Background For more than three decades, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) has provided a framework to quantify health loss due to diseases, injuries, and associated risk factors. This paper presents GBD 2023 findings on disease and injury burden and risk-attributable health loss, offering a global audit of the state of world health to inform public health priorities. This work captures the evolving landscape of health metrics across age groups, sexes, and locations, while reflecting on the remaining post-COVID-19 challenges to achieving our collective global health ambitions. Methods The GBD 2023 combined analysis estimated years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 375 diseases and injuries, and risk-attributable burden associated with 88 modifiable risk factors. Of the more than 310 000 total data sources used for all GBD 2023 (about 30% of which were new to this estimation round), more than 120 000 sources were used for estimation of disease and injury burden and 59 000 for risk factor estimation, and included vital registration systems, surveys, disease registries, and published scientific literature. Data were analysed using previously established modelling approaches, such as disease modelling meta-regression version 2.1 (DisMod-MR 2.1) and comparative risk assessment methods. Diseases and injuries were categorised into four levels on the basis of the established GBD cause hierarchy, as were risk factors using the GBD risk hierarchy. Estimates stratified by age, sex, location, and year from 1990 to 2023 were focused on disease-specific time trends over the 2010–23 period and presented as counts (to three significant figures) and age-standardised rates per 100 000 person-years (to one decimal place). For each measure, 95% uncertainty intervals [UIs] were calculated with the 2·5th and 97·5th percentile ordered values from a 250-draw distribution. Findings Total numbers of global DALYs grew 6·1% (95% UI 4·0–8·1), from 2·64 billion (2·46–2·86) in 2010 to 2·80 billion (2·57–3·08) in 2023, but age-standardised DALY rates, which account for population growth and ageing, decreased by 12·6% (11·0–14·1), revealing large long-term health improvements. Non-communicable diseases (NCDs) contributed 1·45 billion (1·31–1·61) global DALYs in 2010, increasing to 1·80 billion (1·63–2·03) in 2023, alongside a concurrent 4·1% (1·9–6·3) reduction in age-standardised rates. Based on DALY counts, the leading level 3 NCDs in 2023 were ischaemic heart disease (193 million [176–209] DALYs), stroke (157 million [141–172]), and diabetes (90·2 million [75·2–107]), with the largest increases in age-standardised rates since 2010 occurring for anxiety disorders (62·8% [34·0–107·5]), depressive disorders (26·3% [11·6–42·9]), and diabetes (14·9% [7·5–25·6]). Remarkable health gains were made for communicable, maternal, neonatal, and nutritional (CMNN) diseases, with DALYs falling from 874 million (837–917) in 2010 to 681 million (642–736) in 2023, and a 25·8% (22·6–28·7) reduction in age-standardised DALY rates. During the COVID-19 pandemic, DALYs due to CMNN diseases rose but returned to pre-pandemic levels by 2023. From 2010 to 2023, decreases in age-standardised rates for CMNN diseases were led by rate decreases of 49·1% (32·7–61·0) for diarrhoeal diseases, 42·9% (38·0–48·0) for HIV/AIDS, and 42·2% (23·6–56·6) for tuberculosis. Neonatal disorders and lower respiratory infections remained the leading level 3 CMNN causes globally in 2023, although both showed notable rate decreases from 2010, declining by 16·5% (10·6–22·0) and 24·8% (7·4–36·7), respectively. Injury-related age-standardised DALY rates decreased by 15·6% (10·7–19·8) over the same period. Differences in burden due to NCDs, CMNN diseases, and injuries persisted across age, sex, time, and location. Based on our risk analysis, nearly 50% (1·27 billion [1·18–1·38]) of the roughly 2·80 billion total global DALYs in 2023 were attributable to the 88 risk factors analysed in GBD. Globally, the five level 3 risk factors contributing the highest proportion of risk-attributable DALYs were high systolic blood pressure (SBP), particulate matter pollution, high fasting plasma glucose (FPG), smoking, and low birthweight and short gestation—with high SBP accounting for 8·4% (6·9–10·0) of total DALYs. Of the three overarching level 1 GBD risk factor categories—behavioural, metabolic, and environmental and occupational—risk-attributable DALYs rose between 2010 and 2023 only for metabolic risks, increasing by 30·7% (24·8–37·3); however, age-standardised DALY rates attributable to metabolic risks decreased by 6·7% (2·0–11·0) over the same period. For all but three of the 25 leading level 3 risk factors, age-standardised rates dropped between 2010 and 2023—eg, declining by 54·4% (38·7–65·3) for unsafe sanitation, 50·5% (33·3–63·1) for unsafe water source, and 45·2% (25·6–72·0) for no access to handwashing facility, and by 44·9% (37·3–53·5) for child growth failure. The three leading level 3 risk factors for which age-standardised attributable DALY rates rose were high BMI (10·5% [0·1 to 20·9]), drug use (8·4% [2·6 to 15·3]), and high FPG (6·2% [–2·7 to 15·6]; non-significant). Interpretation Our findings underscore the complex and dynamic nature of global health challenges. Since 2010, there have been large decreases in burden due to CMNN diseases and many environmental and behavioural risk factors, juxtaposed with sizeable increases in DALYs attributable to metabolic risk factors and NCDs in growing and ageing populations. This long-observed consequence of the global epidemiological transition was only temporarily interrupted by the COVID-19 pandemic. The substantially decreasing CMNN disease burden, despite the 2008 global financial crisis and pandemic-related disruptions, is one of the greatest collective public health successes known. However, these achievements are at risk of being reversed due to major cuts to development assistance for health globally, the effects of which will hit low-income countries with high burden the hardest. Without sustained investment in evidence-based interventions and policies, progress could stall or reverse, leading to widespread human costs and geopolitical instability. Moreover, the rising NCD burden necessitates intensified efforts to mitigate exposure to leading risk factors—eg, air pollution, smoking, and metabolic risks, such as high SBP, BMI, and FPG—including policies that promote food security, healthier diets, physical activity, and equitable and expanded access to potential treatments, such as GLP-1 receptor agonists. Decisive, coordinated action is needed to address long-standing yet growing health challenges, including depressive and anxiety disorders. Yet this can be only part of the solution. Our response to the NCD syndemic—the complex interaction of multiple health risks, social determinants, and systemic challenges—will define the future landscape of global health. To ensure human wellbeing, economic stability, and social equity, global action to sustain and advance health gains must prioritise reducing disparities by addressing socioeconomic and demographic determinants, ensuring equitable health-care access, tackling malnutrition, strengthening health systems, and improving vaccination coverage. We live in times of great opportunity. Funding Gates Foundation and Bloomberg Philanthropies.

In the field of municipal waste, expanding cities and growing trend of the population have increasing and problematic effects. Improperly emptied containers jeopardize the possibility of the development of cleaner and more liveable city. Directly occurring problems can be the environmental and road-safety aspects during reaching the containers. Through the application of modern technologies, there are opportunities to apply sign-in-time frequency-based communication. This leads not only to the optimization of the collection route but also to the reduction of the above mentioned problems and problematic effects.

The aim of our study is to review the new vehicle diagnostic requirements that support economical and environmentally friendly operation. Vehicle technology is undergoing continuous and significant changes. At the same time, it is not enough to develop energy-efficient and environmentally friendly technologies; they must be operated in proper technical conditions and with proper driving techniques. Accordingly, new, innovative procedures are constantly needed for the economical and environmentally friendly operation of vehicles, and it is important to emphasize that vehicle diagnostics must also follow these changes! The practical applications of our publication and our research focus on several areas. This research is particularly important in the case of public transport vehicles and transport fleets. An important practical aspect is that large transport companies also achieve significant cost savings and, at the same time, contribute to environmentally friendly transport. The publication represents a new direction in vehicle diagnostics and research and development; this is the ECO-Diagnostics discussed in the material. ECO-Diagnostics is a procedure that takes into account both ecological and economic factors during vehicle diagnostic tests. Vehicle diagnostics, as an independent, professional, and scientific field, began to develop in the 1970s. This field of research experiences a paradigm shift, on average, every 20 years. Today, an epochal shift is taking place, with the development and spread of alternative propulsion systems (e.g., electric, hydrogen, or gas) and autonomous vehicles being the main areas of focus. The changes in vehicle technology must be followed by vehicle diagnostics too. Some of the already-known diagnostic methods (e.g., for internal combustion engines) can be included in this category, but new methods are also needed to enable the economical and environmentally friendly operation of vehicles. These facts make it important and urgent to define and research this area. Research in this area is particularly important for public transport vehicles and transport fleets. It is not enough to develop energy-efficient and environmentally friendly technologies: they must be operated in the right technical condition and with the right driving techniques for the intended purpose. This will help large transport companies to achieve significant cost savings and contribute to the environmentally friendly transport of passengers and goods. A major new area in vehicle diagnostics needs to be introduced and expanded. ECO-Diagnostics is a new category that has not been used before, and it also marks a new area of research and development. The article presents the basics of categorization and supports them with its own research results and application examples. As an introduction, a systematic overview of vehicle diagnostics as a whole is also provided. This is important (and novel) as no such systematic overview is available in the technical and scientific literature. The new category should also be included in this scheme. In parallel with the development of vehicles and diagnostic procedures, the methods and their context covered by the umbrella term ECO-Diagnostics (in ecological and economic terms) should, of course, be constantly expanded. Artificial intelligence can play an important role in this process. In the future, there will be a strong demand for the development of procedures in the field of ECO-Diagnostics. For both economic and environmental reasons, it is urgent and important to research and develop procedures in this category. This fact will also influence the work of researchers in the future.

In recent years, investors, corporations, and enterprises have shown great interest in the Bitcoin network; thus, promoting its products and services is crucial. This study utilizes an empirical analysis for financial time series and machine learning to perform prediction of bitcoin price and Garman-Klass (GK) volatility using Long Short-Term Memory (LSTM), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Facebook prophet models. The performance findings show that the LTSM boost has a noticeable improvement compared to SARIMA and Facebook Prophet in terms of MSE (Mean Squared Error) and MAE (Mean Average Error). Unlike Long Short-Term Memory (LSTM), a component of Deep Learning (DL), the finding explains why the bitcoin and its volatility forecasting difficulty has been partially met by traditional time series forecasting (SARIMA) and auto-machine-learning technique (Fb-Prophet). Furthermore, the finding confirmed that Bitcoin values are extremely seasonally volatile and random and are frequently influenced by external variables (or news) such as cryptocurrency laws, investments, or social media rumors. Additionally, results show a robust optimistic trend, and the days when most people commute are Monday and Saturday and an annual seasonality. The trend of the price and volatility of bitcoin using SARIMA and FB-Prophet is more predictable. The Fb-Prophet cannot easily fit within the Russian-Ukrainian conflict period, and in some COVID-19 periods, its performance will suffer during the turbulent era. Moreover, Garman-Klass (GK) forecasting seems more effective than the squared returns price measure, which has implications for investors and fund managers. The research presents innovative insights pertaining to forthcoming cryptocurrency regulations, stock market dynamics, and global resource allocation.

In a previous study, it was concluded that the da Vinci robotic systems installed in the Hungarian healthcare system were, with one privately funded exception, fully financed by EU funds. The present article drives a similar conclusion on a global scale. Massive public investments, or reimbursements, are needed to ensure the prevalence and financial sustainability of robotic surgical systems. The financial sustainability of RAS depends on the economic development of a country and its healthcare system, the number of medical schools, the history of robotic surgery and the funding mechanisms of the healthcare system. Even in the most advanced economies of the world, access to the benefits of RAS may be burdened by limitations in terms of financial (funding) and geographical access.

Monument protection is a multi-disciplinary, multi-faceted social activity, to which civi­lized states have been devoting time, money, and energy since the second half of the 19th century, operated educational institutions, research institutes, and creating legal regulations. Among the actors are investors, the architectural profession, experts, au­thorities, educational institutions, and civil associations. According to the historical preservation profession, preserving the values of historical buildings strengthens social identity. Thanks to memory as a psychological process, the sight, use, and presence of old things, including old buildings, in our lives evokes positive emotions in most people, which is why we accept the inconveniences and additional costs associated with maintaining old buildings. However, there is a broad social stratum for whom old only means junk and is not motivated at all to preserve historical values. Society's interest is shown by the fact that the press occasionally emphasizes a suppos­edly successful restoration of a monument, or even the story of a perishing asset. The Hungarian professional monument protection system has undergone a radical trans­formation since 2010. The central bodies have crumbled, and the regional organizational units that performed official tasks have been integrated into the public administration system and are trying to carry out value protection work under the general building authorities. In this situation, professional civil society organizations active in the field of monument protection are playing an increasingly important role.

The purpose of this paper is to discuss the mergers and acquisitions activity from various perspectives. The concept of mergers and acquisitions always has a strong economic background, which will be considered even if the concept is discussed from a legal perspective. After clarification of the basic terms of mergers and acquisitions, the economic background of mergers and acquisitions will be examined. From legal point of view this paper mainly concentrates on the relevant directives of the European Union. Currently, there are four relevant company law directives related to corporate reconstruction in the law of the European Union: the Merger Directive, which regulates mergers between public companies, the Sixth Company Law Directive, which covers the division of an existing public company into entities, the directive, which concerns cross-border mergers and last but not least the Takeover Directive. From this four company law directives, this paper mainly focuses, besides the economical background and basic terms of mergers, on the Merger and Cross-Border Directive.

This study explores how women entrepreneurs in a resource-constrained setting adopt and experience personal technology for business purposes within the broader context of digital transformation. Drawing on the technology acceptance model (TAM) and work–life border theory (WLBT), qualitative data were collected through 32 semi-structured interviews with women entrepreneurs operating micro and small enterprises in Mauritius. Findings reveal that perceived usefulness, ease of use, and institutional support drive the adoption of personal devices, enabling flexibility, cost savings, and improved responsiveness to clients. However, constant connectivity also blurs boundaries between work and family life, heightening stress, emotional fatigue, and security concerns, particularly in the absence of technical support. These dynamics unfold in gendered contexts shaped by cultural expectations and caregiving responsibilities, with technology simultaneously supporting business needs while intensifying work–life conflict. Building on these insights, this study proposes a conceptual model highlighting personal technology's dual impact on business performance and well-being, as well as the moderating and mitigating roles of gender norms, structural constraints, and support systems. The findings contribute to scholarship on gender and digital entrepreneurship, offering implications for gender-sensitive policies that promote equitable and supportive technology adoption in similar Global South (GS) contexts.

This paper deals with the numerical analysis of the Problem No. 32 of the TEAM Workshops. This is a three-limbed ferromagnetic core with pick up coils, which is a test bench for validation of numerical analysis with hysteresis. The numerical procedure is based on the magnetic field computation taking the hysteresis into account. The scalar Preisach model is integrated into a finite element analysis. The hysteretic nonlinearity is handled by the fixed point iterative technique. The results are validated by comparison with the experiments.