OSGAR: a scene graph with uncertain transformations

An important problem for augmented reality is registration error. No system can be perfectly tracked, calibrated or modeled. As a result, the overlaid graphics are not aligned perfectly with objects in the physical world. This can be distracting, annoying or confusing. In this paper, we propose a method for mitigating the effects of registration errors that enables application developers to build dynamically adaptive AR displays. Our solution is implemented in a programming toolkit called OSGAR. Built upon OpenSceneGraph (OSG), OSGAR statistically characterizes registration errors, monitors those errors and, when a set of criteria are met, dynamically adapts the display to mitigate the effects of the errors. Because the architecture is based on a scene graph, it provides a simple, familiar and intuitive environment for application developers. We describe the components of OSGAR, discuss how several proposed methods for error registration can be implemented, and illustrate its use through a set of examples

The global burden of cancer 2013 global burden of disease cancer collaboration

Importance Cancer is among the leading causes of death worldwide. Current estimates of cancer burden in individual countries and regions are necessary to inform local cancer control strategies. Objective To estimate mortality, incidence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs) for 28 cancers in 188 countries by sex from 1990 to 2013. Evidence Review The general methodology of the Global Burden of Disease (GBD) 2013 study was used. Cancer registries were the source for cancer incidence data as well as mortality incidence (MI) ratios. Sources for cause of death data include vital registration system data, verbal autopsy studies, and other sources. The MI ratios were used to transform incidence data to mortality estimates and cause of death estimates to incidence estimates. Cancer prevalence was estimated using MI ratios as surrogates for survival data; YLDs were calculated by multiplying prevalence estimates with disability weights, which were derived from population-based surveys; YLLs were computed by multiplying the number of estimated cancer deaths at each age with a reference life expectancy; and DALYs were calculated as the sum of YLDs and YLLs. Findings In 2013 there were 14.9 million incident cancer cases, 8.2 million deaths, and 196.3 million DALYs. Prostate cancer was the leading cause for cancer incidence (1.4 million) for men and breast cancer for women (1.8 million). Tracheal, bronchus, and lung (TBL) cancer was the leading cause for cancer death in men and women, with 1.6 million deaths. For men, TBL cancer was the leading cause of DALYs (24.9 million). For women, breast cancer was the leading cause of DALYs (13.1 million). Age-standardized incidence rates (ASIRs) per 100 000 and age-standardized death rates (ASDRs) per 100 000 for both sexes in 2013 were higher in developing vs developed countries for stomach cancer (ASIR, 17 vs 14; ASDR, 15 vs 11), liver cancer (ASIR, 15 vs 7; ASDR, 16 vs 7), esophageal cancer (ASIR, 9 vs 4; ASDR, 9 vs 4), cervical cancer (ASIR, 8 vs 5; ASDR, 4 vs 2), lip and oral cavity cancer (ASIR, 7 vs 6; ASDR, 2 vs 2), and nasopharyngeal cancer (ASIR, 1.5 vs 0.4; ASDR, 1.2 vs 0.3). Between 1990 and 2013, ASIRs for all cancers combined (except nonmelanoma skin cancer and Kaposi sarcoma) increased by more than 10% in 113 countries and decreased by more than 10% in 12 of 188 countries. Conclusions and Relevance Cancer poses a major threat to public health worldwide, and incidence rates have increased in most countries since 1990. The trend is a particular threat to developing nations with health systems that are ill-equipped to deal with complex and expensive cancer treatments. The annual update on the Global Burden of Cancer will provide all stakeholders with timely estimates to guide policy efforts in cancer prevention, screening, treatment, and palliation

Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study

Background: Assessing the mortality impact of the 2009 influenza A H1N1 virus (H1N1pdm09) is essential for optimizing public health responses to future pandemics. The World Health Organization reported 18,631 laboratory-confirmed pandemic deaths, but the total pandemic mortality burden was substantially higher. We estimated the 2009 pandemic mortality burden through statistical modeling of mortality data from multiple countries. Methods and Findings: We obtained weekly virology and underlying cause-of-death mortality time series for 2005–2009 for 20 countries covering ~35% of the world population. We applied a multivariate linear regression model to estimate pandemic respiratory mortality in each collaborating country. We then used these results plus ten country indicators in a multiple imputation model to project the mortality burden in all world countries. Between 123,000 and 203,000 pandemic respiratory deaths were estimated globally for the last 9 mo of 2009. The majority (62%–85%) were attributed to persons under 65 y of age. We observed a striking regional heterogeneity, with almost 20-fold higher mortality in some countries in the Americas than in Europe. The model attributed 148,000–249,000 respiratory deaths to influenza in an average pre-pandemic season, with only 19% in person

O3oxidation of SO2in sea-salt aerosol water: Size distribution of non-sea-salt sulfate during the First Aerosol Characterization Experiment (ACE 1)

Non sea-salt sulfate (NSS) of 2.2-2.3 nmol m(-3) total magnitude in aerosols observed during the First Aerosol Characterization Experiment (ACE-1) at Cape Grim, Tasmania, was trimodally distributed with similar to 1 nmol NSS m(-3) in > 0.7 mu m ambient diameter (diam) coarse seasalt mode aerosols; despite this low NSS concentration, [H2SO4(g)] was so low that 0.7 mu m diam aerosols. The mechanism of O-3 oxidation of SO2 in sea-salt aerosol water (SSAW) is assessed for its capability to explain this coarse aerosol NSS. Limitation of this mechanism's NSS contribution is largely due to SSAW's buffering capacity since its reaction rate is reduced by 2 orders of magnitude at pH 6 versus the pH greater than or equal to 8 of unreacted SSAW. However, the buffering capacity of sea-salt aerosols may have been significantly enhanced over that of bulk seawater alkalinity. This appears to be due to carbonate resulting from small fragments of biogenic CaCO3 in the ocean's surface microlayer. Given the observed nonsoil calcium excess over that in bulk seawater, the estimated actual buffering capacity of sea-salt aerosols observed during ACE 1 was 50%, or more, enhanced over that due to bulk seawater alkalinity. Considering this enhanced buffering capacity, O-3 oxidation of SO2 in SSAW can produce sufficient NSS to explain 70-90% of the similar to 1 nmol m(-3) found in > 0.7 mu m diam coarse sea-salt aerosols with cloud processing and further oxidation of SO2 in SSAW (i.e., pH < 6) by other sea-salt conversion mechanisms contributing the remainder. The amount of NSS produced by sea-salt conversion mechanisms during the ACE 1 remote Southern Ocean experiment vied with homogeneous and cloud processing in their contribution to the total observed NSS of 2.2-2.3 nmol m(-3)