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In this paper, basic notions of von Neumann algebra and its direct analogous in the realm of groupoids and measure spaces have been considered. By recovering the action of a locally compact Lie group from a crossed product of a von Neumann algebra, other proof of one of a geometric proposition of O'Neil and an extension of it has been proposed. Also, using the advanced exploration of nilmanifolds in measure spaces and their corresponding automorphisms (Lie algebraic derivations) a different proof of an analytic proposition of Gordon and Mao has been attained. These two propositions are of the most important ones for rigidity problems of Riemannian manifolds especially 2-step nilmanifolds. Keywords. Von Neumann algebras, 2-step nilmanifolds, Free and ergodic actions, Derivations, Automorphisms., 1. Introduction Motivation. Let M is a simply connected 2-step nilpotent Lie group with a left invariant metric and [LAMBDA] is a cocompact discrete subgroup of isometries of M. In [...]

Chlorobenzoic acids (CBAs) are recalcitrant and toxic materials which enter the environment directly using pesticides and herbicides, or indirectly through the biodegradation of polychlorinated biphenyl (PCB) compounds. In the conducted study, biodegradation of 4-chlrobenzoic acid was investigated by Lysinibacillus macrolidesDSM54T, which had previously been isolated from PCB-polluted soils. Environmental factors including pH, temperature, 4-CBA concentration and inoculation percentage were optimized using response surface methodology (RSM). 58 experiments were designed according to Historical Data, because of the arbitrary selection of experiments, and the combined effects of the independent variables were investigated through the cubic model (P< 0.0001). Degradation percentage of 4-CBA was measured by gas chromatography/mass spectroscopy. One hundred percent removal of 4-CBA was statistically estimated after 96 h at the best environmental conditions, which were pH = 5.25, temperature = 32.75 (°C), 4-CBA concentration = 237.17 (ppm), and inoculation percentage = 18.32 (%V/V). The inoculation percentage was the most effective parameter on the biodegradation of 4-CBA (P< 0.0001), while, the temperature had the least impact (P= 0.7340). High removal efficiency (93.45% in practice and 100% in theory) proved that the examined strain could be a promising candidate for bioremediation of chlorobenzoic acids from polluted soils.

Optimization techniques are used to find the strategies for chemically enhanced oil recovery in a sandstone reservoir. This research develops a multi-objective optimization methodology by combining experimental design methods and artificial intelligence techniques. The capability of this hybrid artificial intelligence methodology is evaluated in the optimal design of control variables to achieve the highest performance of a surfactant/polymer injection project into a sandstone reservoir. In the first step, a two-level full factorial design is used to screen initial control variables. Thereafter a response surface methodology (RSM) is employed to optimize the RF and NPV of a CEOR application. The neuro-simulation technique provides the required outputs for screening and RSM designs. The performance of network is improved using the imperialist competitive algorithm (ICA). Having precise fitness functions, multi-attribute optimization was performed using particle swarm optimization (PSO) and fuzzy logic (FL). This paper discusses the advantages of different perspectives over single-objective approaches. Using the RF-objective PSO algorithm, RF exceeded 64% of original oil in place (OOIP), while the profit of project slumped to $5.90 MM. On the other hand, NPV-attribute PSO increased NPV to $8.48 MM. Meanwhile, RF, as the technical success of the project, plunged to less than 53% OOIP. However, the proposed multi-objective algorithm increased RF to 57% OOIP with NPV of $8.11 MM, solving the trade-off between technical and economic terms. The results of this study indicate the efficacy of proposed hybrid workflow for multi-attribute decision-making of CEOR field implementation.