The potential environmental implications of a Pb (Lead)-Zn (Zinc) sulfide tailing impoundment were found to be dependent on its geochemical characteristics. One typical lead-zinc sulfide tailing impoundment was studied. Ten boreholes were set with the grid method and 36 tailings were sampled and tested. According to the results of metal content analysis, the tailing samples contained considerably high contents of heavy metals, ranging from 6.99 to 89.0 mg/kg for Cd, 75.3 to 602 mg/kg for Cu, 0.53% to 2.63% for Pb and 0.30% to 2.54% for Zn. Most of the heavy metals in the sample matrix showed a uniform concentration distribution, except Cd. Cd, Pb, Zn, and Mn were associated with each other, and were considered to be the dominant contributors based on hierarchical cluster analysis. XRD, SEM and XPS were employed for evaluation of the tailing weathering characteristics, confirming that the tailings had undergone intensive weathering. The maximum potential acidity of the tailings reached 244 kg H2SO4/ton; furthermore, the bioavailability of heavy metals like Pb, Cd, Cr, Cu, and Zn was 37.8%, 12.9%, 12.2%, 5.95%, and 5.46% respectively. These metals would be potentially released into drainage by the weathering process. Analysis of a gastrointestinal model showed that Pb, Cr, Ni and Cu contained in the tailings were high-risk metals. Thus, control of the heavy metals' migration and their environmental risks should be planned from the perspective of geochemistry.In this study, N-doped porous carbons were produced with commercial phenolic resin as the raw material, urea as the nitrogen source and KOH as the activation agent. Different from conventional carbonization-nitriding-activation three-step method, a facile two-step process was explored to produce N-incorporated porous carbons. The as-obtained adsorbents hold superior CO2 uptake, i.e. 5.01 and 7.47 mmol/g at 25 °C and 0 °C under 1 bar, respectively. The synergistic effects of N species on the surface and narrow micropores of the adsorbents decide their CO2 uptake under 25 °C and atmospheric pressure. These phenolic resin-derived adsorbents also possess many extremely promising CO2 adsorption features like good recyclability, quick adsorption kinetics, modest heat of adsorption, great selectivity of CO2 over N2 and outstanding dynamic adsorption capacity.  https://www.selleckchem.com/products/Cyclopamine.html  Cheap precursor, easy preparation strategy and excellent CO2 adsorption properties make these phenolic resin-derived N-doped carbonaceous adsorbents highly promising in CO2 capture.Volatile organic compounds (VOCs) are major contributors to air pollution. Based on the emission characteristics of 99 VOCs that daily measured at 10 am in winter from 15 December 2015 to 17 January 2016 and in summer from 21 July to 25 August 2016 in Beijing, the environmental impact and health risk of VOC were assessed. In the winter polluted days, the secondary organic aerosol formation potential (SOAP) of VOC (199.70 ± 15.05 μg/m3) was significantly higher than that on other days. And aromatics were the primary contributor (98.03%) to the SOAP during the observation period. Additionally, the result of the ozone formation potential (OFP) showed that ethylene contributed the most to OFP in winter (26.00% and 27.64% on the normal and polluted days). In summer, however, acetaldehyde was the primary contributor to OFP (22.00% and 21.61% on the normal and polluted days). Simultaneously, study showed that hazard ratios and lifetime cancer risk values of acrolein, chloroform, benzene, 1,2-dichloroethane, acetaldehyde and 1,3-butadiene exceeded the thresholds established by USEPA, thereby presenting a health risk to the residents. Besides, the ratio of toluene-to-benzene indicated that vehicle exhausts were the main source of VOC pollution in Beijing. The ratio of m-/p-xylene-to-ethylbenzene demonstrated that there were more prominent atmospheric photochemical reactions in summer than that in winter. Finally, according to the potential source contribution function (PSCF) results, compared with local pollution sources, the spread of pollution from long-distance VOCs had a greater impact on Beijing.Autism spectrum disorder is a neurodevelopmental disorder characterized by impaired social abilities and communication difficulties. The golden standard for autism diagnosis in research rely on behavioral features, for example, the autism diagnosis observation schedule, the Autism Diagnostic Interview-Revised. In this study we introduce a computer-aided diagnosis system that uses features from structural MRI (sMRI) and resting state functional MRI (fMRI) to help predict an autism diagnosis by clinicians. The proposed system is capable of parcellating brain regions to show which areas are most likely affected by autism related abnormalities and thus help in targeting potential therapeutic interventions. When tested on 18 data sets (n = 1060) from the ABIDE consortium, our system was able to achieve high accuracy (sMRI 0.75-1.00; fMRI 0.79-1.00), sensitivity (sMRI 0.73-1.00; fMRI 0.78-1.00), and specificity (sMRI 0.78-1.00; fMRI 0.79-1.00). The proposed system could be considered an important step toward helping physicians interpret results of neuroimaging studies and personalize treatment options. To the best of our knowledge, this work is the first to combine features from structural and functional MRI, use them for personalized diagnosis and achieve high accuracies on a relatively large population.In preparation for a larger case-control study of children with autism spectrum disorder (ASD) and anxiety, we conducted a pilot study using a noninvasive electrocardiographic device to measure cardiovascular reactivity in 10 children (age range 9-14) with ASD. The 45-minute procedure included 6 conditions baseline rest, an interview about school, interim rest, an unfair computerized ball-toss game followed by a fair version of the game, and a final rest. Data were successfully collected for 95% of all conditions. Omnibus Skillings-Mack tests suggested that heart rate variability variables including mean heart rate, mean RR interval, and root mean square of successive differences showed statistically significant variation across conditions. The procedure appears feasible and may be an informative biomarker of anxiety in ASD.