Luminescent liquid crystalline polymers (LLCPs) show extensive application potentials, such as liquid crystal displays and circularly polarized luminescence. In this work, we employ a hydrogen-bonding strategy different from the traditional covalent-bonding method to fabricate LLCPs. First, the acceptor and donor of hydrogen bonding, (4,4′-dibutanoxy tetraphenylethylene)-1-pyridine (PTPEC4) and poly(2-vinyl terephthalic acid) (PPA), respectively, are successfully synthesized. Then, mixtures with different molar ratios (x’s) of PTPEC4 to PPA are used to prepare a series of LLCPs [denoted as PPA(PTPEC4) x ]. The resultant LLCPs show a smectic A phase (x ≥ 0.8), a columnar nematic phase (0.6 ≤ x ≤ 0.05), and an amorphous state (x = 0.025), depending on the x value. Meanwhile, all polymers exhibit typical aggregation-induced emission behavior. More interestingly, with the variation of the PTPEC4 content, the series of LLCPs show different colors, that is, the emission peak red shifts from 510 nm (x = 1.0) to 551 nm (x = 0.025). Furthermore, because of the reversible protonation effect of the N atom of pyridine in PTPEC4 by the strong proton acid, PPA(PTPEC4) x shows reversible color transformation. This work provides a new method to construct LLCPs with different emission colors and reversible color transformation.
Hydrological models are widely applied for simulating complex watershed processes and directly linking meteorological, topographical, land-use, and geological conditions. In this study, the Soil and Water Assessment Tool (SWAT) was calibrated at two monitoring stations, which improved model performance and increased the reliability of flow predictions in the Upper Xijiang River Basin. This study evaluated the potential impacts of climate change on the streamflow and water yield of the Upper Xijiang River Basin using Arc-SWAT. The model was calibrated (1991–1997) and validated (1998–2001) using the Sequential Uncertainty Fitting Algorithm (SUFI-2). Model calibration and validation suggest a good match between the measured and simulated monthly streamflow, indicating the applicability of the model for future daily streamflow predictions. Large negative changes of low flows are projected under future climate scenarios, exhibiting a 10% and 30% decrease in water yield over the watershed on a monthly scale. Overall, findings generally indicated that winter flows are expected to be affected the most, with a maximum impact during the January–April period, followed by the wet monsoon season in the May–September period. Water balance components of the Upper Xijiang River Basin are expected to change significantly due to the projected climate change that, in turn, will seriously affect the water resources and streamflow patterns in the future. Thus, critical problems, such as ground water shortages, drops in agricultural crop yield, and increases in domestic water demand are expected at the Xijiang River Basin.
Precipitation trend detection is vital for water resources development and decision support systems. This study predicts the climate change impacts on long-term precipitation trends. It deals with the analysis of observed historical (1960–2010) and arithmetic mean method in assembling precipitation from CMIP5 Global Climate Models (GCMs) datasets for a future period (2020–2099) under four emission scenarios. Daily precipitation data of 32 weather stations in the Xijiang River Basin were provided by National Meteorological Information Centre (NMIC) of the China Meteorological Administration (CMA) and Global Climate Models (GCMs) with all four emission scenarios statistically downscaled using Bias Correction Special Disaggregation (BCSD) and applied for bias correction via Climate Change Toolkit (CCT). Nonparametric Mann–Kendall test was applied for statistical significance trend analysis while the magnitude of the trends was determined by nonparametric Sen’s estimator method on a monthly scale to detect monotonic trends in annual and seasonal precipitation time series. The results showed a declined trend was observed for the past 50 years over the basin with negative values of MK test (Z) and Sen’s slope Q. Historical GCMs precipitation detected decreasing trends except for NoerESM1-M which observed slightly increasing trends. The results are further validated by historical precipitation recorded by the Climate Research Unit (CRU-TS-3.1). The future scenarios will likely be positive trends for annual rainfall. Significant positive trends were observed in monsoon and winter seasons while premonsoon and postmonsoon seasons will likely be slightly downward trends. The 2040s will likely observe the lowest increase of 6.6% while the 2050s will observe the highest increase of 11.5% over the 21st century under future scenarios. However, due to the uncertainties in CMIP5, the future precipitation projections should be interpreted with caution. Thus, it could be concluded that the trend of change in precipitation around the Xijiang River Basin is on the increase under future scenarios. The results can be valuable to water resources and agriculture management policies, as well as the approach for managing floods and droughts under the perspective of global climate change.
We examine subsidiary survival from an intersubsidiary competition perspective. Drawing from 87 Taiwanese subsidiaries of MNEs we examine the influences of strategic importance of a subsidiary, resource asymmetry, and characteristics of value activities on the survival rate of a subsidiary. Results show that these factors have differential effects on the survival rates of a firm's foreign subsidiaries. Specifically, strategic importance and gains in intangible resources enhance a subsidiary's survival rate, whereas local responsiveness, gains in physical resources, and similarity and mobility of value‐added activities decrease its survival rate. Copyright © 2007 ASAC. Published by John Wiley & Sons, Ltd.
It has demonstrated that miR‐22 overexpression can suppress the inflammation process of rheumatoid arthritis (RA) in synoviocytes. But, the underlying mechanism of miR‐22 expression in regulating RA is still not well illustrated. In this study, we investigated the functional role and underlying mechanism of miR‐22 in regulating RA. Human RA fibroblast‐like synoviocyte (FLS) cell line MH7A cells was transfected by miR‐22 mimic and its control. CCK8 was utilized to detect cell proliferation. Cell apoptosis was analyzed by flow cytometry. MH7A cells stimulating with interleukin‐1β (IL‐1β) were transfected with miR‐22 mimic. Quantitative real time polymerase chain reaction (qRT‐PCR) and western blot assays were utilized to detect mRNA and protein expression. miR‐22 targets were predicted and validated by Targetscan and luciferase reporter assay. We revealed that miR‐22 showed downregulated expression in MH7A after stimulation with IL‐1β. Additionally, miR‐22 overexpression suppressed the proliferation and facilitated apoptosis in MH7A cells. IL6R was a target of miR‐22. Besides, miR‐22 overexpression inhibited the expression of IL6R and also suppressed inflammatory pathway NF‐κB. These results indicated that miR‐22 overexpression could restrain the activity of inflammation cells in RA by targeting IL6R and might be concerned with the inhibition of NF‐κB pathway.
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.