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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 ?

Driver’s facial recognition is an important part for designing the active automotive safety system. Aiming at the problem that it is more difficult to recognize the face under obscure conditions, a driver’s facial contour recognition method was designed by use of illumination compensation and Gaussian model. The algorithm steps were given and some obscure pictures were tested in MATLAB. The result shows that the driver’s face contour was distinguished from background area accurately, and the face area was recognized successfully.

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.

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.

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.

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.

While research on the perception of line drawings has long demonstrated the importance of contours in object recognition, recent work shows that contours can also convey material properties. For example, even simple 2D shapes with varying contours have been shown to evoke vivid impressions of different materials. However, such static representations capture only a single moment in time. When a material moves, its contours shift, evolve, or deform over time, creating contour motion. Does this contour motion convey diagnostic information about material properties, independent of surface appearance? Existing studies on the role of dynamic cues in material perception either use fully rendered 3D stimuli, where contour motion is confounded with rich surface information, or motion-only displays (dynamic dot stimuli or noise patches), which eliminate surface cues but also lack clearly defined contours. As a result, the relative contribution of contour motion to material perception remains unclear. To address this gap, we measured how human observers perceive materials from dynamic line drawings (“line”), compared to animations of fully textured stimuli that carry optical and motion information (“full”), as well as dynamic dot stimuli (“dot”). Stimuli were three rendered versions (full, dot, line) of material animations from five material categories (jelly, liquid, smoke, fabric, and rigid-breakable). In one experiment, participants rated five material attributes (dense, flexible, wobbly, fluid, airy motion), and in a second experiment, participants were asked to choose one of the two materials that is more similar to a third material across all possible combinations. Results from both experiments consistently show that perceptual organization in both line and dot conditions strongly corresponds to that observed in the full condition. A control rating experiment with static line drawings (single images) showed significantly weaker correspondence to the full condition than between dynamic line drawings and the full condition, indicating that contour motion, not static shape alone, drives the effect. Together, these findings show that contour motion provides diagnostic information for material perception by jointly conveying contour shape and its time-varying dynamics, extending beyond what can be inferred from static contour cues alone.

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.