اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدMinimal cost-time strategies for population replacement using the IIT
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Vector control plays a central role in the fight against vector-borne diseases and, in particular, arboviruses. The use of the endosymbiotic bacterium Wolbachia has proven effective in preventing the transmission of some of these viruses between mosquitoes and humans, making it a promising control tool. The Incompatible Insect Technique (IIT) consists in replacing the wild population by a population carrying the aforementioned bacterium, thereby preventing outbreaks of the associated vector-borne diseases. In this work, we consider a two species model incorporating both Wolbachia infected and wild mosquitoes. Our system can be controlled thanks to a term representing an artificial introduction of Wolbachia-infected mosquitoes. Under the assumption that the birth rate of mosquitoes is high, we may reduce the model to a simpler one on the proportion of infected mosquitoes. We investigate minimal cost-time strategies to achieve a population replacement both analytically and numerically for the simplified 1D model and only numerically for the full 2D system
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In this article, we are interested in the analysis and simulation of solutions to an optimal control problem motivated by population dynamics issues. In order to control the spread of mosquito-borne arboviruses, the population replacement technique c
onsists in releasing into the environment mosquitoes infected with the Wolbachia bacterium, which greatly reduces the transmission of the virus to the humans. Spatial releases are then sought in such a way that the infected mosquito population invades the uninfected mosquito population. Assuming very high mosquito fecundity rates, we first introduce an asymptotic model on the proportion of infected mosquitoes and then an optimal control problem to determine the best spatial strategy to achieve these releases. We then analyze this problem, including the optimality of natural candidates and carry out first numerical simulations in one dimension of space to illustrate the relevance of our approach.
Our goal is to study controllability and observability properties of the 1D heat equation with internal control (or observation) set $omega_{varepsilon}=(x_{0}-varepsilon, x_{0}+varepsilon )$, in the limit $varepsilonrightarrow 0$, where $x_{0}in (0,
1)$. It is known that depending on arithmetic properties of $x_{0}$, there may exist a minimal time $T_{0}$ of pointwise control at $x_{0}$ of the heat equation. Besides, for any $varepsilon$ fixed, the heat equation is controllable with control set $omega_{varepsilon}$ in any time $T>0$. We relate these two phenomena. We show that the observability constant on $omega_varepsilon$ does not converge to $0$ as $varepsilonrightarrow 0$ at the same speed when $T>T_{0}$ (in which case it is comparable to $varepsilon^{1/2}$) or $T<T_{0}$ (in which case it converges faster to $0$). We also describe the behavior of optimal $L^{2}$ null-controls on $omega_{varepsilon}$ in the limit $varepsilon rightarrow 0$.
Robotic vision plays a key role for perceiving the environment in grasping applications. However, the conventional framed-based robotic vision, suffering from motion blur and low sampling rate, may not meet the automation needs of evolving industrial
requirements. This paper, for the first time, proposes an event-based robotic grasping framework for multiple known and unknown objects in a cluttered scene. Compared with standard frame-based vision, neuromorphic vision has advantages of microsecond-level sampling rate and no motion blur. Building on that, the model-based and model-free approaches are developed for known and unknown objects grasping respectively. For the model-based approach, event-based multi-view approach is used to localize the objects in the scene, and then point cloud processing allows for the clustering and registering of objects. Differently, the proposed model-free approach utilizes the developed event-based object segmentation, visual servoing and grasp planning to localize, align to, and grasp the targeting object. The proposed approaches are experimentally validated with objects of different sizes, using a UR10 robot with an eye-in-hand neuromorphic camera and a Barrett hand gripper. Moreover, the robustness of the two proposed event-based grasping approaches are validated in a low-light environment. This low-light operating ability shows a great advantage over the grasping using the standard frame-based vision. Furthermore, the developed model-free approach demonstrates the advantage of dealing with unknown object without prior knowledge compared to the proposed model-based approach.
Mosquitoes are responsible for the transmission of many diseases such as dengue fever, zika or chigungunya. One way to control the spread of these diseases is to use the sterile insect technique (SIT), which consists in a massive release of sterilize
d male mosquitoes. This strategy aims at reducing the total population over time, and has the advantage being specific to the targeted species, unlike the use of pesticides. In this article, we study the optimal release strategies in order to maximize the efficiency of this technique. We consider simplified models that describe the dynamics of eggs, males, females and sterile males in order to optimize the release protocol. We determine in a precise way optimal strategies, which allows us to tackle numerically the underlying optimization problem in a very simple way. We also present some numerical simulations to illustrate our results.
We study the chemotaxis model $partial$ t u = div($ abla$u -- u$ abla$w) + $theta$v -- u in (0, $infty$) x $Omega$, $partial$ t v = u -- $theta$v in (0, $infty$) x $Omega$, $partial$ t w = D$Delta$w -- $alpha$w + v in (0, $infty$) x $Omega$, with no-
flux boundary conditions in a bounded and smooth domain $Omega$ $subset$ R 2 , where u and v represent the densities of subpopulations of moving and static individuals of some species, respectively, and w the concentration of a chemoattractant. We prove that, in an appropriate functional setting, all solutions exist globally in time. Moreover, we establish the existence of a critical mass M c > 0 of the whole population u + v such that, for M $in$ (0, M c), any solution is bounded, while, for almost all M > M c , there exist solutions blowing up in infinite time. The building block of the analysis is the construction of a Liapunov functional. As far as we know, this is the first result of this kind when the mass conservation includes the two subpopulations and not only the moving one.
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