Book Review: Religion in a New Key

A review of M. Darrol Bryant\u27s Religion in a New Key

Supply Chain Managers and Risk Behavior: Testing the Sitkin and Pablo Model

The frequency of supply chain disruptions is increasing and the resulting costs amplify with the growth of supply chain density and complexity. Supply chain managers serve a pivotal role in ensuring continued firm competitiveness and success. Having the right person whose risk preferences, propensity to take risks, and history dealing with risks match the needs of the company is important. A foundational study performed by Sitkin and Pablo (1992) proposed a conceptual model focused on specific predictors of risk behavior from the individual, organizational, and problem-related perspectives. Questions still remain to the validity of the model given that it has not been fully tested. With the gaps in the current literature, the purpose of this study is to examine (1) does the Sitkin and Pablo (1992) model serve as a valid fit to measure supply chain manager’s propensity and perception of risk and (2) how does the managerial disruption perspective affects the risk perceptions/risk behavior relationship? The findings of the study will contribute to theoretical development through the expansion of the managerial disruption perspective on risk perceptions and through addressing the mediating relationship of risk propensity and risk perception on risk behaviors. Empirical testing is performed using a sample of supply chain managers with statistical analysis of the study results

Survey of instrumental programs in nine medium-sized towns within commuting distance from New York City

Thesis (M.M.E.)--Boston Universit

Interpreting the Earth's time varying geopotential as observed from space and comparisons to global models of hydrologic transport

textMeasurements of temporal changes in Earthís gravitational field were measured using six years of satellite laser ranging (SLR) to Lageos-1 and Lagoes-2 and the results were compared to geophysical models of mass variability for the atmosphere, ocean, and continental hydrology. Annual estimates of spherical harmonic gravity coefficients (degree and order four expansion) derived from the SLR observations when compared to combinations of the mass models had degree correlations that generally exceeded the 90% confidence limit and agreed to about the 1 mm level in terms of geoid height anomaly. The Gravity Recovery and Climate Experiment (GRACE) is measuring Earthís gravitational field approximately every month at spatial scales of a few hundred kilometers. In order to achieve smaller temporal and spatial scales, it is necessary to account for the effects of short period, non-tidal, mass variability which was not previously included in other gravity determinations. Orbital simulations of GRACE showed that the highest degrees were impacted the most by unmodeled variability in the atmosphere, oceans, and continental hydrology (a factor of ~20 increase in degree error in the case of the atmosphere). The use of approximate models gave the greatest reduction in aliasing error for the mid-degrees and higher; however, the lowest degrees (~2-5) were dominated by the sensitivity of the GRACE processing system to systematic error. GRACE data processing that used a combined atmosphere-ocean de-aliasing (AOD) model showed improvement in the gravity estimates consistent with the simulations: the shorter spatial wavelengths (higher degrees) were improved while the longest spatial wavelengths (particularly important for time-variable gravity studies) were relatively unaffected. Monthly gravity solutions from GRACE resolved features on the order of 2-3 mm geoid height anomaly when smoothed to 400-km spatial scales. Comparisons with the Global Land Data Assimilation System (GLDAS) terrestrial water storage model indicated a high degree of correlation up to spatial wavelengths of 600 km or larger; a significant improvement over the spatial and temporal scales obtained with SLR observations. However, temporal variability in the degree 2 coefficients, particularly the zonal, seemed to be better resolved by SLR observations than by GRACE observations.Aerospace Engineering and Engineering Mechanic

Structural Neuroimaging of Anorexia Nervosa: Future Directions in the Quest for Mechanisms Underlying Dynamic Alterations.

Anorexia nervosa (AN) is a serious eating disorder characterized by self-starvation and extreme weight loss. Pseudoatrophic brain changes are often readily visible in individual brain scans, and AN may be a valuable model disorder to study structural neuroplasticity. Structural magnetic resonance imaging studies have found reduced gray matter volume and cortical thinning in acutely underweight patients to normalize following successful treatment. However, some well-controlled studies have found regionally greater gray matter and persistence of structural alterations following long-term recovery. Findings from diffusion tensor imaging studies of white matter integrity and connectivity are also inconsistent. Furthermore, despite the severity of AN, the number of existing structural neuroimaging studies is still relatively low, and our knowledge of the underlying cellular and molecular mechanisms for macrostructural brain changes is rudimentary. We critically review the current state of structural neuroimaging in AN and discuss the potential neurobiological basis of structural brain alterations in the disorder, highlighting impediments to progress, recent developments, and promising future directions. In particular, we argue for the utility of more standardized data collection, adopting a connectomics approach to understanding brain network architecture, employing advanced magnetic resonance imaging methods that quantify biomarkers of brain tissue microstructure, integrating data from multiple imaging modalities, strategic longitudinal observation during weight restoration, and large-scale data pooling. Our overarching objective is to motivate carefully controlled research of brain structure in eating disorders, which will ultimately help predict therapeutic response and improve treatment

Cloning of a Carcinoembryonic Antigen Gene Family Member Expressed in Leukocytes of Chronic Myeloid Leukemia Patients and Bone Marrow

The carcinoembryonic antigen (CEA) gene family belongs to the immunoglobulin superfamily and can be subdivided into the CEA and pregnancy-specific glycoprotein subgroups. The basic structure of the encoded proteins consists of, in addition to a leader, one IgV-like and 2, 3, or 6 IgC-like domains. These domains are followed by varying COOH-terminal regions responsible for secretion, transmembrane anchoring, or insertion into the membrane by a glycosyl phosphatidylinositol tail. Here we report on the characterization of CGM6, a new member of the CEA gene subgroup, by complementary DNA cloning. The deduced coding region comprises 349 amino acids and consists of a leader, one IgV-like, two IgC-like domains, and a hydrophobic region, which is replaced by a glycosyl phosphatidylinositol moiety in the mature protein. CGM6 transcripts were only found thus far in leukocytes of chronic myeloid leukemia patients, in normal bone marrow, and in marginal amounts in normal granulocytes. The CGM6 gene product might, therefore, represent a myeloid marker. Analyses of CGM6 protein-expressing HeLa transfectants with monoclonal antibodies strongly indicate that the CGM6 gene codes for the CEA family member NCA-95

Simulation tools for ultrasonic inspections of multi-layer armor panels

Some armor panels are fabricated from several layers of material including ceramics, graphite and∕or glass composites, and rubber. This multi‐layer makeup can complicate UT inspection, since many possible sound paths (including intra‐layer reverberations) can contribute to observed UT signals. At last year’s QNDE conference we reported on baseline property measurements (density, sound speed, attenuation, etc.) for the constituent layers of one prototype panel, and we discussed how that information was used to design an ultrasonic inspection to look for disbonding at interfaces. We now report on progress to develop better simulation tools for armor panel inspections. In particular we consider normal‐incidence pulse∕echo inspections and use a paraxial beam model to predict time‐domain signals for unflawed panels and those containing large delaminations. The model uses the frequency‐dependent baseline property data as inputs, and treats beam spread and focusing effects. We describe the modeling approach and present comparisons of model predictions to the experimental data gathered last year during inspections of five‐layer armor panels