Local model predictive control experiences with differential driven wheeled mobile robots

This work extends a previously developed research concerning about the use of local model predictive control in differential driven mobile robots. Hence, experimental results are presented as a way to improve the methodology by considering aspects as trajectory accuracy and time performance. In this sense, the cost function and the prediction horizon are important aspects to be considered. The aim of the present work is to test the control method by measuring trajectory tracking accuracy and time performance. Moreover, strategies for the integration with perception system and path planning are briefly introduced. In this sense, monocular image data can be used to plan safety trajectories by using goal attraction potential fields

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

A subcritical instability of wave-driven alongshore currents

The development of shear instabilities of a wave-driven alongshore current is investigated. In particular, we use weakly nonlinear theory to investigate the possibility that such instabilities, which have been observed at various sites on the U.S. coast and in the laboratory, can grow in linearly stable flows as a subcritical bifurcation by resonant triad interaction, as first suggested by Shrira eta/. [1997]. We examine a realistic longshore current profile and include the effects of eddy viscosity and bottom friction. We show that according to the weakly nonlinear theory, resonance is possible and that these linearly stable flows may exhibit explosive instabilities. We show that this phenomenon may occur also when there is only approximate resonance, which is more likely in nature. Furthermore, the size of the perturbation that is required to trigger the instability is shown in some circumstances to be consistent with the size of naturally occurring perturbations. Finally, we consider the differences between the present case examined and the more idealized case of Shrira et a/. [ 1997]. It is shown that there is a possibility of coupling between triads, due to the richer modal structure in more realistic flows, which may act to stabilize the flow and act against the development of subcritical bifurcations. Extensive numerical tests are called for.

A Smartphone-Based Prototype System for Incident/Work Zone Management Driven by Crowd-Sourced Data, 2015

This project develops a smartphone-based prototype system that supplements the 511 system to improve its dynamic traffic routing service to state highway users under non-recurrent congestion. This system will save considerable time to provide crucial traffic information and en-route assistance to travelers for them to avoid being trapped in traffic congestion due to accidents, work zones, hazards, or special events. It also creates a feedback loop between travelers and responsible agencies that enable the state to effectively collect, fuse, and analyze crowd-sourced data for next-gen transportation planning and management. This project can result in substantial economic savings (e.g. less traffic congestion, reduced fuel wastage and emissions) and safety benefits for the freight industry and society due to better dissemination of real-time traffic information by highway users. Such benefits will increase significantly in future with the expected increase in freight traffic on the network. The proposed system also has the flexibility to be integrated with various transportation management modules to assist state agencies to improve transportation services and daily operations.

GUS gene expression driven by a citrus promoter in transgenic tobacco and 'Valencia' sweet orange

The objective of this work was the transformation of tobacco and 'Valencia' sweet orange with the GUS gene driven by the citrus phenylalanine ammonia-lyase (PAL) gene promoter (CsPP). Transformation was accomplished by co-cultivation of tobacco and 'Valência' sweet orange explants with Agrobacterium tumefaciens containing the binary vector CsPP-GUS/2201. After plant transformation and regeneration, histochemical analyses using GUS staining revealed that CsPP promoter preferentially, but not exclusively, conferred gene expression in xylem tissues of tobacco. Weaker GUS staining was also detected throughout the petiole region in tobacco and citrus CsPP transgenic plants.

Gravity-driven slug motion in capillary tubes

The velocity of a liquid slug falling in a capillary tube is lower than predicted for Poiseuille flow due to presence of menisci, whose shapes are determined by the complex interplay of capillary, viscous, and gravitational forces. Due to the presence of menisci, a capillary pressure proportional to surface curvature acts on the slug and streamlines are bent close to the interface, resulting in enhanced viscous dissipation at the wedges. To determine the origin of drag-force increase relative to Poiseuille flow, we compute the force resultant acting on the slug by integrating Navier-Stokes equations over the liquid volume. Invoking relationships from differential geometry we demonstrate that the additional drag is due to viscous forces only and that no capillary drag of hydrodynamic origin exists (i.e., due to hydrodynamic deformation of the interface). Requiring that the force resultant is zero, we derive scaling laws for the steady velocity in the limit of small capillary numbers by estimating the leading order viscous dissipation in the different regions of the slug (i.e., the unperturbed Poiseuille-like bulk, the static menisci close to the tube axis and the dynamic regions close to the contact lines). Considering both partial and complete wetting, we find that the relationship between dimensionless velocity and weight is, in general, nonlinear. Whereas the relationship obtained for complete-wetting conditions is found in agreement with the experimental data of Bico and Quere [J. Bico and D. Quere, J. Colloid Interface Sci. 243, 262 (2001)], the scaling law under partial-wetting conditions is validated by numerical simulations performed with the Volume of Fluid method. The simulated steady velocities agree with the behavior predicted by the theoretical scaling laws in presence and in absence of static contact angle hysteresis. The numerical simulations suggest that wedge-flow dissipation alone cannot account for the entire additional drag and that the non-Poiseuille dissipation in the static menisci (not considered in previous studies) has to be considered for large contact angles.

Targeting IL-1β and IL-17A driven inflammation during influenza-induced exacerbations of chronic lung inflammation.

For patients with chronic lung diseases, such as chronic obstructive pulmonary disease (COPD), exacerbations are life-threatening events causing acute respiratory distress that can even lead to hospitalization and death. Although a great deal of effort has been put into research of exacerbations and potential treatment options, the exact underlying mechanisms are yet to be deciphered and no therapy that effectively targets the excessive inflammation is available. In this study, we report that interleukin-1β (IL-1β) and interleukin-17A (IL-17A) are key mediators of neutrophilic inflammation in influenza-induced exacerbations of chronic lung inflammation. Using a mouse model of disease, our data shows a role for IL-1β in mediating lung dysfunction, and in driving neutrophilic inflammation during the whole phase of viral infection. We further report a role for IL-17A as a mediator of IL-1β induced neutrophilia at early time points during influenza-induced exacerbations. Blocking of IL-17A or IL-1 resulted in a significant abrogation of neutrophil recruitment to the airways in the initial phase of infection or at the peak of viral replication, respectively. Therefore, IL-17A and IL-1β are potential targets for therapeutic treatment of viral exacerbations of chronic lung inflammation.

Genetic bottlenecks driven by population disconnection.

Connectivity among populations plays a crucial role in maintaining genetic variation at a local scale, especially in small populations affected strongly by genetic drift. The negative consequences of population disconnection on allelic richness and gene diversity (heterozygosity) are well recognized and empirically established. It is not well recognized, however, that a sudden drop in local effective population size induced by such disconnection produces a temporary disequilibrium in allelic frequency distributions that is akin to the genetic signature of a demographic bottleneck. To document this effect, we used individual-based simulations and empirical data on allelic richness and gene diversity in six pairs of isolated versus well-connected (core) populations of European tree frogs. In our simulations, population disconnection depressed allelic richness more than heterozygosity and thus resulted in a temporary excess in gene diversity relative to mutation drift equilibrium (i.e., signature of a genetic bottleneck). We observed a similar excess in gene diversity in isolated populations of tree frogs. Our results show that population disconnection can create a genetic bottleneck in the absence of demographic collapse.

Avalanche-like vortex penetration driven by pulsed microwave fields in an epitaxial LaSrCuO thin film

Different vortex penetration regimes have been registered in the output voltage signal of a magnetometer when single microwave pulses are applied to an epitaxial overdoped La2− x Sr x CuO4 thin film in a perpendicular dc magnetic field. The onset of a significant variation in the sample magnetization which exists below threshold values of temperature, dc magnetic field, and pulse duration is interpreted as an avalanche-type flux penetration. The microwave contribution to the background electric field suggests that the nucleation of this fast vortex motion is of electric origin, which also guarantees the occurrence of vortex instabilities under adiabatic conditions via the enhancement of the flux flow resistivity. Flux creep phenomena and heat transfer effects act as stabilizing factors against the microwave-pulse-induced fast flux diffusion.

Knowledge Licensing in a Model of R&D-driven Endogenous Growth

In this paper I present an endogenous growth model where the engine of growth is in-house R&D performed by high-tech firms. I model knowledge (patent) licensing among high-tech firms. I show that if there is knowledge licensing, high-tech firms innovate more and economic growth is higher than in cases when there are knowledge spillovers or there is no exchange of knowledge among high-tech firms. However, in case when there is knowledge licensing the number of high-tech firms is lower than in cases when there are knowledge spillovers or there is no exchange of knowledge.

Asymmetric stochastic switching driven by intrinsic molecular noise

Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.

Knowledge Licensing in a Model of R&D-driven Endogenous Growth

In this paper I present an endogenous growth model where the engine of growth is in-house R&D performed by high-tech firms. I model knowledge (patent) licensing among high-tech firms. I show that if there is knowledge licensing, high-tech firms innovate more and economic growth is higher than in cases when there are knowledge spillovers or there is no exchange of knowledge among high-tech firms. However, in case when there is knowledge licensing the number of high-tech firms is lower than in cases when there are knowledge spillovers or there is no exchange of knowledge.

Genetic transformation of sweet oranges with the D4E1 gene driven by the AtPP2 promoter

The objective of this work was to produce transgenic 'Pêra' and 'Valência' sweet orange plants using the D4E1 gene driven by the Arabidopsis thaliana phloem protein (AtPP2) promoter and to quantify transgene expression in different transformation events. Genetic transformation experiments were carried out with epicotyl segments co‑cultivated with Agrobacterium tumefaciens. Six plants from 'Pêra' sweet orange and seven plants from 'Valência' sweet orange were confirmed as different transgenic events by means of the polymerase chain reaction (PCR) and the Southern blot techniques. Transgene expression was quantified using real‑time quantitative PCR. D4E1 gene expression levels vary from 5 up to 50 times among different transformation events.

On the transcriptional role of NLRC5 and the function of NLRC5-driven MHC class I expression in the immune system

Major histocompatibility complex (MHC) molecules are of crucial importance for the immune system to recognize and defend the body against external attacks. Foreign antigens are presented by specialized cells, called antigen presenting cells, to T lymphocytes in the context of MHC molecules, thereby inducing T cell activation. In addition, MHC molecules are essential for Natural Killer (NK) cell biology, playing a role in NK cell education and activation. Recently, the NOD-like receptor (NLR) family member NLRC5 (NLR caspase recruitment domain containing protein 5) was found to act as transcriptional regulator of MHC class I, in particular in T and NK cells. Its role in MHC class I expression is however minor in dendritic cells (DCs). This raised the question of whether inflammatory conditions, which augment the levels of NLRC5 in DCs, could increase its contribution to MHC class I expression. Our work shows that MHC class I transcript and intracellular levels depend on NLRC5, while its role in MHC class I surface expression is instead negligible. We describe however a general salvage mechanism that enables cells with low intracellular MHC class I levels to nevertheless maintain relatively high MHC class I on the cell surface. In addition, we lack a thorough understanding of NLRC5 target gene specificity and mechanism of action. Our work delineates the unique consensus sequence in MHC class I promoters required for NLRC5 recruitment and pinpoints conserved features conferring its specificity. Furthermore, through genome-wide analyses, we confirm that NLRC5 regulates classical MHC class I genes and identify novel target genes all encoding non-classical MHC class I molecules exerting an array of functions in immunity and tolerance. We finally asked why a dedicated factor co-regulates MHC class I expression specifically in T and NK lymphocytes. We show that deregulated NLRC5 expression affects the education of NK cells and alters the crosstalk between T and NK cells, leading to NK cell-mediated killing of T lymphocytes. Altogether this thesis work brings insights into molecular and physiological aspects of NLRC5 function, which might help understand certain aspects of immune responses and disorders. -- Les molécules du complexe majeur d'histocompatibilité (CMH) sont essentielles au système immunitaire pour l'initiation de la réponse immunitaire. En effet, l'activation des lymphocytes T nécessite la reconnaissance d'un antigène étranger présenté par les cellules présentatrices d'antigènes sur une molécule du CMH. Les molécules du CMH ont également un rôle fondamental pour la fonction des cellules Natural Killer (NK) puisqu'elles sont nécessaires à leur processus d'éducation et d'activation. Récemment, NLRC5 (NLR caspase recruitment domain containing protein 5), un membre de la famille des récepteurs de type NOD (NLRs), a été décrit comme un facteur de transactivation de l'expression des gènes du CMH de classe I. A l'état basai, cette fonction transcriptionnelle est essentielle dans les lymphocytes T et NK, alors que ce rôle reste mineur pour l'expression des molécules du CMH de classe I dans les cellules dendritiques (DCs). Dans des conditions inflammatoires, l'expression de NLRC5 augmente dans les DCs. Notre travail démontre que, dans ces conditions, les transcrits et les niveaux intracellulaires des molécules du CMH de classe I augmentent aussi d'une façon dépendante de NLRC5. A contrario, le rôle de NLRC5 sur les niveaux de molécules de surface reste minoritaire. Cette observation nous a conduits à l'identification d'un mécanisme général de compensation qui permet aux cellules de maintenir des niveaux relativement élevés de molécules de CMH de class I à leur surface malgré de faibles niveaux intracellulaires. De plus, il semblait nécessaire de s'orienter vers une approche plus globale afin de déterminer l'étendue de la fonction transcriptionnelle de NLRC5. Par une approche du génome entier, nous avons pu décrire une séquence consensus conservée présente dans les promoteurs des gènes du CMH de classe I, sur laquelle NLRC5 est spécifiquement recruté. Nous avons pu également identifier de nouveaux gènes cibles codant pour des molécules de CMH de classe I non classiques impliqués dans l'immunité et la tolérance. Finalement, nous nous sommes demandé quel est l'intérêt d'avoir un facteur transcriptionnel, en l'occurrence NLRC5, qui orchestre l'expression du CMH de classe I dans les lymphocytes T et NK. Nous montrons que la dérégulation de l'expression de NLRC5 affecte l'éducation des cellules NK et conduit à la mort cellulaire des lymphocytes T médiée par les cellules NK. Dans l'ensemble ce travail de thèse contribue à la caractérisation du rôle de NLRC5, tant au niveau moléculaire que physiologique, ce qui présente un intérêt dans le cadre de la compréhension de certains aspects physiopathologique de la réponse immunitaire.

Emergence of oriented circuits driven by synaptic pruning associated with spike-timing-dependent plasticity (STDP)

ABSTRACT: Massive synaptic pruning following over-growth is a general feature of mammalian brain maturation. Pruning starts near time of birth and is completed by time of sexual maturation. Trigger signals able to induce synaptic pruning could be related to dynamic functions that depend on the timing of action potentials. Spike-timing-dependent synaptic plasticity (STDP) is a change in the synaptic strength based on the ordering of pre- and postsynaptic spikes. The relation between synaptic efficacy and synaptic pruning suggests that the weak synapses may be modified and removed through competitive "learning" rules. This plasticity rule might produce the strengthening of the connections among neurons that belong to cell assemblies characterized by recurrent patterns of firing. Conversely, the connections that are not recurrently activated might decrease in efficiency and eventually be eliminated. The main goal of our study is to determine whether or not, and under which conditions, such cell assemblies may emerge out of a locally connected random network of integrate-and-fire units distributed on a 2D lattice receiving background noise and content-related input organized in both temporal and spatial dimensions. The originality of our study stands on the relatively large size of the network, 10,000 units, the duration of the experiment, 10E6 time units (one time unit corresponding to the duration of a spike), and the application of an original bio-inspired STDP modification rule compatible with hardware implementation. A first batch of experiments was performed to test that the randomly generated connectivity and the STDP-driven pruning did not show any spurious bias in absence of stimulation. Among other things, a scale factor was approximated to compensate for the network size on the ac¬tivity. Networks were then stimulated with the spatiotemporal patterns. The analysis of the connections remaining at the end of the simulations, as well as the analysis of the time series resulting from the interconnected units activity, suggest that feed-forward circuits emerge from the initially randomly connected networks by pruning. RESUME: L'élagage massif des synapses après une croissance excessive est une phase normale de la ma¬turation du cerveau des mammifères. L'élagage commence peu avant la naissance et est complété avant l'âge de la maturité sexuelle. Les facteurs déclenchants capables d'induire l'élagage des synapses pourraient être liés à des processus dynamiques qui dépendent de la temporalité rela¬tive des potentiels d'actions. La plasticité synaptique à modulation temporelle relative (STDP) correspond à un changement de la force synaptique basé sur l'ordre des décharges pré- et post- synaptiques. La relation entre l'efficacité synaptique et l'élagage des synapses suggère que les synapses les plus faibles pourraient être modifiées et retirées au moyen d'une règle "d'appren¬tissage" faisant intervenir une compétition. Cette règle de plasticité pourrait produire le ren¬forcement des connexions parmi les neurones qui appartiennent à une assemblée de cellules caractérisée par des motifs de décharge récurrents. A l'inverse, les connexions qui ne sont pas activées de façon récurrente pourraient voir leur efficacité diminuée et être finalement éliminées. Le but principal de notre travail est de déterminer s'il serait possible, et dans quelles conditions, que de telles assemblées de cellules émergent d'un réseau d'unités integrate-and¬-fire connectées aléatoirement et distribuées à la surface d'une grille bidimensionnelle recevant à la fois du bruit et des entrées organisées dans les dimensions temporelle et spatiale. L'originalité de notre étude tient dans la taille relativement grande du réseau, 10'000 unités, dans la durée des simulations, 1 million d'unités de temps (une unité de temps correspondant à une milliseconde), et dans l'utilisation d'une règle STDP originale compatible avec une implémentation matérielle. Une première série d'expériences a été effectuée pour tester que la connectivité produite aléatoirement et que l'élagage dirigé par STDP ne produisaient pas de biais en absence de stimu¬lation extérieure. Entre autres choses, un facteur d'échelle a pu être approximé pour compenser l'effet de la variation de la taille du réseau sur son activité. Les réseaux ont ensuite été stimulés avec des motifs spatiotemporels. L'analyse des connexions se maintenant à la fin des simulations, ainsi que l'analyse des séries temporelles résultantes de l'activité des neurones, suggèrent que des circuits feed-forward émergent par l'élagage des réseaux initialement connectés au hasard.