Explore the vast range of titles available.

Sujet souvent ignoré avant la crise du Covid, la question de la « souveraineté sanitaire » a été largement popularisée, au point de prendre une place centrale dans les débats publics lors de la campagne présidentielle 2022 : une prise de conscience salutaire aprés des années de régulation économique du médicament en France qui a poussé les entreprises pharmaceutiques a délocaliser. Désormais, la nécessité d'une autonomie stratégique est indiscutable, mais il reste â en définir les contours précis. Peut-on vraiment assurer une autonomie totale en termes de médicaments a l'échelle de notre seul pays ?

Object contour plays an important role in fields such as semantic segmentation and image classification. However, the extraction of contour is a difficult task, especially when the contour is incomplete or unclosed. In this paper, the existing contour detection approaches are reviewed and roughly divided into three categories: pixel-based, edge-based, and region-based. In addition, since the traditional contour detection approaches have achieved a high degree of sophistication, the deep convolutional neural networks (DCNNs) have good performance in image recognition, therefore, the DCNNs based contour detection approaches are also covered in this paper. Moreover, the future development of contour detection is analyzed and predicted.

The text is spare, and the visual narrative, in fluid line drawing with closed contours and the increasing introduction of colour, eloquently carry the idea.

Knowledge of the location and extent of agricultural fields is required for many applications, including agricultural statistics, environmental monitoring, and administrative policies. Furthermore, many mapping applications, such as object-based classification, crop type distinction, or large-scale yield prediction benefit significantly from the accurate delineation of fields. Still, most existing field maps and observation systems rely on historic administrative maps or labor-intensive field campaigns. These are often expensive to maintain and quickly become outdated, especially in regions of frequently changing agricultural patterns. However, exploiting openly available remote sensing imagery (e.g., from the European Union’s Copernicus programme) may allow for frequent and efficient field mapping with minimal human interaction. We present a new approach to extracting agricultural fields at the sub-pixel level. It consists of boundary detection and a field polygon extraction step based on a newly developed, modified version of the growing snakes active contours model we refer to as graph-based growing contours. This technique is capable of extracting complex networks of boundaries present in agricultural landscapes, and is largely automatic with little supervision required. The whole detection and extraction process is designed to work independently of sensor type, resolution, or wavelength. As a test case, we applied the method to two regions of interest in a study area in the northern Germany using multi-temporal Sentinel-2 imagery. Extracted fields were compared visually and quantitatively to ground reference data. The technique proved reliable in producing polygons closely matching reference data, both in terms of boundary location and statistical proxies such as median field size and total acreage.

We generalize ideas in the recent literature and develop new ones in order to propose a general class of contour integral methods for linear convection–diffusion PDEs and in particular for those arising in finance. These methods aim to provide a numerical approximation of the solution by computing its inverse Laplace transform. The choice of the integration contour is determined by the computation of a few suitably weighted pseudo-spectral level sets of the leading operator of the equation. Parabolic and hyperbolic profiles proposed in the literature are investigated and compared to the elliptic contour originally proposed by Guglielmi, López-Fernández and Nino 2020, see Guglielmi et al. (Math Comput 89:1161–1191, 2020). In summary, the article provides a comparison among three different integration profiles; proposes a new fast pseudospectral roaming method; optimizes the selection of time windows on which one may arbitrarily approximate the solution by no extra computational cost with respect to the case of a fixed time instant; focuses extensively on computational aspects and it is the reference of the MATLAB code [ 20 ], where all algorithms described here are implemented.

We revisit the Atiyah-Hitchin manifold using the generalized Legendre transform approach. Originally it is examined by Ivanov and Roček, and it has been further explored by Ionaș, with a particular focus on calculating the explicit forms of the Kähler potential and the Kähler metric. Notably, there exists a distinction between the former study and the latter. In the framework of the generalized Legendre transform approach, a Kähler potential is formulated through the contour integration of a specific function with holomorphic coordinates. It’s essential to note that the choice of the contour in the latter differs from that in the former. This discrepancy in contour selection may result in variations in both the Kähler potential and, consequently, the Kähler metric. Our findings demonstrate that the former exclusively yields the real Kähler potential, aligning with its defined properties. In contrast, the latter produces a complex Kähler potential. We present the derivation of the Kähler potential and metric for the Atiyah-Hitchin manifold in terms of holomorphic coordinates, considering the contour specified by Ivanov and Roček.

Five-axis linear commands are blended as the local smoothed toolpaths by inserting clothoid and airthoid splines at corners in five-axis CNC machining. The contour error is the bottleneck to achieve the precise dimension of the machined parts, when following the local smoothed toolpaths. This paper presents a contour error estimation and control method for the five-axis smoothed toolpaths with airthoid splines, according to the geometric characteristics of the toolpaths. The tool-tip contour error is analytically calculated based on the expression of the smoothed toolpaths. Consequently, the tool-orientation contour error is obtained by synchronizing the tool-orientation contour point with the tool-tip item based on the motion time through the designed time scale coefficient, when the toolpaths are scheduled by the time-synchronization scheme. Furthermore, a contour error compensation strategy is constructed to adaptively determine the compensator gain. It can be qualified to maximally eliminate the contour errors and steadily hold the control stability of the feed drives, in spite of the modeling error between the nominal and actual control models. The simulation and experiment results show that the estimation algorithm has higher accuracy than traditional methods, and the compensation strategy effectively eliminates the five-axis contour error.

The contours of the “social quality perspective” have recently been revised and developed by a team of scholars from Eastern and Western Europe. This began to take shape in 2016 and was extended in a working paper of the International Association of Social Quality with contributions from the Academy of Sciences of Ukraine (IASQ 2019: 48–56)—namely, Working Paper 17/b. The latter discussion became more important in response to the tragedy of the invasion of Ukraine by Russia in February 2022. This raised the urgency of the question of what the policy application of the social quality perspective means.

Unlike the real line, the real space ℝ d , for d ≥ 2, is not canonically ordered. As a consequence, such fundamental univariate concepts as quantile and distribution functions and their empirical counterparts, involving ranks and signs, do not canonically extend to the multivariate context. Palliating that lack of a canonical ordering has been an open problem for more than half a century, generating an abundant literature and motivating, among others, the development of statistical depth and copula-based methods. We show that, unlike the many definitions proposed in the literature, the measure transportation-based ranks and signs introduced in Chernozhukov, Galichon, Hallin and Henry (Ann. Statist. 45 (2017) 223–256) enjoy all the properties that make univariate ranks a successful tool for semiparametric inference. Related with those ranks, we propose a new center-outward definition of multivariate distribution and quantile functions, along with their empirical counterparts, for which we establish a Glivenko–Cantelli result. Our approach is based on McCann (Duke Math. J. 80 (1995) 309–323) and our results do not require any moment assumptions. The resulting ranks and signs are shown to be strictly distribution-free and essentially maximal ancillary in the sense of Basu (Sankhyā 21 (1959) 247–256) which, in semiparametric models involving noise with unspecified density, can be interpreted as a finite-sample form of semiparametric efficiency. Although constituting a sufficient summary of the sample, empirical center-outward distribution functions are defined at observed values only. A continuous extension to the entire d-dimensional space, yielding smooth empirical quantile contours and sign curves while preserving the essential monotonicity and Glivenko–Cantelli features of the concept, is provided. A numerical study of the resulting empirical quantile contours is conducted.

The numerical solution of partial differential equations is often performed on a numerical grid, where the grid points are used for estimating the partial derivatives. The grid can be fully static as in Eulerian type of solution method, or the grid points can move during the solution, which is the case in Lagrangian type of method. In the current article, a numerical solution method is presented, where the grid points are located on iso-contours of the two-dimensional field. The method calculates the local movement of the iso-contours according to an evolution equation described by the PDE, and the solution proceeds by moving the grid points towards the calculated direction. Additional stability is obtained by setting the grid points to move along the iso-contour line. To exemplify the application of the method, numerical examples are calculated for the two-dimensional diffusion equation.