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.

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Mechanisms of molecular and structural interactions between lentil and quinoa proteins in aqueous solutions induced by pH recycling

There has been a growing interest in plant proteins due to their beneficial health effects, low cost and variety of applications in food industries. The low solubility of lentil proteins (LPs) is one of the significant factors that limit their use in food applications. Quinoa proteins (QPs), which have high water solubility, were combined with LPs at pH 12 to generate LP-QP complexes to generate pH-based soluble protein compounds. The LP-QP complexes demonstrated a large surface charge with an increase solubilisation of the protein complexes by more than 85%, together with resistance to protein aggregation. The combination of LPs to QPs led to a significant increase (P < 0.05) in unique tertiary and secondary protein structures as determined by the protein–protein interaction (PPI) technique involving pH recycling. Interactions between LPs and QPs affected the surface morphology of the protein complexes formed. Electrostatic interactions, hydrophobic forces and hydrogen bonding were indicated to play key roles in the PPIs. The capacity of pH cycling to illustrate the above protein interactions shows that this is a robust approach for assessing the emulsion and foaming properties of food proteins.     

Low Temperature Hall Effect Investigation of Conducting Polymer-Carbon Nanotubes Composite Network

Polypyrrole (PPy) and polypyrrole-carboxylic functionalized multi wall carbon nanotube composites (PPy/f-MWCNT) were synthesized by in situ chemical oxidative polymerization of pyrrole on the carbon nanotubes (CNTs). The structure of the resulting complex nanotubes was characterized by transmission electron microscopy (TEM) and X-ray diffraction (XRD). The effects of f-MWCNT concentration on the electrical properties of the resulting composites were studied at temperatures between 100 K and 300 K. The Hall mobility and Hall coefficient of PPy and PPy/f-MWCNT composite samples with different concentrations of f-MWCNT were measured using the van der Pauw technique. The mobility decreased slightly with increasing temperature, while the conductivity was dominated by the gradually increasing carrier density.     

Synthesis and Characterization of Novel Sulfur-Functionalized Silica Gels as Mercury Adsorbents

This paper describes the synthesis, functionalization, and characterization of silica gels as mercury adsorbents. The synthesis was carried out according to the modified Stöber method using tetraethyl orthosilicate [TEOS], 3-mercaptopropyl trimethoxysilane [MPTMS] and bis(triethoxysilylpropyl) tetrasulfide [BTEPST] as precursors. The functionalization was carried out via co-condensation and impregnation methods using MPTMS, BTESPT, elemental sulfur [ES], and carbon disulfide [CS₂] as sulfur ligands. The choice of the sulfur ligands as precursors and functionalization agents was due to the existence of sulfur active groups in their molecular structures which were expected to have high affinity toward Hg(II) ions. The synthesized adsorbents were characterized by using scanning electron microscope, fourier transform infrared spectrophotometer, nitrogen adsorption/desorption, and energy dispersive X-ray diffractometer. The batch Hg(II) adsorption experiments were employed to evaluate the Hg(II) adsorption performances of the synthesized adsorbents under different pH values. The results revealed that the highest Hg(II) adsorption capacity was obtained for the SG-MPTMS(10) which was 47.83 mg/g at pH 8.5. In general, the existence of sulfur functional groups, especially MPTMS in the silica matrices, gave a significant enhancement of Hg(II) adsorption capacity and the sulfur functionalization via co-condensation method, which is potential as a superior approach in the mercury adsorbent synthesis.