ToyArchitecture: Unsupervised Learning of Interpretable Models of the World

Research in Artificial Intelligence (AI) has focused mostly on two extremes: either on small improvements in narrow AI domains, or on universal theoretical frameworks which are usually uncomputable, incompatible with theories of biological intelligence, or lack practical implementations. The goal of this work is to combine the main advantages of the two: to follow a big picture view, while providing a particular theory and its implementation. In contrast with purely theoretical approaches, the resulting architecture should be usable in realistic settings, but also form the core of a framework containing all the basic mechanisms, into which it should be easier to integrate additional required functionality. In this paper, we present a novel, purposely simple, and interpretable hierarchical architecture which combines multiple different mechanisms into one system: unsupervised learning of a model of the world, learning the influence of one's own actions on the world, model-based reinforcement learning, hierarchical planning and plan execution, and symbolic/sub-symbolic integration in general. The learned model is stored in the form of hierarchical representations with the following properties: 1) they are increasingly more abstract, but can retain details when needed, and 2) they are easy to manipulate in their local and symbolic-like form, thus also allowing one to observe the learning process at each level of abstraction. On all levels of the system, the representation of the data can be interpreted in both a symbolic and a sub-symbolic manner. This enables the architecture to learn efficiently using sub-symbolic methods and to employ symbolic inference.Comment: Revision: changed the pdftitl

Lagrangian Magneto-Hydrodynamics Based On Curvilinear Finite Elements

The magneto-hydrodynamic model is widely used for description of magnetized fluids in plasma dynamics, microfluidics, astrophysics and many other applications. In terms of modelling, the Lagrangian formulation is favourable for the rapid expansion during laser­target interaction for example. This is the case for inertial fusion and laboratory astrophysics applications, which are our primary interest. However, the proposed numerical method remains general and can be applied elsewhere. The conservation properties and divergence-free magnetic field are crucial aspects, which are not satisfied by the traditional numerical schemes. Here, the Lagrangian hydrodynamics using curvilinear finite elements is extended to the resistive magneto-hydrodynamics. An energy-conserving numerical scheme is formulated maintaining divergence-free magnetic field. The mixed finite element formulation provides theoretically arbitrary order of the spatial convergence and application on unstructured Lagrangian grids in multiple dimensions. An example of a physically relevant numerical simulation is presented

Active optical fibers doped with ceramic nanocrystals

Erbium-doped active optical fiber was successfully prepared by incorporation of ceramic nanocrystals inside a core of optical fiber. Modified chemical vapor deposition was combined with solution-doping approach to preparing preform. Instead of inorganic salts erbium-doped yttrium-aluminium garnet nanocrystals were used in the solution-doping process. Prepared preform was drawn into single-mode optical fiber with a numerical aperture 0.167. Optical and luminescence properties of the fiber were analyzed. Lasing ability of prepared fiber was proofed in a fiber-ring set-up. Optimal laser properties were achieved for a fiber length of 20~m. The slope efficiency of the fiber-laser was about 15%. Presented method can be simply extended to the deposition of other ceramic nanomaterials

Rotigotine Effects on Early Morning Motor Function and Sleep in Parkinson's Disease: A Double-Blind, Randomized, pLacebo-Controlled Study (RECOVER)

In a multinational, double-blind, placebo-controlled trial (NCT00474058), 287 subjects with Parkinson's disease (PD) and unsatisfactory early-morning motor symptom control were randomized 2:1 to receive rotigotine (2–16 mg/24 hr [n = 190]) or placebo (n = 97). Treatment was titrated to optimal dose over 1–8 weeks with subsequent dose maintenance for 4 weeks. Early-morning motor function and nocturnal sleep disturbance were assessed as coprimary efficacy endpoints using the Unified Parkinson's Disease Rating Scale (UPDRS) Part III (Motor Examination) measured in the early morning prior to any medication intake and the modified Parkinson's Disease Sleep Scale (PDSS-2) (mean change from baseline to end of maintenance [EOM], last observation carried forward). At EOM, mean UPDRS Part III score had decreased by −7.0 points with rotigotine (from a baseline of 29.6 [standard deviation (SD) 12.3] and by −3.9 points with placebo (baseline 32.0 [13.3]). Mean PDSS-2 total score had decreased by −5.9 points with rotigotine (from a baseline of 19.3 [SD 9.3]) and by −1.9 points with placebo (baseline 20.5 [10.4]). This represented a significantly greater improvement with rotigotine compared with placebo on both the UPDRS Part III (treatment difference: −3.55 [95% confidence interval (CI) −5.37, −1.73]; P = 0.0002) and PDSS-2 (treatment difference: −4.26 [95% CI −6.08, −2.45]; P < 0.0001). The most frequently reported adverse events were nausea (placebo, 9%; rotigotine, 21%), application site reactions (placebo, 4%; rotigotine, 15%), and dizziness (placebo, 6%; rotigotine 10%). Twenty-four-hour transdermal delivery of rotigotine to PD patients with early-morning motor dysfunction resulted in significant benefits in control of both motor function and nocturnal sleep disturbances. © 2010 Movement Disorder Societ

Some aspects of numerical methods for laser plasma hydrodynamics

V rámci této práce jsou vyvíjeny numerické metody pro 1D a 2D hydrodynamické kódy. Dvouteplotní popis nevazkou stlačitelnou tekutinou je aplikován v lagrangeovských souřadnicích, kde regularita 2D sítě je dosažena metodou ALE. Model absorpce laserového záření založený na stacionárních Maxwellových rovnicích je dále zkoumán a vylepšován pro numerickou robustnost a přesnost metody. Její aplikace do 2D navržená v rámci minulé práce je vylepšena pro dosažení vyššího rádu metody. Jsou porovnány sofistikované modely electron?iontových srážkových frekvencí. Schéma vedení tepla je aplikováno na dvouteplotní model a rozšíreno o teplotní relaxaci. Model nelokálního transportu záření a elektronu je doplněn o transport iontu. Provedené 1D a 2D numerické simulace jsou analyzovány a porovnány s literaturou.Numerical methods for the 1D and 2D hydrodynamical codes are developed in the context of this thesis. Two-temperature description by a non-viscous compressible fluid is applied in Lagrangian coordinates, where regularity of the 2D mesh is maintained by the ALE method. The model of laser absorption based on stationary Maxwell?s equations is studied and improved for numerical robustness and accuracy of the method. Its application in 2D, that has been developed in the previous academic work, is improved to attain higher order of the method. Sophisticated models of electron?ion collision frequencies are compared. The heat conduction scheme is applied on the twotemperature model and extended by the temperature relaxation. The ion transport is added to the model of non-local transport of radiation and electrons. Performed 1D and 2D simulations are analysed and compared with literature

Charge Transfer and Charge Trapping Processes in Ca- or Al-Co-doped Lu₂SiO₅ and Lu₂Si₂O₇ Scintillators Activated by Pr³⁺ or Ce³⁺ Ions

Lutetium oxyorthosilicate Lu2SiO5 (LSO) and pyrosilicate Lu2Si2O7 (LPS) activated by Ce3+ or Pr3+ are known to be effective and fast scintillation materials for the detection of X-rays and γ-rays. Their performances can be further improved by co-doping with aliovalent ions. Herein, we investigate the Ce3+(Pr3+) → Ce4+(Pr4+) conversion and the formation of lattice defects stimulated by co-doping with Ca2+ and Al3+ in LSO and LPS powders prepared by the solid-state reaction process. The materials were studied by electron paramagnetic resonance (EPR), radioluminescence spectroscopy, and thermally stimulated luminescence (TSL), and scintillation decays were measured. EPR measurements of both LSO:Ce and LPS:Ce showed effective Ce3+ → Ce4+ conversions stimulated by Ca2+ co-doping, while the effect of Al3+ co-doping was less effective. In Pr-doped LSO and LPS, a similar Pr3+ → Pr4+ conversion was not detected by EPR, suggesting that the charge compensation of Al3+ and Ca2+ ions is realized via other impurities and/or lattice defects. X-ray irradiation of LPS creates hole centers attributed to a hole trapped in an oxygen ion in the neighborhood of Al3+ and Ca2+. These hole centers contribute to an intense TSL glow peak at 450–470 K. In contrast to LPS, only weak TSL peaks are detected in LSO and no hole centers are visible via EPR. The scintillation decay curves of both LSO and LPS show a bi-exponential decay with fast and slow component decay times of 10–13 ns and 30–36 ns, respectively. The decay time of the fast component shows a small (6–8%) decrease due to co-doping

Physics-enhanced neural networks for equation-of-state calculations

Rapid access to accurate equation-of-state (EOS) data is crucial in the warm-dense matter (WDM) regime, as it is employed in various applications, such as providing input for hydrodynamic codes to model inertial confinement fusion processes. In this study, we develop neural network models for predicting the EOS based on first-principles data. The first model utilises basic physical properties, while the second model incorporates more sophisticated physical information, using output from average-atom (AA) calculations as features. AA models are often noted for providing a reasonable balance of accuracy and speed; however, our comparison of AA models and higher-fidelity calculations shows that more accurate models are required in the WDM regime. Both the neural network models we propose, particularly the physics-enhanced one, demonstrate significant potential as accurate and efficient methods for computing EOS data in WDM