Analysis and optimization of the satellite-to-plane link of an aeronautical global system

En aquest projecte s’ha analitzat i optimitzat l’enllaç satèl·lit amb avió per a un sistema aeronàutic global. Aquest nou sistema anomenat ANTARES està dissenyat per a comunicar avions amb estacions base mitjançant un satèl·lit. Aquesta és una iniciativa on hi participen institucions oficials en l’aviació com ara l’ECAC i que és desenvolupat en una col·laboració europea d’universitats i empreses. El treball dut a terme en el projecte compren bàsicament tres aspectes. El disseny i anàlisi de la gestió de recursos. La idoneïtat d’utilitzar correcció d’errors en la capa d’enllaç i en cas que sigui necessària dissenyar una opció de codificació preliminar. Finalment, estudiar i analitzar l’efecte de la interferència co-canal en sistemes multifeix. Tots aquests temes són considerats només per al “forward link”. L’estructura que segueix el projecte és primer presentar les característiques globals del sistema, després centrar-se i analitzar els temes mencionats per a poder donar resultats i extreure conclusions.

Line search multilevel optimization as computational methods for dense optical flow

We evaluate the performance of different optimization techniques developed in the context of optical flowcomputation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we develop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow computation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.

Restriction site-associated DNA sequencing, genotyping error estimation and de novo assembly optimization for population genetic inference.

Restriction site-associated DNA sequencing (RADseq) provides researchers with the ability to record genetic polymorphism across thousands of loci for nonmodel organisms, potentially revolutionizing the field of molecular ecology. However, as with other genotyping methods, RADseq is prone to a number of sources of error that may have consequential effects for population genetic inferences, and these have received only limited attention in terms of the estimation and reporting of genotyping error rates. Here we use individual sample replicates, under the expectation of identical genotypes, to quantify genotyping error in the absence of a reference genome. We then use sample replicates to (i) optimize de novo assembly parameters within the program Stacks, by minimizing error and maximizing the retrieval of informative loci; and (ii) quantify error rates for loci, alleles and single-nucleotide polymorphisms. As an empirical example, we use a double-digest RAD data set of a nonmodel plant species, Berberis alpina, collected from high-altitude mountains in Mexico.

An algorithm for semi-infinite polynomial optimization

"Vegeu el resum a l'inici del document del fitxer adjunt."

A linear optimization technique for graph pebbling

Graph pebbling is a network model for studying whether or not a given supply of discrete pebbles can satisfy a given demand via pebbling moves. A pebbling move across an edge of a graph takes two pebbles from one endpoint and places one pebble at the other endpoint; the other pebble is lost in transit as a toll. It has been shown that deciding whether a supply can meet a demand on a graph is NP-complete. The pebbling number of a graph is the smallest t such that every supply of t pebbles can satisfy every demand of one pebble. Deciding if the pebbling number is at most k is NP 2 -complete. In this paper we develop a tool, called theWeight Function Lemma, for computing upper bounds and sometimes exact values for pebbling numbers with the assistance of linear optimization. With this tool we are able to calculate the pebbling numbers of much larger graphs than in previous algorithms, and much more quickly as well. We also obtain results for many families of graphs, in many cases by hand, with much simpler and remarkably shorter proofs than given in previously existing arguments (certificates typically of size at most the number of vertices times the maximum degree), especially for highly symmetric graphs. Here we apply theWeight Function Lemma to several specific graphs, including the Petersen, Lemke, 4th weak Bruhat, Lemke squared, and two random graphs, as well as to a number of infinite families of graphs, such as trees, cycles, graph powers of cycles, cubes, and some generalized Petersen and Coxeter graphs. This partly answers a question of Pachter, et al., by computing the pebbling exponent of cycles to within an asymptotically small range. It is conceivable that this method yields an approximation algorithm for graph pebbling.

A parameter-free approach for solving combinatorial optimization problems through biased randomization of efficient heuristics

This paper discusses the use of probabilistic or randomized algorithms for solving combinatorial optimization problems. Our approach employs non-uniform probability distributions to add a biased random behavior to classical heuristics so a large set of alternative good solutions can be quickly obtained in a natural way and without complex conguration processes. This procedure is especially useful in problems where properties such as non-smoothness or non-convexity lead to a highly irregular solution space, for which the traditional optimization methods, both of exact and approximate nature, may fail to reach their full potential. The results obtained are promising enough to suggest that randomizing classical heuristics is a powerful method that can be successfully applied in a variety of cases.

On the stability of the optimal value and the optimal set in optimization problems

The paper develops a stability theory for the optimal value and the optimal set mapping of optimization problems posed in a Banach space. The problems considered in this paper have an arbitrary number of inequality constraints involving lower semicontinuous (not necessarily convex) functions and one closed abstract constraint set. The considered perturbations lead to problems of the same type as the nominal one (with the same space of variables and the same number of constraints), where the abstract constraint set can also be perturbed. The spaces of functions involved in the problems (objective and constraints) are equipped with the metric of the uniform convergence on the bounded sets, meanwhile in the space of closed sets we consider, coherently, the Attouch-Wets topology. The paper examines, in a unified way, the lower and upper semicontinuity of the optimal value function, and the closedness, lower and upper semicontinuity (in the sense of Berge) of the optimal set mapping. This paper can be seen as a second part of the stability theory presented in [17], where we studied the stability of the feasible set mapping (completed here with the analysis of the Lipschitz-like property).

The de facto independence of regulatory agencies and its consequences for policy making and regulatory outcomes

This dissertation focuses on the practice of regulatory governance, throughout the study of the functioning of formally independent regulatory agencies (IRAs), with special attention to their de facto independence. The research goals are grounded on a "neo-positivist" (or "reconstructed positivist") position (Hawkesworth 1992; Radaelli 2000b; Sabatier 2000). This perspective starts from the ontological assumption that even if subjective perceptions are constitutive elements of political phenomena, a real world exists beyond any social construction and can, however imperfectly, become the object of scientific inquiry. Epistemologically, it follows that hypothetical-deductive theories with explanatory aims can be tested by employing a proper methodology and set of analytical techniques. It is thus possible to make scientific inferences and general conclusions to a certain extent, according to a Bayesian conception of knowledge, in order to update the prior scientific beliefs in the truth of the related hypotheses (Howson 1998), while acknowledging the fact that the conditions of truth are at least partially subjective and historically determined (Foucault 1988; Kuhn 1970). At the same time, a sceptical position is adopted towards the supposed disjunction between facts and values and the possibility of discovering abstract universal laws in social science. It has been observed that the current version of capitalism corresponds to the golden age of regulation, and that since the 1980s no government activity in OECD countries has grown faster than regulatory functions (Jacobs 1999). Following an apparent paradox, the ongoing dynamics of liberalisation, privatisation, decartelisation, internationalisation, and regional integration hardly led to the crumbling of the state, but instead promoted a wave of regulatory growth in the face of new risks and new opportunities (Vogel 1996). Accordingly, a new order of regulatory capitalism is rising, implying a new division of labour between state and society and entailing the expansion and intensification of regulation (Levi-Faur 2005). The previous order, relying on public ownership and public intervention and/or on sectoral self-regulation by private actors, is being replaced by a more formalised, expert-based, open, and independently regulated model of governance. Independent regulation agencies (IRAs), that is, formally independent administrative agencies with regulatory powers that benefit from public authority delegated from political decision makers, represent the main institutional feature of regulatory governance (Gilardi 2008). IRAs constitute a relatively new technology of regulation in western Europe, at least for certain domains, but they are increasingly widespread across countries and sectors. For instance, independent regulators have been set up for regulating very diverse issues, such as general competition, banking and finance, telecommunications, civil aviation, railway services, food safety, the pharmaceutical industry, electricity, environmental protection, and personal data privacy. Two attributes of IRAs deserve a special mention. On the one hand, they are formally separated from democratic institutions and elected politicians, thus raising normative and empirical concerns about their accountability and legitimacy. On the other hand, some hard questions about their role as political actors are still unaddressed, though, together with regulatory competencies, IRAs often accumulate executive, (quasi-)legislative, and adjudicatory functions, as well as about their performance.

Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation

This paper presents the Juste-Neige system for predicting the snow height on the ski runs of a resort using a multi-agent simulation software. Its aim is to facilitate snow cover management in order to i) reduce the production cost of artificial snow and to improve the profit margin for the companies managing the ski resorts; and ii) to reduce the water and energy consumption, and thus to reduce the environmental impact, by producing only the snow needed for a good skiing experience. The software provides maps with the predicted snow heights for up to 13 days. On these maps, the areas most exposed to snow erosion are highlighted. The software proceeds in three steps: i) interpolation of snow height measurements with a neural network; ii) local meteorological forecasts for every ski resort; iii) simulation of the impact caused by skiers using a multi-agent system. The software has been evaluated in the Swiss ski resort of Verbier and provides useful predictions.

ENaC and its regulatory proteins as drug targets for blood pressure control.

Hypertension is a serious medical problem affecting millions of people worldwide. A key protein regulating blood pressure is the Epithelial Na(+) Channel (ENaC). In accord, loss of function mutations in ENaC (PHA1) cause hypotension, whereas gain of function mutations (Liddle syndrome) result in hypertension. The region mutated in Liddle syndrome, called the PY motif (L/PPxY), serves as a binding site for the ubiquitin ligase Nedd4-2, a C2-WW-Hect E3 ubiquitin ligase. Nedd4-2 binds the ENaC-PY motif via it WW domains, ubiquitylates the channel and targets it for endocytosis, a process impaired in Liddle syndrome due to poor binding of the channel to Nedd4-2. This leads to accumulation of active channels at the cell surface and increased Na(+) (and fluid) absorption in the distal nephron, resulting in elevated blood volume and blood pressure. Compounds that destabilize cell surface ENaC, or enhance Nedd4-2 activity in the kidney, could potentially serve as drug targets for hypertension. In addition, recent discoveries of regulation of activation of ENaC by proteases such as furin, prostasin and elastase, which cleave the extracellular domain of this channel leading to it activation, as well as the identification of inhibitors that block the activity of these proteases, provide further avenues for drug targeting of ENaC and the control of blood pressure.

Progesterone/RANKL is a major regulatory axis in the human breast.

Estrogens and progesterones are major drivers of breast development but also promote carcinogenesis in this organ. Yet, their respective roles and the mechanisms underlying their action in the human breast are unclear. Receptor activator of nuclear factor κB ligand (RANKL) has been identified as a pivotal paracrine mediator of progesterone function in mouse mammary gland development and mammary carcinogenesis. Whether the factor has the same role in humans is of clinical interest because an inhibitor for RANKL, denosumab, is already used for the treatment of bone disease and might benefit breast cancer patients. We show that progesterone receptor (PR) signaling failed to induce RANKL in PR(+) breast cancer cell lines and in dissociated, cultured breast epithelial cells. In clinical specimens from healthy donors and intact breast tissue microstructures, hormone response was maintained and RANKL expression was under progesterone control, which increased RNA stability. RANKL was sufficient to trigger cell proliferation and was required for progesterone-induced proliferation. The findings were validated in vivo where RANKL protein expression in the breast epithelium correlated with serum progesterone levels and the protein was expressed in a subset of luminal cells that express PR. Thus, important hormonal control mechanisms are conserved across species, making RANKL a potential target in breast cancer treatment and prevention.

Hard-wired heterogeneity in blood stem cells revealed using a dynamic regulatory network model.

MOTIVATION: Combinatorial interactions of transcription factors with cis-regulatory elements control the dynamic progression through successive cellular states and thus underpin all metazoan development. The construction of network models of cis-regulatory elements, therefore, has the potential to generate fundamental insights into cellular fate and differentiation. Haematopoiesis has long served as a model system to study mammalian differentiation, yet modelling based on experimentally informed cis-regulatory interactions has so far been restricted to pairs of interacting factors. Here, we have generated a Boolean network model based on detailed cis-regulatory functional data connecting 11 haematopoietic stem/progenitor cell (HSPC) regulator genes. RESULTS: Despite its apparent simplicity, the model exhibits surprisingly complex behaviour that we charted using strongly connected components and shortest-path analysis in its Boolean state space. This analysis of our model predicts that HSPCs display heterogeneous expression patterns and possess many intermediate states that can act as 'stepping stones' for the HSPC to achieve a final differentiated state. Importantly, an external perturbation or 'trigger' is required to exit the stem cell state, with distinct triggers characterizing maturation into the various different lineages. By focusing on intermediate states occurring during erythrocyte differentiation, from our model we predicted a novel negative regulation of Fli1 by Gata1, which we confirmed experimentally thus validating our model. In conclusion, we demonstrate that an advanced mammalian regulatory network model based on experimentally validated cis-regulatory interactions has allowed us to make novel, experimentally testable hypotheses about transcriptional mechanisms that control differentiation of mammalian stem cells. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.