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Based on the fact that sports culture, as an important part of social culture, is also one of the key contents of the construction of social-ecological civilization, this paper proposes a smart sports training ecosystem based on the integration and development of artificial intelligence and sports culture sports training. Investigating the Evolution of Sports Culture and Athletic Training through the Lens of Intelligent Sports The foreground and background separation is used to obtain the user’s skeletal features, and the initial skeletal feature data is filtered for the abnormal data that will cause the skeletal data-position deviation, followed by optimizing the monitoring and guidance functions of the smart sports training ecosystem through the Hidden Markov-based motion recognition, and an example analysis is conducted to optimize the operation of the smart sports training ecosystem. The results show that: in the angle detection results during running, the ankle joint angle change interval of the participants in the test is [85.44°, 123.699°], and the average value is 404.5695°. The initial change range of ankle joint angle of the athletes at the moment of landing is 105.73°~108.98°, which confirms that the intelligent sports training ecosystem can provide users with high-quality interactive experience and real-time feedback on the changes of their own sports status. This study can improve the athletic ability and sports culture literacy of college students, and provide a theoretical basis and practical reference for the development path of sports culture and sports training under the perspective of smart sports.

Based on multi‐model large‐ensemble experiments provided by Polar Amplification Model Intercomparison Project (PAMIP), we investigate the influence of the projected sea ice loss in Barents‐Kara Seas (BKS) and Sea of Okhotsk (SOK) on the Arctic stratospheric polar vortex (SPV). Results show that future BKS sea ice reduction leads to a weakened SPV during November‐February by enhancing the upward‐propagating planetary wave 1, which is more pronounced during Quasi‐Biennial Oscillation (QBO) easterly than westerly phase. Through weakening the upward‐propagating planetary wave 2, future SOK sea ice reduction is favorable for a strengthened SPV during January‐April. Inter‐model spread in the magnitudes of SPV responses to BKS sea ice reduction can be largely explained by the divergent planetary wave responses, but less so for SOK sea ice reduction. Results from a linearized baroclinic model further validate the importance of the planetary‐scale wave responses in explaining the differing SPV responses to sea‐ice loss over the two regions. Plain Language Summary: Arctic sea ice reduction influences the Northern Hemispheric weather and climate through modulating Arctic stratospheric polar vortex, which is a band of strong westerly encircling the pole during winter at ∼15–40 km above the Earth's surface. However, sea ice reduction over different regions could lead to different effects on the polar vortex. Here, we compare the effects of future sea ice reduction over the Barents‐Kara Seas, in the far‐north Atlantic Ocean, and the Sea of Okhotsk, in the northwest Pacific Ocean. We use carefully designed numerical simulations to estimate the effects of sea ice reduction, separately in the above‐mentioned two regions, on the polar vortex. Sea ice reduction over the Barents‐Kara Seas weakens the polar vortex, whereas sea ice reduction over Sea of Okhotsk strengthens the polar vortex. These contrasting effects are explained by opposing changes in wave activity entering the stratosphere from below. Barents‐Kara sea ice reduction leads to the strengthened upward propagating planetary waves, which break in the stratosphere and slow the polar vortex. Conversely, Okhotsk sea ice loss reduces upward waves and strengthens the polar vortex. Key Points: Barents‐Kara and Sea of Okhotsk sea ice loss weakens and strengthens polar vortex, respectively, with attendant changes in SSW frequencyPlanetary wave responses to Barents‐Kara and Okhotsk sea ice loss interfere constructively and destructively with mean flow, respectivelyPolar vortex weakening induced by Barents‐Kara sea ice loss is greater during easterly than westerly Quasi‐Biennial Oscillation phase [ABSTRACT FROM AUTHOR]

The influence of acute glycemic variability (GV) on early outcomes of patients after cardiac surgery remains not fully determined. We performed a systematic review and meta-analysis to evaluate the association between acute GV and in-hospital outcomes of patients after cardiac surgery. Relevant observational studies were obtained by search of electronic databases including Medline, Embase, Cochrane Library, and Web of Science. A randomized-effects model was selected to pool the data by incorporating the influence of potential heterogeneity. Nine cohort studies involving 16 411 patients after cardiac surgery were included in this meta-analysis. Pooled results showed that a high acute GV was associated with an increased risk of major adverse events (MAE) during hospitalization for patients after cardiac surgery [odds ratio [OR]: 1.29, 95% CI: 1.15 to 1.45, p<0.001, I22=38%]. Sensitivity analysis limited to studies of on-pump surgery and GV evaluated by coefficient of variation of blood glucose showed similar results. Subgroup analysis suggested that a high acute GV was related to an increased incidence of MAE in patients after coronary artery bypass graft, but not for those after isolated valvular surgery (p=0.04), and the association was weakened after adjustment of glycosylated hemoglobin (p=0.01). Moreover, a high acute GV was also related to an increased risk of in-hospital mortality (OR: 1.55, 95% CI: 1.15 to 2.09, p=0.004; I22=0%). A high acute GV may be associated with poor in-hospital outcomes in patients after cardiac surgery. [ABSTRACT FROM AUTHOR]