L’optimisation des réseaux cellulaires assistée par ordinateur: le logiciel RNO (Radio Network Optimisation)

Quality of service has become today a major concern for operators of mobile communication networks. The massive development of networks and strong competition between operators has lead to the necessary and daily follow-up of network quality of service, a key factor for its subscriber’s fidelity. This article aims at presenting the optimization methodology and proposes its illustration with a case of RNO (Radio Network Optimisation) software usage, one of the Alcatel optimization toolchain component. After a short presentation of cellular network, the optimization basic principles are described. RNO software and its main functionnalities are then detailed before a last part dedicated to a real case of optimization done with RNO software.     

Fast template tracking in video sequences

Tracking of poorly defined, rotating and/or distorted objects in a video sequence poses significant problems especially in medical diagnostics including ultrasound (sonographic) video used for examination and diagnosis of internal movement of tissue or muscle and nerve action. Cross-correlation techniques have been successful in retrieving dynamic information directly from ultrasound video data. We outline a fast implementation of tracking based on normalized cross-correlation using an adaptive template and present results from our application, developed in MATLAB?, which successfully tracks arbitrarily selected objects in deformed or severely compromised images. Common ultrasound image evaluation is qualitative but there is need to retrieve quantitative dynamic information such as the trajectory or velocity of selected areas. Our approach uses normalized two-dimensional cross-correlation to find the position of an initially selected template enclosing the feature of interest and map its trajectory frame-by-frame to produce displacement and velocity plots. We illustrate operation of the application using routine ultrasound data and demonstrate its performance using test video of objects rotating full circle and rolling down a ramp. We analyse errors associated with sampling to compare performance of our implementation with a more rigorous but tedious and computationally expensive correlation of a resampled, rotated, and shifted template.     

Dynamics of learning near singularities in layered networks

We explicitly analyze the trajectories of learning near singularities in hierarchical networks, such as multilayer perceptrons and radial basis function networks, which include permutation symmetry of hidden nodes, and show their general properties. Such symmetry induces singularities in their parameter space, where the Fisher information matrix degenerates and odd learning behaviors, especially the existence of plateaus in gradient descent learning, arise due to the geometric structure of singularity. We plot dynamic vector fields to demonstrate the universal trajectories of learning near singularities. The singularity induces two types of plateaus, the on-singularity plateau and the near-singularity plateau, depending on the stability of the singularity and the initial parameters of learning. The results presented in this letter are universally applicable to a wide class of hierarchical models. Detailed stability analysis of the dynamics of learning in radial basis function networks and multilayer perceptrons will be presented in separate work.     

Ferritin Protein Regulates the Degradation of Iron Oxide Nanoparticles

Proteins implicated in iron homeostasis are assumed to be also involved in the cellular processing of iron oxide nanoparticles. In this work, the role of an endogenous iron storage protein—namely the ferritin—is examined in the remediation and biodegradation of magnetic iron oxide nanoparticles. Previous in vivo studies suggest the intracellular transfer of the iron ions released during the degradation of nanoparticles to endogenous protein cages within lysosomal compartments. Here, the capacity of ferritin cages to accommodate and store the degradation products of nanoparticles is investigated in vitro in the physiological acidic environment of the lysosomes. Moreover, it is questioned whether ferritin proteins can play an active role in the degradation of the nanoparticles. The magnetic, colloidal, and structural follow‐up of iron oxide nanoparticles and proteins in lysosome‐like medium confirms the efficient remediation of potentially harmful iron ions generated by nanoparticles within ferritins. The presence of ferritins, however, delays the degradation of particles due to a complex colloidal behavior of the mixture in acidic medium. This study exemplifies the important implications of intracellular proteins in processes of degradation and metabolization of iron oxide nanoparticles.     

On the composition of time Petri nets

Complex systems are often designed and built from smaller pieces, called components. Components are open sub-systems meant to be combined (or composed) to form other components or closed systems. It is well known that Petri nets allow such a component based modeling, relying on parallel composition and transition synchronization. However, synchronizing transitions that carry temporal constraints does not yield a compositional method for assembling components, a highly desirable property. The paper addresses this particular problem: how to build complex systems in a compositional manner from components specified by Time Petri nets (TPN). A first solution is proposed, adequate for a particular subclass of Time Petri nets but significantly increasing the complexity of components. Then an improved solution is developed, relying on an extension of Time Petri nets with two relations added on transitions. This latter solution requires a much simpler transformation of nets, does not significantly increase their complexity, and is applicable to a larger class of TPN.     

A gradient-based path optimization method for motion planning

Most algorithms in probabilistic sampling-based path planning compute collision-free paths made of straight line segments lying in the configuration space. Due to the randomness of sampling, the paths make detours that need to be optimized. The contribution of this paper is to propose a basic gradient-based algorithm that transforms a polygonal collision-free path into a shorter one. While requiring only collision checking, and not any time-consuming obstacle distance computation nor geometry simplification, we constrain only part of the configuration variables that may cause a collision, and not entire configurations. Thus, parasite motions that are not useful for the problem resolution are reduced without any assumption. Experimental results include navigation and manipulation tasks, eg a manipulator arm-filling boxes and a PR2 robot working in a kitchen environment. Comparisons with a random shortcut optimizer and a partial shortcut have also been studied.     

Stabilization of slugging in oil production facilities with or without upstream pressure sensors

This paper presents methods for suppressing the slugging phenomenon occurring in multiphase flow. The considered systems include industrial oil production facilities such as gas-lifted wells and flowline risers with low-points. Given the difficulty to maintain sensors in deep locations, a particular emphasis is put on observer-based control design. It appears that, without any upstream pressure sensor, such a strategy can stabilize the flow. Besides, given a measurement or estimate of the upstream pressure, we propose a control strategy alternative to the classical techniques. The efficiency of these methods is assessed through experiments on a mid-scaled multiphase flow loop.     

Modulation of Cellular Fate of Vinyl Triarylamines through Structural Fine Tuning: To Stay or Not To Stay in the Mitochondria?

Mitochondria are involved in many cellular pathways and dysfunctional mitochondria are linked to various diseases. Hence efforts have been made to design mitochondria-targeted fluorophores for monitoring the mitochondrial status. However, the factors that govern the mitochondria-targeted potential of dyes are not well-understood. In this context, we synthesized analogues of the TP-2Bzim probe belonging to the vinyltriphenylamine (TPA) class and already described for its capacity to bind nuclear DNA in fixed cells and mitochondria in live cells. These analogues ( TP-1Bzim, TPⁿ-2Bzim, TP¹⁺-2Bzim, TN-2Bzim ) differ in the cationic charge, the number of vinylbenzimidazolium branches and the nature of the triaryl core. Using microscopy, we demonstrated that the cationic derivatives accumulate in mitochondria but do not reach mtDNA. Under depolarisation of the mitochondrial membrane, TP-2Bzim and TP¹⁺-2Bzim translocate to the nucleus in direct correlation with their strong DNA affinity. This reversible phenomenon emphasizes that these probes can be used to monitor ΔΨ_m variations.