Efficiently Computing {phi}-Nodes On-The-Fly

Recently, Static Single Assignment Form and Sparse Evaluation Graphs have been advanced for the efficient solution of program optimization problems. Each method is provided with an initial set of flow graph nodes that inherently affect a problem\u27s solution. Other relevant nodes are those where potentially disparate solutions must combine. Previously, these so-called {phi}-nodes were found by computing the iterated dominance frontiers of the initial set of nodes, a process that could take worst case quadratic time with respect to the input flow graph. In this paper we present an almost-linear algorithm for detemining exactly the same set of {phi}-nodes

Racial/Ethnic Disparities in HPV-associated Anogenital Cancers Among Males in the United States: A Population-Based Retrospective Cohort Study

Little is known regarding racial/ethnic differences in human papillomavirus (HPV)-associated anogenital cancer among males. We examined age-adjusted incidence, late-stage diagnosis, survival and mortality of anogenital cancers among males in the United States. This population-based retrospective cohort study included 39,601 males diagnosed with HPV-associated invasive penile and anorectal cancers between 2005-2016 from the North American Association of Central Cancer Registries. We evaluated the association of race/ethnicity with outcomes using multivariable logistic regression, adjusted survival curves, and Cox proportional hazard modeling, adjusting for age, insurance, residential characteristics (metropolitan/non-metropolitan, area poverty, and geographic region), stage, and treatment. We also assessed interaction of race/ethnicity with other covariates in our late-stage and mortality models. Hispanic and Non-Hispanic (NH) Black males had highest age-adjusted incidence of penile and anorectal cancer, respectively. Higher odds of late-stage penile cancer was observed among NH Black (adjusted odds ratios [aOR] 1.22, 95% CI 1.07-1.39) and Hispanic males (aOR 1.17, 95% CI 1.04-1.31). Higher odds of late-stage anorectal cancer was observed among NH Black (aOR 1.25, 95% CI 1.14-1.36) and NH Other males (aOR 1.29, 95% CI 1.01-1.66). Compared to all other groups, NH Black males had the lowest cumulative and mean survival of both cancers and higher cancer-specific mortality (penile adjusted hazards ratios [aHR] 1.23, 95% CI 1.01-1.49; anorectal aHR 1.25, 95% CI 1.10-1.42). Racial/ethnic disparities in HPV-associated anogenital cancers differ depending on site. Interventions to increase HPV vaccination rates, early detection, and treatment of anogenital cancers in males are needed, particularly among men of color

Bandwidth-Centric Allocation of Independent Tasks on Heterogeneous Platforms

In this paper, we consider the problem of allocating a large number of independent, equal-sized tasks to a heterogenerous "grid" computing platform. Such problems arise in collaborative computing efforts like SETI@home. We use a tree to model a grid, where resources can have different speeds of computation and communication, as well as different overlap capabilities. We define a base model, and show how to determine the maximum steady-state throughput of a node in the base model, assuming we already know the throughput of the subtrees rooted at the node's children. Thus, a bottom-up traversal of the tree determines the rate at which tasks can be processed in the full tree. The best allocation is {\em bandwidth-centric}: if enough bandwidth is available, then all nodes are kept busy; if bandwidth is limited, then tasks should be allocated only to the children which have sufficiently small communication times, regardless of their computation power. We then show how nodes with other capabilities -- ones that allow more or less overlapping of computation and communication than the base model -- can be transformed to equivalent nodes in the base model. We also show how to handle a more general communication model. Finally, we present simulation results of several demand-driven task allocatio- n policies that show that our bandwidth-centric method obtains better results than allocating tasks to all processors on a first-come, first serve basis

Feasibility and potential efficacy of commercial mHealth/eHealth tools for weight loss in African American breast cancer survivors: pilot randomized controlled trial

Weight management after breast cancer (BC) treatment in African American (AA) women is crucial to reduce comorbid conditions and health disparities. We examined feasibility and potential efficacy of commercial eHealth/mHealth tools for weight management in AA BC survivors in New Jersey. Participants (N = 35) were randomized to an intervention (SparkPeople) plus activity tracker, Fitbit Charge (n = 18), or wait-list active control group (Fitbit only, n = 17). Anthropometric, behavioral, and quality of life (QOL) outcomes were collected at baseline, 3, 6, and 12 months. Differences in outcomes were assessed using intent-to-treat analysis. Retention was 97.1%. Both groups lost weight, with no significant differences between groups. At month 6, mean weight change was: intervention: -1.71 kg (SD 2.33; p = .006), 33.3% lost ≥3% of baseline weight; control: -2.54 kg (SD 4.00, p = .002), 23.5% lost ≥3% weight. Intervention participants achieved significant improvements in waist circumference (-3.56 cm, SD 4.70, p = .005), QOL (p = .030), and use of strategies for healthy eating (p = .025) and decreasing calories (p \u3c .001). Number of days logged food per week was associated with decreases in waist circumference at 6 months (β -0.79, 95% CI, -1.49, -0.09, p = .030) and 12 months (β -2.16, 95% CI, -4.17, -0.15, p = .038). Weight loss was maintained at 12 months. This is the first study to demonstrate potential efficacy of commercial eHealth/mHealth tools for weight loss in AA BC survivors, without additional counseling from the research team. If effective, they may be convenient weight loss tools that can be easily and widely disseminated. Clinical Trials registration: ClinicalTrials.gov NCT02699983

Scheduling multiple bags of tasks on heterogeneous master- worker platforms: centralized versus distributed solutions

Multiple applications that execute concurrently on heterogeneous platforms compete for CPU and network resources. In this paper we consider the problem of scheduling applications to ensure fair and efficient execution on master-worker platforms where the communication is restricted to a tree embedded in the network. The goal of the scheduling is to obtain the best throughput while enforcing some fairness between applications. We show how to derive an asymptotically optimal periodic schedule by solving a linear program expressing all problem constraints. For single-level trees, the optimal solution can be analytically computed. For large-scale platforms, gathering the global knowledge needed by the linear programming approach might be unrealistic. One solution is to adapt the multi-commodity flow algorithm of Awerbuch and Leighton, but it still requires some global knowledge. Thus, we also investigates heuristic solutions using only local information, and test them via simulations. The best of our heuristics achieves the optimal performance on about two-thirds of our test cases, but is far worse in a few cases

Barriers to adequate follow-up during adjuvant therapy may be important factors in the worse outcome for Black women after breast cancer treatment

<p>Abstract</p> <p>Introduction</p> <p>Black women appear to have worse outcome after diagnosis and treatment of breast cancer. It is still unclear if this is because Black race is more often associated with known negative prognostic indicators or if it is an independent prognostic factor. To study this, we analyzed a patient cohort from an urban university medical center where these women made up the majority of the patient population.</p> <p>Methods</p> <p>We used retrospective analysis of a prospectively collected database of breast cancer patients seen from May 1999 to June 2006. Time to recurrence and survival were analyzed using the Kaplan-Meier method, with statistical analysis by chi-square, log rank testing, and the Cox regression model.</p> <p>Results</p> <p>265 female patients were diagnosed with breast cancer during the time period. Fifty patients (19%) had pure DCIS and 215 patients (81%) had invasive disease. Racial and ethnic composition of the entire cohort was as follows: Black (N = 150, 56.6%), Hispanic (N = 83, 31.3%), Caucasian (N = 26, 9.8%), Asian (N = 4, 1.5%), and Arabic (N = 2, 0.8%). For patients with invasive disease, independent predictors of poor disease-free survival included tumor size, node-positivity, incompletion of adjuvant therapy, and Black race. Tumor size, node-positivity, and Black race were independently associated with disease-specific overall survival.</p> <p>Conclusion</p> <p>Worse outcome among Black women appears to be independent of the usual predictors of survival. Further investigation is necessary to identify the cause of this survival disparity. Barriers to completion of standard post-operative treatment regimens may be especially important in this regard.</p

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background: Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods: 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings: Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation: Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic