Barely Significant

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4 a), shrinking from 7.972 million km2 to 7.769 million km2, and then increasing to 8.126 million km2, indicating that the tourism eco-efficiency of Fujian Province is in an elevated trend, mainly because the cities in Fujian Province have paid more attention to green ecological development in recent years, and the tourism development model has been optimized, which has played a protective role for the ecological environment; From the shape index (Fig. 4 c), the long half axis of the standard deviation ellipse is always larger than the short half axis, and the spatial distribution of tourism eco-efficiency in Fujian Province shows an obvious “northeast–southwest” directional distribution pattern.
ctionality of the spatial distribution gradually decreases in this period and the spatial agglomeration feature gradually becomes significant; From the trend of the long half axis of the ellipse, it shortens from 1.529 in 2011 to 1.488 in 2014, and then gradually increases until 1.569 in 2020, with an overall trend of continuous increase, indicates that the clustering of tourism eco-efficiency gradually decreases in the "northeast-southwest" direction.
The shape index decreases in 2011–2012 and 2019–2020, indicating that the directionality of the spatial distribution of tourism eco-efficiency increases in this period and regional differences increase, while the shape index of 2012–2019 shows an increasing trend and the shape tends to be more and more positive circle, implying that the directionality of the spatial distribution gradually decreases in this period and the spatial agglomeration feature gradually becomes significant; From the trend of the long half axis of the ellipse, it shortens from 1.529 in 2011 to 1.488 in 2014, and then gradually increases until 1.569 in 2020, with an overall trend of continuous increase, indicates that the clustering of tourism eco-efficiency gradually decreases in the "northeast-southwest" direction.
highly significantqualifiedgold
In addition, although statistical methods can determine that certain indicators have a significant impact on the risk of death in patients with sepsis, statistical methods cannot rank the impact of multiple highly significant indicators on the mortality of sepsis patients, in order to further determine which indicators are the most core indicators.