469 research outputs found

    Experimental Evidence for Two-Dimensional Magnetic Order in Proton Bombarded Graphite

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    We have prepared magnetic graphite samples bombarded by protons at low temperatures and low fluences to attenuate the large thermal annealing produced during irradiation. An overall optimization of sample handling allowed us to find Curie temperatures Tc≳350 T_c \gtrsim 350 K at the used fluences. The magnetization versus temperature shows unequivocally a linear dependence, which can be interpreted as due to excitations of spin waves in a two dimensional Heisenberg model with a weak uniaxial anisotropy.Comment: 4 pages, 3 figure

    Direct Global Measurements of Tropspheric Winds Employing a Simplified Coherent Laser Radar using Fully Scalable Technology and Technique

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    Innovative designs of a space-based laser remote sensing 'wind machine' are presented. These designs seek compatibility with the traditionally conflicting constraints of high scientific value and low total mission cost. Mission cost is reduced by moving to smaller, lighter, more off-the-shelf instrument designs which can be accommodated on smaller launch vehicles

    Fokker-Planck Equation for Boltzmann-type and Active Particles: transfer probability approach

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    Fokker-Planck equation with the velocity-dependent coefficients is considered for various isotropic systems on the basis of probability transition (PT) approach. This method provides the self-consistent and universal description of friction and diffusion for Brownian particles. Renormalization of the friction coefficient is shown to occur for two dimensional (2-D) and three dimensional (3-D) cases, due to the tensorial character of diffusion. The specific forms of PT are calculated for the Boltzmann-type of collisions and for the absorption-type of collisions (the later are typical for dusty plasmas and some other systems). Validity of the Einstein's relation for the Boltzmann-type collisions is analyzed for the velocity-dependent friction and diffusion coefficients. For the Boltzmann-type collisions in the region of very high grain velocity as well as it is always for non-Boltzmann collisions, such as, e.g., absorption collisions, the Einstein relation is violated, although some other relations (determined by the structure of PT) can exist. The generalized friction force is investigated in dusty plasma in the framework of the PT approach. The relation between this force, negative collecting friction force and scattering and collecting drag forces is established.+AFwAXA- The concept of probability transition is used to describe motion of active particles in an ambient medium. On basis of the physical arguments the PT for a simple model of the active particle is constructed and the coefficients of the relevant Fokker-Planck equation are found. The stationary solution of this equation is typical for the simplest self-organized molecular machines.+AFwAXA- PACS number(s): 52.27.Lw, 52.20.Hv, 52.25.Fi, 82.70.-yComment: 18 page

    Design and Analysis of a Turbopump for a Conceptual Expander Cycle Upper-Stage Engine

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    This viewgraph presentation reviews the motivation for the study, the numerical method used, the numerical simulations of the vaneless diffuser and vaned diffuser. It also reviews the conclusions from the stud

    PEDF and GDNF are key regulators of photoreceptor development and retinal neurogenesis in reaggregates from chick embryonic retina

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    Here, role(s) of pigment epithelial-derived factor (PEDF) and glial-derived neurotrophic factor (GDNF) on photoreceptor development in three-dimensional reaggregates from the retinae of the E6 chick embryo (rosetted spheroids) was investigated. Fully dispersed cells were reaggregated under serum-reduced conditions and supplemented with 50 ng/ml PEDF alone or in combination with 50 ng/ml GDNF. The spheroids were analyzed for cell growth, differentiation, and death using proliferating cell nuclear antigen, terminal deoxynucleotidyl transferase deoxyuridine triphosphate nick end labeling, and other immunocytochemical stainings and semi-quantitative reverse transcription polymerase chain reaction (RT-PCR) methods. PEDF strongly promoted synthesis of the messenger RNAs for blue and violet cone opsins and to a lesser extent on the red and green cone opsins. This correlated with an increase in the number of cone photoreceptors, as determined by the cone cell marker CERN906. Likewise, PEDF nearly completely inhibited rod differentiation, as detected by immunostaining with anti-rho4D2 and RT-PCR. Furthermore, PEDF accelerated proliferation of cells in the spheroids and inhibited apoptosis. As negative effects, PEDF inhibited the normal histotypic tissue formation of retinal aggregates and reduced the frequency of photoreceptor rosettes and IPL-like areas. Noticeably, supplementation of PEDF-treated cultures with GDNF reversed the effects of PEDF on spheroid morphology and on rod differentiation. This study establishes that PEDF strongly affects three-dimensional retinogenesis in vitro, most notably by inhibiting rod development and supporting proliferation and differentiation of cones, effects which are partially counteracted by GDNF

    Insights from the NeurIPS 2021 NetHack Challenge

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    In this report, we summarize the takeaways from the first NeurIPS 2021 NetHack Challenge. Participants were tasked with developing a program or agent that can win (i.e., ‘ascend’ in) the popular dungeon-crawler game of NetHack by interacting with the NetHack Learning Environment (NLE), a scalable, procedurally generated, and challenging Gym environment for reinforcement learning (RL). The challenge showcased community-driven progress in AI with many diverse approaches significantly beating the previously best results on NetHack. Furthermore, it served as a direct comparison between neural (e.g., deep RL) and symbolic AI, as well as hybrid systems, demonstrating that on NetHack symbolic bots currently outperform deep RL by a large margin. Lastly, no agent got close to winning the game, illustrating NetHack’s suitability as a long-term benchmark for AI research
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