Monte Carlo results for the hydrogen Hugoniot

We propose a theoretical Hugoniot obtained by combining results for the equation of state (EOS) from the Direct Path Integral Monte Carlo technique (DPIMC) and those from Reaction Ensemble Monte Carlo (REMC) simulations. The main idea of such proposal is based on the fact that DPMIC provides first-principle results for a wide range of densities and temperatures including the region of partially ionized plasmas. On the other hand, for lower temperatures where the formation of molecules becomes dominant, DPIMC simulations become cumbersome and inefficient. For this region it is possible to use accurate REMC simulations where bound states (molecules) are treated on the Born-Oppenheimer level using a binding potential calculated by Kolos and Wolniewicz. The remaining interaction is then reduced to the scattering between neutral particles which is reliably treated classically applying effective potentials. The resulting Hugoniot is located between the experimental values of Knudson {\textit{et al.}} \cite{1} and Collins {\textit{et al.}} \cite{2}.Comment: 10 pges, 2 figures, 2 table

Rigorous Multiple-Precision Evaluation of D-Finite Functions in SageMath

We present a new open source implementation in the SageMath computer algebra system of algorithms for the numerical solution of linear ODEs with polynomial coefficients. Our code supports regular singular connection problems and provides rigorous error bounds

Unsupervised Text Extraction from G-Maps

This paper represents an text extraction method from Google maps, GIS maps/images. Due to an unsupervised approach there is no requirement of any prior knowledge or training set about the textual and non-textual parts. Fuzzy CMeans clustering technique is used for image segmentation and Prewitt method is used to detect the edges. Connected component analysis and gridding technique enhance the correctness of the results. The proposed method reaches 98.5% accuracy level on the basis of experimental data sets.Comment: Proc. IEEE Conf. #30853, International Conference on Human Computer Interactions (ICHCI'13), Chennai, India, 23-24 Aug., 201

Mechanisms underlying extremely fast muscle V˙O2 on-kinetics in humans.

The time constant of the primary phase of pulmonary V˙O2 on-kinetics (τp ), which reflects muscle V˙O2 kinetics during moderate-intensity exercise, is about 30 s in young healthy untrained individuals, while it can be as low as 8 s in endurance-trained athletes. We aimed to determine the intramuscular factors that enable very low values of t0.63 to be achieved (analogous to τp , t0.63 is the time to reach 63% of the V˙O2 amplitude). A computer model of oxidative phosphorylation (OXPHOS) in skeletal muscle was used. Muscle t0.63 was near-linearly proportional to the difference in phosphocreatine (PCr) concentration between rest and work (ΔPCr). Of the two main factors that determine t0.63 , a huge increase in either OXPHOS activity (six- to eightfold) or each-step activation (ESA) of OXPHOS intensity (>3-fold) was needed to reduce muscle t0.63 from the reference value of 29 s (selected to represent young untrained subjects) to below 10 s (observed in athletes) when altered separately. On the other hand, the effect of a simultaneous increase of both OXPHOS activity and ESA intensity required only a twofold elevation of each to decrease t0.63 below 10 s. Of note, the dependence of t0.63 on OXPHOS activity and ESA intensity is hyperbolic, meaning that in trained individuals a large increase in OXPHOS activity and ESA intensity are required to elicit a small reduction in τp . In summary, we postulate that the synergistic action of elevated OXPHOS activity and ESA intensity is responsible for extremely low τp (t0.63 ) observed in highly endurance-trained athletes

Modeling Life as Cognitive Info-Computation

This article presents a naturalist approach to cognition understood as a network of info-computational, autopoietic processes in living systems. It provides a conceptual framework for the unified view of cognition as evolved from the simplest to the most complex organisms, based on new empirical and theoretical results. It addresses three fundamental questions: what cognition is, how cognition works and what cognition does at different levels of complexity of living organisms. By explicating the info-computational character of cognition, its evolution, agent-dependency and generative mechanisms we can better understand its life-sustaining and life-propagating role. The info-computational approach contributes to rethinking cognition as a process of natural computation in living beings that can be applied for cognitive computation in artificial systems.Comment: Manuscript submitted to Computability in Europe CiE 201