The Unification of Electromagnetism and Gravitation in the Context of Quantized Fractal Space Time

The attempts to unify electromagnetism and gravitation have included the formulations of Herman Weyl and the Kaluza Klein theory with the fifth dimension. More recently there have been fruitful attempts in the domain of Quantum Superstrings and the author's formulation in terms of Quantum Mechanical Kerr-Newman Black Holes. Though all these appear to be widely divergent approaches, they are shown to have a unified underpinning in the context of quantized fractal space time.Comment: 8 pages, Te

The Dark Matter Distribution in Abell 383: Evidence for a Shallow Density Cusp from Improved Lensing, Stellar Kinematic and X-ray Data

We extend our analyses of the dark matter (DM) distribution in relaxed clusters to the case of Abell 383, a luminous X-ray cluster at z=0.189 with a dominant central galaxy and numerous strongly-lensed features. Following our earlier papers, we combine strong and weak lensing constraints secured with Hubble Space Telescope and Subaru imaging with the radial profile of the stellar velocity dispersion of the central galaxy, essential for separating the baryonic mass distribution in the cluster core. Hydrostatic mass estimates from Chandra X-ray observations further constrain the solution. These combined datasets provide nearly continuous constraints extending from 2 kpc to 1.5 Mpc in radius, allowing stringent tests of results from recent numerical simulations. Two key improvements in our data and its analysis make this the most robust case yet for a shallow slope \beta of the DM density profile \rho_DM ~ r^-\beta on small scales. First, following deep Keck spectroscopy, we have secured the stellar velocity dispersion profile to a radius of 26 kpc for the first time in a lensing cluster. Secondly, we improve our previous analysis by adopting a triaxial DM distribution and axisymmetric dynamical models. We demonstate that in this remarkably well-constrained system, the logarithmic slope of the DM density at small radii is \beta < 1.0 (95% confidence). An improved treatment of baryonic physics is necessary, but possibly insufficient, to reconcile our observations with the recent results of high-resolution simulations.Comment: Accepted to ApJ Letter

From cusps to cores: a stochastic model

The cold dark matter model of structure formation faces apparent problems on galactic scales. Several threads point to excessive halo concentration, including central densities that rise too steeply with decreasing radius. Yet, random fluctuations in the gaseous component can 'heat' the centres of haloes, decreasing their densities. We present a theoretical model deriving this effect from first principles: stochastic variations in the gas density are converted into potential fluctuations that act on the dark matter; the associated force correlation function is calculated and the corresponding stochastic equation solved. Assuming a power law spectrum of fluctuations with maximal and minimal cutoff scales, we derive the velocity dispersion imparted to the halo particles and the relevant relaxation time. We further perform numerical simulations, with fluctuations realised as a Gaussian random field, which confirm the formation of a core within a timescale comparable to that derived analytically. Non-radial collective modes enhance the energy transport process that erases the cusp, though the parametrisations of the analytical model persist. In our model, the dominant contribution to the dynamical coupling driving the cusp-core transformation comes from the largest scale fluctuations. Yet, the efficiency of the transformation is independent of the value of the largest scale and depends weakly (linearly) on the power law exponent; it effectively depends on two parameters: the gas mass fraction and the normalisation of the power spectrum. This suggests that cusp-core transformations observed in hydrodynamic simulations of galaxy formation may be understood and parametrised in simple terms, the physical and numerical complexities of the various implementations notwithstanding.Comment: Minor revisions to match version to appear in MNRAS; Section~2.3 largely rewritten for clarit

Partially pyrolyzed-non-activated olive stones: Characterization and utilization of olive stones partially-pyrolyzed at various temperatures for 2-chlorophenol removal from water

This paper reports the development of the chemical and structural properties of partially pyrolyzed olive stones (OS) (at 250, 400, 500, 600, 700 and 850 °C) intended for use as a less expensive and more environmental-friendly adsorbent within water treatment applications. The following properties were followed: mass loss, surface chemistry (acid/base titrations and IR analysis), crystalline matter and elemental analysis, SEM, BET and TGA analysis. The major mass loss (68%) occurred between 250 and 400 °C. Acidic oxides disappeared after 500 °C, while surface basicity increased with increasing pyrolysis temperature. The partially pyrolyzed-non-activated OS sorbents were used for 2-chlorohenol (2-CP) removal from water, where 2-CP uptake increased with increasing pyrolysis temperature. The maximum adsorption was recorded at pH 7 using the pyrolyzed OS at 850 °C, which was only 13% more than that of OS pyrolyzed at 600 °C (sorbent carb600). So that carb600 (adsorption capacity: 34.1 mg g−1) was recommended as a cost-effective-environmental-friendly adsorbent. The re-usability of carb600 for removing 2-chlorophenol from real water sample was evident, where ∼70% of its adsorption efficiency was reserved even in the presence of competing ions

The Density Profiles of Massive, Relaxed Galaxy Clusters. II. Separating Luminous and Dark Matter in Cluster Cores

We present stellar and dark matter (DM) density profiles for a sample of seven massive, relaxed galaxy clusters derived from strong and weak gravitational lensing and resolved stellar kinematic observations within the centrally-located brightest cluster galaxies (BCGs). In Paper I of the series, we demonstrated that the total density profile derived from these data, which span 3 decades in radius, is consistent with numerical DM-only simulations at radii >~ 5-10 kpc, despite the significant contribution of stellar material in the core. Here we decompose the inner mass profiles of these clusters into stellar and dark components. Parametrizing the DM density profile as a power law rho_DM ~ r^{-\beta} on small scales, we find a mean slope = 0.50 +- 0.10 (random) +0.14-0.13 (systematic). Alternatively, cored Navarro-Frenk-White (NFW) profiles with = 1.14 +- 0.13 (random) +0.14-0.22 (systematic) provide an equally good description. These density profiles are significantly shallower than canonical NFW models at radii <~ 30 kpc, comparable to the effective radii of the BCGs. The inner DM profile is correlated with the distribution of stars in the BCG, suggesting a connection between the inner halo and the assembly of stars in the central galaxy. The stellar mass-to-light ratio inferred from lensing and stellar dynamics is consistent with that inferred using stellar population synthesis models if a Salpeter initial mass function is adopted. We compare these results to theories describing the interaction between baryons and DM in cluster cores, including adiabatic contraction models and the possible effects of galaxy mergers and active galactic nucleus feedback, and evaluate possible signatures of alternative DM candidates.Comment: Updated to matched the published version in Ap

The ascidian mouth opening is derived from the anterior neuropore: Reassessing the mouth/neural tube relationship in chordate evolution

AbstractThe relative positions of the brain and mouth are of central importance for models of chordate evolution. The dorsal hollow neural tube and the mouth have often been thought of as developmentally distinct structures that may have followed independent evolutionary paths. In most chordates however, including vertebrates and ascidians, the mouth primordia have been shown to fate to the anterior neural boundary. In ascidians such as Ciona there is a particularly intimate relationship between brain and mouth development, with a thin canal connecting the neural tube lumen to the mouth primordium at larval stages. This so-called neurohypophyseal canal was previously thought to be a secondary connection that formed relatively late, after the independent formation of the mouth primordium and the neural tube. Here we show that the Ciona neurohypophyseal canal is present from the end of neurulation and represents the anteriormost neural tube, and that the future mouth opening is actually derived from the anterior neuropore. The mouth thus forms at the anterior midline transition between neural tube and surface ectoderm. In the vertebrate Xenopus, we find that although the mouth primordium is not topologically continuous with the neural tube lumen, it nonetheless forms at this same transition point. This close association between the mouth primordium and the anterior neural tube in both ascidians and amphibians suggests that the evolution of these two structures may be more closely linked than previously appreciated

Automating the application of smart materials for protein crystallization

The fabrication and validation of the first semi-liquid nonprotein nucleating agent to be administered automatically to crystallization trials is reported. This research builds upon prior demonstration of the suitability of molecularly imprinted polymers (MIPs; known as 'smart materials') for inducing protein crystal growth. Modified MIPs of altered texture suitable for high-throughput trials are demonstrated to improve crystal quality and to increase the probability of success when screening for suitable crystallization conditions. The application of these materials is simple, time-efficient and will provide a potent tool for structural biologists embarking on crystallization trials. © 2015, IUCR. All rights reserved

The effects of baryon physics, black holes and AGN feedback on the mass distribution in clusters of galaxies

The spatial distribution of matter in clusters of galaxies is mainly determined by the dominant dark matter component, however, physical processes involving baryonic matter are able to modify it significantly. We analyse a set of 500 pc resolution cosmological simulations of a cluster of galaxies with mass comparable to Virgo, performed with the AMR code RAMSES. We compare the mass density profiles of the dark, stellar and gaseous matter components of the cluster that result from different assumptions for the subgrid baryonic physics and galaxy formation processes. First, the prediction of a gravity only N-body simulation is compared to that of a hydrodynamical simulation with standard galaxy formation recipes, then all results are compared to a hydrodynamical simulation which includes thermal AGN feedback from Super Massive Black Holes (SMBH). We find the usual effects of overcooling and adiabatic contraction in the run with standard galaxy formation physics, but very different results are found when implementing SMBHs and AGN feedback. Star formation is strongly quenched, producing lower stellar densities throughout the cluster, and much less cold gas is available for star formation at low redshifts. At redshift z = 0 we find a flat density core of radius 10 kpc in both of the dark and stellar matter density profiles. We specu- late on the possible formation mechanisms able to produce such cores and we conclude that they can be produced through the coupling of different processes: (I) dynamical friction from the decay of black hole orbits during galaxy mergers; (II) AGN driven gas outflows producing fluctuations of the gravitational potential causing the removal of collisionless matter from the central region of the cluster; (III) adiabatic expansion in response to the slow expulsion of gas from the central region of the cluster during the quiescent mode of AGN activity.Comment: Published on MNRAS - 13 pages, 4 tables, 9 figure

Enabling near-atomic-scale analysis of frozen water

Transmission electron microscopy has undergone a revolution in recent years with the possibility to perform routine cryo-imaging of biological materials and (bio)chemical systems, as well as the possibility to image liquids via dedicated reaction cells or graphene-sandwiching. These approaches however typically require imaging a large number of specimens and reconstructing an average representation and often lack analytical capabilities. Here, using atom probe tomography we provide atom-by-atom analyses of frozen liquids and analytical sub-nanometre three dimensional reconstructions. The analyzed ice is in contact with, and embedded within, nanoporous gold (NPG). We report the first such data on 2-3 microns thick layers of ice formed from both high purity deuterated water and a solution of 50mM NaCl in high purity deuterated water. We present a specimen preparation strategy that uses a NPG film and, additionally, we report on an analysis of the interface between nanoporous gold and frozen salt water solution with an apparent trend in the Na and Cl concentrations across the interface. We explore a range of experimental parameters to show that the atom probe analyses of bulk aqueous specimens come with their own special challenges and discuss physical processes that may produce the observed phenomena. Our study demonstrates the viability of using frozen water as a carrier for near-atomic scale analysis of objects in solution by atom probe tomography

On the Inability of Markov Models to Capture Criticality in Human Mobility

We examine the non-Markovian nature of human mobility by exposing the inability of Markov models to capture criticality in human mobility. In particular, the assumed Markovian nature of mobility was used to establish a theoretical upper bound on the predictability of human mobility (expressed as a minimum error probability limit), based on temporally correlated entropy. Since its inception, this bound has been widely used and empirically validated using Markov chains. We show that recurrent-neural architectures can achieve significantly higher predictability, surpassing this widely used upper bound. In order to explain this anomaly, we shed light on several underlying assumptions in previous research works that has resulted in this bias. By evaluating the mobility predictability on real-world datasets, we show that human mobility exhibits scale-invariant long-range correlations, bearing similarity to a power-law decay. This is in contrast to the initial assumption that human mobility follows an exponential decay. This assumption of exponential decay coupled with Lempel-Ziv compression in computing Fano's inequality has led to an inaccurate estimation of the predictability upper bound. We show that this approach inflates the entropy, consequently lowering the upper bound on human mobility predictability. We finally highlight that this approach tends to overlook long-range correlations in human mobility. This explains why recurrent-neural architectures that are designed to handle long-range structural correlations surpass the previously computed upper bound on mobility predictability