Model-Independent Relations for the Magnetic Properties of the Skyrmion

A relation is derived between the densities of isovector charge and magnetic dipole moment of the pionic skyrmion, which is largely independent of the properties of the lagrangian, and this is used to obtain relations for the mean-squared radii. The results apply to both linear and non-linear sigma-models

A Thorium Metal-Organic Framework with Outstanding Thermal and Chemical Stability.

A new thorium metal-organic framework (MOF), Th(OBA)2 , where OBA is 4,4'-oxybis(benzoic) acid, has been synthesized hydrothermally in the presence of a range of nitrogen-donor coordination modulators. This Th-MOF, described herein as GWMOF-13, has been characterized by single-crystal and powder X-ray diffraction, as well as through a range of techniques including gas sorption, thermogravimetric analysis (TGA), solid-state UV/Vis and luminescence spectroscopy. Single-crystal X-ray diffraction analysis of GWMOF-13 reveals an interesting, high symmetry (cubic Ia 3 ‾ d) structure, which yields a novel srs-a topology. Most notably, TGA analysis of GWMOF-13 reveals framework stability to 525 °C, matching the thermal stability benchmarks of the UiO-66 series MOFs and zeolitic imidazolate frameworks (ZIFs), and setting a new standard for thermal stability in f-block based MOFs

Wide-coverage deep statistical parsing using automatic dependency structure annotation

A number of researchers (Lin 1995; Carroll, Briscoe, and Sanfilippo 1998; Carroll et al. 2002; Clark and Hockenmaier 2002; King et al. 2003; Preiss 2003; Kaplan et al. 2004;Miyao and Tsujii 2004) have convincingly argued for the use of dependency (rather than CFG-tree) representations for parser evaluation. Preiss (2003) and Kaplan et al. (2004) conducted a number of experiments comparing “deep” hand-crafted wide-coverage with “shallow” treebank- and machine-learning based parsers at the level of dependencies, using simple and automatic methods to convert tree output generated by the shallow parsers into dependencies. In this article, we revisit the experiments in Preiss (2003) and Kaplan et al. (2004), this time using the sophisticated automatic LFG f-structure annotation methodologies of Cahill et al. (2002b, 2004) and Burke (2006), with surprising results. We compare various PCFG and history-based parsers (based on Collins, 1999; Charniak, 2000; Bikel, 2002) to find a baseline parsing system that fits best into our automatic dependency structure annotation technique. This combined system of syntactic parser and dependency structure annotation is compared to two hand-crafted, deep constraint-based parsers (Carroll and Briscoe 2002; Riezler et al. 2002). We evaluate using dependency-based gold standards (DCU 105, PARC 700, CBS 500 and dependencies for WSJ Section 22) and use the Approximate Randomization Test (Noreen 1989) to test the statistical significance of the results. Our experiments show that machine-learning-based shallow grammars augmented with sophisticated automatic dependency annotation technology outperform hand-crafted, deep, widecoverage constraint grammars. Currently our best system achieves an f-score of 82.73% against the PARC 700 Dependency Bank (King et al. 2003), a statistically significant improvement of 2.18%over the most recent results of 80.55%for the hand-crafted LFG grammar and XLE parsing system of Riezler et al. (2002), and an f-score of 80.23% against the CBS 500 Dependency Bank (Carroll, Briscoe, and Sanfilippo 1998), a statistically significant 3.66% improvement over the 76.57% achieved by the hand-crafted RASP grammar and parsing system of Carroll and Briscoe (2002)

Multiple-mouse Neuroanatomical Magnetic Resonance Imaging

The field of mouse phenotyping with magnetic resonance imaging (MRI) is rapidly growing, motivated by the need for improved tools for characterizing and evaluating mouse models of human disease. MRI is an excellent modality for investigating genetically altered animals. It is capable of whole brain coverage, can be used in vivo, and provides multiple contrast mechanisms for investigating different aspects of neuranatomy and physiology. The advent of high-field scanners along with the ability to scan multiple mice simultaneously allows for rapid phenotyping of novel mutations

Probing Hydrogen and Halogen-Oxo Interactions in Uranyl Coordination Polymers:A Combined Crystallographic and Computational Study

The syntheses and crystal structures of four compounds containing the UO22+ cation and either benzoic acid (1), m-chlorobenzoic acid (2), m-bromobenzoic acid (3), or m-iodobenzoic acid (4) are described and the vibrational spectroscopic properties for compounds 3 and 4 are reported. Single crystal X-ray diffraction analysis of these materials shows that uranyl oxo atoms are engaged in non-covalent assembly via either hydrogen (1 and 2) or halogen bonding (3 and 4) interactions. The halogen bonding in compounds 3 and 4 is notable as the crystallographic metric percentage of the sum of the van der Waals radii indicates these interactions are of similar strength. Characteristics of the halogen-oxo interactions of 3 and 4 were probed via Raman and infrared spectroscopy, which revealed significant differences in stretching frequency values for the two compounds. Additionally, compounds 3 and 4 were characterized via quantum chemical calculations and density-based quantum theory of atoms in molecules (QTAIM) analysis, which indicated that the I-oxo interaction in 4 is likely the stronger of the two interactions, with differences between the two interactions resulting from both inductive effects and halogen polarizability