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Background Intracerebral hemorrhage (ICH) results from the rupture of blood vessels causing bleeding within the brain and is one of the major causes of death and long-term disability globally, particularly in low- and middle-income countries. Despite having a lower incidence than ischemic stroke, ICH imposes a greater social and economic burden. To our knowledge, since the release of the 2021 Global Burden of Disease (GBD) report, there has been no comprehensive update on the epidemiology and trends of ICH. This study aims to analyze the impact of gender, age, and the Sociodemographic Index (SDI) on the burden of ICH at global, regional, and national levels. Methods Data on the incidence, deaths, and disability-adjusted life years (DALYs) of ICH and its related risk factors from 1990 to 2021 were extracted from the GBD 2021 project, encompassing 203 countries and regions. Furthermore, temporal trends of the global intracerebral hemorrhage burden were assessed through Joinpoint analysis. Results In 2021, there were 3.444 million new cases of ICH worldwide, with an age-standardized prevalence rate of 40.8 per 100,000 people, representing a 31.4% decrease compared to 1990. In 2021, ICH caused 3.308 million deaths, with an age-standardized mortality rate of 39.1 per 100,000 people, a reduction of 36.6% since 1990. Globally, ICH accounted for 79.457 million DALYs, with an age-standardized DALY rate of 92.4 per 100,000 people, representing a 39.1% decrease since 1990. Regionally, Central Asia, Oceania, and Southeast Asia had the highest age-standardized prevalence rates of ICH, whereas Australasia, high-income North America, and Western Europe had the lowest rates. Nationally, the Solomon Islands, Mongolia, and Kiribati had the highest age-standardized prevalence rates, whereas Switzerland, New Zealand, and Australia had the lowest. Hypertension, smoking, and environmental pollution were identified as the primary risk factors for ICH. This study also validated the significant association between SDI and the burden of ICH, with the age-standardized DALY rate of ICH decreasing significantly as SDI increased. Conclusion Despite the decreasing burden of intracerebral hemorrhage, it remains a significant public health issue in countries with a lower SDI. Prevention strategies should prioritize hypertension management, air quality improvement, and smoking control to further mitigate the impact of intracerebral hemorrhage.

Mobile robots play a pivotal role in advancing smart manufacturing technologies. However, existing Obstacle avoidance path Planning (OP) algorithms for mobile robots suffer from low stability and applicability. Therefore, this paper proposes an enhanced Secret Bird Optimization Algorithm (SBOA)-based OP algorithm for mobile robots to address these challenges, termed AGMSBOA. Firstly, an adaptive learning strategy is introduced, where individuals enhance the diversity of the algorithm’s population by summarizing relationships among candidates of varying quality, thereby strengthening the algorithm’s ability to locate globally optimal obstacle avoidance path regions. Secondly, a group learning strategy is incorporated by dividing the population into learning and teaching groups, enhancing the algorithm’s exploitation capabilities, improving the accuracy of obstacle avoidance path planning, and reducing actual runtime. Lastly, a multiple population evolution strategy is proposed, which balances the exploration/exploitation phases of the algorithm by analyzing the nature of different individuals, improving the algorithm’s ability to escape suboptimal obstacle avoidance path traps. Subsequently, AGMSBOA was used to solve the OP problem on five maps and two OP problems in real-world environments. The experiments illustrate that AGMSBOA achieves more than 5% performance improvement in path length and a 100–win rate in runtime metrics, as well as faster convergence and stability of the solution. Therefore, AGMSBOA proposed in this paper is an efficient, robust, and robust OP method for mobile robots.

The safety of underlying metro tunnels is significantly compromised when the excavation of the overlying foundation pit is not properly conducted. Currently, research on the longitudinal deformation of tunnels induced by upper excavation typically relies on the Pasternak model, which assumes the tunnel behaves as a slender beam with a circular cross-section. However, due to the complexity in characterizing convergence deformation under lateral loading conditions, few studies have systematically explored its influence on the tunnel deformation. In this study, a theoretical model considering the lateral response of the tunnel was developed. Then, analytical evaluations of engineering cases were performed to validate the model’s accuracy. The results indicate that the proposed model provides a more accurate prediction of tunnel deformation due to overlying excavation compared to the Pasternak and Winkler foundation model. Additionally, the maximum vertical displacement of the tunnel increased with the widening of the foundation pit. It was also found that the maximum vertical displacement of the tunnel decreased almost linearly with an increase in the burial depth of the tunnel. In comparison to these two factors, the distance between the tunnel axis and the foundation pit had less influence on the tunnel deformation induced by excavation. The conclusions provide a theoretical reference for engineering calculations and practical applications.

Background Idiopathic epilepsy (IE) remains a significant neurological disorder, contributing to substantial global morbidity and mortality. This study aims to comprehensively evaluate the global burden of IE from 1990 to 2021, focusing on trends in incidence, mortality, and disability-adjusted life years (DALYs) across different geographic regions. Additionally, the study projects IE burden trends through 2036, providing insights for future public health interventions. Methods Data were extracted from the Global Burden of Disease Study 2021 (GBD 2021). IE incidence, mortality, and DALYs were analyzed by age, sex, year, and geographic location. Age-standardized rates were computed to facilitate comparisons across countries and regions. Temporal trends in IE burden were evaluated using Joinpoint regression, while future trends were projected using the Bayesian age-period-cohort (BAPC) model. Results In 2021, there were approximately 3.27 million new cases of IE globally (95% uncertainty interval [UI]: 2.4 to 4.13 million) and 140,000 deaths (95% UI: 120,000 to 150,000). Total DALYs reached 13.88 million (95% UI: 10.73 to 17.62 million). The global age-standardized incidence rate increased from 38.12 per 100,000 in 1990 to 42.82 per 100,000 in 2021. The Andean and Central Latin American regions exhibited the highest incidence rates, while East Asia and Oceania reported the lowest. Despite a decrease in the global age-standardized mortality rate from 2.07 per 100,000 in 1990 to 1.74 per 100,000 in 2021, mortality rates remained elevated in low- and middle-income countries, particularly in sub-Saharan Africa. Male patients showed consistently higher incidence, mortality, and DALY rates compared to females, with the highest burden observed in children under 5 years and adults over 60 years. Conclusion Over the past three decades, global IE incidence has steadily increased, while mortality and DALY rates have declined, especially in high-income countries. However, low- and middle-income regions continue to face significant challenges due to limited access to healthcare. Public health efforts must prioritize enhancing early diagnosis and treatment capabilities in these resource-limited areas.

This study examines the desirable public debt threshold for African economies and the effect of foreign direct investment (FDI) on economic growth, using secondary data from 1995 to 2019. The analysis employed panel-data threshold regression, and the results indicate that the debt threshold desirable for economic growth ranges from 22% to 85% of GDP, depending on the kind of model employed. Also, the results conclusively show that FDI always has a negative effect on economic growth when the economy operates below the bottom-debt threshold, with the negative FDI coefficient remaining significant across most of the analysis. It is thus crucial for policymakers to continue pursuing policies that encourage debt financing for major infrastructure projects that drive increased industrialization. This will also help to increase the local economies’ attractiveness to foreign investment and ensure that the FDI will only further boost economic growth and development.

Polyhydroxyalkanoates (PHA) are sustainable alternatives to conventional plastics due to biodegradability and biocompatibility. However, most PHA-producing strains are Gram-negative, which co-produce endotoxins that limit their applicability in high-quality biomedical fields. Additionally, industrial-scale PHA production is hindered by high costs, with feedstocks accounting for half the total expenses. In this study, a Gram-positive strain, GM-4, was isolated and evaluated for industrial potential. This strain achieved a dry cell weight (DCW) of 5.4 g/L and a PHA content of 63% with glucose, exhibiting the highest production rates at the genus level. GM-4 could efficiently utilize sugarcane molasses and corn steep liquor, yielding 13.60 g/L DCW and 9.84 g/L PHA, which represents one of the highest PHA production observed from a wild bacterial strain utilizing waste-derived feedstocks at the flask scale. This feedstock combination significantly enhanced biomass growth and PHA production by 2.6-fold and 3.1-fold, respectively, offering economic and environmental benefits. The produced PHA was determined as polyhydroxybutyrate with excellent material properties through comprehensive characterization. Whole-genome analysis clarified the metabolic pathways that convert diverse substrates into PHA. These findings position GM-4 as a promising candidate for sustainable and cost-effective PHA production, with potential for biomedical and other applications. Graphical abstract

When the inverse finite element method (inverse FEM) is used to reconstruct the deformation field of a multi-element structure with strain measurements, strain measurement errors can lower the reconstruction accuracy of the deformation field. Furthermore, the calibration ability of a self-structuring fuzzy network (SSFN) is weak when few strain samples are used to train the SSFN. To solve this problem, a novel two-step calibration method for improving the reconstruction accuracy of the inverse FEM method is proposed in this paper. Initially, the errors derived from measured displacements and reconstructed displacements are distributed to the degrees of freedom (DOFs) of nodes. Then, the DOFs of nodes are used as knots, in order to produce non-uniform rational B-spline (NURBS) curves, such that the sample size employed to train the SSFN can be enriched. Next, the SSFN model is used to determine the relationship between the measured strain and the DOFs of the end nodes. A loading deformation experiment using a three-element structure demonstrates that the proposed algorithm can significantly improve the accuracy of reconstruction displacement.

Synthetic Aperture Radar (SAR), an active remote sensing imaging radar technology, has certain surface penetration ability and can work all day and in all weather conditions. It is widely applied in ship detection to quickly collect ship information on the ocean surface from SAR images. However, the ship SAR images are often blurred, have large noise interference, and contain more small targets, which pose challenges to popular one-stage detectors, such as the single-shot multi-box detector (SSD). We designed a novel network structure, a combinational fusion SSD (CF-SSD), based on the framework of the original SSD, to solve these problems. It mainly includes three blocks, namely a combinational fusion (CF) block, a global attention module (GAM), and a mixed loss function block, to significantly improve the detection accuracy of SAR images and remote sensing images and maintain a fast inference speed. The CF block equips every feature map with the ability to detect objects of all sizes at different levels and forms a consistent and powerful detection structure to learn more useful information for SAR features. The GAM block produces attention weights and considers the channel attention information of various scale feature information or cross-layer maps so that it can obtain better feature representations from the global perspective. The mixed loss function block can better learn the positions of the truth anchor boxes by considering corner and center coordinates simultaneously. CF-SSD can effectively extract and fuse the features, avoid the loss of small or blurred object information, and precisely locate the object position from SAR images. We conducted experiments on the SAR ship dataset SSDD, and achieved a 90.3% mAP and fast inference speed close to that of the original SSD. We also tested our model on the remote sensing dataset NWPU VHR-10 and the common dataset VOC2007. The experimental results indicate that our proposed model simultaneously achieves excellent detection performance and high efficiency.

Telomere length maintenance is essential for cellular immortalization and tumorigenesis. 5% − 10% of human cancers rely on a recombination-based mechanism termed alternative lengthening of telomeres (ALT) to sustain their replicative immortality, yet there are currently no targeted therapies. Through CRISPR/Cas9-based genetic screens in an ALT-immortalized isogenic cellular model, here we identify histone lysine demethylase KDM2A as a molecular vulnerability selectively for cells contingent on ALT-dependent telomere maintenance. Mechanistically, we demonstrate that KDM2A is required for dissolution of the ALT-specific telomere clusters following recombination-directed telomere DNA synthesis. We show that KDM2A promotes de-clustering of ALT multitelomeres through facilitating isopeptidase SENP6-mediated SUMO deconjugation at telomeres. Inactivation of KDM2A or SENP6 impairs post-recombination telomere de-SUMOylation and thus dissolution of ALT telomere clusters, leading to gross chromosome missegregation and mitotic cell death. These findings together establish KDM2A as a selective molecular vulnerability and a promising drug target for ALT-dependent cancers. Alternative lengthening of telomeres (ALT) provides cancer cells a mechanism to sustain replicative immortality. Here, the authors identify KDM2A as a molecular vulnerability in ALT-dependent cancer cells and demonstrate its role in the resolution of ALT-specific telomere clusters via recruitment of SENP6.

Diffusion models have attracted considerable scholarly interest for their outstanding performance in generative tasks. However, current style transfer techniques based on diffusion models still rely on fine-tuning during the inference phase to optimize the generated results. This approach is not merely laborious and resource-demanding but also fails to fully harness the creative potential of expansive diffusion models. To overcome this limitation, this paper introduces an innovative solution that utilizes a pretrained diffusion model, thereby obviating the necessity for additional training steps. The scheme proposes a Feature Normalization Mapping Module with Cross-Attention Mechanism (INN-FMM) based on the dual-path diffusion model. This module employs soft attention to extract style features and integrate them with content features. Additionally, a parameter-free Similarity Attention Mechanism (SimAM) is employed within the image feature space to facilitate the transfer of style image textures and colors, while simultaneously minimizing the loss of structural content information. The fusion of these dual attention mechanisms enables us to achieve style transfer in texture and color without sacrificing content integrity. The experimental results indicate that our approach exceeds existing methods in several evaluation metrics.