Learning Formal Definitions for Snomed CT from Text

Snomed CT is a widely used medical ontology which is formally expressed in a fragment of the Description Logic EL++. The underlying logics allow for expressive querying, yet make it costly to maintain and extend the ontology. Existing approaches for ontology generation mostly focus on learning superclass or subclass relations and therefore fail to be used to generate Snomed CT definitions. In this paper, we present an approach for the extraction of Snomed CT definitions from natural language texts, based on the distance relation extraction approach. By benefiting from a relatively large amount of textual data for the medical domain and the rich content of Snomed CT, such an approach comes with the benefit that no manually labelled corpus is required. We also show that the type information for Snomed CT concept is an important feature to be examined for such a system. We test and evaluate the approach using two types of texts. Experimental results show that the proposed approach is promising to assist Snomed CT development

Reactivity of Acyclic (pentadienyl)iron(1+) Cations with Phosphonate Stabilized Nucleophiles: Application to the Synthesis of Oxygenated Metabolites of Carvone

The addition of phosphonate stabilized carbon nucleophiles to acyclic (pentadienyl)iron(1+) cations proceeds predominantly at an internal carbon to afford (pentenediyl)iron complexes. Those complexes bearing an electron withdrawing group at the σ-bound carbon (i.e., 13/14) are stable and isolable, while complexes which do not contain an electron withdrawing group at the σ-bound carbon undergo CO insertion, reductive elimination and conjugation of the double bond to afford cyclohexenone products (21/22). Deprotonation of the phosphonate 13/14 or 21 and reaction with paraformaldehyde affords the olefinated products. This methodology was utilized to prepare oxygenated carvone metabolites (±)-25 and (±)-26

Resource Allocation in MIMO setup

In a multi-input multi-output (MIMO) setup, where one side of the link comprises a linear antenna array, data can be transmitted over the direction of incident rays. Channel capacity for this setup is studied in this paper. We define two different setups; one when the energy is constant and equal over all rays, and one when available energy is evenly distributed over rays. For the latter, we show that there is an upper bound for channel capacity, regardless of the number of rays and antennas. Also, we have compared this setup with the legacy single-input single-output (SISO) AWGN channel

Supramolecular structure in the membrane of Staphylococcus aureus

The fundamental processes of life are organized and based on common basic principles. Molecular organizers, often interacting with the membrane, capitalize on cellular polarity to precisely orientate essential processes. The study of organisms lacking apparent polarity or known cellular organizers (e.g., the bacterium Staphylococcus aureus) may enable the elucidation of the primal organizational drive in biology. How does a cell choose from infinite locations in its membrane? We have discovered a structure in the S. aureus membrane that organizes processes indispensable for life and can arise spontaneously from the geometric constraints of protein complexes on membranes. Building on this finding, the most basic cellular positioning system to optimize biological processes, known molecular coordinators could introduce further levels of complexity. All life demands the temporal and spatial control of essential biological functions. In bacteria, the recent discovery of coordinating elements provides a framework to begin to explain cell growth and division. Here we present the discovery of a supramolecular structure in the membrane of the coccal bacterium Staphylococcus aureus, which leads to the formation of a large-scale pattern across the entire cell body; this has been unveiled by studying the distribution of essential proteins involved in lipid metabolism (PlsY and CdsA). The organization is found to require MreD, which determines morphology in rod-shaped cells. The distribution of protein complexes can be explained as a spontaneous pattern formation arising from the competition between the energy cost of bending that they impose on the membrane, their entropy of mixing, and the geometric constraints in the system. Our results provide evidence for the existence of a self-organized and nonpercolating molecular scaffold involving MreD as an organizer for optimal cell function and growth based on the intrinsic self-assembling properties of biological molecules

Wavefunction-Independent Relations between the Nucleon Axial-Coupling g_A and the Nucleon Magnetic Moments

We calculate the proton's magnetic moment $\mu_p$ and its axial-vector coupling $g_A$ as a function of its Dirac radius $R_1$ using a relativisitic three-quark model formulated on the light-cone. The relationship between $\mu_p$ and $g_A$ is found to be independent of the assumed form of the light-cone wavefunction. At the physical radius $R_1=0.76$ fm, one obtains the experimental values for both $\mu_p$ and $g_A$, and the helicity carried by the valence $u$ and $d$ quarks are each reduced by a factor $\simeq 0.75$ relative to their non-relativistic values. At large proton radius, $\mu_p$ and $g_A$ are given by the usual non-relativistic formulae. At small radius, $\mu_p$ becomes equal to the Dirac moment, as demanded by the Drell-Hearn-Gerasimov sum rule. In addition, as $R_1 \to 0,$ the constituent quark helicities become completely disoriented and $g_A \to 0$.Comment: 17 pages, RevTeX, 4 uuencoded figures, SLAC-PUB-643

Some novel aspects of quantile regression: local stationarity, random forests and optimal transportation

This paper is written for a Festschrift in honour of Professor Marc Hallin and it proposes some developments on quantile regression. We connect our investigation to Marc's scientific production and we present some theoretical and methodological advances for quantiles estimation in non standard settings. We split our contributions in two parts. The first part is about conditional quantiles estimation for nonstationary time series. The second part is about conditional quantiles estimation for the analysis of multivariate independent data in the presence of possibly large dimensional covariates. Monte Carlo studies illustrate numerically the performance of our methods and compare them to some extant techniques