Co‐culture strategies for increased biohydrogen production

Biological hydrogen production from organic wastes is a less expensive, less energy‐demanding, and environmental‐friendly process. Pure monoculture delivers low H₂ content and low yield; these limitations are overcome by a defined co‐culture system, which outperforms mixed cultures with increased H₂ yield. The strategies used in co‐culture systems for increasing H₂ production have been discussed in this review. The strategies include hydrolysis of a variety of complex substrates, such as cellulose, molasses, crude glycerol, and algal biomass into simple fermentable sugars for increased H₂ yield by eliminating the use of exogenous enzymes. The strategies can bring geographically distant isolated microorganisms from different sources to coexist for simultaneous utilization of substrate and end metabolites into H₂ production of 99.99% purity without the expenses of reducing agents. In the case of maximum hydrogen production using co‐culture strategies, Clostridium, Enterobacter, and photo‐fermenting bacteria in a consolidated bioprocess system will result in increased H₂ yield. A co‐culture system is more feasible to achieve theoretical H₂ yield with high conversion efficiency of organic wastes, enhance the economic viability of H₂ production, provide better effluent treatment quality, and concurrently address the limitations of H₂ production. Copyright © 2015 John Wiley & Sons, Ltd.     

Dielectric and electrical response of hydroxyapatite – Na0.5K0.5NbO3 bioceramic composite

In recent years, the development of electrically active materials for orthopedic implant applications attracted attention owing to the fact that inherent electricity of bone mediates it's various metabolic processes. In this perspective, the present work investigates the effect of incorporation of varying amounts of piezoelectric biocompatible Na_0.5K_0.5NbO₃ (NKN) on dielectric and electrical properties of hydroxyapatite (HA) over a wide range of temperature (30–500?°C) and frequency (1?Hz?–?1?MHz). The composites HA-x NKN (x?=?10–30?wt%) were synthesized by solid state ceramic method and optimally sintered at 1075?°C for 2?h. X-Ray Diffraction (XRD) and Fourier Transform Infrared (FTIR) patterns confirmed the formation of phase pure HA and NKN in the composite system. The dielectric response of the samples has been compared with that of the existing theoretical models. The dielectric measurement suggests that the space charge as well as dipolar polarization is the dominant polarization mechanisms. The complex plane impedance and modulus spectroscopic analyses were performed to reveal the conduction mechanism. The activation energies for grain and grain boundary resistance for HA- (10–30?wt%) NKN were 1.03, 1.464, 1.28 and 1.34, 1.56, 1.30?eV, respectively. These results suggest that ionic conduction is the dominant conduction mechanism. Hydroxyl ions and oxygen vacancies are observed to be responsible for the conduction in HA-xNKN composite system. Overall, HA- x NKN composite system can be suggested as a potential material for electro-active orthopedic implant application.     

Impact of pH Value on Structural,Thermal, Optical and Raman Studies of Neodymium Phosphate (NdP) Nanoparticles Synthesized by Co-Precipitation Technique

Abstract

The present study deals with the impact of pH value on neodymium phosphate (NdP) nanoparticles which have been successfully synthesized via wet chemical co precipitation technique. PXRD revealed the formation of monoclinic phase, purity and crystallinity. TEM reveals spherical morphology with the formation of slight agglomeration and grain size decrease at low pH as compared to high pH. TGA/DTA suggests that as synthesized nanoparticle shows phase transition above 800^°C. FTIR and Raman spectroscopy signifies slight shifting of bands towards lower wave number at high pH and gives relevant peaks of phosphates (PO₄^3?) group. Optical absorption with selected value of pH were studied in UV-VIS spectrophotometer and showed a strong absorbance with a tendency towards blue shift.     

A fundamental approach to specify thermal and pressure loadings on containment buildings of sodium cooled fast reactors during a core disruptive accident

Reactor Containment Building (RCB) is the ultimate barrier to the environment against activity release in any nuclear power plant. It has to be designed to withstand both positive and negative pressures that are credible. Core Disruptive Accident (CDA) is an important event that specifies the design basis for RCB in sodium cooled fast reactors. In this paper, a fundamental approach towards quantification of thermal and pressure loadings on RCB during a CDA, has been described. Mathematical models have been derived from fundamental conservation principles towards determination of sodium release during a CDA, subsequent sodium fire inside RCB, building up of positive and negative pressures inside RCB, potential of in-vessel sodium fire due to failed seals and temperature evolution in RCB walls during extended period of containment isolation. Various heating sources for RCB air and RCB wall and their potential have been identified. Scaling laws for conducting CDA experiments in small-scale water models by chemical explosives and the rule for extrapolation of water leak to quantify sodium leak in reactor are proposed. Validation of the proposed models and experimental simulation rules has been demonstrated by applying them to Indian prototype fast breeder reactor. Finally, it is demonstrated that in-vessel sodium fire potential is very weak and no special containment cooling system is essential.     

Development of bimetal-grown multi-scale carbon micro-nanofibers as an immobilizing matrix for enzymes in biosensor applications

This study describes the development of a novel bimetal (Fe and Cu)-grown hierarchical web of carbon micro-nanofiber-based electrode for biosensor applications, in particular to detect glucose in liquids. Carbon nanofibers (CNFs) are grown on activated carbon microfibers (ACFs) by chemical vapor deposition (CVD) using Cu and Fe as the metal catalysts. The transition metal-fiber composite is used as the working electrode of a biosensor applied to detect glucose in liquids. In such a bi-nanometal-grown multi-scale web of ACF/CNF, Cu nanoparticles adhere to the ACF-surface, whereas Fe nanoparticles used to catalyze the growth of nanofibers attach to the CNF tips. By ultrasonication, Fe nanoparticles are dislodged from the tips of the CNFs. Glucose oxidase (GOx) is subsequently immobilized on the tips by adsorption. The dispersion of Cu nanoparticles at the substrate surface results in increased conductivity, facilitating electron transfer from the glucose solution to the ACF surface during the enzymatic reaction with glucose. The prepared Cu-ACF/CNF/GOx electrode is characterized for various surface and physicochemical properties by different analytical techniques, including scanning electron microscopy (SEM), electron dispersive X-ray analysis (EDX), Fourier-transform infrared spectroscopy (FTIR), BET surface area analysis, and transmission electron microscopy (TEM). The electrochemical tests show that the prepared electrode has fast response current, electrochemical stability, and high electron transfer rate, corroborated by CV and calibration curves. The prepared transition metal-based carbon electrode in this study is cost-effective, simple to develop, and has a stable immobilization matrix for enzymes.     

An AMBTC compression based data hiding scheme using pixel value adjusting strategy

Multidimensional Systems and Signal Processing - Image steganography is one of the most important research areas of information security where secret data is embedded in the images to conceal its...     

A new accelerated proximal technique for regression with high-dimensional datasets

We consider the problem of minimization of the sum of two convex functions, one of which is a smooth function, while another one may be a nonsmooth function. Many high-dimensional learning problems (classification/regression) can be designed using such frameworks, which can be efficiently solved with the help of first-order proximal-based methods. Due to slow convergence of traditional proximal methods, a recent trend is to introduce acceleration to such methods, which increases the speed of convergence. Such proximal gradient methods belong to a wider class of the forward–backward algorithms, which mathematically can be interpreted as fixed-point iterative schemes. In this paper, we design few new proximal gradient methods corresponding to few state-of-the-art fixed-point iterative schemes and compare their performances on the regression problem. In addition, we propose a new accelerated proximal gradient algorithm, which outperforms earlier traditional methods in terms of convergence speed and regression error. To demonstrate the applicability of our method, we conducted experiments for the problem of regression with several publicly available high-dimensional real datasets taken from different application domains. Empirical results exhibit that the proposed method outperforms the previous methods in terms of convergence, accuracy, and objective function values.     

VANET Based p-RSA Scheduling Algorithm Using Dynamic Cloud Storage

Wireless Personal Communications - Future intelligent transport systems would heavily rely on Vehicular Ad hoc Network which provides seamless services to the driver on national high-ways. This...