Synthesis of Ion Imprinted Polymers by Copolymerization of Zn(II) and Al(III)8-hydroxy Quinolone Complexes with Divinylbenzene and Methacryclic Acid

In this research work, Zinc(II) and Aluminum(III)-IIP's were synthesized by optimizing the amount of methacrylic acid as monomer, divinylbenzene as cross-linker. The IIP's were functionalized with 8-hydroxy quinolone complexes of the two metal ions under thermal conditions by copolymerization with monomer and cross-linker. The IIP's and Non-IIP's were characterized using FT-IR, TGA, and SEM analysis. A quite remarkable difference in the size was observed of the polymers (Zn(II) 1.0 µm and Al(III) 0.1 µm). A stronger affinity was observed with IIP in comparison with Non-IIP at pH 3.1 and 4.5 for Zn(II) and Al(III) ions on their respective polymers.     

Deep Learning for Accelerated Seismic Reliability Analysis of Transportation Networks

To optimize mitigation, preparedness, response, and recovery procedures for infrastructure systems, it is essential to use accurate and efficient means to evaluate system reliability against probabilistic events. The predominant approach to quantify the impact of natural disasters on infrastructure systems is the Monte Carlo approach, which still suffers from high computational cost, especially when applied to large systems. This article presents a deep learning framework for accelerating seismic reliability analysis, on a transportation network case study. Two distinct deep neural network surrogates are constructed and studied: (1) a classifier surrogate that speeds up the connectivity determination of networks and (2) an end‐to‐end surrogate that replaces modules such as roadway status realization, connectivity determination, and connectivity averaging. Numerical results from k‐terminal connectivity analysis of a California transportation network subject to a probabilistic earthquake event demonstrate the effectiveness of the proposed surrogates in accelerating reliability analysis while achieving accuracies of at least 99%.     

Exploring the best sequence LSTM modeling architecture for flood prediction

Neural Computing and Applications - Accurate and efficient models for rainfall–runoff (RR) simulations are crucial for flood risk management. Recently, the success of the recurrent neural...     

A green approach for modification and functionalization of wool fabric using bio- and nano-technologies

In the present work, we propose a green and sustainable strategy for eco-friendly surface modification of wool structure using biosynthesized kerationlytic proteases, from C4-ITA-EGY, Streptomyces harbinensis S11-ITA-EGY and Streptomyces carpaticus S33-ITA-EGY, followed by subsequent environmentally sound functionalization of the bio-treated substrates using ZnONPs, ZrO₂NPs, ascorbic acid and vanillin, individually, to provide durable antibacterial as well as UV-protection properties. Both surface modification changes and the extent of functionalization of the final products were characterized by SEM, EDX, antibacterial efficacy, UV-blocking ability, loss in weight, nitrogen content and durability to washing analysis. The obtained data reveal that the developed green wool fabrics exhibit outstanding durable antibacterial activity and UV-blocking ability for fabricating multi-functional textile products that can be utilized in a wide range of sustainable protective textiles, irrespective of the used post-finishing formulation ingredients. The results also show that both modification and functionalization processes are governed by the type of enzyme and kind of active material respectively. Moreover, the biosynthesized kerationlytic proteases could be accessibly used to remove protein-based stains like blood and egg.

Graphical abstract

     

Inhibition of Listeria monocytogenes and Salmonella by Combinations of Oriental Mustard,Malic Acid,and EDTA

The antimicrobial activities of oriental mustard extract alone or combined with malic acid and EDTA were investigated against Salmonella spp. or Listeria monocytogenes at different temperatures. Five strain Salmonella or L. monocytogenes cocktails were separately inoculated in Brain Heart Infusion broth containing 0.5% (w/v) aqueous oriental mustard extract and incubated at 4 °C to 21 °C for 21 d. For inhibitor combination tests, Salmonella Typhimurium 02:8423 and L. monocytogenes 2–243 were individually inoculated in Mueller Hinton broth containing the mustard extract with either or both 0.2% (w/v) malic acid and 0.2% (w/v) EDTA and incubated at 10 °C or 21 °C for 10 to 14 d. Mustard extract inhibited growth of the L. monocytogenes cocktail at 4 °C up to 21 d (2.3 log₁₀ CFU/mL inhibition) or at 10 °C for 7 d (2.4 log₁₀ CFU/mL inhibition). Salmonella spp. viability was slightly, but significantly reduced by mustard extract at 4 °C by 21 d. Although hydrolysis of sinigrin in mustard extract by both pathogens was 2 to 6 times higher at 21 °C than at 4 °C to 10 °C, mustard was not inhibitory at 21 °C, perhaps because of the instability of its hydrolysis product (allyl isothiocyanate). At 21 °C, additive inhibitory effects of mustard extract with EDTA or malic acid led to undetectable levels of S. Typhimurium and L. monocytogenes by 7 d and 10 d, respectively. At 10 °C, S. Typhimurium was similarly susceptible, but combinations of antimicrobials were not more inhibitory to L. monocytogenes than the individual agents.     

Biosorption of thorium from aqueous solution by Ca-pretreated brown algae Cystoseira indica

The potential use of a biosorbent, Cystoseira indica, obtained from the Persian Gulf was investigated for the removal of Th (IV) ions from aqueous solutions by considering equilibrium, kinetic and thermodynamic aspects. The FT-IR spectra of unloaded and Th-loaded biomass indicated various functionalities on the biomass surface including hydroxyl, amide and carboxyl groups, which are responsible for the binding of thorium ions. Th (IV) uptake by C. indica was pH dependent. An increase in biosorbent dosage up to 1 g/L caused an increase in the Th (IV) percentage removal. Biosorption process at all studied initial Th (IV) ion concentrations follows the pseudo-second order kinetic model. The biosorption data could be well described by Redlich-Peterson isotherm in comparison to Langmuir and Freundlich isotherms. The maximum sorption capacity of Th (IV) by Langmuir isotherm was estimated to be 169.49 mg/g at 45 °C with pH of 3. The thermodynamic parameters indicated the biosorption of Th on the biomass was a feasible, spontaneous and endothermic process. Th sorption capacity remained unaffected or slightly affected (<10% inhibition) in the presence of several interfering ions such as uranium (VI), nickel (II) and copper (II). The reusability of the biomass was also determined after five sorption-desorption cycles.     

Spectral Fourier–Galerkin benchmark solution for natural convection in an inclined saturated porous medium

This paper presents some novel problems associated with the steady natural convection flow in an inclined square cavity filled with a saturated porous medium. The proposed method is a high-accurate spectral method based on the Fourier–Galerkin technique. The numerical results have demonstrated the advantage for the following reasons. (a) The high-accurate method deals with inclined geometries successfully. (b) The streamlines, isotherms, and the average Nusselt numbers are affected significantly by the inclination of the cavity for high values of Rayleigh number. (c) In contrast with the finite element method a highly accurate and efficient solution with less computational effort is obtained.     

A new mathematical model for integrating all incidence matrices in multi-dimensional cellular manufacturing system

In the past several years, many studies have been carried out on cellular manufacturing based on a two-dimensional machine–part incidence matrix. Since workers have important role in doing jobs on machines, assignment of workers to cells becomes a crucial factor for fully utilization of cellular manufacturing systems. In this paper, an attempt is made to solve cell formation problem and minimize the number of voids and exceptional elements in a three dimensional (cubic) machine–part–worker incidence matrix. The proposed mathematical model captures the capability of workers in doing different jobs. To demonstrate the effectiveness of the proposed model, the solution of some test problems is compared with the literature method.