RNA Protection is Effectively Achieved by Pullulan Film Formation

RNA is a functionally versatile polymer but suffers from susceptibility to spontaneous and RNase‐catalyzed degradation. This vulnerability makes it difficult to preserve RNA for extended periods of time, thus limiting its use in various contexts, including practical applications as functional nucleic acids. Here we present a simple method to preserve RNA by pullulan (a complex sugar produced by Aureobasidium pullulans fungus) film formation. This strategy can markedly suppress both spontaneous and RNase degradation. Importantly, the pullulan film readily dissolves in aqueous solution, thus allowing retrieval of fully functional RNA species. In order to illustrate the advantage of this protective method in a practical application, we engineered a simple paper sensor containing a bacteria‐detecting RNA‐cleaving DNAzyme. This detection capability of the device was unchanged after storage at room temperature for six months.     

An evolutionary‐based adaptive neuro‐fuzzy inference system for intelligent short‐term load forecasting

The continuing growth in size and complexity of electric power systems requires the development of applicable load forecasting models to estimate the future electrical energy demands accurately. This paper presents a novel load forecasting approach called genetic‐based adaptive neuro‐fuzzy inference system (GBANFIS) to construct short‐term load forecasting expert systems and controllers. At the first stage, all records of data are searched by a novel genetic algorithm (GA) to find the most suitable feature of inputs to construct the model. Then, determined inputs are fed into the adaptive neuro‐fuzzy inference system to evolve the initial knowledge‐base of the expert system. Finally, the initial knowledge‐base is searched by another robust GA to induce a better cooperation among the rules by rule weight derivation and rule selection mechanisms. We show the superiority and applicability of our approach by applying it to the Iranian monthly electrical energy demand problem and comparing it with the most frequently adopted approaches in this field. Results indicate that GBANFIS outperforms its rival approaches and is a promising tool for dealing with short‐term load forecasting problems.     

Three-particle deterministic secure and high bit-rate direct quantum communication protocol

A scheme for deterministic secure and high bit-rate direct communication without resorting to a distinct control interval is proposed. It utilizes three entangled qubits, and presents higher bit transfer rate of information and higher security. The security of protocol is asserted by introducing a security control for each transferred bit. The protocol is investigated for a class of individual attacks and it is explicitly showed that the protocol has a high security even in the presence of channel loss.     

Interpretation of small and intermediate strain characteristics of Hostun sand for various stress states

Small and intermediate strain properties of soils are key parameters to assess ground motion characteristics during an earthquake and other dynamic events. These properties are affected by various parameters. Among them, the effect of anisotropic stress state on the soil specimen is interest of investigation in this paper. Experiments were carried out using the modified resonant column device at Ruhr Universität Bochum on dry Hostun sand with relative density of 35%-95%. The results show the significant effect of density and anisotropic stress states on the small strain properties, G_max, of Hostun sand. At intermediate strain level, the results show the significant effect of anisotropic stress state on the shear stiffness and damping ratio. In addition, it is concluded that the effect of compression stress component on the small and intermediate strain properties is more significant than the effect of the deviatoric stress component. At the end, the paper shows the successful application of stress-based approach to describe G(γ) and η(γ) in Hostun sand subjected to the isotropic and anisotropic stress states.     

Multiobjective optimization for force and moment balance of a four-bar linkage using evolutionary algorithms

In this study, force and moment balance of a planar four-bar linkage is implemented using evolutionary algorithms. In the current problem, the concepts of inertia counterweights and physical pendulum are utilized to complete balance of all mass effects, independent of input angular velocity. A proposed multiobjective particle swarm optimization, and non-dominated sorting genetic algorithm II are applied to minimize two objective functions subject to some design constraints. The applied algorithms produced a set of feasible solutions called pareto optimal solutions for the design problem. Finally, a fuzzy decision maker is utilized to select the best solution among the obtained pareto solutions. The results show that optimal solutions minimize the weights of applied counterweights and eliminate both shaking forces and moments transmitted to the ground, simultaneously.     

Fault diagnosis and classification based on wavelet transform and neural network

In this paper we present a novel method in fault recognition and classification in Nuclear Power Plant (NPP) using wavelet transform based Artificial Neural Network (ANN). We first simulate 10 design basis accidents (DBA) of a VVER-1000 using 15 input parameters with employing a Multilayer Perceptron (MLP) Neural Network with Resilient Backpropagation (RBP) algorithm. Afterwards we present the application of wavelet transform for its temporal shift property and multiresolution analysis characteristics to reduce disturbing perturbations in input training set data. Simulation of Artificial Neural Network and wavelet transform was performed using MATLAB software. The results show an enhanced accuracy and speed in fault recognition and high degree of robustness.     

Synthesis and properties of new photosensitive and chiral poly(amide‐imide)s based on bicyclo[2,2,2]oct‐7‐ene‐2,3,5,6‐tetracarboxylic diimide and dibenzalacetone moieties in the main chain

Aromatic poly(amide‐imide)s (PAIs) are high‐performance materials with a good compromise between thermal stability and processability when compared with polyamides or polyimides of analogous structures. In addition, the incorporation of photosensitive functional groups and chiral segments into the polymer backbone can lead to interesting polymers for various applications. In this work, six new photosensitive and chiral PAIs were synthesized from the direct polycondensation reaction of novel N,N′‐(bicyclo[2,2,2]oct‐7‐ene‐tetracarboxylic)‐bis‐L ‐amino acids with 2,5‐bis(4‐aminobenzylidene)cyclopentanone as dibenzalacetone moiety using two different methods. The polymerization reactions produced a series of photosensitive and optically active PAIs in high yields and with good inherent viscosities. The resulting polymers were characterized using Fourier transform infrared and ¹H NMR spectroscopy, elemental analysis, inherent viscosity, specific rotation, solubility tests and UV‐visible spectroscopy. The thermal properties of the PAIs were investigated using thermogravimetric analysis. Due to the presence of the dibenzalacetone moiety in the polymer chain, the PAIs have photosensitive properties. Also, these PAIs are optically active and soluble in various organic solvents. These resulting new polymers have the potential to be used in column chromatography for the separation of enantiomeric mixtures. Copyright © 2009 Society of Chemical Industry     

Prediction of the mechanical characteristics of multi-walled carbon nanotube/epoxy composites using a new form of the rule of mixtures

Multi-walled carbon nanotubes (MWCNTs) were used in the low-viscosity, thermosetting polyester epoxy/amine resin LY-5052 with high temperature resistance to fabricate MWCNT/epoxy composites. Tensile tests of the specimens were carried out to obtain mechanical properties of MWCNT/epoxy composites for various weight-percents (wt.%) of MWCNTs. Experimental results show that the Young’s modulus and the tensile strength of the composites can be significantly improved by adding a small percentage of MWCNT. A new form of the rule of mixtures, including an exponential shape function, length efficiency parameter, orientation efficiency factor and a waviness parameter, is proposed for a more accurate prediction of the mechanical properties of MWCNT-reinforced epoxy composites, for both low and high wt.% ranges. In order to verify the suitability of the model, the ensuing predictions are compared to the available experimental data in the literature. Results demonstrate a good predictability of the modified form over a wide range of tests.     

Performance analysis of a continuous bioreactor for ethanol and acetate synthesis from syngas via <Emphasis Type="Italic">Clostridium ljungdahlii</Emphasis> using exergy concept

In this paper, the exergetic performance of a continuous bioreactor for ethanol and acetate synthesis from syngas via a strictly anaerobic autotrophic bacterium Clostridium ljungdahlii was carried out for the first time. The fermentation process was evaluated using both conventional exergy and eco-exergy principles for measuring the productivity and renewability of the process at various liquid media flow rates. The microorganisms successfully upgraded the syngas into invaluable ethanol and acetate through the Wood–Ljungdahl pathway. The exergy efficiency was found to be in the range of 6.5–77.5 and 6.8–77.5 % during the fermentation using conventional exergy and eco-exergy concepts, respectively. The subtle differences observed in the exergetic parameters using the two exergetic concepts were ascribed to the slow growth rate of the microorganisms. Nevertheless, the eco-exergy concept would strongly be recommended for commercial bioreactor containing living organisms due to the inclusion of the information carried by microorganisms in the exergetic calculation. A desired liquid media flow rate of 0.55 mL/min was found according to a newly defined thermodynamic indictor namely exergetic productivity index. More specifically, the maximum exergetic productivity index of the fermentation process was found to be 8.0 using both approaches when the rate of inflow liquid was adjusted at the optimal value. The results of this study revealed that process yield alone cannot be a reliable performance metric for decision making on the productivity of various biofuel production pathways. Finally, the proposed exergetic framework could assist engineers and researchers to link biochemical and physical knowledge more robustly and to quantify and elucidate the general purpose of productivity and renewability.     

Viscosity of a CaO-MgO-Al2O3-SiO2 melt containing spinel particles at 1646K

This article reports an experimental investigation into the effect of solid suspension on the viscosity of molten slags. Up to about 20 vol pct of spinel (MgAl₂O₄) particles of three size ranges (fine: 0.10 to 0.21 mm; medium: 0.21 to 0.44 mm; and coarse: 0.44 to 0.99 mm) were added to a CaO-MgO-Al₂O₃-SiO₂ melt at 1646 (±10)K. A Brookfield DVII+ viscometer was used. The viscosity determined for the solid-free melts was in good agreement with the results of published work. The viscosity for the solid-containing melt was found to increase with the addition of the particles. With more than 10 vol pct solid particles, particularly the fine and the coarse ones, the melt showed an apparent “Bingham” behavior, i.e., the shear stress increased linearly with the shear rate but had a residual shear stress (up to 3 Pa depending on the amount and size of solid added) at zero shear rate. The viscosity of the solid-containing slag, η, was found to fit an Einstein-Roscoe type equation, η=η ₀ (1−af)⁻ⁿ, where η ₀ is the viscosity of the solid-free melt, f is the volume fraction of solid particles in the melt, and a and n are parameters taking the value of 4.24, 3.29, and 3.56 and 1.28, 2.36, and 2.24 for the fine, medium, and coarse particles, respectively, for best fit.