Plasma Spray Deposition Enhancement of Titanium Nitride Layer Using Nitrogen-Contained Plasma Irradiation of Titanium Substrate as a Pre-spraying Method

Reactive plasma spray of TiN ceramic coating attracts much attention over the years because of its ability to deposit thick layers on various metal surfaces. However, some mechanical properties of the coating such as its hardness should be improved. In this study, initially a thin layer of titanium nitride was prepared on a titanium substrate during irradiation of titanium substrate by a thermal DC nitrogen-contained plasma jet. Then, during reactive plasma spraying, Ti particles were injected into plasma jet, converted to titanium nitride and huddled on to the substrate. This new hybrid method (primary plasma irradiation and post-reactive plasma spraying) for deposition of TiN coatings would combine the advantages of both plasma-enhanced chemical vapor deposition and reactive plasma spraying methods in part. It resulted in a thick and hard layer of titanium nitride film. Sample produced by this method was analyzed with x-ray diffraction confirming titanium nitride production. Vickers hardness was measured using optical microscopy which was around 1319 H_v300g. To study the cross section of the layer, optical microscopy and scanning electron microscopy (SEM) were used.     

Synthesis,Characterization, and Bioactivity Evaluation of Amorphous and Crystallized 58S Bioglass Nanopowders

The aim of this work was synthesis and characterization of amorphous and crystallized 58S nanopowders produced via sol‐gel method. According to the thermal analysis, the nanopowders were heat‐treated at 600°C and 1100°C. X‐ray diffraction results revealed that the phases of Wollastonite and tricalcium phosphate were formed at 1100°C. The in vitro tests showed that hydroxyl carbonate apatite was precipitated on both crystallized and amorphous nanopowders, while amorphous nanopowder showed a higher bioactivity than that of crystallized nanopowder. In contrast, mechanical properties of crystallized specimen were higher than those of amorphous specimen.     

Concentration and distribution of heavy metals in urban airborne particulate matter in Frankfurt am Main, Germany

Heavy metal concentrations were measured in airborne dust collected at three sites with different traffic densities from August 2001 to July 2002 in the Frankfurt am Main area. Bulk samples of particulate matter (PM) with an aerodynamic equivalent diameter of <22 microm were collected on cellulose nitrate filters using air filtration devices. Fractionated samples of PM with an aerodynamic equivalent diameter of <10 microm were collected using an eight-stage Andersen impactor. Pb, Cd, Mn, Ni, Zn, V, As, Sb, Cu, Cr, Co, and Ce were determined by inductively coupled plasma sector field mass spectrometry, Pt and Rh were determined by adsorptive voltammetry, and Pd was determined by total reflection X-ray fluorescence analysis. The results show that the highest airborne heavy metal concentrations occurred at the main street with a large volume of traffic. With the exception of Co, V, Ce, and Mn, the heavy metals had an elevated enrichment factor compared to their concentrations in the continental crust. The main street site was especially contaminated with Sb, Zn, Cu, V, and Ni. Motor vehicles are the likely source of emissions. With the exception of Cr, Cu, and Zn, most of the airborne heavy metal concentrations determined for impactor samples deviate slightly from the results for total airborne dust. Heavy metal particle size distributions can be divided into three groups. For metals such as As, Cd, Pb, and V, the main fraction can be found in fine particles with a diameter of <2.1 microm, whereas Ce, Cr, Co, and Ni occur mainly in coarse particles with a diameter of >2.1 microm. Cu, Mn, Sb, Zn, Pt, Pd, and Rh occur in high concentrations in the medium range of the impactor stages (particle diameters of 1.1-4.7 microm). Metal concentrations in fine dust particles are needed to assess the human health risks of their inhalation.     

Fabrication,characterization and evaluation of the effect of PLGA and PLGA–PEG biomaterials on the proliferation and neurogenesis potential of human neural SH-SY5Y cells

In recent years with regard to the development of nanotechnology and neural stem cell discovery, the combinatorial therapeutic strategies of neural progenitor cells and appropriate biomaterials have raised the hope for brain regeneration following neurological disorders. This study aimed to explore the proliferation and neurogenic effect of PLGA and PLGA–PEG nanofibers on human SH-SY5Y cells in in vitro condition. Nanofibers of PLGA and PLGA–PEG biomaterials were synthesized and fabricated using electrospinning method. Physicochemical features were examined using HNMR, FT-IR, and water contact angle assays. Ultrastructural morphology, the orientation of nanofibers, cell distribution and attachment were visualized by SEM imaging. Cell survival and proliferation rate were measured. Differentiation capacity was monitored by immunofluorescence staining of Map-2. HNMR, FT-IR assays confirmed the integration of PEG to PLGA backbone. Water contact angel assay showed increasing surface hydrophilicity in PLGA–PEG biomaterial compared to the PLGA substrate. SEM analysis revealed the reduction of PLGA–PEG nanofibers' diameter compared to the PLGA group. Cell attachment was observed in both groups while PLGA–PEG had a superior effect in the promotion of survival rate compared to other groups (p < .05). Compared to the PLGA group, PLGA–PEG increased the number of Ki67⁺ cells (p < .01). PLGA–PEG biomaterial induced neural maturation by increasing protein Map-2 compared to the PLGA scaffold in a three-dimensional culture system. According to our data, structural modification of PLGA with PEG could enhance orientated differentiation and the dynamic growth of neural cells.     

Do wood fibers from a pulp mill affect the distribution of total and methyl mercury in river sediments?

The St. Lawrence River near Cornwall Ontario is affected by industrial mercury contamination of sediments and biota. It has been suggested that pulp and paper mill effluents may stimulate bacterial mercury methylation in these sediments, leading to contamination of aquatic biota. To test this hypothesis, we examined sediment–porewater dynamics of total mercury (THg) and methyl mercury (MeHg) at a site with high concentrations of wood fibers from a pulp and paper mill effluent and a nearby reference site with low wood fiber content. Dissolved phase THg (THg_diss) and MeHg (MeHg_diss) in porewater profiles showed that 38 ± 30.9% (SD) of THg in porewaters was in the methylated form regardless of wood fiber content. MeHg_diss and THg_diss concentrations were homogeneous between porewater and overlying water, indicating (a) that there is minimal net diffusion of MeHg_diss and THg_diss and (b) that redox-dependent processes such as sulfate reduction and Fe reduction were not associated with MeHg_diss distribution in these sediment profiles. MeHg and THg in solid phase showed coincident subsurface peaks at depths > 40 cm suggesting either that historical deposits of MeHg on particles (MeHg_(p)) are preserved in deep sediments, or that Hg methylation is active in deep sediments.     

Fuzzy logic based static VAR compensators for enhancing the performance of synchronous and asynchronous motor loads

The paper presents a simple yet powerful fuzzy logic based static VAR compensator (FLSVC) applied to an industrial power network consisting of three phase synchronous and asynchronous motor loads. In the proposed fuzzy logic controller (FLC), the speed and acceleration variations of a specific machine are taken as the inputs. To demonstrate the effectiveness and capabilities of the employed FLSVC, several non-linear time-domain digital simulation tests are performed. The results show that over a wide range of operating conditions and disturbances, the FLSVC improves remarkably the voltage profile and the overall dynamic performance.     

Optimal design of laser solid freeform fabrication system and real-time prediction of melt pool geometry using intelligent evolutionary algorithms

With the rapid growth of laser applications and the introduction of high efficiency lasers (e.g. fiber lasers), laser material processing has gained increasing importance in a variety of industries. Among the applications of laser technology, laser cladding has received significant attention due to its high potential for material processing such as metallic coating, high value component repair, prototyping, and even low-volume manufacturing. In this paper, two optimization methods have been applied to obtain optimal operating parameters of Laser Solid Freeform Fabrication Process (LSFF) as a real world engineering problem. First, Particle Swarm Optimization (PSO) algorithm was implemented for real-time prediction of melt pool geometry. Then, a hybrid evolutionary algorithm called Self-organizing Pareto based Evolutionary Algorithm (SOPEA) was proposed to find the optimal process parameters. For further assurance on the performance of the proposed optimization technique, it was compared to some well-known vector optimization algorithms such as Non-dominated Sorting Genetic Algorithm (NSGA-II) and Strength Pareto Evolutionary Algorithm (SPEA 2). Thereafter, it was applied for simultaneous optimization of clad height and melt pool depth in LSFF process. Since there is no exact mathematical model for the clad height (deposited layer thickness) and the melt pool depth, the authors developed two Adaptive Neuro-Fuzzy Inference Systems (ANFIS) to estimate these two process parameters. Optimization procedure being done, the archived non-dominated solutions were surveyed to find the appropriate ranges of process parameters with acceptable dilutions. Finally, the selected optimal ranges were used to find a case with the minimum rapid prototyping time. The results indicate the acceptable potential of evolutionary strategies for controlling and optimization of LSFF process as a complicated engineering problem.     

Purpose-restricted Anonymous Mobile Communications Using Anonymous Signatures in Online Credential Systems

To avoid the risk of long-term storage of secrets on a portable device, an online credential system supports the roaming user in retrieving securely at various locations his private key and other material to generate anonymous signatures. The protocol proposed here allows a roaming mobile user to access anonymously services such as whistle blowing and net-counselling. Our approach: (1) allows a mobile user, remembering a short password, to anonymously and securely retrieve the credentials necessary for his anonymous communication without assuming a pre-established anonymous channel to the credential server or establishing an anonymous channel using the time-consuming existing rerouting techniques; (2) provides authenticated anonymous access to privacy-related services without rerouting the packets; (3) helps combatting the abuse of anonymity for performing illegal activities (e.g. redistribution of copy-righted contents, illegal drug trading and so on).     

MATRIX AND CEMENT EFFECTS ON RESIDUAL OIL SATURATION IN SANDSTONE FORMATIONS: A NEURAL NETWORK APPROACH

Residual oil in sandstone is affected by mineral composition, clay matrix and cementing material. Matrix minerals affect the affinity of a fluid to spread on a rock surface significantly and in turn controls the fluid distribution within the pore spaces. At the interface between the rock surface and the contacting fluid, electrical charges are in the origin of the extent of phase wetness. Available framework grains, a dominant component of rock matrix, affect porosity and, hence, amounts of rock preferential wetness. Cement, clay matrix and quartz overgrowth, which make up for the rest of the grain population in a rock, influence wetness and, therefore, amounts of residual oil. In this paper, spectro-electromicroscopy (SEM) point-count technique in conjunction with neural network analysis were used to determine the effect of certains rock parameters on the amounts of residual oil following waterflooding operations. Using artifcial neural network, the intent was then to predict the extent of residual oil in sandstone rocks given limited information about rock matrix, cementing material and primary porosity.     

On the Performance of FFT/DWT/DCT-based OFDM Systems with Chaotic Interleaving and Channel Estimation Algorithms

The efficiency of data transmission over fading channels in orthogonal frequency division multiplexing (OFDM) systems depends on the employed interleaving method. In this study, we propose an improved chaotic interleaving scheme which aims to improve the performance of OFDM system under fading channel. In the proposed scheme, the binary data is interleaved with chaotic Baker map prior to the modulation process. In the sequel, significant degree of encryption is being added during data transmission. The performance of the proposed approach is tested on the conventional fast Fourier transform OFDM, discrete wavelet transform OFDM, and discrete cosine transform OFDM with and without chaotic interleaving. Furthermore, an expectation–maximization (EM) algorithm is proposed for improving channel impulse response (CIR) estimation based on a maximum likelihood principle. The proposed scheme makes use of EM algorithm to update the channel estimates until convergence is reached. The simulation results show the efficiency of the proposed algorithms under Rayleigh fading environments where the symbol error rate essentially coincides with that of the perfect channel case after the fifth EM iteration.