The two-stage Bayesian approach integrates prior knowledge from generic data in the first stage and updates it with specific data using Bayes’ theorem in the second stage. Focusing on the first stage, previous work assumed a time-dependent failure intensity function based on the two-parameter Weibull distribution, with independent prior distributions for the scale α and shape β parameters. The estimation of these prior distributions considered non-homogeneous failure count over total observed time data as generic information, referred to as the KT model. The present work introduces a model that estimates prior distributions using non-homogeneous and time-to-failure data (TTF model) and then compares its performance with the KT model. The TTF model leverages failure time data to estimate independent priors for the Weibull parameters through Particle Swarm Optimization (PSO), enabling a more detailed and flexible reliability assessment. Simulations using theoretical priors were conducted across various dataset configurations, with multiple PSO runs. Results demonstrated that the TTF model provides consistent and accurate estimates, closely aligning with the KT model while offering more precise distributions due to its use of detailed failure data. Although computational time increased for larger datasets, parallel computing proved effective in mitigating processing delays. These findings highlight the TTF model's potential as a robust tool for failure prediction and maintenance planning in reliability engineering.
Croton heliotropiifolius and Croton jacobinensis are species native to Brazil, commonly found in the Caatinga phytogeographic domain. Although some previous studies have reported the effects of seasonal factors on the chemical composition of the essential oils of these plants, information on variation in antioxidant activity across seasons remains scarce in the literature. In this context, the present study evaluated the influence of seasonality on the chemical composition and antioxidant activity of essential oils from C. heliotropiifolius (EOCH) and C. jacobinensis (EOCJ) collected during the year 2024. Yields ranged from 0.05 to 0.16% for EOCH and from 0.07 to 0.11% for EOCJ. Based on gas chromatography-mass spectrometry (GC/MS) analysis, 27 compounds in EOCH and 22 compounds in EOCJ were tentatively identified. E-caryophyllene (20.25 – 33.23%) was the most abundant compound in EOCH, whereas bicyclogermacrene (30.33 – 47.77%) stood out as the main compound in EOCJ across all seasons. Moderate results were obtained using the DPPH method, with EOCH and EOCJ showing higher antioxidant activity in summer (IC50 = 6.38 mg/mL) and spring (IC50 = 4.49 mg/mL), respectively. The results obtained clearly indicate the influence of seasonal variations on the chemical composition and antioxidant activity of EOCH and EOCJ.
Urbanization and the size of green areas can alter numerous environmental and biological factors, including the ecological interactions between plants and animals in urban areas. Urban green areas contribute positively to the maintenance of biodiversity, provide resources for pollinators, and bring numerous benefits to the population in terms of ecosystem services. This study aimed to evaluate the effect of urbanization and the size of green areas on the interaction networks between Leguminosae trees pollinated by bees and their floral visitors. The study was carried out in eight urban green spaces in Recife, a Brazilian metropolis, in northeastern Brazil, with 10 species of native and exotic Leguminosae trees. In general, (1) Trigona spinipes and Xylocopa frontalis showed greater interaction with the Leguminosae; (2) increases in urbanization reduces the number of flower/inflorescence, the number of total visits and the generality, despite increasing interaction evenness between the Leguminosae pollinated by bees and their floral visitors; (3) increases in the size of urban green areas favours the interaction evenness of networks, the selectivity of occasional pollinators and harbour more specialized plant species; (4) simultaneously, reductions in urbanization and increases in urban green area size are associated with increased specialization of Leguminosae species. Our study highlights that urban green areas in tropical cities have enormous potential to sustain plant communities and floral visitors/pollinators, especially native bees. To manage urban biodiversity in the long term, cooperation between policymakers, conservation organizations, scientists and the population is essential to understand how species interact in complex and diverse urban landscapes and their importance for human well-being.
The Dioscoreaceae, a family of monocotyledonous flowering plants comprising about 650 species across four genera, is prevalent in tropical regions and plays a vital role in diets across the Global South. Its edible tubers, known as yams, are both nutritional staples and widely used in traditional medicine. This review of 121 studies synthesizes knowledge on the traditional uses, biological activities, phytochemistry, nutritional value, and technological applications of Dioscoreaceae species. The most used species, Dioscorea alata and D. bulbifera, are employed across Asia, Africa, and South America to treat gastrointestinal disorders, diabetes, rheumatism, and infections. In Africa, species such as D. dregeana and D. smilacifolia are primarily used for inflammatory and respiratory conditions, while in Asia, particularly China and India, D. cirrhosa, D. japonica, and D. polystachya are associated with digestive, metabolic, and endocrine disorders. Phytochemical studies consistently identify steroidal saponins, pregnane glycosides, and phenanthrene glycosides, underscoring their potential for drug discovery. These species also exhibit diverse evaluated biological activities, including anti-inflammatory, anticancer, antidiabetic effects, supporting some of their traditional uses. With a global production of 75 million tons, yam tubers are nutrient-dense, supplying carbohydrates, proteins, and essential minerals to food-insecure populations. Additionally, polysaccharides from Dioscoreaceae demonstrate technological applications, including bioplastics, hydrogels, and functional food enhancement. Overall, this synthesis highlights the Dioscoreaceae family’s nutritional, medicinal, and technological significance, bridging traditional knowledge with modern applications, and emphasizing its cultural and innovative potential.
In today's dynamic industrial landscape, maintenance managers are increasingly seeking innovative approaches to enhance efficiency in maintenance decision-making and optimization processes. Among these approaches, Reinforcement Learning (RL) has emerged as a powerful tool, offering promising avenues for achieving optimal policies amidst the complexities of evolving environments and data intricacies. This paper presents a comprehensive literature review, aiming to illuminate the application of RL in the realm of maintenance optimization and decision-making support. Utilizing a systematic approach, relevant literature was carefully selected from leading databases including Scopus, Web of Science, and IEEE Xplore. Through rigorous analysis of the selected works, this study offers detailed insights into the current state of RL's deployment in maintenance optimization and decision-making, while also identifying prevailing limitations, challenges, and future trends in the field. By providing a comprehensive overview of RL's applications in maintenance optimization, this research contributes to a deeper understanding of its efficacy and potential, while also pinpointing key areas for further exploration and identifying major knowledge gaps. Ultimately, this endeavor seeks to catalyze advancements in maintenance strategies by addressing critical challenges and leveraging emerging trends in RL-based decision-making paradigms.
