Fungal xylanases‐mediated synthesis of silver nanoparticles for catalytic and biomedical applications

Green synthesis of nanoparticles has fuelled the use of biomaterials to synthesise a variety of metallic nanoparticles. The current study investigates the use of xylanases of Aspergillus niger L3 (NEA) and Trichoderma longibrachiatum L2 (TEA) to synthesise silver nanoparticles (AgNPs). Characterisation of AgNPs was carried out using UV–Vis spectroscopy, Fourier transform infrared spectroscopy (FTIR), and transmission electron microscopy, while their effectiveness as antimicrobial, antioxidant, catalytic, anticoagulant, and thrombolytic agents were determined. The colloidal AgNPs was brownish with surface plasmon resonance at 402.5 and 410 nm for NEA‐AgNPs and TEA‐AgNPs, respectively; while FTIR indicated that protein molecules were responsible for the capping and stabilisation of the nanoparticles. The spherical nanoparticles had size of 15.21–77.49 nm. The nanoparticles significantly inhibited the growth of tested bacteria (63.20–88.10%) and fungi (82.20–86.10%), and also scavenged DPPH (37.48–79.42%) and hydrogen peroxide (20.50–96.50%). In addition, the AgNPs degraded malachite green (78.97%) and methylene blue (25.30%). Furthermore, the AgNPs displayed excellent anticoagulant and thrombolytic activities using human blood. This study has demonstrated the potential of xylanases to synthesise AgNPs which is to the best of our knowledge the first record of such. The present study underscores the relevance of xylanases in nanobiotechnology.Inspec keywords: visible spectra, catalysis, ultraviolet spectra, silver, microorganisms, antibacterial activity, transmission electron microscopy, surface plasmon resonance, nanoparticles, nanofabrication, colloids, blood, Fourier transform infrared spectra, particle sizeOther keywords: Ag, fungal xylanases‐mediated synthesis, silver nanoparticles, catalytic applications, biomedical applications, green synthesis, metallic nanoparticles, Trichoderma longibrachiatum L2, transmission electron microscopy, antimicrobial agents, antioxidant agents, catalytic agents, thrombolytic agents, surface plasmon resonance, spherical nanoparticles, FTIR spectra, anticoagulant agents, colloidal nanoparticles, biomaterials, Aspergillus niger L3, UV‐vis spectroscopy, Fourier transform infrared spectroscopy, protein molecules, DPPH, hydrogen peroxide, malachite green, methylene blue, human blood, nanobiotechnology     

Type 2 Diabetes Risk Prediction Using Deep Convolutional Neural Network Based-Bayesian Optimization

Diabetes mellitus is a long-term condition characterized by hyperglycemia. It could lead to plenty of difficulties. According to rising morbidity in recent years, the world’s diabetic patients will exceed 642 million by 2040, implying that one out of every ten persons will be diabetic. There is no doubt that this startling figure requires immediate attention from industry and academia to promote innovation and growth in diabetes risk prediction to save individuals’ lives. Due to its rapid development, deep learning (DL) was used to predict numerous diseases. However, DL methods still suffer from their limited prediction performance due to the hyperparameters selection and parameters optimization. Therefore, the selection of hyper-parameters is critical in improving classification performance. This study presents Convolutional Neural Network (CNN) that has achieved remarkable results in many medical domains where the Bayesian optimization algorithm (BOA) has been employed for hyperparameters selection and parameters optimization. Two issues have been investigated and solved during the experiment to enhance the results. The first is the dataset class imbalance, which is solved using Synthetic Minority Oversampling Technique (SMOTE) technique. The second issue is the model's poor performance, which has been solved using the Bayesian optimization algorithm. The findings indicate that the Bayesian based-CNN model superbases all the state-of-the-art models in the literature with an accuracy of 89.36%, F1-score of 0.88.6, and Matthews Correlation Coefficient (MCC) of 0.88.6.     

Light and Electron Microscopy Studies of the Visible Diffusion Zone of Mild Steel Pack Cyanided in Processed Cassava Leaves

This study investigates the microstructure of the processed cassava leaves. Standard parts machined from low visible diffusion zone formed in low carbon steel pack cyanided using carbon steel were pack cyanided by high temperature in-situ diffusion of nascent carbon and nitrogen into austenite. Formation of a visible diffusion zone was confirmed after observation with a Reichert-Jung Polyval optical microscope coupled with Zeiss AxioCam ICc 1 camera. High magnification Scanning Electron Microscope （SEM） imaging of the visible diffusion zone was done with a CamScan Series 2 scanning electron microscope. The zone was found variable in depth as measured from a representative position. The structure of all samples consists of ferrite and pearlite as determined by optical and SEM examination. Resulting products were thus both tough and hard suitable for service environments requiring high resistance to both wear and impact failure.     

Design and fabrication of flexible poly(vinyl chloride) dielectric composite reinforced with ZnO microvaristors

Flexible poly(vinyl chloride)/varistor composites were fabricated by solution casting method. High‐field ZnO varistor particles processed from micron‐sized Zn dust is explored as multifunctional filler for PVC composites. Mechanical blending of Zn dust with La₂O₃‐CeO₂ rare earths and varistor forming minor additives followed by sintering at 1250 °C resulted in fine‐grained ZnO varistors. Bulk varistor was subsequently milled to obtain ZnO microvaristor grains. The effect of microvaristor on the UV stability, dielectric, and mechanical properties of the PVC composite was analyzed. The varistor filler in PVC enhanced the microhardness and retained the tensile properties without any significant loss. After UV irradiation PVC/varistor composite shows remarkable mechanical stability retention (95%) compared to pure PVC (75%). Also, microvaristor reinforcement resulted in dielectric constant tunability (? = 2–37) without any drastic change in the dielectric loss (0.02–0.05). Thus, Zn dust‐derived ZnO varistors could be potentially exploited to design functional PVC composites for electronic applications. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2018 , 135, 46031.     

Predicting correlations properties of crude oil systems using type-2 fuzzy logic systems

This paper presented a new prediction model of pressure–volume–temperature (PVT) properties of crude oil systems using type-2 fuzzy logic systems. PVT properties are very important in the reservoir engineering computations, and its accurate determination is important in the primary and subsequent development of an oil field. Earlier developed models are confronted with several limitations especially in uncertain situations coupled with their characteristics instability during predictions. In this work, a type-2 fuzzy logic based model is presented to improve PVT predictions. In the formulation used, the value of a membership function corresponding to a particular PVT properties value is no longer a crisp value; rather, it is associated with a range of values that can be characterized by a function that reflects the level of uncertainty. In this way, the model will be able to adequately model PVT properties. Comparative studies have been carried out and empirical results show that Type-2 FLS approach outperforms others in general and particularly in the area of stability, consistency and the ability to adequately handle uncertainties. Another unique advantage of the newly proposed model is its ability to generate, in addition to the normal target forecast, prediction intervals without extra computational cost.     

Surface morphology,thermomechanical and barrier properties of poly(ether sulfone)‐toughened epoxy clay ternary nanocomposites

Poly(ether sulfone) (PES)‐toughened epoxy clay ternary nanocomposites were prepared by melt blending of PES with diglycidyl ether of bisphenol A epoxy resin along with Cloisite 30B followed by curing with 4,4′‐diaminodiphenylsulfone. The effect of organoclay and thermoplastic on the fracture toughness, permeability, viscoelasticity and thermomechanical properties of the epoxy system was investigated. A significant improvement in fracture toughness and modulus with reduced coefficient of thermal expansion (CTE) and gas permeability were observed with the addition of thermoplastic and clay to the epoxy system. Scanning electron microscopy of fracture‐failed specimens revealed crack path deflection and ductile fracture without phase separation. Oxygen gas permeability was reduced by 57% and fracture toughness was increased by 66% with the incorporation of 5 phr clay and 5 phr thermoplastic into the epoxy system. Optical transparency was retained even with high clay content. The addition of thermoplastic and organoclay to the epoxy system had a synergic effect on fracture toughness, modulus, CTE and barrier properties. Planetary ball‐milled samples gave exfoliated morphology with better thermomechanical properties compared to ultrasonicated samples with intercalated morphology. Copyright © 2010 Society of Chemical Industry