Features of Thermomechanical Stability of Anionic–Cation Exchange Matrix “Polikon AC” on Viscose Non-Woven Materials

The thermomechanical stability of the anion–cation exchange matrix “Polikon AC” on viscose nonwoven materials is investigated. In this work, a molecular model of a solvation environment for experimentally obtained “Polikon AC” mosaic membranes is refined. Mosaic membranes on a viscose fiber base were fabricated by the method of polycondensation filling. The temperature dependence of deformation was investigated for dry and wet anion and cation exchange membrane components at a constant tensile load of 1.5 N and a heating rate of 8 °C/min. The effect of moisture content on the deformation of anionite and cationite fragments under a constant external tensile load of 1.5 and 3 N in a temperature range up to 100 °C was studied.

Nopalea cochenillifera Biomass as Bioadsorbent in Water Purification

Contaminated water consumption is one of the greatest risks to human health, especially in underdeveloped and developing countries. Water is a universal right, but millions of people worldwide consume untreated surface water. The objective in this study is to evaluate water purification with Nopalea cochenillifera var. Miúda biomass. Fragments (1, 2, and 3 g) of N. cochenillifera were added to the aqueous solution containing red-yellow Chromic and Podzolic Luvisol simulating turbid water sources in Northeastern Brazil. The total, non-structural (i.e., reducing and non-reducing sugars, alcohol insoluble solids), and structural (i.e., pectin) carbohydrates, adsorption kinetics, turbidity, electrical conductivity, pH, zeta potential, and total coliforms presence were evaluated. Findings show that the Nopalea cochenillifera biomass adsorbed the suspended particles in the aqueous solution, making it more translucent due to the complex and heterogeneous adsorbents’ ion exchange matrix, but the biomass addition did not eliminate total coliforms from the aqueous solution. We concluded that the Nopalea cochenillifera biomass water treatment reduces suspended dissolved particles and turbidity, but it needs to be associated with other treatments to eliminate total coliforms and ensure water safety for human consumption.

Gas Turbine Tubular Coilpipes Regenerators Optimized According to the Minimum Mass Criterion

The aim of this work is to determine the effect of the elements, which do not participate in heat transfer, on the mass of the regenerator of a gas turbine plant X, as well as to define the re-strictions that are imposed on the regenerator design based on the conditions of manufacturabil-ity, placement at the facility and transportability. This goal is achieved using an algorithm for finding rational geometric parameters of the heat exchange matrix with minimization of the re-generator mass by Newton's method. It has been determined that the mass of the heat exchange matrix can be 0.48–0.58 of the mass of the regenerator. This makes it necessary, even at the initial design stages, to take into account the effect of the above factors on the mass of the re-generator and the choice of the rational geometrical parameters. A significant result of the stud-ies performed is determination of the effect of dimensional restrictions and requirements for the shape of the regenerator to be increased in its mass. The values of the geometrical parameters of the heat exchange matrix were obtained, at which the mass of the regenerator takes on a mini-mum value. The significance of the work is that the obtained relationships between the mass of the regenerator and its geometry makes it possible to reduce the metal consumption of the regen-erator and the gas turbine plant, which allows designing the heat exchangers for power plants

The Ranked-Orbital Approach to Selecting Active Spaces

The past decade has seen a great increase in the application of high-throughput computation to a variety of important problems in chemistry. However, one area which has been resistant to the high-throughput approach is multireference wave function methods, in large part due to the technicalities of setting up these calculations and in particular the not always intuitive challenge of active space selection. As we look towards a future of applying high-throughput computation to all areas of chemistry, it is important to prepare these methods for large-scale automation. Here, we propose a ranked-orbital approach to selecting active spaces with the goal of standardizing multireference methods for high-throughput computation. This method allows for the meaningful comparison of different active space selection schemes and orbital localizations, and we demonstrate the utility of this approach across 1120 multireference calculations for the excitation energies of small molecules. Additionally, we propose our own active space selection scheme that estimates the importance of an orbital for the active space through a pair-interaction framework from orbital energies and features of the Hartree-Fock exchange matrix. We call this new scheme the "Approximate Pair Coefficient" (APC) method and it performs quite well for the test systems presented

The Ranked-Orbital Approach to Selecting Active Spaces

The past decade has seen a great increase in the application of high-throughput computation to a variety of important problems in chemistry. However, one area which has been resistant to the high-throughput approach is multireference wave function methods, in large part due to the technicalities of setting up these calculations and in particular the not always intuitive challenge of active space selection. As we look towards a future of applying high-throughput computation to all areas of chemistry, it is important to prepare these methods for large-scale automation. Here, we propose a ranked-orbital approach to selecting active spaces with the goal of standardizing multireference methods for high-throughput computation. This method allows for the meaningful comparison of different active space selection schemes and orbital localizations, and we demonstrate the utility of this approach across 1120 multireference calculations for the excitation energies of small molecules. Additionally, we propose our own active space selection scheme that estimates the importance of an orbital for the active space through a pair-interaction framework from orbital energies and features of the Hartree-Fock exchange matrix. We call this new scheme the "Approximate Pair Coefficient" (APC) method and it performs quite well for the test systems presented

CHARACTERISATION OF CHOLINESTERASE ACTIVITY FROM ASIAN SWAMP EEL; MONOPTERUS ALBUS, AND TESTING ITS CAPABILITIES AS A BIOSENSOR ON METAL ION CONTAMINATION / PENCIRIAN AKTIVITI KOLINESTERES DARI OTOT BELUT SAWAH; MONOPTERUS ALBUS, DAN PENGUJIAN KEUPAYAANNYA SEBAGAI BIOPENANDA TERHADAP PENCEMARAN ION LOGAM

The presence of high concentrations of heavy metals in the river impedes daily activities and damages the surrounding aquatic ecosystem. Continuous monitoring should be implemented to prevent continuous discharge resulting in increased levels of pollution over time. This study aims to determine the sensitivity of Monopterus albus muscle ChE to metal ions. Priorly, ChE was purified from M. albus muscle tissue using the ion exchange matrix, DEAE, with the yield percentage of 42.16% with the purification fold of 2.17. PTC was selected as a specific synthetic substrate with the highest concentration and lowest biomolecular constant at 145838 ± 7533 μM.min.-1mg.-1 and 0.26 mM, while optimal assay parameters were obtained at pH 7.5 at 20 ° C. Inhibition studies of metal ions involving Cr, Cd, Ag, As, Hg, Pb, Ni and Cu at the concentration of 10 mg/L. The activity of M. albus ChE was 56.61% inhibited by Hg2+ and the highest recorded compared to the other metals ion arranged in declining order; Cr <Cd = Ni <Cu <Pb <As <Ag. Overall, purified ChE from M. albus muscle has proven its ability to be applied as a biosensor that can be used for environmental monitoring programs.

EXPERIENCE OF THE INPUT-OUTPUT MODELS APPLICATION TO THE MOLDOVAN ECONOMY

The main goal of this article is to present an overview of the input-output models which have been applied to Moldovan economy development study. We examined: static input-output model, dynamic input-output model restricted by limited energy resources, and the Markov chain approach based on the input-output tables. All these models have been examined using statistic data referring to the input-output table, constructed on the base of aggregated branches of the Moldovan economy. Static and dynamic optimization models were formulated, simulation calculation was done and analysed. Input-output table balancing problem was solved using RAS method. For dynamic model matrix of the investment coefficients was constructed. The emphasis was putt on the problem of applying the theory of Markov chain for examination of the 19 and 16 branches in the framework of the input-output model for Republic of Moldova. A square exchange matrix of order has been constructed. Every branch was considered as one of the states of the Markov chain with states. We introduced a new -th absorption state so that the examined matrix became of the order . The obtained transition matrix – probabilities matrix has been used for forecasting

An improved gain-phase error self-calibration method for robust DOA estimation

A novel online antenna array calibration method is presented in this paper for estimating direction-of-arrival (DOA) in the case of uncorrelated and coherent signals with unknown gain-phase errors. Conventional calibration methods mainly consider incoherent signals for uniform linear arrays with gain-phase errors. The proposed method has better performance not only for uncorrelated signals but also for coherent signals. First, an on-grid sparse technique based on the covariance fitting criteria is reformulated aiming at gain-phase errors to obtain DOA and the corresponding source power, which is robust to coherent sources. Second, the gain-phase errors are estimated in the case of uncorrelated and coherent signals via introducing an exchange matrix as the pre-processing of a covariance matrix and then decomposing the eigenvalues of the covariance matrix. Those parameters estimate values converge to the real values by an alternate iteration process. The proposed method does not require the presence of calibration sources and previous calibration information unlike offline ways. Simulation results verify the effectiveness of the proposed method which outperforms the traditional approaches.