Application of response surface methodology for optimization of lead biosorption in an aqueous solution by Aspergillus niger

Response surface methodology was applied to optimize the removal of lead ion by Aspergillus niger in an aqueous solution. Experiments were conducted based on a rotatable central composite design (CCD) and analyzed using response surface methodology (RSM). The biosorption process was investigated as a function of three independent factors viz. initial solution pH (2.8-7.2), initial lead concentration (8-30 mg/l) and biomass dosage (1.6-6 g/l). The optimum conditions for the lead biosorption were found to be 3.44, 19.28 mg/l and 3.74 g/l, respectively, for initial solution pH, initial lead ion concentration and biomass dosage. Lead biosorption capacity on dead A. niger fungal biomass was enhanced by pretreatment using NaOH. Under these conditions, maximum biosorption capacity of the biomass for removal of lead ions was obtained to 96.21%. The desirability function was used to evaluate all the factors and response in the biosorption experiments in order to find an optimum point where the desired conditions could be obtained. The A. niger particles with clean surface and high porosity may have application as biosorbent for heavy metal removal from wastewater effluents.     

Optimizations of wear resistance and toughness of hydroxyapatite nickel free stainless steel new bio-composites for using in total joint replacement

The aim of this work was to produce novel bio-composites made of hydroxyapatite and nickel free stainless steel (prepared by heat treating bone ash) and studying their mechanical properties including their tribology under various loads, toughness, and compressive and bending strengths. Different amounts of nickel free stainless steel powder (30, 40, 50 and 60 wt.%) was added to this hydroxyapatite powder to get bio-composites. Their hardness, wear resistance and friction coefficient, as a function of the metal (nickel free stainless steel) content were investigated. Hardness and wear resistance were decreased by increasing of the weight percentage of stainless steel, while friction coefficient was increased. Strength and toughness of composites increases considerably by increasing of NFSS content. The toughness enhancement is contributed mainly by crack bridging and plastic deformation of the nickel free stainless steel. The strengthening effect is contributed by both the matrix grain refinement and the toughness enhancement. According to results of all mechanical tests done on composites, composite with 50 wt.% nickel free stainless steel has the most appropriate mechanical properties among other composites for using in orthopaedic applications.     

Effect of sea water on water absorption and flexural properties of?wood-polypropylene composites

The effects of Caspian Sea and Persian Gulf waters on the physical and mechanical properties of wood- polypropylene composites were studied. For physical tests, the composites were immersed in Caspian Sea, Persian Gulf and distilled water and long term water absorption was determined. For mechanical tests, the prepared composites were immersed in Caspian Sea, Persian Gulf and distilled water for 7 or 30 days, removed from water and their flexural properties were measured. The composites immersed in Persian Gulf water exhibited higher water absorption and lower flexural properties than those immersed in Caspian Sea and distilled water, respectively. At higher sawdust content, the type of water is more effective on increasing water absorption and decreasing flexural properties.     

Multi-atlas based neonatal brain extraction using atlas library clustering and local label fusion

Multimedia Tools and Applications - Brain extraction is one of the most important preprocessing steps in cerebral magnetic resonance (MR) image analysis. Brain extraction from neonatal MR images is...     

Region-based scalable self-recovery for salient-object images

Self-recovery is a tamper-detection and image recovery methods based on data hiding. It generates two types of data and embeds them into the original image: authentication data for tamper detection and reference data for image recovery. In this paper, a region-based scalable self-recovery (RSS) method is proposed for salient-object images. As the images consist of two main regions, the region of interest (ROI) and the region of non-interest (RONI), the proposed method is aimed at achieving higher reconstruction quality for the ROI. Moreover, tamper tolerability is improved by using scalable recovery. In the RSS method, separate reference data are generated for the ROI and RONI. Initially, two compressed bitstreams at different rates are generated using the embedded zero-block coding source encoder. Subsequently, each bitstream is divided into several parts, which are protected through various redundancy rates, using the Reed-Solomon channel encoder. The proposed method is tested on 10 000 salient-object images from the MSRA database. The results show that the RSS method, compared to related methods, improves reconstruction quality and tamper tolerability by approximately 30% and 15%, respectively.     

A wavelet-based classification of hyperspectral images using Schroedinger eigenmaps

This article proposes a new algorithm for hyperspectral image classification. The proposed method is a spectral–spatial method based on wavelet transforms, kernel minimum noise fraction (KMNF) and spatial–spectral Schroedinger eigenmaps (SSSE). To overcome the computation complexity, one-dimensional discrete wavelet transform (1D-DWT) is applied in spectral domain. To reduce noise, KMNF coefficients are extracted in wavelet space. To solve time-consuming problem, 2D-DWT coefficients are employed in spatial space. Hence, the combination of 1D-DWT, KMNF, and 2D-DWT is suggested to create SSSE features. The classification is carried out by a Support Vector Machine (SVM) classifier. Experimental results show that classification accuracy and time consumption are effectively improved compared to the state-of-the art reported spectral–spatial SVM-based methods.     

Tenogenic Induction of Human MSCs by Anisotropically Aligned Collagen Biotextiles

A novel biofabrication modality, electrophoretic compaction with macromolecular alignment, is utilized to make collagen threads that mimic the native tendon's structure and mechanical properties. A device with kinematic electrodes is designed to fabricate collagen threads in continuous length. For the first time, a 3D‐biotextile is woven purely from collagen. Mechanical properties and load‐displacement behavior of the biotextile mimic those of the native tendon while presenting a porosity of 80%. The open pore network facilitates cell seeding across the continuum of the bioscaffold. Mesenchymal stem cells (MSCs) seeded in the woven scaffold undergo tenogenic differentiation in the absence of growth factors and synthesize a matrix that is positive for tenomodulin, COMP and type I collagen. Up‐regulation of tenomodulin, a tendon specific marker, is 11.6 ± 3.5 fold, COMP is up‐regulated 16.7 ± 5.5 fold, and Col I is up‐regulated 6.9 ± 2.7 fold greater on ELAC threads when compared to randomly oriented collagen gels. These results demonstrate that a bioscaffold woven using collagen threads with densely compacted and anisotropically aligned substrate texture stimulates tenogenesis topographically, rendering the electrochemically aligned collagen as a promising candidate for functional repair of tendons and ligaments.