Study of the effect of refinery waste water exposure on Allium cepa's enzymatic antioxidant defense: probing potential biomarkers

The effects of heavy metals, hydrocarbons, and various toxicants present in Mathura Refinery Waste Water (MRWW) on Allium cepa were examined as a model plant system. The study was based on exposure of A. cepa to different concentrations of MRWW and compared to untreated control (exposure of onion bulbs with aquaguard purified water) to determine the total protein content and activities of certain antioxidant enzymes. These enzymes were evaluated for their efficacy to serve as biomarkers of refinery waste water pollution. DNA damaging potential of MRWW was also investigated. Data demonstrated maximal enhancement in ascorbate peroxidase activity subsequent to MRWW insult, although a significant increase in activities was also noted for other enzymes in the following order: superoxide dismutase?>?glutathione-S-transferase?> catalase. This is suggestive of their potency as a biomarker of MRWW toxicity. Increase in activities of monodehydroascorbate reductase (MDHAR; 152%) and deoxyribonuclease (345%) were also found in the A. cepa system as a result of MRWW exposure. In conclusion, A. cepa system might thus serve as an appropriate tool for monitoring water pollution, especially produced by petroleum waste and heavy metals in term of induction of glutathione peroxidase, MDHAR, and deoxyribonuclease activity.     

Understanding and eliminating pressure fluctuations in an extended chlor-alkali plant due to the size detail of seal pots: A design correlation

When chlorine lines from a new caustic soda plant were added to chlorine lines from an older plant that used the same chlorine compression and liquefaction systems, we encountered abnormal pressure fluctuations on the chlorine side of the new plant. These fluctuations were being transmitted to the chlorine cycle in the older plant, posing a safety hazard in both facilities. After checking the pressure control systems, a design correlation for positive-pressure seal pot was observed and it was found from the inconsistency in the sizes of those equipments in the two plants. The problem was solved by reducing the diameter of the chlorine pipeline in the positive-pressure seal pot of the new plant. After implementing this solution, pressure fluctuations were fully removed, and satisfactory pressure control was attained in both plants.     

Exploitation of iron ore tailing for the development of ceramic tiles

India ranks as the sixth largest producer of iron ore in the world. The current practice of washing iron ore in India generates as high as 18 million tonnes of tailings per year. These tailings are stored in massive ponds and pose environmental hazards. Safe disposal or utilisation of these materials thus remains a challenging task for the iron ore industry in India. The present paper describes a new development in managing these tailings by converting them into value added products such as ceramic floor and wall tiles for building application. These tiles have high strength and hardness compared to conventional tiles and conform to most of the EN standards. Energy economy and lower production costs are some other benefits.     

Analytical solution of two-dimensional advection–dispersion equation with spatio-temporal coefficients for point sources in an infinite medium using Green’s function method

In the present study analytical solutions of a two-dimensional advection–dispersion equation (ADE) with spatially and temporally dependent longitudinal and lateral components of the dispersion coefficient and velocity are obtained using Green’s Function Method (GFM). These solutions describe solute transport in infinite horizontal groundwater flow, assimilating the spatio-temporal dependence of transport properties, dependence of dispersion coefficient on velocity, and the particulate heterogeneity of the aquifer. The solution is obtained in the general form of temporal dependence and the source term, from which solutions for instantaneous and continuous point sources are derived. The spatial dependence of groundwater velocity is considered non-homogeneous linear, whereas the dispersion coefficient is considered proportional to the square of spatial dependence of velocity. An asymptotically increasing temporal function is considered to illustrate the proposed solutions. The solutions are validated with the existing solutions derived from the proposed solutions in three special cases. The effect of spatially/temporally dependent heterogeneity on the solute transport is also demonstrated. To use the GFM, the ADE with spatio-temporally dependent coefficients is reduced to a dispersion equation with constant coefficients in terms of new position variables introduced through properly developed coordinate transformation equations. Also, a new time variable is introduced through a known transformation.     

MSW stabilization in an anaerobic bioreactor landfill and evaluation of in-situ leachate treatment potential with the help of quadric model

Journal of Material Cycles and Waste Management - Recirculation of the leachate using bioreactor technology for in-situ treatment of leachate is an efficient method for reducing the contaminants...     

Effect of fabricated V-rib roughness experimentally investigated in a rectangular channel of solar air heater: a comprehensive review

Environmental Science and Pollution Research - Solar power is one of the main sources of renewable energy which helps for protecting the environmental and reducing pollution. Technologies and...     

Pulling force prediction using neural networks

Purpose. In ergonomics and human factors investigations, pulling force (PF) estimation has usually been achieved using various types of biomechanical models, and independent approximation of PF was done with the help of upper extremity joints. Recently, multiple regression methods have gained importance for task-relevant inputs in predicting PF. Artificial neural networks (ANNs) also play a vital role in fitting the data; however, their use in work-related biomechanics and ergonomics is inadequate. Therefore, the current research aimed to accomplish comparative investigation of ANN and regression models by assessing their capacity to predict PF values. Methods. Multipositional PF data were acquired from 200 subjects at three different handle heights and body locations. ANN and regression models were formed using a random sample of three subsets (75% training, 15% selection, 10% validation) for proving the outcomes. Results. The comparison of ANN and regression models shows that the predictions of ANN models had a profoundly explained variance and lower root mean square difference values for the PF data at three handle heights. Conclusions. These outcomes advise that ANNs offer a precise and robust substitute for regression methods, and should be considered a useful method in biomechanics and ergonomics task assessments.