .001). Group VRE had significantly more E.coli (OR, 2.905; 95% CI, 1.505-5.618; P = .001), and more Enterococcus (OR, 4.550; 95% CI, 2.253-9.187; P < .001) than Group Negative. There was no statistical difference in antibiotic resistance according to MDR colonization in E coli, but for Enterococcus spp., Group VRE and CRE showed significantly more resistance to numerous antibiotics than Group Negative. MDR colonization increases the risk of UTI and is associated with greater antibiotic resistance. For appropriate administration of antibiotics in UTI, continuous monitoring of the latest trends in uropathogenic distribution is required, and clinicians should pay more attention to the use of initial empirical antibiotics in patients with MDR colonization.

Three-dimensional modeling of moisture transport in wood using near-infrared hyperspectral imaging and X-ray computed tomography in conjunction with finite element analysis

In past studies, finite element analysis (FEA) methods have been used to simulate the thermal and moisture coupling of wood. However, challenges remain in achieving high-quality three-dimensional (3D) simulations, mainly because of the heterogeneous and complex structure of wood and its difficult-to-detect internal structure, which makes modeling challenging, in addition to the lack of robust experimental techniques to validate simulation results. In this study, the FEA simulation model was refined by combining X-ray computed tomography (CT) and near-infrared hyperspectral imaging (NIR-HSI). CT was used to probe the 3D density of wood, and a novel FEA tetrahedral mesh was constructed based on the results. The NIR-HSI method visualizes the moisture distribution during adsorption and desorption inside the wood. This result is then used to adjust the parameters of the FEA simulation model and as a reference value to evaluate the simulation results. The visualization and simulation results fit well with the theoretical properties. The simulation results can more accurately reflect the spatial distribution and transfer trend of wood moisture at different points in time. Therefore, the CT and NIR-HSI-based 3D heat and moisture-coupled FEA model of wood proposed in this study can be used as a basis for optimizing drying parameters to provide high-quality wood.

Spillover Analysis of Carbon Market, Crude Oil Market, and Coal Market based on BEKK-GARCH

Global warming has become an urgent issue for all mankind, and climate change caused by carbon dioxide emissions is a growing concern. China, as a major global energy consumer, has set "carbon neutrality" as its vision for 2035. This study aims to explore the impact of carbon neutral policy on the volatility of the energy market, and through a comprehensive analysis of the historical data of the carbon market, crude oil market, and power coal market returns, we aim to reveal the volatility spillover effect among markets. In this study, we determine the distribution trend of yield receipts as t-distribution by performing statistical tests, ADF analysis on the yield historical data of the three markets. Under this premise, ARCH model, GARCH model and EGARCH model are further used to carry out the preliminary validation of the yield series of each market, and under the premise of ensuring the existence of volatility benefits in the data of each market, BEKK-GARCH model is used to carry out the analysis of multi-market spillover benefits, and the significance of the results is ensured by the WALD test. Finally, the results of the study are linked to actual policies and market operations to provide relevant recommendations for governments, investors, enterprises and carbon trading platforms. This study provides in-depth market perspectives and policy support for addressing the challenge of climate warming, and provides strong data support and decision-making reference for achieving the goal of carbon neutrality.

A Statistical Study Based on the Top 50 Blockchain Companies Analyzing the Current Development of Blockchain Applications

Nowadays, because of the Bitcoin and meta universe, blockchain wins a lot of attention from both the public and researchers, more and more people have started to work hard in this new area which has led the quick updates of the latest research progress and applications. This article tries to help other researchers have a clearer understanding of the current situation of blockchain applications. Chapter One first gives the historical background of blockchain's applications. It then comes out the research on the top popular applications in the blockchain field, how they become popular, and what improvements they can have. On the one hand, it aims to help researchers and entrepreneurs understand the market distribution and blockchain application development trends. On the other hand, it provides some ideas about existing problems of blockchain applications.

Premalignant and Malignant Esophageal Lesions in Bangladeshi Patients-A Study in a Tertiary Care Hospital

Background: In Bangladesh esophageal carcinoma is the leading malignant condition. Mortality rate of esophageal cancer is very high. Like other malignancies, early detection offers the best prognosis for esophageal carcinoma. Regular endoscopic and histologic surveillance have become standard procedure for follow up of patients with premalignant lesions. Objectives: The aim of this study was to evaluate the frequency and pattern of esophageal lesions with respect to age and sex groups and to determine the trends of histology, site distribution and risk factors of it. Methods: This study was a cross sectional study, carried out at the department of Pathology in Dhaka Medical College and Hospital from March 2018 to February 2020. Total 54 cases of esophageal biopsy were included in this study. All obtained samples were selected for routine histopathological study. Results: Most of the patients were male and mean age was 55.04 (±15.48) years. Squamous cell carcinoma was the most common malignancy seen in (26 cases) 48.15 % of patients and Barrett’s esophagus was common (13 cases, 24.07%) premalignant lesion. Maximum malignant and premalignant lesions (40 cases, 74.07%) were located in lower thoracic region of esophagus including gastro esophageal junction. Dysphagia was the main presenting complain in 96.3% of patients and 55.6% of patients were smoker. Conclusion: Barrett’s esophagus was the common premalignant lesion and squamous cell carcinoma was the commonest esophageal carcinoma followed by adenocarcinoma. Central Medical College Journal Vol 7 No 1 January 2023 Page: 20-25

Correlation of microstructure and hardness distribution of high-speed train wheels under original and service statuses

High-speed train wheels have complex service environments during wheel–rail contact, and a comprehensive understanding of the microstructural inhomogeneity at the rim is critical for service safety assessment. The local quenching process in the vicinity of the rim will cause a difference in microstructure, directly affecting the service performance of the material. In this study, high-throughput characterization method based on material genome engineering was used, the methods for characterising and identifying the microstructure of wheel steel were developed using high-throughput scanning electron microscopy, and the accuracy and reproducibility of the methods were evaluated. A point-to-point research scheme for microstructure image and hardness data was designed based on the concept of statistical mapping characterization. The area fraction of the proeutectoid ferrite and micro-Vickers hardness distribution in a large size range of the key area of the rim and their internal correlation was obtained, these helped avoid statistical and representativeness limitations of traditional local selection analysis of microstructure and hardness. The results indicates that the area fraction of proeutectoid ferrite and micro-Vickers hardness showed a clear gradient distribution, and opposite distribution trend, with a high negative correlation. In addition, by observing the correlation between microstructure and hardness, and studying the evolution of microstructure, it was found that the microstructure and hardness of the rim near the tread demonstrated a significant synergistic evolution law under the influence of service, this was observed both statistically and microscopically. These findings enhanced the application prospects of the microstructure-performance statistical mapping method, and were beneficial in efficiently evaluating the service life and safety of key components.

Statistical Framework: Estimating the Cumulative Shares of Nobel Prizes from 1901 to 2022

Studying trends in the geographical distribution of the Nobel Prize is an interesting topic that has been examined in the academic literature. To track the trends, we develop a stochastic estimate for the cumulative shares of Nobel Prizes awarded to recipients in four geographical groups: North America, Europe, Asia, Other. Specifically, we propose two models to estimate how cumulative shares change over time in the four groups. We estimate parameters, develop a prediction interval for each model, and validate our models. Finally, we apply our approach to estimate the distribution of the cumulative shares of Nobel Prizes for the four groups from 1901 to 2022.

Anthrax outbreak: exploring its biological agents and public health implications

The (re)emergence of several infectious zoonoses underlines the need for the re-evaluation of the transmission patterns and key players responsible for effective inter-species transfer of diseases. Anthrax is caused by Bacillus anthracis, a zoonotic rod-shaped, Gram-positive, spore-forming bacterium that is highly fatal to both human and animal populations. B. anthracis is widespread across several regions of the world, including Africa, Asia, southern Europe, North and South America, and Australia, and it has a remarkably high attendant impact on the sustainability and profitability of livestock. The current trend in the global distribution of anthrax necessitates an urgent contextual understanding of the key drivers of the spread of B. anthracis in different parts of the world toward the end goal of an anthrax-free world. The understanding of the drivers is integral for the development of control and preventive measures, and also the development of agents such as therapeutics and vaccines against B. anthracis. This review presents a holistic description of the transmission pattern and epidemiology of B. anthracis, and updates on the diagnostic techniques and approaches available for the detection of B. anthracis. In addition, this review highlights plausible prevention and control strategies for the bacterium. This review further underscores the need for participatory epidemiology, hygiene, and safety protocols, the establishment of comprehensive surveillance systems, and global collaborative efforts toward vaccine development as critical steps in controlling anthrax.

Toxicokinetics of Zearalenone following Oral Administration in Female Dezhou Donkeys.

Zearalenone (ZEN) is a mycotoxin produced by various Fusarium strains, that is present in food and feed raw materials worldwide, causing toxicity effects in animals and humans. This research aimed to explore the toxicokinetics of ZEN on female Dezhou donkeys following a single oral exposure dosage of 2 mg/kg BW (body weight). The sample collection of donkeys plasma was carried out at 0, 5, 10, 15, 20, 30, 45, 60, 90 min, 2 h, 2.5 h, 3 h, 3.5 h, 4 h, 4.5 h, 6 h, 9 h, 12 h, 24 h, 48 h, 72 h, 96 h and 120 h via intravenous catheter, and fecal and urinary samples were severally collected at 0 h and every 6 h until 120 h. The concentrations of ZEN, α-zearalenol (α-ZOL), β-zearalenol (β-ZOL), α-zearalanol (α-ZAL), β-zearalanol (β-ZAL), zearalanone (ZAN) in plasma, urine, and feces were detected by UPLC-MS/MS. Only ZEN was detected in plasma, and the maximum was 15.34 ± 5.12 µg/L occurred at 0.48 h after gavage. The total plasma clearance (Cl) of ZEN was 95.20 ± 8.01 L·kg·BW-1·h-1. In addition, the volume of distribution (Vd) was up to 216.17 ± 58.71 L/kg. The percentage of total ZEN (ZEN plus the main metabolites) excretion in feces and urine was 2.49% and 2.10%, respectively. In summary, ZEN was fast absorbed and relatively slowly excreted in female donkeys during 120 h after a single gavage, indicating a trend of wider tissue distribution and longer tissue persistence.

Trends in Distributions of Hearing Threshold Levels by Ages: A Comparison of the ISO 7029 and Newly Available Country-Specific Data.

Hearing thresholds provide essential information and references about the human auditory system. This study aimed to identify changing trends in distributions of hearing threshold levels across ages by comparing the International Organization for Standardization (ISO) 7029 and newly available data after publishing ISO 7029. To compare ISO 7029 and newly available hearing threshold data after publishing ISO 7029, four country-specific datasets that presented average hearing threshold levels under conditions similar to ISO 7029 were utilized. For frequencies between 125 Hz and 8,000 Hz, the deviations of hearing threshold values by ages from the hearing threshold of the youngest age group for each data point were utilized. For frequencies from 9,000 Hz to 12,500 Hz, the median threshold information was utilized. Hearing threshold data reported after publishing ISO 7029 from the four countries were mostly similar to the ISO 7029 data but tended to deviate in some age groups and sexes. As national hearing threshold trends change, the following ISO 7029 revision suggests the need to integrate hearing threshold data from different countries.

Spatial Distribution and Migration of Heavy Metals in Dry and Windy Area Polluted by Their Production in the North China

We explored the migration and distribution of heavy metal pollution in a dry and windy area in northern China. We collected soil, atmospheric deposition, and water samples, and measured heavy metal concentrations. Cu, Zn, As, and Pb in the 0–10 cm soil layer had a fan-shaped distribution, consistent with their atmospheric deposition fluxes. This indicates that the distribution of these heavy metals was driven by strong winds. The concentration of Cd in the river increased from 0.257 mg/L upstream to 0.460 mg/L downstream, resulting in the same distribution trends as soil near the river. Surface runoff may therefore drive Cd migration. The concentration of Pb in the river exceeded the pollution threshold, resulting in accumulation in the 5–10 cm soil layer. Atmospheric deposition fluxes were consistent with the soil distribution results, and principal component analysis showed that the contribution of surface runoff was high. This suggests that the migration of Pb and Cr is driven by both wind and surface runoff. Six heavy metals showed different migration behaviors, suggesting specific control strategies should be implemented for individual heavy metals.

Balancing low-carbon and eco-friendly development: coordinated development strategy for land use carbon emission efficiency and land ecological security.

Correctly identifying and handling the relationship between land use carbon emission efficiency (LUCEE) and land ecological security (LES) are important to promote carbon neutrality in the overall layout of ecological civilization construction. This study takes 30 provinces in China as the research unit and measures the level of LUCEE and LES in each province in the period from 2011 to 2020 via a super-efficient slack-based measure model considering undesirable output. The coupling coordination degree (CCD) of LUCEE and LES is calculated, and its spatiotemporal evolution pattern is explored by kernel density estimation and standard deviational ellipse (SDE). The Dagum Gini coefficient is used to study spatial regional differences and the sources of differences. Results show that (1) China's LUCEE exhibited a downward and then an upward trend, as well as a spatial pattern of "high in the west and low in the east" with obvious regional differences. The LES experienced a positive transformation of "less secure → basically secure → more secure" nationwide, with no apparent regional differences. (2) The kernel density curves showed a continuous increase in CCD in general, while interprovincial differences increased, then decreased, and shifted from multipolar to bipolar differentiation. (3) The migration of SDE centers in CCD demonstrated a path of "southeast → southwest → northeast," and the ellipticity increased from 0.167 to 0.173, showing a trend of concentrated distribution. (4) The overall Gini coefficient of the national CCD indicated a decreasing trend, but imbalances remained, with the largest annual average value in the western region (0.120) and the smallest in the northeast (0.044). The main source of regional disparity was the intensity of transvariation. Accordingly, this study proposes targeted regional development strategies to promote low-carbon sustainable land use and improve the ability of land ecosystems to prevent security risks.

Rapid recovery of invasive wild pig (Sus scrofa) populations following density reduction

Trapping is an effective strategy for control of invasive wild pig (Sus scrofa), but eradication of populations via trapping alone typically is impractical throughout much of the species’ introduced range. Consequently, recovery of wild pig populations to pre-trapping levels following control is a major impediment to success of long-term control. In this study, we conducted camera-trap surveys to monitor recovery of two wild pig populations immediately following density reductions achieved via trapping on two sites on the Savannah River Site, SC. We used spatial capture-recapture models to estimate wild pig density during seven 3 week periods spanning 12 months to: (1) determine the time required for populations to recover to pre-trapping levels; and (2) evaluate trends in population growth, density, and distribution during recovery. Recovery of both wild pig populations started immediately after trapping ceased, with populations reaching pre-trapping levels in 3 and 5 months. Threeweek population growth rates for each wild pig population during recovery averaged 1.28 (range = 1.11–1.39 on site 1) and 1.24 (range = 0.64–1.92 on site 2), which corresponded to a 345% and 132% increase in abundance (an increase of 141 and 126 individual wild pigs on site 1 and 2, respectively) of each population by the last survey period. Rapid recovery and growth beyond pre-trapping levels of wild pig populations likely were driven by residual wild pigs not removed by trapping and compensatory reproduction and immigration. Our study is one of the first to provide information on how quickly wild pig populations can recover following overall density reductions of 54–68% and indicates practitioners should be prepared to reinitiate trapping efforts in as little as 3 months to prevent recovery of wild pig populations following control.

Spatial distribution and temporal trends of tuberculosis case notifications, Uganda: a ten-year retrospective analysis (2013–2022)

BackgroundUganda has a high incidence and prevalence of tuberculosis (TB). Analysis of spatial and temporal distribution of TB is an important tool for supporting spatial decision-making, planning, and policy formulations; however, this information is not readily available in Uganda. We determined the spatial distribution and temporal trends of tuberculosis notifications in Uganda, 2013–2022.MethodsWe conducted a retrospective analysis of routinely-generated program data reported through the National TB and Leprosy Programme (NTLP) surveillance system. We abstracted data on all TB cases diagnosed from 2013 to 2022 by district and region. We drew choropleth maps for Uganda showing the TB case notification rates (CNR) per 100,000 and calculated the CNR using the cases per district as the numerator and individual district populations as the denominators. Population estimates were obtained from the 2014 National Population and Housing Census, and a national growth rate of 3% was used to estimate the annual population increase.ResultsOver the entire study period, 568,957 cases of TB were reported in Uganda. There was a 6% annual increase in TB CNR reported from 2013 (134/100,000) to 2022 (213/100,000) (p-value for trend p < 0.00001). Cases were reported from all 12 Ministry of Health regions during the entire period. The distribution of CNR was heterogeneous throughout the country and over time. Moroto, Napak and Kampala districts had consistently high CNR throughout the ten years. Kalangala district had lower CNR from 2013 to 2018 but high CNR from 2019 to 2022. Moroto region, in the northeast, had consistently high CNR while Mbale and Soroti regions in Eastern Uganda had the lowest CNR throughout the ten years.ConclusionThere was an overall increasing trend in TB CNR from 2013 to 2022. We recommend that the National TB program institutes intensified measures aided by more funding to mitigate and reverse the negative impacts of the COVID-19 pandemic on TB.

Assessing exposure to climate extremes over the Arabian Peninsula using ERA5 reanalysis data: Spatial distribution and temporal trends

Understanding climate extremes and indices is crucial for addressing climate change impacts, including the increased variability in local weather patterns and extreme events. Previous studies on the Arabian Peninsula (AP) have been limited by sparse station data and restricted spatial coverage. To overcome this limitation, this paper aims to assess the spatial distribution and temporal trends of temperature and precipitation indices suggested by the Expert Team on Climate Change Detection and Indices (ETCCDI) using ERA5 reanalysis data from 1951 to 2020 for the AP. Additionally, this study investigated the changes relative to the reference period (1951–1980). The modified Mann-Kendall test and Sen's Slope estimator are utilized to detect significant trends and estimate their magnitude. Results revealed that ERA5 was consistent with previous studies that utilized in-situ station data, which offers a more detailed picture of the affected areas. The findings indicated a significant warming trend in temperature indices, with an increase of over 1 °C per decade observed across several areas, including the northern AP, and certain regions experiencing a discrepant change of 3 °C increase compared to the reference period. Changes in rainfall indices indicate a shift in rainfall patterns from the AP's fertile southwest regions towards more intense patterns in specific eastern regions, including Oman, Kuwait, Saudi Arabia, and Yemen. However, the precipitation temporal trends are weak in magnitude and variable spatially, with dominant decreases in both intensity (-10 mm per decade) and frequency indices (-5 days per decade). Some locations are subject to the combined effects of most heatwave indicators simultaneously, while flood indicators and yet others by drought indicators influence others. All these locations have been accurately identified in this study. The findings provide valuable information regarding the region's climate change vulnerability and adaptation needs.

Vertical distribution characteristics of soil organic carbon and vegetation types under different elevation gradients in Cangshan, Dali.

The Cangshan National Nature Reserve of Dali City was adopted as the research object to clarify the vertical distribution characteristics of soil organic carbon (SOC) and vegetation types at different elevations in western Yunnan. The contents of SOC, light fraction organic carbon (LFOC), heavy fraction organic carbon (HFOC), and water-soluble organic carbon (WSOC) in the 0-30 cm soil layer at different elevations (2,400, 2,600, 2,800, 3,000, 3,200, 3,400, and 3,600 m) were determined, and the above-ground vegetation types at different elevations were investigated. Results showed that the SOC content was the highest in 0-20 cm surface soil and gradually decreased with the deepening of the soil layer. It increased then decreased with the increase in elevation, and it peaked at 3,000 m. The LFOC content was between 1.28 and 7.3515 gkg-1. It exhibited a decreasing trend and little change in profile distribution. The HFOC content ranged between 12.9727 and 23.3708gkg-1; it increased then decreased with the increase in profile depth. The WSOC content was between 235.5783 and 392.3925 mgkg-1, and the response sensitivity to elevation change was weak. With the increase in elevation, WSOC/SOC and LFOC/SOC showed a similar trend, whereas HFOC presented an opposite trend. This observation indicates that the active organic carbon content at 3,600 m was lower than that at 2,400 m, and the middle elevation was conducive to the storage of active organic carbon. Meanwhile, the physical and chemical properties of soil affected the distribution of organic carbon to a certain extent. The vegetation type survey showed that the above-ground dominant species within 2,400-2,800 m were Pinus yunnanensis and Pinus armandii. Many evergreen and mixed coniferous broadleaf forests were distributed from 3,000 m to 3,200 m. Species of Abies delavayi were mainly distributed from 3,400m to 3,600m. This research serves as a reference for the study of forest soil carbon stability in high-elevation areas and plays an important role in formulating reasonable land use management policies, protecting forest soil, reducing organic carbon loss, and investigating the carbon sequestration stability of forest ecosystems.