Subcritical water extraction (SWE) uses hot compressed water as an effective solvent for both polar and nonpolar compounds and has been developed as an environmentally benign extraction technology for natural materials. Polysaccharides as one of the main ingredients in Dendrobium plants showed obvious biological activity. Thus, SWE of polysaccharides obtained from Dendrobium nobile Lindl. was investigated in this work. The response surface methodology (RSM) was combined with a Box–Behnken design to evaluate the influence that the three independent variables had on the response. The optimal extraction conditions (determined via RSM) were 129.83 °C extraction temperature, 16.71 min extraction time, and 1.12 MPa extraction pressure. The maximum predicted polysaccharide yield was 20.67%, which corresponded well with the experiential extraction (21.88%). The polysaccharides obtained from either the stirring extraction, refluxing extraction, ultrasound extraction, or SWE methods were compared, and the extraction processes were modeled. The molecular weight, monosaccharide composition, and antioxidative activities of the polysaccharides were analyzed.
Mixed-valence compounds are of great interest due to their interesting properties and wide applications. Recently, gold (Au) chemistry has experienced an unprecedented development. However, Au with mixed-valence states in Au-O compounds has not been reported thus far. Here, two hitherto unknown AuO and AuS compounds with mixed-valence character were identified with the aid of first-principles swarm structure searching calculations. AuO consists of quasi-square AuO moiety and AuO octahedron in which Au shows the mixed-valence states of III and V, the first example in Au-O binary compounds. AuS contains the linear AuS and quasi-square AuS units exhibiting Au mixed-valence states. The analysis of electronic property demonstrates that AuO and AuS are narrow band gap semiconductors with strong hybridization between Au 5d and O 2p or S 3p. With the increase of pressure, Au-O and Au-S compounds show completely different thermodynamic stabilities, resulting from distinct shifting of pressure-induced atomic orbital energy levels of O and S atoms. Our work provides an opportunity for understanding mixed-valence character in Au-O and Au-S compounds.
Changes in the land use/cover alter the Earth system processes and affect the provision of ecosystem services, posing a challenge to achieve sustainable development. In the past few decades, the Yellow River (YR) basin faced enormous social and environmental sustainability challenges associated with environmental degradation, soil erosion, vegetation restoration, and economic development, which makes it important to understand the long-term land use/cover dynamics of this region. Here, using three decades of Landsat imagery (17,080 images) and incorporating physiography data, we developed an effective annual land use/cover mapping framework and provided a set of 90 m resolution continuous annual land use/cover maps of the YR basin from 1986 to 2018 based on the Google Earth Engine and the Classification and Regression Trees algorithm. The independent random sampling validations based on the field surveys (640 points) and Google Earth (3456 points) indicated that the overall accuracy of these maps is 78.3% and 80.0%, respectively. The analysis of the land system of the YR basin showed that this region presents complex temporal and spatial changes, and the main change patterns include no change or little change, cropland loss and urban expansion, grassland restoration, increase in orchard and terrace, and increase in forest during the entire study period. The major land use/cover change has occurred in the transitions from forests, grasslands, and croplands to the class of orchard and terrace (19.8% of all change area), which not only increase the greenness but also raised the income, suggesting that YR progress towards sustainable development goals for livelihood security, economic growth, and ecological protection. Based on these data and analysis, we can further understand the role of the land system in the mutual feedback between society and the environment, and provide support for ecological conservation, high-quality development, and the formulation of sustainable management policies in this basin, highlighting the importance of continuous land use/cover information for understanding the interactions between the human and natural systems.
Background Intolerance of uncertainty (IU) is considered to be associated with emotional disorders, such as generalized anxiety disorder (GAD), depression, obsessive compulsive disorder (OCD), and social anxiety. Therefore, a comprehensive instrument to measure IU is needed. The purposes of the present study were as follows: 1) developing a Chinese version of the Intolerance of Uncertainty Inventory (CIUI) and 2) measuring the reliability and validity of CIUI. Methods We translated the Intolerance of Uncertainty Inventory (IUI) into Chinese. A sample consisting of Chinese college students from three universities was used to evaluate the internal consistency, test–retest reliability, and validity of the CIUI. Participants answered the CIUI, IUS-12, GAD-7, BDI-II, and PSWQ. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were run to explore the factor structure of CIUI. Results The results demonstrated an acceptable internal consistency for CIUI (Part A of CIUI [CIUIA]: α = 0.920; Part B of CIUI [CIUIB]: α = 0.947) and test–retest reliability (CIUIA: ICC = 0.788; CIUIB: ICC = 0.859). The results of EFA and CFA all supported a two-factor structure for CIUIA (Intolerance of the unexpected and difficulty waiting in an uncertain situation and Intolerance of uncertainty and of uncertain situations) and a four-factor structure for CIUIB (Overestimation, Control, Uncertainty makes one feel stressful, and Reassurance), and acceptable validity was obtained. Conclusion The CIUI is an appropriate instrument for measuring IU in Chinese populations. Future studies should confirm the psychometric properties using a comprehensive sample.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.