Nanobiotechnology as a novel paradigm for enzyme immobilisation and stabilisation with potential applications in biodiesel production

Nanobiotechnology is emerging as a new frontier of biotechnology. The potential applications of nanobiotechnology in bioenergy and biosensors have encouraged researchers in recent years to investigate new novel nanoscaffolds to build robust nanobiocatalyt

Nurse-led titration of angiotensin converting enzyme inhibitors, beta-adrenergic blocking agents and angiotensin receptor blockers for patients with left ventricular systolic dysfunction

This is the protocol for a review and there is no abstract. The objectives are as follows:

To assess the effects of nurse-led titration of ACEIs, beta-adrenergic blocking agents and ARBs in patients with left ventricular systolic dysfunction in terms of safety and patient outcomes.

Fuzzy logic optimized wireless sensor network routing protocol

Wireless sensor networks (WSNs) are used in health monitoring, tracking and security applications. Such networks transfer data from specific areas to a nominated destination. In the network, each sensor node acts as a routing element for other sensor nodes during the transmission of data. This can increase energy consumption of the sensor node. In this paper, we propose a routing protocol for improving network lifetime and performance. The proposed protocol uses type-2 fuzzy logic to minimize the effects of uncertainty produced by the environmental noise. Simulation results show that the proposed protocol performs better than a recently developed routing protocol in terms of extending network lifetime and saving energy and also reducing data packet lost.

Monitoring the early stage self-assembly of enzyme-assisted peptide hydrogels

The early stages of the self-assembly of peptide hydrogels largely determine their final material properties. Here we discuss experimental methodologies for monitoring the self-assembly kinetics which underpin peptide hydrogel formation. The early stage assembly of an enzyme-catalysed Fmoc-trileucine based self-assembled hydrogel was examined using spectroscopic techniques (circular dichroism, CD, and solution NMR) as well as chromatographic (HPLC) and mechanical (rheology) techniques. Optimal conditions for enzyme-assisted hydrogel formation were identified and the kinetics examined. A lag time associated with the formation and accumulation of the self-assembling peptide monomer was observed and a minimum hydrogelator concentration required for gelation was identified. Subsequent formation of well defined nano-and microscale structures lead to self-supporting hydrogels at a range of substrate and enzyme concentrations. 1H NMR monitoring of the early self-assembly process revealed trends that were well in agreement with those identified using traditional methods (i.e. HPLC, CD, rheology) demonstrating 1H NMR spectroscopy can be used to non-invasively monitor the self-assembly of peptide hydrogels without damaging or perturbing the system.

A new neural network-based type reduction algorithm for interval type-2 fuzzy logic systems

This paper introduces a new type reduction (TR) algorithm for interval type-2 fuzzy logic systems (IT2 FLSs). Flexibility and adaptiveness are the key features of the proposed non-parametric algorithm. Lower and upper firing strengths of rules as well as their consequent coefficients are fed into a neural network (NN). NN output is a crisp value that corresponds to the defuzzified output of IT2 FLSs. The NN type reducer is trained through minimization of an error-based cost function with the purpose of improving modelling and forecasting performance of IT2 FLS models. Simulation results indicate that application of the proposed TR algorithm greatly enhances modelling and forecasting performance of IT2 FLS models. This benefit is achieved in no cost, as the computational requirement of the proposed algorithm is less than or at most equivalent to traditional TR algorithms.

Review short: Rachael Briggs’s Free Logic

 Review of Rachael Briggs' poetry collection, Free Logic, UQP, 2013.

Control of polystyrene batch reactor using fuzzy logic controller

Control of polymerization reactors is a challenging issue for researchers due to the complex reaction mechanisms. A lot of reactions occur simultaneously during polymerization. This leads to a polymerization system that is highly nonlinear in nature. In this work, a nonlinear advanced controller, named fuzzy logic controller (FLC), is developed for monitoring the batch free radical polymerization of polystyrene (PS) reactor. Temperature is used as an intermediate control variable to control polymer quality, because the products quality and quantity of polymer are directly depends on temperature. Different FLCs are developed through changing the number of fuzzy membership functions (MFs) for inputs and output. The final tuned FLC results are compared with the results of another advanced controller, named neural network based model predictive controller (NN-MPC). The simulation results reveal that the FLC performance is better than NN-MPC in terms of quantitative and qualitative performance criterion.