Synthesis and characterization of Sn‑doped TiO2 flm for antibacterial applications

Simple sol–gel method has been exploited to deposit Sn-doped TiO2 thin flms on glass substrates. The resultant coatings were characterized by X-ray difraction (XRD), UV–visible techniques (UV–Vis), Fourier transform infrared spectroscopy (FTIR), and photoluminescence analysis (PL). The XRD pattern reveals an increase in crystallite size of the prepared samples with the increasing doping concentration. A decrease in doping concentrating resulted in the decrease in bandgap values. The diferent chemical bonds on these flms were identifed from their FTIR spectra. The photoluminescence analysis shows an increase in the emission peak intensity with increasing dopant concentration, and this can be attributed to the efect created due to surface states. The prepared samples were tested as antibacterial agent toward both Gram-positive and Gram-negative bacteria like S.aureus (Staphylococcus aureus) and E.coli (Escherichia coli), respectively. The size of the inhibition zones indicates that the sample shows maximum inhibitory property toward E.coli when compared to S.aureus

Automated Force Volume Image Processing for Biological Samples

Atomic force microscopy (AFM) has now become a powerful technique for investigating on a molecular level, surface forces, nanomechanical properties of deformable particles, biomolecular interactions, kinetics, and dynamic processes. This paper specifically focuses on the analysis of AFM force curves collected on biological systems, in particular, bacteria. The goal is to provide fully automated tools to achieve theoretical interpretation of force curves on the basis of adequate, available physical models. In this respect, we propose two algorithms, one for the processing of approach force curves and another for the quantitative analysis of retraction force curves. In the former, electrostatic interactions prior to contact between AFM probe and bacterium are accounted for and mechanical interactions operating after contact are described in terms of Hertz-Hooke formalism. Retraction force curves are analyzed on the basis of the Freely Jointed Chain model. For both algorithms, the quantitative reconstruction of force curves is based on the robust detection of critical points (jumps, changes of slope or changes of curvature) which mark the transitions between the various relevant interactions taking place between the AFM tip and the studied sample during approach and retraction. Once the key regions of separation distance and indentation are detected, the physical parameters describing the relevant interactions operating in these regions are extracted making use of regression procedure for fitting experiments to theory. The flexibility, accuracy and strength of the algorithms are illustrated with the processing of two force-volume images, which collect a large set of approach and retraction curves measured on a single biological surface. For each force-volume image, several maps are generated, representing the spatial distribution of the searched physical parameters as estimated for each pixel of the force-volume image

A rough set-based association rule approach implemented on exploring beverages product spectrum

[[abstract]]When items are classified according to whether they have more or less of a characteristic, the scale used is referred to as an ordinal scale. The main characteristic of the ordinal scale is that the categories have a logical or ordered relationship to each other. Thus, the ordinal scale data processing is very common in marketing, satisfaction and attitudinal research. This study proposes a new data mining method, using a rough set-based association rule, to analyze ordinal scale data, which has the ability to handle uncertainty in the data classification/sorting process. The induction of rough-set rules is presented as method of dealing with data uncertainty, while creating predictive if—then rules that generalize data values, for the beverage market in Taiwan. Empirical evaluation reveals that the proposed Rough Set Associational Rule (RSAR), combined with rough set theory, is superior to existing methods of data classification and can more effectively address the problems associated with ordinal scale data, for exploration of a beverage product spectrum.[[notice]]補正完畢[[incitationindex]]SCI[[booktype]]紙本[[booktype]]電子

Observation of the diphoton decay of the Higgs boson and measurement of its properties

Peer reviewe

Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV

Peer reviewe

Search for Dark Matter and Supersymmetry with a Compressed Mass Spectrum in the Vector Boson Fusion Topology in Proton-Proton Collisions at root s=8 TeV

Peer reviewe

Measurements of the tt¯ charge asymmetry using the dilepton decay channel in pp collisions at √s=7 TeV

Peer reviewe