Urban micro-climate in the City of Fez, Morocco

The proportion of the world’s population living in urban areas is constantly increasing. Different urban shapes result in different microclimates. The way cities are planned and built is therefore important for the global energy use. This study presents results from measurements of street climate in the city of Fez, Morocco, in contrasting traditional and modern housing areas, each with its own problems and qualities. Air temperature, relative humidity and wind velocity were measured in the two types of housing area, during both hot and cold seasons. These preliminary results confirm the night-time heat island phenomenon, while during the day the two areas show different behaviour. Further studies aim at recommendations on how to plan and build new housing areas in the region, to increase urban and indoor thermal comfor

A meshless method for an inverse two-phase one-dimensional nonlinear Stefan problem

We extend a meshless method of fundamental solutions recently proposed by the authors for the one-dimensional two-phase inverse linear Stefan problem, to the nonlinear case. In this latter situation the free surface is also considered unknown which is more realistic from the practical point of view. Building on the earlier work, the solution is approximated in each phase by a linear combination of fundamental solutions to the heat equation. The implementation and analysis are more complicated in the present situation since one needs to deal with a nonlinear minimization problem to identify the free surface. Furthermore, the inverse problem is ill-posed since small errors in the input measured data can cause large deviations in the desired solution. Therefore, regularization needs to be incorporated in the objective function which is minimized in order to obtain a stable solution. Numerical results are presented and discussed

Digital implementation of the cellular sensor-computers

Two different kinds of cellular sensor-processor architectures are used nowadays in various applications. The first is the traditional sensor-processor architecture, where the sensor and the processor arrays are mapped into each other. The second is the foveal architecture, in which a small active fovea is navigating in a large sensor array. This second architecture is introduced and compared here. Both of these architectures can be implemented with analog and digital processor arrays. The efficiency of the different implementation types, depending on the used CMOS technology, is analyzed. It turned out, that the finer the technology is, the better to use digital implementation rather than analog

Criteria of efficiency for conformal prediction

We study optimal conformity measures for various criteria of efficiency of classification in an idealised setting. This leads to an important class of criteria of efficiency that we call probabilistic; it turns out that the most standard criteria of efficiency used in literature on conformal prediction are not probabilistic unless the problem of classification is binary. We consider both unconditional and label-conditional conformal prediction.Comment: 31 page

Dissecting Galaxy Formation: II. Comparing Substructure in Pure Dark Matter and Baryonic Models

We compare the substructure evolution in pure dark matter (DM) halos with those in the presence of baryons (PDM and BDM). The prime halos have been analyzed by Romano-Diaz et al (2009). Models have been evolved from identical initial conditions using Constrained Realizations, including star formation and feedback. A comprehensive catalog of subhalos has been compiled and properties of subhalos analyzed in the mass range of 10^8 Mo - 10^11 Mo. We find that subhalo mass functions are consistent with a single power law, M_sbh^{alpha}, but detect a nonnegligible shift between these functions, alpha -0.86 for the PDM, and -0.98 for the BDM. Overall, alpha const. in time with variations of +-15%. Second, we find that the radial mass distribution of subhalos can be approximated by a power law, R^{gamma} with a steepening around the radius of a maximal circular velocity, Rvmax, in the prime halos. Gamma ~-1.5 for the PDM and -1 for the BDM, inside Rvmax, and is steeper outside. We detect little spatial bias between the subhalo populations and the DM of the main halos. The subhalo population exhibits much less triaxiality with baryons, in tandem with the prime halo. Finally, we find that, counter-intuitively, the BDM population is depleted at a faster rate than the PDM one within the central 30kpc of the prime. Although the baryons provide a substantial glue to the subhalos, the main halos exhibit the same trend. This assures a more efficient tidal disruption of the BDM subhalos. This effect can be reversed for a more efficient feedback from stellar evolution and supermassive black holes, which will expel baryons from the center and decrease the concentration of the prime halo. We compare our results with via Lactea and Aquarius simulations and other published results.Comment: 12 pages, 9 figures, to be published by the Astrophysical Journa

Safe Reinforcement Learning using Data-Driven Predictive Control

Reinforcement learning (RL) algorithms can achieve state-of-the-art performance in decision-making and continuous control tasks. However, applying RL algorithms on safety-critical systems still needs to be well justified due to the exploration nature of many RL algorithms, especially when the model of the robot and the environment are unknown. To address this challenge, we propose a data-driven safety layer that acts as a filter for unsafe actions. The safety layer uses a data-driven predictive controller to enforce safety guarantees for RL policies during training and after deployment. The RL agent proposes an action that is verified by computing the data-driven reachability analysis. If there is an intersection between the reachable set of the robot using the proposed action, we call the data-driven predictive controller to find the closest safe action to the proposed unsafe action. The safety layer penalizes the RL agent if the proposed action is unsafe and replaces it with the closest safe one. In the simulation, we show that our method outperforms state-of-the-art safe RL methods on the robotics navigation problem for a Turtlebot 3 in Gazebo and a quadrotor in Unreal Engine 4 (UE4)

Forming Early-Type Galaxies in LambdaCDM Simulations -I. Assembly histories

We present a sample of nine high resolution cosmological simulations in the mass range of M_vir=7x10^11-4x10^12 M_sun starting from LambdaCDM initial conditions. Our simulations include primordial radiative cooling, photoionization, star formation, supernova II feedback, but exclude supernova driven winds and AGN feedback. The simulated galaxies assemble in two phases, with the initial growth dominated by compact (r<r_eff) in situ star formation fueled by cold, low entropy gas streams resulting in a very similar mean assembly redshift of z_{f,ins}~2.5 for the in situ stellar component in all galaxies. The late growth is dominated by accretion of old stars formed in subunits outside the main galaxy (r>r_eff) resulting in an assembly redshift of z_{f,acc}~0.5-1.5 with much larger scatter. We find a positive correlation between the fraction of accreted stars and the final mass of our galaxies. We show that gravitational feedback strongly suppresses late star formation in massive galaxies contributing to the observed galaxy color bimodality. The accretion of stellar material is also responsible for the observed size growth of early-type galaxies. In addition, we find that the dark matter fractions within the stellar half-mass radii continuously increase towards lower redshift from about f_DM~0.05 at z~3 to f_DM~0.1-0.3 at z=0. Furthermore, the logarithmic slope of the total density profile is nearly isothermal at the present-day (gamma'~1.9-2.2). Finally, the input of gravitational heating lowers the central dark matter densities in the galaxies, with the effect being smaller compared to simulations without supernova feedback.Comment: 23 pages, 16 figures, accepted for publication in Ap

Infant Mortality in American Indians and Alaska Natives 1995–1999 and 2000–2004

Objectives. (1) To determine the infant mortality rate (IMR) in American Indians/ Alaska Natives (AI/AN) and Whites between 1995–1999 and 2000–2004. (2) To compare the leading causes of infant mortality in AI/AN and Whites. (3) To examine differences in neonatal vs. postneonatal causes of death in Whites and AI/AN. Methods. Using the 1995–99 and 2000–04 Centers for Disease Control and Prevention’s National Center for Health Statistics national linked birth/infant death data, we examined neonatal and postneonatal IMR among AI/AN and Whites. Results. AI/AN experienced significantly greater overall IMR in 1995–1999 and 2000–2004 than Whites. While the reduction in the IMR between these time periods was statistically significant for Whites, the reduction among AI/AN was not. We found that AI/AN had an IMR 1.5 times as high as that of Whites. Conclusions. While the overall IMR has decreased in AI/AN, disparities in postneonatal IMR persist between AI/AN and Whites

Mesenchymal stem cell-based therapy for ischemic stroke

Ischemic stroke represents a major, worldwide health burden with increasing incidence. Patients affected by ischemic strokes currently have few clinically approved treatment options available. Most currently approved treatments for ischemic stroke have narrow therapeutic windows, severely limiting the number of patients able to be treated. Mesenchymal stem cells represent a promising novel treatment for ischemic stroke. Numerous studies have demonstrated that mesenchymal stem cells functionally improve outcomes in rodent models of ischemic stroke. Recent studies have also shown that exosomes secreted by mesenchymal stem cells mediate much of this effect. In the present review, we summarize the current literature on the use of mesenchymal stem cells to treat ischemic stroke. Further studies investigating the mechanisms underlying mesenchymal stem cells tissue healing effects are warranted and would be of benefit to the field

Finite time corrections in KPZ growth models

We consider some models in the Kardar-Parisi-Zhang universality class, namely the polynuclear growth model and the totally/partially asymmetric simple exclusion process. For these models, in the limit of large time t, universality of fluctuations has been previously obtained. In this paper we consider the convergence to the limiting distributions and determine the (non-universal) first order corrections, which turn out to be a non-random shift of order t^{-1/3} (of order 1 in microscopic units). Subtracting this deterministic correction, the convergence is then of order t^{-2/3}. We also determine the strength of asymmetry in the exclusion process for which the shift is zero. Finally, we discuss to what extend the discreteness of the model has an effect on the fitting functions.Comment: 34 pages, 5 figures, LaTeX; Improved version including shift of PASEP height functio