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The associations of sleep duration and depressive status on cognitive function among the elderly remain controversial. This study aimed to investigate the associative effects and mediating mechanisms between sleep duration and depressive status on cognitive function in elderly adults. Participants were recruited from cross-sectional and cohort surveys of the Chinese Longitudinal Healthy Longevity Survey (CLHLS). We identified thresholds for sleep duration and depression and used logistic regression to explore their independent and joint effects on cognitive impairment. Further, we analyze the mediating effects of depressive status on the association between sleep duration and cognitive function. Of 13840 elderly (median age: 84 years, female: 54.6 %), 2835 (20.5 %) had cognitive impairment. Compared with those who slept 6–8 h, the ORs (95% CIs) for those who slept < 6 h and > 8 h were 0.98 (0.85, 1.12) and 1.48 (1.32, 1.66). Compared with non-depressed, the OR (95% CI) for the depressed participants was 1.74 (1.53, 1.98). Compared with those with sleep 6–8 h and none-depression, those with sleep > 8 h and depression had the highest odds of cognitive impairment (OR = 2.40, 95% CI : 1.88–3.07). Additionally, Compared with those who slept 6–8 h, the associations between depression-mediated short and long sleep and cognitive impairment were 51.1 % and 6.5 %, respectively. Cross-sectional studies require caution in the interpretation of causal associations. Long sleep and depression were independently and jointly associated with higher odds of cognitive impairment among the Chinese elderly, and short sleep increased the risk of cognitive impairment by promoting the prevalence of depression. • Sleep duration and depressive status were found to have a J-shaped association with cognitive function. • The thresholds for sleep duration and depressive status were 6 h and 9 points. • Long sleep and depression have a joint effect on cognitive impairment. • Depression status mediated the association between sleep duration and cognitive function. [ABSTRACT FROM AUTHOR]

When on-site tests are performed in artificial ground freezing projects, the conventional analytical method for determining the soil temperature field often presents significant error under certain conditions, particularly when the temperature-measuring pipe is far removed from the freezing front. This paper proposes a new method—called the undetermined coefficient method (UCM)—that more accurately predicts the actual soil temperature field and position of the freezing front. The UCM comprises a new mathematical formula developed based on a series of model tests performed under three different conditions—no seepage, constant seepage, and sudden seepage—and a multiple data regression analysis-based method for determining the coefficients in the developed formula. The proposed UCM was compared to a conventional analytical method based on the results from model tests and from the construction of the cross-channel of Guangzhou Metro Line 11. The results indicated that the UCM presented higher stability and practical value than conventional alternatives and could accurately predict the actual soil temperature field and position of the freezing front. Therefore, the UCM is expected to be of high practical value in artificial ground-freezing operations. • A novel analytical method—the undetermined coefficient method (UCM)—is proposed. • A model test about different seepage condition was carried out. • The UCM can be applied to real large-scale artificial ground freezing operations. • The optimal measurement point positions in UCM were determined. [ABSTRACT FROM AUTHOR]