Axially aligned electrically conducting biodegradable nanofibers for neural regeneration

In this study, electrically conducting axially aligned nanofibers have developed to provide both electrical and structural cues. Poly(lactide-co-glycolide) (PLGA) with poly(3-hexylthiophene) (PHT) was electrospun into 2D random (196 ± 98 nm) and 3D axially aligned nanofibers (200 ± 80 nm). Electrospun random and aligned PLGA–PHT fibers were characterized for surface morphology, mechanical property, porosity, degradability, and electrical conductivity. The pore size of random PLGA–PHT nanofibers (6.0 ± 3.3 μm) were significantly higher than the aligned (1.9 ± 0.4 μm) (P < 0.05) and the Young’s modulus of aligned scaffold was significantly lower than the random. Aligned nanofibers showed significantly lesser degradation rate and higher electrical conductivity (0.1 × 10^?5 S/cm) than random nanofibers (P < 0.05). Results of in vitro cell studies indicate that aligned PLGA–PHT nanofibers have a significant influence on the adhesion and proliferation of Schwann cells and could be potentially used as scaffold for neural regeneration.     

Preparation and Characterisation of Pelletised Glass Electrolytes for Fuel Cells

This paper reports on the preparation and characterisation of pelletised glass electrolytes that were fabricated with a proton conducting glass derived from a sol–gel technique, and several kinds of binders. The electrolytes, consisting of a glass powder that had been pulverised by planetary ball milling and mixed with an orthophosphoric acid binder, gave rise to a maximum proton conductivity of 1.3 × 10^–2 S cm^–1 measured at 80 °C and 80% relative humidity. The pore diameter of the PGE was in this case ∼2 nm. The hydrogen gas permeability was analysed as a function of the temperature and was found to be on the order of 10^–10 mol cm^–1 s^–1 Pa^–1 at 100 °C. Current–voltage measurements were carried out at room temperature using the PGE under H₂ and O₂ flow. Power densities were obtained from the I–V curves during fuel cell operation at 80 °C and 100% R.H.     

Dynamic mechanical analysis of pineapple leaf/glass hybrid fiber reinforced polyester composites

The dynamic mechanical properties of randomly oriented intimately mixed hybrid composites based on pineapple leaf fibers (PALF) and glass fibers (GF) in unsaturated polyester (PER) matrix were investigated. The PALFs have high‐specific strength and improve the mechanical properties of the PER matrix. In this study, the volume ratio of the two fibers was varied by incorporating small amounts of GF such as PALF/GF, 90/10, 80/20, 70/30, and 50/50, keeping the total fiber loading constant at 40 wt%. The dynamic modulus of the compositeswas found to increase on GF addition. The intimately mixed (IM) hybrid composites with PALF/GF, 80/20 (0.2 V_f GF) showed highest E′ values and least damping. Interestingly, the impact strength of the composites was minimum at this volume ratio. The composites with 0.46 V_f GF or PALF/GF (50/50) showed maximum damping behavior and highest impact strength. The results were compared with hybrid composites of different layering patterns such as GPG (GF skin and PALF core) and PGP (PALF skin and GF core). IM and GPG hybrid composites are found more effective than PGP. The activation energy values for the relaxation processes in different composites were calculated. The overall results showed that hybridization with GF enhanced the performance properties. POLYM. COMPOS., 2010. © 2009 Society of Plastics Engineers     

Synthesis and characterization of ZnS-based quantum dots to trace low concentration of ammonia

In the present work,a solution-based co-precipitation method has been adopted to synthesize pure and cobalt-doped ZnS quantum dots and characterized by XRD,SEM,TEM with EDX,FTIR and gas sensing properties.XRD analysis has shown a single phase of ZnS quantum dots having a zinc blend structure.TEM and XRD line broadening indicated that the aver-age crystallite size in the sample is in the range of 2 to 5 nm.SEM micrographs show spherical-shaped quantum dots.FTIR stud-ies show that cobalt has been successfully doped into the ZnS cubic lattice.EDX spectra have analyzed the elemental pres-ence in the samples and it is evident that the spectra confirmed the presence of cobalt (Co),zinc (Zn),oxygen (O),and sulphur(S) elements only and no other impurities are observed.The ZnS-based quantum dot sensors reveal high sensitivity towards 50 ppm of ammonia vapors at an operating temperature of 70 ℃.Hence,ZnS-based quantum dots can be a promising and quick traceable sensor towards ammonia sensing applications with good response and recovery time.     

Truncation and Rounding-Based Scalable Approximate Multiplier Design for Computer Imaging Applications

Advanced technology used for arithmetic computing application, comprises greater number of approximate multipliers and approximate adders. Truncation and Rounding-based Scalable Approximate Multiplier (TRSAM) distinguish a variety of modes based on height (h) and truncation (t) as TRSAM (h, t) in the architecture. This TRSAM operation produces higher absolute error in Least Significant Bit (LSB) data shift unit. A new scalable approximate multiplier approach that uses truncation and rounding TRSAM (3, 7) is proposed to increase the multiplier accuracy. With the help of foremost one bit architecture, the proposed scalable approximate multiplier approach reduces the partial products. The proposed approximate TRSAM multiplier architecture gives better results in terms of area, delay, and power. The accuracy of 95.2% and the energy utilization of 24.6 nJ is observed in the proposed multiplier design. The proposed approach shows 0.11%, 0.23%, and 0.24% less Mean Absolute Relative Error (MARE) when compared with the existing approach for the input of 8-bit, 16-bit, and 32-bit respectively. It also shows 0.13%, 0.19%, and 0.2% less Variance of Absolute Relative Error (VARE) when compared with the existing approach for the input of 8-bit, 16-bit, and 32-bit respectively. The proposed approach is implemented with Field-Programmable Gate Array (FPGA) and shows the delay of 3.640, 6.481, 12.505, 22.572, and 36.893 ns for the input of 8-bit, 16-bit, 32-bit, 64-bit, and 128-bit respectively. The proposed approach is applied in digital filters design which shows the Peak-Signal-to-Noise Ratio (PSNR) of 25.05 dB and Structural Similarity Index Measure (SSIM) of 0.98 with 393 pJ energy consumptions when used in image application. The proposed approach is simulated with Xilinx and MATLAB and implemented with FPGA.     

Rough set based decision rule generation to find behavioural patterns of customers

Rough sets help in finding significant attributes of large data sets and generating decision rules for classifying new instances. Though multiple regression analysis, discriminant analysis, log-it analysis and several other techniques can be used for predicting results, they consider insignificant information also for processing which may lead to false positives and false negatives. In this study, we proposed rough set based decision rule generation framework to find reduct and to generate decision rules for predicting the Decision class. We conducted experiments over data of Portuguese Banking institution. From the proposed method, the dimensionality of data is reduced and decision rules are generated which predicts deposit nature of customers by 90% accuracy.     

Structural Characterization of Sputter-Deposited 304 Stainless Steel+10 wt pct Al Coatings

An SS304?+?10?wt pct Al (with a nominal composition of Fe-18Cr-8Ni-10Al by wt pct and corresponding to Fe-17Cr-6Ni-17Al by at. pct) coating was deposited on a 304-type austenitic stainless steel (Fe-18Cr-8Ni by wt pct) substrate by the magnetron sputter-deposition technique using two targets: 304-type stainless steel (SS304) and Al. The as-deposited coatings were characterized by X-ray diffraction, transmission electron microscopy, and three-dimensional (3-D) atom probe techniques. The coating consists of columnar grains with ?? ferrite with the body-centered cubic (bcc) (A2) structure and precipitates with a B2 structure. It also has a deposition-induced layered structure with two alternative layers (of 3.2 nm wavelength): one rich in Fe and Cr, and the other enriched with Al and Ni. The layer with high Ni and Al contents has a B2 structure. Direct confirmation of the presence of B2 phase in the coating was obtained by electron diffraction and 3-D atom probe techniques.