Automatic full field analysis of perfusion images gained by scanning laser Doppler flowmetry

BACKGROUND: Scanning laser Doppler flowmetry (SLDF) enables the measurement of the laser Doppler frequency shift in retinal tissue. This process allows the quantification of retinal and optic nerve head perfusion in an area of 2.7 mm x 0.7 mm within 2 seconds and with a spatial resolution of 10 microns x 10 microns. Owing to the local heterogeneity of the retinal microcirculation itself and to heart associated pulsation the capillary retinal blood flow depends on location and time. Because of technical limitations measurements of flow are only valid in retinal points with adequate brightness and focus, and away from big vessels. To include the heart beat associated pulsation and the spatial heterogeneity of retinal blood flow into the evaluation of blood flow an algorithm was developed examining automatically the whole SLDF perfusion image. AIM: To report intraobserver reliability and interobserver reliability of a new method for analysing automatically full field perfusion images. METHOD: The base of blood flow calculation by the automatic full field perfusion image analyser (AFFPIA) was 16,384 intensity time curves of all pixels of the whole perfusion image gained by the SLDF. AFFPIA calculates the Doppler frequency shift and the haemodynamic variables flow, volume, and velocity of each pixel. The resulting perfusion image was processed with respect to (1) underexposed and overexposed pixels, (2) saccades, and (3) the retinal vessel tree. The rim area and the saccades were marked interactively by the operator. The capillaries and vessels of the retinal vessel tree were identified automatically by pattern analysis. Retinal vessels with a diameter greater than 30 microns, underexposed or overexposed areas, and saccades were excluded automatically. Based on the whole perfusion image total mean flow, total mean volume, total mean velocity, standard deviation, cumulative distribution curve of flow, and the capillary pulsation index were calculated automatically. Heart beat associated pulsation of capillary blood flow was estimated by plotting the mean capillary flow of each horizontal line against time. Intraobserver reliability was estimated by measuring 10 eyes of 10 subjects on five different days by one observer. Interobserver reliability of AFFPIA was evaluated by analysing 10 perfusion maps by five different operators. To find a baseline of retinal blood flow, perfusion maps of 67 eyes of normal subjects with a mean age of 40.4 (SD 15) years were evaluated by AFFPIA. RESULTS: The coefficient of reliability of the intraobserver reproducibility of flow was 0.74. The coefficient of reliability of the interobserver reproducibility was 0.95. The juxtapapillary retinal capillary flow was temporally 484 (SD 125), nasally 450 (117); the rim area capillary flow was 443 (110). The mean capillary pulsation index of retinal flow was 0.56 (0.14). CONCLUSION: Retinal blood flow evaluation by the AFFPIA increases significantly the interobserver reliability compared with conventional evaluation of 100 microns x 100 microns areas in SLDF images with the original Heidelberg retina flowmeter software. The intraobserver reliability of AFFPIA was in the same range as conventional evaluation.     

Fatty acids from Macoma sp. of bivalve mollusc

Fatty acids of the total lipids of flesh and hepatopancreas of Macoma sp. have been determined. The level of 20:5w3 (ca 17%), a biologically important fatty acid, was found to be considerably high. Other major component fatty acids were 16:0, 16:1, 18:1 and 22:4w6. High levels of 22:5w6 (8%), 22:5w3 (8%) and 22:6w3 (ca 15%) were found in flesh lipid. Nonsaponifiables were also high (28–30%). Alkyl ether acyl glycerols were found in flesh (1.3%) and hepatopancreas (3.8%).     

An integrated modeling approach to predict flooding on urban basin.

Correct prediction of flood extents in urban catchments has become a challenging issue. The traditional urban drainage models that consider only the sewerage-network are able to simulate the drainage system correctly until there is no overflow from the network inlet or manhole. When such overflows exist due to insufficient drainage capacity of downstream pipes or channels, it becomes difficult to reproduce the actual flood extents using these traditional one-phase simulation techniques. On the other hand, the traditional 2D models that simulate the surface flooding resulting from rainfall and/or levee break do not consider the sewerage network. As a result, the correct flooding situation is rarely addressed from those available traditional 1D and 2D models. This paper presents an integrated model that simultaneously simulates the sewerage network, river network and 2D mesh network to get correct flood extents. The model has been successfully applied into the Tenpaku basin (Nagoya, Japan), which experienced severe flooding with a maximum flood depth more than 1.5 m on September 11, 2000 when heavy rainfall, 580 mm in 28 hrs (return period > 100 yr), occurred over the catchments. Close agreements between the simulated flood depths and observed data ensure that the present integrated modeling approach is able to reproduce the urban flooding situation accurately, which rarely can be obtained through the traditional 1D and 2D modeling approaches.     

A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

Healing substrates with mobile, particle-filled microcapsules: designing a 'repair and go' system.

We model the rolling motion of a fluid-driven, particle-filled microcapsule along a heterogeneous, adhesive substrate to determine how the release of the encapsulated nanoparticles can be harnessed to repair damage on the underlying surface. We integrate the lattice Boltzmann model for hydrodynamics and the lattice spring model for the micromechanics of elastic solids to capture the interactions between the elastic shell of the microcapsule and the surrounding fluids. A Brownian dynamics model is used to simulate the release of nanoparticles from the capsule and their diffusion into the surrounding solution. We focus on a substrate that contains a damaged region (e.g. a crack or eroded surface coating), which prevents the otherwise mobile capsule from rolling along the surface. We isolate conditions where nanoparticles released from the arrested capsule can repair the damage and thereby enable the capsules to again move along the substrate. Through these studies, we establish guidelines for designing particle-filled microcapsules that perform a 'repair and go' function and thus, can be utilized to repair damage in microchannels and microfluidic devices.     

Nano-octopus: a new form of branching carbon nanofiber

A new multibranched octopus-type structure of carbon nanofibers is synthesized from a natural precursor, camphor, by a thermal chemical vapor deposition technique. An alloy of Cu:Ni catalyst is prepared by electrochemically coating nickel on a copper sheet, with nickel sulfate as an electrolyte, and heating that nickel-coated copper sheet to a higher temperature. Deposition of carbon on these substrates leads to the formation of a branched nanostructure in the temperature range of 923 K to 1023 K. The fiber diameter increases from 30 nm to 250 nm with increasing pyrolysis temperature. Detailed morphology and the internal structure of these fibers are studied by scanning and transmission electron microscopy.