The influence of collimation on the appearance of relativistic jets

The question of the collimation of relativistic jets is the subject of a lively debate in the community. We numerically compute the apparent velocity and the Doppler factor of a non homokinetic jet using different velocity profile, to study the effect of collimation on the appearance of relativistic jets (apparent velocity and Doppler factor). We argue that if the motion is relativistic, the high superluminal velocities are possible only if the geometrical collimation is smaller than the relativistic beaming angle $\gamma^{-1}$. In the opposite case, the apparent image will be dominated by the part of the jet traveling directly towards the observer resulting in a smaller apparent velocity. Furthermore, getting rid of the homokinetic hypothesis yields a complex relation between the observing angle and the Doppler factor, resulting in important consequences for the numerical computation of AGN population and unification scheme model.Comment: 4 pages, 4 figures. To appear in Proceedings of IAU Symposium 275 "Jets at all Scales", 13-17 September 2010, Buenos Aires, Argentin

A parameterized approximation scheme for the 2D-Knapsack problem with wide items

We study a natural geometric variant of the classic Knapsack problem called 2D-Knapsack: we are given a set of axis-parallel rectangles and a rectangular bounding box, and the goal is to pack as many of these rectangles inside the box without overlap. Naturally, this problem is NP-complete. Recently, Grandoni et al. [ESA'19] showed that it is also W[1]-hard when parameterized by the size $k$ of the sought packing, and they presented a parameterized approximation scheme (PAS) for the variant where we are allowed to rotate the rectangles by 90{\textdegree} before packing them into the box. Obtaining a PAS for the original 2D-Knapsack problem, without rotation, appears to be a challenging open question. In this work, we make progress towards this goal by showing a PAS under the following assumptions: - both the box and all the input rectangles have integral, polynomially bounded sidelengths; - every input rectangle is wide -- its width is greater than its height; and - the aspect ratio of the box is bounded by a constant.Our approximation scheme relies on a mix of various parameterized and approximation techniques, including color coding, rounding, and searching for a structured near-optimum packing using dynamic programming

Synthetic Aperture Radar Image Segmentation with Quantum Annealing

In image processing, image segmentation is the process of partitioning a digital image into multiple image segment. Among state-of-the-art methods, Markov Random Fields (MRF) can be used to model dependencies between pixels, and achieve a segmentation by minimizing an associated cost function. Currently, finding the optimal set of segments for a given image modeled as a MRF appears to be NP-hard. In this paper, we aim to take advantage of the exponential scalability of quantum computing to speed up the segmentation of Synthetic Aperture Radar images. For that purpose, we propose an hybrid quantum annealing classical optimization Expectation Maximization algorithm to obtain optimal sets of segments. After proposing suitable formulations, we discuss the performances and the scalability of our approach on the D-Wave quantum computer. We also propose a short study of optimal computation parameters to enlighten the limits and potential of the adiabatic quantum computation to solve large instances of combinatorial optimization problems.Comment: 13 pages, 6 figures, to be published in IET Radar, Sonar and Navigatio

Phase-coded Radar Waveform Design with Quantum Annealing

The Integrated Side Lobe Ratio (ISLR) problem we consider here consists in finding optimal sequences of phase shifts in order to minimize the mean squared cross-correlation side lobes of a transmitted radar signal and a mismatched replica. Currently, ISLR does not seem to be easier than the general polynomial unconstrained binary problem, which is NP-hard. In our work, we aim to take advantage of the exponential scalability of quantum computing to find new optima, by solving the ISLR problem on a quantum annealer. This quantum device is designed to solve quadratic optimization problems with binary variables (QUBO). After proposing suitable formulation for different instances of the ISLR, we discuss the performances and the scalability of our approach on the D-Wave quantum computer. More broadly, our work enlightens the limits and potential of the adiabatic quantum computation for the solving of large instances of combinatorial optimization problems.Comment: 11 pages, 4 figures, 1 table, to be published in IET Radar, Sonar and Navigatio

Self-consistent gyrokinetic modelling of turbulent and neoclassical tungsten transport in toroidally rotating plasmas

The effect of toroidal rotation on both turbulent and neoclassical transport of tungsten (W) in tokamaks is investigated using the flux-driven, global, nonlinear 5D gyrokinetic code GYSELA. Nonlinear simulations are carried out with different levels of momentum injection that drive W to the supersonic regime, while the toroidal velocity of the main ions remains in the subsonic regime. The numerical simulations demonstrate that toroidal rotation induces centrifugal forces that cause W to accumulate in the outboard region, generating an in-out poloidal asymmetry. This asymmetry enhances neoclassical inward convection, which can lead to central accumulation of W in cases of strong plasma rotation. The core accumulation of W is mainly driven by inward neoclassical convection. However, as momentum injection continues, roto-diffusion, proportional to the radial gradient of the toroidal velocity, becomes significant and generate outward turbulent flux in the case of ion temperature gradient (ITG) turbulence. Overall, the numerical results from nonlinear GYSELA simulations are in qualitative agreement with the theoretical predictions for impurity transport, as well as experimental observations.Comment: 26 pages, 10 figures, to be publishe

Oral Health in Women During Preconception and Pregnancy: Implications for Birth Outcomes and Infant Oral Health

The mouth is an obvious portal of entry to the body, and oral health reflects and influences general health and well being. Maternal oral health has significant implications for birth outcomes and infant oral health. Maternal periodontal disease, that is, a chronic infection of the gingiva and supporting tooth structures, has been associated with preterm birth, development of preeclampsia, and delivery of a small-for-gestational age infant. Maternal oral flora is transmitted to the newborn infant, and increased cariogenic flora in the mother predisposes the infant to the development of caries. It is intriguing to consider preconception, pregnancy, or intrapartum treatment of oral health conditions as a mechanism to improve women's oral and general health, pregnancy outcomes, and their children's dental health. However, given the relationship between oral health and general health, oral health care should be a goal in its own right for all individuals. Regardless of the potential for improved oral health to improve pregnancy outcomes, public policies that support comprehensive dental services for vulnerable women of childbearing age should be expanded so that their own oral and general health is safeguarded and their children's risk of caries is reduced. Oral health promotion should include education of women and their health care providers ways to prevent oral disease from occurring, and referral for dental services when disease is present

Social Media in Human Resource Management

With the emergence of social media platforms undeniably shaping our world, the integration of social media in Human Resources Management (HRM) practices has emerged as a significant area of interests for organizations in the past 10 years. Traditional methods of HRM such as advertisements in newspapers shifted to digital methods like online job boards. Social media platforms enhance more cost and time effective methods in all dimensions of HRM. Through a comprehensive review of literature and empirical analysis, insights are provided into the op-portunities and challenges associated with social media in HRM. The research delved into the impact of social media employed in the multiple facets of HRM and used an inductive approach and qualitative data analysis throughout. The empirical analysis is founded on archival research based on secondary sources in form of relevant publications in the time span of 10 years. The key results underscore that social media have a significant impact on many dimensions of HRM in-cluding recruitment, employee engagement, onboarding, and feedback. Moreover, it is reported that all dimensions of HRM are interconnected. Overall, social media allows for a streamline recruitment process, better communication and collaboration fostering a sense of community within the organization, not only employees but also former employee and employee candidates. However, it was emphasized the im-portance of addressing ethical considerations, privacy concerns, and the need for ongoing monitoring and adaptation when integrating social media into HRM practices. By navigating these challenges thought-fully, organizations can effectively use social media to drive organizational success

Peer's influence on the inhibition of an addictive behavior and role of the subthalamic nucleus

Addiction is a plague affecting countless people. Recent studies suggest a new therapy to fight it: Deep Brain Stimulation (DBS) of the Subthalamic Nucleus (STN). The activity of this structure is associated with improved inhibitory control, which makes it a promising target for DBS. The goals of this study are, on the one hand, to provide a better understanding of the STN and how it works within the basal ganglia; i.e. group of nuclei that play a role in both the execution and inhibition of a given behaviour. On the other hand, to investigate socio-emotional factors that improve inhibition in a population with a casual-drinking behaviour. The study aims to establish, using fMRI, how these factors modulate the structures and networks underlying inhibition, and whether the STN is involved in this process..