SAR Image Regularization With Fast Approximate Discrete Minimization

Synthetic aperture radar (SAR) images, like other coherent imaging modalities, suffer from speckle noise. The presence of this noise makes the automatic interpretation of images a challenging task and noise reduction is often a prerequisite for successful use of classical image processing algorithms. Numerous approaches have been proposed to filter speckle noise. Markov random field (MRF) modelization provides a convenient way to express both data fidelity constraints and desirable properties of the filtered image. In this context, total variation minimization has been extensively used to constrain the oscillations in the regularized image while preserving its edges. Speckle noise follows heavy-tailed distributions, and the MRF formulation leads to a minimization problem involving nonconvex log-likelihood terms. Such a minimization can be performed efficiently by computing minimum cuts on weighted graphs. Due to memory constraints, exact minimization, although theoretically possible, is not achievable on large images required by remote sensing applications. The computational burden of the state-of-the-art algorithm for approximate minimization (namely the alpha -expansion) is too heavy specially when considering joint regularization of several images. We show that a satisfying solution can be reached, in few iterations, by performing a graph-cut-based combinatorial exploration of large trial moves. This algorithm is applied to joint regularization of the amplitude and interferometric phase in urban area SAR images.     

Long Distance Enhancement of Nonlinear Optical Properties Using Low Concentration of Plasmonic Nanostructures in Dye Doped Monolithic Sol–Gel Materials

Monolithic sol–gel silica composites incorporating platinum‐based chromophores and various types of gold nanoparticles (AuNPs) are prepared and polished to high optical quality. Their photophysical properties are investigated. The glass materials show well‐defined localized surface plasmon resonance (SPR) absorbance from the visible to NIR. No redshifts of the AuNP plasmon absorption peaks due to the increase in nanoparticle doping concentration are observed in the glasses, proving that no or very small SPR coupling effects occur between the AuNPs. At 600 nm excitation, but not at 532 nm, the AuNPs improve the nonlinear absorption performance of glasses codoped with 50 × 10^?3 m of a Pt‐acetylide chromophore. The glasses doped with lower concentrations of AuNPs (2–5 μm average distance) and 50 × 10^?3 m in chromophore, show a marked improvement in nonlinear absorption, with no or only small improvement for the more highly AuNP doped glasses. This study shows the importance of excitation wavelength and nanoparticle concentration for composite systems employing AuNPs to improve two‐photon absorption of chromophores.     

Molecular Origin of the Charge Carrier Mobility in Small Molecule Organic Semiconductors

Small‐molecule organic semiconductors are used in a wide spectrum of applications, ranging from organic light emitting diodes to organic photovoltaics. However, the low carrier mobility severely limits their potential, e.g., for large area devices. A number of factors determine mobility, such as molecular packing, electronic structure, dipole moment, and polarizability. Presently, quantitative ab initio models to assess the influence of these molecule‐dependent properties are lacking. Here, a multiscale model is presented, which provides an accurate prediction of experimental data over ten orders of magnitude in mobility, and allows for the decomposition of the carrier mobility into molecule‐specific quantities. Molecule‐specific quantitative measures are provided how two single molecule properties, the dependence of the orbital energy on conformation, and the dipole‐induced polarization determine mobility for hole‐transport materials. The availability of first‐principles based models to compute key performance characteristics of organic semiconductors may enable in silico screening of numerous chemical compounds for the development of highly efficient optoelectronic devices.     

Linking improvement models to manufacturing strategies - a methodology for SMEs and other enterprises

Small Manufacturing Enterprises (SMES) are of major importance to the future economic growth of the European Community. To sustain this role, they need support in defining their specific technological and organizational needs and in finding the right approach to respond to these needs. The main objective of the research described in this article is to develop a supporting methodology for determining the improvement priorities of SMEs through a process similar to the manufacturing strategy formulation. However, the tools and techniques proposed in this paper are of a general nature and need not be restricted to SMEs. The methodology uses Quality Function Deployment (QFD), a product oriented quality technique, to apply a contingency oriented approach to improvement priorities. The essence of the QFD method is to extract the customer needs or desires and then to translate them into technical product quality characteristics. Here, the customers are interviewees from a sample of Small Manufacturing Enterprises. We assume that the manufacturing system improvement needs stem from strategic manufacturing priorities and from concerns that express unsatisfied needs. To propagate the improvement needs from the strategic level to the action level, two QFD oriented matrices were developed. The first matrix was used to define the operating improvement needs of an enterprise while the second was used to determine its improvement priorities. Cluster analysis, a multivariate technique, identified several generic improvement models of the sampled enterprises.     

Modelling of growth, growth/no-growth interface and nonthermal inactivation areas of Listeria in foods

Growth, growth boundary and inactivation models have been extensively developed in predictive microbiology and are commonly applied in food research nowadays. Few studies though report the development of models which encompass all three areas together. A tiered modelling approach, based on the Gamma hypothesis, is proposed here to predict the behaviour of Listeria.Datasets of Listeria spp. behaviour in laboratory media, meat, dairy, seafood products and vegetables were collected from literature, unpublished sources and from the databases ComBase and Sym'Previus. The explanatory factors were temperature, pH, water activity, lactic and sorbic acids. For the growth part, 697 growth kinetic datasets were fitted. The estimated growth rates and 2021 additional growth primary datasets were used to fit the secondary growth models. In a second step, the fitted model was used to predict the growth/no-growth boundary. For the inactivation modelling phase, 535 inactivation curves were used.Gamma models with and without interactions between the explanatory factors were used for the growth and boundary models. The correct prediction percentage (predicted growth when growth is observed + predicted inactivation when inactivation is observed) varied from 62% to 81% for the models without interactions, and from 85% to 87% for the models with interactions. The median error for the predicted population size was less than 0.34 log₁₀(CFU/mL) for all models. The kinetics of inactivation were fitted with modified Weibull primary models and the estimated bacterial resistance was then modelled as a function of the explanatory factors. The error for the predicted microbial population size was less than 0.71 log₁₀(CFU/mL) with a median value of less than 0.21 for all foods.The model enables the quantification of the increase or decrease in the bacterial population for a given formulation or storage condition. It might also be used to optimise a food formulation or storage condition in the case of a targeted increase or decrease of the bacterial population.     

天然与合成紫晶的3 543 cm-1红外吸收谱带及其鉴定价值

重点对3 800～3 000 cm-1范围的红外吸收光谱在鉴别天然与合成紫晶中的适用性和局限性进行了研究.3 680, 3 664, 3 630 cm-1处吸收带的存在可以确认紫晶为人工合成的, 但仅指那些在近中性NH4F溶液中合成的紫晶.相反, 商业上大量的合成紫晶是在碱性K2CO3溶液中合成的, 这些紫晶的红外吸收光谱并无明显的鉴定特征.前人的研究发现了在近3 595, 3 543 cm-1处吸收带的潜在鉴定价值.3 595 cm-1吸收带在合成紫晶的红外吸收光谱中并未出现, 在一些天然紫晶中也常常缺失.3 543 cm-1吸收带出现在绝大多数碱性溶液中合成紫晶的红外吸收光谱中, 但有时也在天然紫晶中出现.因此, 它只是鉴别合成紫晶的临时性证据.3 543 cm-1吸收带在有些类型的合成紫晶中缺失.要准确地鉴定天然与合成紫晶一定要根据其红外光谱、内部生长结构(包括双晶)和包裹体特征综合判断.     

Influence of drying mode on iridoid bitter constituent levels in gentian root

Root samples of wild gentian (Gentiana lutea L) were harvested from six localities (altitude 970 m to 1350 m) from May to November 2000. Each batch of roots was split into three: fresh roots, naturally dried roots (ambient air) and artificially dried roots (40 °C). In all the samples, levels of iridoid bitter constituents and of xanthone coloured compounds were determined by HPLC. The mean total iridoid content in the fresh roots was 102.4 g kg^?1 in dry matter (DM). The mean level of the principal bitter compound gentiopicroside was particularly high at 81 g kg^?1 DM. Loganic acid, not previously reported in G lutea, was the second most abundant bitter compound at a mean level of 14.3 g kg^?1 DM. Swertiamarin was present at 5.4 g kg^?1, with another minor unidentified iridoid. Levels of iridoid compounds were strongly dependent of the drying mode. These amounts were 88.5 g kg^?1 DM in artificially dried roots and 62.5 g kg^?1 DM in naturally dried roots, mostly owing to a marked decrease in gentiopicroside. The temperature of 40 °C preserved the bitter compounds and the bitterness of fresh gentian roots. The amount of coloured xanthones was relatively low at 3.3 g kg^?1 and did not change with the drying mode. Copyright © 2004 Society of Chemical Industry