Suppose x is an unknown vector in Ropfm (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements n can be dramatically smaller than the size m. Thus, certain natural classes of images with m pixels need only n=O(m1/4log5/2(m)) nonadaptive nonpixel samples for faithful recovery, as opposed to the usual m pixel samples. More specifically, suppose x has a sparse representation in some orthonormal basis (e.g., wavelet, Fourier) or tight frame (e.g., curvelet, Gabor)-so the coefficients belong to an lscrp ball for 0<ples1. The N most important coefficients in that expansion allow reconstruction with lscr2 error O(N1/2-1p/). It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients. Moreover, a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing. The nonadaptive measurements have the character of "random" linear combinations of basis/frame elements. Our results use the notions of optimal recovery, of n-widths, and information-based complexity. We estimate the Gel'fand n-widths of lscrp balls in high-dimensional Euclidean space in the case 0<ples1, and give a criterion identifying near- optimal subspaces for Gel'fand n-widths. We show that "most" subspaces are near-optimal, and show that convex optimization (Basis Pursuit) is a near-optimal way to extract information derived from these near-optimal subspaces

Compressed sensing

2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC). Developed with the special contribution of the Heart Failure Association (HFA) of the ESC.

https://www.thelancet.com/pdfs/journals/lancet/PIIS0140-6736(12)61728-0.pdf

Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010

Global strategy for asthma management and prevention

https://hull-repository.worktribe.com/preview/1797952/1-s2.0-S0140673618322797-main.pdf

Global, regional, and national incidence, prevalence, and years lived with disability for 328 diseases and injuries for 195 countries, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016

It should be stressed that although many phenomena are complex, 15 the concept of ‘complexity’ is more specific. Complexity is the study of complex adaptive systems. These have been defined as ‘a collection of individual agents with freedom to act in ways that are not always totally predictable, and whose actions are interconnected so that one agent’s actions changes the context for other agents’. 16 Such systems include living cells, the brain, the immune system, the financial markets, ecosystems, and human populations. They are complex in the sense that there are a great many apparently independent agents interacting with each other, but the richness of these interactions allows the system as a whole to undergo self-organization. 1 They are also characterized as involving non-linearity and feedback loops in which small changes can have striking effects that cannot be understood simply by analysing the individual components. 17 The whole is more than the sum of its (reductionist) parts. Such complex systems can exist on a number of different levels from the subatomic through to the individual level, the population level, and beyond. 18 The most striking example of a complex self-organizing system is life itself, not only in terms of individual organisms but also in evolutionary terms—organisms adapt to each other through evolution into a finely tuned ecosystem. Similarly, various populations have evolved traditional ways of life that are now responding to the changes brought by the industrial revolution, colonization, and globalization. 19

/pdf/complexity-simplicity-and-epidemiology-42h1j6rxfc.pdf

Complexity, simplicity, and epidemiology

The association between occupational exposure to polycy-clic aromatic hydrocarbons (PAH) and bladder cancer development was investigated in a population-based case-control study carried out in the Bormida valley, Italy. One hundred and twenty-one male cases and 342 male controls, matched by age were collected from local hospitals. Occupational exposure to PAH and aromatic amines (AA) was evaluated by means of a job exposure matrix, constructed specifically for this study. Subjects considered as sharing a “definite exposure to PAH” showed an increased risk even after adjustment for cigarette smoking and exposure to AA (OR = 2.14, 95% CL 0.82-5.60). No elevation in risk was found for the category “possible exposure to PAH” (OR = 1.05, 95% CL 0.45-2.44). The findings of this study are consistent with previous studies indicating PAH as a risk factor for bladder cancer. A possible residual confounding effect due to AA impurities is discussed.

Bladder cancer and occupational exposure to polycyclic aromatic hydrocarbons.

We explored the contribution of stage at diagnosis to ethnic disparities in cancer survival in New Zealand. We linked 115811 adult patients with invasive cancer registered on the cancer registry (1994 to 2002) to mortality data. Age-standardized, 5-year relative survival rates were lowest for Maori, intermediate for Pacific people (otherwise known as Pacific Islanders), and highest for non-Maori/non-Pacific people for many cancers. Stage at diagnosis accounted for only part of these differences. Possible factors responsible for ethnic inequalities might include access to specialized cancer services and the quality of care received.

/pdf/ethnic-inequalities-in-cancer-survival-in-new-zealand-1q6h1npkwn.pdf

Ethnic Inequalities in Cancer Survival in New Zealand: Linkage Study

OBJECTIVES: A cross sectional study of respiratory symptoms and lung function in welders was performed at eight New Zealand welding sites: 62 current welders and 75 non-welders participated. METHODS: A questionnaire was administered to record demographic data, smoking habit, and current respiratory symptoms. Current and previous welding exposures were recorded to calculate a total lifetime welding fume exposure index. Forced expiratory volume in one second (FEV1), forced vital capacity (FVC), and peak expiratory flow (PEF) were measured before the start of the shift. RESULTS: There were no significant differences in ethnicity, smoking habits, or years of work experience between welders and non-welders. Symptoms of chronic bronchitis were more common in current welders (11.3%) than in non-welders (5.0%). Of those workers with a cumulative exposure index to welding fume > or = 10 years, 16.7% reported symptoms of chronic bronchitis compared with 4.7% of those with a cumulative exposure index 10 years (OR 9.5, 1.3 to 71.9) were independent risk factors for chronic bronchitis. The report of any work related respiratory symptom was more prevalent in welders (30.7%) than non-welders (15.0%) and workers with these symptoms had significantly lower FEV, (p = 0.004) and FVC (p = 0.04) values. Multivariate analysis identified a high proportion of time spent welding in confined spaces as the main risk factor for reporting these symptoms (OR 2.8, 1.0 to 8.3). CONCLUSION: This study has documented a high prevalence of symptoms of chronic bronchitis and other work related respiratory symptoms in current welders. Also, workers with chronic bronchitis had reduced PEF and FEV/FVC compared with those without chronic bronchitis. These symptoms related both to cigarette smoking and a measure of lifetime exposure to welding fume.

https://oem.bmj.com/content/oemed/55/3/150.full.pdf

Chronic bronchitis, work related respiratory symptoms, and pulmonary function in welders in New Zealand.

1. Introduction I. BASIC PRINCIPLES OF ASTHMA EPIDEMIOLOGY 2. Study Design Options 3. Study Design Issues II. ASTHMA MORBIDITY 4. Measuring Asthma Prevalence 5. Measuring Asthma Morbidity 6. Measuring Asthma Risk Factors III. ASTHMA MORTALITY 7. Studying Time Trends in Asthma Deaths 8. Studying the Causes of Asthma Deaths

Neil Pearce

Papers

Complexity, simplicity, and epidemiology

Bladder cancer and occupational exposure to polycyclic aromatic hydrocarbons.

Ethnic Inequalities in Cancer Survival in New Zealand: Linkage Study

Chronic bronchitis, work related respiratory symptoms, and pulmonary function in welders in New Zealand.

Asthma Epidemiology: Principles and Methods