Detecting scene changes using synthetic aperture radar interferometry

Copyright © 2006 IEEEIn repeat-pass interferometric synthetic aperture radar (SAR), man-made scene disturbances are commonly detected by identifying changes in the mean backscatter power of the scene or by identifying regions of low coherence. Change statistics such as the sample mean backscatter-power ratio and the sample coherence, however, are susceptible to high false-alarm rates unless the change in the mean backscatter power is large or there is sufficient contrast in scene coherence between the changed and unchanged regions of the image pair. Furthermore, as the sample mean backscatter-power ratio and sample coherence measure different properties of a SAR image pair, both change statistics need to be considered to properly characterize scene changes. In this paper, models describing the changed and unchanged regions of a scene are postulated, and the detection problem is expressed in a Bayesian hypothesis-testing framework. Forming the log-likelihood ratio gives a single sufficient statistic, encoding changes in both the coherence and the mean backscatter power, for discriminating between the unchanged- and changed-scene models. The theoretical detection performance of the change statistic is derived and shows a significant improvement over both the sample mean backscatter-power ratio and sample coherence change statistics. Finally, the superior detection performance of the log-likelihood change statistic is demonstrated using experimental data collected using the Defence Science and Technology Organisation's Ingara X-band airborne SAR.Mark Preiss, Douglas A. Gray, and Nick J. S. Stac

Factors contributing to disparities in mortality among patients with non-small-cell lung cancer

Historically, non-small-cell lung cancer (NSCLC) patients who are non-white, have low incomes, low educational attainment, and non-private insurance have worse survival. We assessed whether differences in survival were attributable to sociodemographic factors, clinical characteristics at diagnosis, or treatments received. We surveyed a multiregional cohort of patients diagnosed with NSCLC from 2003 to 2005 and followed through 2012. We used Cox proportional hazard analyses to estimate the risk of death associated with race/ethnicity, annual income, educational attainment, and insurance status, unadjusted and sequentially adjusting for sociodemographic factors, clinical characteristics, and receipt of surgery, chemotherapy, and radiotherapy. Of 3250 patients, 64% were white, 16% black, 7% Hispanic, and 7% Asian; 36% of patients had income

Factors contributing to disparities in mortality among patients with non–small‐cell lung cancer

Historically, non–small‐cell lung cancer (NSCLC) patients who are non‐white, have low incomes, low educational attainment, and non‐private insurance have worse survival. We assessed whether differences in survival were attributable to sociodemographic factors, clinical characteristics at diagnosis, or treatments received. We surveyed a multiregional cohort of patients diagnosed with NSCLC from 2003 to 2005 and followed through 2012. We used Cox proportional hazard analyses to estimate the risk of death associated with race/ethnicity, annual income, educational attainment, and insurance status, unadjusted and sequentially adjusting for sociodemographic factors, clinical characteristics, and receipt of surgery, chemotherapy, and radiotherapy. Of 3250 patients, 64% were white, 16% black, 7% Hispanic, and 7% Asian; 36% of patients had incomes <$20 000/y; 23$60 000/y, not attending college, and not having private insurance were all associated with an increased risk of mortality. Black‐white differences were not statistically significant after adjustment for sociodemographic factors, although patients with patients without a high school diploma and patients with incomes <$40 000/y continued to have an increased risk of mortality. Differences by educational attainment were not statistically significant after adjustment for clinical characteristics. Differences by income were not statistically significant after adjustment for clinical characteristics and treatments. Clinical characteristics and treatments received primarily contributed to mortality disparities by race/ethnicity and socioeconomic status in patients with NSCLC. Additional efforts are needed to assure timely diagnosis and use of effective treatment to lessen these disparities.Using data from the Cancer Care Outcomes Research and Surveillance (CanCORS) consortium, a large, multi‐regional observational study of newly diagnosed cancer patients, we documented higher unadjusted mortality for NSCLC among patients who were black, have lower income, less well‐educated, and with non‐private insurance. We used a series of Cox proportional hazards model to estimate the increased risk of death associated with sociodemographic factors, clinical characteristics, and treatments received to determine what accounted for the disparities. We found that patients’ clinical characteristics and treatments received primarily contributed to the mortality disparities that we observed in patients with NSCLC.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146607/1/cam41796.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146607/2/cam41796_am.pd

Oncologists' perspectives on post-cancer treatment communication and care coordination with primary care physicians

Post-treatment cancer care is often fragmented and of suboptimal quality. We explored factors that may affect cancer survivors' post-treatment care coordination, including oncologists' use of electronic technologies such as e-mail and integrated electronic health records (EHRs) to communicate with primary care physicians (PCPs). We used data from a survey (357 respondents; participation rate 52.9%) conducted in 2012-2013 among medical oncologists caring for patients in a large US study of cancer care delivery and outcomes. Oncologists reported their frequency and mode of communication with PCPs, and role in providing post-treatment care. Seventy-five per cent said that they directly communicated with PCPs about post-treatment status and care recommendations for all/most patients. Among those directly communicating with PCPs, 70% always/usually used written correspondence, while 36% always/usually used integrated EHRs; telephone and e-mail were less used. Eighty per cent reported co-managing with PCPs at least one post-treatment general medical care need. In multivariate-adjusted analyses, neither communication mode nor intensity were associated with co-managing survivors' care. Oncologists' reliance on written correspondence to communicate with PCPs may be a barrier to care coordination. We discuss new research directions for enhancing communication and care coordination between oncologists and PCPs, and to better meet the needs of cancer survivors post-treatment

Engineering Orthogonal Polypeptide GalNAc-Transferase and UDP-Sugar Pairs

O-Linked α-N-acetylgalactosamine (O-GalNAc) glycans constitute a major part of the human glycome. They are difficult to study because of the complex interplay of 20 distinct glycosyltransferase isoenzymes that initiate this form of glycosylation, the polypeptide N-acetylgalactosaminyltransferases (GalNAc-Ts). Despite proven disease relevance, correlating the activity of individual GalNAc-Ts with biological function remains challenging due to a lack of tools to probe their substrate specificity in a complex biological environment. Here, we develop a “bump–hole” chemical reporter system for studying GalNAc-T activity in vitro. Individual GalNAc-Ts were rationally engineered to contain an enlarged active site (hole) and probed with a newly synthesized collection of 20 (bumped) uridine diphosphate N-acetylgalactosamine (UDP-GalNAc) analogs to identify enzyme–substrate pairs that retain peptide specificities but are otherwise completely orthogonal to native enzyme–substrate pairs. The approach was applicable to multiple GalNAc-T isoenzymes, including GalNAc-T1 and -T2 that prefer nonglycosylated peptide substrates and GalNAcT-10 that prefers a preglycosylated peptide substrate. A detailed investigation of enzyme kinetics and specificities revealed the robustness of the approach to faithfully report on GalNAc-T activity and paves the way for studying substrate specificities in living systems

Consumer Perspectives on Access to Directâ toâ Consumer Genetic Testing: Role of Demographic Factors and the Testing Experience

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137391/1/milq12262.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137391/2/milq12262_am.pd

Participant and workplace champion experiences of an intervention designed to reduce sitting time in desk-based workers : SMART work & life

Background: A cluster randomised controlled trial demonstrated the effectiveness of the SMART Work & Life (SWAL) behaviour change intervention, with and without a height-adjustable desk, for reducing sitting time in desk-based workers. Staff within organisations volunteered to be trained to facilitate delivery of the SWAL intervention and act as workplace champions. This paper presents the experiences of these champions on the training and intervention delivery, and from participants on their intervention participation. Methods: Quantitative and qualitative feedback from workplace champions on their training session was collected. Participants provided quantitative feedback via questionnaires at 3 and 12 month follow-up on the intervention strategies (education, group catch ups, sitting less challenges, self-monitoring and prompts, and the height-adjustable desk [SWAL plus desk group only]). Interviews and focus groups were also conducted at 12 month follow-up with workplace champions and participants respectively to gather more detailed feedback. Transcripts were uploaded to NVivo and the constant comparative approach informed the analysis of the interviews and focus groups. Results: Workplace champions rated the training highly with mean scores ranging from 5.3/6 to 5.7/6 for the eight parts. Most participants felt the education increased their awareness of the health consequences of high levels of sitting (SWAL: 90.7%; SWAL plus desk: 88.2%) and motivated them to change their sitting time (SWAL: 77.5%; SWAL plus desk: 85.77%). A high percentage of participants (70%) reported finding the group catch up session helpful and worthwhile. However, focus groups highlighted mixed responses to the group catch-up sessions, sitting less challenges and self-monitoring intervention components. Participants in the SWAL plus desk group felt that having a height-adjustable desk was key in changing their behaviour, with intrinsic as well as time based factors reported as key influences on the height-adjustable desk usage. In both intervention groups, participants reported a range of benefits from the intervention including more energy, less fatigue, an increase in focus, alertness, productivity and concentration as well as less musculoskeletal problems (SWAL plus desk group only). Work-related, interpersonal, personal attributes, physical office environment and physical barriers were identified as barriers when trying to sit less and move more. Conclusions: Workplace champion and participant feedback on the intervention was largely positive but it is clear that different behaviour change strategies worked for different people indicating that a ‘one size fits all’ approach may not be appropriate for this type of intervention. The SWAL intervention could be tested in a broader range of organisations following a few minor adaptations based on the champion and participant feedback. Trial registration: ISCRCTN registry (ISRCTN11618007)

The structured health intervention for truckers (SHIFT) cluster randomised controlled trial : a mixed methods process evaluation

Funding This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme (reference: NIHR PHR 15/190/42). The study was also supported by the NIHR Leicester Biomedical Research Centre which is a partnership between University Hospitals of Leicester NHS Trust, Loughborough University, and the University of Leicester. Laura Gray is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (ARC EM). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Funding to cover intervention costs (Fitbits, cab workout equipment) was provided by the Higher Education Innovation Fund, via the Loughborough University Enterprise Projects Group. The Colt Foundation provided funding for a PhD Studentship, awarded to Amber Guest (reference: JD/618), which covered Amber’s time and contributions to this project. None of the funding bodies had any role in study design; election, synthesis, and interpretation of data; writing of the report; or the decision to submit the manuscript for publication. Acknowledgements We gratefully acknowledge the support provided by senior Health and Safety personnel and Transport Managers at our partner logistics company in facilitating this research. We also thank all participants for taking part. We are grateful to the independent members of the Trial Steering Committee for their continued support and advice throughout the trial: Dr. Derrick Bennett, Prof Emma McIntosh, Prof Petra Wark and Mr. Paul Gardiner.Peer reviewedPublisher PD

Drivers with and without Obesity Respond Differently to a Multi-Component Health Intervention in Heavy Goods Vehicle Drivers

Funding This project was funded by the National Institute for Health Research (NIHR) Public Health Research programme (reference: NIHR PHR 15/190/42). The study was also supported by the NIHR Leicester Biomedical Research Centre which is a partnership between University Hospitals of Leicester NHS Trust, Loughborough University and the University of Leicester. Laura Gray is supported by the National Institute for Health Research (NIHR) Applied Research Collaboration East Midlands (ARC EM). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. Funding to cover the intervention costs (Fitbits and cab workout equipment) was provided by the Higher Education Innovation Fund, via the Loughborough University Enterprise Projects Group. The Colt Foundation provided funding for a PhD Studentship, awarded to Amber Guest (reference: JD/618), which covered Amber’s time and contributions to this project. The funders played no role in study design, data collection, data analysis, data interpretation or in the preparation of this manuscript.Peer reviewedPublisher PD