Megalithic Mystery Hill

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Deconstructing therapy outcome measurement with Rasch analysis of a measure of general clinical distress: the Symptom Checklist-90-Revised

Rasch analysis was used to illustrate the usefulness of item-level analyses for evaluating a common therapy outcome measure of general clinical distress, the Symptom Checklist-90-Revised (SCL-90-R; Derogatis, 1994). Using complementary therapy research samples, the instrument's 5-point rating scale was found to exceed clients' ability to make reliable discriminations and could be improved by collapsing it into a 3-point version (combining scale points 1 with 2 and 3 with 4). This revision, in addition to removing 3 misfitting items, increased person separation from 4.90 to 5.07 and item separation from 7.76 to 8.52 (resulting in alphas of .96 and .99, respectively). Some SCL-90-R subscales had low internal consistency reliabilities; SCL-90-R items can be used to define one factor of general clinical distress that is generally stable across both samples, with two small residual factors

Electron Transport through Disordered Domain Walls: Coherent and Incoherent Regimes

We study electron transport through a domain wall in a ferromagnetic nanowire subject to spin-dependent scattering. A scattering matrix formalism is developed to address both coherent and incoherent transport properties. The coherent case corresponds to elastic scattering by static defects, which is dominant at low temperatures, while the incoherent case provides a phenomenological description of the inelastic scattering present in real physical systems at room temperature. It is found that disorder scattering increases the amount of spin-mixing of transmitted electrons, reducing the adiabaticity. This leads, in the incoherent case, to a reduction of conductance through the domain wall as compared to a uniformly magnetized region which is similar to the giant magnetoresistance effect. In the coherent case, a reduction of weak localization, together with a suppression of spin-reversing scattering amplitudes, leads to an enhancement of conductance due to the domain wall in the regime of strong disorder. The total effect of a domain wall on the conductance of a nanowire is studied by incorporating the disordered regions on either side of the wall. It is found that spin-dependent scattering in these regions increases the domain wall magnetoconductance as compared to the effect found by considering only the scattering inside the wall. This increase is most dramatic in the narrow wall limit, but remains significant for wide walls.Comment: 23 pages, 12 figure

Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning

Classical intermolecular potentials typically require an extensive parametrization procedure for any new compound considered. To do away with prior parametrization, we propose a combination of physics-based potentials with machine learning (ML), coined IPML, which is transferable across small neutral organic and biologically-relevant molecules. ML models provide on-the-fly predictions for environment-dependent local atomic properties: electrostatic multipole coefficients (significant error reduction compared to previously reported), the population and decay rate of valence atomic densities, and polarizabilities across conformations and chemical compositions of H, C, N, and O atoms. These parameters enable accurate calculations of intermolecular contributions---electrostatics, charge penetration, repulsion, induction/polarization, and many-body dispersion. Unlike other potentials, this model is transferable in its ability to handle new molecules and conformations without explicit prior parametrization: All local atomic properties are predicted from ML, leaving only eight global parameters---optimized once and for all across compounds. We validate IPML on various gas-phase dimers at and away from equilibrium separation, where we obtain mean absolute errors between 0.4 and 0.7 kcal/mol for several chemically and conformationally diverse datasets representative of non-covalent interactions in biologically-relevant molecules. We further focus on hydrogen-bonded complexes---essential but challenging due to their directional nature---where datasets of DNA base pairs and amino acids yield an extremely encouraging 1.4 kcal/mol error. Finally, and as a first look, we consider IPML in denser systems: water clusters, supramolecular host-guest complexes, and the benzene crystal.Comment: 15 pages, 9 figure

Using all transverse degrees of freedom in quantum communications based on a generic mode sorter

The dimension of the state space for information encoding offered by the transverse structure of light is usually limited by the finite size of apertures. The widely used orbital angular momentum (OAM) number of Laguerre-Gaussian (LG) modes in free-space communications cannot achieve the theoretical maximum transmission capacity unless the radial degree of freedom is multiplexed into the protocol. While the methodology to sort the radial quantum number has been developed, the application of radial modes in quantum communications requires an additional ability to efficiently measure the superposition of LG modes in the mutually unbiased basis. Here we develop and implement a generic mode sorter that is capable of sorting the superposition of LG modes through the use of a mode converter. As a consequence, we demonstrate an 8-dimensional quantum key distribution experiment involving all three transverse degrees of freedom: spin, azimuthal, and radial quantum numbers of photons. Our protocol presents an important step towards the goal of reaching the capacity limit of a free-space link and can be useful to other applications that involve spatial modes of photons

A Comparison of Functional Models for Use in the Function-Failure Design Method

When failure analysis and prevention, guided by historical design knowledge, are coupled with product design at its conception, shorter design cycles are possible. By decreasing the design time of a product in this manner, design costs are reduced and the product will better suit the customer s needs. Prior work indicates that similar failure modes occur with products (or components) with similar functionality. To capitalize on this finding, a knowledge base of historical failure information linked to functionality is assembled for use by designers. One possible use for this knowledge base is within the Elemental Function-Failure Design Method (EFDM). This design methodology and failure analysis tool begins at conceptual design and keeps the designer cognizant of failures that are likely to occur based on the product s functionality. The EFDM offers potential improvement over current failure analysis methods, such as FMEA, FMECA, and Fault Tree Analysis, because it can be implemented hand in hand with other conceptual design steps and carried throughout a product s design cycle. These other failure analysis methods can only truly be effective after a physical design has been completed. The EFDM however is only as good as the knowledge base that it draws from, and therefore it is of utmost importance to develop a knowledge base that will be suitable for use across a wide spectrum of products. One fundamental question that arises in using the EFDM is: At what level of detail should functional descriptions of components be encoded? This paper explores two approaches to populating a knowledge base with actual failure occurrence information from Bell 206 helicopters. Functional models expressed at various levels of detail are investigated to determine the necessary detail for an applicable knowledge base that can be used by designers in both new designs as well as redesigns. High level and more detailed functional descriptions are derived for each failed component based on NTSB accident reports. To best record this data, standardized functional and failure mode vocabularies are used. Two separate function-failure knowledge bases are then created aid compared. Results indicate that encoding failure data using more detailed functional models allows for a more robust knowledge base. Interestingly however, when applying the EFDM, high level descriptions continue to produce useful results when using the knowledge base generated from the detailed functional models