A framework for orthology assignment from gene rearrangement data

Abstract. Gene rearrangements have successfully been used in phylogenetic reconstruction and comparative genomics, but usually under the assumption that all genomes have the same gene content and that no gene is duplicated. While these assumptions allow one to work with organellar genomes, they are too restrictive when comparing nuclear genomes. The main challenge is how to deal with gene families, specifically, how to identify orthologs. While searching for orthologies is a common task in computational biology, it is usually done using sequence data. We approach that problem using gene rearrangement data, provide an optimization framework in which to phrase the problem, and present some preliminary theoretical results.

Regional prediction of landslide hazard using probability analysis of intense rainfall in the Hoa Binh province, Vietnam.

The main objective of this study is to assess regional landslide hazards in the Hoa Binh province of Vietnam. A landslide inventory map was constructed from various sources with data mainly for a period of 21 years from 1990 to 2010. The historic inventory of these failures shows that rainfall is the main triggering factor in this region. The probability of the occurrence of episodes of rainfall and the rainfall threshold were deduced from records of rainfall for the aforementioned period. The rainfall threshold model was generated based on daily and cumulative values of antecedent rainfall of the landslide events. The result shows that 15-day antecedent rainfall gives the best fit for the existing landslides in the inventory. The rainfall threshold model was validated using the rainfall and landslide events that occurred in 2010 that were not considered in building the threshold model. The result was used for estimating temporal probability of a landslide to occur using a Poisson probability model. Prior to this work, five landslide susceptibility maps were constructed for the study area using support vector machines, logistic regression, evidential belief functions, Bayesian-regularized neural networks, and neuro-fuzzy models. These susceptibility maps provide information on the spatial prediction probability of landslide occurrence in the area. Finally, landslide hazard maps were generated by integrating the spatial and the temporal probability of landslide. A total of 15 specific landslide hazard maps were generated considering three time periods of 1, 3, and 5 years

Global estimates of mortality associated with long-term exposure to outdoor fine particulate matter.

Exposure to ambient fine particulate matter (PM2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations

On the helicity of 3D-periodic Navier-Stokes equations II: the statistical case

1 online resource (PDF, 38 pages)Foias, C.; Hoang, Luan Thach; Nicoalenko, B.. (2008). On the helicity of 3D-periodic Navier-Stokes equations II: the statistical case. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/179958

An Examination of Wearable Sensors and Video Data Capture for Human Exercise Classification

Wearable sensors such as Inertial Measurement Units (IMUs) are often used to assess the performance of human exercise. Common approaches use handcrafted features based on domain expertise or automatically extracted features using time series analysis. Multiple sensors are required to achieve high classification accuracy, which is not very practical. These sensors require calibration and synchronization and may lead to discomfort over longer time periods. Recent work utilizing computer vision techniques has shown similar performance using video, without the need for manual feature engineering, and avoiding some pitfalls such as sensor calibration and placement on the body. In this paper, we compare the performance of IMUs to a video-based approach for human exercise classification on two real-world datasets consisting of Military Press and Rowing exercises. We compare the performance using a single camera that captures video in the frontal view versus using 5 IMUs placed on different parts of the body. We observe that an approach based on a single camera can outperform a single IMU by 10 percentage points on average. Additionally, a minimum of 3 IMUs are required to outperform a single camera. We observe that working with the raw data using multivariate time series classifiers outperforms traditional approaches based on handcrafted or automatically extracted features. Finally, we show that an ensemble model combining the data from a single camera with a single IMU outperforms either data modality. Our work opens up new and more realistic avenues for this application, where a video captured using a readily available smartphone camera, combined with a single sensor, can be used for effective human exercise classification

Authors’ Reply to “Training and Supporting Residents, for All Family Medicine Practice Settings.”

TO THE EDITOR: We appreciate Dr Wu’s comments and agree wholeheartedly that meeting community needs and negotiating relationships are essential skills for all family physicians. The need for these skills is amplified in the intimacy of the rural environment, as physicians navigate daily life amongst patients at grocery stores, restaurants, schools, and social gatherings

Addressing multiple modifiable risks through structured community-based Learning Clubs to improve maternal and infant health and infant development in rural Vietnam: protocol for a parallel group cluster randomised controlled trial

Introduction: Optimal early childhood development is an international priority. Risks during pregnancy and early childhood have lasting effects because growth is rapid. We will test whether a complex intervention addressing multiple modifiable risks: maternal nutrition, mental health, parenting capabilities, infant health and development and gender-based violence, is effective in reducing deficient cognitive development among children aged two in rural Vietnam. Methods and analysis: The Learning Clubs intervention is a structured programme combining perinatal stage-specific information, learning activities and social support. It comprises 20 modules, in 19 accessible, facilitated groups for women at a community centre and one home visit. Evidence-informed content is from interventions to address each risk tested in randomised controlled trials in other resource-constrained settings. Content has been translated and culturally adapted for Vietnam and acceptability and feasibility established in pilot testing. We will conduct a two-arm parallel-group cluster-randomised controlled trial, with the commune as clustering unit. An independent statistician will select 84/112 communes in Ha Nam Province and randomly assign 42 to the control arm providing usual care and 42 to the intervention arm. In total, 1008 pregnant women (12 per commune) from 84 clusters are needed to detect a difference in the primary outcome (Bayley Scales of Infant and Toddler Development Cognitive Score \u3c1 SD below standardised norm for 2 years of age) of 15% in the control and 8% in the intervention arms, with 80% power, significance 0.05 and intracluster correlation coefficient 0.03. Ethics and dissemination: Monash University Human Research Ethics Committee (Certificate Number 20160683), Melbourne, Victoria, Australia and the Institutional Review Board of the Hanoi School of Public Health (Certificate Number 017-377IDD- YTCC), Hanoi, Vietnam have approved the trial. Results will be disseminated through a comprehensive multistranded dissemination strategy including peer-reviewed publications, national and international conference presentations, seminars and technical and lay language reports

Incidence of Postpartum Infection after Vaginal Delivery in Viet Nam

This study assessed the incidence of postpartum infection which is rarely clinically evaluated and is probably underestimated in developing countries. This prospective study identified infection after vaginal delivery by clinical and laboratory examinations prior to discharge from hospital and again at six weeks postpartum in Ho Chi Minh City, Viet Nam. Textbook definitions, physicians' diagnoses, symptomatic and verbal autopsy definitions were used for classifying infection. Logistic regression was used for determining associations of postpartum infection with socioeconomic and reproductive characteristics. In total, 978 consecutive, eligible consenting women were followed up at 42\ub17 (range 2-45) days postpartum (not associated with incidence). Ninety-eight percent took 'prophylactic' antibiotics. The most conservative estimate of the incidence of postpartum infection was 1.7%. The incidence of serious infection was 0.5%, but increased to 4.6% when verbal autopsy and symptomatic definitions were used. Postpartum infection, particularly serious infection, is greatly underestimated. Just preventing or treating infection could have a substantial impact on reducing maternal mortality in developing countries