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At least 145 records · Page 8

Quasi-Atomic Bond Analyses in the Sixth Period: I. Relativistic Accurate Atomic Minimal Basis Sets for the Elements Cesium to Radon

Full-valence relativistic accurate atomic minimal basis set (AAMBS) orbitals are developed for the sixth-row elements from cesium to radon, including the lanthanides. Saturated primitive atomic basis sets are developed and subsequently used to form the AAMBS orbitals. By use of a saturated basis, properties computed based on the AAMBS orbitals are basis set independent. In molecules, the AAMBS orbitals can be used to construct valence virtual orbitals (VVOs) that provide chemically meaningful abinitio lowest unoccupied molecular orbitals (LUMOs) with basis set independent orbital energies. The optimized occupied molecular orbitals complemented with the VVOs form a set of full-valence molecular orbitals. They can be transformed into a set of oriented quasi-atomic orbitals (QUAOs) that provide information on intramolecular bonding via an intrinsic density analysis. The development of the AAMBS for the sixth row is introduced in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Path integral suppression of badly behaved causal sets

Abstract Causal set theory is a discrete model of spacetime that retains a notion of causal structure. We understand how to construct causal sets that approximate a given spacetime, but most causal sets are not at all manifold-like, and must be dynamically excluded if something like our Universe is to emerge from the theory. Here we show that the most common of these ‘bad’ causal sets, the Kleitman–Rothschild orders, are strongly suppressed in the gravitational path integral, and we provide evidence that a large class of other ‘bad’ causal sets are similarly suppressed. It thus becomes plausible that continuum behavior could emerge naturally from causal set quantum theory.

Astronomy & Astrophysics↗

Optimal adjustment sets for causal query estimation in partially observed biomolecular networks

Abstract Causal query estimation in biomolecular networks commonly selects a ‘valid adjustment set’, i.e. a subset of network variables that eliminates the bias of the estimator. A same query may have multiple valid adjustment sets, each with a different variance. When networks are partially observed, current methods use graph-based criteria to find an adjustment set that minimizes asymptotic variance. Unfortunately, many models that share the same graph topology, and therefore same functional dependencies, may differ in the processes that generate the observational data. In these cases, the topology-based criteria fail to distinguish the variances of the adjustment sets. This deficiency can lead to sub-optimal adjustment sets, and to miss-characterization of the effect of the intervention. We propose an approach for deriving ‘optimal adjustment sets’ that takes into account the nature of the data, bias and finite-sample variance of the estimator, and cost. It empirically learns the data generating processes from historical experimental data, and characterizes the properties of the estimators by simulation. We demonstrate the utility of the proposed approach in four biomolecular Case studies with different topologies and different data generation processes. The implementation and reproducible Case studies are at https://github.com/srtaheri/OptimalAdjustmentSet.

59 BASIC BIOLOGICAL SCIENCES↗

SU-F-P-18: Development of the Technical Training System for Patient Set-Up Considering Rotational Correction in the Virtual Environment Using Three-Dimensional Computer Graphic Engine

Purpose: Patient set-up skills in radiotherapy treatment room have a great influence on treatment effect for image guided radiotherapy. In this study, we have developed the training system for improving practical set-up skills considering rotational correction in the virtual environment away from the pressure of actual treatment room by using three-dimensional computer graphic (3DCG) engine. Methods: The treatment room for external beam radiotherapy was reproduced in the virtual environment by using 3DCG engine (Unity). The viewpoints to perform patient set-up in the virtual treatment room were arranged in both sides of the virtual operable treatment couch to assume actual performance by two clinical staffs. The position errors to mechanical isocenter considering alignment between skin marker and laser on the virtual patient model were displayed by utilizing numerical values expressed in SI units and the directions of arrow marks. The rotational errors calculated with a point on the virtual body axis as the center of each rotation axis for the virtual environment were corrected by adjusting rotational position of the body phantom wound the belt with gyroscope preparing on table in a real space. These rotational errors were evaluated by describing vector outer product operations and trigonometric functions in the script for patient set-up technique. Results: The viewpoints in the virtual environment allowed individual user to visually recognize the position discrepancy to mechanical isocenter until eliminating the positional errors of several millimeters. The rotational errors between the two points calculated with the center point could be efficiently corrected to display the minimum technique mathematically by utilizing the script. Conclusion: By utilizing the script to correct the rotational errors as well as accurate positional recognition for patient set-up technique, the training system developed for improving patient set-up skills enabled individual user to indicate efficient positional correction methods easily.

60 APPLIED LIFE SCIENCES↗

On the Choice of a Distributed Basis Set in Calculations of Transition-Dipole Moments in the One-Determinant Approximation

The so-called “asymptotic projection technique” developed in previous papers of the authors is applied to the calculation of electronic transition-dipole moments (TDMs) in the one-determinant approximation between states of the same spin and spatial symmetry. The basic equations of the method and specific features of their application to a TDM calculation are briefly discussed. The attention focusses on the choice of a finite one-particle basis set. For this purpose, two possible algorithms for constructing distributed basis sets are proposed. In the first of them, the construction is based on minimization of the Hartree–Fock energy (E{sub HF}) with respect to nonlinear basis set parameters. In the second case, the parameters are determined by minimizing the functional E = E{sub HF} + E{sub MP2}, which includes the electron correlation through the second order of Møller–Plesset perturbation theory (Е{sub МР2}). On the whole, the results of calculations in both basis sets are in agreement with high-accuracy calculations performed by configuration interaction methods. The basis set adapted for E = E{sub HF} + E{sub MP2} significantly improves the accuracy as compared to the basis set of the first type.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Comparing Designed Training Sets to Optimize Multivariate Regression Models for Pr, Nd, and Nitric Acid Using Spectrophotometry

Chemometric regression models were developed for the quantification of praseodymium (Pr, 0–1000 µg/mL), neodymium (Nd, 0–1000 µg/mL), and nitric acid (HNO 3 , 0.1–5 M) using spectrophotometry. Designed calibration sets were composed of 20 samples each: 10 model points and 10 lack-of-fit (LOF) points. The D-optimal designs effectively minimized the number of samples required to build models, and each design resulted in similar prediction performance, suggesting that statistical design of experiments can provide a reliable framework for selecting training set samples in three-variable systems. Partial least squares regression (PLSR) models were validated against a one-factor-at-a-time validation set composed of 125 samples (three variables, five levels). The top PLS-1 models resulted in average percent root mean square error of prediction error values of 3.5%, 1.7%, and 1.2% for Pr(III), Nd(III), and HNO 3 , respectively. Power set augmentations of the model and LOF samples were investigated to optimize the number of training set samples. PLSR models built using just required model points (10) had similar predictive capabilities as models including the LOF points (20) but with fewer samples. The number of validation samples was also varied systematically to learn how many samples are needed to validate regression models. This work addresses long-standing questions in the field of chemometrics to help make this approach amenable to the near-real-time quantification of hazardous species in remote settings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Retrospective analysis of pulse oximeter alarm settings in an intensive care unit patient population

Background: The cacophony of alerts and alarms in a hospital produced by medical devices results in alarm fatigue. The pulse oximeter is one of the most common sources of alarms. One of the ways to reduce alarm rates is to adjust alarm settings at the bedside. This study is aimed to retrospectively examine individual pulse oximeter alarm settings on alarm rates and inter- and intra- patient variability. Methods: Nine hundred sixty-two previously collected intensive care unit (ICU) patient records were obtained from the Multiparameter Intelligent Monitoring in Intensive Care II Database (Beth Israel Deaconess Medical Center, Boston, MA). Inclusion criteria included patient records that contained SpO 2 trend data sampled at 1 Hz for at least 1 h and a matching clinical record. SpO 2 alarm rates were simulated by applying a range of thresholds (84, 86, 88, and 90 %) and delay times (10 to 60 s) to the SpO 2 data. Patient records with at least 12 h of SpO 2 data were examined for the variability in alarm rate over time. Results: Decreasing SpO 2 thresholds and increasing delay times resulted in decreased alarm rates. A limited number of patient records accounted for most alarms, and this number increased as alarm settings loosened (the top 10 % of patient records were responsible for 57.4 % of all alarms at an SpO 2 threshold of 90 % and 15 s delay and 81.6 % at an SpO 2 threshold of 84 % and 45 s delay). Alarm rates were not consistent over time for individual patients with periods of high and low alarms for all alarm settings. Conclusion: Pulse oximeter SpO 2 alarm rates are variable between patients and over time, and the alarm rate and the extent of inter- and intra-patient variability can be affected by the alarm settings. Personalized alarm settings for a patient’s current status may help to reduce alarm fatigue for nurses.

59 BASIC BIOLOGICAL SCIENCES↗

ARM Trajectories Data Set Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s ARM Trajectories Data Set (ARMTRAJ) Value-Added Product (VAP) provides trajectory data sets initialized at ARM deployment coordinates and configured using ARM data sets. The four trajectory data sets support aerosol, cloud, and planetary boundary-layer research. Trajectory calculations use the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model informed by the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) data set at its highest spatial resolution (~31 km). HYSPLIT also runs at multiple initial starting locations surrounding ARM deployments (in latitude/longitude and/or vertical coordinates), facilitating an ensemble for each sample in the data sets. The ensemble mean and variability reported in ARMTRAJ improve the fidelity and provide uncertainty estimates of trajectory coordinates, thermodynamic properties, and other output fields.

54 ENVIRONMENTAL SCIENCES↗

ARM Trajectories Data Set Value-Added Product Report

The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s ARM Trajectories Data Set (ARMTRAJ) Value-Added Product (VAP) provides trajectory data sets initialized at ARM deployment coordinates and configured using ARM data sets. The six trajectory data sets support aerosol, cloud, planetary boundary layer, and related research (aerosol-cloud interactions, etc.), as well as studies using ARM Aerial Facility (AAF) and tethered balloon system (TBS) measurements. Trajectory calculations use the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model informed by the European Centre for Medium-Range Weather Forecasts (ECMWF) fifth-generation atmospheric reanalysis (ERA5) data set at its highest spatial resolution (~31 km). HYSPLIT also runs at multiple initial starting locations surrounding ARM deployments (in latitude/longitude and/or vertical coordinates), facilitating an ensemble for each sample in the data sets. The ensemble mean and variability reported in ARMTRAJ improve the fidelity and provide uncertainty estimates of trajectory coordinates, thermodynamic properties, and other output fields.

54 ENVIRONMENTAL SCIENCES↗

Hexagonal multiple phase-and-amplitude-shift-keyed signal sets

Selection of a particular signal set array for a bandwidth-constrained multiple phase-and-amplitude-shift-keyed (MPASK) communication system for a linear additive Gaussian noise channel requires consideration of factors such as average and/or peak power vs symbol error probability, signal amplitude dynamic range, simplicity of generation and detection, and number of bit errors per symbol error (Gray code properties). A simple technique is presented for generating and optimally detecting the honeycomb (hexagonal) signal set, i.e., the signal set that has the tightest sphere-packing properties. The symbol and bit error probability performance of this set is compared to other two-dimensional signal sets that have been investigated in the literature, and is shown to be slightly superior from an average power standpoint. The paper concludes with a comparison of all of these signal sets from the standpoint of the factors listed above.

Simon, M. K.↗

The use of LANDSAT-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

The MSS sensor on LANDSAT 4 is, in certain performance aspects, different from those on LANDSATS 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of LANDSAT 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using LANDSAT 4 and LANDSAT 2 data (33.35 meters) and the temporal data set constructed from two LANDSAT 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Anderson, J. E.↗

Data management support for selected climate data sets using the climate data access system

The functional capabilities of the Goddard Space Flight Center (GSFC) Climate Data Access System (CDAS), an interactive data storage and retrieval system, and the archival data sets which this system manages are discussed. The CDAS manages several climate-related data sets, such as the First Global Atmospheric Research Program (GARP) Global Experiment (FGGE) Level 2-b and Level 3-a data tapes. CDAS data management support consists of three basic functions: (1) an inventory capability which allows users to search or update a disk-resident inventory describing the contents of each tape in a data set, (2) a capability to depict graphically the spatial coverage of a tape in a data set, and (3) a data set selection capability which allows users to extract portions of a data set using criteria such as time, location, and data source/parameter and output the data to tape, user terminal, or system printer. This report includes figures that illustrate menu displays and output listings for each CDAS function.

Reph, M. G.↗

Atlas of Archived Vegetation, Land-use and Seasonal Albedo Data Sets

Global digital data bases of natural vegetation and land use were compiled, for use in climate studies, at 1 deg resolution from over 100 published sources. A series of 6 data sets, derived from the original compilations, was prepared and archived on tape at the National Center for Atmospheric Research (NCAR) (Matthews, 1984). The first is a vegetation data set representing natural (pre-agricultural) vegetation based on the UNESCO classification system. The second, derived from the land-use compilation, is a cultivation-intensity data set defining the areal extent of presently-cultivated land in the 1 deg cells. The last four are integrated surface-albedo data sets (January, April, July, October) for snow-free conditions, incorporating natural-vegetation and cultivation characteristics from the vegetation and cultivation-intensity data sets. Each of these data sets covers the entire surface of the earth. They include non-zero data for permanent land only, including continental ice; water, including oceans and lakes, is zero. The present report includes maps, presented by continent, of the complete archived data, with the exception of Antarctica.

Matthews, E.↗

The use of Landsat-4 MSS digital data in temporal data sets and the evaluation of scene-to-scene registration accuracy

The MSS sensor on Landsat 4 is, in certain performance aspects, diferent from those of Landsats 1 through 3. These differences created some concern in the NASA research community as to whether individual data sets can be registered accurately enough to produce acceptable data sets for multitemporal data analysis. The use of Landsat 4 MSS digital data in temporal data sets is examined and a method is presented for estimating temporal registration accuracy based on the use of an X-Y digitizer and grey tone electrostatic plots. Results indicate that the RMS temporal registration errors are not significantly different from the temporal data sets generated using Landsat 4 and Landsat 2 data (33.35 meters) and the temporal data set constructed from two Landsat 2 data sets (33.61 meters). A derivation of the model used to evaluate the temporal registration is included.

Anderson, J. E.↗

High quality Gaussian basis sets for fourth-row atoms

Energy optimized Gaussian basis sets of triple-zeta quality for the atoms Rb-Xe have been derived. Two series of basis sets are developed: (24s 16p 10d) and (26s 16p 10d) sets which were expanded to 13d and 19p functions as the 4d and 5p shells become occupied. For the atoms lighter than Cd, the (24s 16p 10d) sets with triple-zeta valence distributions are higher in energy than the corresponding double-zeta distribution. To ensure a triple-zeta distribution and a global energy minimum, the (26s 16p 10d) sets were derived. Total atomic energies from the largest basis sets are between 198 and 284 (mu)E(sub H) above the numerical Hartree-Fock energies.

Partridge, Harry↗

An experimental methodology for a fuzzy set preference model

A flexible fuzzy set preference model first requires approximate methodologies for implementation. Fuzzy sets must be defined for each individual consumer using computer software, requiring a minimum of time and expertise on the part of the consumer. The amount of information needed in defining sets must also be established. The model itself must adapt fully to the subject's choice of attributes (vague or precise), attribute levels, and importance weights. The resulting individual-level model should be fully adapted to each consumer. The methodologies needed to develop this model will be equally useful in a new generation of intelligent systems which interact with ordinary consumers, controlling electronic devices through fuzzy expert systems or making recommendations based on a variety of inputs. The power of personal computers and their acceptance by consumers has yet to be fully utilized to create interactive knowledge systems that fully adapt their function to the user. Understanding individual consumer preferences is critical to the design of new products and the estimation of demand (market share) for existing products, which in turn is an input to management systems concerned with production and distribution. The question of what to make, for whom to make it and how much to make requires an understanding of the customer's preferences and the trade-offs that exist between alternatives. Conjoint analysis is a widely used methodology which de-composes an overall preference for an object into a combination of preferences for its constituent parts (attributes such as taste and price), which are combined using an appropriate combination function. Preferences are often expressed using linguistic terms which cannot be represented in conjoint models. Current models are also not implemented an individual level, making it difficult to reach meaningful conclusions about the cause of an individual's behavior from an aggregate model. The combination of complex aggregate models and vague linguistic preferences has greatly limited the usefulness and predictive validity of existing preference models. A fuzzy set preference model that uses linguistic variables and a fully interactive implementation should be able to simultaneously address these issues and substantially improve the accuracy of demand estimates. The parallel implementation of crisp and fuzzy conjoint models using identical data not only validates the fuzzy set model but also provides an opportunity to assess the impact of fuzzy set definitions and individual attribute choices implemented in the interactive methodology developed in this research. The generalized experimental tools needed for conjoint models can also be applied to many other types of intelligent systems.

Turksen, I. B.↗

Development of a Simulated Data Set for the SeaWiFS Mission

A realistic simulated data set is essential for mission readiness preparations and can potentially assist in all phases of ground support for a future mission. Such a data set was created for the Sea-viewing Wide Field-of-view Sensor (SeaWiFS), a global ocean color mission due for launch in 1997. This data set incorporates a representation of virtually every known aspect of the flight mission. Thus, it provides a high fidelity data set for testing most phases of the ground system, Including data processing, data transfers, calibration and validation, quality control, and mission operations. The data set is constructed for a seven-day period, March 25-31, 1994. Specific features of the data set: it includes Global Area Coverage (GAC), recorded Local Area Coverage (LAC), and real-time High Resolution Picture Transmission (HRFIT) data for the seven-day period; it includes a realistic orbit which is propagated using a Brouwer-Lyddane model with drag; the data correspond to a command schedule based on the orbit for this seven-day period; it includes total (at-satellite) radiances for ocean, land, clouds, and ice; it utilizes a high-resolution land/sea mask; it includes actual SeaWiFS spectral responses; it includes the actual sensor saturation responses; it is formatted according to current onboard data structures; and it includes corresponding telemetry (instrument and spacecraft) data. The methods are described and some examples of the output are given.

Gregg, Watson W.↗

Large Atomic Natural Orbital Basis Sets for the First Transition Row Atoms

Large atomic natural orbital (ANO) basis sets are tabulated for the Sc to Cu. The primitive sets are taken from the large sets optimized by Partridge, namely (21s 13p 8d) for Sc and Ti and (20s 12p 9d) for V to Cu. These primitive sets are supplemented with three p, one d, six f, and four g functions. The ANO sets are derived from configuration interaction density matrices constructed as the average of the lowest states derived from the 3d(sup n)4s(sup 2) and 3d(sup n+1)4s(sup 1) occupations. For Ni, the 1S(3d(sup 10)) state is included in the averaging. The choice of basis sets for molecular calculations is discussed.

Bauschlicher, Charles W., Jr.↗