Search Results (2,164)

In light of the increasing frequency and intensity of natural phenomena, whether climatic or telluric, the relevance of multi-risk assessment approaches has become an important issue for understanding and estimating the impacts of disasters on complex socioeconomic systems. Two aspects contribute to the worsening of this situation. First, climate change has heightened the incidence and, in conjunction, the seriousness of geohazards that often occur with each other. Second, the complexity of these impacts on societies is drastically exacerbated by the interconnections between urban areas, industrial sites, power or water networks, and vulnerable ecosystems. In front of the recent research on this problem, and the necessity to figure out the best scientific positioning to address it, we propose, through this review analysis, to revisit existing literature on multi-risk assessment methodologies. By this means, we emphasize the new recent research frameworks able to produce determinant advances. Our selection corpus identifies pertinent scientific publications from various sources, including personal bibliographic databases, but also OpenAlex outputs and Web of Science contents. We evaluated these works from different criteria and key findings, using indicators inspired by the PRISMA bibliometric method. Through this comprehensive analysis of recent advances in multi-risk assessment approaches, we highlight main issues that the scientific community should address in the coming years, we identify the different kinds of geohazards concerned, the way to integrate them in a multi-risk approach, and the characteristics of the presented case studies. The results underscore the urgency of developing robust, adaptable methodologies, effectively able to capture the complexities of multi-risk scenarios. This challenge should be at the basis of the keys and solutions contributing to more resilient socioeconomic systems. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) represents a major global health challenge characterized by complex adipose–liver interactions mediated by adipokines and hepatokines. Despite rapid field evolution, a comprehensive understanding of research trends and translational advances remains fragmented. This study systematically maps the scientific landscape through bibliometric analysis, identifying emerging domains and future clinical translation directions. Methods: A comprehensive bibliometric analysis of 1002 publications from 2004 to 2025 was performed using thematic mapping, temporal trend evaluation, and network analysis. Analysis included geographical and institutional distributions, thematic cluster identification, and research paradigm evolution assessment, focusing specifically on adipokine–hepatokine signaling mechanisms and clinical implications. Results: The United States and China are at the forefront of research output, whereas European institutions significantly contribute to mechanistic discoveries. The thematic map analysis reveals the motor/basic themes residing at the heart of the field, such as insulin resistance, fatty liver, metabolic syndrome, steatosis, fetuin-A, and other related factors that drive innovation. Basic clusters include metabolic foundations (obesity, adipose tissue, FGF21) and adipokine-centered subjects (adiponectin, leptin, NASH). New themes focus on inflammation, oxidative stress, gut microbiota, lipid metabolism, and hepatic stellate cells. Niche areas show targeted fronts such as exercise therapies, pediatric/novel adipokines (chemerin, vaspin, omentin-1), and advanced molecular processes that focus on AMPK and endoplasmic-reticulum stress. Temporal analysis shows a shift from single liver studies to whole models that include the gut microbiota, mitochondrial dysfunction, and interactions between other metabolic systems. The network analysis identifies nine major clusters: cardiovascular–metabolic links, adipokine–inflammatory pathways, hepatokine control, and new therapeutic domains such as microbiome interventions and cellular stress responses. Conclusions: In summary, this study delineates current trends and emerging areas within the field and elucidates connections between mechanistic research and clinical translation to provide guidance for future research and development in this rapidly evolving area. Full article

More recently, artificial intelligence (AI)-generated content (AIGC) is fundamentally transforming multiple sectors, including materials discovery, healthcare, education, scientific research, and industrial manufacturing. As for the complexities and challenges of intelligent robot design, AIGC has the potential to offer a new paradigm, assisting in conceptual and technical design, functional module design, and the training of the perception ability to accelerate prototyping. Taking the design of an apple-harvesting robot, for example, we demonstrate a basic framework of the AIGC-assisted robot design methodology, leveraging the generation capabilities of available multimodal large language models, as well as the human intervention to alleviate AI hallucination and hidden risks. Second, we study the enhancement effect on the robot perception system using the generated apple images based on the large vision-language models to expand the actual apple images dataset. Further, an apple-harvesting robot prototype based on an AIGC-aided design is demonstrated and a pick-up experiment in a simulated scene indicates that it achieves a harvesting success rate of 92.2% and good terrain traversability with a maximum climbing angle of 32°. According to the tentative research, although not an autonomous design agent, the AIGC-driven design workflow can alleviate the significant complexities and challenges of intelligent robot design, especially for beginners or young engineers. Full article

The large-scale integration of volatile and intermittent renewables necessitates greater flexibility in the power system. Improving this flexibility is key to achieving a high proportion of renewable energy consumption. In this context, the scientific selection of energy storage technology is of great significance for the construction of new power systems. From the perspective of life cycle cost analysis, this paper conducts an economic evaluation of four mainstream energy storage technologies: lithium iron phosphate battery, pumped storage, compressed air energy storage, and hydrogen energy storage, and quantifies and compares the life cycle cost of multiple energy storage technologies. On this basis, a three-dimensional multi-energy storage comprehensive evaluation indicator system covering economy, technology, and environment is constructed. The improved grade one method and entropy weight method are used to determine the comprehensive performance, and the fuzzy comprehensive evaluation method is used to carry out multi-attribute decision-making on the multi-energy storage technology in the source, network, and load scenarios. The results show that pumped storage and compressed air energy storage have significant economic advantages in long-term and large-scale application scenarios. With its fast response ability and excellent economic and technical characteristics, the lithium iron phosphate battery has the smallest score change rate (15.2%) in various scenarios, showing high adaptability. However, hydrogen energy storage technology still lacks economic and technological maturity, and breakthrough progress is still needed for its wide application in various application scenarios in the future. Full article

Alzheimer’s disease (AD) is one of the most common chronic neurodegenerative disorders worldwide. It is characterized by progressive memory loss and cognitive decline, leading to dementia. The pathogenesis of the disease is primarily attributed to two pathological protein structures: amyloid-beta (Aβ) plaques and tau protein neurofibrils. The current treatment strategies for AD are mainly symptomatic, highlighting the urgent need for the development of new, more effective therapies for the disease. The purpose of this paper is to provide a comprehensive and scientific review of the latest research regarding novel therapeutic options in the treatment of AD. In recent years, research has focused on more advanced and diversified strategies, including immunotherapy, gene therapy, tyrosine kinase inhibitors, therapies targeting mitochondrial function, and neurogenesis-related process modulation. One of the most promising treatment strategies for AD is immunotherapy. Intensive research is currently underway on both passive immunization, which involves the administration of monoclonal antibodies, and active immunization through vaccinations that stimulate the body to produce specific antibodies. Further research into novel therapeutic directions is essential, particularly concerning the role of the immune system in the pathogenesis of AD. Immunization appears to be a highly promising approach to developing effective methods for preventing AD or delaying the progression of this disease. Full article

The subject of ship structural dynamics has faced new technological obstacles due to scientific and technological advancements, and one of the main concerns in related sectors is how to effectively reduce the vibration levels of different ships. This article focuses on the application scenarios of ship floating raft isolation systems, establishing a wave propagation model for acoustic black hole (ABH) structures based on the idea of the ABH effect. Then, a transfer matrix model for serially connected ABH structures is derived, which serves as a basis for subsequent structural designs. Second, the finite element method is used to study the energy distribution and vibration characteristics of a symmetrically distributed periodic non-uniform multi-level ABH structure. Meanwhile, it examines its bandgap distribution under a one-dimensional periodic arrangement and then investigates the vibration properties of non-uniform multi-level ABH thin-plate constructions with different periods from the perspective of engineering applications. Moreover, parameter optimization studies of non-uniform multi-level ABH structures with finite periods are carried out with an emphasis on engineering applications. The first step is to use the design space to determine the range of values for the parameters that need to be optimized. The hyper Latin cubic sampling method is then employed to select samples, and the EI criterion and PSO optimization algorithm are applied to add new samples to improve the Kriging surrogate model’s accuracy. When the optimal structural parameters have been determined, they are applied to the raft rib plate to verify the isolation effect of the non-uniform multi-level ABH structure by analyzing the vibration level difference at specific raft positions before and after embedding it. Full article

Background: Energy drinks (EDs) are non-alcoholic, functional beverages sold worldwide in more than 165 countries. These products are very popular and often consumed by children, teenagers, and young adults to improve physical performance, reduce drowsiness, and improve memory and concentration with increased intellectual effort. However, their consumption is associated with an increased risk of various health consequences. Objectives: The purpose of this non-systematic review was to discuss the components of EDs and their effects, summarize the AEs reported in the literature associated with the consumption of EDs, and briefly characterize the possible ED-related drug interactions. Methods: Scientific evidence was extracted by searching the databases PubMed and Google Scholar. In addition, the reference lists of the retrieved papers were reviewed and cross-referenced to reveal additional relevant scientific evidence. Results: The most common ingredients in EDs are caffeine, taurine, glucuronolactone, B vitamins, the vitamin-like compound inositol, and sweeteners (sugar, fructose, glucose–fructose syrup or artificial sweeteners). Although it is difficult to conclusively prove a cause-and-effect relationship between the consumption of EDs and the observed pathophysiological abnormalities, most scientific evidence (mostly clinical case reports) indicates that both occasional and especially chronic use of EDs is associated with the occurrence of numerous adverse effects (AEs). Among these, the best documented AEs are those on the cardiovascular system. It should also be noted that the components of EDs (primarily caffeine) may have drug interactions; therefore, EDs may be an important factor influencing the safety of pharmacotherapy in patients consuming EDs. Conclusions: Consuming energy drinks lead to various health problems and may interfere with pharmacotherapy due to the potential development of drug interactions. Due to the widespread availability of EDs, their suggestive advertising aimed at the youngest customers, and ambiguous regulations, new legislative policies are required to limit the widespread consumption of such products and their negative health effects. Full article

In this article, we investigate the fractional soliton solutions as well as the chaotic analysis of the fourth-order nonlinear Ablowitz–Kaup–Newell–Segur wave equation. This model is considered an intriguing high-order nonlinear partial differential equation that integrates additional spatial and dispersive effects to extend the concepts to more intricate wave dynamics, relevant in engineering and science for understanding complex phenomena. To examine the solitary wave solutions of the proposed model, we employ sophisticated analytical techniques, including the generalized projective Riccati equation method, the new improved generalized exponential rational function method, and the modified F-expansion method, along with mathematical simulations, to obtain a deeper insight into wave propagation. To explore desirable soliton solutions, the nonlinear partial differential equation is converted into its respective ordinary differential equations by wave transforms utilizing $\beta$-fractional derivatives. Further, the solutions in the forms of bright, dark, singular, combined, and complex solitons are secured. Various physical parameter values and arrangements are employed to investigate the soliton solutions of the system. Variations in parameter values result in specific behaviors of the solutions, which we illustrate via various types of visualizations. Additionally, a key aspect of this research involves analyzing the chaotic behavior of the governing model. A perturbed version of the system is derived and then analyzed using chaos detection techniques such as power spectrum analysis, Poincaré return maps, and basin attractor visualization. The study of nonlinear dynamics reveals the system’s sensitivity to initial conditions and its dependence on time-decay effects. This indicates that the system exhibits chaotic behavior under perturbations, where even minor variations in the starting conditions can lead to drastically different outcomes as time progresses. Such behavior underscores the complexity and unpredictability inherent in the system, highlighting the importance of understanding its chaotic dynamics. This study evaluates the effectiveness of currently employed methodologies and elucidates the specific behaviors of the system’s nonlinear dynamics, thus providing new insights into the field of high-dimensional nonlinear scientific wave phenomena. The results demonstrate the effectiveness and versatility of the approach used to address complex nonlinear partial differential equations. Full article

The review summarizes the historical and current research on perennial grain breeding in Russia within the context of growing global interest in perennial crops. N.V. Tsitsin’s pioneering work in the 1930s produced the first wheat–wheatgrass amphiploids, which demonstrated the capacity to regrow after harvest and survive for 2–3 years. Subsequent research at the Main Botanical Garden in Moscow focused on characterizing Tsitsin’s material, selecting superior germplasm, and expanding genetic diversity through new cycles of hybridization and selection. This work led to the development of a new crop species, Trititrigia, and the release of cultivar ‘Pamyati Lyubimovoy’ in 2020, designed for dual-purpose production of high-quality grain and green biomass. Intermediate wheatgrass (Thinopyrum intermedium) is native to Russia, where several forage cultivars have been released and cultivated. Two large-grain cultivars (Sova and Filin) were developed from populations provided by the Land Institute and are now grown by farmers. Perennial rye was developed through interspecific crosses between Secale cereale and S. montanum, demonstrating persistence for 2–3 years with high biomass production and grain yields of 1.5–2.0 t/ha. Hybridization between Sorghum bicolor and S. halepense resulted in two released cultivars of perennial sorghum used primarily for forage production under arid conditions. Russia’s agroclimatic diversity in agricultural production systems provides significant opportunities for perennial crop development. The broader scientific and practical implications of perennial crops in Russia extend to climate-resilient, sustainable agriculture and international cooperation in this emerging field. Full article

Microplastic (MP) pollution is an escalating global environmental concern, with a growing body of research addressing diverse dimensions of this issue. Despite this progress, the field remains hindered by generating large, heterogeneous datasets that follow inconsistent reporting standards, resulting in fragmented and often incompatible databases. While various databases on MPs have been developed, they primarily operate in isolation, limiting the accessibility and cross-comparison of data. This study presents a foundational approach to aggregating and accessing existing MP pollution datasets. A comprehensive review of the currently available databases was conducted to evaluate their integration potential. It revealed key challenges such as non-standardized data formats, limited accessibility, and difficulty performing comparative analyses across sources. To address these barriers, a prototype web-based platform was developed that enables unified access to MP datasets. The architecture includes a smart standardization layer that harmonizes inputs from disparate sources. The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) techniques was proposed to facilitate natural language querying. This enables researchers to interact with the platform intuitively and extract meaningful insights more efficiently. The proposed system aims to enhance data discoverability, promote interoperability, and support robust, data-driven environmental research, paving the way toward more informed policy-making and scientific collaboration in the fight against MP pollution. With this platform, there is a potential for new discoveries and a future in which the tools to effectively combat this global issue are available, making the audience realize the potential for new discoveries. Full article

With the rise in immunocompromised individuals and patients with immune-related comorbidities such as COVID-19, the rate of fungal infections is growing. This increase, along with the current plateau in antifungal drug development, has made understanding the pathogenesis and dissemination of these organisms more pertinent than ever. The mouse model of fungal infection, while informative on a basic scientific level, has severe limitations in terms of translation to the human disease. Here we present data supporting the implementation of the human cerebral organoid model, which is generated from human embryonic stem cells and accurately recapitulates relevant brain cell types and structures, to study fungal infection and dissemination to the central nervous system (CNS). This approach provides direct insight into the relevant pathogenesis of specific fungal organisms in human tissues where in vivo models are impossible. With this model system we assessed the specific brain tropisms and cellular effects of fungal pathogens known to cross the blood–brain barrier (BBB), such as Cryptococcus neoformans. We determined the effects of this fungal pathogen on the overall gross morphology, cellular architecture, and cytokine release from these model organoids. Furthermore, we demonstrated that C. neoformans penetrates and invades the organoid tissue and remains present throughout the course of infection. These results demonstrate the utility of this new model to the field and highlight the potential for this system to elucidate fungal pathogenesis to develop new therapeutic strategies to prevent and treat the disseminated stages of fungal diseases such as cryptococcal meningitis. Full article

Pleurotus ostreatus is a mushroom species renowned for its abundant nutritional and medicinal properties. Nevertheless, the yield of its fruiting bodies has long remained at a standstill, making it arduous to achieve substantial improvements. Because the traditional composting approach for enhancing the yield of Pleurotus ostreatus has drawbacks such as a long duration and a high susceptibility to mold contamination, incorporating nutritional supplements into the culture medium of P. ostreatus has emerged as a relatively straightforward yet effective approach to enhancing its yield. This study was predicated on the roles of nucleotides and nucleosides in cellular metabolism and signal transduction. These substances were applied during the cultivation process of P. ostreatus to investigate their impact on the growth and nutritional composition of this mushroom. The findings of this study demonstrate that the supplementation of nucleotides and nucleosides not only improved the yield and biological efficiency of P. ostreatus but also increased its dietary fiber content and amino acids. Furthermore, this research has disclosed that nucleotides and nucleosides exert a notable influence on the lignocellulolytic enzyme system. This investigation provides a scientific foundation for the development of novel yields—enhancing agents for P. ostreatus and offering new insights into cultivation techniques for the progress of P. ostreatus cultivation techniques in both academic and practical arenas. Full article

Amidst the escalating global challenges of deforestation and climate change, effective forest governance has become a critical global imperative. As a key actor in this arena, China presents a crucial case for understanding state-led environmental governance. This study addresses the thematic evolution and governance structure of China’s forest policy planning from 1980 to 2024. Grounded in multi-level governance (MLG) theory, we apply the Non-negative Matrix Factorization (NMF) topic model to a corpus of 1265 policy documents sourced from the PKULaw database, spanning four administrative levels from central to county. An analysis of 13 core policy themes reveals a significant transition, shifting from early regulatory development and resource utilization to a modern emphasis on ecological protection, scientific monitoring, financial support, and governance innovation. The findings delineate a complex governance architecture: a vertical division of labor (central guidance, local implementation), a horizontal model of inter-departmental interaction where specialized management coexists with comprehensive coordination, and adaptive governance reflecting regional heterogeneity. These results illuminate the dynamic evolution of power allocation, central–local relations, and synergy within China’s forest sector. This study not only provides new empirical evidence and an analytical framework for understanding China’s natural resource policy transition but also offers scientific insights for optimizing multi-level forest governance systems and enhancing policy synergy and efficacy. Full article

Background/Objectives: Extracting meaningful medical information from chest X-ray images and transcribing it into text is a complex task that requires a high level of expertise and directly affects clinical decision-making processes. Automatic reporting systems for this field in Turkish represent an important gap in scientific research, as they have not been sufficiently addressed in the existing literature. Methods: A deep learning-based approach called Model-SEY was developed with the aim of automatically generating Turkish medical reports from chest X-ray images. The Swin Transformer structure was used in the encoder part of the model to extract image features, while the text generation process was carried out using the cosmosGPT architecture, which was adapted specifically for the Turkish language. Results: With the permission of the ethics committee, a new dataset was created using image–report pairs obtained from Elazıg Fethi Sekin City Hospital and Indiana University Chest X-Ray dataset and experiments were conducted on this new dataset. In the tests conducted within the scope of the study, scores of 0.6412, 0.5335, 0.4395, 0.4395, 0.3716, and 0.2240 were obtained in BLEU-1, BLEU-2, BLEU-3, BLEU-4, and ROUGE word overlap evaluation metrics, respectively. Conclusions: Quantitative and qualitative analyses of medical reports autonomously generated by the proposed model have shown that they are meaningful and consistent. The proposed model is one of the first studies in the field of autonomous reporting using deep learning architectures specific to the Turkish language, representing an important step forward in this field. It will also reduce potential human errors during diagnosis by supporting doctors in their decision-making. Full article

During the late Ming and early Qing Dynasties, China underwent a period of broad-based economic and societal transformation. Among the cultural forces at play, the Christian culture has significantly impacted the trajectory of Chinese history. At the time, responding to a distinct socio-political environment, Western missionaries employed a variety of religious methodologies to pursue the goal of proselytizing. As part of missionary efforts, they introduced Western scientific and cultural knowledge into China alongside Christian doctrines, coinciding with a period of political and cultural transformation and development in China. Accordingly, this influx of new ideas from the West had a far-reaching impact on Chinese society. This paper focuses on the Chinese translation of Euclid’s Elements, examining the intercultural dissemination of Western mathematical knowledge through missionary activities. Furthermore, the study also elucidates the positive impact of Western mathematics carried with religious efforts on the Chinese traditional mathematical system via presenting a comparison of paradigms in mathematics. Finally, this study argues that the translation practice by Christian emissaries from the West in the natural sciences during the Ming and Qing Dynasties engendered novel intellectual currents, thereby facilitating the development of a contemporary Chinese knowledge framework and a shift in religious research toward comprehensive perspectives. Full article