Are the Jameson Land muskoxen, Northeast Greenland, in decline?

The Jameson Land region contains the largest muskox population in Northeast Greenland. In the period 1980-1990, late winter population size averaged 3,645. A late winter 2000 survey estimated ca. 1,705 muskoxen. Although no further late winter surveys for muskox abundance have occurred since, there have been two summer bird surveys, which recorded incidental observations of muskoxen, i.e., 607 in 2008 and 610 in 2009. We report on muskox observations obtained in a subarea of Jameson Land during the summer 2016 ground survey for birds. Although in the 1982-2000 period this subarea averaged 1,153 ± 346 muskoxen, we observed 138 individuals and a low calf number. The few muskoxen observed and poor calf production suggest population decline. We briefly discuss possible factors that could influence muskox mortality and population abundance. Surveys specific to muskoxen are necessary to ascertain current population abundance, demographics and trend.  &nbsp

Budgeted Reinforcement Learning in Continuous State Space

A Budgeted Markov Decision Process (BMDP) is an extension of a Markov Decision Process to critical applications requiring safety constraints. It relies on a notion of risk implemented in the shape of a cost signal constrained to lie below an - adjustable - threshold. So far, BMDPs could only be solved in the case of finite state spaces with known dynamics. This work extends the state-of-the-art to continuous spaces environments and unknown dynamics. We show that the solution to a BMDP is a fixed point of a novel Budgeted Bellman Optimality operator. This observation allows us to introduce natural extensions of Deep Reinforcement Learning algorithms to address large-scale BMDPs. We validate our approach on two simulated applications: spoken dialogue and autonomous driving.Comment: N. Carrara and E. Leurent have equally contribute

Caractérisation de matériaux diélectriques anisotropes

International audienceDe nos jours, le fonctionnement de la grande majorité des convertisseurs hertzien/optique repose sur les propriétés électrooptiques d'un matériau anisotrope cristallin, le niobate de lithium. Lorsqu'une onde optique pénètre dans le matériau, sa vitesse de propagation varie en fonction de l'intensité du champ électrique appliqué suivant l'effet Pockels (variation d'indice dépendante de l'intensité de champ). En général, cette variation est transformée en modulation d'intensité dans un interféromètre de type Mach-Zender ou à l'aide de polariseurs qui transforment la rotation de la polarisation en une variation d'intensité. La principale différence entre les deux méthodes est que dans le premier cas la structure de modulation est planaire, et qu'elle est volumique dans l'autre cas. Bien que déjà très répandu, le niobate de lithium a plusieurs inconvénients non négligeables : son coût de fabrication est très élevé, son coefficient électrooptique est faible et sa constante diélectrique haute fréquence est élevée. Pour pallier ces inconvénients, des matériaux à base de polymères sont actuellement développés. Nous nous intéressons à la caractérisation et à l'utilisation de ce type de matériaux. Dans cet article, nous présentons la méthode de mesure mise en œuvre pour déterminer la partie réelle de la constante diélectrique de ces matériaux en tenant compte de l'anisotropie

Electrooptic microwave antenna using organic poled polymers

International audienceWe propose a new electrooptic antenna design using organic polymer to receive microwave signals. In this paper we present the characterization of an electrooptic organic polymer. We measured the dielectric constant at microwave frequencies, and the electrooptic coefficient. We measured values of r33 of 3.35 pm/V at 1310 nm and 1.98 pm/V at 1550 nm. The goal of the electrooptic antenna design is to obtain maximum microwave and optical interaction. We propose a novel approach based on resonance effect in both optical and microwave domain. For the optical resonance effect we use a Fabry-Perot cavity, and a patch structure as microwave resonator

Characterization of electrooptic polymer applied to microwave sensing

International audienceIn this paper we present electrooptic measurement of a crosslinked side chain PGMA/DR1 polymer. Measured values are as high as 11 pm/V at 1310 nm, we present measurement as a function of incident beam reflexion point and show dependance between the reflexion point location over the sample and the measured electrooptic coefficient. We present low frequency relative dielectric constant using a capacitance measurement method. Using this method, we found a relative permittivity of 4.46plusmn0.38 for our polymer. We present a new electrooptic microwave sensor, where we enhance the electrooptical interaction by increasing the optical path length using a Fabry-Perot cavity and we concentrate the electric field inside our device using a microstrip resonator. Expected interaction enhancement value is expected to be as high 310deg compared to the simple reflexion case at low frequenc

Passive electro-optic antenna using polymer material

International audienceThe experimental results of a polymer microwave electro-optic antenna are reported. The device amplitude-modulates an optical input beam with a free-space propagating electromagnetic wave. By using a new dipole printed antenna, the electromagnetic energy is concentrated inside the device. An antenna factor of 168 dB/m is achieved with only 1 mum of electro-optic polyme

The crucial role of macromolecular engineering, drug encapsulation and dilution on the thermoresponsiveness of UCST diblock copolymer nanoparticles used for hyperthermia

International audiencePoly(acrylamide-co-acrylonitrile) (P(AAm-co-AN)), an upper critical solution temperature (UCST)-type copo-lymer in water, was synthesized by reversible addition fragmentation chain transfer (RAFT) copolymerization and used as a macro-RAFT agent for the polymerization of oligo(ethylene glycol) methyl ether methacrylate (OEGMA) to yield amphiphilic diblock P(AAm-co-AN)-b-POEGMA copolymer. A series of copolymers with different AN content was obtained allowing to finely tune the UCST behavior (cloud point (T t-UCST) from 35 to 78°C). Addition of the POEGMA block did not modify the T t-UCST regardless its Mn but provided a lower critical solution temperature behavior at high temperature. Nanoparticles were then formulated by the nanoprecipita-tion technique revealing that copolymers with higher T t-UCST yield smaller, better-defined nanoparticles. Eventually, doxorubicin (Dox) was encapsulated into nanoparticles made from the copolymer having a T t-UCST close to mild hyperthermia (~43°C). Surprisingly, Dox encapsulation increased T t-UCST and gave smaller na-noparticles as opposed to their unloaded counterparts. The dilution of the suspension also led to a decrease of Tt-UCST. No obvious hyperthermia effect was observed on the cytotoxicity of Dox-loaded nanoparticles. Our study highlighted the influence of macromolecular engineering, drug encapsulation and nanoparticle dilution on UCST behavior, important features often overlooked despite their crucial impact in the development of thermo-sensitive nanoscale drug delivery systems

Budgeted Reinforcement Learning in Continuous State Space

International audienceA Budgeted Markov Decision Process (BMDP) is an extension of a Markov Decision Process to critical applications requiring safety constraints. It relies on a notion of risk implemented in the shape of a cost signal constrained to lie below an-adjustable-threshold. So far, BMDPs could only be solved in the case of finite state spaces with known dynamics. This work extends the state-of-the-art to continuous spaces environments and unknown dynamics. We show that the solution to a BMDP is a fixed point of a novel Budgeted Bellman Optimality operator. This observation allows us to introduce natural extensions of Deep Reinforcement Learning algorithms to address large-scale BMDPs. We validate our approach on two simulated applications: spoken dialogue and autonomous driving

Passive temperature tomography experiments to characterize transmissivity and connectivity of preferential flow paths in fractured media

International audienceThe detection of preferential flow paths and the characterization of their hydraulic properties are major challenges in fractured rock hydrology. In this study, we propose to use temperature as a passive tracer to characterize fracture connectivity and hydraulic properties. In particular, we propose a new temperature tomography field method in which borehole temperature profiles are measured under different pumping conditions by changing successively the pumping and observation boreholes. To interpret these temperature- depth profiles, we propose a three step inversion-based framework. We consider first an inverse model that allows for automatic permeable fracture detection from borehole temperature profiles under pumping conditions. Then we apply a borehole-scale flow and temperature model to produce flowmeter profiles by inversion of temperature profiles. This second step uses inversion to characterize the relationship between temperature variations with depth and borehole flow velocities (Klepikova et al., 2011). The third inverse step, which exploits cross-borehole flowmeter tests, is aimed at inferring inter-borehole fracture connectivity and transmissivities. This multi-step inverse framework provides a means of including temperature profiles to image fracture hydraulic properties and connectivity. We test the proposed approach with field data obtained from the Ploemeur (N.W. France) fractured rock aquifer, where the full temperature tomography experiment was carried out between three 100 m depth boreholes 10 m apart. We identified several transmissive fractures and their connectivity which correspond to known fractures and corroborate well with independent information, including available borehole flowmeter tests and geophysical data. Hence, although indirect, temperature tomography appears to be a promising approach for characterizing connectivity patterns and transmissivities of the main flow paths in fractured rock

A simulation framework for rapid prototyping and evaluation of thermal mitigation techniques in many-core architectures

International audienceModern SoCs are characterized by increasing power density and consequently increasing temperature, that directly impacts performances, reliability and cost of a device through its packaging. Thermal issues need to be predicted and mitigated as early as possible in the design flow, when the optimization opportunities are the highest. In this paper, we present an efficient framework for the design of dynamic thermal mitigation schemes based on a high-level SystemC virtual prototype tightly coupled with efficient power and thermal simulation tools. We demonstrate the benefit of our approach through silicon comparison with the SThorm 64-core architecture and provide simulation speed results making it a sound solution for the design of thermal mitigation early in the flow