A Novel UV-C/XOH(X=Na or K) Based Highly Alkaline Advanced Oxidation Process (HA-AOP) for Degradation of Emerging Micropollutants

Herein, a novel and comprehensible approach has been suggested to degrade the emerging micropollutants such as synthetic dyes. In this study, a continuous UV-C irradiation has been used to treat the aqueous matrix of synthetic pollutant dyes under highly alkaline environment (pH >13.0). In this HA-AOP, the treatment rate and degradation efficiency are primarily found to be affected by the type of pollutant dye present in the matrix, concentration of XOH or pH and UV-C fluence rate. In addition, the kinetic study indicates that HA-AOP or UV-C/XOH(X=Na or K) process follows zero order reaction kinetics during the degradation of parent pollutant species. The explored approach is quite auspicious due to its tremendous potential to handle versatile aqueous matrices containing natural organic materials, inorganic salts, fatty matters, surfactants and many more things. Overall, unlike other AOPs, this novel UV-C/XOH(X=Na or K) based HA-AOP could be highly utilized for the effective treatment of various alkaline wastewater streams

A Novel UV-C/XOH(X=Na or K) Based Highly Alkaline Advanced Oxidation Process (HA-AOP) for Degradation of Emerging Micropollutants

Herein, a novel and comprehensible approach has been suggested to degrade the emerging micropollutants such as synthetic dyes. In this study, a continuous UV-C irradiation has been used to treat the aqueous matrix of synthetic pollutant dyes under highly alkaline environment (pH >13.0). In this HA-AOP, the treatment rate and degradation efficiency are primarily found to be affected by the type of pollutant dye present in the matrix, concentration of XOH or pH and UV-C fluence rate. In addition, the kinetic study indicates that HA-AOP or UV-C/XOH(X=Na or K) process follows zero order reaction kinetics during the degradation of parent pollutant species. The explored approach is quite auspicious due to its tremendous potential to handle versatile aqueous matrices containing natural organic materials, inorganic salts, fatty matters, surfactants and many more things. Overall, unlike other AOPs, this novel UV-C/XOH(X=Na or K) based HA-AOP could be highly utilized for the effective treatment of various alkaline wastewater streams

A CFD analysis of thermal behaviour of transportation cask under fire test conditions

Thermal design of transportation cask for shipping radioactive waste needs strict compliance with the guidelines of the regulatory bodies. Lead shielding is usually provided in these casks for arresting gamma rays and reducing hazardous emissions to the environment below permissible limits. During transportation, accidental fire may break out and cause melting of lead for a prescribed duration. The present analysis reports, for the first time, a comprehensive CFD analysis of the thermal behaviour of melting of lead under high Rayleigh number convection during the fire test. The study reveals a substantial influence of natural convection on the thermal state and melting behaviour of lead which may have a great bearing on the safety and security of public during transportation of cask. (C) 2011 Elsevier B.V. All rights reserved

Fidelity of WRF model in simulating heat wave events over India

Abstract The evaluation of Weather Research and Forecasting (WRF) model has been performed for simulating episodic Heat Wave (HW) events of 2015 and 2016 with varied horizontal resolutions of 27 km for the entire India (d01), 9 km for the North West (NW (d02)) and South East (SE (d03)) domain. Study compares the maximum temperature (Tmax) simulated by WRF model, using six different combination of parameterization schemes, with observations from the India Meteorological Department (IMD) during the HW events. Among the six experiments, Exp2 (i.e., combination of WSM6 microphysics (MP) together with radiation parameterization CAM, Yonsei (PBL), NOAH land surface and Grell-3D convective schemes) is found closest to the observations in reproducing the temperature. The model exhibits an uncertainty of ± 2 °C in maximum temperature (Tmax) for both the regions, suggesting regional temperature is influenced by the location and complex orography. Overall, statistical results reveal that the best performance is achieved with Exp2. Further, to understand the dynamics of rising HW intensity, two case studies of HW days along with influencing parameters like Tmax, RH and prevailing wind distribution have been simulated. Model simulated Tmax during 2015 reaches up to 44 °C in NW and SE part of India. In 2016, HW is more prevailing towards NW, while in SE region Tmax reaches upto 34–38 °C with high RH (60–85%). The comparative research made it abundantly evident that these episodic events are unique in terms of duration and geographical spread which can be used to assess the WRF performance for future projections of HW

ZnO-rGO nanocomposite based bioelectrode for sensitive and ultrafast detection of dopamine in human serum

We present a tyrosinase-conjugated zinc oxide-reduced graphene oxide (Tyr/ZnO-rGO) nanocomposite system as a biosensing test-bed for rapid and sensitive detection of dopamine (DA). The bioelectrodes (Tyr/ZnO-rGO/ITO) were designed by covalently immobilizing tyrosinase enzyme on spin-coated films of ZnO-rGO nanocomposite prepared via self-assembly approach. The cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) showed fast electron transfer kinetics of ZnO-rGO/ITO electrode. The response studies of the Tyr/ZnO-rGO/ITO bioelectrode revealed ultrafast (0.34 +/- 0.09 s) detection of DA in a wide linear dynamic range of 0.1-1500 pM. The significant performance of the biosensor in terms of low detection limit (8.75 +/- 0.64 pM) and high sensitivity (39.56 +/- 0.41 mu A nM(-1)) values is attributed to the fast and unhindered electron transfer mechanism of ZnO-rGO matrix having low electrochemical band gap. The nanoplatform exhibited high selectivity toward DA in human sera, and remained stable up to 3 months at 4 degrees C, representing its suitability for clinical applications

Enhanced Network Intrusion Detection System

A reasonably good network intrusion detection system generally requires a high detection rate and a low false alarm rate in order to predict anomalies more accurately. Older datasets cannot capture the schema of a set of modern attacks; therefore, modelling based on these datasets lacked sufficient generalizability. This paper operates on the UNSW-NB15 Dataset, which is currently one of the best representatives of modern attacks and suggests various models. We discuss various models and conclude our discussion with the model that performs the best using various kinds of evaluation metrics. Alongside modelling, a comprehensive data analysis on the features of the dataset itself using our understanding of correlation, variance, and similar factors for a wider picture is done for better modelling. Furthermore, hypothetical ponderings are discussed for potential network intrusion detection systems, including suggestions on prospective modelling and dataset generation as well