Caracterització d'oscil·ladors basats en CMOS-M/NEMS i la seva aplicació com a sensors de massa

El present projecte tracta sobre la caracterització d'oscil·ladors basats en ressonadors micro/nanoelectromecànics (M/NEMS) i la seva aplicació com a sensors de massa. Els oscil·ladors utilitzats es basen en un pont i una palanca ressoants M/NEMS, integrats en tecnologia CMOS. En primer lloc s'ha fet una introducció teòrica als conceptes utilitzats per a entendre el funcionament i la caracterització dels dispositius. A continuació s'han realitzat proves per tal de caracteritzar els paràmetres importants per a l'ús dels oscil·ladors com a sensors de massa, com la seva estabilitat en freqüència. Per acabar s'han aplicat aquests sensors en la caracterització i modelització del flux de massa a través d'obertures de dimensions micromètriques.

Cooperative strategies for imperfect CSI scenarios based on distributed Alamouti

Les comunicacions cooperatives estan guanyant un gran interès en les comunicacions modernes degut a que permeten millorar la transmissió dʼinformació entre un emissor i un receptor utilitzant una sèrie de terminals situats entre ells. Aquest projecte és un estudi complet del sistemes cooperatius, analitzant el seu rendiment i comparant lʼús dʼun sol dʼaquests terminals amb lʼús del codi Alamouti, que utilitza dos terminals. Primer hi ha una introducció als sistemes cooperatius i a la teoria de la informació. Després hem estudiat un sistema cooperatiu amb la teoria de la informació com a base, en termes de probabilitat de fallada del sistema, i posteriorment lʼhem adaptat a un sistema cooperatiu real utilitzant una modulació QPSK, estudiant la seva probabilitat dʼerror de paquet. Finalment es proposen diversos protocols que permeten millorar el rendiment del sistema cooperatiu estudiat.

A gene knockout approach in mice to identify glucose sensors controlling glucose homeostasis.

A key aspect of glucose homeostasis is the constant monitoring of blood glucose concentrations by specific glucose sensing units. These sensors, via stimulation of hormone secretion and activation of the autonomic nervous system (ANS), regulate tissue glucose uptake, utilization or production. The best described glucose detection system is that of the pancreatic beta-cells which controls insulin secretion. Secretion of other hormones, in particular glucagon, and activation of the ANS, are regulated by glucose through sensing mechanisms which are much less well characterized. Here I review some of the studies we have performed over the recent years on a mouse model of impaired glucose sensing generated by inactivation of the gene for the glucose transporter GLUT2. This transporter catalyzes glucose uptake by pancreatic beta-cells, the first step in the signaling cascade leading to glucose-stimulated insulin secretion. Inactivation of its gene leads to a loss of glucose sensing and impaired insulin secretion. Transgenic reexpression of the transporter in GLUT2/beta-cells restores their normal secretory function and rescues the mice from early death. As GLUT2 is also expressed in other tissues, these mice were then studied for the presence of other physiological defects due to absence of this transporter. These studies led to the identification of extra-pancreatic, GLUT2-dependent, glucose sensors controlling glucagon secretion and glucose utilization by peripheral tissues, in part through a control of the autonomic nervous system.

Desenvolupament d'una xarxa de sensors i actuadors sense fils de propòsit industrial

Aquesta memòria de projecte final de carrera és un estudi i implementació bàsica de l’estat actual en quant a les tecnologies/protocols sense fils existents, en particular centrat en ZigBee sobre la plataforma CC2430 de Texas Instruments, per a una aplicació industrial amb una taxa de transferència de dades baixa, que no presenta un alt grau de complexitat, però que requereix gran versatilitat i fiabilitat.

Plataforma per a la simulació de xarxes de sensors

Aquest projecte descriu una plataforma de simulació per a xarxes de sensors des de la perspectiva dels sistemes multi-agents. La plataforma s'ha dissenyat per facilitar la simulació de diferents aplicacions concretes de xarxes de sensors. A més, s'ha entregat com a artefacte del projecte IEA (Institucions Electròniques Autònomes, TIN2006-15662-C02-0) de l'IIIACSIC. Dins l'entorn de l'IEA, aquesta és l'eina que aporta les capacitats de simulació per donar suport al disseny d'algorismes adaptatius per a xarxes de sensors.

Sparse regularization for fiber ODF reconstruction: from the suboptimality of ℓ2 and ℓ1 priors to ℓ0.

Diffusion MRI is a well established imaging modality providing a powerful way to probe the structure of the white matter non-invasively. Despite its potential, the intrinsic long scan times of these sequences have hampered their use in clinical practice. For this reason, a large variety of methods have been recently proposed to shorten the acquisition times. Among them, spherical deconvolution approaches have gained a lot of interest for their ability to reliably recover the intra-voxel fiber configuration with a relatively small number of data samples. To overcome the intrinsic instabilities of deconvolution, these methods use regularization schemes generally based on the assumption that the fiber orientation distribution (FOD) to be recovered in each voxel is sparse. The well known Constrained Spherical Deconvolution (CSD) approach resorts to Tikhonov regularization, based on an ℓ(2)-norm prior, which promotes a weak version of sparsity. Also, in the last few years compressed sensing has been advocated to further accelerate the acquisitions and ℓ(1)-norm minimization is generally employed as a means to promote sparsity in the recovered FODs. In this paper, we provide evidence that the use of an ℓ(1)-norm prior to regularize this class of problems is somewhat inconsistent with the fact that the fiber compartments all sum up to unity. To overcome this ℓ(1) inconsistency while simultaneously exploiting sparsity more optimally than through an ℓ(2) prior, we reformulate the reconstruction problem as a constrained formulation between a data term and a sparsity prior consisting in an explicit bound on the ℓ(0)norm of the FOD, i.e. on the number of fibers. The method has been tested both on synthetic and real data. Experimental results show that the proposed ℓ(0) formulation significantly reduces modeling errors compared to the state-of-the-art ℓ(2) and ℓ(1) regularization approaches.

A first attempt of geographically-distributed Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM): mapping human time and energy throughput in metropolitan Barcelona

This study presents a first attempt to extend the “Multi-scale integrated analysis of societal and ecosystem metabolism (MuSIASEM)” approach to a spatial dimension using GIS techniques in the Metropolitan area of Barcelona. We use a combination of census and commercial databases along with a detailed land cover map to create a layer of Common Geographic Units that we populate with the local values of human time spent in different activities according to MuSIASEM hierarchical typology. In this way, we mapped the hours of available human time, in regards to the working hours spent in different locations, putting in evidence the gradients in spatial density between the residential location of workers (generating the work supply) and the places where the working hours are actually taking place. We found a strong three-modal pattern of clumps of areas with different combinations of values of time spent on household activities and on paid work. We also measured and mapped spatial segregation between these two activities and put forward the conjecture that this segregation increases with higher energy throughput, as the size of the functional units must be able to cope with the flow of exosomatic energy. Finally, we discuss the effectiveness of the approach by comparing our geographic representation of exosomatic throughput to the one issued from conventional methods.

Semigroup analysis of structured populations with distributed states-at-birth arising in mathematical aquaculture

Motivated by the modelling of structured parasite populations in aquaculture we consider a class of physiologically structured population models, where individuals may be recruited into the population at different sizes in general. That is, we consider a size-structured population model with distributed states-at-birth. The mathematical model which describes the evolution of such a population is a first order nonlinear partial integro-differential equation of hyperbolic type. First, we use positive perturbation arguments and utilise results from the spectral theory of semigroups to establish conditions for the existence of a positive equilibrium solution of our model. Then we formulate conditions that guarantee that the linearised system is governed by a positive quasicontraction semigroup on the biologically relevant state space. We also show that the governing linear semigroup is eventually compact, hence growth properties of the semigroup are determined by the spectrum of its generator. In case of a separable fertility function we deduce a characteristic equation and investigate the stability of equilibrium solutions in the general case using positive perturbation arguments.

Quantitative comparison of reconstruction methods for intra-voxel fiber recovery from diffusion MRI.

Validation is arguably the bottleneck in the diffusion magnetic resonance imaging (MRI) community. This paper evaluates and compares 20 algorithms for recovering the local intra-voxel fiber structure from diffusion MRI data and is based on the results of the "HARDI reconstruction challenge" organized in the context of the "ISBI 2012" conference. Evaluated methods encompass a mixture of classical techniques well known in the literature such as diffusion tensor, Q-Ball and diffusion spectrum imaging, algorithms inspired by the recent theory of compressed sensing and also brand new approaches proposed for the first time at this contest. To quantitatively compare the methods under controlled conditions, two datasets with known ground-truth were synthetically generated and two main criteria were used to evaluate the quality of the reconstructions in every voxel: correct assessment of the number of fiber populations and angular accuracy in their orientation. This comparative study investigates the behavior of every algorithm with varying experimental conditions and highlights strengths and weaknesses of each approach. This information can be useful not only for enhancing current algorithms and develop the next generation of reconstruction methods, but also to assist physicians in the choice of the most adequate technique for their studies.

PGC1alpha expression is controlled in skeletal muscles by PPARbeta, whose ablation results in fiber-type switching, obesity, and type 2 diabetes.

Mice in which peroxisome proliferator-activated receptor beta (PPARbeta) is selectively ablated in skeletal muscle myocytes were generated to elucidate the role played by PPARbeta signaling in these myocytes. These somatic mutant mice exhibited a muscle fiber-type switching toward lower oxidative capacity that preceded the development of obesity and diabetes, thus demonstrating that PPARbeta is instrumental in myocytes to the maintenance of oxidative fibers and that fiber-type switching is likely to be the cause and not the consequence of these metabolic disorders. We also show that PPARbeta stimulates in myocytes the expression of PGC1alpha, a coactivator of various transcription factors, known to play an important role in slow muscle fiber formation. Moreover, as the PGC1alpha promoter contains a PPAR response element, the effect of PPARbeta on the formation and/or maintenance of slow muscle fibers can be ascribed, at least in part, to a stimulation of PGC1alpha expression at the transcriptional level.

Foot worn inertial sensors for gait assessment and rehabilitation based on motorized shoes.

Fall prevention in elderly subjects is often based on training and rehabilitation programs that include mostly traditional balance and strength exercises. By applying such conventional interventions to improve gait performance and decrease fall risk, some important factors are neglected such as the dynamics of the gait and the motor learning processes. The EU project "Self Mobility Improvement in the eLderly by counteractING falls" (SMILING project) aimed to improve age-related gait and balance performance by using unpredicted external perturbations during walking through motorized shoes that change insole inclination at each stance. This paper describes the shoe-worn inertial module and the gait analysis method needed to control in real-time the shoe insole inclination during training, as well as gait spatio-temporal parameters obtained during long distance walking before and after the 8-week training program that assessed the efficacy of training with these motorized shoes.