Comparison of ribosomal DNA length and restriction site polymorphisms in Gremmeniella and Ascocalyx isolates

The small subunit (SSU) and the internal transcribed spacer (ITS) of nuclear ribosomal DNA genes from 27 specimens of the fungal genera Gremmeniella and Ascocalyx were amplified by PCR. Length polymorphisms were observed in the SSU and allowed the differentiation of four groups among the isolates tested: (i) Ascocalyx abietis; (ii) Gremmeniella isolates from Picea spp.; (iii) Gremmeniella isolates from Abies balsamea; and (iv) Gremmeniella isolates from Abies sacchalinensis, Larix spp., and Pinus spp. The amplified ITS was the same length for all Gremmeniella specimens and was 60 bp longer in A. abietis. Phylogenetic analysis of length polymorphisms and of 24 restriction sites in the SSU and ITS showed that Gremmeniella isolates were more related to each other than to the Ascocalyx isolate. Furthermore, seven groups were evident within the genus Gremmeniella. Our results confirm that Gremmeniella and Ascocalyx should be kept as different taxa and suggest that the taxonomy of the former could be revised to consider isolates from Abies balsamea and from Picea spp. to be two different varieties while incorporating Gremmeniella laricina into G. abietina, as a new variety.     

Large cell lymphoma complicating persistent polyclonal B cell lymphocytosis

Persistent polyclonal B cell lymphocytosis (PPBL) is a rare lymphoproliferative disorder of unclear natural history and its potential for B cell malignancy remains unknown. We describe the case of a 39-year-old female who presented with stage IV-B large cell lymphoma 19 years after an initial diagnosis of PPBL; her disease was rapidly fatal despite intensive chemotherapy and blood stem cell transplantation. Because we had recently identified multiple bcl-2/Ig gene rearrangements in blood mononuclear cells of patients with PPBL, we sought evidence of this oncogene in this particular patient: bcl-2/Ig gene rearrangements were found in blood mononuclear cells but not in lymphoma cells. Owing to the possible role of Epstein-Barr virus (EBV) in the pathogenesis of PPBL, we also hypothesized our patient might have an EBV-related lymphoproliferative disorder. Despite serologies consistent with past exposure to this virus, it was not found in lymphoma cells using a sensitive polymerase chain reaction technique. We conclude that non-Hodgkin's lymphoma may occur during the course of PPBL. However, longer follow-up in more patients will be needed in order to better clarity the risk of hematologic malignancy in patients with PPBL.     

Effects of fullerenes and single-wall carbon nanotubes on murine and human macrophages

The discovery in 1985 of C-fullerenes, a novel carbon allotrope with a polygonal structure made up solely by 60 carbon atoms, and in 1991 of C-nanotubes, thin carbon filaments (1-3 μm in length and 0.001 μm in diameter) with extraordinary mechanical properties, opened a wide field of activity in carbon research. While toxicity and biocompatibility of C-fullerenes have been widely investigated, literature data concerning the biological properties and biotoxicity of C-nanotubes are poor and contradictory. Here we test the ability of highly purified C-Single-Walled-Nanotubes (SWNTs) and C-fullerenes to elicit an inflammatory response by murine and human macrophage cells in vitro. In order to determine the potential of these C-derivatives as biological inducers of inflammatory reactions we evaluate the ability of C-single-walled nanotubes and C-fullerenes to induce the release of NO by murine macrophages cells, to stimulate the phagocytic activity of human macrophage cells and to be cytotoxic against these cells. We show that SWNTs-C-nanotubes, when highly purified, as well as C-fullerenes, do not stimulate the release of NO by murine macrophage cells in culture, their uptake by human macrophage cells is very low, and they possess a very low toxicity against human macrophage cells.     

Superpipelined high-performance optical-flow computation architecture

Optical-flow computation is a well-known technique and there are important fields in which the application of this visual modality commands high interest. Nevertheless, most real-world applications require real-time processing, an issue which has only recently been addressed. Most real-time systems described to date use basic models which limit their applicability to generic tasks, especially when fast motion is presented or when subpixel motion resolution is required. Therefore, instead of implementing a complex optical-flow approach, we describe here a very high-frame-rate optical-flow processing system. Recent advances in image sensor technology make it possible nowadays to use high-frame-rate sensors to properly sample fast motion (i.e. as a low-motion scene), which makes a gradient-based approach one of the best options in terms of accuracy and consumption of resources for any real-time implementation. Taking advantage of the regular data flow of this kind of algorithm, our approach implements a novel superpipelined, fully parallelized architecture for optical-flow processing. The system is fully working and is organized into more than 70 pipeline stages, which achieve a data throughput of one pixel per clock cycle. This computing scheme is well suited to FPGA technology and VLSI implementation. The developed customized DSP architecture is capable of processing up to 170 frames per second at a resolution of 800 × 600 pixels. We discuss the advantages of high-frame-rate processing and justify the optical-flow model chosen for the implementation. We analyze this architecture, measure the system resource requirements using FPGA devices and finally evaluate the system’s performance and compare it with other approaches described in the literature.     

Analysis of the Functional Block Involved in the Design of Radial Basis Function Networks

The main architectures, learning abilities and applications of radial basis function (RBF) neural networks are well documented. However, to the best of our knowledge, no in-depth analyses have been carried out into the influence on the behaviour of the neural network arising from the use of different alternatives for the design of an RBF (different non-linear functions, distances, number of neurons, structures, etc.). Thus, as a complement to the existing intuitive knowledge, it is necessary to have a more precise understanding of the significance of the different alternatives. In the present contribution, the relevance and relative importance of the parameters involved in such a design are investigated by using a statistical tool, the ANalysis Of the VAriance (ANOVA). In order to obtain results that are widely applicable, various problems of classification, functional approximation and time series estimation are analyzed. Conclusions are drawn regarding the whole set.     

A new method for representing and matching shapes of natural objects

A new method for the representation and comparison of irregular two-dimensional shapes is presented. This method uses a polar transformation of the contour points about the geometric centre of the object. The distinctive vertices of the shape are extracted and used as comparative parameters to minimize the difference of contour distance from the centre. Experiments are performed, more than 39 000 comparisons of database shapes, provided by Sebastian et al. (ICCV (2001) 755), are made and the results are compared to those obtained therein. In addition, 450 comparisons of leaf shape are made and leaves of very similar shape are accurately distinguished. The method is shown to be invariant to translation, rotation and scaling and highly accurate in shape distinction. The method shows more tolerance to scale variation than that of Sebastian et al. (ICCV (2001) 755) and is less computationally intense.     

Optimal conditions for wet snow detection using RADARSAT SAR data

This paper presents simulation results of the backscattering coefficient, in order to discriminate between wet snow and dry snow covers sensed at 5.3 GHz by the RADARSAT Synthetic Aperture Radar (SAR) sensor. Snow-field measurements coinciding with the RADARSAT SAR overpasses are used to explore and set out optimal conditions for wet snow detection, as a function of the sensor incidence angles. The conditions concern wet snow surface characteristics, mainly the roughness represented by the surface slope m and the volumetric liquid water content, snwc (vol.%). Based on the 3-dB threshold value used in several wet snow detection algorithms, the results show that in order to be discriminated from dry snow covers, wet snow surfaces must be characterized as: (a) m≤0.058 and snwc≤1.1, if the sensor operates in the S1 mode (20-27° incidence angle range), and (b) m≤0.082 and snwc≤3.0, if the observations are made in the S7 mode (45-49° incidence angle range). For the identification of a very wet snow, it is also shown that the S7 mode of RADARSAT SAR sensor is more suitable than the S1 mode. The latter, however, provides better discrimination for low values of the snow liquid water content. Furthermore, for wet snow detection based on modeling, the present paper demonstrates the importance of using the appropriate methodology to assess the dielectric constant of the background medium.     

Optimal greenhouse gas emissions in NGCC plants integrating life cycle assessment

The optimal design of an energy-intensive process involves a compromise between costs and greenhouse gas emissions, complicated by the interaction between optimal process emissions and supply chain emissions. We propose a method that combines generic abatement cost estimates and the results of existing (LCA) life cycle assessment studies, so that supply chain emissions are properly handled during optimization. This method is illustrated for a (NGCC) natural gas combined cycle power plant model with the following design and procurement options: procurement of natural gas from low-emissions producers, fuel substitution with (SNG) synthetic natural gas from wood, and variable-rate CO₂ capture and sequestration from both the NGCC and SNG plants. Using multi-objective optimization, we show two Pareto-optimal sets with and without the proposed LCA method. The latter can then be shown to misestimate CO₂ abatement costs by a few percent, penalizing alternate fuels and energy-efficient process configurations and leading to sub-optimal design decisions with potential net losses of the order of $1/MWh. Thus, the proposed LCA method can enhance the economic analysis of emissions abatement technologies and emissions legislation in general.     

PDMS microfluidics developed for polymer based photonic biosensors

In this work, advances in the fabrication technology and functional analysis of a polymer microfluidic system—as a significant part of a developed polymer photonic biosensor—are reported. Robust and cost-effective microfluidics in PDMS including sample preparation functions is designed and realized by using SU-8 moulding replica. Surface modification strategies using Triton X-100 and PDMS-PEO and their effect on device sealing and non-specific protein adsorption are investigated by contact angle measurement and in situ fluorescence microscopy.