MPC-Based Haptic Shared Steering System: A Driver Modeling Approach for Symbiotic Driving

Advanced Driver Assistance Systems (ADAS) aim to increase safety and reduce mental workload. However, the gap in the understanding of the closed-loop driver-vehicle interaction often leads to reduced user acceptance. In this study, an optimal torque control law is calculated online in the Model Predictive Control (MPC) framework to guarantee continuous guidance during the steering task. The research contribution is in the integration of an extensive prediction model covering cognitive behaviour, neuromuscular dynamics, and the vehicle- steering dynamics, within the MPC-based haptic controller to enhance collaboration. The driver model is composed of a preview cognitive strategy based on a Linear-Quadratic-Gaussian, sensory organs, and neuromuscular dynamics, including muscle co-activation and reflex action. Moreover, an adaptive cost-function algorithm enables dynamic allocation of the control authority. Experiments were performed in a fixed-base driving simulator at Toyota Motor Europe involving 19 participants to evaluate the proposed controller with two different cost functions against a commercial Lane Keeping Assist (LKA) system as an industry benchmark. The results demonstrate the proposed controller fosters symbiotic driving and reduces driver-vehicle conflicts with respect to a state-of-the-art commercial system, both subjectively and objectively, while still improving path-tracking performance. Summarising, this study tackles the need to blend human and ADAS control, demonstrating the validity of the proposed strategy

MPC-Based Haptic Shared Steering System: A Driver Modeling Approach for Symbiotic Driving

Advanced Driver Assistance Systems (ADAS) aim to increase safety and reduce mental workload. However, the gap in the understanding of the closed-loop driver-vehicle interaction often leads to reduced user acceptance. In this study, an optimal torque control law is calculated online in the Model Predictive Control (MPC) framework to guarantee continuous guidance during the steering task. The research contribution is in the integration of an extensive prediction model covering cognitive behaviour, neuromuscular dynamics, and the vehicle- steering dynamics, within the MPC-based haptic controller to enhance collaboration. The driver model is composed of a preview cognitive strategy based on a Linear-Quadratic-Gaussian, sensory organs, and neuromuscular dynamics, including muscle co-activation and reflex action. Moreover, an adaptive cost-function algorithm enables dynamic allocation of the control authority. Experiments were performed in a fixed-base driving simulator at Toyota Motor Europe involving 19 participants to evaluate the proposed controller with two different cost functions against a commercial Lane Keeping Assist (LKA) system as an industry benchmark. The results demonstrate the proposed controller fosters symbiotic driving and reduces driver-vehicle conflicts with respect to a state-of-the-art commercial system, both subjectively and objectively, while still improving path-tracking performance. Summarising, this study tackles the need to blend human and ADAS control, demonstrating the validity of the proposed strategy

Debris Disks: Probing Planet Formation

Debris disks are the dust disks found around ~20% of nearby main sequence stars in far-IR surveys. They can be considered as descendants of protoplanetary disks or components of planetary systems, providing valuable information on circumstellar disk evolution and the outcome of planet formation. The debris disk population can be explained by the steady collisional erosion of planetesimal belts; population models constrain where (10-100au) and in what quantity (>1Mearth) planetesimals (>10km in size) typically form in protoplanetary disks. Gas is now seen long into the debris disk phase. Some of this is secondary implying planetesimals have a Solar System comet-like composition, but some systems may retain primordial gas. Ongoing planet formation processes are invoked for some debris disks, such as the continued growth of dwarf planets in an unstirred disk, or the growth of terrestrial planets through giant impacts. Planets imprint structure on debris disks in many ways; images of gaps, clumps, warps, eccentricities and other disk asymmetries, are readily explained by planets at >>5au. Hot dust in the region planets are commonly found (<5au) is seen for a growing number of stars. This dust usually originates in an outer belt (e.g., from exocomets), although an asteroid belt or recent collision is sometimes inferred.Comment: Invited review, accepted for publication in the 'Handbook of Exoplanets', eds. H.J. Deeg and J.A. Belmonte, Springer (2018

Association of MC1R Variants and host phenotypes with melanoma risk in CDKN2A mutation carriers: a GenoMEL study

&lt;p&gt;&lt;b&gt;Background&lt;/b&gt; Carrying the cyclin-dependent kinase inhibitor 2A (CDKN2A) germline mutations is associated with a high risk for melanoma. Penetrance of CDKN2A mutations is modified by pigmentation characteristics, nevus phenotypes, and some variants of the melanocortin-1 receptor gene (MC1R), which is known to have a role in the pigmentation process. However, investigation of the associations of both MC1R variants and host phenotypes with melanoma risk has been limited.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Methods&lt;/b&gt; We included 815 CDKN2A mutation carriers (473 affected, and 342 unaffected, with melanoma) from 186 families from 15 centers in Europe, North America, and Australia who participated in the Melanoma Genetics Consortium. In this family-based study, we assessed the associations of the four most frequent MC1R variants (V60L, V92M, R151C, and R160W) and the number of variants (1, &#8805;2 variants), alone or jointly with the host phenotypes (hair color, propensity to sunburn, and number of nevi), with melanoma risk in CDKN2A mutation carriers. These associations were estimated and tested using generalized estimating equations. All statistical tests were two-sided.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Results&lt;/b&gt; Carrying any one of the four most frequent MC1R variants (V60L, V92M, R151C, R160W) in CDKN2A mutation carriers was associated with a statistically significantly increased risk for melanoma across all continents (1.24 × 10−6 &#8804; P &#8804; .0007). A consistent pattern of increase in melanoma risk was also associated with increase in number of MC1R variants. The risk of melanoma associated with at least two MC1R variants was 2.6-fold higher than the risk associated with only one variant (odds ratio = 5.83 [95% confidence interval = 3.60 to 9.46] vs 2.25 [95% confidence interval = 1.44 to 3.52]; Ptrend = 1.86 × 10−8). The joint analysis of MC1R variants and host phenotypes showed statistically significant associations of melanoma risk, together with MC1R variants (.0001 &#8804; P &#8804; .04), hair color (.006 &#8804; P &#8804; .06), and number of nevi (6.9 × 10−6 &#8804; P &#8804; .02).&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusion&lt;/b&gt; Results show that MC1R variants, hair color, and number of nevi were jointly associated with melanoma risk in CDKN2A mutation carriers. This joint association may have important consequences for risk assessments in familial settings.&lt;/p&gt

Importance of TLR2 on Hepatic Immune and Non-Immune Cells to Attenuate the Strong Inflammatory Liver Response During Trypanosoma cruzi Acute Infection

Trypanosoma cruzi, an obligate intracellular protozoan, is the etiological agent of Chagas Disease that represents an important public health burden in Latin America. The infection with this parasite can lead to severe complications in cardiac, liver and gastrointestinal tissue depending on the strain of parasite and host genetics. Recently, we reported a fatal liver injury in T. cruzi infected B6 mice. However, the local immune response against this parasite is poorly understood. This work highlights some of the molecular and cellular mechanisms involved in liver pathology during the acute phase of infection. Using two mouse strains with different genetic backgrounds and responses to infection, B6 and BALB/c, we found that infected B6 mice develop a strong pro-inflammatory environment associated with high TLR9 expression. Conversely, infected BALB/c mice showed a more balanced inflammatory response in liver. Moreover, higher TLR2 and TLR4 expression were found only in hepatocytes from BALB/c. These data emphasize the importance of an adequate integration of signalling between immune and non-immune cells to define the outcome of infection. In addition, the pre-treatment with TLR2-agonist reverts the strong pro-inflammatory environment in T. cruzi infected B6 mice. These results could be useful in the understanding and design of novel immune strategies in controlling liver pathologies

A threshold level of NFATc1 activity facilitates thymocyte differentiation and opposes notch-driven leukaemia development.

International audienceNFATc1 plays a critical role in double-negative thymocyte survival and differentiation. However, the signals that regulate Nfatc1 expression are incompletely characterized. Here we show a developmental stage-specific differential expression pattern of Nfatc1 driven by the distal (P1) or proximal (P2) promoters in thymocytes. Whereas, preTCR-negative thymocytes exhibit only P2 promoter-derived Nfatc1beta expression, preTCR-positive thymocytes express both Nfatc1beta and P1 promoter-derived Nfatc1alpha transcripts. Inducing NFATc1alpha activity from P1 promoter in preTCR-negative thymocytes, in addition to the NFATc1beta from P2 promoter impairs thymocyte development resulting in severe T-cell lymphopenia. In addition, we show that NFATc1 activity suppresses the B-lineage potential of immature thymocytes, and consolidates their differentiation to T cells. Further, in the pTCR-positive DN3 cells, a threshold level of NFATc1 activity is vital in facilitating T-cell differentiation and to prevent Notch3-induced T-acute lymphoblastic leukaemia. Altogether, our results show NFATc1 activity is crucial in determining the T-cell fate of thymocytes

Hierarchical Bayesian level set inversion

The level set approach has proven widely successful in the study of inverse problems for inter- faces, since its systematic development in the 1990s. Re- cently it has been employed in the context of Bayesian inversion, allowing for the quantification of uncertainty within the reconstruction of interfaces. However the Bayesian approach is very sensitive to the length and amplitude scales in the prior probabilistic model. This paper demonstrates how the scale-sensitivity can be cir- cumvented by means of a hierarchical approach, using a single scalar parameter. Together with careful con- sideration of the development of algorithms which en- code probability measure equivalences as the hierar- chical parameter is varied, this leads to well-defined Gibbs based MCMC methods found by alternating Metropolis-Hastings updates of the level set function and the hierarchical parameter. These methods demon- strably outperform non-hierarchical Bayesian level set methods

Stoichiometric representation of geneproteinreaction associations leverages constraint-based analysis from reaction to gene-level phenotype prediction

Genome-scale metabolic reconstructions are currently available for hundreds of organisms. Constraint-based modeling enables the analysis of the phenotypic landscape of these organisms, predicting the response to genetic and environmental perturbations. However, since constraint-based models can only describe the metabolic phenotype at the reaction level, understanding the mechanistic link between genotype and phenotype is still hampered by the complexity of gene-protein-reaction associations. We implement a model transformation that enables constraint-based methods to be applied at the gene level by explicitly accounting for the individual fluxes of enzymes (and subunits) encoded by each gene. We show how this can be applied to different kinds of constraint-based analysis: flux distribution prediction, gene essentiality analysis, random flux sampling, elementary mode analysis, transcriptomics data integration, and rational strain design. In each case we demonstrate how this approach can lead to improved phenotype predictions and a deeper understanding of the genotype-to-phenotype link. In particular, we show that a large fraction of reaction-based designs obtained by current strain design methods are not actually feasible, and show how our approach allows using the same methods to obtain feasible gene-based designs. We also show, by extensive comparison with experimental 13C-flux data, how simple reformulations of different simulation methods with gene-wise objective functions result in improved prediction accuracy. The model transformation proposed in this work enables existing constraint-based methods to be used at the gene level without modification. This automatically leverages phenotype analysis from reaction to gene level, improving the biological insight that can be obtained from genome-scale models.DM was supported by the Portuguese Foundationfor Science and Technologythrough a post-doc fellowship (ref: SFRH/BPD/111519/ 2015). This study was supported by the PortugueseFoundationfor Science and Technology (FCT) under the scope of the strategic fundingof UID/BIO/04469/2013 unitand COMPETE2020 (POCI-01-0145-FEDER-006684) and BioTecNorte operation (NORTE-01-0145FEDER-000004) fundedby EuropeanRegional Development Fund under the scope of Norte2020Programa Operacional Regional do Norte. This project has received fundingfrom the European Union’s Horizon 2020 research and innovation programme under grant agreementNo 686070. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript