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Herein, α-cyanostilbene-based luminogen with an electron donor-π-electron acceptor (D-π-A) architecture was formylated into the salicylaldehyde-analogue luminogen, followed by the Schiff base reaction with phenylamine, a red-emitting luminogen was elaborately designed and successfully synthesized in a high yield of 89%. Its well-defined structure was confirmed by FT-IR, MALDI-TOF-MS, HR-MS and 1H/13C NMR technologies. Based on the synergistic mechanisms of aggregation-induced emission (AIE), excited-state intramolecular proton transfer (ESIPT) and intramolecular charge transfer (ICT), it enjoyed a red-fluorescence emission at 627 nm in THF/water mixtures (fw = 95%) and was used as a probe. Moreover, the TLC-based test strips loaded with the probe not only exhibited the reversible fluorescence response to amine/acid vapor but also showed sensitive and selective fluorescence response towards Cu2+. Furthermore, the fluorescence titration experiment between the probe and Cu2+ in THF/water mixtures (fw = 95%, pH = 7.4) revealed that the detection limit was 1.18 × 10-7 M and the binding constant was 1.59 × 105. Job's plot experiment and HR-MS analysis revealed the 2:1 binding stoichiometry of the probe with Cu2+. The method enabled real-time assessment for Cu2+ in real water samples. This study could offer insightful opinions on the development of long-wavelength emissive luminogens based on α-cyanostilbene. [ABSTRACT FROM AUTHOR]

The straw-derived biochar of wheat straws (WS), corn straws (CS), and rape straws (RS) was successfully synthesized by the pyrolysis of biomass in an oxygen-deficient environment at 773 K and characterized by SEM, BET, FTIR, Raman, and XRD. Solution pH, contact time, and initial concentration of solution as adsorption parameters were analyzed to optimize the conditions for maximum adsorption capacity by central composite design (CCD) in response surface methodology (RSM). The results showed that the adsorption process of wheat straw biochar (WBC), corn straw biochar (CBC) and rape straw biochar (RBC) followed the pseudo-second-order model and Langmuir model. Modeling analysis showed that the influence degree of each variable on the response value could be ordered in solution pH>initial concentration>adsorption time, and optimum conditions for achieving 8.25 mg/g of methylene blue (MB) by WBC were determined to be 1g/L of adsorbent dose, pH=7.00, 25 min of adsorption time, and 30 mg/L initial concentration. The adsorption mechanism involved electrostatic interaction, hydrogen-bond interaction, π-π interaction, etc. [ABSTRACT FROM AUTHOR]

The prediction of the spatiotemporal dynamic evolution of vegetation cover in the Huainan mining area and the quantitative evaluation of its driving factors are of great significance for protecting and restoring the environment in this area. This study uses the Landsat 5 TM and Landsat 8 OLI time-series data to estimate the vegetation cover and uses the transition matrix to analyze the spatiotemporal transfer of vegetation cover from 1989 to 2004, 2004 to 2021, and 2021 to 2030. In addition, a structural equation model (SEM) was established in this study to assess the driving factors of vegetation cover. The quantitative analysis and the cellular automata (CA)-Markov model were performed to predict the future vegetation cover in the Huainan mining area. The results are as follows: (1) In different periods, the vegetation cover types were mainly high cover types transferred to other vegetation cover types; (2) human activities are the key factors affecting the vegetation growth, while topographical factor is the most influential factor promoting the vegetation growth; (3) highly consistent CA-Markov and multi-criteria evaluation (MCE) predicted results of vegetation cover in 2030 compared to that in 2021. The proportion of bare soil and low cover types had increased significantly, mainly concentrated in the internal area of the mines. The prediction of the spatiotemporal evolution of vegetation cover in the Huainan mining area and the quantitative change in driving factors are of significant importance for the restoration of the environment in mining areas. [ABSTRACT FROM AUTHOR]

Coal mining has produced a large amount of coal gangue. It makes the soil around the mining area seriously polluted by heavy metals, affects the growth of crops, and endangers human health. Therefore, there is an urgent need to develop new materials for remediation of Cd in soil. In this study, mercaptosilane-modified sepiolite (Q-Sep) was used as a basic passivator, and it was pretreated with acid (H-Q-Sep) and high temperature (R-Q-Sep) respectively. By analyzing the forms of Cd and pH values in soil after adding modified sepiolite, we compared the remediation effects of two modified methods on Cd in soil. The enrichment of spinach (Spinacia oleracea L) to Cd and changes in physiological and biochemical indexes of spinach were determined, and the effect of modified sepiolite on the growth of spinach was judged. The experimental results showed that the addition of modified sepiolite could significantly increase the soil pH values (p < 0.05); the content of exchangeable Cd in soil decreased by 60.4%; and the maximum increase of residual state was 32.9%. The absorption of Cd in soil by spinach decreased, and root length, plant height, and biomass of spinach all increased. It was proved that the addition of modified sepiolite can improve the productivity of soil, reduce toxicity of heavy metals in soil, and promote growth of plants. As a result, the addition of H-Q-Sep and R-Q-Sep can effectively repair Cd in gangue filled soil, which provides a certain theoretical basis for the passivation remediation of Cd in soil. [ABSTRACT FROM AUTHOR]

Land use demand change in the Huaihe River basin (HRB) and ecosystem service values (ESVs) in watersheds are important for the sustainable development and use of land resources. This paper takes the HRB as the research object, and using remote sensing images of land use as the data source adopts the comprehensive evaluation analysis method of ESVs based on equivalent factors and sensitivity analysis of the performance characteristics of ESV changes of different land use types. The PLUS model is used to predict spatiotemporal land use change characteristics to 2030 combining inertial development, ecological development, and cultivated land development. The spatial distribution and aggregation of ESVs at each scale were also explored by analyzing ESVs at municipal, county, and grid scales. Considering also hotspots, the contribution of land use conversion to ESVs was quantified. The results showed that (1) from 2000 to 2020, cultivated land decreased sharply to 28,344.6875 km2, while construction land increased sharply to 26,914.563 km2, and the change of other land types was small. (2) The ESVs in the HRB were 222,019 × 1012 CNY in 2000, 235,015 × 1012 CNY in 2005, 234,419 × 1012 CNY in 2010, 229,885 × 1012 CNY in 2015, and 224,759 × 1012 CNY in 2020, with an overall fluctuation, first increasing and then decreasing. (3) The ESVs were 219,977 × 1012 CNY, 218,098 × 1012 CNY, 219,757 × 1012 CNY, and 213,985 × 1012 CNY under the four simulation scenarios of inertial development, ecological development, cultivated land development, and urban development, respectively. At different scales, the high-value areas decreased, and the low-value areas increased. (4) The hot and cold spots of ESV values were relatively clustered, with the former mainly clustered in the southeast region and the latter mainly clustered in the northwest region. The sensitivity of ecological value was lower than 1, while the ESV was inelastic to the ecological coefficient, and the results were plausible. The mutual conversion of cultivated land to water contributed the most to ESVs. Based on the multi-scenario simulation of land use in the HRB by the PLUS model, we identified the spatial distribution characteristics of ESVs at different scales, which can provide a scientific basis and multiple perspectives for the optimization of land use structure and socio-economic development decisions. [ABSTRACT FROM AUTHOR]

This study investigated the environmental geochemical characteristics of rare-earth elements (REEs) in surface waters in the Huainan mining area, Anhui Province, China. The REEs concentrations were determined by ICP-MS, and the inorganic species of dissolved REEs in the river and coal mining subsidence area water samples were calculated by using the Visual MINTEQ (version 3.1) code. On this basis, the distribution and geochemical characteristics of REEs in the surface waters were systematically analyzed, and the main inorganic species of REEs were investigated. The results showed the following: (1) The REEs concentrations in the surface waters were relatively low, ranging from 0.1361 to 0.3536 μg/L, and the average ∑REEs concentration was 0.2062 μg/L. Compared with light rare-earth elements (LREEs), heavy rare-earth elements (HREEs) were significantly enriched, with an average enrichment factor of 1.4642. Due to the interaction of high pH values and high cation concentrations, the ∑REEs content in the subsidence area water was significantly lower than that in the river water. (2) The distribution pattern of REEs in the surface waters normalized against the North American Shale Composite (NASC) showed that the REEs in the study area had different degrees of cerium (Ce) and europium (Eu) anomalies. The negative Ce anomalies were probably closely related to the pH conditions, whereas the positive Eu anomalies were mainly attributed to preferential chemical weathering and the dissolution of feldspar minerals. (3) The simulation results obtained by using Visual MINTEQ code showed that the dominant and typically inorganic complex form of REEs in the surface waters was carbonate complexes, and this form was one of the reasons for the enrichment of HREEs in the surface water. [ABSTRACT FROM AUTHOR]

The Huainan mining area is rich in coal resources and has sparse vegetation and many collapsed waterways. Large-scale and long-term underground coal mining has led to a fragile ecological environment in the mining area, and it is urgent to solve the contradiction between coal development and ecological environmental protection. The Huainan mining area was selected as the research object, and the vegetation cover was extracted using 10-phase Landsat multispectral remote sensing images from 1989 to 2021 to analyze its spatial and temporal changes and driving forces to provide a scientific basis for the guided restoration of the ecological environment in the region. Combined with the image dichotomous model, regression slope, correlation coefficient, and standard deviation of vegetation cover grid points in different time series, standard deviation ellipse, and center of gravity migration, we analyzed the spatial and temporal variation pattern of vegetation cover for 33 years and revealed the responses of temperature, precipitation, population density, GDP, and afforestation area to vegetation cover. Results show the following: (1) from 1989 to 2021, the overall vegetation cover in the study area tended to decrease with 36.48% of the areas increasing and 63.52% of the areas decreasing, primarily in the very low and medium range; (2) the center of gravity of different types of vegetation cover generally shifted from north to south during 33 years; (3) climate and social activities had a substantial effect on the spatial heterogeneity of the vegetation cover in the study area. There is significant spatial heterogeneity in the effects of climate and social activities on the vegetation in the study area with human activities negatively correlating with vegetation cover. Mining activities are the primary driver of the evolution of regional vegetation cover, with climate change serving as a secondary driver. [ABSTRACT FROM AUTHOR]

The deep Carboniferous Taiyuan Formation and Ordovician limestone water are not only valuable groundwater resources in North China but also the main source of water hazards for Carboniferous-Permian coal mining. Currently, there are still insufficient studies on the recharge, circulation, and water–rock interactions of deep limestone water. Taking the Panxie mining area of Huainan, Anhui Province, as the research area, this study investigated the water–rock interaction and water cycle of deep limestone groundwater by combining hydrochemistry and stable isotopes of hydrogen and oxygen. The results show that (1) the average total dissolved solids (TDS) values of the Taiyuan Formation limestone and Ordovician limestone water were 852.72 mg/L and 2785.52 mg/L, respectively, and the Ordovician limestone water was high-salinity water. The main hydrochemical type of the Taiyuan Formation limestone water is Cl·HCO3-Na, and the main type of Ordovician limestone water is Cl-Na. Evaporite dissolution and cation alternate adsorption jointly control the source and composition of limestone water chemical ions. The dissolution effect of evaporite in Ordovician limestone water is stronger, while cation alternate adsorption in Taiyuan Formation limestone water is stronger. (2) The hydrogen and oxygen stable isotope values of limestone water are distributed at the lower right of the atmospheric precipitation line and close to the precipitation line, indicating that the groundwater is primarily derived from atmospheric precipitation. Some water sample points deviate far from the atmospheric precipitation line, mainly due to the isotope exchange equilibrium reaction between groundwater and surrounding rock in long-term full contact, showing a certain degree of the "oxygen (deuterium) drift" phenomenon. (3) Most of the Taiyuan Formation limestone water isotopic values are greater than the average annual precipitation, while those of the Ordovician limestone water are the opposite, which indicates that the Taiyuan Formation limestone water produces varying degrees of evaporation and infiltration in the replenishment path, and Ordovician limestone water is unevenly recharged by precipitation in different seasons. [ABSTRACT FROM AUTHOR]

Exogenous humus can change the content and migration activity of cadmium (Cd) in soil. Humic acid (HA) is an important soluble humus component in soil. In order to explore the relationship between cadmium pollution mechanism and ecological environment of humic acid in reclaimed soil, the characteristics of humic acid adsorbing cadmium in alkaline conditions were studied. This study employed reclaimed soil from the Huainan mining area, China. The adsorption and desorption characteristics as well as influence mechanisms on the heavy metal cadmium (Cd) were explored under the influence of HA. The results show that: (1) When Cd concentration was low (0.2–10 mg/L), HA had little effect on Cd adsorption and desorption in reclaimed soil. When the Cd concentration was high (15–80 mg/L), HA had a great influence on the adsorption and desorption of Cd in reclaimed soil. The addition of HA can inhibit the adsorption of Cd by reclaimed soil and effectively improve the desorption capacity of Cd by reclaimed soil. (2) The kinetic curves of Cd adsorption and desorption of reclaimed soil with added HA show that both processes (adsorption and desorption) include two stages: rapid reaction and slow reaction. The adsorption of Cd by reclaimed soil under the influence of HA was 18.18% lower than that of normal reclaimed soil, and the increase of Cd desorption was 50.29%. (3) The factors affecting the adsorption and desorption of Cd in the soil were analyzed with gray theory, and their importance can be ordered as follows: Cd concentration > HA concentration > pH > temperature. Considering the influence of HA, a multi-factor coupling function model of adsorption and desorption of Cd in soil is established. This model provides theoretical guidance for the scientific prediction and evaluation of Cd environmental pollution risks in soil and will be useful for developing a new solution for engineering remediation of high concentration Cd contaminated soil. [ABSTRACT FROM AUTHOR]

Background: Determining the rupture risk of unruptured intracranial aneurysm is crucial for treatment strategy. The purpose of this study was to predict the rupture risk of middle cerebral artery (MCA) aneurysms using a machine learning technique. Methods: We retrospectively reviewed 403 MCA aneurysms and randomly partitioned them into the training and testing datasets with a ratio of 8:2. A generalized linear model with logit link was developed using training dataset to predict the aneurysm rupture risk based on the clinical variables and morphological features manually measured from computed tomography angiography. To facilitate the clinical application, we further constructed an easy-to-use nomogram based on the developed model. Results: Ruptured MCA aneurysm had larger aneurysm size, aneurysm height, perpendicular height, aspect ratio, size ratio, bottleneck factor, and height-width ratio. Presence of a daughter-sac was more common in ruptured than in unruptured MCA aneurysms. Six features, including aneurysm multiplicity, lobulations, size ratio, bottleneck factor, height-width ratio, and aneurysm angle, were adopted in the model after feature selection. The model achieved a relatively good performance with areas under the receiver operating characteristic curves of 0.77 in the training dataset and 0.76 in the testing dataset. The nomogram provided a visual interpretation of our model, and the rupture risk probability of MCA aneurysms can be directly read from it. Conclusion: Our model can be used to predict the rupture risk of MCA aneurysm. [ABSTRACT FROM AUTHOR]