Assessment of Amyloid Forming Tendency of Peptide Sequences from Amyloid Beta and Tau Proteins Using Force-Field,Semi-Empirical,and Density Functional Theory Calculations

A wide variety of neurodegenerative diseases are characterized by the accumulation of protein aggregates in intraneuronal or extraneuronal brain regions. In Alzheimer’s disease (AD), the extracellular aggregates originate from amyloid-β proteins, while the intracellular aggregates are formed from microtubule-binding tau proteins. The amyloid forming peptide sequences in the amyloid-β peptides and tau proteins are responsible for aggregate formation. Experimental studies have until the date reported many of such amyloid forming peptide sequences in different proteins, however, there is still limited molecular level understanding about their tendency to form aggregates. In this study, we employed umbrella sampling simulations and subsequent electronic structure theory calculations in order to estimate the energy profiles for interconversion of the helix to β-sheet like secondary structures of sequences from amyloid-β protein (KLVFFA) and tau protein (QVEVKSEKLD and VQIVYKPVD). The study also included a poly-alanine sequence as a reference system. The calculated force-field based free energy profiles predicted a flat minimum for monomers of sequences from amyloid and tau proteins corresponding to an α-helix like secondary structure. For the parallel and anti-parallel dimer of KLVFFA, double well potentials were obtained with the minima corresponding to α-helix and β-sheet like secondary structures. A similar double well-like potential has been found for dimeric forms for the sequences from tau fibril. Complementary semi-empirical and density functional theory calculations displayed similar trends, validating the force-field based free energy profiles obtained for these systems.     

Cervical Diseases Prediction Using LHVR Techniques

The stabilizing mechanisms of cervical spine spondylosis are involved in the degenerating segmentation vertebra, which often causes pain. Health of the individual is affected, both physically and mentally. Due to depression, nervousness, and psychological damages occur thereby losing their human activity functions. The nucleus pulposus of spinal disc herniation is prolapsed through a deficiency of annulus fibrosus. A jelly-like core part of the disc contains proteins that cause the tissues to become swollen when it touches the nucleus pulposus. The proposed Gradient Linear Classification (GLC) algorithm is used for the efficient automatic classification of disc degeneration herniation of Inter vertebral/ vertebra in a cervical disc. Distance between the disc degeneration is classified through gradient operator and is estimated using the rotation of angles between the correlations. Specialists of the orthopedic spine are searching for high-precision algorithms, which are achieved using proposed Linear Hybrid Vertebra Regression (LHVR) diagnostic techniques to identify the degree of cervical disc degeneration using an accurate location. Our experimental results have been used to determine a high range of classification in predicting the spinal cord which saves handling time and accomplishes high accuracy in detection.     

Smart fuzzy-based energy-saving photovoltaic burp charging system

This paper focuses on the optimal usage of photovoltaic energy by implementing ‘pulse charging’ technique to charge batteries and to keep the supply from the solar panel continuously without any interruption. The burp-pulse charging technique is used to supply multiple loads. Three different batteries Bp, Ba1 and Ba2 are smart charged concurrently and individually during three kinds of charge statuses controlled by a charge regulation system. The high-frequency input pulses are obtained from an interleaved flyback converter. The charge for prime battery (Bp) is from the positive pulse and that for auxiliary battery-1 (Ba1) is from the break period between the pulses. Finally the third battery, that is, auxiliary battery-2 (Ba2) is incorporated to utilise the negative pulse charge through an inductor when the step-up chopper is closed. This can otherwise be put as, utilising the discharge current of Bp to supply a load. The Ba2 voltage is stepped up to supply a motor load when supply from prime battery Bp is unavailable. The closed loop simulation introduces a fuzzy logic controller which controls the generation of pulses according to the variations in the input source voltage. By this way, a linear and smoother current is available to charge the batteries. Thus, the energy-saving concept is fulfilled by the proposed design. Faster and uninterrupted charging and better battery life are other facets of the proposed system. The closed loop simulation is performed and results are presented.     

Structural and optical characterization of Ni-doped CdS quantum dots

Ni-doped CdS quantum dots have been prepared by chemical precipitation technique. The X-diffraction results indicated that the particle size of Ni-doped CdS nanoparticles is smaller than that of undoped CdS and no secondary phase was observed. The average grain size of the nanoparticles is found to lie in the range of 2.7–4 nm. The compositional analysis results show that Cd, Ni, and S are present in the samples. HRTEM studies reveal that the average particle size of undoped and Ni-doped CdS quantum dots is 2 and 3 nm, respectively. Raman spectra shows that 1LO, 2LO, and 3LO peaks of the Ni-doped CdS samples are slightly red shifted when compared to that of undoped CdS. The absorption edge of Ni-doped CdS nanoparticles is found to shift towards the higher-wavelength (red shift) side when compared to that of undoped CdS and the band gap is observed to lie in the range of 3.79–3.95 eV. This band gap is higher than that of the bulk CdS and is due to quantum confinement effect present in CdS nanoparticles.     

ANFIS‐EM approach for PET brain image reconstruction

In this article, for the reconstruction of the positron emission tomography (PET) images, an iterative MAP algorithm was instigated with its adaptive neurofuzzy inference system based image segmentation techniques which we call adaptive neurofuzzy inference system based expectation maximization algorithm (ANFIS‐EM). This expectation maximization (EM) algorithm provides better image quality when compared with other traditional methodologies. The efficient result can be obtained using ANFIS‐EM algorithm. Unlike any usual EM algorithm, the predicted method that we call ANFIS‐EM minimizes the EM objective function using maximum a posteriori (MAP) method. In proposed method, the ANFIS‐EM algorithm was instigated by neural network based segmentation process in the image reconstruction. By the image quality parameter of PSNR value, the adaptive neurofuzzy based MAP algorithm and de‐noising algorithm compared and the PET input image is reconstructed and simulated in MATLAB/simulink package. Thus ANFIS‐EM algorithm provides 40% better peak signal to noise ratio (PSNR) when compared with MAP algorithm. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 1–6, 2015     

Effect of heat treatment on pitting corrosion resistance of 6061 Al/SiC<Subscript>P</Subscript> composite coated by the cerium oxide film in 3.5 N NaCl solution

One of the main drawbacks of 6061 Al/SiC_P composite is its poor pitting corrosion resistance in the aggressive environment containing chloride ions, such as seawater, for example. The present article deals with the investigations of effects of aging on the corrosion behavior of 6061 Al/SiC_P composite and of the heat treatment on the pitting corrosion resistance of 6061 Al/SiC_P composite coated by cerium oxide prepared by chemical bath technique. Potentiodynamic polarization test was used to study the corrosion behavior of cerium oxide coatings in 3.5N NaCl solution. The microstructure of cerium oxide was examined by scanning electron microscopy (SEM) and the formed phases were identified by X-ray diffraction (XRD). The pitting corrosion resistance of the cerium oxide coating was found to be improved after heat treatment at 300°C for 30 min.     

Mixed convection about a rotating sphereConvection mixte autour d'une sphere tournanteMischkonvektion an einer rotierenden kugelCмeшaHHaя кoHвeкция oкoлo вpaщaющeйCя Cфepы

The paper presents a theoretical analysis of flow and heat transfer characteristics of the effects of buoyancy force on laminar boundary layer over a rotating sphere in forced flow under two kinds of heating conditions: uniform wall temperature and uniform surface heat flux. By applying appropriate coordinate transformations and using Merk's types of series, the governing momentum and energy equations are reduced to a set of coupled ordinary differential equations, which depend on wedge, rotation and buoyancy parameters. Numerical computations are carried out for Prandtl numbers 0.7,1.0 and for various values of buoyancy and rotation parameters. For aiding flow, it is found that both the friction factor and the local Nusselt number increase with increasing buoyancy force. The local free stream velocity increases with buoyancy which, in turn, affects the friction coefficient and Nusselt number. The coupling between rotation and buoyancy results in increased overshooting of the velocity profiles in the vicinity of the rotating sphere. For an equivalent buoyancy effect, heating by uniform surface heat flux yields larger local Nusselt number than heating by uniform wall temperature. The ratio Nu_UHF/Nu_UWT is higher for the rotating sphere (as compared to a nonrotating case) and further the ratio increases as the sphere spins faster. The effect of free stream, rotation and buoyancy on the eruption of flow is examined and also a suggestion for further investigation is made.     

Development of Ni-Al2O3In-Situ Nanocomposite by Reactive Milling and Spark Plasma Sintering

In the present study, Ni-30 vol pct Al₂O₃ in-situ nanocomposite was developed by reactive milling of NiO-Al-Ni powder mixture followed by spark plasma sintering (SPS). During milling, fcc to hcp transformation was observed in Ni(Al) phase and it transformed back to fcc phase around 773 K (500 °C). The hardness and yield strength of Ni-30 vol pct Al₂O₃ nanocomposite are approximately two times higher than that of pure Ni of similar grain size. The improved mechanical properties of nanocomposite are attributed to the presence of alumina particles of nanometer size.