Preparation of urushiol-containing poly(methyl methacrylate) copolymers for antibacterial and antifouling coatings

Synthesis of an eco-friendly and efficient antibacterial and antifouling coatings is presented by exploiting urushiol, a natural varnishing material. Since urushiol has inherent outstanding surface-protecting and antimicrobial properties, a series of poly (methyl methacrylate)-urushiol polymer compositions were prepared and fabricated into films. The prepared films were subjected to antimicrobial and antifouling studies. The polymer systems were characterized by various physico-spectroscopic techniques such as ¹H NMR, Fourier transform infrared spectroscopy, differential scanning calorimetry, atomic force microscopy, and thermal gravimetric analysis. The confocal laser scanning micrographs, obtained for Pseudomonas aeruginosa biofilm formation, demonstrated an excellent antimicrobial response of the urushiol-incorporated polymers against this bacterial strain. We also demonstrated an inhibitory attachment effect against Navicula incerta, a fouling microalgal strain.     

A Hierarchical 3D Nanostructured Microfluidic Device for Sensitive Detection of Pathogenic Bacteria

Efficient capture and rapid detection of pathogenic bacteria from body fluids lead to early diagnostics of bacterial infections and significantly enhance the survival rate. We propose a universal nano/microfluidic device integrated with a 3D nanostructured detection platform for sensitive and quantifiable detection of pathogenic bacteria. Surface characterization of the nanostructured detection platform confirms a uniform distribution of hierarchical 3D nano‐/microisland (NMI) structures with spatial orientation and nanorough protrusions. The hierarchical 3D NMI is the unique characteristic of the integrated device, which enables enhanced capture and quantifiable detection of bacteria via both a probe‐free and immunoaffinity detection method. As a proof of principle, we demonstrate probe‐free capture of pathogenic Escherichia coli (E. coli) and immunocapture of methicillin‐resistant‐Staphylococcus aureus (MRSA). Our device demonstrates a linear range between 50 and 10⁴ CFU mL^?1, with average efficiency of 93% and 85% for probe‐free detection of E. coli and immunoaffinity detection of MRSA, respectively. It is successfully demonstrated that the spatial orientation of 3D NMIs contributes in quantifiable detection of fluorescently labeled bacteria, while the nanorough protrusions contribute in probe‐free capture of bacteria. The ease of fabrication, integration, and implementation can inspire future point‐of‐care devices based on nanomaterial interfaces for sensitive and high‐throughput optical detection.     

Optical properties of Eu<Superscript>3+</Superscript> activated SrLa<Subscript>2</Subscript>O<Subscript>4</Subscript> red-emitting phosphors for WLED applications

The SrLa_2?xO₄:xEu³⁺ phosphors are synthesized through high-temperature solid-state reaction method at 1473 K with various doping concentration. Their phase structures, absorption spectra, and luminescence properties are investigated by X-ray diffraction (XRD), UV–Vis spectrophotometer and photoluminescence spectrometry. The intense absorption of SrLa_2?xO₄:xEu³⁺ phosphors have occurred around 400 nm. The prominent luminescence spectra of the prepared phosphors exhibited bright red emission at 626 nm. The doping concentration 0.12 mol% of Eu³⁺ is shown to be optimal for prominent red emission and chromaticity coordinates are x?=?0.692, y?=?0.3072. Considering the high colour purity and appropriate emission intensity of Eu³⁺ doped SrLa₂O₄ can be used as red phosphors for white light emitting diodes (WLEDs).     

Diabetic Retinopathy Detection from Fundus Images Using Machine Learning Techniques : A Review

Diabetic retinopathy is one of the leading causes of blindness in today’s world. One of the major causes of Diabetic retinopathy is diabetes and also this occurs due to hereditary reasons. DR is classified into proliferative, non-proliferative and diabetic maculopathy. This paper approaches to one of the signs of non-proliferative DR called as exudates (commonly called hard exudates) and several methods which is introduced to detect them in retina. The work includes the algorithms, outcomes, datasets used and other results related with it. The results are compared by tabulating the evaluations and procedures.

     

Correction to: The Impact of Memory‑Efficient Bots on IoT‑WSN Botnet Propagation

Wireless Personal Communications - The Acknowledgements section in the initial online publication was incomplete. The original article has been corrected.     

A meta‐heuristic Bayesian network classification for intrusion detection

Software‐defined networking (SDN) is an innovative network paradigm much in demand today in academics and industry. In this network, the SDN controller must be able to observe and examine traffic flow through the network systems. However, intrusion‐based data packets affect the whole system is a major drawback. To overcome this issue, we propose a Novel Agent Program (NAP) framework for preventing switches from the external compromised attacks. A Meta‐Heuristic Bayesian Network Classification (MHBNC) algorithm for intrusion detection is proposed in this paper. The proposed algorithm follows certain procedures for preprocessing, feature selection, feature optimization, and classification. Normal and anomaly‐based data packets are classified successfully with its improved detection capabilities based on the optimization technique. The simulation results of the proposed ID_MBC (intrusion detection based on meta‐heuristic Bayesian classifier) technique is compared with existing techniques such as the association rule, PSO+GA, and the GA+RVM. The proposed MHBNC classifier performs better than existing methods.     

Investigation of polymer dynamics in chitosan-maghemite nanocomposites: a potential green superparamagnetic material

Magnetic composites with superparamagnetic properties have attracted great scientific interest recently. In this article we have investigated chitosan-maghemite (γ-Fe₂O₃) nanocomposite. We have analyzed the effect of temperature and the concentration of maghemite nanoparticles upon the relaxation behaviour of the nanocomposite using Broad band dielectric spectroscopy (BDS). Additionally, various characterization techniques such as X-ray diffraction (XRD), Fourier transform infra red spectra (FTIR), Scanning electron microscopy (SEM), Transmission electron spectroscopy (TEM), Thermo gravimetric Analysis (TGA), Vibrating Sample Magnetometer (VSM), Atomic Force Microscopy (AFM) and Raman spectroscopy have been used for our investigation. Our investigation shows that maghemite nanoparticles interact with chitosan leading to morphological changes in the films and results in modifications in the dielectric and electrical characteristics of the nanocomposite. New relaxations have been identified and their modifications due to maghemite nanoparticles have been investigated. The nanocomposites exhibit superparamagnetic behaviour. This research will benefit research in battery technology and super capacitors.     

Multi-objective search group algorithm for thermo-economic optimization of flat-plate solar collector

Neural Computing and Applications - This study aims to develop a multi-objective version of the search group algorithm (SGA) called the multi-objective search group algorithm (MOSGA) to help...     

Nanosize stabilization of cubic and tetragonal phases in reactive plasma synthesized zirconia powders

Pure zirconium oxide powders with particle size 2–33 nm are synthesized by reactive plasma processing. Transmission electron microscopy investigation of these particles revealed size dependent behavior for their phase stabilization. The monoclinic phase is found to be stable when particle size is ≥20 nm; Tetragonal is found to be stabilized in the range of 7–20 nm and as the particle size decreases to 6 nm and less, the cubic phase is stabilized.