A connection between the Camassa-Holm equations and turbulent flows in channels and pipes

In this paper we discuss recent progress in using the Camassa-Holm equations to model turbulent flows. The Camassa-Holm equations, given their special geometric and physical properties, appear particularly well suited for studying turbulent flows. We identify the steady solution of the Camassa-Holm equation with the mean flow of the Reynolds equation and compare the results with empirical data for turbulent flows in channels and pipes. The data suggests that the constant $\alpha$ version of the Camassa-Holm equations, derived under the assumptions that the fluctuation statistics are isotropic and homogeneous, holds to order $\alpha$ distance from the boundaries. Near a boundary, these assumptions are no longer valid and the length scale $\alpha$ is seen to depend on the distance to the nearest wall. Thus, a turbulent flow is divided into two regions: the constant $\alpha$ region away from boundaries, and the near wall region. In the near wall region, Reynolds number scaling conditions imply that $\alpha$ decreases as Reynolds number increases. Away from boundaries, these scaling conditions imply $\alpha$ is independent of Reynolds number. Given the agreement with empirical and numerical data, our current work indicates that the Camassa-Holm equations provide a promising theoretical framework from which to understand some turbulent flows.Comment: tex file, 29 pages, 4 figures, Physics of Fluids (in press

Secular trends in work disability and its relationship to musculoskeletal pain and mental health: a time-trend analysis using five cross-sectional surveys (2002-2010) in the general population.

OBJECTIVES: International evidence suggests that rates of inability to work because of illness can change over time. We hypothesised that one reason for this is that the link between inability to work and common illnesses, such as musculoskeletal pain and mental illness, may also change over time. We have investigated this in a study based in one UK district. METHODS: Five population surveys (spanning 2002-2010) of working-age people aged >50 years and ≤65 years were used. Work disability was defined as a single self-reported item 'not working due to ill-health'. Presence of moderate-severe depressive symptoms was identified from the Mental Component Score of the Short Form-12, and pain from a full-body manikin. Data were analysed with multivariable logistic regression. RESULTS: The proportion of people reporting work disability across the surveys declined, from 17.0% in 2002 to 12.1% in 2010. Those reporting work disability, one-third reported regional pain, one-half widespread pain (53%) and two-thirds moderate-severe depressive symptoms (68%). Both factors were independently associated with work disability; their co-occurrence was associated with an almost 20-fold increase in the odds of reporting work disability compared with those with neither condition. CONCLUSIONS: The association of work disability with musculoskeletal pain was stable over time; depressive symptoms became more prominent in persons reporting work disability, but overall prevalence of work disability declined. The frequency and impact of both musculoskeletal pain and depression highlight the need to move beyond symptom-directed approaches towards a more comprehensive model of health and vocational advice for people unable to work because of illness

Phase-Control of Photoabsorption in Optically Dense Media

We present a self-consistent theory, as well as an illustrative application to a realistic system, of phase control of photoabsorption in an optically dense medium. We demonstrate that, when propagation effects are taken into consideration, the impact on phase control is significant. Independently of the value of the initial phase difference between the two fields, over a short scaled distance of propagation, the medium tends to settle the relative phase so that it cancels the atomic excitation. In addition, we find some rather unusual behavior for an optically thin layer.Comment: 5 pages, 3 figures, submitted to PR

Landmark Tracking in Liver US images Using Cascade Convolutional Neural Networks with Long Short-Term Memory

This study proposed a deep learning-based tracking method for ultrasound (US) image-guided radiation therapy. The proposed cascade deep learning model is composed of an attention network, a mask region-based convolutional neural network (mask R-CNN), and a long short-term memory (LSTM) network. The attention network learns a mapping from a US image to a suspected area of landmark motion in order to reduce the search region. The mask R-CNN then produces multiple region-of-interest (ROI) proposals in the reduced region and identifies the proposed landmark via three network heads: bounding box regression, proposal classification, and landmark segmentation. The LSTM network models the temporal relationship among the successive image frames for bounding box regression and proposal classification. To consolidate the final proposal, a selection method is designed according to the similarities between sequential frames. The proposed method was tested on the liver US tracking datasets used in the Medical Image Computing and Computer Assisted Interventions (MICCAI) 2015 challenges, where the landmarks were annotated by three experienced observers to obtain their mean positions. Five-fold cross-validation on the 24 given US sequences with ground truths shows that the mean tracking error for all landmarks is 0.65+/-0.56 mm, and the errors of all landmarks are within 2 mm. We further tested the proposed model on 69 landmarks from the testing dataset that has a similar image pattern to the training pattern, resulting in a mean tracking error of 0.94+/-0.83 mm. Our experimental results have demonstrated the feasibility and accuracy of our proposed method in tracking liver anatomic landmarks using US images, providing a potential solution for real-time liver tracking for active motion management during radiation therapy

Understanding surfaces and buried interfaces of polymer materials at the molecular level using sum frequency generation vibrational spectroscopy

This paper reviews recent progress in the studies on polymer surfaces/interfaces using sum frequency generation (SFG) vibrational spectroscopy. SFG theory, technique, and some experimental details have been presented. The review is focused on the SFG studies on buried interfaces involving polymer materials, such as polymer–water interfaces and polymer–polymer interfaces. Molecular interactions between polymer surfaces and adhesion promoters as well as biological molecules such as proteins and peptides have also been elucidated using SFG. This review demonstrates that SFG is a powerful technique to characterize molecular level structural information of complicated polymer surfaces and interfaces in situ . Copyright © 2006 Society of Chemical IndustryPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/56019/1/2201_ftp.pd

The dynamic crossover in water does not require bulk water

Many of the anomalous properties of water may be explained by invoking a second critical point that terminates the coexistence line between the low- and high-density amorphous states in the liquid. Direct experimental evidence of this point, and the associated polyamorphic liquid–liquid transition, is elusive as it is necessary for liquid water to be cooled below its homogeneous-nucleation temperature. To avoid crystallization, water in the eutectic LiCl solution has been studied but then it is generally considered that “bulk” water cannot be present. However, recent computational and experimental studies observe cooperative hydration in which case it is possible that sufficient hydrogen-bonded water is present for the essential characteristics of water to be preserved. For femtosecond optical Kerr-effect and nuclear magnetic resonance measurements, we observe in each case a fractional Stokes–Einstein relation with evidence of the dynamic crossover appearing near 220 K and 250 K respectively. Spectra obtained in the glass state also confirm the complex nature of the hydrogen-bonding modes reported for neat room-temperature water and support predictions of anomalous diffusion due to “worm-hole” structure

Cross-validation of the Work Organization Assessment Questionnaire across genders: a study in the Australian health care sector

Objectives The main aim of this study was to examine the measurement invariance of the Work Organisation Assessment Questionnaire (WOAQ) across genders in a group of healthcare employees, using bifactor modelling. There is a very limited research that uses invariance testing of bifactor models, despite their usefulness. Establishing validity of the WOAQ in this way is important for demonstrating its relevance for both males and females. Methods A bifactor modelling procedure was used here to examine the validity of the WOAQ with a sample of 946 paramedics employed in a large Australian organization in the healthcare sector. Results The results of this study show that the WOAQ has good psychometric properties across genders in healthcare settings. In addition, there were significant mean differences between males and females in their perceptions of ‘quality of relationships with colleagues’, and ‘reward and recognition’. There were no differences between males and females on the remaining factors: ‘quality of relationships with the management’, ‘quality of relationships with colleagues’, and ‘quality of the physical environment’. Conclusions The use of bifactor modelling to establish the cross-validity of the WOAQ across male and female paramedics adds to evidence for the measure’s good psychometric properties. The findings add to those of previous research that has used higher order Confirmatory Factor Analysis (CFA). Moreover, mean differences between males and females were found to be significant in two of the five WOAQ subscales. These findings have practical implications for healthcare organizations, in terms of assessing work characteristics and developing activities to support the health and well-being of their employees

Evasion of anti-growth signaling: a key step in tumorigenesis and potential target for treatment and prophylaxis by natural compounds

The evasion of anti-growth signaling is an important characteristic of cancer cells. In order to continue to proliferate, cancer cells must somehow uncouple themselves from the many signals that exist to slow down cell growth. Here, we define the anti-growth signaling process, and review several important pathways involved in growth signaling: p53, phosphatase and tensin homolog (PTEN), retinoblastoma protein (Rb), Hippo, growth differentiation factor 15 (GDF15), AT-rich interactive domain 1A (ARID1A), Notch, insulin-like growth factor (IGF), and Krüppel-like factor 5 (KLF5) pathways. Aberrations in these processes in cancer cells involve mutations and thus the suppression of genes that prevent growth, as well as mutation and activation of genes involved in driving cell growth. Using these pathways as examples, we prioritize molecular targets that might be leveraged to promote anti-growth signaling in cancer cells. Interestingly, naturally-occurring phytochemicals found in human diets (either singly or as mixtures) may promote anti-growth signaling, and do so without the potentially adverse effects associated with synthetic chemicals. We review examples of naturally-occurring phytochemicals that may be applied to prevent cancer by antagonizing growth signaling, and propose one phytochemical for each pathway. These are: epigallocatechin-3-gallate (EGCG) for the Rb pathway, luteolin for p53, curcumin for PTEN, porphyrins for Hippo, genistein for GDF15, resveratrol for ARID1A, withaferin A for Notch and diguelin for the IGF1-receptor pathway. The coordination of anti-growth signaling and natural compound studies will provide insight into the future application of these compounds in the clinical setting

Exploring What Factors Mediate Treatment Effect: Example of the STarT Back Study High-Risk Intervention

Interventions developed to improve disability outcomes for low back pain (LBP) often show only small effects. Mediation analysis was used to investigate what led to the effectiveness of the STarT Back trial, a large primary care-based trial that treated patients consulting with LBP according to their risk of a poor outcome. The high-risk subgroup, randomized to receive either psychologically-informed physiotherapy (n = 93) or current best care (n = 45), was investigated to explore pain-related distress and pain intensity as potential mediators of the relationship between treatment allocation and change in disability. Structural equation modeling was used to generate latent variables of pain-related distress and pain intensity from measures used to identify patients at high risk (fear-avoidance beliefs, depression, anxiety, and catastrophizing thoughts). Outcome was measured using the Roland–Morris Disability Questionnaire. Change in pain-related distress and pain intensity were found to have a significant mediating effect of .25 (standardized estimate, bootstrapped 95% confidence interval, .09–.39) on the relationship between treatment group allocation and change in disability outcome. This study adds to the evidence base of treatment mediation studies in pain research and the role of distress in influencing disability outcome in those with complex LBP. Perspective Mediation analysis using structural equation modeling found that change in pain-related distress and pain intensity mediated treatment effect in the STarT Back trial. This type of analysis can be used to gain further insight into how interventions work, and lead to the design of more effective interventions in future