Optimizing culture conditions for the production of endo-&#946-1,4-glucanase by Aspergillus awamori strain Vietnam Type Culture Collection (VTCC)-F099

In the present study, twenty six strains of Aspergillus awamori from the Vietnam Type Culture Collection (Institute of Microbiology and Biotechnology, Vietnam University Hanoi) were used for the endoglucanase production by growing at 37°C in the growth medium. Result showed that A. awamori strain VTCC-F099 produced the highest level of endo β-1,4-glucanase in the growth medium, pH 6.5, at 30°C for 96 h, agitated at 200 rpm. The optimal concentration of the inducer CMC (carboxymethyl cellulose) for the endoglucanase production by A. awamori VTCC-F099 was 2%. Among tested carbon sources (coconut fiber, coffee shell, corncob, dried tangerine skin, peanut shell, rice bran, saw dust, sugar-cane bagasse as organic wasters and glucose, lactose sucrose as pure carbon sources), corncob showed the highest endoglucanase production by A. awamori VTCC-F099 at the concentration of 3%. Ammonium acetate was the best among nitrogen source (casein, peptone, fish powder, soybean powder as organic sources and CH3COONH4, NH4NO3, (NH4)2SO4, urea as inorganic sources) for the endoglucanase production by A. awamori VTCC-F099 at the concentration of 0.3%.Key words: Aspergillus awamori, carboxymethyl cellulose, endoglucanase production, optimization of culture conditions

Effect of Dissolved Silicon on the Removal of Heavy Metals from Aqueous Solution by Aquatic Macrophyte Eleocharis acicularis

Silicon (Si) has been recently reconsidered as a beneficial element due to its direct roles in stimulating the growth of many plant species and alleviating metal toxicity. This study aimed at validating the potential of an aquatic macrophyte Eleocharis acicularis for simultaneous removal of heavy metals from aqueous solutions under different dissolved Si. The laboratory experiments designed for determining the removal efficiencies of heavy metals were conducted in the absence or presence of Si on a time scale up to 21 days. Eleocharis acicularis was transplanted into the solutions containing 0.5 mg L−1 of indium (In), gallium (Ga), silver (Ag), thallium (Tl), copper (Cu), zinc (Zn), cadmium (Cd), and lead (Pb) with various Si concentrations from 0 to 4.0 mg L−1. The results revealed that the increase of dissolved Si concentrations enhanced removal efficiencies of E. acicularis for Ga, Cu, Zn, Cd, and Pb, while this increase did not show a clear effect for In, Tl, and Ag. Our study presented a notable example of combining E. acicularis with dissolved Si for more efficient removals of Cu, Zn, Cd, Pb, and Ga from aqueous solutions. The findings are applicable to develop phytoremediation or phytomining strategy for contaminated environment.</jats:p

A modified dual-population approach for solving multi-objective problems

Maintaining the balance between convergence and diversity plays a vital role in multi-objective evolutionary algorithms (MOEAs). However, most MOEAs cannot reach a satisfying balance, especially when solving problems having complicated pareto optimal sets. In this paper, we present a modified cooperative co-evolution approach for achieving better convergence and diversity simultaneously (namely DPP2). In DPP2, while populations are trying to achieve both criteria, the priority being set for these criteria will be different. One population focuses on achieving better convergence (by using pareto-based ranking scheme), while the other is for ensuring the population diversity (by using the decomposition-based method). After that, we use a cooperation mechanism to integrate the two populations and create a new combined population with hopes of having both characteristics (i.e. converged and diverse). Performance of DPP2 is examined on the well-known benchmarks of multiobjective optimization problems (MOPs) using the hypervolume (HV), the generational distance (GD), the inverted generational distance (IGD) metrics. In comparison with the original version DPP algorithm, experimental results indicated that DPP2 can significantly outperform DPP on the benchmark problems with stable results

A competitive co-evolutionary approach for the multi-objective evolutionary algorithms

In multi-objective evolutionary algorithms (MOEAs), convergence and diversity are two basic issues and keeping a balance between them plays a vital role. There are several studies that have attempted to address this problem, but this is still an open challenge. It is thus the purpose of this research to develop a dual-population competitive co-evolutionary approach to improving the balance between convergence and diversity. We utilize two populations to solve separate tasks. The first population uses Pareto-based ranking scheme to achieve better convergence, and the second one tries to guarantee population diversity via the use of a decomposition-based method. Next, by operating a competitive mechanism to combine the two populations, we create a new one with a view to having both characteristics (i.e. convergence and diversity). The proposed method’s performance is measured by the renowned benchmarks of multi-objective optimization problems (MOPs) using the hypervolume (HV) and the inverted generational distance (IGD) metrics. Experimental results show that the proposed method outperforms cutting-edge coevolutionary algorithms with a robust performance

Existence of solution to a new class of coupled variational-hemivariational inequalities

The objective of this paper is to introduce and study a complicated nonlinear system, called coupled variational-hemivariational inequalities, which is described by a highly nonlinear coupled system of inequalities on Banach spaces. We establish the nonemptiness and compactness of the solution set to the system. We apply a new method of proof based on a multivalued version of the Tychonoff fixed point principle in a Banach space combined with the generalized monotonicity arguments, and elements of the nonsmooth analysis. Our results improve and generalize some earlier theorems obtained for a very particular form of the system.Comment: 17

Wastewater treatment and biomass growth of eight plants for shallow bed wetland roofs

© 2017 Elsevier Ltd Wetland roof (WR) could bring many advantages for tropical cities such as thermal benefits, flood control, green coverage and domestic wastewater treatment. This study investigates wastewater treatment and biomass growth of eight local plants in shallow bed WRs. Results showed that removal rates of WRs were 21–28 kg COD ha−1 day−1, 9–13 kg TN ha−1 day−1 and 0.5–0.9 kg TP ha−1 day−1, respectively. The plants generated more biomass at lower hydraulic loading rate (HLR). Dry biomass growth was 0.4–28.1 g day−1 for average HLR of 247–403 m3 ha−1 day−1. Green leaf area of the plants was ranging as high as 67–99 m2 leaves per m2 of WR. In general, the descent order of Kyllinga brevifoliaRottb (WR8), Cyperus javanicus Houtt (WR5) and Imperata cylindrical (WR4) was suggested as effective vegetations in WR conditions in terms of wastewater treatment, dry biomass growth and green coverage ratio

Arsenic removal by a membrane hybrid filtration system

Arsenic is a toxic semi-metallic element that can be fatal to human health. Membrane filtration can remove a number of contaminants from water, including arsenic. Removal of arsenic by membrane filtration is highly dependent on the species of arsenic and the properties of the membrane. The performance of the nanofilter is better for removing As(V) than As(III). About 57% of As(III) and 81% of As(V) was removed from 500 mg/L arsenic solutions by nanofiltration (NTR729HF, Nitto Denko Corp., Japan) of 700 molecular weight (MW) cutoff. The removal efficiency of microfiltration (MF) was much lower than that of nanofiltration (NF) due to its larger pore size. By comparison only 37% of As(III) and 40% of As(V) were removed by microfiltration (PVA membrane, Pure-Envitech, Korea). However, the removal efficiency of microfiltration was increased dramatically when a small amount of nanoscale zero valent iron (nZVI) was added. The removal efficiency by MF increased up to 90% with As(V) and 84% with As(III) when an amount of 0.1 g/L of nZVI was added into the arsenic solution. © 2008 Elsevier B.V. All rights reserved

Phosphate Adsorption by Silver Nanoparticles-Loaded Activated Carbon derived from Tea Residue.

This study presents the removal of phosphate from aqueous solution using a new silver nanoparticles-loaded tea activated carbon (AgNPs-TAC) material. In order to reduce costs, the tea activated carbon was produced from tea residue. Batch adsorption experiments were conducted to evaluate the effects of impregnation ratio of AgNPs and TAC, pH solution, contact time, initial phosphate concentration and dose of AgNPs-AC on removing phosphate from aqueous solution. Results show that the best conditions for phosphate adsorption occurred at the impregnation ratio AgNPs/TAC of 3% w/w, pH 3, and contact time lasting 150 min. The maximum adsorption capacity of phosphate on AgNPs-TAC determined by the Langmuir model was 13.62 mg/g at an initial phosphate concentration of 30 mg/L. The adsorption isotherm of phosphate on AgNPs-TAC fits well with both the Langmuir and Sips models. The adsorption kinetics data were also described well by the pseudo-first-order and pseudo-second-order models with high correlation coefficients of 0.978 and 0.966, respectively. The adsorption process was controlled by chemisorption through complexes and ligand exchange mechanisms. This study suggests that AgNPs-TAC is a promising, low cost adsorbent for phosphate removal from aqueous solution

Highly accurate step counting at variouswalking states using low-cost inertial measurement unit support indoor positioning system

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Accurate step counting is essential for indoor positioning, health monitoring systems, and other indoor positioning services. There are several publications and commercial applications in step counting. Nevertheless, over-counting, under-counting, and false walking problems are still encountered in these methods. In this paper, we propose to develop a highly accurate step counting method to solve these limitations by proposing four features: Minimal peak distance, minimal peak prominence, dynamic thresholding, and vibration elimination, and these features are adaptive with the user’s states. Our proposed features are combined with periodicity and similarity features to solve false walking problem. The proposed method shows a significant improvement of 99.42% and 96.47% of the average of accuracy in free walking and false walking problems, respectively, on our datasets. Furthermore, our proposed method also achieves the average accuracy of 97.04% on public datasets and better accuracy in comparison with three commercial step counting applications: Pedometer and Weight Loss Coach installed on Lenovo P780, Health apps in iPhone 5s (iOS 10.3.3), and S-health in Samsung Galaxy S5 (Android 6.01)