Influence of the Yukon River on the Bering Sea

The distribution of near-surface, turbid water, discharged by the Yukon River, was studied based on analysis of satellite imagery. The interannual analyses indicates that the net flow of near-surface, turbid water is northward of the delta across the entrance to Norton Sound. Only turbid water to the east enters Norton Sound and consists of 25% of the total area. Approximately 10% of the water circulates into the sound along the southern coast and is lost to view in the vicinity of Unalakleet. Suspended sediments transported by this southern circulation are primarily deposited along the southern coast. Three distinct zones within the turbid water were identified based on relative brightness levels. These zones appear to be primarily related to differences in suspended-sediment concentrations and position of the sediments in the water column. The extent of turbid water varies seasonally. It is most extensive June through October even though discharge of the Yukon River decreases substantially after July

A comparative analysis of graphical interaction and logistic regression modelling: self-care and coping with a chronic illness in later life

Quantitative research especially in the social, but also in the biological sciences has been limited by the availability and applicability of analytic techniques that elaborate interactions among behaviours, treatment effects, and mediating variables. This gap has been filled by a newly developed statistical technique, known as graphical interaction modelling. The merit of graphical models for analyzing highly structured data is explored in this paper by an empirical study on coping with a chronic condition as a function of interrelationships between three sets of factors. These include background factors, illness context factors and four self--care practices. Based on a graphical chain model, the direct and indirect dependencies are revealed and discussed in comparison to the results obtained from a simple logistic regression model ignoring possible interaction effects. Both techniques are introduced from a more tutorial point of view instead of going far into technical details

Shell Model Monte Carlo Methods

We review quantum Monte Carlo methods for dealing with large shell model problems. These methods reduce the imaginary-time many-body evolution operator to a coherent superposition of one-body evolutions in fluctuating one-body fields; the resultant path integral is evaluated stochastically. We first discuss the motivation, formalism, and implementation of such Shell Model Monte Carlo (SMMC) methods. There then follows a sampler of results and insights obtained from a number of applications. These include the ground state and thermal properties of {\it pf}-shell nuclei, the thermal and rotational behavior of rare-earth and $\gamma$-soft nuclei, and the calculation of double beta-decay matrix elements. Finally, prospects for further progress in such calculations are discussed

Design and fabrication of the NASA HL-20 full scale research model

A full-scale engineering model of the HL-20 Personnel Launch System (PLS) was constructed for systems and human factors evaluation. Construction techniques were developed to enable the vehicle to be constructed with a minimum of time and cost. The design and construction of the vehicle are described

Association of prior depressive symptoms and suicide attempts with subsequent victimisation - analysis of population-based data from the Adult Psychiatric Morbidity Survey

Background: Symptoms of mental disorder, particularly schizophrenia, predispose to victimisation. Much less is known about the relationship between depressive symptoms and later victimisation in the general population, the influence of these symptoms on types of subsequent victimisation, or the role of symptom severity. We investigated this in nationally representative data from the UK. Methods: Data were from the Adult Psychiatric Morbidity Survey 2007. Multivariable logistic regressions estimated association between: a. prior depressive symptoms, and b. prior depressive symptoms with suicide attempt, and types of more recent victimisation. Gender-specific associations were estimated using multiplicative interactions. Results: Prior depressive symptoms were associated with greater odds of any recent intimate partner violence (IPV), emotional IPV, sexual victimisation, workplace victimisation, any victimisation, and cumulative victimisation (adjusted odds ratio (aOR) for increasing types of recent victimisation: 1.47, 95% confidence interval (CI): 1.14, 1.89). Prior depressive symptoms with suicide attempt were associated with any recent IPV, emotional IPV, any victimisation, and cumulative victimisation (aOR for increasing types of recent victimisation: 2.33, 95%: 1.22, 4.44). Limitations: Self-reported recalled data on previous depressive symptoms, may have limited accuracy. Small numbers of outcomes for some comparisons resulted in imprecision of these estimates. Conclusion: Aside from severe mental illness such as schizophrenia, previous depressive symptoms in the general population are associated with greater subsequent victimisation. Men and women with prior depressive symptoms may be vulnerable to a range of types of victimisation, and may benefit from interventions to reduce this vulnerability

Shell-Model Monte Carlo Simulations of BCS-BEC Crossover in Few-Fermion Systems

We study a trapped system of fermions with a zero-range two-body interaction using the shell-model Monte Carlo method, providing {\em ab initio} results for the low particle number limit where mean-field theory is not applicable. We present results for the $N$-body energies as function of interaction strength, particle number, and temperature. The subtle question of renormalization in a finite model space is addressed and the convergence of our method and its applicability across the BCS-BEC crossover is discussed. Our findings indicate that very good quantitative results can be obtained on the BCS side, whereas at unitarity and in the BEC regime the convergence is less clear. Comparison to N=2 analytics at zero and finite temperature, and to other calculations in the literature for $N>2$ show very good agreement.Comment: 6 pages, 5 figures, Revtex4, final versio

Image reconstruction in fluorescence molecular tomography with sparsity-initialized maximum-likelihood expectation maximization

We present a reconstruction method involving maximum-likelihood expectation maximization (MLEM) to model Poisson noise as applied to fluorescence molecular tomography (FMT). MLEM is initialized with the output from a sparse reconstruction-based approach, which performs truncated singular value decomposition-based preconditioning followed by fast iterative shrinkage-thresholding algorithm (FISTA) to enforce sparsity. The motivation for this approach is that sparsity information could be accounted for within the initialization, while MLEM would accurately model Poisson noise in the FMT system. Simulation experiments show the proposed method significantly improves images qualitatively and quantitatively. The method results in over 20 times faster convergence compared to uniformly initialized MLEM and improves robustness to noise compared to pure sparse reconstruction. We also theoretically justify the ability of the proposed approach to reduce noise in the background region compared to pure sparse reconstruction. Overall, these results provide strong evidence to model Poisson noise in FMT reconstruction and for application of the proposed reconstruction framework to FMT imaging