Facile fabrication of polyethylene/silver nanoparticle nanocomposites with silver nanoparticles traps and holds early antibacterial effect

Antibacterial polyethylene (PE)/silver nanoparticle (AgNP) nanocomposites containing AgNPs at concentrations of 5 × 10^?5, 5 × 10^?4, and 5 × 10^?3 wt % were fabricated and tested. Transmission electron microscopy revealed an even dispersion of surface AgNPs in the PE/AgNP nanocomposites. No AgNP agglomeration was observed. The tensile strength, elongation at break, and Young's modulus of these PE/AgNP nanocomposites were similar to those of neat PE. Differential scanning calorimetry demonstrated that the PE/AgNP nanocomposites and neat PE had similar melting and crystallization temperatures of 126 ± 0.5 and 109 ± 0.6°C, respectively. The heats of fusion of the PE/AgNP nanocomposites containing AgNPs at concentrations of 5 × 10^?5 and 5 × 10^?4 and of 5 × 10^?3 wt % were lower than those of neat PE by 5 and 7%, respectively. These PE/AgNP nanocomposites were immersed in shaking liquid cultures of the potential pathogenic bacteria Escherichia coli, Bacillus subtilis, and Salmonella typhimurium in the lag phase. The results show that the growth rates of all of the tested bacteria were restricted effectively after 1.5, 3, and 6 h of cultivation, respectively. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43331.     

Puff pastry and trends in fat reduction: an update

Puff pastry is a popular nonleavened pastry product with unique textural properties. Puff pastry is processed from laminated dough, comprising alternating and discrete layers of dough and fat. Puff pastry quality can vary substantially depending on the raw material quality and production processes. The high fat content of commercial puff pastry usually containing significant amounts of saturated and trans fats, which are known to be associated with potential health risks, has led to increased demand for lower fat baked products. This review discusses the puff pastry production process and factors affecting puff pastry quality together with strategies to reduce total fat content and improving the fat composition in puff pastries.     

Determining Significant Classification Factors for Senior Learning: A Case Study of Thai Seniors and Social Media Skill Learning

The senior learns in order to have a better quality of life. The challenge of seniors in learning is their learning ability that deteriorates because of age. Suitable management for different types of seniors, so called personalized learning is required. Therefore, this study focuses on determining significant classification factors for classification of seniors which is an important component of personalized learning. In this study, the assumption of personal background and health issue can be used for classifying types of seniors. The decision tree is used for determining significant classification factors and constructing the model. The study is conducted with 75 seniors for social network skill learning. The classification results show that the significant classification factors affecting the classification model of senior learning are age, daily internet time spending, number of applications, memory problem, and education background. The model constructed by decision tree provides 93.33% classification accuracy. Also, the obtained factors are verified by testing with two machine learning methods including artificial neural network (ANN) and K-nearest neighbors (K-NN). The comparison results show that 5 factors provide high classification accuracy for both classifiers, which are 93.33% and 92.00% for ANN, and K-NN, respectively.

     

A novel approach for characterisation of ischaemic stroke lesion using histogram bin-based segmentation and gray level co-occurrence matrix features

Among the various brain diseases, stroke is the major cause of death worldwide, next to heart attack. This paper proposes an algorithm in predicting the ischaemic stroke lesion using midline sketching and histogram bin-based technique. The visible ischaemic stroke lesion region and the normal region of the same computed tomography image are segmented with the help of histogram bins and the features are extracted. The first- and second-order statistical features for both regions are analysed. The differences in the features are utilised to categorise the lesion and non-lesion region. The statistical t-test analysis-based observations with a confidence interval of 95% for each feature are tabulated. These observations indicate that among the nine features, as per the statistical analysis, six features provide the clear differentiation between normal and abnormal regions.     

Modified differential evolution algorithm for simple assembly line balancing with a limit on the number of machine types

This article proposes the differential evolution algorithm (DE) and the modified differential evolution algorithm (DE-C) to solve a simple assembly line balancing problem type 1 (SALBP-1) and SALBP-1 when the maximum number of machine types in a workstation is considered (SALBP-1M). The proposed algorithms are tested and compared with existing effective heuristics using various sets of test instances found in the literature. The computational results show that the proposed heuristics is one of the best methods, compared with the other approaches.     

Structural aspects of mesoporous AlPO4-5 (AFI) zeotype using microwave radiation and alumatrane precursor

A new route for preparation of mesoporous AlPO₄-5 (AFI) zeotype has been synthesized using alumatrane precursor, prepared from aluminum hydroxide and triisopropanolamine (TIS) by the oxide one pot synthesis (OOPS), via microwave technique using triethylamine (TEA) as a structure-directing agent. The influences of the reaction mixture composition, HF acid, water content and the crystallization temperature and time were investigated. The prepared materials were characterized using X-ray diffraction, SEM and BET. The results showed a mesoporous AlPO₄-5 zeotype having a uniform rod-like structure with surface area around 120–180 m²/g. The high crystallinity with narrow size distribution of crystals was obtained at a high amount of structure-directing agent (the mole ratio of TEA/Al₂O₃ = 3.5). The presence of fluorine ion retarded the nucleation and growth rate, leading to a bigger crystal size. The crystal of the AFI grew preferentially in the c-direction with the reaction time and the water content. The use of lower reaction temperature to obtain good crystalline material can be compensated by a longer reaction time.     

Study on mechanical behaviors of pneumatic artificial muscle

Nowadays, Pneumatic Artificial Muscle (PAM) has become one of the most widely-used fluid-power actuators which yields remarkable muscle-like properties such as high force to weight ratio, soft and flexible structure, minimal compressed-air consumption and low cost. To obtain optimum design and usage, it is necessary to understand mechanical behaviors of the PAM. In this study, the proposed models are experimentally derived to describe mechanical behaviors of the PAMs. The experimental results show a non-linear relationship between contraction as well as air pressure within the PAMs and a pulling force of the PAMs. Three different sizes of PAMs available in industry are studied for empirical modeling and simulation. The case studies are presented to verify close agreement on the simulated results to the experimental results when the PAMs perform under various loads.     

Multiline two-dimensional guided-mode resonant filters

A novel multiline filter using a two-dimensional guided-mode resonant (GMR) filter is proposed. The filter concept utilizes the multiple planes of diffraction produced by the two-dimensional grating. Multiple resonances are obtained by matching the guided modes in the different planes of diffraction to different wavelengths. It is shown that the location and the separation between resonances can be specifically controlled by modifying the periodicity of the grating and the other physical dimensions of the structure. This is in contrast to the one-dimensional GMR filters where the location of the resonances is material dependent. Two-line reflection filter designs with spectral linewidths less than 1 nm and a controllable spectral separation of up to 23% of the short resonance wavelength are presented using rectangular-grid grating GMR structures. Three-line filters are designed in hexagonal-grid grating GMR structures with two independently controllable resonance locations.     

Directed information dissemination in vehicular ad-hoc networks

In this article, we utilize the idea of multipoint relays (MPRs) found in literature (Jacquet et al. in Proceedings of IEEE INMIC, 2001), to propagate accident information in a restricted way (e.g., only backwards). We devise an algorithm to identify MPRs that are geographically situated behind a particular node using only its neighbor table, and speed information of the neighboring vehicles. With the identification of the backward MPRs, it is possible to restrict the information dissemination to vehicles behind a particular vehicular ad-hoc network (VANET) node only. This might benefit the approaching vehicles so that the driver could take preventive measures in real-time since he/she will have an indication of the severity of road conditions ahead. We assume that there exists an inter vehicular network using optimized link state routing (OLSR) where accident information can be propagated to all nodes using on-going OLSR control packets. We envision our application will run on top of existing routing protocols (e.g., OLSR), thereby resulting in very little integration effort, and retaining OLSR’s reduced network traffic advantage through the use of MPRs. We analyze our back MPR identification algorithm in a detailed manner. We also show that by using our approach the location of the accident alert instigator node could be pinpointed if a subset of the nodes in the same VANET know their geographical positions. We use VANET mobility models generated by SUMO into NS-3 for our simulations, and also perform preliminary experiments to verify the algorithm’s effectiveness. Our analysis and experiments show favorable results.     

Scanning electron microscopy and energy-dispersive X-ray analysis of self-etching adhesive systems to ground and unground enamel

The morphological analysis of the ground and unground enamel was treated with three different self-etching adhesive systems. Ultrastructural features were observed by using the field emission scanning electron microscope (FESEM) in combination with Energy Dispersive X-Ray Spectroscopy (EDS) analysis. Thirty extracted human molars were used for this study. Teeth were divided into two groups. In the first group unground enamel was etched with either Clearfil SE Bond (Kuraray-Japan), G Bond (GC-Japan) or Tri S Bond (Kuraray-Japan) according to the manufactures instructions. In the second group ground enamel was treated as above. In addition 24 ungrounded and grounded enamel specimens were etched and bonded with the three self-etching adhesives and restored with composite resin (Clearfil ST-Kuraray). Then they were cross-sectioned and interfacial analysis was done with the combination of EDS analysis. Etching patterns of the enamel varied according to the self-etching adhesive. Clearfil SE Bond produced micro-irregular etching pattern creating crater like area in ground enamel while other two produced mild etching pattern. All three adhesives produced incomplete etching on unground enamel. Interfacial studies showed demineralization for the bonding agent penetration and the formation of hybrid layer. The self-etching adhesives produced different specific SEM morphologies on unground and ground enamel.