Circadian misalignment on submarines and other non-24-h environments – from research to application

Circadian clocks have important physiological and behavioral functions in humans and other organisms, which enable organisms to anticipate and respond to periodic environmental changes. Disturbances in circadian rhythms impair sleep, metabolism, and behavior. People with jet lag, night workers and shift workers are vulnerable to circadian misalignment. In addition, non-24-h cycles influence circadian rhythms and cause misalignment and disorders in different species, since these periods are beyond the entrainment ranges. In certain special conditions, e.g., on submarines and commercial ships, non-24-h watch schedules are often employed, which have also been demonstrated to be deleterious to circadian rhythms. Personnel working under such conditions suffer from circadian misalignment with their on-watch hours, leading to increased health risks and decreased cognitive performance. In this review, we summarize the research progress and knowledge concerning circadian rhythms on submarines and other environments in which non-24-h watch schedules are employed.

Sodium chloride exacerbates dextran sulfate sodiuminduced colitis by tuning proinflammatory and antiinflammatory lamina propria mononuclear cells through p38/MAPK pathway in mice

AIM To investigate the influence of high salt on dextran sulfate sodium(DSS)-induced colitis in mice and explore the underlying mechanisms of this effect.METHODS DSS and NaC l were used to establish the proinflammatory animal model. We evaluated the colitis severity. Flow cytometry was employed for detecting the frequencies of Th1, macrophages and Tregs in spleen, mesenteric lymph node and lamina propria. The important role of macrophages in the promotion of DSS-induced colitis by NaCl was evaluated by depleting macrophages with clodronate liposomes. Activated peritoneal macrophages and lamina propria mononuclear cells(LPMCs) were stimulated with NaCl, and proteins were detected by western blotting. Cytokines and inflammation genes were analyzed by enzyme-linked immunosorbent assay and RT-PCR, respectively.RESULTS The study findings indicate that NaC l up-regulates the frequencies of CD11b^+ macrophages and CD4^+IFN-γ^+IL-17^+ T cells in lamina propria in DSS-treated mice. CD3^+CD4^+CD25^+Foxp^3+ T cells, which can secrete high levels of IL-10 and TGF-β, increase through feedback in NaCl-and DSS-treated mice. Furthermore, clodronate liposomes pretreatment significantly alleviated DSSinduced colitis, indicating that macrophages play a vital role in NaCl proinflammatory activity. NaCl aggravates peritoneal macrophage inflammation by promoting the expressions of interleukin(IL)-1, IL-6 and mouse inducible nitric oxide synthase. Specifically, high NaCl concentrations promote p38 phosphorylation in lipopolysaccharide-and IFN-γ-activated LPMCs mediated by SGK1. CONCLUSION Proinflammatory macrophages may play an essential role in the onset and development of NaCl-promoted inflammation in DSS-induced colitis. The underlining mechanism involves up-regulation of the p38/MAPK axis.

TSC prediction and dynamic control of BOF steelmaking with state-of-the-art machine learning and deep learning methods

Mathematical(data-driven)models based on state-of-the-art(SOTA)machine learning and deep learning models and data collected from 12,786 heats were established to predict the values of temperature,sample,and carbon(TSC)test,including temperature of molten steel(TSC-Temp),carbon content(TSC-C)and phosphorus content(TSC-P),which made prepa-ration for eliminating the TSC test.To maximize the prediction accuracy of the proposed approach,various models with different inputs were implemented and compared,and the best models were applied to the production process of a Hesteel Group steelmaking plant in China in the field.The number of tabular features(hot metal information,scrap,additives,blowing practices,and preset values)was expanded,and time series(off-gas profiles and blowing practice curves)that could reflect the entire steelmaking process were introduced as inputs.First,the latest machine learning models(LightGBM,CatBoost,TabNet,and NODE)were used to make predictions with tabular features,and the best coefficient of determination R^(2)values obtained for TSC-P,TSC-C and TSC-Temp predictions were 0.435(LightGBM),0.857(Cat-Boost)and 0.678(LightGBM),respectively,which were higher than those of classic models(backpropagation and support vector machine).Then,making predictions was performed by using SOTA time series regression models(SCINet,DLinear,Informer,and MLSTM-FCN)with original time series,SOTA image regression models(NesT,CaiT,ResNeXt,and GoogLeNet)with resized time series,and the proposed Concatenate-Model and Parallel-Model with both tabular features and time series.Through optimization and comparisons,it was finally determined that the Concatenate-Model with MLSTM-FCN,SCINet and Informer as feature extractors performed the best,and its R^(2)values for predicting TSC-P,TSC-C and TSC-Temp reached 0.470,0.858 and 0.710,respectively.Its field test accuracies for TSC-P,TSC-C and TSC-Temp were 0.459,0.850 and 0.685,respectively.A related importance analysis was carried out,and dynamic control methods based on prediction values were proposed.

Influence of Ca treatment on particle-microstructure relationship in heat-affected zone of shipbuilding steel with Zr-Ti deoxidation after high-heat-input welding

The effects of Ca treatment on the particle, microstructure, and toughness of heat-affected zone (HAZ) of shipbuilding steel with Zr-Ti deoxidation after high-heat-input welding were investigated. The simulated welding at a high-heat-input welding of 200 kJ/cm was carried out using Gleeble-3800 welding simulation. Then, particle characteristics were characterized using an Aztec-Feature automatic particle analysis system. Additionally, an in-situ observation experiment was performed to study the relationships between particle and microstructure by high-temperature confocal laser scanning microscopy (HT-CLSM). The results indicated that the average HAZ toughness at -40 ℃ was increased from 183 to 290 J by adding 0.0026 wt.% Ca. Meanwhile, the formation of acicular ferrite ratio was increased from 49.34% to 60.28% due to the addition of Ca. The scanning electron microscopy results clearly showed that CaO-Al_(2)O_(3)-TiOx-ZrO_(2)-MnS particles could act as effective nucleation sites for the formation of acicular ferrite, which has been verified by the observation of the particle-microstructure relationship under HT-CLSM. Furthermore, particle characterization results show that the cumulative frequency of particles with the size of 1-3 lm was 33.2% in HAZ of Zr-Ti shipbuilding steel but 66.2% in HAZ of Zr-Ti-Ca shipbuilding steel.