Platinum nanoparticles decorated on graphitic carbon nitride-ZIF-67 composite support: An electrocatalyst for the oxidation of butanol in fuel cell applications

In the present study, we report an eco-friendly and simple route to design and synthesize novel nanocomposite catalyst based on platinum nanoparticles anchored on binary support of graphitic carbon nitride (g-C₃N₄) and cobalt-metal-organic framework (ZIF-67). For this purpose, ZIF-67 was prepared by precipitation method and g-C₃N₄ was prepared through thermal polymerization method. Later, ZIF-67 and g-C₃N₄ were hybridized through sonication to get homogeneous g–C₃N₄–ZIF-67 nanocomposite support material. Platinum nanoparticles (PtNPs) were uniformly deposited on g–C₃N₄–ZIF-67 by an electrochemical method. The as-developed nanocatalyst was characterized by morphological, structural and electrochemical techniques. The electrocatalytic activity of PtNPs@g–C₃N₄–ZIF-67 nanocatalyst towards butanol oxidation was evaluated via CV, CA, LSV and EIS in an alkaline medium. Results revealed that the proposed catalyst showed greatly enhanced electrooxidation of butanol in terms of high magnificent current density, lower oxidation potential, excellent long-term stability, large surface area, low charge transfer resistance and less toxic ability. Enhanced catalytic performance of the proposed catalyst could be ascribed to the synergistic effect of g–C₃N₄–ZIF-67 nanocomposite and PtNPs. The PtNPs@g–C₃N₄–ZIF-67 catalyst holds promising potential applications to be used as an anodic electrocatalyst for the development of high-performance alkaline fuel cells.     

Cooperative Diversity in Secondary Systems: Efficient Relaying Protocol for Cognitive Radio

Wireless Personal Communications - This paper considers half-duplex cooperative spectrum sharing scheme where both primary and secondary systems mutually cooperate with each other to exploit...     

Studies on dielectric relaxation and ac conductivity of cellulose acetate hydrogen phthalate–poly (vinyl pyrrolidone) blend

The dielectric constant, dielectric loss, and ac conductivity of polyblends of cellulose acetate hydrogen phthalate (CAP) and poly (vinyl pyrrolidone) (PVP) of different compositions were measured in the temperature range of 300–430 K and in the frequency range of 50 Hz–100 kHz. In the blends, the dielectric constant as well as the dielectric loss as a function of the temperature display a single peak corresponding to the glass transition temperature (T_g) in the region between the T_g values of the pure polymers. The T_g values observed agree well with those values obtained from DSC. Dielectric studies show that CAP forms a miscible blend with PVP. Ac conductivity values were calculated from the dielectric data and the conduction mechanism is discussed. © 2002 Wiley Periodicals, Inc. J Appl Polym Sci 86: 1702–1708, 2002     

Observer-invariant histopathology using genetics-based machine learning

Prostate cancer accounts for one-third of noncutaneous cancers diagnosed in US men and is a leading cause of cancer-related death. Advances in Fourier transform infrared spectroscopic imaging now provide very large data sets describing both the structural and local chemical properties of cells within prostate tissue. Uniting spectroscopic imaging data and computer-aided diagnoses (CADx), our long term goal is to provide a new approach to pathology by automating the recognition of cancer in complex tissue. The first step toward the creation of such CADx tools requires mechanisms for automatically learning to classify tissue types—a key step on the diagnosis process. Here we demonstrate that genetics-based machine learning (GBML) can be used to approach such a problem. However, to efficiently analyze this problem there is a need to develop efficient and scalable GBML implementations that are able to process very large data sets. In this paper, we propose and validate an efficient GBML technique——based on an incremental genetics-based rule learner. exploits massive parallelisms via the message passing interface (MPI) and efficient rule-matching using hardware-implemented operations. Results demonstrate that is capable of performing prostate tissue classification efficiently, making a compelling case for using GBML implementations as efficient and powerful tools for biomedical image processing.     

Cluster-Based Opportunistic Spectrum Allocation in CRWMN’s Using Co-operative Mechanism

With the innovation of Cognitive Radio Wireless Mesh Network’s, Opportunistic Spectrum Allocation can possibly moderate spectrum lack, by letting Secondary User’s a chance to sense and use unused bits of opportunistic licensed spectrum without any unfavourable effect on the Primary User’s. In Cognitive Radio Wireless Mesh Network’s, the Medium-Access-Control protocols characterizes the utilization of spectrum proficiently by allocating the channels among the users. Majority of proposed Medium-Access-Control protocols are utilizing Common-Control-Channel for dealing with the assets of Secondary-Users. The major downsides of these Medium-Access-Control protocols are broadcasting of Control-channel when substantial number of Secondary-User exists. In contrast with these Medium-Access-Control protocols, we develop an algorithm Time-Slotted-Allocation-Medium-Access-Control (TSA-MAC) protocol which is based on Clustered Time-Division-Medium-Access approach, which permits Secondary-User’s to allocate opportunistic spectrum with the help of co-operative decisions by exchange control information. In this approach, we are dividing the channels as different slots on which Secondary-User’s can transfer control and data packets. The TSA-MAC protocol will enhance the throughput for the Secondary-User’s over the communication channel. And also this method will facilitate to decide and allocate free channels for Secondary-User’s without interfering with Primary User’s.     

Mass transfer of viscous gas flow over porous stretching/shrinking sheet in the presence of slip and mass transpiration

The effect of the mass transpiration parameter on the viscous gas flow past a porous stretching/shrinking sheet in the presence of Navier's slip is investigated, and also, the mass transfer characteristics are examined. The physical flow problem executes the Navier–Stokes and the mass equation, which forms the system of nonlinear partial differential equations. These are transformed via similarity variables into a system of ordinary differential equations. The slip flow model of the total mass transfer on the moving sheet is modeled by introducing gas slip velocity. The total mass transfer on the moving sheet is modeled by inducing slip models of first and second order. Further, the suction which induces the slip velocity as opposed to the surface movement is examined. The mass suction-induced slip forces the adjacent gases to flow in the reverse direction to sheet movement. Thus, the solution space expands with the slip-induced suction and sheet movement. In the mass injection case, the induced slip increases the effect of the fluid flow for sheet movement. Upon all previous flow models, the present investigation is significant due as it investigates the mass transfer of viscous gasses flow past a porous medium in the presence of slip and mass transpiration.     

Far-infrared detector based on HgTe/HgCdTe superlattices

HgTe/Hg_0.05Cd_0.95Te superlattices (SLs) were grown on (112)B oriented Cd_0.96Zn_0.04 Te substrates using molecular beam epitaxy (MBE). The SLs, consisting of 100 periods of 80-Å-thick HgTe wells alternating with 77-Å-thick Hg_0.05Cd_0.95Te barriers, were designed to operate as detectors in the far-infrared (FIR) region. Infrared absorption spectroscopy, high-resolution transmission electron microscopy (TEM), Hall effect measurements, and x-ray diffraction were used to characterize the superlattice layers. A series of annealing experiments were initiated to quantify the temperature-dependent interdiffusion of the HgTe wells and Hg_0.05Cd_0.95Te barriers and consequently their degradation, which shifts the absorption edges of the SLs to higher energies, since a high-temperature ex situ anneal is normally required in order to produce the p-type material required for a photovoltaic detector. Results from infrared absorption spectroscopy, TEM, and Hall effect measurements for the annealed samples are presented. A FIR SLs single-element photoconductive (PC) device was designed and fabricated. Both material characterization and device testing have established the applicability of the HgTe/Hg_0.05Cd_0.95Te SLs for the FIR region.     

A new trust-based mechanism for detecting intrusions in MANET

Providing security to Mobile Ad-hoc Networks (MANET) is a challenging and demanding task. It is important to secure the network against intrusions in MANET for assuring the development of services. For this purpose, some intrusion-detection systems (IDSs) have been developed in traditional works. However, these have some drawbacks, such as that there is no assurance for public key authentication, certificate validation between two nodes is not possible, and they require a large amount of time for processing. To overcome all these issues, a Trust-Based Authentication Routing with Bio-Inspired Intrusion Detection System (TRAB-IDS) is developed in this article. The main aim of this article is to provide security to the network against harmful intrusions. Here, the trust and deep packet inspection (DPI) concepts are integrated for improving the security. Moreover, the certificate authority generates a public and private key pair for initiating the route agent and authenticating the neighboring nodes. Based on the trust of the node, the packet is forwarded to the intermediate node by calculating a bogus key. Then, the DPI is initiated for extracting the packet features and the similarity between the features is estimated. If the packet is matched with the attacker, an error report will be forwarded to the certificate authority; otherwise, the packet will be forwarded to the other node. The experimental results evaluate the performance of the proposed TRAB-IDS in terms of delivery ratio, delay, security cost, and misdetection ratio.     

Multiplexed cancer biomarker detection using quartz-based photonic crystal surfaces

A photonic crystal (PC) surface is demonstrated as a high-sensitivity platform for detection of a panel of 21 cancer biomarker antigens using a sandwich enzyme-linked immunosorbent assay (ELISA) microarray format. A quartz-based PC structure fabricated by nanoimprint lithography, selected for its low autofluorescence, supports two independent optical resonances that simultaneously enable enhancement of fluorescence detection of biomarkers and label-free quantification of the density of antibody capture spots. A detection instrument is demonstrated that supports fluorescence and label-free imaging modalities, with the ability to optimize the fluorescence enhancement factor on a pixel-by-pixel basis throughout the microarray using an angle-scanning approach for the excitation laser that automatically compensates for variability in surface chemistry density and capture spot density. Measurements show that the angle-scanning illumination approach reduces the coefficient of variation of replicate assays by 20-99% compared to ordinary fluorescence microscopy, thus supporting reduction in limits of detectable biomarker concentration. Using the PC resonance, biomarkers in mixed samples were detectable at the lowest concentrations tested (2.1-41 pg/mL), resulting in a three-log range of quantitative detection.