Polyurethane/poly(ethylene‐co‐ethyl acrylate) and functional carbon black‐based hybrids: Physical properties and shape memory behavior

A polyurethane (PU) was developed from poly(dimethylamine‐co‐epichlorohydrin‐co‐ethylenediamine) (PDMAE) and polyethylene glycol (PEG) as soft segment and 2,4‐toluene diisocyanate (TDI) incorporating as hard segment. Later PU was blended with poly(ethylene‐co‐ethyl acrylate) (PEEA). Poly(vinyl alcohol)‐functionalized carbon black (CB‐PVA) nanoparticles was used as filler. The structure, morphology, mechanical, crystallization, and shape memory behavior (heat and voltage) were investigated methodically. Due to physical interaction of the blend components, unique self‐assembled network morphology was observed. The interpenetrating network was responsible for 83% rise in tensile modulus and 46% increase in Young's modulus of PU/PEEA/CB‐PVA 1 hybrid compared with neat PU/PEEA bend. Electrical conductivity was increased to 0.2 Scm^?1 with 1 wt % CB‐PVA nanofiller. The original shape of sample was almost 94% recovered using heat induced shape memory effect while 97% recovery was observed in an electric field of 40 V. Electroactive shape memory results were found better than heat stimulation effect. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43481.     

Cure characterization of Cycom 977‐2A carbon/epoxy composites for quickstep processing

In this effort, Quickstep, a relatively a new technique, have been employed for manufacturing of composite materials. The cure schedule provided by a prepreg manufacturer is usually designed for autoclave or other traditional processing techniques and thermosetting resin systems are formulated for ramp rate curing 2–3 K min^?1. While in case of Quickstep processing, ramp rates of 15 K min^?1 can be achieved, thus changing the chemorheology of resin. The cure process of 977‐2A carbon/epoxy composites was evaluated for Quickstep processing using differential scanning calorimetry (DSC), dynamic mechanical and thermal analysis, and Fourier transformed infrared and results were compared with cure cycle employed for autoclave curing. Optimum hold time for Quickstep processing at upper curing temperature (180°C) was determined using DSC. The hold time of 120 min at 180°C was found to be suitable for Quickstep cure cycle, producing a panel of similar degree of cure to that achieved through autoclave processing schedule. Final degree of cure was dependent on time spent at upper cure temperature and slightly on initial steps of the cure cycle which was used to control the resin flow, fiber wetting, and void removal. Quickstep processed samples exhibited higher T_g and crosslink density and similar molecular network structure to the autoclave cured samples. POLYM. ENG. SCI., 54:887–898, 2014. © 2013 Society of Plastics Engineers     

Accuracy improving guidelines for network anomaly detection systems

An unprecedented growth in computer and communication systems in the last two decades has resulted in a proportional increase in the number and sophistication of network attacks. In particular, the number of previously-unseen attacks has increased exponentially in the last few years. Due to the rapidly evolving nature of network attacks, a considerable paradigm shift has taken place in the intrusion detection community. The main focus is now on Network Anomaly Detection Systems (NADSs) which model and flag deviations from normal/benign behavior of a network and can hence detect previously-unseen attacks. Contemporary NADS borrow concepts from a variety of theoretical fields (e.g., Information theory, stochastic and machine learning, signal processing, etc.) to model benign behavior. These NADSs, however, fall short of achieving acceptable performance levels as therefore widespread commercial deployments. Thus, in this paper, we firstly evaluate the performance of eight prominent network-based anomaly detectors under malicious portscan attacks to identify which NADSs perform better than others and why. These NADSs are evaluated on three criteria: accuracy (ROC curves), scalability (with respect to varying normal and attack traffic rates, and deployment points) and detection delay. These criteria are evaluated using two independently collected datasets with complementary strengths. We then propose novel methods and promising guidelines to improve the accuracy and scalability of existing and future anomaly detectors. Experimental analysis of the proposed guidelines is also presented for the proof of concept.     

Enhanced electrical and thermal conductivity of modified poly(acrylonitrile-co-butadiene)-based nanofluid containing functional carbon black-graphene oxide

Solution refluxing and high-pressure homogenization technique were reported for synthesizing nanofluids based on modified poly(acrylonitrile-co-butadiene) (M-PANB) as base fluid and carbon black (CB)/carbon black-graphene oxide (CB-GO) as filler. The physiochemical properties were studied to analyze the structure, morphology, thermal and electrical conductivity. FTIR analysis corroborated the structure of CB-GO nanobifiller and nanocomposite. Microstructure analysis of M-PANB/CB-GO revealed good dispersion of CB-GO nanosheets, while CB series showed granular distribution. XRD studies confirmed amorphous structure of M-PANB/CB-GO nanocomposite. Thermal conductivity of nanofluid was found to increase upto 1.41 W/mK for 10 wt.% CB-GO loading and electrical conductivity was increased to 2.5 × 10^?3 Scm^?1.     

A Study on Poly(vinyl alcohol-co-ethylene)-graft-Polystyrene Reinforced with Two Functional Nanofillers

A facile route was adopted to graft polystyrene on poly(vinyl alcohol-co-ethylene) matrix. Poly(vinyl alcohol-co-ethylene)-graft-polystyrene (PVAE-g-PS) was then reinforced with two types of nanofillers, i.e., graphene oxide (GO) and nanodiamond functional graphene oxide (GO-ND). PVAE-g-PS/GO and PVAE-g-PS/GO-ND nanocomposite series reinforced with 0.1—5 wt.% nanofiller were fabricated by solution processing. Structure of nanofillers and composite was confirmed by FTIR. FESEM imaging revealed that nanodiamond functional GO platelets were fully incorporated into matrix. TGA demonstrated enhanced stability of PVAE-g-PS/GO-ND nanomposites containing GO-ND. Similarly, UL 94 and electrical conductivity measurement of GO-ND-based system were found to be superior compared to one of copolymer/GO.     

Photocatalytic degradation of diclofenac using hybrid MIL-53(Al)@TiO2 and MIL-53(Al)@ZnO catalysts

In this work, TiO₂ and ZnO were incorporated successfully into a MIL-53(Al) metal–organic framework (MOF) to form nanocomposites via a facile post-modification technique. The hybrid MIL-53(Al)@TiO₂ and MIL-53(Al)@ZnO were characterized by several characterization tests. The X-ray diffraction (XRD), Fourier-transform infrared (FTIR), and field-emission scanning electron microscopy (FE-SEM) analyses showed evidence of the successful incorporation of TiO₂ and ZnO within the MIL-53(Al) framework. The thermal gravimetric analysis (TGA) analysis demonstrated the excellent thermal stability of MIL-53(Al)@TiO₂ and MIL-53(Al)@ZnO, while diffuse reflectance spectroscopy (DRS) determined the direct optical band gaps of MIL-53(Al)@ZnO and MIL-53(Al)@TiO₂ to be 3.24 and 3.34 eV, respectively. The composites were also tested for the photocatalytic degradation of diclofenac (DCF) as a micropollutant. The DCF degradation efficiency of the photocatalysts was ranked in the following order: MIL-53(Al)@TiO₂ > MIL-53(Al) > TiO₂ > ZnO > MIL-53(Al)@ZnO. The incorporation of TiO₂ enhanced the optical properties of MIL-53 (Al), which was confirmed with the superior photodegradation efficiency of MIL-53(Al)@TiO₂ (>85% in 2 h) as compared to the pristine MIL-53(Al) (around 80% in 2 h). The improvement in the photodegradation of the hybrid-MOF is mostly associated with the possible dual function of the adsorption and photodegradation mechanisms. The reusability of MIL-53(Al) and its composites was inspected over 3 cycles of photodegradation experiments with DCF. The photocatalytic activity of MIL-53(Al)@TiO₂ remained unchanged (>90%), while for MIL-53(Al) and MIL-53(Al)@ZnO a slight drop was observed over three cyclic degradation experiments. Fluorescence measurements revealed that the hydroxyl radical is an important reactive oxygen species produced by all the photocatalysts that aid in the photodegradation of DCF. Furthermore, the kinetic modelling of the photoreaction identified a second-order kinetics for all catalysts. Experiments with scavengers showed that hydroxyl radicals played a major role in the photocatalytic process, and it was found that only 2 h of treatment was sufficient to obtain a considerable chemical oxygen demand (COD) reduction of 58%.     

Xylitol: A Review on Bioproduction,Application, Health Benefits,and Related Safety Issues

Xylitol is a pentahydroxy sugar-alcohol which exists in a very low quantity in fruits and vegetables (plums, strawberries, cauliflower, and pumpkin). On commercial scale, xylitol can be produced by chemical and biotechnological processes. Chemical production is costly and extensive in purification steps. However, biotechnological method utilizes agricultural and forestry wastes which offer the possibilities of economic production of xylitol by reducing required energy. The precursor xylose is produced from agricultural biomass by chemical and enzymatic hydrolysis and can be converted to xylitol primarily by yeast strain. Hydrolysis under acidic condition is the more commonly used practice influenced by various process parameters. Various fermentation process inhibitors are produced during chemical hydrolysis that reduce xylitol production, a detoxification step is, therefore, necessary. Biotechnological xylitol production is an integral process of microbial species belonging to Candida genus which is influenced by various process parameters such as pH, temperature, time, nitrogen source, and yeast extract level. Xylitol has application and potential for food and pharmaceutical industries. It is a functional sweetener as it has prebiotic effects which can reduce blood glucose, triglyceride, and cholesterol level. This review describes recent research developments related to bioproduction of xylitol from agricultural wastes, application, health, and safety issues.     

Taxonomic investigation of selected rust fungi using scanning electron microscopy from Khyber Pakhtunkhwa,Pakistan

Rusts comprises the largest natural group of plant pathogens including approximately 8% of all described Fungi. Rust fungi are extremely plant pathogens responsible for great losses to agriculture productivity. Rust species belong to several genera among which more than half are Puccinia species. In Pakistan, rust causes severe damage to agriculture crops. Current study was carried out to identify and characterize different rust species common in the research area through microscopy and Scanning electron microscopy (SEM) in Khyber Pakhtunkhwa, Pakistan. Morpho-anatomical investigation of each collected rust species was carried out using different standard protocols. The dimensions of spores were measured and snapped under a stereomicroscope. SEM was used to examine the shape, size, and ornamentation of the spores of each rust fungus. Results revealed documentation of seven rust fungi, that is, Melampsora euphorbiae, Phragmidium barclayi, Puccinia nepalensis, P. exhausta, P. menthae, Uromyces capitatus, and Uromyces decorates belong to four different genera, were recorded. SEM revealed that spermogonia and Aecia were missing in most of the rust fungus studied. Uredinia was found in a scattered, irregular, lengthy, and epidermis-enclosed form. Urediniospores were found to be ovulating, elongated, echinulate, globose to sub-globose, ellipsoid to ovoid, and globose to sub-globose. Telia was found as sub-epidermal, amphigenous, dispersed, minute, and spherical cells. Teliospores ranged in form from cylindrical to oblong. The germ pores were detected in both apical (top cell) and basal (bottom cell) idiosyncratic and pedicel-attached cells. The techniques used in the current investigation will aid mycologists in rust identification and microscopic characterization.     

Detection of microscopic glaucoma through fundus images using deep transfer learning approach

Glaucoma disease in humans can lead to blindness if it progresses to the point where it affects the oculus' optic nerve head. It is not easily detected since there are no symptoms, but it can be detected using tonometry, ophthalmoscopy, and perimeter. However, advances in artificial intelligence approaches have permitted machine learning techniques to diagnose at an early stage. Numerous methods have been proposed using Machine Learning to diagnose glaucoma with different data sets and techniques but these are complex methods. Although, medical imaging instruments are used as glaucoma screening methods, fundus imaging specifically is the most used screening technique for glaucoma detection. This study presents a novel DenseNet and DarkNet combination to classify normal and glaucoma affected fundus image. These frameworks have been trained and tested on three data sets of high-resolution fundus (HRF), RIM 1, and ACRIMA. A total of 658 images have been used for healthy eyes and 612 images for glaucoma-affected eyes classification. It has also been observed that the fusion of DenseNet and DarkNet outperforms the two CNN networks and achieved 99.7% accuracy, 98.9% sensitivity, 100% specificity for the HRF database. In contrast, for the RIM1 database, 89.3% accuracy, 93.3% sensitivity, 88.46% specificity has been attained. Moreover, for the ACRIMA database, 99% accuracy, 100% sensitivity, 99% specificity has been achieved. Therefore, the proposed method is robust and efficient with less computational time and complexity compared to the literature available.     

Structural,electronic, and optical properties of orthorhombic and triclinic BiNbO4 determined via DFT calculations

We performed ab initio calculations using the FPLAW method with the local density approximation (LDA) implemented in the WIEN2 k code for the orthorhombic (α) and triclinic (β) phases of BiNbO₄. The modified Becke–Johnson exchange potential (mBJ)-LDA approach was also used to improve the electronic properties. The lattice constants calculated for both structures using the LDA are in good agreement with the experimental values. For the band structure calculations, the mBJ-LDA approach provides reasonable agreement for the band gap value compared with the LDA. The estimated (mBJ)-LDA band gap values are 2.89 eV (3.73 eV) and 2.62 eV (3.15 eV) for the α and β phases of BiNbO₄, respectively. Significant optical anisotropy is clearly observed in the visible-light region. We also calculated and evaluated the electron energy loss spectrum for BiNbO₄. This work provides the first quantitative theoretical prediction of optical properties and electron energy loss spectra for both the orthorhombic and triclinic phases of BiNbO₄.