Nonlinear model predictive control of a passenger vehicle for automated lane changes

This article presents a nonlinear Model Predictive Control (MPC) for lane changes, based on a simplified Single Track Model (STM) of the vehicle. The STM includes the position of the vehicle in global coordinates as a state so that the position of the target lane can be specified to the MPC for reference tracking. Moreover, a constraint for maintaining a safety distance with the vehicles in the target lane is included. Simulation results show the effectiveness of the MPC in scenarios with different initial conditions that demonstrate the correct implementation of the safety distance constraint

A wide family of singularity-free cosmological models

In this paper a family of non-singular cylindrical perfect fluid cosmologies is derived. The equation of state corresponds to a stiff fluid. The family depends on two independent functions under very simple conditions. A sufficient condition for geodesic completeness is provided.Comment: 7 pages, RevTeX

Complexity and white-dwarf structure

From the low-mass non-relativistic case to the relativistic limit, the density profile of a white dwarf is used to evaluate the complexity measure. Similarly to the recently reported atomic case where, by averaging shell effects, complexity grows with the atomic number, here complexity grows as a function of the star mass reaching a maximum finite value in the Chandrasekhar limit.Comment: 9 pages and 4 figure

Conflicts treatment for ubiquitous collective and context-aware applications

Context-aware computing is a research field that defines systems capable of adapting their behavior according to any relevant information about entities (e.g., people, places and objects) of interest. The ubiquitous computing is closely related to the use of contexts, since it aims to provide personalized, transparent and on-demand services. Ubiquitous systems are frequently shared among multiple users, which may lead to conflicts that occur during adaptation actions due to individual profiles divergences and/or environment resources incompatibility. In such situations it is interesting to detect and solve those conflicts, considering what is better for the group but also being fair enough with each individual demand, whenever possible. This work presents the important concepts on the collective ubiquitous context-aware applications field. Furthermore, it proposes a novel methodology for conflicts detection and resolution that considers the trade-off between quality of services and resources consumption. A case study based on a collective tourist guide was implemented as a proof-of-study to the proposed methodology.Key words: context and awareness in collaborative systems, ubiquitous computing, adaptive collaborative environments

Electrochemical oxidation of dibenzothiophene compounds on BDD electrode in acetonitrile-water medium

The electrochemical oxidation of dibenzothiophene and two derivatives, namely 4-methyldibenzothiophene and 4,6-dimethyldibenzothiophene, was investigated either separately or as a mixture, on a BDD anode in a miscible acetonitrile (87.5% v/v)-water (12.5% v/v, 0.01 M NaNO3) solution. Linear sweep voltammetry, cyclic voltammetry, chronoamperometry and bulk electrolysis under potentiostatic conditions suggested the probable occurrence of two pathways: direct electrochemical oxidation and indirect reaction with hydroxyl radicals and other reactive oxygen species formed at the BDD anode surface during water discharge. The products extracted upon electrolysis at 1.5 and 2.0 V vs. SCE were analyzed by Fourier-transform infrared spectroscopy, gas chromatography-mass spectrometry and ultra-high performance liquid chromatography coupled to electrospray ionization and quadrupole time-of-flight mass spectrometry (UHPLC-ESI-Q-TOF-MS). The main molecules identified were the corresponding sulfoxides or sulfones, depending on the applied anodic potential. Possible oxidation routes for the dibenzothiophene compounds are proposed

Effects of an exercise program on brain health outcomes for children with overweight or obesity

Importance Pediatric overweight and obesity are highly prevalent across the world, with implications for poorer cognitive and brain health. Exercise might potentially attenuate these adverse consequences. Objectives To investigate the effects of an exercise program on brain health indicators, including intelligence, executive function, academic performance, and brain outcomes, among children with overweight or obesity and to explore potential mediators and moderators of the main effects of exercise. Design, Setting, and Participants All preexercise and postexercise data for this 20-week randomized clinical trial of 109 children aged 8 to 11 years with overweight or obesity were collected from November 21, 2014, to June 30, 2016, with neuroimaging data processing and analyses conducted between June 1, 2017, and December 20, 2021. All 109 children were included in the intention-to-treat analyses; 90 children (82.6%) completed the postexercise evaluation and attended 70% or more of the recommended exercise sessions and were included in per-protocol analyses. Interventions All participants received lifestyle recommendations. The control group continued their usual routines, whereas the exercise group attended a minimum of 3 supervised 90-minute sessions per week in an out-of-school setting. Main Outcomes and Measures Intelligence, executive function (cognitive flexibility, inhibition, and working memory), and academic performance were assessed with standardized tests, and hippocampal volume was measured with magnetic resonance imaging. Results The 109 participants included 45 girls (41.3%); participants had a mean (SD) body mass index of 26.8 (3.6) and a mean (SD) age of 10.0 (1.1) years at baseline. In per-protocol analyses, the exercise intervention improved crystallized intelligence, with the exercise group improving from before exercise to after exercise (mean z score, 0.62 [95% CI, 0.44-0.80]) compared with the control group (mean z score, –0.10 [95% CI, –0.28 to 0.09]; difference between groups, 0.72 SDs [95% CI, 0.46-0.97]; P < .001). Total intelligence also improved significantly more in the exercise group (mean z score, 0.69 [95% CI, 0.48-0.89]) than in the control group (mean z score, 0.07 [95% CI, –0.14 to 0.28]; difference between groups, 0.62 SDs [95% CI, 0.31-0.91]; P < .001). Exercise also positively affected a composite score of cognitive flexibility (mean z score: exercise group, 0.25 [95% CI, 0.05-0.44]; control group, –0.17 [95% CI, –0.39 to 0.04]; difference between groups, 0.42 SDs [95% CI, 0.13-0.71]; P = .005). These main effects were consistent in intention-to-treat analyses and after multiple-testing correction. There was a positive, small-magnitude effect of exercise on total academic performance (mean z score: exercise group, 0.31 [95% CI, 0.18-0.44]; control group, 0.10 [95% CI, –0.04 to 0.24]; difference between groups, 0.21 SDs [95% CI, 0.01-0.40]; P = .03), which was partially mediated by cognitive flexibility. Inhibition, working memory, hippocampal volume, and other brain magnetic resonance imaging outcomes studied were not affected by the exercise program. The intervention increased cardiorespiratory fitness performance as indicated by longer treadmill time to exhaustion (mean z score: exercise group, 0.54 [95% CI, 0.27-0.82]; control group, 0.13 [95% CI, –0.16 to 0.41]; difference between groups, 0.42 SDs [95% CI, 0.01-0.82]; P = .04), and these changes in fitness mediated some of the effects (small percentage of mediation [approximately 10%-20%]). The effects of exercise were overall consistent across the moderators tested, except for larger improvements in intelligence among boys compared with girls. Conclusions and Relevance In this randomized clinical trial, exercise positively affected intelligence and cognitive flexibility during development among children with overweight or obesity. However, the structural and functional brain changes responsible for these improvements were not identified

Modeling the Subsurface Structure of Sunspots

While sunspots are easily observed at the solar surface, determining their subsurface structure is not trivial. There are two main hypotheses for the subsurface structure of sunspots: the monolithic model and the cluster model. Local helioseismology is the only means by which we can investigate subphotospheric structure. However, as current linear inversion techniques do not yet allow helioseismology to probe the internal structure with sufficient confidence to distinguish between the monolith and cluster models, the development of physically realistic sunspot models are a priority for helioseismologists. This is because they are not only important indicators of the variety of physical effects that may influence helioseismic inferences in active regions, but they also enable detailed assessments of the validity of helioseismic interpretations through numerical forward modeling. In this paper, we provide a critical review of the existing sunspot models and an overview of numerical methods employed to model wave propagation through model sunspots. We then carry out an helioseismic analysis of the sunspot in Active Region 9787 and address the serious inconsistencies uncovered by \citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find that this sunspot is most probably associated with a shallow, positive wave-speed perturbation (unlike the traditional two-layer model) and that travel-time measurements are consistent with a horizontal outflow in the surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic

Genetic variants in anti-Müllerian hormone-related genes and breast cancer risk: results from the AMBER consortium

Purpose: Circulating anti-Müllerian hormone (AMH) levels are positively associated with time to menopause and breast cancer risk. We examined breast cancer associations with single nucleotide polymorphisms (SNPs) in the AMH gene or its receptor genes, ACVR1 and AMHR2, among African American women. Methods: In the AMBER consortium, we tested 65 candidate SNPs, and 1130 total variants, in or near AMH, ACVR1, and AMHR2 and breast cancer risk. Overall, 3649 cases and 4230 controls contributed to analyses. Odds ratios (OR) and 95% confidence intervals (CI) for breast cancer were calculated using multivariable logistic regression. Results: After correction for multiple comparisons (false-discovery rate of 5%), there were no statistically significant associations with breast cancer risk. Without correction for multiple testing, four candidate SNPs in ACVR1 and one near AMH were associated with breast cancer risk. In ACVR1, rs13395576[C] was associated with lower breast cancer risk overall (OR 0.84; 95% CI 0.72, 0.97) and for ER+ disease (OR 0.75; CI 0.62, 0.89) (p < 0.05). Rs1220110[A] and rs1220134[T] each had ORs of 0.89–0.90 for postmenopausal and ER+ breast cancer (p ≤ 0.03). Conversely, rs1682130[T] was associated with higher risk of ER+ breast cancer (OR 1.17; 95% CI 1.04, 1.32). Near AMH, rs6510652[T] had ORs of 0.85–0.90 for breast cancer overall and after menopause (p ≤ 0.02). Conclusions: The present results, from a large study of African American women, provide limited support for an association between AMH-related polymorphisms and breast cancer risk and require replication in other studies