Computer-aided method for quantification of cartilage thickness and volume changes using MRI: validation study using a synthetic model

The primary objective of this study was to develop a computer-aided method for the quantification of three-dimensional (3-D) cartilage changes over time in knees with osteoarthritis (OA). We introduced a local coordinate system (LCS) for the femoral and tibial cartilage boundaries that provides a standardized representation of cartilage geometry, thickness, and volume. The LCS can be registered in different data sets from the same patient so that results can be directly compared. Cartilage boundaries are segmented from 3-D magnetic resonance (MR) slices with a semi-automated method and transformed into offset-maps, defined by the LCS. Volumes and thickness are computed from these offset-maps. Further anatomical labeling allows focal volumes to be evaluated in predefined subregions. The accuracy of the automated behavior of the method was assessed, without any human intervention, using realistic, synthetic 3-D MR images of a human knee. The error in thickness evaluation is lower than 0.12 mm for the tibia and femur. Cartilage volumes in anatomical subregions show a coefficient of variation ranging from 0.11% to 0.32%. This method improves noninvasive 3-D analysis of cartilage thickness and volume and is well suited for in vivo follow-up clinical studies of OA knees.     

Resonator stability subject to dynamic random-tilt aberration

We derive the behavior of the average exit time (i.e., the number of reflections before escape) of a ray path traveling between two perfect mirrors subject to dynamic random-tilt aberrations. Our calculation is performed in the paraxial approximation. When small random tilts are taken into account, we may consider an asymptotic regime that generically reduces the problem to the study of the exit time from an interval for a harmonic, frictionless oscillator driven by Gaussian white noise. Despite its apparent simplicity, the exact solution of this problem remains an open mathematical challenge, and we propose here a simple approximation scheme. For flat mirrors, the natural frequency of the oscillator vanishes, and, in this case, the average exit time is known exactly. It exhibits a 2/3 scaling-law behavior in terms of the variance of the random tilts. This behavior also follows from our approximation scheme, which establishes the consistency of the scaling law. Our mathematical results are confirmed with simulation experiments.     

Comparative study of purine and pyrimidine nucleoside analogues acting on the thymidylate kinases of Mycobacterium tuberculosis and of humans

Thymidine monophosphate kinase (TMPK) from Mycobacterium tuberculosis (TMPKmt) is an attractive target for the design of specific inhibitors. This fact is the result of its key role in the thymidine pathway and of unique structural features in the active site observed by X-ray crystallography, especially in comparison to its human counterpart (TMPKh). Different 5-modified thymidine derivatives, as well as purine and pyrimidine analogues or C-nucleosides were tested on TMPKmt and TMPKh, and the results were rationalized by docking studies. 5-Halogenated 2'-deoxyuridines are the best inhibitors of TMPKmt found and present the highest selectivity indexes in favor of TMPKmt.     

Chemical Defenses of the Sacoglossan Mollusk Elysia rufescens and Its Host Alga Bryopsis sp.

Sacoglossans are a group of opisthobranch mollusks that have been the source of numerous secondary metabolites; however, there are few examples where a defensive ecological role for these compounds has been demonstrated experimentally. We investigated the deterrent properties of the sacoglossan Elysia rufescens and its food alga Bryopsis sp. against natural fish predators. Bryopsis sp. produces kahalalide F, a major depsipeptide that is accumulated by the sacoglossan and that shows in vitro cytotoxicity against several cancer cell lines. Our data show that both Bryopsis sp. and Elysia rufescens are chemically protected against fish predators, as indicated by the deterrent properties of their extracts at naturally occurring concentrations. Following bioassay-guided fractionation, we observed that the antipredatory compounds of Bryopsis sp. were present in the butanol and chloroform fractions, both containing the depsipeptide kahalalide F. Antipredatory compounds of Elysia rufescens were exclusively present in the dichloromethane fraction. Further bioassay-guided fractionation led to the isolation of kahalalide F as the only compound responsible for the deterrent properties of the sacoglossan. Our data show that kahalalide F protects both Bryopsis sp. and Elysia rufescens from fish predation. This is the first report of a diet-derived depsipeptide used as a chemical defense in a sacoglossan.     

Towards efficient data distribution on computational desktop grids with BitTorrent

Datacentric applications are still a challenging issue for large-scale distributed computing systems. The emergence of new protocols and software for collaborative content distribution over the Internet offers a new opportunity for efficient and fast delivery of a high volume of data. This paper presents an evaluation of the BitTorrent protocol for computational desktop grids. We first present a prototype of a generic subsystem dedicated to data management and designed to serve as a building block for any desktop grid system. Based on this prototype we conduct experiments to evaluate the potential of BitTorrent compared to a classical approach based on FTP data server. The preliminary results obtained with a 65-node cluster measure the basic characteristics of BitTorrent in terms of latency and bandwidth and evaluate the scalability of BitTorrent for the delivery of large input files. Moreover, we show that BitTorrent has a considerable latency overhead compared to FTP but clearly outperforms FTP when distributing large files or files to a high number of nodes. Tests on a synthetic application show that BitTorrent significantly increases the communication/computation ratio of the applications eligible to run on a desktop grid system.     

Extension of the Hansen-Bliek Method to Right-Quantified Linear Systems

The problem of finding the smallest box enclosing the united solution set of a linear interval system, also known as the “interval hull” problem, was proven to be NP-hard. However, Hansen, Bliek, and others subsequently, have provided a polynomial-time solution in the case of systems preconditioned by the midpoint inverse matrix. Based upon a similar approach, this paper deals with the interval hull problem in the context of AE-solution sets, where parameters may be given different quantifiers. A polynomial-time algorithm is proposed for computing the hull of AE-solution sets where parameters involved in the matrix are constrained to be existentially quantified. Such AE-solution sets are called right-quantified solution sets. They have recently been shown to be of practical interest.     

Well-structured languages

This paper introduces the notion of well-structured language. A well-structured language can be defined by a labelled well-structured transition system, equipped with an upward-closed set of accepting states. That peculiar class of transition systems has been extensively studied in the field of computer-aided verification, where it has direct an important applications. Petri nets, and their monotonic extensions (like Petri nets with non-blocking arcs or Petri nets with transfer arcs), for instance, are special subclasses of well-structured transition systems. We show that the class of well-structured languages enjoy several important closure properties. We propose several pumping lemmata that are applicable respectively to the whole class of well-structured languages and to the classes of languages recognized by Petri nets or Petri nets with non-blocking arcs. These pumping lemmata allow us to characterize the limits in the expressiveness of these classes of language. Furthermore, we exploit the pumping lemmata to strictly separate the expressive power of Petri nets, Petri nets with non-blocking arcs and Petri nets with transfer arcs.     

Hydraulic behaviour of a representative structural volume for containment buildings

For particular structures like containment buildings of nuclear power plants, the study of the hydraulic behaviour is of great concern. These structures are indeed the third barrier used to protect the environment in case of accidents. The evolution of the leaking rate through the porous medium is closely related to the changes in the permeability during the ageing process of the structure. It is thus essential to know the relation between concrete degradation and the transfer property when the consequences of a mechanical loading on the hydraulic behaviour have to be evaluated. A chained approach is designed for this purpose. The mechanical behaviour is described by an elastic plastic damage formulation, where damage is responsible for the softening evolution while plasticity accounts for the development of irreversible strains. The drying process is evaluated according to a non-linear equation of diffusion. From the knowledge of the damage and the degree of saturation, a relation is proposed to calculate the permeability of concrete. Finally, the non-homogeneous distribution of the hydraulic conductivity is included in the hydraulic problem which is in fact the association of the mass balance equation for gas phase and Darcy law. From this methodology, it is shown how an indicator for the hydraulic flows can be deduced.     

Quantum speed-up for unsupervised learning

We show how the quantum paradigm can be used to speed up unsupervised learning algorithms. More precisely, we explain how it is possible to accelerate learning algorithms by quantizing some of their subroutines. Quantization refers to the process that partially or totally converts a classical algorithm to its quantum counterpart in order to improve performance. In particular, we give quantized versions of clustering via minimum spanning tree, divisive clustering and k-medians that are faster than their classical analogues. We also describe a distributed version of k-medians that allows the participants to save on the global communication cost of the protocol compared to the classical version. Finally, we design quantum algorithms for the construction of a neighbourhood graph, outlier detection as well as smart initialization of the cluster centres.