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This study assessed trends in age-standardized incidence (ASIR), prevalence (ASPR), and mortality rates (ASMR) per 100,000 population for asthma, Type 1 Diabetes Mellitus (T1DM), Inflammatory Bowel Disease (IBD), Multiple Sclerosis (MS), Psoriasis, and Rheumatoid Arthritis (RA) in China from 1990 to 2021 and projected ASIR trends through 2046. Data were obtained from the Global Burden of Disease (GBD) 2021 study. Trends in ASIR, ASPR, and ASMR were analyzed using Joinpoint regression to calculate annual percentage change (APC) and average APC (AAPC). Bayesian age–period–cohort (BAPC) modeling was applied to project future ASIR trends. In 2021, asthma had the highest ASIR (364.17/100,000), followed by psoriasis (59.70/100,000) and RA (13.70/100,000), while MS (0.16/100,000) and IBD (1.40/100,000) were the least common. Asthma exhibited significant declines in ASIR (-1.23% AAPC), ASPR (-1.49%), and ASMR (-4.4%). Conversely, T1DM showed rising ASIR (+ 1.16%) and ASPR (+ 1.15%) alongside declining ASMR (-2.62%). Psoriasis (+ 0.74%) and IBD (+ 2.09%) also showed rising ASIR. Gender differences were notable, with greater T1DM ASIR increases in males and more significant asthma improvements in females. By 2046, the ASIR of T1DM, psoriasis, and RA is projected to reach 5.8, 80.9, and 15.54 per 100,000, respectively, while asthma is expected to decline to 330.98 per 100,000. The rising ASIR and ASPR for most autoimmune diseases in China contrast with declining ASMR, highlighting the dual challenge of managing increasing disease burdens while sustaining reductions in mortality. Targeted prevention and management strategies are essential to address these evolving public health needs. [ABSTRACT FROM AUTHOR]

The inherent model uncertainty in precipitation projections is found to be more dominant over tropical regions thereby reducing the reliability of using them in climate change impact assessment studies. To address such issues, a subset of well performing global climate models (GCMs) can provide narrow range of possible future outcomes, which can be helpful in formulating mitigation and adaptation strategies that are more targeted and efficient. In this study, climate models are selected based on their performance in simulating relative humidity and vertical velocity since these variables play an important role in precipitation simulation and significantly contribute toward the intermodel spread. The models are evaluated by using various statistical performance measures and ranked using multi‐criteria decision‐making approaches. Finally, based on Jenks natural breaks optimization algorithm, subset of GCMs consisting of ACCESS1.0, ACCESS1.3 and INM‐CM4 models, are considered as the best possible subset for precipitation simulation over tropical land regions. Two observational precipitation datasets are further considered to investigate the effectiveness of the proposed framework. The proposed methodology is validated to be effective in identifying the best climate models since the resulting subset is capable of both capturing observed precipitation and minimizing the uncertainty in future projections. Hence, this methodology can be utilized further for performance evaluation of GCMs focusing different geography and climatic drivers. [ABSTRACT FROM AUTHOR]

Background: Age-related macular degeneration (AMD) is a leading cause of blindness and low vision worldwide. This study examines the global burden and trends in AMD-related low vision and blindness from 1990 to 2021, with projections through 2050. Methods: Data were obtained from the 2021 Global Burden of Disease (GBD 2021) study, covering 204 countries and regions. Key metrics, including the prevalent case numbers, annual disability-adjusted life years (DALYs), age-standardized prevalence rates (ASPR), and age-standardized DALY rates (ASDALYR), specific to low vision and blindness due to AMD, were calculated per 100,000 population. Trend analysis used the estimated annual percentage change (EAPC) method, and K-means clustering identified regions with similar burdens and trends. Autoregressive Integrated Moving Average(ARIMA) and Exponential Smoothing(ES) models provided future projections. Results: Globally, the total number of prevalent cases and DALYs has substantially increased. The number of prevalent cases of low vision and blindness due to AMD increased from 3,640,180 (95% UI: 3,037,098 − 4,353,902) in 1990 to 8,057,521 (95% UI: 6,705,284-9,823,238) in 2021. DALYs increased from 302,902 (95% UI: 206,475 − 421,952) in 1990 to 578,020 (95% UI: 401,241–797,570) in 2021. From 1990 to 2021, both the ASPR and ASDALYR for AMD-related low vision and blindness showed a downward trend. The ASPR was 94 (95% UI: 78.32-114.42) per 100,000 population, with an EAPC of -0.26 (95% CI: -0.31 to -0.22), and the ASDALYR was 6.78 (95% UI: 4.7–9.32) per 100,000 population, with an EAPC of -0.94 (95% CI: -1.01 to -0.88). The disease burden of AMD-related low vision and blindness increases with age, and the burden for female patients is slightly higher than for males. Regional stratification by the Socio-Demographic Index (SDI) shows that the burden of AMD-related low vision and blindness in areas with low SDI is higher than in areas with high SDI. From 1990 to 2021, notable increases in ASPR and ASDALYR were observed mainly in the southern and central regions of sub-Saharan Africa. Moreover, the increases in prevalence and DALYs vary by region, country, and level of socioeconomic development. The ARIMA model predicts that by 2050, the number of prevalent cases of low vision and blindness due to AMD will reach 13,880,610(95% CI: 9,805,575–17,955,645), and the DALYs will be 764,731(95% CI: 683,535–845,926). The ES model predicts that by 2050, the number of prevalent cases of AMD-related low vision and blindness will reach 9,323,124(95% CI: 5,222,474–13,423,774), and the DALYs will be 641,451 (95% CI: 383,588–899,318). Conclusion: This study indicates that between 1990 and 2021, the global prevalent cases and DALYs caused by AMD-related low vision and blindness have increased over the past three decades, correlating with factors such as age, gender, socioeconomic status, and geographical location. Predictive models indicate that as the population ages, the number of patients with low vision and blindness due to AMD, along with associated DALYs, will continue to rise. By 2050, it is expected that over 9 million people worldwide will be affected by AMD-related vision loss, with women being particularly impacted. These findings can provide data support for public health planning, resource allocation, and the formulation of medical policies, ensuring an effective response to the challenges posed by the future increase in AMD-related low vision and blindness. [ABSTRACT FROM AUTHOR]

The long‐term incidence trends of 32 cancers in China remained unclear. Cancer statistics for young population were often presented in aggregate, masking important heterogeneity. We aimed to assess the incidence trends of 32 cancers in China from 1983 to 2032, stratified by sex and age groups. Data on cancer incidence from 1983 to 2017 were extracted from Cancer Incidence in Five Continents Volumes VI–XII. The age‐period‐cohort model was utilized to assess age and birth cohort effects on the temporal trends of 32 cancers in China, while the Bayesian age‐period‐cohort model was utilized to project future trends from 2018 to 2032. An increase in cohort effects is observed in some cancers such as thyroid and kidney cancers. Eight of the 12 obesity‐related cancers may rise in the 0–14 age group, and nine in the 15–39 age group from 2013 to 2032. Liver and stomach cancers show an increasing trend among the younger population, contrasting with the observed declining trend in the middle‐aged population. There has been a significant rise in the proportions of cervical cancer among females aged 40–64 (4.3%–19.1%), and prostate cancer among males aged 65+ (1.1%–11.8%) from 1983 to 2032. Cancer spectrum in China is shifting toward that in developed countries. Incidence rates of most cancers across different age groups may increase in recent cohorts. It is essential to insist effective preventive interventions, and promote healthier lifestyles, such as reducing obesity, especially among younger population. [ABSTRACT FROM AUTHOR]

The goal of this research is to present the results of a detailed analysis of detected and projected temperature changes in Montenegro. A total of 10 temperature parameters from 18 meteorological stations were used. Initially, an analysis of temperature changes during the instrumental period (1961–2020) was conducted, followed by the results of high‐resolution (12.5 km) bias‐corrected projections from the regional ALADIN, REMO and CCLM4 models for the period 2021–2100, according to the RCP4.5 and RCP8.5 scenarios (representative concentration pathways). The simple difference method and trend method were employed for research purposes. Compared with the period 1961–1990, the highest temperature increase during 1991–2020 is observed in summer (TSu), while the rates of increase were slower in spring, winter and autumn (TSp, TW and TA). The average annual maximum temperature (TYx) registered a higher increase compared with the average minimum (TYn). Frosty days (FD) decreased, while the number of summer and tropical days (SU and TD) increased. The projection results indicate that the period 2021–2050 is expected to be warmer, the period 2051–2080 even warmer, and the period 2081–2100 is expected to be the warmest. In the last analysed period (2081–2100), according to the RCP8.5 scenario, the average TSu is expected to be higher by 3.7–4.6°C (CCLM4), 4.1–4.7°C (ALADIN) and 4.7–5.8°C (REMO), with an anticipated increase in TW ranging between 3.3–4.5°C (ALADIN), 3.6–5.4°C (CCLM4) and 3.4–5.6°C (REMO). In the period 2021–2100, according to the RCP4.5 scenario, the expected average trend values for TYx (TYn) are expected to be (°C/decade) 0.24 (0.26), 0.16 (0.12) and 0.20 (0.23) for the ALADIN, REMO and CCLM4 models, respectively, and according to the RCP8.5 scenario, 0.47 (0.52), 0.63 (0.57) and 0.51 (0.53), respectively. These findings have implications for planning mitigation and adaptation measures to address climate change, particularly in strategic economic sectors such as tourism, agriculture and water management in Montenegro. [ABSTRACT FROM AUTHOR]

The main aim of this paper is to develop a new algorithm for computing a nonnegative low multi‐rank tensor approximation for a nonnegative tensor. In the literature, there are several nonnegative tensor factorizations or decompositions, and their approaches are to enforce the nonnegativity constraints in the factors of tensor factorizations or decompositions. In this paper, we study nonnegativity constraints in tensor entries directly, and a low rank approximation for the transformed tensor by using discrete Fourier transformation matrix, discrete cosine transformation matrix, or unitary transformation matrix. This strategy is particularly useful in imaging science as nonnegative pixels appear in tensor entries and a low rank structure can be obtained in the transformation domain. We propose an alternating projections algorithm for computing such a nonnegative low multi‐rank tensor approximation. The convergence of the proposed projection method is established. Numerical examples for multidimensional images are presented to demonstrate that the performance of the proposed method is better than that of nonnegative low Tucker rank tensor approximation and the other nonnegative tensor factorizations and decompositions. [ABSTRACT FROM AUTHOR]

Let M and N be nests on separable Hilbert space. If the two nest algebras are distance less than 1 ( d (T (M) , T (N)) < 1 ), then the nests are distance less than 1 ( d (M , N) < 1 ). If the nests are distance less than 1 apart, then the nest algebras are similar, i.e. there is an invertible S such that S M = N , so that S T (M) S - 1 = T (N) . However there are examples of nests closer than 1 for which the nest algebras are distance 1 apart. [ABSTRACT FROM AUTHOR]

Transforming the food system while addressing climate change requires proactive measures based on quantitative projections of anticipated future conditions. A key component of the food system that must be considered during this transformation is food safety, which is the focus of this paper. Milk safety has been selected as a case study. Future milk contamination levels in Europe, in terms of total bacterial counts, are evaluated under various climate change scenarios. Projections from multiple climate models are integrated into a data-driven milk contamination model, validated using data from Malta, Spain, and Belgium. The modeling framework accounts for variability among dairy farms and the inherent uncertainties in climate projections. Results are presented through geographical heatmaps, highlighting coastal and southern areas such as Portugal, Western Spain, Southern Italy, and Western France as regions expected to face the highest bacterial counts. The analysis underlines the significant roles of humidity and wind speed, alongside temperature. It also examines compliance with the regulatory threshold for raw milk, revealing an increased frequency of summer weeks exceeding the threshold of 100,000 colony-forming units. Based on this analysis, regions are classified into low-risk, high-risk, and emerging-risk categories. This classification can guide the selection of farm strategies aimed at meeting future food safety standards. By informing these decisions with the anticipated impacts of climate change, the food system can be future-proofed. [ABSTRACT FROM AUTHOR]

Background: Pancreatitis is a significant global health concern with rising incidence, complex management, and substantial mortality. This study aimed to assess global and regional trends in pancreatitis from 1990 to 2021 and project future trends to 2050 using data from the Global Burden of Disease (GBD) Study 2021. Methods: We analyzed GBD 2021 data to evaluate age-standardized incidence (ASIR), mortality (ASMR), and disability-adjusted life years (DALYs) rates of pancreatitis. Regional trends, gender disparities, and correlations with the Socio-demographic Index (SDI) were examined. Key risk factors, including alcohol consumption, smoking, and metabolic disorders such as hyperlipidemia, were extracted and evaluated. A Bayesian age-period-cohort model (BAPC) was used for future projections. Results: From 1990 to 2021, global pancreatitis cases increased from 1.73 million to 2.75 million, representing a rise of 59%. Despite this, ASIR decreased slightly from 37.62 to 32.81 per 100,000, a 12.8% reduction. Deaths rose from 68,490 to 122,416, an increase of 78.7%, while ASMR decreased from 1.69 to 1.45 per 100,000, a reduction of 14.2%. DALYs increased from 2.58 million to 4.10 million (59%). Significant regional variations were found, with Eastern Europe showing the highest ASIR, ASMR, and DALY rates. Projections indicate continued declines in ASIR, ASMR, and DALYs through 2050. Conclusions: While global age-standardized rates of pancreatitis have declined, significant regional and socioeconomic disparities persist. Targeted prevention efforts, particularly in high-burden areas like Eastern Europe, and addressing modifiable risk factors such as alcohol use are crucial for reducing the future burden of pancreatitis. [ABSTRACT FROM AUTHOR]

Background: This study aims to analyze the historical trends of inflammatory bowel disease (IBD) burden in the elderly from 1990 to 2021 and forecast future trends up to 2051. Methods: Data from the Global Burden of Disease Study 2021 were utilized. Age-standardized rates (ASR) for incidence, prevalence, mortality, and disability-adjusted life years (DALYs) were calculated. Estimated annual percentage changes (EAPCs) were computed to quantify temporal trends. A Bayesian Age-Period-Cohort model was employed to project future trends. Results: From 1990 to 2021, the global number of elderly IBD increased from 573,500 to 1,278,190. The age-standardized incidence rate (ASIR) rose from 8.01 to 8.77 per 100,000, while the age-standardized prevalence rate (ASPR) slightly decreased from 118.14 to 117.29 per 100,000. Death number increased from 14,400 to 33,490, but the age-standardized mortality rate decreased from 3.21 to 2.84 per 100,000. DALYs increased from 324,100 to 683,750, with the age-standardized DALYs rate declining from 68.78 to 60.88 per 100,000. Significant geographical variations were observed, with high Socio-demographic Index regions showing the highest burden. Projections suggest that by 2051, elderly IBD prevalence number may reach 2,316,000, with ASIR and ASPR potentially rising after 2035 and 2042, respectively. Deaths and DALYs are projected to increase to 75,000 and 1,401,000 respectively, despite continued declines in ASRs. Conclusion: The absolute burden of IBD in the elderly population is projected to increase substantially by 2051, despite decreasing ASRs. These findings underscore the need for tailored healthcare strategies and resource allocation to address the growing challenge of elderly IBD globally. [ABSTRACT FROM AUTHOR]

We summarise the contributions to the Topical Collection on quality of climate information for adaptation decision support. Based on these contributions, we draw some further lessons for the development of high-quality climate information and services, bridging between a “credibility-first” paradigm (exemplified by top-down information provision from systematic downscaling or impact projections) and a “salience-first” paradigm (exemplified by user-led tailored information products or storylines) by looking to identify their respective strengths and use cases. We emphasise that a more nuanced collective understanding of the dimensions of information quality in climate information and services would be beneficial to users and providers and ultimately support more confident and effective climate adaptation decisions and policy-making. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to assess the prevalence of mild and moderate hearing loss spanning three decades, from 1990 to 2019, and to project the anticipated trends from 2020 to 2030 among adolescents, young adults, middle-aged adults, and age-standardised groups in Malaysia. Methods: This study involved secondary data analysis of mild and moderate hearing loss prevalence over 30 years among the Malaysian population aged 15–19, 25–29, 35–39, 45–49, and age-standardised groups. Subsequently, three time-series models were evaluated and the best models with the minimal Mean Absolute Percentage Error (MAPE) and Root Mean Squared Error (RMSE) were selected for projecting the prevalence of hearing loss until 2030. Results: A relatively stable trend of mild hearing loss prevalence and gradual decline of moderate hearing loss were observed across all age groups throughout the study period. The prevalence of mild hearing loss was consistently higher than moderate hearing loss across all age groups, with its prevalence increasing with age. The projected prevalence of hearing loss exhibits a gradual declining trend in the future for all age groups, except for mild hearing loss for the 15-19-year-old group. Conclusion: Over the past 30 years, there has been a relatively stable and slightly declining trend in the prevalence of mild and moderate hearing loss among the Malaysian population, respectively with projections showing a slow reduction in the future. These findings highlighted the need for identifying the best intervention and vulnerable age groups, directing increased resources and prioritization towards them. [ABSTRACT FROM AUTHOR]

Aims: The global historical and projected health impacts of the escalating burden of obesity on young adults, who are particularly susceptible to weight gain during transitional life stages, remain insufficiently understood. Materials and Methods: Using data from the Global Burden of Disease Study 2019, we analysed the disability‐adjusted life‐years (DALYs) and deaths attributable to high body mass index (BMI) among young adults aged 20–44 years globally and by age, sex, year, location and disease between 1990 and 2019. Future projections until 2050 were further assessed. Results: The global burden for young adults attributable to high BMI more than doubled from 1990 to 2019, reaching 24,509.8 (95% uncertainty interval [UI] 20,191.8–28,966.0) thousand for DALYs and 321.9 (258.3–384.2) thousand for deaths. Males had a higher burden and faster increase than females. The burden escalated with advancing age. From 1990 to 2019, regions with middle Socio‐demographic Index (SDI) replaced regions with high‐middle SDI to have the highest age‐standardized rates of DALYs and deaths, while regions with low‐middle SDI witnessed the largest rise. Stroke, ischaemic heart disease and diabetes mellitus were consistently the top three causes of high BMI‐related burden, together accounting for 74.7% (70.8–78.4) for DALYs and 81.2% (77.6–84.2) for deaths in 2019. By 2050, the age‐standardized rates of DALYs due to high BMI tripled that in 1990, with the corresponding rates for deaths expected to double. Among the 10 most populous countries, India was projected to have the highest rates and the fastest increase in both DALYs and deaths by 2050. Conclusions: The escalating disease burden attributable to high BMI in young adults, marked by notable demographic and geographic variations, highlights the urgent need for tailored public health interventions on weight management during young adulthood. [ABSTRACT FROM AUTHOR]

Abstract Background Age-related macular degeneration (AMD) is a leading cause of blindness and low vision worldwide. This study examines the global burden and trends in AMD-related low vision and blindness from 1990 to 2021, with projections through 2050. Methods Data were obtained from the 2021 Global Burden of Disease (GBD 2021) study, covering 204 countries and regions. Key metrics, including the prevalent case numbers, annual disability-adjusted life years (DALYs), age-standardized prevalence rates (ASPR), and age-standardized DALY rates (ASDALYR), specific to low vision and blindness due to AMD, were calculated per 100,000 population. Trend analysis used the estimated annual percentage change (EAPC) method, and K-means clustering identified regions with similar burdens and trends. Autoregressive Integrated Moving Average(ARIMA) and Exponential Smoothing(ES) models provided future projections. Results Globally, the total number of prevalent cases and DALYs has substantially increased. The number of prevalent cases of low vision and blindness due to AMD increased from 3,640,180 (95% UI: 3,037,098 − 4,353,902) in 1990 to 8,057,521 (95% UI: 6,705,284-9,823,238) in 2021. DALYs increased from 302,902 (95% UI: 206,475 − 421,952) in 1990 to 578,020 (95% UI: 401,241–797,570) in 2021. From 1990 to 2021, both the ASPR and ASDALYR for AMD-related low vision and blindness showed a downward trend. The ASPR was 94 (95% UI: 78.32-114.42) per 100,000 population, with an EAPC of -0.26 (95% CI: -0.31 to -0.22), and the ASDALYR was 6.78 (95% UI: 4.7–9.32) per 100,000 population, with an EAPC of -0.94 (95% CI: -1.01 to -0.88). The disease burden of AMD-related low vision and blindness increases with age, and the burden for female patients is slightly higher than for males. Regional stratification by the Socio-Demographic Index (SDI) shows that the burden of AMD-related low vision and blindness in areas with low SDI is higher than in areas with high SDI. From 1990 to 2021, notable increases in ASPR and ASDALYR were observed mainly in the southern and central regions of sub-Saharan Africa. Moreover, the increases in prevalence and DALYs vary by region, country, and level of socioeconomic development. The ARIMA model predicts that by 2050, the number of prevalent cases of low vision and blindness due to AMD will reach 13,880,610(95% CI: 9,805,575–17,955,645), and the DALYs will be 764,731(95% CI: 683,535–845,926). The ES model predicts that by 2050, the number of prevalent cases of AMD-related low vision and blindness will reach 9,323,124(95% CI: 5,222,474–13,423,774), and the DALYs will be 641,451 (95% CI: 383,588–899,318). Conclusion This study indicates that between 1990 and 2021, the global prevalent cases and DALYs caused by AMD-related low vision and blindness have increased over the past three decades, correlating with factors such as age, gender, socioeconomic status, and geographical location. Predictive models indicate that as the population ages, the number of patients with low vision and blindness due to AMD, along with associated DALYs, will continue to rise. By 2050, it is expected that over 9 million people worldwide will be affected by AMD-related vision loss, with women being particularly impacted. These findings can provide data support for public health planning, resource allocation, and the formulation of medical policies, ensuring an effective response to the challenges posed by the future increase in AMD-related low vision and blindness.

The mass variation effect of the test particle is studied in the collinear restricted four-body configuration with the assumption that the shapes of the three primary bodies are triaxial. It is assumed that these three primary bodies are placed in consecutive order on the abscissa axis and their axes are always parallel to the synodic ones. We also consider that the central body have solar radiation effect and whole the system is affected by Coriolis as well as centrifugal forces. Under these assumptions and using Jeans’ law, the equations of motion and quasi-Jacobian integral are determined. And hence the locations of parking points, Poincaré surfaces of section, surfaces with projection and basins of attractions are illustrated for the various values of the variation parameters .$\mu, \phi_1 , \phi_2 ,T_{11} , T_{21} , T_{31} , T_{12} , T_{22} , T_{32} , T_{13} , T_{23} , T_{33}$. Further-more the stability of the parking points are examined in the in-plane as well as in the out-of-plane.

Au Togo, le changement climatique est une des préoccupations majeures pour les populations locales et l’ensemble des écosystèmes. L’objectif de la présente étude est de contribuer à l’amélioration de la prise de décision dans la lutte contre les changements climatiques. La méthodologie est basée sur l’analyse de données journalières de précipitations de dix modèles climatiques régionaux de 2021 à 2080. Les résultats montrent que d’incertitudes allant de 1 à 9% dans les zones des savanes et de -6 à -1% pour celles de montagnes. Cependant, de 2051 à 2080, l’analyse projetée présente -1 à -3% de baisse sur les monts Togo et 12% d’augmentation au Nord Togo. Ce qui atteste que les tendances futures des précipitations dans la région des savanes sont précaires et peu encourageant pour les activités socioéconomiques des populations locales. A cet effet, il est recommandé l’agriculture et l’élevage intelligents face au climat, l’agroforesterie et les bonnes pratiques de gestion des ressources en eau comme solutions d’adaptatives plus appropriées dans cette péjoration climatique.

Abstract Background Pancreatitis is a significant global health concern with rising incidence, complex management, and substantial mortality. This study aimed to assess global and regional trends in pancreatitis from 1990 to 2021 and project future trends to 2050 using data from the Global Burden of Disease (GBD) Study 2021. Methods We analyzed GBD 2021 data to evaluate age-standardized incidence (ASIR), mortality (ASMR), and disability-adjusted life years (DALYs) rates of pancreatitis. Regional trends, gender disparities, and correlations with the Socio-demographic Index (SDI) were examined. Key risk factors, including alcohol consumption, smoking, and metabolic disorders such as hyperlipidemia, were extracted and evaluated. A Bayesian age-period-cohort model (BAPC) was used for future projections. Results From 1990 to 2021, global pancreatitis cases increased from 1.73 million to 2.75 million, representing a rise of 59%. Despite this, ASIR decreased slightly from 37.62 to 32.81 per 100,000, a 12.8% reduction. Deaths rose from 68,490 to 122,416, an increase of 78.7%, while ASMR decreased from 1.69 to 1.45 per 100,000, a reduction of 14.2%. DALYs increased from 2.58 million to 4.10 million (59%). Significant regional variations were found, with Eastern Europe showing the highest ASIR, ASMR, and DALY rates. Projections indicate continued declines in ASIR, ASMR, and DALYs through 2050. Conclusions While global age-standardized rates of pancreatitis have declined, significant regional and socioeconomic disparities persist. Targeted prevention efforts, particularly in high-burden areas like Eastern Europe, and addressing modifiable risk factors such as alcohol use are crucial for reducing the future burden of pancreatitis.

Climate change has rapidly altered marine ecosystems and is expected to continue to push systems and species beyond historical baselines into novel conditions. Projecting responses of organisms and populations to these novel environmental conditions often requires extrapolations beyond observed conditions, challenging the predictive limits of statistical modeling capabilities. Bioenergetics modeling provides the mechanistic basis for projecting climate change effects on marine living resources in novel conditions, has a long history of development, and has been applied widely to fish and other taxa. We provide our perspective on 4 opportunities that will advance the ability of bioenergetics-based models to depict changes in the productivity and distribution of fishes and other marine organisms, leading to more robust projections of climate impacts. These are (1) improved depiction of bioenergetics processes to derive realistic individual-level response(s) to complex changes in environmental conditions, (2) innovations in scaling individual-level bioenergetics to project responses at the population and food web levels, (3) more realistic coupling between spatial dynamics and bioenergetics to better represent the local- to regional-scale differences in the effects of climate change on the spatial distributions of organisms, and (4) innovations in model validation to ensure that the next generation of bioenergetics-based models can be used with known and sufficient confidence. Our focus on specific opportunities will enable critical advancements in bioenergetics modeling and position the modeling community to make more accurate and robust projections of the effects of climate change on individuals, populations, food webs, and ecosystems.

Abstract Background The number of people with palliative care needs is projected to increase globally. Chile has recently introduced legislation for universal access to palliative care services for patients with severe and terminal illnesses, including non-cancer conditions. We aimed to estimate the number of people affected by serious health-related suffering and need for palliative care in Chile to 2050. Methods We used data on all deaths registered in Chile between 1997-2019 and population estimates for 1997–2050. We used Poisson regression to model past trends in causes of death adjusted by age, sex and population estimates, to project the number of deaths for each cause from 2021 to 2050. We applied the Lancet Commission on Palliative Care and Pain Relief weights to these projections to identify decedents and non-decedents with palliative care needs. Results Population palliative care needs in Chile are projected to increase from 117 (95% CI 114 to 120) thousand people in 2021 to 209 (95% CI 198 to 223) thousand people in 2050, a 79% increase (IRR 1.79; 95% CI 1.78–1.80). This increase will be driven by non-cancer conditions, particularly dementia (IRR 2.9, 95% CI 2.85–2.95) and cardiovascular conditions (IRR 1.86, 95% CI 1.83–1.89). By 2050, 50% of those estimated to need palliative care will be non-decedents (not expected to die within a year). Conclusions Chile will experience a large increase in palliative care needs, particularly for people with dementia and other non-cancer conditions. Improved availability of high-quality services, expanded clinician training and new sustainable models of care are urgently required to ensure universal access to palliative care.

Abstract Projection is a helpful description for treating bipartite networks as (monopartite) networks with pairwise interactions. Projections induce correlation spontaneously, avoiding negative degree correlation, even if bipartite networks are entirely random. In this study, we examined the structure of projections of random bipartite networks characterized by the degree distribution of individual and group nodes through the generating function method. We decomposed a projection into two subgraphs, the giant component, and finite components and analyzed their degree correlation. We demonstrate that positive degree correlations in projections originating from the clique size fluctuation remain after the decomposition at the set of finite components, although the values of their clustering coefficient are still finite. The giant component can exhibit either positive or negative degree correlations based on the structure of the projection. However, they are positively correlated in most cases. In addition, we found that a projection removed the giant component coincides with one in the subcritical phase, i.e., the discrete duality relation, when the degree distributions for group and individual are of Poisson.

The occurrence of fires can lead to accidents with high potential, and vertical fire compartmentation is a measure to reduce these incidents. Increasingly, computational numerical analyses play a crucial role in studying fire behavior for control and mitigation. The computational tool Fire Dynamics Simulator (FDS) is one of the main programs aimed at numerically analyzing fire spread. By using the FDS program, this research aims to numerically analyze the effectiveness of using horizontal projection and the combination of horizontal and vertical projections simultaneously, as specified in the Technical Instruction of the Fire Department of the State of São Paulo in combating the propagation of external vertical fire to the facade. Temperature measurements on the compartment facade were used to compare temperatures on the upper floor with the autoignition of material values commonly found in facades. Models with only horizontal projections showed greater effectiveness compared to models with the combinations of projections, mainly due to the presence of the spandrel component, which has a harmful effect on fire propagation. Despite the lower effectiveness of combination models for a fire with a heat release rate of 300 MJ/m², there would be no external vertical fire propagation. [ABSTRACT FROM AUTHOR]

One of the motivating forces for the current surge of interest in non-regular fractional factorial designs (non-RFrFDs) is that they have partially aliased effects that can be estimated together. Thus, from some estimation perspectives, non-RFrFDs outperform their regular counterparts that have either fully aliased or orthogonal effects. Elsawah (Communications in Mathematics and Statistics 10:623-652, 2022) presented a novel class of four-level non-RFrFDs, called multiple quadruple designs (MQDs), that are attractive from the practical perspective due to their structural and analytical simplicities. Level permutations and factor projections are widely used techniques for improving the eligibility and estimation efficiency of non-RFrFDs that are desirable for factor screening. This paper investigates the potential benefits of level permutations and factor projections for improving the performance of the MQDs in the full-dimension and any low-dimension and constructing new non-isomorphic four-level non-RFrFDs. The results provide theoretical benchmarks and conditions for improving the efficiency of the MQDs and constructing non-isomorphic MQDs. The efficiency is investigated in view of the widely used optimality criteria and modeling performance. The main numerical results show that the generated designs provide good representative points for the experimental domains that help investigators to effectively design and model high-dimensional experiments without prior assumptions about the forms of their underlying models. [ABSTRACT FROM AUTHOR]

The present study aims to develop scenario projections for the territorial distribution of farms in Bulgaria spanned between 2020 and 2030. It will mark important stages of the modern development of agriculture, which is within direction of prioritization designated into integrating the measures related to climate change and protection of environment setup in the Green Deal. On the one hand, the study is interesting because it works with a proportional extrapolation method through which projections are made in three scenarios. On the other hand, it illustrates the feasible future distribution of farms in Bulgaria in rural and non-rural areas driven by the effects of the Green Deal. The effects and impact of the Green Deal specifically on the number of farms was made on the basis of a literature study and a expert judgment method. The results of the research show that the number of farms will experience an apparent change in the direction of reduction, and probably it will not be with the same intensity, both due to the multiple factors that may appear meanwhile as well as in terms of territorial dimensions between separate municipalities. The number of farms in the country is expected to go down, and between 2010 and 2020 the decline is estimated up to 64%, whereas by 2030 without the effects of the Green Deal it is expected to reach a decrease by another 43% in the Statius-quo scenario, and because of the Green Deal, this percentage may aggravate additionally by between 1,7 – 5,7% until 2030. [ABSTRACT FROM AUTHOR]

Conventional radiography is widely used for postmortem foetal imaging, but its role in diagnosing congenital anomalies is debated. This study aimed to assess the effectiveness of X-rays in detecting skeletal abnormalities and guiding genetic analysis and counselling. This is a retrospective analysis of all post-abortion diagnostic imaging studies conducted at a centre serving a population of over 300,000 inhabitants from 2008 to 2023. The data were analysed using descriptive statistics. X-rays of 81 aborted foetuses (total of 308 projections; mean: 3.8 projections/examination; SD: 1.79) were included. We detected 137 skeletal anomalies. In seven cases (12.7%), skeletal anomalies identified through radiology were missed by prenatal sonography. The autopsy confirmed radiological data in all cases except for two radiological false positives. Additionally, radiology failed to identify a case of syndactyly, which was revealed by anatomopathology. X-ray is crucial for accurately classifying skeletal abnormalities, determining the causes of spontaneous abortion, and guiding the request for genetic counselling. Formal training for both technicians and radiologists, as well as multidisciplinary teamwork, is necessary to perform X-ray examinations on aborted foetuses and interpret the results effectively. [ABSTRACT FROM AUTHOR]

Dynamical downscaling is a widely‐used approach for generating regional projections of climate extremes at a finer scale. However, the systematic bias of the global climate model (GCM) generally degrades the reliability of projections. Recently, novel bias‐corrected CMIP6 data was generated using a mean‐variance‐trend (MVT) bias correction method for dynamical downscaling simulation. To validate the effectiveness of this data in the dynamical downscaling simulation of climate extremes, we carry out three Weather Research and Forecasting (WRF) simulations over Asia‐western North Pacific with a 25 km grid spacing from 1980 to 2014. The dynamical downscaling simulations driven by the raw GCM data set (hereafter WRF_GCM) and the bias‐corrected GCM (hereafter WRF_GCMbc) were assessed against the simulation driven by the European Center for Medium‐Range Weather Forecasts Reanalysis 5 data set. The results indicate that the MVT bias correction significantly improves the climatological mean and inter‐annual variability of downscaled climate extreme indices. In terms of the climatological mean, the WRF_GCMbc shows a 25%–82% decrease in root mean square errors (RMSEs) against the WRF_GCM. As for the inter‐annual variability, the MVT bias correction can improve the downscaling simulation of almost all precipitation extreme indices and 70% of the temperature extreme indices, characterized by the RMSEs' reduction of 1%–58%. The improvements of the climate extremes in terms of the climatological mean in the WRF_GCMbc primarily stem from the improved large‐scale circulation and ocean evaporation in the WRF, which in turn improves the downscaled precipitation and 2 m temperature through the advection, radiation, and surface energy exchange process. Plain Language Summary: High‐resolution projection of climate extremes is critical for climate risk assessment and regional adaptation planning. Regional climate model (RCM) is widely used to project future changes of climate extremes at a finer scale. However, as the input data for RCM, the global climate model (GCM) suffers from systematic biases, which greatly reduces the reliability of climate extremes' projections. Using the raw GCM data and the bias‐corrected GCM data by the mean‐variance‐trend (MVT) bias correction method, we conduct RCM simulations over the Asian‐western North Pacific region. We found that the MVT method can significantly improve the RCM simulations of various indices for precipitation and temperature extremes, reducing the overall bias by 1%–82%. Bias‐corrected GCM data contributes to better simulation of the large‐scale circulation in the RCM and further improves the simulation of climate extremes by various physical processes. Our results highlight the effectiveness of the bias‐corrected GCM data by the MVT method in RCM simulation of climate extremes. Key Points: Global climate model (GCM) bias should be constrained in the future projections of regional climate extremes by dynamical downscalingMultivariate bias correction method for GCM can greatly improve the downscaled simulation of climate extremesGCM bias corrections promote better simulations of the large‐scale circulation, resulting in improvements in downscaled climate extremes [ABSTRACT FROM AUTHOR]

Motor learning (ML), which plays a fundamental role in growth and physical rehabilitation, involves different stages of learning and memory processes through different brain regions. However, the neural mechanisms that underlie ML are not sufficiently understood. Here, a previously unreported neuronal projection from the dorsal hippocampus (dHPC) to the zona incerta (ZI) involved in the regulation of ML behaviors is identified. Using recombinant adeno‐associated virus, the projections to the ZI are surprisingly identified as originating from the dorsal dentate gyrus (DG) and CA1 subregions of the dHPC. Furthermore, projection‐specific chemogenetic and optogenetic manipulation reveals that the projections from the dorsal CA1 to the ZI play key roles in the acquisition and consolidation of ML behaviors, whereas the projections from the dorsal DG to the ZI mediate the retrieval/retention of ML behaviors. The results reveal new projections from the dorsal DG and dorsal CA1 to the ZI involved in the regulation of ML and provide insight into the stages over which this regulation occurs. [ABSTRACT FROM AUTHOR]

Compound extreme events pose more grave threats to human health, the natural environment, and socioeconomic systems than do individual extreme events. However, the drivers and spatiotemporal change characteristics of compound extreme events under climate transition remain poorly understood, especially in the arid region of Northwest China. This study examined the spatiotemporal change characteristics and driving mechanisms of extreme temperature and precipitation compound events in Northwest China based on data from 86 national meteorological stations and 11 climate models of the Coupled Model Intercomparison Project, Phase 6. The results indicated that (1) the frequency values of heat extremity–dry (1.60/10a) and heat extremity–heavy precipitation (0.60/10a) events increased from 1961 to 2020, and showed a faster uptrend after 1990 than before. (2) Under four shared socioeconomic pathway scenarios, there is also the likelihood of an upward trend in heat extremity–dry and heat extremity–heavy precipitation events in Northwest China by the end of 21 century, especially under SSP585, with probability values of 1.70/10a and 1.00/10a, respectively. (3) A soil moisture deficit leads to decreased evaporation and increased sensible heat by reduction in the soil–atmosphere exchange; the non-adiabatic heating process leads to a higher frequency of hot days. This land–air interaction feedback mechanism is a significant driver of heat extremity–dry events in Northwest China. (4) In the Northwest China region, the warmer trend surpasses the wetter trend, contributing to increased specific humidity, and the vapor pressure deficit may lead to an increasing frequency of extreme precipitation, consequently increasing heat extremity–heavy precipitation events. These results provide new insights for the understanding of compound extreme events, in order to cope with their risks. [ABSTRACT FROM AUTHOR]

Background: The number of people with palliative care needs is projected to increase globally. Chile has recently introduced legislation for universal access to palliative care services for patients with severe and terminal illnesses, including non-cancer conditions. We aimed to estimate the number of people affected by serious health-related suffering and need for palliative care in Chile to 2050. Methods: We used data on all deaths registered in Chile between 1997-2019 and population estimates for 1997–2050. We used Poisson regression to model past trends in causes of death adjusted by age, sex and population estimates, to project the number of deaths for each cause from 2021 to 2050. We applied the Lancet Commission on Palliative Care and Pain Relief weights to these projections to identify decedents and non-decedents with palliative care needs. Results: Population palliative care needs in Chile are projected to increase from 117 (95% CI 114 to 120) thousand people in 2021 to 209 (95% CI 198 to 223) thousand people in 2050, a 79% increase (IRR 1.79; 95% CI 1.78–1.80). This increase will be driven by non-cancer conditions, particularly dementia (IRR 2.9, 95% CI 2.85–2.95) and cardiovascular conditions (IRR 1.86, 95% CI 1.83–1.89). By 2050, 50% of those estimated to need palliative care will be non-decedents (not expected to die within a year). Conclusions: Chile will experience a large increase in palliative care needs, particularly for people with dementia and other non-cancer conditions. Improved availability of high-quality services, expanded clinician training and new sustainable models of care are urgently required to ensure universal access to palliative care. Key messages: Estimating the number of people who experience serious health-related suffering and might benefit from palliative care need is key for service planning. This is particularly relevant in Chile, where a new law has been implemented that guarantees access to palliative care services for all patients with terminal conditions and severe diseases. We estimated the number of people who will experience serious health-related suffering and palliative care needs in Chile by 2050. The number of people with palliative care needs in Chile is going to almost double by 2050, mainly due to an increase in the number of people living and dying with dementia and non-cancer conditions. The projected increase in the number of people with palliative care needs highlights the need for enhancing availability of services, increase personnel training and new sustainable models of care, in particular for non-cancer conditions. [ABSTRACT FROM AUTHOR]

The number of older adults in the Netherlands is growing rapidly, and an increasing share of them is foreign-born. This may have implications for long-term care (LTC) demand. This study provides insights into older migrants’ current and future use of LTC provisions under the Dutch long-term care act (LTCA). We distinguish three types of LTC and six groups of older migrants and analyze register data of all foreign-born older adults. Descriptive statistics for the 2016–2022 period and logistic regression analyses show considerable heterogeneity regarding the LTC-services used and the origin of care users. Most notably, Moroccan and Turkish older adults are least likely to use residential care and more likely to use personal care budgets. By combining our models’ results with population projections, we project that older migrants’ use of home-based care and personal budgets will increase rapidly in the next decade. Migrants with western and Surinamese origin will most often use LTC. Although the demand for residential care will rise less markedly, residential care will remain most used by older migrants under the LTCA. The rising demand for home-based care calls for policy efforts accommodating flexibility, room for differences, and grounds for establishing trustworthy relationships between all involved actors. [ABSTRACT FROM AUTHOR]

Under the influence of climate warming, the frequency and intensity of extreme weather events are increasing, posing a greater risk of exposing the ecological environment to extreme climatic conditions. Ecological land, as a land use type of paramount importance to both the natural environment and humanity, has not been examined regarding its exposure under extreme climatic conditions. Therefore, this study focuses on the ecologically significant Southwest China, characterized by frequent extreme temperature events. Based on CMIP6 climate data and land use data, and utilizing ArcGIS software, the exposure of ecological land to extreme temperature conditions is analyzed. The results indicate that, compared to historical periods, the area of ecological land exposed to extreme high temperatures is rapidly increasing, while the area exposed to extreme low temperatures is decreasing. Various types of ecological land show differences in area changes under extreme temperature exposure, and there is significant spatial heterogeneity in the changes in ecological land exposure, primarily due to the different spatial distributions of ecological land and extreme temperature indicators. The changes in exposure area of ecological land under extreme temperatures exhibit prominent topographical gradients. The findings of this study can provide crucial and clear information for the formulation of disaster prevention mitigation policies and land planning. [ABSTRACT FROM AUTHOR]

The Montenegrin climate is characterised as very heterogeneous due to its complex topography. The viticultural heritage, dating back to before the Roman empire, is settled in a Mediterranean climate region, located south of the capital Podgorica, where climate conditions favour red wine production. However, an overall increase in warmer and drier periods affects traditional viticulture. The present study aims to discuss climate change impacts on Montenegrin viticulture. Bioclimatic indices, ensembled from five climate models, were analysed for both historical (1981–2010) and future (2041–2070) periods upon three socio-economic pathways: SSP1-2.6, SSP3-7.0 and SSP5-8.5. CHELSA (≈1 km) was the selected dataset for this analysis. Obtained results for all scenarios have shown the suppression of baseline conditions for viticulture. The average summer temperature might reach around 29.5 °C, and the growing season average temperature could become higher than 23.5 °C, advancing phenological events. The Winkler index is estimated to range from 2900 °C up to 3100 °C, which is too hot for viticulture. Montenegrin viticulture requires the application of adaptation measures focused on reducing temperature-increase impacts. The implementation of adaptation measures shall start in the coming years, to assure the lasting productivity and sustainability of viticulture. [ABSTRACT FROM AUTHOR]

Wind erosion climatic erosivity is a measure of climatic conditions that affect wind erosion. Projecting wind erosion climatic erosivity is curcial for predicting future wind erosion risk. In this study, we employed dynamic downscaling outputs from the MPI-ESM1-2-HR model to project changes in wind erosion climatic erosivity over High Mountain Asia (HMA) from 2041 to 2060 under a middle-emission scenario (an additional radiative forcing of 4.5 W/m2 by 2100). From 1995 to 2014, wind erosion climatic erosivity in HMA was high in the southwest, on the Qiangtang Plateau, and in the Qaidam Basin, exceeding 1 kg·m−1 s−1. Compared to the period 1995–2014, wind erosion climatic erosivity is projected to decrease by 0.5 kg·m−1 s−1 over the east of the Qiangtang Plateau and increase by approximately 1 kg·m−1 s−1 in the southwest of the HMA during 2041–2060 under the middle emission scenario. This increase in wind erosion climatic erosivity in the southwest of HMA is attributed to a projected rise in high-wind frequency for 2041–2060 compared to 1995–2014. Conversely, the decrease in wind erosion climatic erosivity in the east of the Qiangtang Plateau results from increased precipitation during 2041–2060, which mitigates the effects of increased high-wind frequencies. Given the growing risk of wind erosion in the southwest of the HMA, it's essential to implement appropriate mitigation policies for the future. [ABSTRACT FROM AUTHOR]

IntroductionAs climate change advances, the looming threat of dengue fever, intricately tied to rising temperatures, intensifies, posing a substantial and enduring public health challenge in the Philippines. This study aims to investigate the historical and projected excess dengue disease burden attributable to temperature to help inform climate change policies, and guide resource allocation for strategic climate change and dengue disease interventions.MethodsThe study utilized established temperature-dengue risk functions to estimate the historical dengue burden attributable to increased temperatures. Future projections were derived using Coupled Model Intercomparison Project Phase 6 (CMIP6) Shared Socioeconomic Pathway (SSP) scenarios to estimate the excess dengue burden on a national scale. Current health burden estimates were calculated by charting the attributable fraction per epidemiological week against the exponential risk function.ResultsProjections indicate a substantial increase in temperature-related dengue incidence across all SSP climate scenarios by 2100. Between 2010-2019, 72.1% of reported dengue cases in the Philippines were attributable to temperature, demonstrating that temperature is a significant driver in dengue transmission. The highest attributable fractions were observed between the warm-dry season to early rainy season (Epi Weeks 15–25). Southern, periequatorial areas, particularly those undergoing rapid urbanization, had the highest temperature-related dengue incidence.DiscussionThe findings emphasize the critical interplay between climate change and socioeconomic factors in shaping future dengue risk. By incorporating future climate scenarios and provincial-level projections, this study provides valuable insights for policy planning, early warning systems, and public health programming. Strengthening health infrastructure, promoting sustainable urban development, and implementing effective vector control measures are crucial to mitigating the future dengue burden in the Philippines.

ObjectiveSmoking is a major risk factor for peptic ulcer disease (PUD) mortality. This study aims to analyze global trends in smoking-attributable PUD mortality from 1990 to 2021 and project future trends to 2046.MethodsData were obtained from the Global Burden of Disease Study 2021. We calculated age-standardized mortality rates (ASMR) and estimated annual percentage changes (EAPC) for smoking-attributable PUD mortality. Bayesian Age-Period-Cohort models were used to project future trends.ResultsFrom 1990 to 2021, global smoking-attributable PUD deaths decreased from 48,900 to 29,400, with the ASMR declining from 1.2 to 0.3 per 100,000 (EAPC: −4.25%). High-income regions showed faster declines, while some low- and middle-income countries experienced slower progress or even increases. Projections suggest a continued global decline in smoking-attributable PUD mortality to 2046, with persistent regional disparities. By 2046, the global ASMR is expected to decrease to approximately 0.1 per 100,000, with higher rates persisting in certain regions such as the Solomon Islands (3.7 per 100,000) and Cambodia (1.6 per 100,000).ConclusionWhile global smoking-attributable PUD mortality has significantly decreased and is projected to continue declining, substantial regional disparities persist. These findings underscore the need for targeted tobacco control interventions, particularly in high-risk regions, to further reduce the global burden of smoking-attributable PUD mortality.

ABSTRACT For effective management practices and decision-making, the uncertainties associated with regional climate models (RCMs) and their scenarios need to be assessed in the context of climate change. This study analyzes long-term trends in precipitation and temperature data sets (maximum and minimum values) from the NASA, Earth Exchange Global Daily Downscaled Prediction (NEX-GDDP), under the São Francisco River Basin Representative Concentration Path (RCP) 4.5 and 8.5, using the REA (Reliable Ensemble Average) method. In each grid, the built multi-model was bias-corrected using the CMhyd software for annual, dry, wet, and pre-season periods – for historical (1961-2005) and future (2006-2100) periods. The multi-model and four different methods, namely: The Mann-Kendall, Mann-Kendall pre-brightening test, bias-corrected pre-brightening, and Spearman correlation, were used to detect trends in precipitation, and minimum and maximum temperature. In the analysis of precipitation and temperature metrics, the results for the NRMSD showed that, in general, the CSIRO model presented more satisfactory results in all physiographic regions. Person's correlation coefficient showed a better adjustment of precipitation for the MIROC5, EC.EARTH and NORESMI1 models, in areas of sub-medium and upper São Francisco. For the minimum temperature, the CSIRO and NORESMI1 models showed the best fit, in general. At maximum temperature, the EC.EARTH and CSIRO models showed more satisfactory results. With regard to trend analysis, the results indicated an increasing trend in mean annual temperature and precipitation across the basin. When analyzed by subregion, the results show an increasing trend in monthly average minimum and maximum temperatures in the middle and lower SFRB, while average monthly rainfall increases during the rainy season and preseason in Upper São Francisco. The results of this research can be used by government entities, such as Civil Defense, to subsidize decision-making that requires actions/measures to relocate people/communities to less risky locations to minimize risk or vulnerability situations for the population living nearby to the river.

Background Stroke is a pressing public health issue worldwide. This study aimed to forecast the future temporal trends and distribution characteristics of the global stroke burden. Methods and Results Global data on stroke incidence, prevalence, deaths, and disability‐adjusted life years between 1990 and 2021 were obtained from the GBD (Global Burden of Disease) Study 2021. The temporal trends of stroke burden were estimated using various regression models. Gross domestic product per capita was adopted as a predictor in the model to consider the impact of economic development on stroke burden. Projections of stroke burden up to 2050 were generated using the optimal model selected based on the Akaike information criterion, encompassing global, World Bank income levels, national levels, and sex‐age groups. In 2050, we projected 21.43 million stroke cases, 159.31 million survivors, 12.05 million deaths, and 224.86 million disability‐adjusted life years due to stroke globally. From 2021 to 2050, there was a declining trend in the global age‐adjusted stroke rates, with −7% in incidence, −4% in prevalence, −28% in deaths, and −28% in disability‐adjusted life years. Upper‐middle‐income countries were projected to have the most severe stroke burden, followed by lower‐middle‐income countries, low‐income countries, and high‐income countries. The stroke burden in over half of the 204 countries and territories was expected to be alleviated from 2022 to 2050. Men and older women worldwide bear higher burden. Conclusions Stroke remains a serious global health challenge, especially in low‐income and middle‐income countries. Targeted implementation of prevention and interventions is imperative across diverse demographic groups.

Transforming the food system while addressing climate change requires proactive measures based on quantitative projections of anticipated future conditions. A key component of the food system that must be considered during this transformation is food safety, which is the focus of this paper. Milk safety has been selected as a case study. Future milk contamination levels in Europe, in terms of total bacterial counts, are evaluated under various climate change scenarios. Projections from multiple climate models are integrated into a data-driven milk contamination model, validated using data from Malta, Spain, and Belgium. The modeling framework accounts for variability among dairy farms and the inherent uncertainties in climate projections. Results are presented through geographical heatmaps, highlighting coastal and southern areas such as Portugal, Western Spain, Southern Italy, and Western France as regions expected to face the highest bacterial counts. The analysis underlines the significant roles of humidity and wind speed, alongside temperature. It also examines compliance with the regulatory threshold for raw milk, revealing an increased frequency of summer weeks exceeding the threshold of 100,000 colony-forming units. Based on this analysis, regions are classified into low-risk, high-risk, and emerging-risk categories. This classification can guide the selection of farm strategies aimed at meeting future food safety standards. By informing these decisions with the anticipated impacts of climate change, the food system can be future-proofed.

A climate change assessment for streamflow availability of the selected rivers in Turkey is presented. Using an Index Basin Mapping (IBM) approach, climate change information is transferred across hydrologically similar rivers. This approach maps rivers of interest without downscaled climate information to index rivers where climate projections are available. Then, monthly perturbation ratios of index rivers, conveying projected climatic changes, are applied to the mapped rivers. Climate change effects on monthly streamflow availability and timing in eight selected rivers are evaluated under 20 scenarios produced from 10 General Circulation Models (GCMs) under medium and high emission cases. Results show that winter streamflow availability will increase due to more precipitation falling as rainfall rather than snowfall. Spring and summer streamflow availability will decrease due to reduced snowmelt runoff. Monthly streamflow variability will increase in all evaluated rivers. Out of eight selected rivers, the Çoruh, Yeşilırmak and Zamantı Rivers will be the most affected by climatic changes, with 14.6, 4.1, and 5.6% reductions in overall water availability under the high emission ensemble scenario. Overall water availability is projected increase in the Ceyhan and Göksu Rivers with climate change. Increased monthly streamflow variability can complicate water management in the region. HIGHLIGHTS Applicability of river mapping between hydroclimatologically similar basins.; Monthly perturbation ratios that reflect seasonal shift and water quantity.; Climate change assessment on timing and magnitude of streamflow availability.; Water availability reduced in spring but increased in winter with climatic changes in the Mediterranean rivers.;