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Objectives: To evaluate the association of interleukin 6 (IL-6) levels with deep vein thrombosis (DVT) and to assess the impact of IL-6 promoter polymorphisms (−174G > C, −572G > C and −597G > A) on its plasma levels and their influence in the development of DVT in India. Methods: One hundred DVT patients and 100 age and sex-matched healthy controls were study subjects. IL-6 polymorphisms were identified by polymerase chain reaction-restriction fragment length polymorphism. IL-6 levels were detected by enzyme-linked immunosorbent assay. Results: Significantly raised IL-6 levels were observed in patients as compared to controls. (Patients: 13.73 ± 6.30 pg/ml, Controls: 11.83 ± 4.47 pg/ml, p = 0.014). The prevalence of C allele of −572G > C polymorphism was significantly higher in patients than controls (Patients: 39.5%, Controls: 27.5%, p = 0.011, χ2=6.463). Subjects with GC and CC genotype had significantly higher IL-6 levels than GG genotype (p=<0.001). Patients with GC and CC genotype increased the DVT risk by 1.39 fold (ORa: 1.39, CI: 0.74-2.62) and 2.69 fold (ORa: 2.42, CI: 1.08-6.70), respectively. IL-6 −174G > C and −597G > A polymorphisms were not associated with raised IL-6 levels and nor with thrombotic risk (−174G > C: p = 0.823 χ2=0.369; −597G > A: p = 0.678 χ2=1.08). Conclusion: Our study emphasizes the importance of −572G > C polymorphism in increasing IL-6 levels, thereby showing its significant role in DVT in India. IL-6 −174G > C and −597G > A were neither associated with raised plasma IL-6 levels nor with thrombotic risk. Thus −572G > C polymorphism detection may be one of the connecting links between IL-6 and thrombotic risk in Indian DVT patients. [ABSTRACT FROM AUTHOR]

High temperature refractory materials of refractoriness above 1665°C having refractory phases such as forsterite (Mg2SiO4), periclase (MgO) and spinel can be developed from the water granulated spongy ferrochromium slag granules (90% particle) of size below 3100 micron by MgO enrichment. MgO enrichment in ferrochrome slag can be achieved by a method comprises of grinding of granulated ferrochrome slag in presence of magnesite raw material followed by compaction and sintering. The ratio of MgO/SiO2> 2.2 and MgO/(Al2O3+ Cr2O3) > 1.71 in the final composition ensures the refractoriness above 1665°C. [ABSTRACT FROM AUTHOR]

The ferrochromium slag is an important by-product of ferrochromium industries. Recycling and efficient utilization of the large volumes of slag generated by ferrochrome production process is a huge challenge for ferrochrome producers. This article reviews ferrochromium slag utilization with reference to refractory, ceramics and construction and other applications. In addition to this the development of crystal phases and the environmental aspects of ferrochromium slag in relation to its utilization are discussed. The crystalline phases evolve during solidification impart unique properties like strength, stability and refractoriness which open its opportunities as an alternative raw material for ceramic, refractory, civil construction. Chemical composition of ferrochromium slag can be altered suitably for application in high temperature refractory ceramic application. The use of ferrochromium slag in building and road making material will relieve some of the burden from natural resources. [ABSTRACT FROM AUTHOR]

Data-driven models are constructed for leaching processes of various low grade manganese resources using various nature inspired strategies based upon genetic algorithms, neural networks, and genetic programming and subjected to a bi-objective Pareto optimization, once again using several evolutionary approaches. Both commercially available software and in-house codes were used for this purpose and were pitted against each other. The results led to an optimum trade-off between maximizing the recovery, which is a profit oriented requirement, along with a minimization of the acid consumption, which addresses the environmental concerns. The results led to a very complex scenario, often with different trends shown by the different methods, which were systematically analyzed. [ABSTRACT FROM AUTHOR]

Several hydrometallurgical processes have been studied for the extraction of metals from lean ores utilizing various flow sheet options. Of particular significance is the grade of the ore being treated, the energy consumed and associated costs, options for byproduct recovery, and the relative price of the products. A process scheme needs to be optimized for simultaneously maximizing metal throughput and minimizing the direct operating costs incurred within constraints set for the operating variables. This leads to a multi-objective optimization problem. The range of input grades for raw material, which a flowsheet can handle, needs to be worked out based on an optimization exercise. A lean manganese-bearing resource such as polymetallic sea nodules has been chosen in this article for the development of an optimization approach based on which the input raw nodules grades are to be treated by a particular flowsheet. Only the chemical consumption costs have been adopted in this article as a measure of direct operating costs. A linear simulation model for the flowsheet has been developed, keeping a set of design parameters constant. The solutions generated by using a sequential modular approach become inputs to an optimization procedure based on a multi-objective genetic algorithm belonging to the differential evolution family. The variables considered in the optimization task are the grade of nodules and reactivity of different species inside the reactor. A nickel equivalent (t/h function) has been suggested as a measure of productivity, as it indirectly enhances the input manganese ore grade through a price ratio effect. This productivity function was maximized with the simultaneous minimization of direct chemical costs. Pareto optimal solutions were generated with grades of nodules and reactivity in the leach reactor as decision variables. The effect of the price ratio on the Pareto optimal solutions was also investigated. The various cases investigated clarifies the methodology for choosing an appropriate ore grade range for a given process flowsheet. Appropriate decisions regarding the nature of raw material to be used for a given flowsheet are then found on the basis of the Pareto optimal solutions. [ABSTRACT FROM AUTHOR]

Existing acid leaching data for low-grade manganese ores are modeled using an evolving neural net. Three distinct cases of leaching in the presence of glucose, sucrose and lactose have been considered and the results compared with an existing analytical model. The neural models are then subjected to bi-objective optimization, using a predator-prey genetic algorithm, maximizing recovery in tandem with a minimization of the acid concentration. The resulting Pareto frontiers are analyzed and discussed. [ABSTRACT FROM AUTHOR]

Treatment of low grade manganese ores is receiving widespread attention due to major use of manganese (85-90%) as ferromanganese alloy in the rapidly growing iron and steel sector and also in other important industrial products like electrolytic manganese dioxide (EMD) used in the energy sector. Manganese bearing polymetallic sea nodules containing less than 40% Mn fall in the category of lean grade ores and besides manganese these nodules are the reserve for other metals like copper, nickel, and cobalt. In this present work, treatment of these polymetallic sea nodules in an acid-based hydrometallurgical route has been proposed using two different schemes, batch and parallel in nature. Both processes have been optimized using multiobjective genetic algorithms. [ABSTRACT FROM AUTHOR]