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The coastal zone is sensitive to sea–land interaction, making it an ideal place to study the transgression–regression process in Quaternary coastal areas. Based on the stratigraphic and lithologic characteristics of two Quaternary drill cores (DZ01 and DZ02) in the coastal zone of Quanzhou Bay, Fujian Province, a stratigraphic chronological framework was established by using AMS-14C and OSL dating methods. Combined with the statistical analysis results of geochemical element content of indicating facies in modern sediments in Quanzhou Bay, the geochemical element ratios, foraminifers, and ostracods' environmental indicators were used to identify transgressive strata since the Late Pleistocene. The transgression–regression processes since the MIS 3 in Quanzhou Bay were analyzed by comparing it with the regional borehole data. The results show that the Sr/Ba and Mn/Fe values vary significantly in the marine sediments at different water depths in Quanzhou Bay, making them suitable as indicator elements in the marine and sea–land transitional sediments in the Quanzhou Bay coast, with the limit values of Sr/Ba

Despite significant progress in the Prognostics and Health Management (PHM) domain using pattern learning systems from data, machine learning (ML) still faces challenges related to limited generalization and weak interpretability. A promising approach to overcoming these challenges is to embed domain knowledge into the ML pipeline, enhancing the model with additional pattern information. In this paper, we review the latest developments in PHM, encapsulated under the concept of Knowledge Driven Machine Learning (KDML). We propose a hierarchical framework to define KDML in PHM, which includes scientific paradigms, knowledge sources, knowledge representations, and knowledge embedding methods. Using this framework, we examine current research to demonstrate how various forms of knowledge can be integrated into the ML pipeline and provide roadmap to specific usage. Furthermore, we present several case studies that illustrate specific implementations of KDML in the PHM domain, including inductive experience, physical model, and signal processing. We analyze the improvements in generalization capability and interpretability that KDML can achieve. Finally, we discuss the challenges, potential applications, and usage recommendations of KDML in PHM, with a particular focus on the critical need for interpretability to ensure trustworthy deployment of artificial intelligence in PHM. [ABSTRACT FROM AUTHOR]

Simple Summary: This study investigated different feeding frequencies for white shrimp in intensive aquaculture using automatic feeders, and found that feeding 6–8 times/day resulted in higher growth, better feed conversion, improved digestive and antioxidant capacity, and higher profits compared to manual feeding. We believe that our study makes a significant contribution to the literature by demonstrating the effectiveness of automatic feeders and different feeding frequencies in white shrimp aquaculture. The findings highlight the benefits of feeding 6–8 times/day, leading to improved growth, feed utilization, and antioxidant capacity, with economic advantages for intensive shrimp culture operations. Feeding frequency is crucial for the growth and development of white shrimp (Litopenaeus vannamei) at various life stages. Although higher feeding frequencies can enhance growth, manual feeding methods significantly increase labor costs. Automatic feeding systems offer a cost-effective and efficient alternative, yet their application in intensive shrimp culture remains under-researched. This study evaluates different feeding frequencies for L. vannamei in intensive aquaculture tanks, focusing on growth performance, survivability, feed utilization, digestive and antioxidant capacities, and economic viability. Juvenile shrimp (3.85 ± 0.3 g) were cultured for 63 days with feeding frequencies of 6, 8, 10, and 12 times/day (A6, A8, A10, and A12 groups, respectively) using automatic feeders, with a control group fed manually 6 times/day (M6). Results indicated that automatic feeding significantly improved final body weight, specific growth rate, and feed conversion ratio compared to manual feeding. Among automatic feeding groups, A6 and A8 showed optimal performance, with a quadratic regression identifying 7.83 times/day as the optimal frequency. While digestive enzyme activity remained consistent across groups, A6 and A8 demonstrated significantly higher antioxidant enzyme levels (superoxide dismutase (SOD) and glutathione peroxidase (GPx)) and lower lipid peroxidation (MDA), suggesting superior digestive and antioxidant capacities. Pearson's correlation confirmed a positive relationship between SOD and GPx. Economically, the A8 group achieved the highest profitability. Consequently, a feeding frequency of 6–8 times/day using automatic feeders is recommended as an optimal and feasible strategy for intensive white shrimp culture in this life stage. [ABSTRACT FROM AUTHOR]

Asymptomatic hyperuricemia（AH）is a common metabolic disease characterized by elevated serum concentrations of uric acid. When the serum uric acid exceeds the concentration threshold, urate crystals will crystallize and deposit in the synovium, cartilage and kidney to induce acute arthritis. Although urate crystals are the gold standard for the diagnosis of gout, not all patients with urate crystals deposition eventually develop gout. Whether urate crystal deposition will eventually cause the attack of gout depends on the joint action of multiple factors, such as urate crystal-related pathogenic genes, immune status, cartilage damage, synovial fluid environment and so on. To identify the pathogenic factors and trigger mechanism of urate crystals in the process of AH developing into gout, it can provide a basis for early screening, stratified management and individualized treatment of gout in patients with AH.