Regional Variability Research Articles

Comparative analysis of chloroplast genomes in ten holly (Ilex) species: insights into phylogenetics and genome evolution

In order to clarify the chloroplast genomes and structural features of ten Ilex species and provide insights into the phylogeny and genome evolution of the genus Ilex, we conducted a comparative analysis of chloroplast genomes using bioinformatics methods. The chloroplast genomes of ten Ilex species were obtained, and their structural features and variations were compared. The results indicated that all chloroplast genomes in the genus Ilex exhibit a double-stranded circular structure, with sizes ranging from 157,356 to 158,018 bp, showing minimal differences in size. The chloroplast genomes of the ten Ilex species have a relatively conservative gene count, with a total of 134 to 135 genes, including 88 or 89 protein-coding genes, and a conserved number of 8 rRNA genes. Each chloroplast genome contains 3 to 123 SSR (Simple Sequence Repeat) sites, predominantly composed of mononucleotide and trinucleotide repeats, with no detection of pentanucleotide or hexanucleotide repeats. The variation in dispersed repeat sequences among Ilex species is minimal, with a total repeat sequence number ranging from 1 to 14, concentrated in the length range of 30 to 42 base pairs. The expansion and contraction of chloroplast genome boundaries among Ilex species are relatively stable, with only minor variations observed in individual species. Variations in non-coding regions are more pronounced than those in coding regions, with the variability in the Large Single Copy region (LSC) being the highest, while the variability in the Inverted Repeat region A (IRa) is the lowest. The divergence time among Ilex species was estimated using the MCMC-tree module, revealing the evolutionary relationships among these species, their common ancestors, and their differentiation throughout the evolutionary process. The research findings provide a valuable reference for the systematic study and molecular marker development of Ilex plants.

Long-Term Teleconnections Between Global Circulation Patterns and Interannual Variability of Surface Air Temperature over Kingdom of Saudi Arabia

Surface air temperature (SAT) variability is investigated for advancing our understanding of the climate patterns over the Kingdom of Saudi Arabia (KSA). SAT variability reveals significant warming trends, particularly from 1994 onward, as demonstrated by nonlinear and linear trend analysis. This warming is linked to global climate patterns, which serve as significant indicators for studying the effects of climate change on surface air temperature patterns across the KSA. The empirical orthogonal function (EOF) method is employed for analyzing SAT due to its effectiveness in extracting dominant patterns of variability during the winter (DJF) and summer (JJA) seasons. The first mode (EOF1) for both seasons shows positive variability across the KSA, explaining more than 45% of the variance. The second mode (EOF2) indicates negative variability in central and northern regions. The third mode (EOF3) describes positive variability but with lower variance over time. PC1 is used to describe the physical mechanism of SAT variability and correlations with global sea surface temperature (SST). The physical mechanism shows that the variability in Mediterranean troughs during the winter season and high pressure over the Indian Ocean and central Asia controls SAT variability over the KSA. The correlation coefficients (CCs) were calculated during the winter and summer season between the SAT of the KSA and six teleconnection indices, El Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), Atlantic Meridional Mode (AMM), Pacific Warm Pool (PWP), North Atlantic Oscillation (NAO), and Tropical North Atlantic (TNA) SST for the period from 1994 to 2022. ENSO shifts from positive to negative correlations with SAT from winter to summer. IOD shows a diminished correlation with SAT due to the absence of upper air dynamics. PWP consistently enhances surface warming in both seasons through upper air convergence during both seasons. AMM and NAO have a non-significant impact on SAT; however, TNA contributes warming over central and northern parts during winter and summer seasons. The seasonal SAT variations emphasize the significant role of ENSO, PWP, and TNA across the seasons. The findings of this study can be helpful for seasonal predictability in the KSA.

The Prevalence of Intraoperative Neuromonitoring in Anterior Cervical Discectomy and Fusion: Trends, Variances, and Value Appraisal.

Retrospective cohort study. The purpose of this study was to (1) evaluate recent trends in the use of intraoperative neuromonitoring (IONM) for anterior cervical discectomy and fusion (ACDF) in the United States, (2) assess regional variations in the use of IONM, and (3) assess the association between IONM and clinical outcomes. IONM is frequently used during anterior cervical procedures to mitigate the risk of neurological injury. Prior studies have demonstrated decreasing utilization of IONM in ACDFs. However, no recent studies have re-assessed these trends. Cases of cervical myelopathy and radiculopathy that underwent ACDF from 2011 to 2021 were identified through the PearlDiver Patient Record Database. Rates of IONM were compared based on patient age, gender, income, and region. Complications, 30-day readmissions, and reimbursement rates were also assessed. We identified 285,939 patients undergoing isolated ACDF, with 45,943 (16.1%) of these cases using IONM. There was a significant increase in the use of IONM for ACDFs over the study period (R2=0.87, P<0.001). Significant regional variability was observed in the utility of IONM (Northeast; 21.2%, Midwest; 16.3%, South; 14.7%, West; 14.2%; P<0.001). Younger age and higher patient income were associated with increased utility of IONM (P<0.001). IONM was associated with significantly higher costs but no reduction in rates of postoperative neurological complications (P<0.001 and 0.29, respectively). This study demonstrates a significant increase in IONM utilization during ACDFs over the past decade. Considerable differences exist in IONM use concerning patient demographics, income, and geographic region, with the highest utilization in the Northeast. Notably, despite the association of IONM with over a 20% increase in reimbursement rates, its implementation was not associated with a reduction in rates of neurological complications.

Research on Whether Artificial Intelligence Affects Industrial Carbon Emission Intensity Based on the Perspective of Industrial Structure and Government Intervention

Artificial intelligence serves as the fundamental catalyst for a new wave of technological innovation and industrial transformation. It holds vital importance in reaching carbon reduction targets and the objectives of “carbon peak and neutrality”. This factor contributes significantly to the reduction in carbon emissions in the industrial domain. This article utilizes panel data from 30 provinces in China, covering the years 2013 to 2021, to develop an evaluation framework for assessing the progress of artificial intelligence development. Through the use of double fixed-effect models, mediation effect models, and threshold effect models, the empirical analysis examines the industrial carbon reduction effects of artificial intelligence and its operating mechanisms. Research indicates that the advancement of AI can significantly reduce carbon emission intensity within the industrial sector. This conclusion remains valid following comprehensive robustness tests. Furthermore, there exists temporal and regional variability in AI’s impact on industrial carbon reduction, particularly more pronounced after 2016 and in central and western regions. AI influences carbon emission reduction in China’s industrial sector through the advancement and optimization of industrial structures. Here, the increase in senior-level operations acts as a partial masking effect, while optimization serves as a partial mediator. The relationship between AI and industrial carbon emission intensity is non-linear, being influenced by the threshold of government intervention; minimal intervention weakens AI’s effect on carbon intensity reduction. These findings enhance our understanding of the factors influencing industrial carbon emissions and contribute to AI-related research. They also lay a solid empirical groundwork for promoting carbon emission reduction in the industrial domain via AI. Additionally, the results offer valuable insights for formulating policies aimed at the green transformation of industry.

Did the COVID-19 Pandemic Affect Suicide Rates Differently in Urban and Rural South Korea?

Abstract Background The influence of the COVID-19 pandemic on suicide rates remains a subject of debate. Despite increases in suicidal ideation and attempts reported during the pandemic, several recent meta-analyses have not demonstrated corresponding rises in suicide rates. Given the potential for substantial regional and demographic variability in the psychological consequences of COVID-19-related restrictions, this study explores differential suicide rates in urban versus rural contexts within South Korea subsequent to the pandemic outbreak. Methods This investigation employed age-standardized suicide rates from two periods, 2015-2019 and 2020-2022, across 234 administrative divisions (152 urban, 82 rural). A difference-in-differences approach was utilized to evaluate the pandemic’s impact on suicide rates, segmented by urban and rural classifications. A linear regression model was developed to examine the interaction between location (urban/rural) and time period, controlled for annual variations, perceived stress, and health status within each locale. Results Analysis revealed higher suicide rates in rural areas compared to urban counterparts (β = 1.247, p = 0.003), although no significant changes were observed during the pandemic period itself (β=-0.425, p = 0.682). Furthermore, the interaction between urban/rural status and the pandemic period did not reach statistical significance (p = 0.367). Conclusions The findings indicate no significant contribution of the COVID-19 pandemic to increased suicide rates, irrespective of the urban or rural setting. Further research is warranted to dissect the impact of more direct socioeconomic factors on this dynamic. Key messages • There in no evidence of increased suicide rates during the COVID-19 pandemic in South Korea. • The impact of the COVID-19 pandemic on suicide rates did not significantly different between urban and rural areas.

Enhancing Labor Market Participation of Older Adults: Health and Workplace Adaptations

Abstract Background The labor market dynamics for older adults have significantly shifted due to extended life expectancy and evolving socioeconomic conditions. This study examines the prerequisites for older adults to remain longer in the labor market across various European countries, emphasizing the interplay between health status, workplace adaptations, and economic factors. Methods This cross-sectional study analyzed data from several European surveys focusing on older workers. The methodology included logistic regression to evaluate the impact of health status and workplace adaptations on continued employment among older adults. Data were further stratified by country to assess regional differences in employment patterns for this demographic. Results Preliminary results indicate that older adults with access to workplace adaptations-such as flexible working hours and ergonomic interventions-show a significantly higher likelihood of remaining in the labor market (OR = 2.3, 95% CI 1.8-2.9). Additionally, those reporting good to excellent health were 1.5 times more likely to continue working compared to their peers with poor health outcomes. The results also highlight substantial regional variability, with Scandinavian countries showing higher employment rates among older adults compared to Southern European regions. Conclusions The data strongly support the need for policy interventions that promote health maintenance among older workers and encourage employers to implement adaptive measures. Such strategies are likely to enhance the labor market participation of older adults, contributing to economic stability and reducing the potential strain on social security systems. Innovative public health policies aimed at supporting aging workers are crucial for sustaining workforce productivity in the face of demographic shifts. NordForsk supports the study Sustainable working-life for aging populations in the Nordic-Baltic region, Project No.: 139986. Key messages • Workplace adaptations and good health significantly extend working life among older adults. • Regional differences in employment for older workers highlight the need for tailored public health policies.

Dynamic Changes in and Driving Factors of Soil Organic Carbon in China from 2001 to 2020

It remains unclear what changes have occurred in the distribution pattern of and trend in soil organic carbon (SOC) in China against the background of climate and land use change. Clarifying the dynamic changes in SOC and their driving factors in different regions of China is therefore crucial for assessing the global carbon cycle. In this study, we collected and supplemented a large amount of soil organic carbon density (SOCD) data in China from 2001 to 2020 and extracted data on environmental covariates (ECs) for the corresponding years. A random forest model was used to estimate the SOCD at a depth of 0–20 cm and 0–100 cm in China for the years 2001, 2005, 2010, 2015, and 2020, and we explored the trend of SOCD changes and their key driving factors. The results showed the following: (1) Compared with previous studies, the predictive ability of the 0–100 cm depth model was greatly improved; the coefficient of determination (R2) was 0.61 and Lin’s concordance correlation coefficient (LCCC) was =0.76. (2) From 2001 to 2020, China’s soil organic carbon stocks (SOCS) were 38.11, 39.11, 39.88, 40.16, and 41.12 Pg C for the 0–20 cm depth and 110.49, 112.67, 112.80, 113.06, and 114.96 Pg C for the 0–100 cm depth, respectively. (3) The effects of temperature and precipitation on SOCD in China showed obvious regional variability, and land use changes had mainly positive effects on SOCD in all regions of China, which was related to the large-scale implementation of ecological protection and restoration and the policy of returning farmland to forests and grasslands in China. This study provides strong scientific support for addressing climate change and rationalizing the use of land resources.

The art of music. The representation of musical instruments in the rock art of Zimbabwe

ABSTRACT This article explores the relationship between music and rock art by looking at the occurrence of musical instruments at rock art sites in Zimbabwe. Much of the attention paid to the rich rock art heritage of this country has focused on the documentation of sites, the meaning of the painted and engraved motifs in them and the regional variability they display. Despite some brief mentions, the depiction of musical instruments is still in need of systematic study. This article’s first objective is to compile the information about this type of motifs found in publications and the SARADA archive. Having identified and classified them, it then explores whether musical instruments depicted at rock art sites are connected to altered states of consciousness. The possible relationship between gender and music is also explored and regional differences in the depiction of musical instruments are commented on.

Competing effects of wind and buoyancy forcing on ocean oxygen trends in recent decades

Ocean deoxygenation is becoming a major stressor for marine ecosystems due to anthropogenic climate change. Two major pathways through which climate change affects ocean oxygen are changes in wind fields and changes in air-sea heat and freshwater fluxes. Here, we use a global ocean biogeochemistry model run under historical atmospheric forcing to show that wind stress is the dominant driver of year-to-year oxygen variability in most ocean regions. Only in areas of water mass formation do air-sea heat and freshwater fluxes dominate year-to-year oxygen dynamics. The deoxygenation since the late 1960s has been driven mainly by changes in air-sea heat and freshwater fluxes. Part of this deoxygenation has been mitigated by wind-driven increases in ventilation and interior oxygen supply, mainly in the Southern Ocean. The predicted slowdown in wind stress intensification, combined with continued ocean warming, may therefore greatly accelerate ocean deoxygenation in the coming decades. The fact that the model used here, along with many state-of-the-art forced ocean models, underestimates recent ocean deoxygenation indicates the need to use forcing fields that better represent pre-industrial conditions during their spin-up.

Grid-Based Precipitation Quantile Estimation Considering Homogeneity Using ERA5-Land Data for the Korean Peninsula

In this study, a grid-based precipitation quantile was estimated using long-term reanalysis precipitation data, considering the homogeneity of the annual maximum series (AMS) for the Korean Peninsula. For regions where significant changes in homogeneity were observed, the precipitation quantile was estimated using only the AMS from after the change point, and these results were compared with those from the original AMS. The examination of homogeneity revealed a significant increasing trend in homogeneity variability in the southeastern region of Korea. This change was particularly pronounced in the location parameter of the Gumbel distribution, resulting in an improved model fit. The change in precipitation quantile was most noticeable for a 2-year return period with a 36 h duration, with an average increase of approximately 11.5%. The results obtained from this study are anticipated to offer crucial foundational data for the design of hydraulic structures in regions with insufficient long-term ground observation data.

Analyzing Perception of Administrators and Teachers on Management of Schools by Values (Kızıltepe Case)

Purpose: The purpose of this study is to analyze the perception of administrators and teachers related to the management of schools according to values in terms of variables of gender, age, seniority, grade, school type, school region and profession type. Design/Methodology/Approach: The research was conducted using mixed method. The population consists of 3338 administrators and teachers working in public and private primary, secondary and high schools in Kızıltepe district of Mardin in the 2021-2022 academic year. The sample of the quantitative part consists of 340 participants determined by simple random sampling technique, while the study group of the qualitative part consists of 10 administrators and 10 teachers selected by maximum diversity technique. The data for the quantitative dimension was collected using the "Management by Values Scale" developed by Yılmaz (2006). To collect the data of the qualitative dimension, a semi-structured interview form developed by the researcher and consisting of six questions was used. T-test was used for the variables of gender, profession type, school region and school type and ANOVA was used for the variables of age, seniority and grade. Tukey Test was used to determine the source of the values which have significant differences. Content analysis was used for qualitative data. Findings: As a result of the analysis of both qualitative and quantitative data, it has been found that the participants have a positive perception about the management of schools according to values. However, no significant difference has been found between the groups according to the variables of gender, age, grade, school type, school region and type of profession. A significant difference has been found between the groups with 1-5 years and 11-15 years of working experience in the seniority variable. Highlights: According to the data obtained from the research and also the literature review, it has been concluded that teachers and administrators have a positive perception that schools are managed according to values. There should be programs to educate managers since there is a substantial need for this based on this research.

Unraveling the paradox of soil erosion and conservation: Insights from China

Analyzing the drivers of soil conservation (SC) service is crucial for ecosystem restoration. However, previous studies often overlook the relationship between soil erosion and SC. In this study, we applied the revised universal soil loss equation (RUSLE) model to analyze the spatiotemporal trends and driving forces of SC service across China from 1990 to 2019. The results indicate that both soil erosion and SC service have exhibited overall increasing trends over the past 30 years. The average SC amount increased 21.3 % from 1990s to 2010s. The average total SC amount and capacity were 229.95 billion t a−1 and 242.91 t ha−1 a−1, respectively. Spatial analysis reveals significant regional variability, with 26.6 % of the land area experiencing fluctuations in SC, these regions contribute to 87.5 % of the total SC amount in the country. We developed a classification system with six patterns to assess the impacts of climate change and human activities on SC. Patterns dominated by climate change exhibit consistent trends in soil erosion and SC service, whereas those dominated by human activities show opposite trends. When climate change and human activities interact, the relationship becomes more complex. Climate change has the most significant influence on SC alterations, affecting 77.1 % of areas with SC changes, while human activities also play a notable role. Although regions primarily impacted by human activities account for only 1.8 % of the total area, they represent 45,200 km2. The remaining 21.1 % of areas are influenced by both climate change and human activities, highlighting the importance of human activities in 22.9 % of areas with SC changes. These findings underscore the synergistic effects of climate change and human activities on SC in China, providing a foundation for future research and the development of targeted SC strategies.

Advancing Subseasonal Surface Air Temperature and Heat Wave Prediction Skill in China by Incorporating Scale Interaction in a Deep Learning Model

AbstractAccurate subseasonal predictions of high surface air temperature (SAT) and heat wave events 10–30 days in advance are crucial for mitigating the risks of extreme weather; however, they pose a challenge for current operational models. In this study, we trained a convolutional neural network (CNN)‐based deep learning model to exploit the modulations in China's SAT by precursor signals across different timescales to improve predictions of future SAT and heat wave events. This CNN model demonstrated superior capability in capturing the evolution of SAT anomalies and the occurrence of heat wave events with forecast lead times beyond 20 days, compared with that of the operational models of the China Meteorological Administration and European Centre for Medium‐Range Weather Forecasts. Explainability analysis highlighted that subseasonal SAT predictability in China is driven primarily by large‐scale intraseasonal perturbations from both lower‐ and higher‐latitude regions of Eurasia and interannual variability.

Impact of Solar Radiation Management on Andean glacier-wide surface mass balance

Solar Radiation Management (SRM) is a climate intervention strategy aimed at mitigating global warming by reducing incoming solar radiation. We investigate the potential influence of SRM on Andean glacier-wide surface mass balance, as glaciers are crucial for downstream ecological functions along the west coast of South America. We numerically simulate the surface mass balance response of thousands of glaciers to SRM and other climate change scenarios throughout the 21st century. Results indicate Pan-Andean negative mass balance, irrespective of the scenario or glacier-climate regimes. However, SRM tends to modify interannual variability and temperature sensitivity in several regions. Our findings also suggest that if SRM had been implemented in the late 1980’s, it would have been effective in avoiding the negative trajectory seen today. The Andes feature nearly all mountain hydroclimatic regimes, representing a globally relevant example of SRM impacts. These findings emphasize the urgency of drastic emissions reduction.

High-Resolution Wind Speed Estimates for the Eastern Mediterranean Basin: A Statistical Comparison Against Coastal Meteorological Observations

Wind speed (and direction) estimated from numerical weather prediction (NWP) models is essential to wind energy applications, especially in the absence of reliable fine scale spatio-temporal wind information. This study evaluates four high-resolution wind speed numerical datasets (UERRA MESCAN-SURFEX, CERRA, COSMO-REA6, and NEWA) against in situ observations from coastal meteorological stations in the eastern Mediterranean basin. The evaluation is based on statistical comparisons of long-term wind speed data from 2009 to 2018 and involves an in-depth statistical comparison as well as a preliminary wind power density assessment at or near the meteorological station locations. The results show that while all datasets provide valuable insights into regional wind variability, there are notable differences in model performance. COSMO-REA6 and UERRA exhibit higher variability in wind speed but tend to underestimate extreme values, particularly in the southern coastal areas, whereas CERRA and NEWA provided closer fits to observed wind speeds, with CERRA showing the highest correlation at most stations. NEWA data, where available, overestimate average wind speeds but capture extreme values well. The comparison reveals that while all datasets provide valuable insights into the spatial and temporal variability of wind resources, their performance varies by location and season, emphasizing the need for the careful selection and potential calibration of these models for accurate wind energy assessments. The study provides essential groundwork for leveraging these datasets in planning and optimizing offshore wind energy projects, contributing to the region’s transition to renewable energy sources.

Analysis of Alzheimer's Disease-Related Mortality Rates Among the Elderly Populations Across the United States: An Analysis of Demographic and Regional Disparities from 1999 to 2020.

Alzheimer's Disease (AD) is the leading cause of dementia and a significant public health concern, characterized by high incidence, mortality, and economic burden. This study analyzes the mortality patterns and demographic disparities in Alzheimer's disease-related deaths among the elderly population in the United States from 1999 through 2020. Alzheimer's disease mortality data for individuals 65 and older were obtained from the CDC WONDER database, utilizing ICD-10 codes G30.0, G30.1, G30.8, and G30.9 for identification. Demographic and regional variables included age, gender, race/ethnicity, place of death, urban- rural status, and geographic region. Crude death rates (CR) and age-adjusted mortality rates (AAMR) per 100,000 individuals were calculated. Joinpoint Regression Program 5.0.2 was used to analyze trends, calculating Annual Percentage Changes (APCs) and Average Annual Percentage Changes (AAPCs). From 1999 to 2020, 1,852,432 deaths were attributed to AD among individuals aged 65 and older. The AAMR increased from 128.8 in 1999 to 254.3 in 2020, with an AAPC of 2.99% (95% CI = 2.61-3.48). The age-adjusted mortality rate (AAMR) was higher in females (218.5) than in males (163.5). Among racial and ethnic groups, non-Hispanic whites had the highest AAMR, followed by Non-Hispanic Blacks and Hispanics. Regionally, the West reported the highest AAMR, while the Northeast recorded the lowest. Most deaths occurred in nursing homes (57.3%), with a significant portion also occurring at decedents' homes (22.4%). AD mortality rates in the U.S. have risen significantly, with notable disparities across age, gender, race, and geographic regions. These findings highlight the need for targeted interventions and research to address the growing burden of AD, particularly among the most affected demographic groups.

Shock wave propagation in a real gas with or without gravitational field in the presence of magnetic field and monochromatic radiation via group invariance method

PurposeThis article aims to find the similarity solutions for the one-dimensional motion of spherical symmetric shock wave in non-ideal gas influenced by the azimuthal magnetic field and monochromatic radiation in the presence or absence of gravitational field. This paper also aims to study the effects of physical parameters on the strength of shock wave, and on the flow variables in the flow-field region behind the shock front.Design/methodology/approachThe Roche model is used to describe the gravitational field effects due to a massive nucleus at the point of symmetry. To derive the similarity solutions, the Lie group symmetry method has been used. Also, the numerical solutions to the present problem are obtained by using Rung–Kutta method of the fourth order with the use of Mathematica software. The effects of variation in the parameter of non-idealness of the gas, the gravitation parameter, the strength of the ambient magnetic field and the adiabatic index of the gas on the shock wave, and on the flow variables is discussed. A comparative study between with and without gravitational field is also, made.FindingsFor different choices of the arbitrary constants that appeared in the solution of infinitesimal generators, we have obtained seven distinct cases of similarity solutions. In the absence of the gravitational field, the similarity solution exists to the power and exponential law shock paths, but in the presence of gravitational field, the similarity solution exists to the power law shock path case only. In the absence of gravitational field, the shock strength is enhanced in the exponential law shock path case in comparison to the power law shock path case. It is found that the shock wave decays with an increase in the value of the adiabatic exponent, the strength of magnetic field, non-idealness of the gas or gravitational parameter.Research limitations/implicationsThe consideration of medium under the influence of gravitational field due to a heavy nucleus at the center and presence of magnetic field decrease the shock strength. This result may be helpful in designing space vehicle and jet engine.Practical implicationsThe result of the present study may be used in the analysis of data from the measurements by space craft in the solar wind and in neighborhood of the Earth’s magnetosphere.Social implicationsThe obtained results may be used for mankind.Originality/valueThe study of spherical shock wave propagation influenced by monochromatic radiation and azimuthal magnetic field in a non-ideal gas with or without gravitational field has yet to be discussed by any authors by using the Lie group symmetry method. In this article, we have discussed all possible cases of similarity solutions using the Lie group symmetry method, which is not studied by anyone as known to us.

Debatable issues of coding chronic forms of ischemic heart disease as the primary cause of death

Aim: to examine the opinions of healthcare professionals on using codes from the ICD-10 group chronic ischemic heart disease (CIHD) (I25.0, I25.1, I25.8, I25.9) as the primary cause of death and discuss the results in the context of comparing with regional variability of standardized mortality ratio (SMR) from different forms of CIHD.Materials and methods. A one-stage study was conducted. This article describes the results of a survey of 366 medical workers (cardiologists, internists/general practitioners/family doctors, pathologists, public health and healthcare specialists, paramedics) from 47 subjects of the Russian Federation who fill out a medical death certificate (MDS) more often than 2–3 times a month. In addition, SMR from coronary heart disease were determined based on a brief nomenclature of causes of death of Rosstat in 82 regions of the Russian Federation for 2022.Results. 80.1 % of respondents expressed the opinion that I25.0, I25.1, I25.8, I25.9 are necessary for coding causes of death, but half of those surveyed do not see any differences in them. At the same time, respondents admit the possibility of using these CIHD codes as the primary cause of death without ante-mortem and pathological verification. The relatively small coefficient of variation of SMR overall from CIHD (34.19 per 100,000 population) is associated with high values from its individual forms: the coefficient of variation of average regional SMRs ranged from 62 % for code I25.1 to 174 % for code I25.0.Conclusions. The results of this study indicate a variable attitude of specialists filling out MSD towards choosing ICD-10 codes from the CIHD group, leading to significant interregional differences in CIHD mortality rates. It is necessary to develop unified recommendations describing situations in which codes from the CIHD group can be considered the primary (main) cause of death.

Understanding the Zonal Variability in Projections of Sahel Precipitation

AbstractThe uncertainty in precipitation projections across the Sahel has persisted across generations of climate models. Many projections show a zonal dipole in the sign of precipitation change, with wetting across the Central Sahel and drying across the Western Sahel. We analyze the outputs from an ensemble of current climate models to explain why some produce this dipole and understand the inter‐model variability in the transition region for these models. Models projecting the dipole tend to shift the Atlantic Intertropical Convergence Zone (ITCZ) to the south, while models that do not tend to shift the ITCZ to the north. We find that the strong relationship between the change in Sahel precipitation and surface temperature‐based indices is highly driven by the non‐dipole models. These indices do not explain most of the variance in where models transition. This suggests that understanding zonal variability in Sahel precipitation change must go beyond these temperature‐based analysis.

Hydrodynamic Performance Improvement of a Tirhandil Yacht by Stern Form Modifications

This paper presents a comprehensive investigation to improve the hydrodynamic performance of a Tirhandil hull form by modification efforts on the stern region. The form improvement approach combines computational fluid dynamics (CFD) methods with computer-aided design (CAD) systems. The design process for the reference and modified models was carried out by using CAD systems. The hydrodynamic characteristics of the reference hull form were evaluated by employing CFD methods and it was determined that form improvements should be concentrated on the stern region. The modification process was conducted by considering constraints on the design variables in the stern region and the main dimensions of the reference model. A grid independence study was performed to evaluate various grid structures to determine the optimal mesh configuration for the numerical analyses. The SST k-Omega turbulence model was used for the numerical analyses to simulate turbulence structure around the hull form. Achieving around a 13.4% reduction in the total resistance coefficient, the modified model also exhibited decreased wave amplitudes, smoother wave transitions, and a significant reduction or cancellation of shoulder and stern waves.