Search Results (947)

Human immunodeficiency virus (HIV) and hepatitis B virus (HBV) continue to be global public health issues. Globally, about 39.9 million persons live with HIV in 2023, according to the Joint United Nations Programme on HIV/AIDS (UNAIDS) 2024 Fact Sheet. Consequently, the World Health Organisation (WHO) reported that about 1.5 million new cases of HBV occur, with approximately 820 thousand mortalities yearly. Conversely, the lower percentage of HBV (30%) cases that receive a diagnosis is a setback in achieving the WHO 2030 target for zero HBV globally. This has necessitated a public health concern to repurpose antiretroviral (ARV) drugs for the treatment of HBV diseases. This review provides an introductory background, including the pros and cons of repurposing antiretrovirals (ARVs) for HBV treatment. We examine the similarities in replication mechanisms between HIV and HBV. We further investigate some clinical studies and trials of co-infected and mono-infected patients with HIV–HBV. The topical keywords including repurposing ARV drugs, repurposing antiretroviral therapy, Hepatitis B drugs, HBV therapy, title, and abstracts are searched in PubMed, Web of Science, and Google Scholar. The advanced search includes the search period 2014–2024, full text, clinical trials, randomized control trials, and review. The search results filtered from 361 to 51 relevant articles. The investigations revealed that HIV and HBV replicate via a common route known as ‘reverse transcription’. Clinical trial results indicate that an early initiation of ARVs, particularly with tenofovir disoproxil fumarate (TDF) as part of a regimen, significantly reduced the HBV viral load in co-infected patients. In mono-infected HBV, timely and correct precise medication is essential for HBV viral load reduction. Therefore, genetic profiling is pivotal for successful ARV drug repurposing in HBV treatment. Pharmacogenetics enables the prediction of the right dosages, specific individual responses, and reactions. This study uniquely explores the intersection of pharmacogenetics and drug repurposing for optimized HBV therapy. Additional in vivo, clinical trials, and in silico research are important for validation of the potency, optimum dosage, and safety of repurposed antiretrovirals in HBV therapy. Furthermore, a prioritization of research collaborations comprising of regulators and funders to foster clinically adopting and incorporating repurposed ARVs for HBV therapy is recommended. Full article

The application of robotic arms in the industrial field is continuously becoming greater and greater. The impact force generated by a robotic arm in a gripping operation leads to vibration and wear. To address this problem, this paper proposes a trajectory planning method based on the improved Slime Mould Algorithm. An interpolation curve under the joint coordinate system is constructed by using seven non-uniform B-spline functions, with time and impact force as the optimization objectives and angular velocity, angular acceleration, and angular acceleration as the constraints. The original algorithm introduces Bernoulli chaotic mapping to increase the diversity of the population, adaptively adjusts the feedback factor, improves the crossover operator to accelerate the global convergence, and combines the original algorithm with an improved artificial bee colony search strategy guided by the global optimal solution, adding a quadratic interpolation method to increase the diversity of the population and to accelerate the global convergence speed. Combined with the improved artificial swarm search strategy guided by the global optimal solution, the quadratic interpolation method is added to enhance the local utilization ability. The simulation and real-machine experimental results show that the improved algorithm shortens the movement time of the robotic arm, reduces the joint impacts, minimizes the vibration and wear, and prolongs the service life of the robotic arm. Full article

The global prevalence of obesity and type 2 diabetes mellitus (T2D) has risen in parallel over recent decades. Most individuals diagnosed with T2D exhibit adiposopathy-related diabetes (ARD), a condition characterized by hyperglycemia accompanied by three core features: increased ectopic and visceral fat deposition, dysregulated adipokine secretion favoring a pro-inflammatory state, and insulin resistance. Despite advancements in precision medicine, international guidelines for T2D continue to prioritize individualized therapeutic approaches focused on glycemic control and complications, and many healthcare providers predominantly maintain a glucocentric strategy. This review advocates for an adipocentric treatment paradigm for most individuals with T2D, emphasizing the importance of prioritizing weight loss and visceral fat reduction as key drivers of therapeutic intensification. By combining lifestyle modifications with pharmacological agents that promote weight loss—including SGLT-2 inhibitors, GLP-1 receptor agonists, or dual GLP-1/GIP receptor agonists—and, when appropriate, metabolic surgery, this approach offers the potential for disease remission in patients with shorter disease duration. For others, it enables superior metabolic control compared to traditional glucose-centered strategies while simultaneously delivering cardiovascular and renal benefits. In conclusion, an adipocentric treatment framework for ARD, which represents the majority of T2D cases, effectively integrates glucocentric and cardio-nephrocentric goals. This approach constitutes the optimal strategy for ARD due to its efficacy in achieving disease remission, improving metabolic control, addressing obesity-related comorbidities, and reducing cardiovascular and renal morbidity and mortality. Full article

Chemometrics, which applies mathematical and statistical methods to aid in experimental design, data analysis, and process optimization, is gaining more importance. It plays an important role in enhancing the sustainability of analytical methods when integrated with green analytical chemistry. Applying chemometrics to liquid chromatographic methods can speed up the analytical method, saving time, energy, and solvent consumption. This would be reflected by a low energy footprint and environmental impact. This review discusses the application of chemometric methods like multivariant data analysis, design of experiments, retention time prediction, and peak deconvolution in green liquid chromatographic analysis of pharmaceuticals. The review highlights the impact of chemometric approaches on the global push for sustainable practices. The integration of chemometrics into sustainable chromatographic analysis will continue to revolutionize the field leading to better performance of analytical methods. Full article

The efficient, low-cost, and large-scale development and utilization of offshore wind energy resources is an inevitable trend for future growth. With the continuous increase in the scale of wind turbines and their expansion into deep-sea locations, there is an urgent need to develop ultra-long, flexible blades suitable for future high-capacity turbines. Existing reviews in the field of blade design lack a simultaneous focus on the two core elements of blade performance calculation and design methods, as well as a detailed evaluation of specific methods. Therefore, this paper reviews the performance calculation and design methodologies of horizontal-axis wind turbine blades from three aspects: aerodynamic design, structural design, and coupled aero-structural design. A critical introduction to various methods is provided, along with a key viewpoint centered around design philosophy: there is no global optimal solution; instead, the most suitable solution is chosen from the Pareto set according to the design philosophy. This review not only provides a concise and clear overview for researchers new to the field of blade design to quickly acquire key background knowledge but also offers valuable insights for experienced researchers through critical evaluations of various methods and the presentation of core viewpoints. The paper also includes a refined review of extended areas such as aerodynamic add-ons and fatigue characteristics, which broadens the scope of the review to touch on multiple research areas and inspire further research. In future research, it is crucial to identify new key issues and challenges associated with increased blade length and flexibility, address the challenges faced in integrated aero-structural design, and develop platforms and tools that support multi-objective optimization design of blades, ensuring the safe, stable, and orderly development of wind turbines. Full article

Sub-Saharan Africa continues to bear a disproportionate burden of the global HIV epidemic. Integrating HIV services into primary healthcare is a crucial strategy to accelerate progress towards ending the epidemic. However, several challenges hinder effective integration, including underfunding, human resource shortages, infrastructure limitations, weak health systems, and sociocultural factors. With this perspective, we discuss strategies to address these challenges. A comprehensive, multi-faceted approach is necessary to overcome these barriers. Investing in human resources, improving infrastructure, and strengthening health information systems are essential for strengthening the health system. Implementing patient-centered care, integrated service delivery models, and community engagement can optimize service delivery. Utilizing digital health tools, such as mobile health applications and electronic health records, can enhance service delivery and data management. Mobilizing for an increase in domestic resources, aligning donor funding, and using cost-effective approaches are crucial for effective financing. Finally, robust monitoring and evaluation systems are necessary to track progress, identify challenges, and inform decision-making. With these strategies, among many others, sub-Saharan African countries can significantly improve the integration of HIV services into primary healthcare, leading to better health outcomes for people living with HIV and more sustainable HIV programs. Full article

Background: Mental disorders are disturbances of brain functions that cause cognitive, affective, volitional, and behavioral functions to be disrupted to varying degrees. One of these disorders is depression, a significant factor contributing to the increase in suicide cases worldwide. Consequently, depression has become a significant public health issue globally. Electroencephalogram (EEG) data can be utilized to diagnose mild depression disorder (MDD), offering valuable insights into the pathophysiological mechanisms underlying mental disorders and enhancing the understanding of MDD. Methods: This survey emphasizes the critical role of EEG in advancing artificial intelligence (AI)-driven approaches for depression diagnosis. By focusing on studies that integrate EEG with machine learning (ML) and deep learning (DL) techniques, we systematically analyze methods utilizing EEG signals to identify depression biomarkers. The survey highlights advancements in EEG preprocessing, feature extraction, and model development, showcasing how these approaches enhance the diagnostic precision, scalability, and automation of depression detection. Results: This survey is distinguished from prior reviews by addressing their limitations and providing researchers with valuable insights for future studies. It offers a comprehensive comparison of ML and DL approaches utilizing EEG and an overview of the five key steps in depression detection. The survey also presents existing datasets for depression diagnosis and critically analyzes their limitations. Furthermore, it explores future directions and challenges, such as enhancing diagnostic robustness with data augmentation techniques and optimizing EEG channel selection for improved accuracy. The potential of transfer learning and encoder-decoder architectures to leverage pre-trained models and enhance diagnostic performance is also discussed. Advancements in feature extraction methods for automated depression diagnosis are highlighted as avenues for improving ML and DL model performance. Additionally, integrating Internet of Things (IoT) devices with EEG for continuous mental health monitoring and distinguishing between different types of depression are identified as critical research areas. Finally, the review emphasizes improving the reliability and predictability of computational intelligence-based models to advance depression diagnosis. Conclusions: This study will serve as a well-organized and helpful reference for researchers working on detecting depression using EEG signals and provide insights into the future directions outlined above, guiding further advancements in the field. Full article

The wind farm layout optimization problem (WFLOP) aims to maximize wind energy utilization efficiency and mitigate energy losses caused by wake effects by optimizing the spatial layout of wind turbines. Although Genetic Algorithms (GAs) and Particle Swarm Optimization (PSO) have been widely used in WFLOP due to their discrete optimization characteristics, they still have limitations in global exploration capability and optimization depth. Meanwhile, the Differential Evolution algorithm (DE), known for its strong global optimization ability and excellent performance in handling complex nonlinear problems, is well recognized in continuous optimization issues. However, since DE was originally designed for continuous optimization scenarios, it shows insufficient adaptability under the discrete nature of WFLOP, limiting its potential advantages. In this paper, we propose a Fractional-Order Difference-driven DE Optimization Algorithm called FODE. By introducing the memory and non-local properties of fractional-order differences, FODE effectively overcomes the adaptability issues of advanced DE variants in WFLOP’s discreteness while organically applying their global optimization capabilities for complex nonlinear problems to WFLOP to achieve more efficient overall optimization performance. Experimental results show that under 10 complex wind farm conditions, FODE significantly outperforms various current state-of-the-art WFLOP algorithms including GA, PSO, and DE variants in terms of optimization performance, robustness, and applicability. Incorporating more realistic wind speed distribution and wind condition data into modeling and experiments, further enhancing the realism of WFLOP studies presented here, provides a new technical pathway for optimizing wind farm layouts. Full article

With the intensification of global population aging, attention to the emotional health of the elderly continues to grow. Traditional interior architectural design primarily focuses on optimizing physical functionality; however, this approach is no longer sufficient to meet the increasingly complex emotional needs of the elderly. Integrating the Three-Level Theory of Emotional Design (TTED) into interior design provides a significant opportunity to systematically address the multidimensional needs of the elderly. However, existing research is often fragmented and lacks thematic literature reviews to summarize the key factors, characteristics, and design strategy frameworks of interior design. This study aims to evaluate the impact of interior design on the emotional experiences of the elderly and to construct a conceptual framework to address current research gaps. By establishing rigorous selection criteria, 39 high-quality studies were identified from the Scopus, Web of Science, and Mendeley databases. Using ATLAS.ti 9 for thematic analysis, five core themes were distilled: aesthetics, use and function, emotional reflection, design strategies, and emotional experience. The findings revealed that architectural interior design practices often paid limited attention to the emotional needs of older adults. Through a comprehensive literature review, 10 key design features were identified, including multi-sensory attributes, morphological characteristics, cultural elements, and natural components, alongside 17 related research directions. The study introduces a dynamic feedback mechanism within the framework of the proposed architectural interior design strategy, highlighting the importance of employing multiple strategies that balance and complement each other in practical applications. Additionally, the study clarifies future research directions, offering theoretical support and practical guidance for designers to address the complex needs of the elderly. This achievement provides a systematic reference for the future development of interior architectural design and has significant implications for improving the emotional experience of the elderly. Full article

Background and Objectives: Colorectal cancer is a major contributor to global cancer morbidity and mortality. Surgical resection remains the cornerstone of treatment, but postoperative complications can significantly affect patient outcomes. Identifying factors that influence postoperative morbidity and mortality is crucial for optimizing patient care. This study aims to evaluate the impact of preoperative, intraoperative, and postoperative factors on surgical outcomes in patients with colorectal cancer. Methods: A retrospective cohort study was conducted on 688 patients who underwent colorectal cancer surgery within a 10-year period. Data collected included demographic information, comorbidities, laboratory values, surgical details, and postoperative outcomes. Statistical analyses were performed using chi-square tests for categorical variables and t-tests for continuous variables. Multivariate logistic regression was used to identify independent predictors of postoperative complications and mortality. Results: Postoperative complications occurred in 28.5% of patients, and the 30-day mortality rate was 5.2%. Preoperative factors such as elevated C-reactive protein (CRP) levels (p < 0.001), low albumin levels (p = 0.003), a high American Society of Anesthesiologists (ASA) score (p < 0.001), and presence of comorbidities like diabetes and hypertension (p = 0.005) were significantly associated with increased postoperative complications. Intraoperative factors such as blood loss greater than 500 mL (p < 0.001) and longer operative time (p = 0.021) were also significant predictors of adverse outcomes. Multivariate analysis identified elevated CRP (OR 2.1, 95% CI 1.5–2.9), low albumin (OR 1.8, 95% CI 1.3–2.5), and blood loss > 500 mL (OR 2.4, 95% CI 1.7–3.4) as independent predictors of postoperative complications. Conclusions: Preoperative inflammatory markers, nutritional status, ASA score, comorbidities, and intraoperative factors like blood loss significantly influence postoperative outcomes in colorectal cancer surgery. Recognizing these risk factors allows for better preoperative optimization and surgical planning, potentially reducing postoperative morbidity and mortality. Full article

The most commonly used objective function in structural optimization is weight minimization. Nodal displacements, compliance, the first natural frequency of vibration, the critical load factor concerning global stability, and others can also be considered additional objective functions. This paper aims to propose seven innovative many-objective structural optimization problems (MOSOPs) applied to 25-, 56-, 72-, 120-, and 582-bar trusses, not yet presented in the literature, in which the main objectives, in addition to the structure’s weight, refer to the structures’ vibrational and stability aspects. These characteristics are essential in designing structural models, such as the natural frequencies of vibration and load factors concerning global stability. Such new MOSOPs have more than three objective functions and are called many-objective structural optimization problems. The chosen objective functions refer to the structure’s weight, the natural frequencies of vibration, the difference between some of the natural frequencies of vibration, the critical load factor concerning the structure’s global stability, and the difference between some of its load factors. The sizing design variables are the cross-sectional areas of the bars (continuous or discrete). The methodology involves the finite element method (FEM) to obtain the objective functions and constraints and multi-objective evolutionary algorithms (MOEAs) based on differential evolution to solve the MOSOPs analyzed in this study. In addition, multi-criteria decision-making (MCDM) is adopted to extract the solutions from the Pareto fronts according to the artificial decision-maker’s (DM) preference scenarios, and the complete data for each chosen solution are provided. For the MOSOP with seven objective functions, it is possible to observe variations in the final weights of the optimum designs, considering the hypothetic scenarios, of 21.09% (25-bar truss), 289.73% (56-bar truss), 70.46% (72-bar truss), 45.35% (120-bar truss), and 74.92% (582-bar truss). Full article

Adolescent Physical Health is crucial for personal growth, family well-being, and the future of the nation, serving as an engine for healthier, sustainable social transformation. In recent years, the continuing decline in Adolescent Physical Health has become a global problem, with adolescents in various countries and regions facing different physical issues and challenges. The aim of this study is to explore the content structure, supply characteristics, and potential problems of current policies using a sample of Chinese Adolescent Physical Health policy documents in order to provide policy optimization recommendations for the promotion of Adolescent Physical Health, both in China and worldwide. Taking 33 Adolescent Physical Health policies enacted at the national level in China from 1979 to 2023 as a research sample, an analytical framework based on the three dimensions of policy tools, facilitating elements, and policy strength was constructed. Using the content analysis method, the policy texts were individually coded in order to analyze the content structure and supply characteristics of China’s Adolescent Physical Health policy, allowing research conclusions to be drawn and policy recommendations to be put forward. Through quantitative statistical analyses, we found that Chinese Adolescent Physical Health policies tend to use supply- and environment-side policy tools, while demand-side policy tools are less frequently used, leading to problems such as an over-reliance on supply-side policy tools and under-use of demand-side policy tools. Physical education teaching is dominant in the facilitating elements dimension, with an overall discrete distribution of characteristics. The types of policies are mainly notices, with a lack of strong normative documents such as laws, regulations, and statutes; therefore, the overall policy strength is weak. Accordingly, it is recommended that the top-level design of policy for Adolescent Physical Health promotion be continuously optimized in three key areas: enhancing the internal structure of policy instruments, improving the distribution of facilitating elements and policy tools, and strengthening the implementation of policies. Full article

Traditional wastewater treatment processes still encounter challenges such as the limited treatment efficiency and excessive greenhouse gas emissions, which restrict their application in environmentally sustainable practices. This study developed an A/O biofilm system and assessed the impact of inoculating the system with the heterotrophic nitrification–aerobic denitrification (HN–AD) strain Alcaligenes faecalis WT14 on pollutant removal efficiency and greenhouse gas emissions. A continuous monitoring experiment was conducted over 140 days, comparing the system inoculated with WT14 (the T_WT14 system) and the non-inoculated system (the CK system). The results demonstrated that the T_WT14 system outperformed the CK system in pollutant removal, with higher NH₄⁺-N, TN, and COD removal efficiencies of 11.22%, 21.96%, and 12.51%, respectively, and the quality of discharge water from T_WT14 maintaining compliance with national discharge standards. This improvement underscores the positive impact of inoculation with the WT14 strain on enhancing the pollutant removal performance of the A/O biofilm system. Regarding greenhouse gas emissions, the T_WT14 system exhibited a significantly higher N₂O emission flux in the aeration tank compared with the CK system, while CO₂ and CH₄ emissions were predominantly concentrated in the anaerobic tank. Global warming potential (GWP) analysis showed no significant difference in the total average GWP between the two systems. However, the T_WT14 system demonstrated a lower GWP per unit of TN removed, highlighting its superior ecological benefits. Environmental factor analysis revealed that the temperature, pH, humidity, and salinity had significant impacts on both pollutant removal efficiency and greenhouse gas emissions. Additionally, microbial community analysis indicated that inoculation with the WT14 strain enhanced microbial diversity and richness within the A/O biofilm system, with Alcaligenes and norank_f_JD30-KF-CM45 playing key roles in nitrogen removal. This study provides valuable insights for optimizing A/O biofilm system design and offers scientific guidance for the sustainable upgrading of wastewater treatment technologies. Full article

Natural broadleaf forests (NBFs) are the most abundant zonal vegetation type in subtropical regions. Understanding the mechanisms influencing stand productivity in NBFs is important for developing “nature-based” solutions for climate change mitigation. However, minimal research has captured the effects of nonlinearities and feature interactions that often have nonlinear impacts on stand productivity and influencing factors. To address this research gap, we used continuous forest inventory data, and a machine learning model for stand productivity of NBFs was constructed. Subsequently, through leveraging the interpretable machine learning framework of the SHapley Additive explanation (SHAP) and partial dependence plot, we determined global and local explanations of the influencing factors of stand productivity. Our findings indicate the following: (1) The Autogluon model performed the strongest based on R², RMSE, and rRMSE metrics. (2) The basal area (BA), neighborhood comparison of diameter at breast height (NC), and stand age (AGE) were the key influencing factors. Stand productivity increased with increasing BA and decreased with increasing NC and AGE. BA was maintained above 15 m²ha⁻¹ and NC was maintained below 0.45, which represent favorable conditions for NBFs to maintain optimal growth. (3) SHAP interaction values were calculated to determine the effects of the five major interactions on stand productivity. Our study provides a reference for the sustainable management of NBFs, thereby highlighting the important role of forests in mitigating climate change. Full article

With the advent of a variety of vaccines against viral infections, there are multiple viruses that can be prevented via vaccination. However, breakthrough infections or uncovered strains can still cause vaccine-preventable viral infections (VPVIs). Therefore, timely diagnosis, treatment, and surveillance of these viruses is critical to patient care and public health. Point-of-care (POC) viral diagnostics tools have brought significant improvements in the detection and management of VPVIs. These cutting-edge technologies enable prompt and accurate results, enhancing patient care by facilitating timely treatment decisions. This review delves into the advancements in POC testing, including antigen/antibody detection and molecular assays, while focusing on their impact on the diagnosis, treatment, and surveillance of VPVIs such as mpox, viral hepatitis, influenza, flaviviruses (dengue, Zika, and yellow fever virus), and COVID-19. The role of POC tests in monitoring viral infection is crucial for tracking disease progression and managing outbreaks. Furthermore, the application of POC diagnostics has shown to be vital for public health strategies. In this review, we also highlight emerging POC technologies such as CRISPR-based diagnostics and smartphone-integrated POC devices, which have proven particularly beneficial in resource-limited settings. We underscore the importance of continued research to optimize these diagnostic tools for wider global use for mpox, viral hepatitis, influenza, dengue, and COVID-19, while also addressing current challenges related to their sensitivity, specificity, availability, efficiency, and more. Full article