RESUMEN
Biochar has been recommended as a carbon material with high porosity, rich functional groups, and low cost for flue gas denitration. In this study, five different biochar materials, including original sludge biochar (SC), the KOH-impregnated biochar (SCK), the biochar of SCK washing by ultra-water (SCK-W), the H2SO4-impregnated biochar (SCS), and the biochar of SCS washing by ultra-water (SCS-W), prepared using a one-step activation method were applied to remove NO from flue gases, acting as both reductants and catalysts. The results indicate that the SCK-700 can lead to the highest NO conversion of 100% at 325 °C, and can suppress the acidic gas generation compared with SCS. The order of reduction capacity at 300-400 °C was SCK-700 > SCK-W-700 > SC-700 > SCS-700 > SCS-W-700. Furthermore, the kinetics indicated that adsorption capacity enhanced with the rise in temperature, and that SCK-700 had the largest adsorption capacity, reaching 337.15 mg/g at 400 °C.
RESUMEN
BACKGROUND: The Clínica Universidad de Navarra-Body Adiposity Estimator (CUN-BAE) index has been recommended as an ideal indicator of body fat and exhibited significant correlation with cardiometabolic risk factors. However, whether the CUN-BAE index correlates with incident diabetes in Asian populations is unknown. Therefore, this longitudinal study was designed to evaluate the association between baseline CUN-BAE index and type 2 diabetes mellitus (T2DM). METHODS: This retrospective longitudinal study involved 15,464 participants of 18-79 years of age in the NAGALA (NAfld in the Gifu Area Longitudinal Analysis) study over the period of 2004-2015. Cox proportional hazards regression was performed to test the relationship between the baseline CUN-BAE index and diabetes incidence. Further stratification analysis was conducted to ensure that the results were robust. The diagnostic utility of the CUN-BAE index was tested by the receiver operating characteristic (ROC) curve. RESULTS: Over the course of an average follow-up of 5.4 years, 373 (2.41%) participants developed diabetes. A higher diabetes incidence was associated with higher CUN-BAE quartiles (P for trend< 0.001). Each 1 unit increase in CUN-BAE index was associated with a 1.08-fold and 1.14-fold increased risk of diabetes after adjustment for confounders in males and females, respectively (both P < 0.001). Stratification analysis demonstrated a consistent positive correlation between baseline CUN-BAE and diabetes incidence. Moreover, based on ROC analysis, CUN-BAE exhibited a better capacity for diabetes prediction than both body mass index (BMI) and waist circumference (WC) in both sexes. CONCLUSIONS: The baseline CUN-BAE level was independently related to the incidence of diabetes. Increased adiposity determined by CUN-BAE could be used as a strong nonlaboratory predictor of incident diabetes in clinical practice.
