Decisions, Decisions: Noise and its Effects on Integral Monte Carlo Algorithms

In the present paper we examine the effects of noise on Monte Carlo algorithms, a problem raised previously by Kennedy and Kuti (Phys. Rev. Lett. {\bf 54}, 2473 (1985)). We show that the effects of introducing unbiased noise into the acceptance/rejection phase of the conventional Metropolis approach are surprisingly modest, and, to a significant degree, largely controllable. We present model condensed phase numerical applications to support these conclusions.Comment: Chemical Physics Letters, 12 pages text, 5 figure

The Construction of Double-Ended Classical Trajectories

In the present paper we describe relaxation methods for constructing double-ended classical trajectories. We illustrate our approach with an application to a model anharmonic system, the Henon-Heiles problem. Trajectories for this model exhibit a number of interesting energy-time relationships that appear to be of general use in characterizing the dynamics.Comment: (12 pages, submitted to Chemical Physics Letters. Figures are too large for convenient e-mail access. they are available via anonymous ftp on willie.chem.brown.edu and reside in the directory pub/chem-ph/9407 as the compressed tar file 9407001.tar.Z. If you have difficulty retrieving the figures, please contact J. Doll ([email protected]) for assistance

Global geometry optimization of clusters using a growth strategy optimized by a genetic algorithm

A new strategy for global geometry optimization of clusters is presented. Important features are a restriction of search space to favorable nearest-neighbor distance ranges, a suitable cluster growth representation with diminished correlations, and easy transferability of the results to larger clusters. The strengths and possible limitations of the method are demonstrated for Si10 using an empirical potential.Comment: accepted by Chem.Phys.Letters; 10 pages text, plus 3 pages for Title, abstract, and figure caption; figures 1a and 1

Convergence of Quantum Annealing with Real-Time Schrodinger Dynamics

Convergence conditions for quantum annealing are derived for optimization problems represented by the Ising model of a general form. Quantum fluctuations are introduced as a transverse field and/or transverse ferromagnetic interactions, and the time evolution follows the real-time Schrodinger equation. It is shown that the system stays arbitrarily close to the instantaneous ground state, finally reaching the target optimal state, if the strength of quantum fluctuations decreases sufficiently slowly, in particular inversely proportionally to the power of time in the asymptotic region. This is the same condition as the other implementations of quantum annealing, quantum Monte Carlo and Green's function Monte Carlo simulations, in spite of the essential difference in the type of dynamics. The method of analysis is an application of the adiabatic theorem in conjunction with an estimate of a lower bound of the energy gap based on the recently proposed idea of Somma et. al. for the analysis of classical simulated annealing using a classical-quantum correspondence.Comment: 6 pages, minor correction

Quantum Field Induced Orderings in Fully Frustrated Ising Spin Systems

We study ordering mechanisms which are induced by the quantum fluctuation in fully frustrated Ising spin systems. Since there are many degenerated states in frustrated systems, "order by thermal disorder" often takes place due to a kind of entropy effect. To consider "order by quantum disorder" in fully frustrated Ising spin systems, we apply transverse field as quantum fluctuation. There exists a ferromagnetic correlation in each sublattice. The sublattice correlation at zero temperature is enlarged due to transverse field. The quantum fluctuation enhances the solid order at zero temperatures. This is an example of quantum field induced ordering in fully frustrated systems. We also study a case in which the transverse field induces a reentrant behavior as another type of order by quantum disorder, and compare correspondent cases in the classical systems.Comment: 3 pages, 4 figures, submitted to Proceedings of Symposia "Nanoscience and Quantum Physics

Determining collagen distribution in articular cartilage using contrast-enhanced micro-computed tomography

Objective: Collagen distribution within articular cartilage (AC) is typically evaluated from histological sections, e.g., using collagen staining and light microscopy (LM). Unfortunately, all techniques based on histological sections are time-consuming, destructive, and without extraordinary effort, limited to two dimensions. This study investigates whether phosphotungstic acid (PTA) and phosphomolybdic acid (PMA), two collagen-specific markers and X-ray absorbers, could (1) produce contrast for AC X-ray imaging or (2) be used to detect collagen distribution within AC. Method: We labeled equine AC samples with PTA or PMA and imaged them with micro-computed tomography (micro-CT) at pre-defined time points 0, 18, 36, 54, 72, 90, 180, 270 h during staining. The micro-CT image intensity was compared with collagen distributions obtained with a reference technique, i.e., Fourier-transform infrared imaging (FTIRI). The labeling time and contrast agent producing highest association (Pearson correlation, BlandeAltman analysis) between FTIRI collagen distribution and micro-CT -determined PTA distribution was selected for human AC. Results: Both, PTA and PMA labeling permitted visualization of AC features using micro-CT in non-calcified cartilage. After labeling the samples for 36 h in PTA, the spatial distribution of X-ray attenuation correlated highly with the collagen distribution determined by FTIRI in both equine (mean +/- S.D. of the Pearson correlation coefficients, r = 0.96 +/- 0.03, n = 12) and human AC (r = 0.82 +/- 0.15, n = 4). Conclusions: PTA-induced X-ray attenuation is a potential marker for non-destructive detection of AC collagen distributions in 3D. This approach opens new possibilities in development of non-destructive 3D histopathological techniques for characterization of OA. (C) 2015 The Authors. Published by Elsevier Ltd and Osteoarthritis Research Society International.Peer reviewe

Lessons learned while starting multi-institutional genetics research in diverse populations: A report from the Clinical Sequencing Evidence-Generating Research (CSER) consortium

Background: Increasing diversity in clinical trial participation is necessary to improve health outcomes and requires addressing existing social, structural, and geographic barriers. The Clinical Sequencing Evidence-Generating Research Consortium (CSER) included six research projects to enroll historically underrepresented/underserved (UR/US) populations in clinical genomics research. Delays and project re-designs emerged shortly after work began. Understanding common experiences of these projects may inform future trial implementation. Methods: Semi-structured interviews with six CSER principal investigators and seven project managers were performed. An interview guide included questions of research/clinical infrastructure, logistics across sites, language, communication, and allocation of grant-related resources. Interviews were recorded, transcribed verbatim; transcripts were analyzed using inductive coding, thematic analysis and consensus building. Results: All projects collaborating with new clinical sub-sites to recruit UR/US populations. Refining trial logistics continued long after enrollment for all projects. Themes of challenges included: sub-site customization for workflow and genetics support, conflicting input from participant advisory groups and approval bodies, developing research personnel, complex data management structures, and external changes (e.g. subcontractors ending contracts) that required redesign. Themes of beneficial lessons included: domains with prior experience were easier, develop project champions at each sub-site, structure communication within the research team, and simplify research design when possible. Conclusions: The operational aspects of expanding clinical research into novel sub-sites are significant and require investment of time and resources. The themes arising from these interviews suggest priority areas for more quantitative analyses in the future including multi-institutional approval policies and processes, data management structures, and incremental research complexity

Information-seeking preferences in diverse patients receiving a genetic testing result in the Clinical Sequencing Evidence-Generating Research (CSER) study

PurposeAccurate and understandable information after genetic testing is critical for patients, family members, and professionals alike.MethodsAs part of a cross-site study from the Clinical Sequencing Evidence-Generating Research consortium, we investigated the information-seeking practices among patients and family members at 5 to 7 months after genetic testing results disclosure, assessing the perceived utility of a variety of information sources, such as family and friends, health care providers, support groups, and the internet.ResultsWe found that individuals placed a high value on information obtained from genetics professionals and health care workers, independent of genetic testing result case classifications as positive, inconclusive, or negative. The internet was also highly utilized and ranked. Study participants rated some information sources as more useful for positive results compared with inconclusive or negative outcomes, emphasizing that it may be difficult to identify helpful information for individuals receiving an uncertain or negative result. There were few data from non-English speakers, highlighting the need to develop strategies to reach this population.ConclusionOur study emphasizes the need for clinicians to provide accurate and comprehensible information to individuals from diverse populations after genetic testing

Neurology

Contains reports on eleven research projects.U.S. Air Force (AF49(638)-1130)Army Chemical Corps (DA-18-108-405-Cml-942)U.S. Public Health Service (B-3055)National Science Foundation (Grant G-16526)U.S. Public Health Service (B-3090)U.S. Air Force (AF33(616)-7588)Office of Naval Research (Nonr-1841(70)