Dam Safety Evaluation Method after Extreme Load Condition Based on Health Monitoring and Deep Learning.

The safety operation of dams after extreme load is an important frontier research topic in the field of dam engineering. The dam health monitoring provides a reliable data basis for a safety evaluation after extreme loads. This study proposes a novel data-driven fusion model for a dam safety evaluation after extreme load based on monitoring data derived by sensors. First, the relationship between dam environmental quantity and effect quantity is deeply excavated based on bidirectional long short-term memory (BiLSTM) network, which is a deeply improved LSTM model. Aiming at the parameter optimization problem of BiLSTM model, sparrow search algorithm (SSA), which is an advanced optimization algorithm, is integrated. Second, conducting the constructed SSA-BiLSTM model to estimate the change law of dam effect quantity after the extreme load. Finally, the Mann-Whitney U-test theory is introduced to establish the evaluation criterion of the dam safety state. Project case shows that the multiple quantitative prediction accuracy evaluation indicators of the proposed method are significantly superior to the comparison method, with mean absolute percentage error (MAPE) and mean absolute error (MAE) values decreasing by 30.5% and 27.8%, respectively, on average. The proposed model can accurately diagnose the dam safety state after the extreme load compared with on-site inspection results of the engineering department, which provides a new method for dam safety evaluation.

Extreme environmental doses of diisobutyl phthalate exposure induce oxidative stress and DNA damage in earthworms (Eisenia fetida): Evidence at the biochemical and molecular levels.

Diisobutyl phthalate (DIBP), as a plasticizer, is widely used and has caused many extreme soil contamination scenarios, posing potential risks to soil fauna. However, the toxic effects and mechanisms of DIBP on soil fauna remain unclear. In this study, earthworms (Eisenia fetida) were used as model animals to explore the subchronic toxicity of extreme DIBP soil exposure (300, 600, and 1200 mg/kg) for 28 days. The results showed that the level of reactive oxygen species (ROS) and the contents of malondialdehyde (MDA) and 8-hydroxydeoxyguanosine (8-OHdG) in E. fetida were significantly increased during continuous DIBP exposure. In addition, the activities of superoxide dismutase (SOD), catalase (CAT) and peroxidase (POD) were significantly inhibited while glutathione S-transferase (GST) activity was activated during continuous exposure. Integrated biological response (IBR) analysis showed that DIBP had positive dose-dependent toxicity and negative time-dependent toxicity to E. fetida, and SOD/CAT were selected as sensitive biomarkers. The molecular docking study found that DIBP could stably bind to SOD/CAT through hydrogen bonding, which further proved its sensitivity. This study provides primary data for ecological and environmental risk assessment of extreme dose DIBP soil pollution.

A surrogate model for estimating extreme tower loads on wind turbines based on random forest proximities.

In the present paper, we present a surrogate model, which can be used to estimate extreme tower loads on a wind turbine from a number of signals and a suitable simulation tool. Due to the requirements of the International Electrotechnical Commission (IEC) Standard 61400-1, assessing extreme tower loads on wind turbines constitutes a key component of the design phase. The proposed model imputes tower loads by matching observed signals with simulated quantities using proximities induced by random forests. In this way, the algorithm's adaptability to high-dimensional and sparse settings is exploited without using regression-based surrogate loads (which may display misleading probabilistic characteristics). Finally, the model is applied to estimate tower loads on an operating wind turbine from data on its operational statistics.

Ammonium Salts Promote Functional Adaptation of Rat Erythrocytes on the Model of Forced Swimming.

Ammonium, an end-product of catabolism, in low doses can promote adaptation of metabolic pathways in erythrocytes under conditions of extreme physical exercise. We compared the effects of two ammonium salts, ammonium chloride and ammonium carbonate, in two doses on biochemical parameters of rat erythrocytes 1 day after extreme physical exercise in a 4-week cycle of forced swimming. Of 16 analyzed parameters, the maximum number of significant shifts from the control was revealed in the groups of rats receiving ammonium chloride in doses of 20 and 10 mg/kg, and the minimal number of differences was found in groups treated with ammonium carbonate in the same doses. The comparison of the levels of reduced glutathione and 2.3-bisphosphoglicerate and activities of 5'-nucleotidase and Ca2+- and Na/K-ATPases attested to more rigorous control of the mechanism of oxygen delivery to tissues by erythrocytes after administration of ammonium chloride in a dose of 20 mg/kg.