Cartan's spiral staircase in physics and, in particular, in the gauge theory of dislocations

In 1922, Cartan introduced in differential geometry, besides the Riemannian curvature, the new concept of torsion. He visualized a homogeneous and isotropic distribution of torsion in three dimensions (3d) by the "helical staircase", which he constructed by starting from a 3d Euclidean space and by defining a new connection via helical motions. We describe this geometric procedure in detail and define the corresponding connection and the torsion. The interdisciplinary nature of this subject is already evident from Cartan's discussion, since he argued - but never proved - that the helical staircase should correspond to a continuum with constant pressure and constant internal torque. We discuss where in physics the helical staircase is realized: (i) In the continuum mechanics of Cosserat media, (ii) in (fairly speculative) 3d theories of gravity, namely a) in 3d Einstein-Cartan gravity - this is Cartan's case of constant pressure and constant intrinsic torque - and b) in 3d Poincare gauge theory with the Mielke-Baekler Lagrangian, and, eventually, (iii) in the gauge field theory of dislocations of Lazar et al., as we prove for the first time by arranging a suitable distribution of screw dislocations. Our main emphasis is on the discussion of dislocation field theory.Comment: 31 pages, 8 figure

Neurokernel: An Open Source Platform for Emulating the Fruit Fly Brain

We have developed an open software platform called Neurokernel for collaborative development of comprehensive models of the brain of the fruit fly Drosophila melanogaster and their execution and testing on multiple Graphics Processing Units (GPUs). Neurokernel provides a programming model that capitalizes upon the structural organization of the fly brain into a fixed number of functional modules to distinguish between these modules’ local information processing capabilities and the connectivity patterns that link them. By defining mandatory communication interfaces that specify how data is transmitted between models of each of these modules regardless of their internal design, Neurokernel explicitly enables multiple researchers to collaboratively model the fruit fly’s entire brain by integration of their independently developed models of its constituent processing units. We demonstrate the power of Neurokernel’s model integration by combining independently developed models of the retina and lamina neuropils in the fly’s visual system and by demonstrating their neuroinformation processing capability. We also illustrate Neurokernel’s ability to take advantage of direct GPU-to-GPU data transfers with benchmarks that demonstrate scaling of Neurokernel’s communication performance both over the number of interface ports exposed by an emulation’s constituent modules and the total number of modules comprised by an emulation

A proof of uniqueness of the Gurarii space

We present a short and elementary proof of isometric uniqueness of the Gurarii space.Comment: 6 pages, some improvements incorporate

Contemplating Mindfulness at Work: An Integrative Review

Mindfulness research activity is surging within organizational science. Emerging evidence across multiple fields suggests that mindfulness is fundamentally connected to many aspects of workplace functioning, but this knowledge base has not been systematically integrated to date. This review coalesces the burgeoning body of mindfulness scholarship into a framework to guide mainstream management research investigating a broad range of constructs. The framework identifies how mindfulness influences attention, with downstream effects on functional domains of cognition, emotion, behavior, and physiology. Ultimately, these domains impact key workplace outcomes, including performance, relationships, and well-being. Consideration of the evidence on mindfulness at work stimulates important questions and challenges key assumptions within management science, generating an agenda for future research

Identification of linear and nonlinear sensory processing circuits from spiking neuron data

Inferring mathematical models of sensory processing systems directly from input-output observations, while making the fewest assumptions about the model equations and the types of measurements available, is still a major issue in computational neuroscience. This letter introduces two new approaches for identifying sensory circuit models consisting of linear and nonlinear filters in series with spiking neuron models, based only on the sampled analog input to the filter and the recorded spike train output of the spiking neuron. For an ideal integrate-and-fire neuron model, the first algorithm can identify the spiking neuron parameters as well as the structure and parameters of an arbitrary nonlinear filter connected to it. The second algorithm can identify the parameters of the more general leaky integrate-and-fire spiking neuron model, as well as the parameters of an arbitrary linear filter connected to it. Numerical studies involving simulated and real experimental recordings are used to demonstrate the applicability and evaluate the performance of the proposed algorithms

Statistical Topology of Cellular Networks in Two and Three Dimensions

Cellular networks may be found in a variety of natural contexts, from soap foams to biological tissues to grain boundaries in a polycrystal, and the characterization of these structures is therefore a subject of interest to a range of disciplines. An approach to describe the topology of a cellular network in two and three dimensions is presented. This allows for the quantification of a variety of features of the cellular network, including a quantification of topological disorder and a robust measure of the statistical similarity or difference of a set of structures. The results of this analysis are presented for numerous simulated systems including the Poisson-Voronoi and the steady-state grain growth structures in two and three dimensions

Nitrogen and phosphorus limitation of oceanic microbial growth during spring in the Gulf of Aqaba

Bioassay experiments were performed to identify how growth of key groups within the microbial community was simultaneously limited by nutrient (nitrogen and phosphorus) availability during spring in the Gulf of Aqaba's oceanic waters. Measurements of chlorophyll a (chl a) concentration and fast repetition rate (FRR) fluorescence generally demonstrated that growth of obligate phototrophic phytoplankton was co-limited by N and P and growth of facultative aerobic anoxygenic photoheterotropic (AAP) bacteria was limited by N. Phytoplankton exhibited an increase in chl a biomass over 24 to 48 h upon relief of nutrient limitation. This response coincided with an increase in photosystem II (PSII) photochemical efficiency (F v /F m), but was preceded (within 24 h) by a decrease in effective absorption crosssection (σPSII) and electron turnover time (τ). A similar response for τ and bacterio-chl a was observed for the AAPs. Consistent with the up-regulation of PSII activity with FRR fluorescence were observations of newly synthesized PSII reaction centers via low temperature (77K) fluorescence spectroscopy for addition of N (and N + P). Flow cytometry revealed that the chl a and thus FRR fluorescence responses were partly driven by the picophytoplankton (æ10 μm) community, and in particular Synechococcus. Productivity of obligate heterotrophic bacteria exhibited the greatest increase in response to a natural (deep water) treatment, but only a small increase in response to N and P addition, demonstrating the importance of additional substrates (most likely dissolved organic carbon) in moderating the heterotrophs. These data support previous observations that the microbial community response (autotrophy relative to heterotrophy) is critically dependent upon the nature of transient nutrient enrichment. © Inter-Research 2009

Intrinsic protein disorder in histone lysine methylation

Histone lysine methyltransferases (HKMTs), catalyze mono-, di- and trimethylation of lysine residues, resulting in a regulatory pattern that controls gene expression. Their involvement in many different cellular processes and diseases makes HKMTs an intensively studied protein group, but scientific interest so far has been concentrated mostly on their catalytic domains. In this work we set out to analyze the structural heterogeneity of human HKMTs and found that many contain long intrinsically disordered regions (IDRs) that are conserved through vertebrate species. Our predictions show that these IDRs contain several linear motifs and conserved putative binding sites that harbor cancer-related SNPs. Although there are only limited data available in the literature, some of the predicted binding regions overlap with interacting segments identified experimentally. The importance of a disordered binding site is illustrated through the example of the ternary complex between MLL1, menin and LEDGF/p75. Our suggestion is that intrinsic protein disorder plays an as yet unrecognized role in epigenetic regulation, which needs to be further elucidated through structural and functional studies aimed specifically at the disordered regions of HKMTs. Reviewers: This article was reviewed by Arne Elofsson and Piotr Zielenkiewicz. © 2016 The Author(s)

Particle-in-cell Simulations of the Parallel Proton Firehose Instability Influenced by the Electron Temperature Anisotropy in Solar Wind Conditions

In situ observations of the solar wind show a limited level of particle temperature anisotropy with respect to the interplanetary magnetic field direction. Kinetic electromagnetic instabilities are efficient to prevent the excessive growth of the anisotropy of particle velocity distribution functions. Among them, the firehose instabilities are often considered to prevent the increase of the parallel temperature and hence to shape the velocity distribution functions of electrons and protons in the solar wind. We present a nonlinear modeling of the parallel firehose instability, retaining a kinetic description for both the electrons and protons. One-dimensional (1D) fully kinetic particle-in-cell simulations using the energy conserving semi-implicit method (ECsim) are performed to clarify the role of the electron temperature anisotropy in the development of the parallel proton firehose instability. We found that in the presence of an electron temperature anisotropy, such that the temperature parallel to the background magnetic field is higher than the temperature in the perpendicular direction, the onset of the parallel proton firehose instability occurs earlier and its growth rate is faster. The enhanced wave fluctuations contribute to the particle scattering reducing the temperature anisotropy to a stable, nearly isotropic state. The simulation results compare well with linear theory. A test case of 1D simulations at oblique angles with respect to the magnetic field is also considered, as a first step to study the cumulative effect of protons and electrons on the full spectrum of instabilities