Radio frequency plasma enhanced synthesis of antifouling polymeric coatings from monoterpene alcohols

Radio frequency plasma enhanced chemical vapor deposition is currently used to fabricate a broad range of functional coatings. This work described fabrication and characterization of a novel bioactive coating, polyterpenol, for encapsulation of three-dimensional indwelling medical devices. The materials are synthesized from monoterpene alcohols under different input power conditions. The chemical composition and structure of the polyterpenol thin films were determined by Xray photoelectron spectroscopy (XPS), Fourier transform infrared (FTIR) spectroscopy, contact angle measurements, and atomic force microscopy (AFM). The application of polyterpenol coating to the substrate reduced surface roughness from 1.5 to 0.4 of a nanometer, and increased the water contact angle from to 9 to 72 degrees. The extent of attachment and extracellular polysaccharide (EPS) production of two medically relevant pathogens, Staphylococcus aureus and Staphylococcus epidermis were analyzed using scanning electron microscopy (SEM) and confocal scanning laser microscopy (CSLM). Application of polyterpenol coating fabricated at 10 W significantly inhibited attachment and growth of both pathogens compared to unmodified substrates, whilst addition of 50 W films resulted in an increased attachment, proliferation and EPS production by both types of bacteria when compared to unmodified surface. Marked dissimilarity in bacterial response between two coatings was attributed to changes in surface chemistry, nano-architecture and surface energy of polymer thin films deposited under different input power conditions.

Multinomial solutions of the beach equation

Exact multinomial solutions of the beach equation for shallow water waves on a uniformly sloping beach are found and related to solution of the same equation found earlier by other investigators, using integral transform techniques. The use of these solutions for a general initialvalue problem for the equation under investigation is briefly discussed.

Effects of seasonal variability on FT-NIR prediction of dry matter content for whole Hass avocado fruit

Fourier Transform (FT)-near infra-red spectroscopy (NIRS) was investigated as a non-invasive technique for estimating percentage (%) dry matter of whole intact 'Hass' avocado fruit. Partial least squares (PLS) calibration models were developed from the diffuse reflectance spectra to predict % dry matter, taking into account effects of seasonal variation. It is found that seasonal variability has a significant effect on model predictive performance for dry matter in avocados. The robustness of the calibration model, which in general limits the application for the technique, was found to increase across years (seasons) when more seasonal variability was included in the calibration set. The R-v(2) and RMSEP for the single season prediction models predicting on an independent season ranged from 0.09 to 0.61 and 2.63 to 5.00, respectively, while for the two season models predicting on the third independent season, they ranged from 0.34 to 0.79 and 2.18 to 2.50, respectively. The bias for single season models predicting an independent season was as high as 4.429 but <= 1.417 for the two season combined models. The calibration model encompassing fruit from three consecutive years yielded predictive statistics of R-v(2) = 0.89, RMSEP = 1.43% dry matter with a bias of -0.021 in the range 16.1-39.7% dry matter for the validation population encompassing independent fruit from the three consecutive years. Relevant spectral information for all calibration models was obtained primarily from oil, carbohydrate and water absorbance bands clustered in the 890-980, 1005-1050, 1330-1380 and 1700-1790 nm regions. These results indicate the potential of FT-NIRS, in diffuse reflectance mode, to non-invasively predict the % dry matter of whole 'Hass' avocado fruit and the importance of the development of a calibration model that incorporates seasonal variation. Crown Copyright (c) 2012 Published by Elsevier B.V. All rights reserved.

A flexible hierarchical approach for facial age estimation based on multiple features

Age estimation from facial images is increasingly receiving attention to solve age-based access control, age-adaptive targeted marketing, amongst other applications. Since even humans can be induced in error due to the complex biological processes involved, finding a robust method remains a research challenge today. In this paper, we propose a new framework for the integration of Active Appearance Models (AAM), Local Binary Patterns (LBP), Gabor wavelets (GW) and Local Phase Quantization (LPQ) in order to obtain a highly discriminative feature representation which is able to model shape, appearance, wrinkles and skin spots. In addition, this paper proposes a novel flexible hierarchical age estimation approach consisting of a multi-class Support Vector Machine (SVM) to classify a subject into an age group followed by a Support Vector Regression (SVR) to estimate a specific age. The errors that may happen in the classification step, caused by the hard boundaries between age classes, are compensated in the specific age estimation by a flexible overlapping of the age ranges. The performance of the proposed approach was evaluated on FG-NET Aging and MORPH Album 2 datasets and a mean absolute error (MAE) of 4.50 and 5.86 years was achieved respectively. The robustness of the proposed approach was also evaluated on a merge of both datasets and a MAE of 5.20 years was achieved. Furthermore, we have also compared the age estimation made by humans with the proposed approach and it has shown that the machine outperforms humans. The proposed approach is competitive with current state-of-the-art and it provides an additional robustness to blur, lighting and expression variance brought about by the local phase features.

Compressive Sensing For Sparsely Excited Speech Signals

Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse response matrix operating on a sparse excitation, as in the linear model of speech production, for recovering compressive sensed speech. Since the linear transform is signal dependent and unknown, unlike the standard CS formulation, a codebook of transfer functions is proposed in a matching pursuit (MP) framework for CS recovery. It is found that MP is efficient and effective to recover CS encoded speech as well as jointly estimate the linear model. Moderate number of CS measurements and low order sparsity estimate will result in MP converge to the same linear transform as direct VQ of the LP vector derived from the original signal. There is also high positive correlation between signal domain approximation and CS measurement domain approximation for a large variety of speech spectra.

Stochastic modelling of monthly rainfall

A transformation is suggested which can transform a non-Gaussian monthly hydrological time series into a Gaussian one. The suggested approach is verified with data of ten Indian rainfall time series. Incidentally, it is observed that once the deterministic trends are removed, the transformation leads to an uncorrelated process for monthly rainfall. The procedure for normalization is general enough in that it should be also applicable to river discharges. This is verified to a limited extent by considering data of two Indian river discharges.

Large-chamber methane and nitrous oxide measurements are comparable to the backward Lagrangian stochastic method

Measurement of individual emission sources (e.g., animals or pen manure) within intensive livestock enterprises is necessary to test emission calculation protocols and to identify targets for decreased emissions. In this study, a vented, fabric-covered large chamber (4.5 × 4.5 m, 1.5 m high; encompassing greater spatial variability than a smaller chamber) in combination with on-line analysis (nitrous oxide [N2O] and methane [CH4] via Fourier Transform Infrared Spectroscopy; 1 analysis min-1) was tested as a means to isolate and measure emissions from beef feedlot pen manure sources. An exponential model relating chamber concentrations to ambient gas concentrations, air exchange (e.g., due to poor sealing with the surface; model linear when ≈ 0 m3 s-1), and chamber dimensions allowed data to be fitted with high confidence. Alternating manure source emission measurements using the large-chamber and the backward Lagrangian stochastic (bLS) technique (5-mo period; bLS validated via tracer gas release, recovery 94-104%) produced comparable N2O and CH4 emission values (no significant difference at P < 0.05). Greater precision of individual measurements was achieved via the large chamber than for the bLS (mean ± standard error of variance components: bLS half-hour measurements, 99.5 ± 325 mg CH4 s-1 and 9.26 ± 20.6 mg N2O s-1; large-chamber measurements, 99.6 ± 64.2 mg CH4 s-1 and 8.18 ± 0.3 mg N2O s-1). The large-chamber design is suitable for measurement of emissions from manure on pen surfaces, isolating these emissions from surrounding emission sources, including enteric emissions. © © American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America.

Superpropagator for a Nonpolynomial Field

By using a method originally due to Okubo we calculate the momentum-space superpropagator for a nonpolynomial field U(x)=1 / [1+fφ(x)] both for a massless and a massive neutral scalar φ(x) field. For the massless case we obtain a representation that resembles the weighted superposition of propagators for the exchange of a group of scalar fields φ(x) as is intuitively expected. The exact equivalence of this representation with the propagator function which has been obtained earlier through the use of the Fourier transform of a generalized function is established. For the massive case we determine the asymptotic form of the superpropagator.

Influence of Sm2O3 doping on formation and structure of SrBi2Nb2O9 nanocrystals in lithium borate glasses

New glasses of 16.66SrO–16.66[(1 − x)Bi2O3–xSm2O3]–16.66Nb2O5–50Li2B4O7 (0 ≤ x ≤ 0.5, in molar ratio), i.e., the pseudo-binary Sm2O3-doped SrBi2Nb2O9–Li2B4O7 glass system, giving the crystallization of Sm3+-doped SrBi2Nb2O9 nanocrystals are developed. It is found that the thermal stability of the glasses against the crystallization and the optical band gap energy increases with increasing Sm2O3 content. The formation of fluorite-type Sm3+-doped SrBi2Nb2O9 nanocrystals (diameters: 13–37 nm) with a cubic structure is confirmed in the crystallized (530 °C, 3 h) samples from X-ray powder diffraction analyses, Raman scattering spectrum measurements, and transmission electron microscope observations. The effect of Sm3+-doping on the microstructure, Raman scattering peak positions, and dielectric properties of composites comprising of fluorite-type SrBi2Nb2O9 nanocrystals and the Li2B4O7 glassy phase is clarified. It is found that fluorite-type SrBi2Nb2O9 nanocrystals transform to stable perovskite-type SrBi2Nb2O9 crystals with an orthorhombic structure by heat treatments at around 630 °C.

Syntheses and Self-Assembling Characteristics of Amphiphilic Star Diblock Copolymers

Uusien polymeeripohjaisten teknologioiden ja materiaalien myötä räätälöityjen polymeerien tarve on kasvanut. Viime vuosituhannen lopussa kehitetyt kontrolloidut polymerointimenetelmät ovat avanneet uusia mahdollisuuksia paitsi monimutkaisten polymeerien synteesiin, myös itsejärjestyvyyteen perustuvien funktionaalisten nanorakenteiden suunnitteluun ja valmistukseen. Nämä voivat jäljitellä luonnossa esiintyviä rakenteita, joita muodostavat esimerkiksi lipidit ja proteiinit. Itsejärjestyvät molekyylit ovat usein amfifiilisiä eli ne koostuvat hydrofiilisistä ja hydrofobisista osista ja polymeereissä nämä osat voivat olla omina lohkoinaan, jolloin puhutaan amfifiilisistä lohko- tai blokkikopolymeereistä. Riippuen järjestyneiden rakenteiden koostumuksesta ja muodosta, amfifiilisiä blokkikopolymeerejä on tutkittu tai jo käytetty nanoteknologiassa, elastomeereissä, voiteluaineissa, pinta-aktiivisina aineina, lääkkeenannostelussa, maaleissa, sekä elektroniikka-, kosmetiikka- ja elintarviketeollisuudessa. Tavallisimmin käytetyt amfifiiliset blokkikopolymeerit ovat olleet lineaarisia, mutta viime aikoina tutkimus on suuntautunut kohti monimutkaisempia rakenteita. Tällaisia ovat esimerkiksi tähtipolymeerit. Tähtimäisissä polymeereissä miselleille tyypillinen ydin-kuori-rakenne säilyy hyvin alhaisissakin polymeerikonsentraatioissa, koska polymeeriketjut ovat kiinni toisissaan yhdessä pisteessä. Siten ne ovat erityisen kiinnostavia tutkimuskohteita erilaisten hydrofobisten orgaanisten yhdisteiden sitomiseksi ja vapauttamiseksi. Tässä työssä on tarkasteltu amfifiilisten tähtipolymeerien itsejärjestymistä vesiliuoksissa sekä kokeellisesti ja tietokonesimulaatioin. Työ koostuu kahdesta osasta: tähtipolymeerien synteesistä makrosyklisillä initiaattoreilla ja amfifiilisten tähtimäisten blokkikopolymeerien ominaisuuksien tutkimisesta.