Geometrical characterization of healthy red blood cells using digital holographic microscopy and parametric shape models for biophysical studies and diagnostic applications

Modeling of the red blood cell (RBC) shape is an integral part of the experimental and computer simulation investigations of light scattering by these cells for fundamental studies as well as diagnostic applications in the techniques like cytometry. In the present work, a comprehensive study of the geometrical characterization of healthy human RBCs using the digital holographic microscopy (DHM) and six frequently employed parametric shape models is reported. It is shown that the comparison of the optical phase profiles, the thickness profiles given by the models with the DHM results gives a better judgement of the appropriateness of the parametric shape models. Results of geometrical characterization of 500 healthy RBCs in terms of volume, surface area and sphericity index lead to the classification of the parametric models in two categories based on the nature of variation of these quantities with the cell diameter. In light of the variability of the healthy RBC shapes, our findings suggest that the parametric models exhibiting a negative correlation between the sphericity index and the cell diameter would provide more reliable estimates of the RBC parameters in diagnostic applications. Statistical distributions and descriptive statistics of the RBC volume, surface area and sphericity index serve as a guide for the assessment of the capability of the studied parametric models to give a reliable account of the variability of the healthy RBC shape and size.Comment: 25 pages, 17 figure

Evolutionary Algorithms for Community Detection in Continental-Scale High-Voltage Transmission Grids

Symmetry is a key concept in the study of power systems, not only because the admittance and Jacobian matrices used in power flow analysis are symmetrical, but because some previous studies have shown that in some real-world power grids there are complex symmetries. In order to investigate the topological characteristics of power grids, this paper proposes the use of evolutionary algorithms for community detection using modularity density measures on networks representing supergrids in order to discover densely connected structures. Two evolutionary approaches (generational genetic algorithm, GGA+, and modularity and improved genetic algorithm, MIGA) were applied. The results obtained in two large networks representing supergrids (European grid and North American grid) provide insights on both the structure of the supergrid and the topological differences between different regions. Numerical and graphical results show how these evolutionary approaches clearly outperform to the well-known Louvain modularity method. In particular, the average value of modularity obtained by GGA+ in the European grid was 0.815, while an average of 0.827 was reached in the North American grid. These results outperform those obtained by MIGA and Louvain methods (0.801 and 0.766 in the European grid and 0.813 and 0.798 in the North American grid, respectively)

Dynamic Contrast-Enhanced MR Microscopy: Functional Imaging in Preclinical Models of Cancer

<p>Dynamic contrast-enhanced (DCE) MRI has been widely used as a quantitative imaging method for monitoring tumor response to therapy. The pharmacokinetic parameters derived from this technique have been used in more than 100 phase I trials and investigator led studies. The simultaneous challenges of increasing the temporal and spatial resolution, in a setting where the signal from the much smaller voxel is weaker, have made this MR technique difficult to implement in small-animal imaging. Existing preclinical DCE-MRI protocols acquire a limited number of slices resulting in potentially lost information in the third dimension. Furthermore, drug efficacy studies measuring the effect of an anti-angiogenic treatment, often compare the derived biomarkers on manually selected tumor regions or over the entire volume. These measurements include domains where the interpretation of the biomarkers may be unclear (such as in necrotic areas).</p><p>This dissertation describes and compares a family of four-dimensional (3D spatial + time), projection acquisition, keyhole-sampling strategies that support high spatial and temporal resolution. An interleaved 3D radial trajectory with a quasi-uniform distribution of points in k-space was used for sampling temporally resolved datasets. These volumes were reconstructed with three different k-space filters encompassing a range of possible keyhole strategies. The effect of k-space filtering on spatial and temporal resolution was studied in phantoms and in vivo. The statistical variation of the DCE-MRI measurement is analyzed by considering the fundamental sources of error in the MR signal intensity acquired with the spoiled gradient-echo (SPGR) pulse sequence. Finally, the technique was applied for measuring the extent of the opening of the blood-brain barrier in a mouse model of pediatric glioma and for identifying regions of therapeutic effect in a model of colorectal adenocarcinoma. </p><p>It is shown that 4D radial keyhole imaging does not degrade the system spatial and temporal resolution at a cost of 20-40% decrease in SNR. The time-dependent concentration of the contrast agent measured in vivo is within the theoretically predicted limits. The uncertainty in measuring the pharmacokinetic parameters with the sequences is of the same order, but always higher than, the uncertainty in measuring the pre-injection longitudinal relaxation time. The histogram of the time-to-peak provides useful knowledge about the spatial distribution of K^trans and microvascular density. Two regions with distinct kinetic parameters were identified when the TTP map from DCE-MRM was thresholded at 1000 sec. The effect of bevacizumab, as measured by a decrease in K^trans, was confined to one of these regions. DCE-MRI studies may contribute unique insights into the response of the tumor microenvironment to therapy.</p>Dissertatio

Virtual manufacturing: prediction of work piece geometric quality by considering machine and set-up

Lien vers la version éditeur: http://www.tandfonline.com/doi/full/10.1080/0951192X.2011.569952#.U4yZIHeqP3UIn the context of concurrent engineering, the design of the parts, the production planning and the manufacturing facility must be considered simultaneously. The design and development cycle can thus be reduced as manufacturing constraints are taken into account as early as possible. Thus, the design phase takes into account the manufacturing constraints as the customer requirements; more these constraints must not restrict the creativity of design. Also to facilitate the choice of the most suitable system for a specific process, Virtual Manufacturing is supplemented with developments of numerical computations (Altintas et al. 2005, Bianchi et al. 1996) in order to compare at low cost several solutions developed with several hypothesis without manufacturing of prototypes. In this context, the authors want to predict the work piece geometric more accurately by considering machine defects and work piece set-up, through the use of process simulation. A particular case study based on a 3 axis milling machine will be used here to illustrate the authors’ point of view. This study focuses on the following geometric defects: machine geometric errors, work piece positioning errors due to fixture system and part accuracy

Antipodal receptions in global acoustics

Bibliography: leaves 96-97.Global Acoustic Propagation is a recently developed scientific discipline within the study of long range underwater acoustic propagation. Acoustic propagation over extremely long ranges involves a combination of effects from earth curvature and the global distribution of oceanographic and geophysical features. Antipodal receptions, that is to ranges of the order of 20Mm (1 Megameter = 1 000 km), require underwater acoustic propagation to very long ranges and thus effects due to the form of the earth and the range dependence of the sound speed field within the ocean can not be ignored. The purpose of this thesis is to investigate the nature of antipodal receptions with reference to the form of the earth and horizontal sound speed variations within the ocean and thereby contribute to the new and specialized field of study, Global Acoustic Propagation. Close to an acoustic source acoustic energy diverges so that local signal strengths decrease with distance from the source. However, as the antipodal region is approached acoustic energy that has not been blocked by bathymetric features will refocus, counteracting the distance loss rule. Thus at antipodal sites there is a good prospect of receiving a focused signal. Even so, the ellipsoidal form of the earth and the horizontal variability within the sound speed field of the ocean means that the re-focusing will result in a region of enhanced signal rather than an exact antipodal point. The precise detail of the advantage of placing receivers in the antipodal region will depend upon the paths taken by the acoustic energy and the characteristics of the acoustic medium encountered along each path. The proposal for this thesis is to develop an algorithm to determine the nature of the antipodal region under certain physical assumptions. The physical assumptions are referred to as the geometric assumption, which refers to the form of the earth, and the refractive assumption, which refers to the horizontal variability of sound speed within the world oceans