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The Xiaoxinganling Mountains–Sanjiang Plain region represents a crucial ecological security barrier for the Northeast China Plain and serves as a vital region for national grain production. Over the past two decades, the region has undergone numerous ecological restoration projects. Nevertheless, the combined impact of enhanced vegetation greening and global climate change on the regional hydrological cycle remains inadequately understood. This study employed the distributed hydrological model ESSI-3, reanalysis datasets, and multi-source satellite remote sensing data to quantitatively evaluate the influences of climate change and vegetation dynamics on regional hydrological processes. The study period spans from 2000 to 2020, during which there were significant increases in regional precipitation and leaf area index (p < 0.05). The hydrological simulation results exhibited strong agreement with observed river discharge, evapotranspiration, and terrestrial water storage anomalies, thereby affirming the ESSI-3 model's reliability in hydrological change assessment. By employing both a constant scenario that solely considered climate change and a dynamic scenario that integrated vegetation dynamics, the findings reveal that: (1) Regionally, climate change driven by increased precipitation significantly augmented runoff fluxes (0.4 mm/year) and water storage components (2.57 mm/year), while evapotranspiration trends downward, attributed primarily to reductions in solar radiation and wind speed; (2) Vegetation greening reversed the decreasing trend in evapotranspiration to an increasing trend, thus exerting a negative impact on runoff and water storage. However, long-term simulations demonstrated that regional runoff fluxes (0.38 mm/year) and water storage components (2.21 mm/year) continue to increase, mainly due to precipitation increments surpassing those of evapotranspiration; (3) Spatially, vegetation greening altered the surface soil moisture content trend in the eastern forested areas from an increase to a decrease. These findings suggested that sub-regional ecological restoration initiatives, such as afforestation, significantly influence the hydrological cycle, especially in areas with higher vegetation greening. Nevertheless, persistent increases in precipitation could effectively mitigate the moisture deficits induced by vegetation greening. The study's outcomes provide a basis for alleviating concerns regarding potential water consumption risks associated with future ecological restoration and extensive vegetation greening projects, thereby offering scientific guidance for sustainable water resource management. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to explore the serial mediating effect of stigma and depression on the association between social support and medication adherence. Patients and Methods: A cross-sectional survey was undertaken in the Changning District of Shanghai using a five-part questionnaire from August to December 2023. A convenient sampling method was employed, and 35 patients with schizophrenia were invited from each of the 9 streets in Changning District to participate in the survey, resulting in a total of 305 valid questionnaires collected. The questionnaire measured social support, stigma, depression, medication adherence, and demographic characteristics. Data analysis involved descriptive statistics, independent samples t-tests, ANOVA, Pearson correlation analysis, and the bootstrap method. Results: There was a direct and significantly positive association between social support and medication adherence (β = 0.69, p < 0.001). Moreover, increased levels of stigma (β = - 0.45, p = 0.013) and depression (β = - 0.09, p = 0.017) were both associated with a decline in medication adherence. Bootstrapping analysis revealed that the association between social support and medication adherence operated indirectly through stigma (β = 0.11, 95% CI: 0.03, 0.18). Additionally, social support was indirectly associated with medication adherence through depression (β =  0.15, 95% CI: 0.04, 0.30). Further analysis indicated that social support had an indirect association with medication adherence through both stigma and depression (β =  0.04, 95% CI: 0.01, 0.07). Conclusion: Stigma and depression serially mediate the association between social support and medication adherence among patients with schizophrenia. This serial multiple mediation model underscores the importance of integrating social support interventions with psychological interventions aimed at reducing stigma and depression, thereby effectively enhancing medication adherence in patients with schizophrenia. [ABSTRACT FROM AUTHOR]

The linear programming (LP) model has been used to identify a cost-effective strategy for reducing CO2 emissions in power plants considering coal washing, pollutant removal, and carbon capture processes, thus CO2 emissions in different production processes can be obtained. The direct emissions (combustion emissions and desulfurization emissions) and indirect emissions (pollutant removal, coal washing, and carbon capture) of CO2 were all considered in the LP model. Three planning periods were set with different CO2 emission control desirability to simulate CO2 emissions of the different reduction requirements. The results can reflect the CO2 emissions across the whole production process of a coal-fired power plant overall. The simulation results showed that for a coal-fired power plant containing two 1000 MW ultra super-critical sets, when the desirability was 0.9, the CO2 total emissions were 2.15, 1.84, and 1.59 million tons for the three planning periods. The research results suggest that the methodology of LP combined with fuzzy desirability function is applicable to represent the whole production process of industry sectors such as coal-fired power plants. The government policy makers could predict CO2 emissions by this method and use the results as a reference to conduct effective industrial and energy structure adjustment. [ABSTRACT FROM AUTHOR]