Photocatalytic paper using zinc oxide nanorods

Zinc oxide (ZnO) nanorods were grown on a paper support prepared from soft wood pulp. The photocatalytic activity of a sheet of paper with ZnO nanorods embedded in its porous matrix has been studied. ZnO nanorods were firmly attached to cellulose fibers and the photocatalytic paper samples were reused several times with nominal decrease in efficiency. Photodegradation of up to 93% was observed for methylene blue in the presence of paper filled with ZnO nanorods upon irradiation with visible light at 963 Wm^–2 for 120 min. Under similar conditions, photodegradation of approximately 35% was observed for methyl orange. Antibacterial tests revealed that the photocatalytic paper inhibits the growth of Escherichia coli under room lighting conditions.     

Morphology, structure and properties of conductive PS/CNT nanocomposite electrospun mat

The morphologies and properties of Polystyrene (PS)/Carbon Nanotube (CNT) conductive electrospun mat were studied in this paper. Nanocomposite fibers were obtained through electrospinning of PS/Di-Methyl Formamide (DMF) solution containing different concentrations and types of CNTs. The dispersion condition of CNTs was correlated to morphologies and properties of nanocomposite fibers. A copolymer as an interfacial agent (SBS, Styrene-butadiene-styrene type) was used to modify the dispersion of CNTs in PS solution before electrospinning. The results showed that the presence of the copolymer significantly enhances CNT dispersion. The fiber diameters varied between 200 nm and 800 nm depending on CNT type, polymer concentration and copolymer. The final morphological study of the fibers showed that CNT addition caused a decrease in beads formation along fiber axis before percolation threshold. However, addition of CNTs above percolation increased the beads formation, depending on the dispersion condition. The presence of SBS modified the dispersion, reduced the fiber diameter and the number of bead structures. Electrical conductivity measurements on nanocomposite mats of 15-300 μm in thickness showed an electrical percolation threshold around 4 wt% MWCNT; while the samples containing SBS showed higher values of conductivities below percolation compared to the samples with no compatibilizer. Enhancement in mechanical properties was observed by the addition of CNTs at concentrations below percolation.     

Transplantation of nano-bioglass/gelatin scaffold in a non-autogenous setting for bone regeneration in a rabbit ulna

Bioactive glass has been investigated for variety of tissue engineering applications. In this study, fabrication, in vitro and in vivo evaluation of bioactive glass nanocomposite scaffold were investigated. The nanocomposite scaffolds with compositions based on gelatin and bioactive glass nanoparticles were prepared. The apatite formation at the surface of the nanocomposite samples confirmed by Fourier transform infrared spectroscopy, scanning electron microscopy and X-ray powder diffraction analyses. The in vitro characteristics of bioactive glass scaffold as well as the in vivo bone formation capacity of the bioactive glass scaffold in rabbit ulnar model were investigated. The bioactive glass scaffold showed no cytotoxicity effects in vitro. The nanocomposite scaffold made from gelatin and bioactive glass nanoparticles could be deliberated as an extremely bioactive and prospective bone tissue engineering implant. Bioactive glass scaffolds were capable of guiding bone formation in a rabbit ulnar critical-sized-defect model. Radiographic evaluation indicated that successful bridging of the critical-sized defect on the sides both next to and away from the radius took place using bioactive glass scaffolds. X-ray analysis also proposed that bioactive glass scaffolds supported normal bone formation via intramembranous formation     

The facility location problem from the perspective of triple bottom line accounting of sustainability

Design of facilities network, allocation of customers to be served from the facilities and their operations have strong economic, environmental and social impacts. Although the decisions in the facility location problem may have varying effects on these impacts, simultaneous consideration of these effects in the early stages of decision-making for facility location selection and network plan has attracted limited attention in the facility location decision literature. Specifically, the social dimension and mathematical modelling are rarely used. In this paper, we present a decision support framework for the facility location problem that incorporates the triple bottom line accounting of sustainability. The framework is a valuable integration of mathematical modelling embedding the criteria with proper measurement indicators in a multi-objective model, perspectives of the related stakeholders, any thresholds and assumption, model analysis, and the decision-maker strategy to find the best-fit alternative. We demonstrate our methodological approach to establish a supply network for digital products in Turkey using real data. The results indicate that the method can balance the economic, environmental and social pillars, based on limitations of the three pillars and strategic perspective of the decision-maker. The decision-maker can interpret the interactions among the three pillars of sustainability and can make his decision by analysing the balance between them.     

Chondrogenic stimulation in mesenchymal stem cells using scaffold-based sustained release of platelet-rich plasma

Developing minimal invasive strategies via injectable hydrogels for effective repairing of cartilage defects is highly desired. Injectable hydrogels, which can simultaneously embed cell and growth factors (GFs), serve as in situ formed scaffolds and could support an accelerated tissue regeneration process. The purpose of this study is to fabricate a composite injectable hydrogel, based on alginate (Alg)/polyvinyl alcohol (PVA) incorporating platelet rich plasma (PRP)-encapsulated Alg sulfate (AlgS) microbeads, as a localized sustained release system of GFs, for the articular cartilage regeneration. The results show that synthesized AlgS microbeads support the sustained release of PRP GFs during 14 days, where preserve the bioactivity of them more than the free PRP. Rabbit adipose-derived mesenchymal stem cells in contact with PRP-loaded AlgS beads show more proliferation (2.7 folds) and have obviously higher deposition of collagen type ΙΙ and GAGs than free PRP treated ones. In addition, cells encapsulated into the hydrogel including PRP sustained release system show upregulated expression of collagen type ΙΙ (61 folds), Aggrecan (294 folds) and SOX9 (71.5 folds), as cartilage-critical genes, compared to the direct treatment by PRP. To summarize, the developed hybrid Alg/PVA hydrogel embedding with PRP-encapsulated AlgS microbeads is suggested as a potential in situ formed scaffold for cartilage regeneration.     

Rheokinetics in curing process of polyfurfuryl alcohol: effect of homologous acid catalysts

Curing reaction of polyfurfuryl alcohol (PFA) resin was investigated using rheological measurements in the presence of different acid catalysts. A homologous series of dicarboxylic acid catalysts with even number of carbons of 2, 4 and 6 were chosen, i.e., oxalic acid (OX, 2 carbon), succinic acid (SU, 4 carbon) and adipic acid (AD, 6 carbon). Acidity of these catalysts in terms of pK _a was in the range of 1.25–4.43. Firstly, non-isothermal curing kinetics were investigated, and then, isothermal studies were performed at three different temperatures using 3 and 5 wt% of each acid catalyst. Isothermal cure behavior was best described by an empirical Arrhenius model of viscosity. An isoconversional method was applied to compute the changes in the effective activation energy as a function of degree of conversion. The change in activation energy at 50–10 kJ mol^?1 was observed for PFA/3 wt% OX system due to the vitrification and diffusion-controlled processes. Gel time, t _gel, was determined as a function of curing temperature, acid catalyst type and its concentration. The gelation time was consistent for all the formulations with an extent of conversion of about 0.7. Significant differences were observed in the curing behavior of resins in the presence of different acid catalysts. Increasing of the curing temperature significantly accelerated the curing process and increased curing rate constant of the PFA resin.     

Ridge regression-based feature extraction for hyperspectral data

Feature extraction based on ridge regression (FERR) is proposed in this article. In FERR, a feature vector is defined in each spectral band using the mean of all classes in that dimension. Then, it is modelled using a linear combination of its farthest neighbours from among other defined feature vectors. The representation coefficients obtained by solving the ridge regression model compose the projection matrix for feature extraction. FERR can extract each desired number of features while the other methods such as linear discriminant analysis (LDA) and generalized discriminant analysis (GDA) have limitations in the number of extracted features. Experimental results on four popular real hyperspectral images show that the efficiency of FERR is superior to those of other supervised feature extraction methods in small sample-size situations. For example, for the Indian Pines dataset, the comparison between the highest average classification accuracies achieved by different feature extraction methods using a support vector machine (SVM) classifier and 16 training samples per class shows that FERR is 7% more accurate than nonparametric weighted feature extraction and is also 9% better than GDA. LDA, having the singularity problem in the small sample-size situations, has 40% less accuracy than FERR. The experiments show that generally the performance of FERR using the SVM classifier is better than when using the maximum likelihood classifier.     

A NOVEL EMBEDDED FEATURE SELECTION METHOD: A COMPARATIVE STUDY IN THE APPLICATION OF TEXT CATEGORIZATION

In text classification based on a vector space model, the high dimension of the feature may pose some problems. These problems occur not only for computational reasons, but also because of overfitting. Feature selection is an important preprocessing step used for text classification applications to reduce the vector space size, control the computational time, and maintain or improve performance. In this study, we used an embedded approach in feature selection in which the Chi-square (CHI) feature selector is a filter step. In this step, the less discriminative features are discarded. In the wrapper step, a novel algorithm is proposed based on the combination of the fast global search ability of the genetic algorithm (GA) and the positive feedback mechanism of ant colony optimization (ACO). In order to validate our approach, we carried out a series of experiments on Reuters-21578 corpus, and we compare the achieved results with some other well-known techniques. The evaluation results are such that our method obtained a better performance compared with the other methods in the majority of cases.     

High-dimensional image data feature extraction by double discriminant embedding

We propose a supervised feature extraction method in this paper that uses two successive transformations to produce the extracted features. The first projection maximizes the difference between spectral features. Thus, produced features have minimum overlap in the new feature space. The second projection maximizes the discrimination between classes. The proposed method, which is called double discriminant embedding (DDE), uses just the first statistics of data. Thus, DDE has good efficiency using limited training samples. The experimental results on four popular hyperspectral images show the better efficiency of DDE in comparison with LDA, GDA, NWFE, and supervised LPP methods in small sample size situation.