191 research outputs found
Research and Education in Computational Science and Engineering
Over the past two decades the field of computational science and engineering
(CSE) has penetrated both basic and applied research in academia, industry, and
laboratories to advance discovery, optimize systems, support decision-makers,
and educate the scientific and engineering workforce. Informed by centuries of
theory and experiment, CSE performs computational experiments to answer
questions that neither theory nor experiment alone is equipped to answer. CSE
provides scientists and engineers of all persuasions with algorithmic
inventions and software systems that transcend disciplines and scales. Carried
on a wave of digital technology, CSE brings the power of parallelism to bear on
troves of data. Mathematics-based advanced computing has become a prevalent
means of discovery and innovation in essentially all areas of science,
engineering, technology, and society; and the CSE community is at the core of
this transformation. However, a combination of disruptive
developments---including the architectural complexity of extreme-scale
computing, the data revolution that engulfs the planet, and the specialization
required to follow the applications to new frontiers---is redefining the scope
and reach of the CSE endeavor. This report describes the rapid expansion of CSE
and the challenges to sustaining its bold advances. The report also presents
strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie
Salt intake and dietary sources of salt on weekdays and weekend days in Australian adults
ObjectiveTo assess if there is a difference in salt intake (24 h urine collection and dietary recall) and dietary sources of salt (Na) on weekdays and weekend days.DesignA cross-sectional study of adults who provided one 24 h urine collection and one telephone-administered 24 h dietary recall.SettingCommunity-dwelling adults living in the State of Victoria, Australia.SubjectsAdults (n 598) who participated in a health survey (53·5 % women; mean age 57·1 (95 % CI 56·2, 58·1) years).ResultsMean (95 % CI) salt intake (dietary recall) was 6·8 (6·6, 7·1) g/d and 24 h urinary salt excretion was 8·1 (7·8, 8·3) g/d. Mean dietary and 24 h urinary salt (age-adjusted) were 0·9 (0·1, 1·6) g/d (P=0·024) and 0·8 (0·3, 1·6) g/d (P=0·0017), respectively, higher at weekends compared with weekdays. There was an indication of a greater energy intake at weekends (+0·6 (0·02, 1·2) MJ/d, P=0·06), but no difference in Na density (weekday: 291 (279, 304) mg/MJ; weekend: 304 (281, 327) mg/MJ; P=0·360). Cereals/cereal products and dishes, meat, poultry, milk products and gravy/sauces accounted for 71 % of dietary Na.ConclusionsMean salt intake (24 h urine collection) was more than 60 % above the recommended level of 5 g salt/d and 8–14 % more salt was consumed at weekends than on weekdays. Substantial reductions in the Na content of staple foods, processed meat, sauces, mixed dishes (e.g. pasta), convenience and takeaway foods are required to achieve a significant consistent reduction in population salt intake throughout the week.<br /
Cardiovascular magnetic resonance parameters of atherosclerotic plaque burden improve discrimination of prior major adverse cardiovascular events
<p>Abstract</p> <p>Aims</p> <p>Patients with prior major cardiovascular or cerebrovascular events (MACE) are more likely to have future recurrent events independent of traditional cardiovascular disease risk factors. The purpose of this study was to determine if patients with traditional risk factors and prior MACE had increased cardiovascular magnetic resonance (CMR) plaque burden measures compared to patients with risk factors but no prior events.</p> <p>Methods and Results</p> <p>Black blood carotid and thoracic aorta images were obtained from 195 patients using a rapid extended coverage turbo spin echo sequence. CMR measures of plaque burden were obtained by tracing lumen and outer vessel wall contours. Patients with prior MACE had significantly higher MR plaque burden (wall thickness, wall area and normalized wall index) in carotids and thoracic aorta compared to those without prior MACE (Wall thickness carotids: 1.03 ± 0.03 vs. 0.93± 0.03, p = 0.001; SD wall thickness carotids: 0.137 ± 0.0008 vs. 0.102 ± 0.0004, p < 0.001; wall thickness aorta: 1.63 ± 0.10 vs. 1.50 ± 0.04, p = 0.009; SD wall thickness aorta: 0.186 ± 0.035 vs. 0.139 ± 0.012, p = 0.009 respectively). Plaque burden (wall thickness) and plaque eccentricity (standard deviation of wall thickness) of carotid arteries were associated with prior MACE after adjustment for age, sex, and traditional risk factors. Area under ROC curve (AUC) for discriminating prior MACE improved by adding plaque eccentricity to models incorporating age, sex, and traditional CVD risk factors as model inputs (AUC = 0.79, p = 0.05).</p> <p>Conclusion</p> <p>A greater plaque burden and plaque eccentricity is prevalent among patients with prior MACE.</p
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Using Very-High-Resolution Multispectral Classification to Estimate Savanna Fractional Vegetation Components
Characterizing compositional and structural aspects of vegetation is critical to effectively assessing land function. When priorities are placed on ecological integrity, remotely sensed estimates of fractional vegetation components (FVCs) are useful for measuring landscape-level habitat structure and function. In this study, we address whether FVC estimates, stratified by dominant vegetation type, vary with different classification approaches applied to very-high-resolution small unoccupied aerial system (UAS)-derived imagery. Using Parrot Sequoia imagery, flown on a DJI Mavic Pro micro-quadcopter, we compare pixel- and segment-based random forest classifiers alongside a vegetation height-threshold model for characterizing the FVC in a southern African dryland savanna. Results show differences in agreement between each classification method, with the most disagreement in shrub-dominated sites. When compared to vegetation classes chosen by visual identification, the pixel-based random forest classifier had the highest overall agreement and was the only classifier not to differ significantly from the hand-delineated FVC estimation. However, when separating out woody biomass components of tree and shrub, the vegetation height-threshold performed better than both random-forest approaches. These findings underscore the utility and challenges represented by very-high-resolution multispectral UAS-derived data (~10 cm ground resolution) and their uses to estimate FVC. Semi-automated approaches statistically differ from by-hand estimation in most cases; however, we present insights for approaches that are applicable across varying vegetation types and structural conditions. Importantly, characterization of savanna land function cannot rely only on a “greenness” measure but also requires a structural vegetation component. Underscoring these insights is that the spatial heterogeneity of vegetation structure on the landscape broadly informs land management, from land allocation, wildlife habitat use, natural resource collection, and as an indicator of overall ecosystem function.</div
Prediction of Breast Cancer-Related Lymphedema By Dermal Backflow Detected With Near-infrared Fluorescence Lymphatic Imaging
PURPOSE: Mild breast cancer-related lymphedema (BCRL) is clinically diagnosed as a 5%-10% increase in arm volume, typically measured no earlier than 3-6 months after locoregional treatment. Early BCRL treatment is associated with better outcomes, yet amid increasing evidence that lymphedema exists in a latent form, treatment is typically delayed until arm swelling is obvious. In this study, we investigated whether near-infrared fluorescence lymphatic imaging (NIRF-LI) surveillance could characterize early onset of peripheral lymphatic dysfunction as a predictor of BCRL.
METHODS: In a prospective, longitudinal cohort/observational study (NCT02949726), subjects with locally advanced breast cancer who received axillary lymph node dissection and regional nodal radiotherapy (RT) were followed serially, between 2016 and 2021, before surgery, 4-8 weeks after surgery, and 6, 12, and 18 months after RT. Arm volume was measured by perometry, and lymphatic (dys) function was assessed by NIRF-LI.
RESULTS: By 18 months after RT, 30 of 42 study subjects (71%) developed mild-moderate BCRL (i.e.,ââ„â5% arm swelling relative to baseline), all manifested by dermal backflow of lymph into lymphatic capillaries or interstitial spaces. Dermal backflow had an 83% positive predictive value and 86% negative predictive value for BCRL, with a sensitivity of 97%, specificity of 50%, accuracy of 83%, positive likelihood ratio of 1.93, negative likelihood ratio of 0.07, and odds ratio of 29.00. Dermal backflow appeared on average 8.3 months, but up to 23 months, before the onset of mild BCRL.
CONCLUSION: BCRL can be predicted by dermal backflow, which often appears months before arm swelling, enabling early treatment before the onset of edema and irreversible tissue changes
Epifania, recriação e ressentimento: fragmentos narrativos sobre a experiĂȘncia da viagem na imigração italiana no Brasil
L'expérience du voyage dans le processus de l'immigration marque le premier contact avec l'inconnu. L'aventure de la traversée de l'océan signifie par conséquent l'abandon du seul monde tangible. Le nouveau monde va se dévoiler à l'émigrant au fur et à mesure que le navire avance en mer, en un mélange de représentations produites avant le départ et de
nouvelles âidĂ©es-imagesâ que l'expĂ©rience elle-mĂȘme du voyage contribue Ă Ă©laborer en continu. Au cours de ce processus, la lecture de "Sull'Oceano" dâEdmondo De Amicis permet une immersion dans ce monde fragmentaire d'images et des rĂ©cits que l'Ă©migrant va produire. Il tente par ce biais de comprendre sa propre expĂ©rience et son existence, en un monde entrecroisĂ© de diffĂ©rentes expressions de la sensibilitĂ©. LĂȘ nouveau monde se rĂ©vĂšle, souvenir tout Ă la fois dâune terre que lâon a abandonnĂ©e et recrĂ©ation d'une reprĂ©sentation pacificatrice
Discovery of candidate disease genes in ENU-induced mouse mutants by large-scale sequencing, including a splice-site mutation in nucleoredoxin.
An accurate and precisely annotated genome assembly is a fundamental requirement for functional genomic analysis. Here, the complete DNA sequence and gene annotation of mouse Chromosome 11 was used to test the efficacy of large-scale sequencing for mutation identification. We re-sequenced the 14,000 annotated exons and boundaries from over 900 genes in 41 recessive mutant mouse lines that were isolated in an N-ethyl-N-nitrosourea (ENU) mutation screen targeted to mouse Chromosome 11. Fifty-nine sequence variants were identified in 55 genes from 31 mutant lines. 39% of the lesions lie in coding sequences and create primarily missense mutations. The other 61% lie in noncoding regions, many of them in highly conserved sequences. A lesion in the perinatal lethal line l11Jus13 alters a consensus splice site of nucleoredoxin (Nxn), inserting 10 amino acids into the resulting protein. We conclude that point mutations can be accurately and sensitively recovered by large-scale sequencing, and that conserved noncoding regions should be included for disease mutation identification. Only seven of the candidate genes we report have been previously targeted by mutation in mice or rats, showing that despite ongoing efforts to functionally annotate genes in the mammalian genome, an enormous gap remains between phenotype and function. Our data show that the classical positional mapping approach of disease mutation identification can be extended to large target regions using high-throughput sequencing
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Modeling Community-Scale Natural Resource Use in a Transboundary Southern African Landscape: Integrating Remote Sensing and Participatory Mapping
Remote sensing analyses focused on non-timber forest product (NTFP) collection and grazing are current research priorities of land systems science. However, mapping these particular land use patterns in rural heterogeneous landscapes is challenging because their potential signatures on the landscape cannot be positively identified without fine-scale land use data for validation. Using field-mapped resource areas and household survey data from participatory mapping research, we combined various Landsat-derived indices with ancillary data associated with human habitation to model the intensity of grazing and NTFP collection activities at 100-m spatial resolution. The study area is situated centrally within a transboundary southern African landscape that encompasses community-based organization (CBO) areas across three countries. We conducted four iterations of pixel-based random forest models, modifying the variable set to determine which of the covariates are most informative, using the best fit predictions to summarize and compare resource use intensity by resource type and across communities. Pixels within georeferenced, field-mapped resource areas were used as training data. All models had overall accuracies above 60% but those using proxies for human habitation were more robust, with overall accuracies above 90%. The contribution of Landsat data as utilized in our modeling framework was negligible, and further research must be conducted to extract greater value from Landsat or other optical remote sensing platforms to map these land use patterns at moderate resolution. We conclude that similar population proxy covariates should be included in future studies attempting to characterize communal resource use when traditional spectral signatures do not adequately capture resource use intensity alone. This study provides insights into modeling resource use activity when leveraging both remotely sensed data and proxies for human habitation in heterogeneous, spectrally mixed rural land areas
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Validation of self-reported anthropometrics in the Adventist Health Study 2
<p>Abstract</p> <p>Background</p> <p>Relying on self-reported anthropometric data is often the only feasible way of studying large populations. In this context, there are no studies assessing the validity of anthropometrics in a mostly vegetarian population. The objective of this study was to evaluate the validity of self-reported anthropometrics in the Adventist Health Study 2 (AHS-2).</p> <p>Methods</p> <p>We selected a representative sample of 911 participants of AHS-2, a cohort of over 96,000 adult Adventists in the USA and Canada. Then we compared their measured weight and height with those self-reported at baseline. We calculated the validity of the anthropometrics as continuous variables, and as categorical variables for the definition of obesity.</p> <p>Results</p> <p>On average, participants underestimated their weight by 0.20 kg, and overestimated their height by 1.57 cm resulting in underestimation of body mass index (BMI) by 0.61 kg/m<sup>2</sup>. The agreement between self-reported and measured BMI (as a continuous variable), as estimated by intraclass correlation coefficient, was 0.97. The sensitivity of self-reported BMI to detect obesity was 0.81, the specificity 0.97, the predictive positive value 0.93, the predictive negative value 0.92, and the Kappa index 0.81. The percentage of absolute agreement for each category of BMI (normoweight, overweight, and obese) was 83.4%. After multivariate analyses, predictors of differences between self-reported and measured BMI were obesity, soy consumption and the type of dietary pattern.</p> <p>Conclusions</p> <p>Self-reported anthropometric data showed high validity in a representative subsample of the AHS-2 being valid enough to be used in epidemiological studies, although it can lead to some underestimation of obesity.</p
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