Manganese ferrite-polyaniline hybrid materials: Electrical and magnetic properties

Magnetic MnFe₂O₄ nanopowders were synthesized by an original solvothermal method in the absence and in the presence of tetra-n-butylammonium bromide (TBAB) and Tween 80 (TW) as surfactants. Manganese ferrite/polyaniline (PANI) hybrid materials were synthesized by in situ polymerization of aniline on the surface of MnFe₂O₄ using ammonium persulfate as oxidant. The purpose of the study was to investigate the influence of the two surfactants on the properties of the MnFe₂O₄ powders and of their composites with PANI. The specific surface area, the cumulative surface area of pores and the cumulative volume of pores are influenced by the nature of surfactant in case of MnFe₂O₄ powders and are higher by comparison to those of the MnFe₂O₄/PANI hybrid materials. The values of saturation magnetization in case of MnFe₂O₄ powders are higher than those of the hybrid materials and are not influenced by the surfactant nature. These features revealed that MnFe₂O₄ powders can be efficiently used as adsorbents for the purification of wastewaters. The values of the electrical conductivity of the composites exhibit a significant increase in comparison to the MnFe₂O₄ powders and depend on the surfactant nature. The highest value of electrical conductivity was achieved by the composite obtained using Tween 80 as surfactant (σ_DC = 54.5·10^?5S?m^?1) which was close to that of PANI (σ_DC = 61.2·10^?5 S?m^?1). The fact that the magnetic and electric properties of the synthesized MnFe₂O₄/PANI composites can be changed by design, demonstrate the high potential of these materials to be used in magneto-electric applications.     

Self Assembly of Polymer Structures Induced by Electric Field

A method has been developed for fabricating polymer microstructures based on electric field induced self assembly and pattern formation. A dielectric fluid placed in between two conductive plates experience a force in an applied electric field gradient across the plates, which can induce a diffusive surface instability and self construction of the fluid surface. This process is exploited for the fabrication of self assembled polymer microstructures as well as replicated patterns through the use of pre-patterned plates or electrodes. FEM simulation is used to decide the minimum wavelength and electric gradient distribution of polymer structures. A variety of structures in the micron and nanometer scales including bio-fluidic MEMS, polymer optoelectronic devices can be fabricated using this method.     

The Role of Rigid Residues in Modulating TEM-1 β-Lactamase Function and Thermostability

The relationship between protein motions (i.e., dynamics) and enzymatic function has begun to be explored in β-lactamases as a way to advance our understanding of these proteins. In a recent study, we analyzed the dynamic profiles of TEM-1 (a ubiquitous class A β-lactamase) and several ancestrally reconstructed homologues. A chief finding of this work was that rigid residues that were allosterically coupled to the active site appeared to have profound effects on enzyme function, even when separated from the active site by many angstroms. In the present work, our aim was to further explore the implications of protein dynamics on β-lactamase function by altering the dynamic profile of TEM-1 using computational protein design methods. The Rosetta software suite was used to mutate amino acids surrounding either rigid residues that are highly coupled to the active site or to flexible residues with no apparent communication with the active site. Experimental characterization of ten designed proteins indicated that alteration of residues surrounding rigid, highly coupled residues, substantially affected both enzymatic activity and stability; in contrast, native-like activities and stabilities were maintained when flexible, uncoupled residues, were targeted. Our results provide additional insight into the structure-function relationship present in the TEM family of β-lactamases. Furthermore, the integration of computational protein design methods with analyses of protein dynamics represents a general approach that could be used to extend our understanding of the relationship between dynamics and function in other enzyme classes.     

Investigation of bio-ethanol steam reforming over cobalt-based catalysts

The catalytic performance of cobalt catalysts supported on γ-Al₂O₃, TiO₂, ZrO₂ were studied for bio-ethanol steam reforming (BESR) reaction. The supported catalysts (10 wt%Co) were prepared by impregnation and characterized through Thermogravimetric analysis (TGA), H₂ chemisorption, laser Raman Spectroscopy, Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS), and temperature-programmed reaction (TPRxn). The metallic cobalt sites were found to correlate with the BESR reaction activity. The reaction and H₂ chemisorption showed that ZrO₂ supported catalyst showed the best dispersion and best catalytic activity. Over the 10% Co/ZrO₂ catalyst, using a H₂O:EtOH:inert molar ratio of 10:1:75 and a GHSV = 5000 h⁻¹, 100% ethanol conversion and a yield of 5.5 mol H₂/mol EtOH were obtained at 550 °C and atmospheric pressure.     

A dynamic lookahead tree based tracking algorithm for wireless sensor networks using particle filtering technique

In this study, five different algorithms are provided for tracking targets that move very fast in wireless sensor networks. The first algorithm is static and clusters are formed initially at the time of network deployment. In the second algorithm, clusters that have members at one hop distance from the cluster head are provided dynamically. In the third algorithm, clustered trees where members of a cluster may be more than one hop distance from the cluster head are provided dynamically. In the fourth, algorithm lookahead trees are formed along the predicted trajectory of the target dynamically. Linear, Kalman and particle filtering techniques are used to predict the target’s next state. The algorithms are compared for linear and nonlinear motions of the target against tracking accuracy, energy consumption and missing ratio parameters. Simulation results show that, for all cases, better performance results are obtained in the dynamic lookahead tree based tracking approach.     

Bandwidth-effective streaming of educational medical videos

Real-time delivery of medical videos requires high level of quality of service that shows no tolerance to loss and delay. In this study, how content-adaptive streaming can aid to maintain high-quality streaming sessions is investigated. The proposed strategy allocates a specific amount of bandwidth to streaming sessions and takes advantage of the general structure of instructional medical videos to decrease bandwidth consumption below this limit. The main contribution of the proposed mechanism is that it eliminates the need for rate adaptation which is common in traditional streaming by employing a proper bandwidth management scheme that enables constant bandwidth consumption below the allocated capacity. A streaming system based on the proposed mechanism has been implemented and its performance has been tested via emulation. Experimental results indicate that content-adaptive streaming successfully eliminates the need of rate adaptation during the delivery of critical data and hence preserves viewers’ satisfaction.     

Neural-network-based segmentation of multi-modal medical images: a comparative and prospective study

This work presents an investigation of the potential of artificial neural networks for classification of registered magnetic resonance and X-ray computer tomography images of the human brain. First, topological and learning parameters are established experimentally. Second, the learning and generalization properties of the neural networks are compared to those of a classical maximum likelihood classifier and the superiority of the neural network approach is demonstrated when small training sets are utilized. Third, the generalization properties of the neural networks are utilized to develop an adaptive learning scheme able to overcome interslice intensity variations typical of MR images. This approach permits the segmentation of image volumes based on training sets selected on a single slice. Finally, the segmentation results obtained both with the artificial neural network and the maximum likelihood classifiers are compared to contours drawn manually.     

On Security and Reliability Using Cooperative Transmissions in Sensor Networks

Cooperative transmissions have received recent attention and research papers have demonstrated their benefits for wireless networks. Such benefits include improving the reliability of links through diversity and/or increasing the reach of a link compared to a single transmitter transmitting to a single receiver (single-input single-output or SISO). In one form of cooperative transmissions, multiple nodes can act as virtual antenna elements and provide diversity gain or range improvement using space-time coding. In a multi-hop ad hoc or sensor network, a source node can make use of its neighbors as relays with itself to reach an intermediate node with greater reliability or at a larger distance than otherwise possible. The intermediate node will use its neighbors in a similar manner and this process continues till the destination is reached. Thus, for the same reliability of a link as SISO, the number of hops between a source and destination may be reduced using cooperative transmissions as each hop spans a larger distance. However, the presence of malicious or compromised nodes in the network impacts the benefits obtained with cooperative transmissions. Using more relays can increase the reach of a link, but if one or more relays are malicious, the transmission may fail. However, the relationships between the number of relays, the number of hops, and success probabilities are not trivial to determine. In this paper, we analyze this problem to understand the conditions under which cooperative transmissions fare better or worse than SISO transmissions. We take into consideration additional parameters such as the path-loss exponent and provide a framework that allows us to evaluate the conditions when cooperative transmissions are better than SISO transmissions. This analysis provides insights that can be employed before resorting to simulations or experimentation.