The build-in electric field derived from oxygen vacancy in Co-based electrocatalysts have become important for energy storage and conversion.

The significance of small-strain stiffness (Gmax) of saturated composite soils are still of great concern in practice, due to the complex influence of fines on soil fabric. This paper presents an experimental investigation conducted through comprehensive bender element tests on Gmax of marine silty sand. Special attention is paid to the influence of initial effective confining pressure ( σ c 0 ′ ), global void ratio (e) and fines content (FC) on Gmax of a marine silty sand. The results indicate that under otherwise similar conditions, Gmax decreases with decreasing e or FC, but decreases with increasing FC. In addition, the reduction rate of Gmax with e increasing is not sensitive to σ c 0 ′ , but obviously sensitive to changes in FC. The equivalent skeleton void ratio (e*) is introduced as an alternative state index for silty sand with various FC, based on the concept of binary packing material. Remarkably, the Hardin model is modified with the new state index e*, allowing unified characterization of Gmax values for silty sand with various FC, e, and σ c 0 ′ . Independent test data for different silty sand published in the literature calibrate the applicability of this proposed model.

BackgroundThe 2019 novel coronavirus disease (COVID-19) outbreak affected people’s lifestyles and increased their risk for depressive and anxiety symptoms (depression and anxiety, respectively hereafter). We assessed depression and anxiety in residents of Macau during “the 6.18 COVID-19 outbreak” period and explored inter-connections of different symptoms from the perspective of network analysis.MethodsIn this cross-sectional study, 1,008 Macau residents completed an online survey comprising the nine-item Patient Health Questionnaire (PHQ-9) and seven-item Generalized Anxiety Disorder Scale (GAD-7) to measure depression and anxiety, respectively. Central and bridge symptoms of the depression-anxiety network model were evaluated based on Expected Influence (EI) statistics, while a bootstrap procedure was used to test the stability and accuracy of the network model.ResultsDescriptive analyses indicated the prevalence of depression was 62.5% [95% confidence interval (CI) = 59.47–65.44%], the prevalence of anxiety was 50.2% [95%CI = 47.12–53.28%], and 45.1% [95%CI = 42.09–48.22%] of participants experienced comorbid depression and anxiety. “Nervousness-Uncontrollable worry” (GADC) (EI = 1.15), “Irritability” (GAD6) (EI = 1.03), and “Excessive worry” (GAD3) (EI = 1.02) were the most central symptoms, while “Irritability” (GAD6) (bridge EI = 0.43), “restlessness” (GAD5) (bridge EI = 0.35), and “Sad Mood” (PHQ2) (bridge EI = 0.30) were key bridge symptoms that emerged in the network model.ConclusionNearly half of residents in Macau experienced comorbid depression and anxiety during the 6.18 COVID-19 outbreak. Central and bridge symptoms identified in this network analysis are plausible, specific targets for treatment and prevention of comorbid depression and anxiety related to this outbreak.

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