ORCID Profile
0000-0002-4641-2858
Current Organisations
University of Colorado at Boulder
,
BRAC University
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Publisher: Elsevier BV
Date: 07-2022
DOI: 10.1016/J.JSAMS.2022.03.010
Abstract: To investigate relationships between load tolerance of single leg isometric knee extension and athlete reported knee pain location and severity during the single leg decline squat. Cross-sectional study. 175 college basketball athletes (99 women, 76 men) in Alberta, Canada participated at the start of the 2018-19 season. Knee pain location (dichotomized into focal/diffuse pain), and severity (numerical rating scale 0-10) were collected during the single leg decline squat. Athletes completed a standardized single leg isometric knee extension to determine load tolerance (defined by pain or reduced form). A quantile regression model was used to examine the association between load tolerance and pain location adjusting for sex, years played, body mass index and team. Athletes with diffuse pain had a significantly lower median load tolerance (-0.89 kg) than athletes without pain (95% confidence interval [-1.49, -0.29] p = 0.003). Athletes with focal pain tolerated similar median loads (-0.42 kg) to those without pain (95% confidence interval [-1.17, 0.33] p = 0.26). Higher knee pain severity was associated with a non-linear but consistent reduction in load tolerance (p < 0.001). Athlete-reported knee pain location during the single leg decline squat influenced load tolerance to isometric knee extension. Athletes with focal pain tolerated similar isometric loads to their pain free teammates. Clinicians should consider load selection of isometric knee extension for athletes with diffuse pain given their lower load tolerance. Future research should consider reporting pain location in addition to pain severity to differentiate clinical presentations and response to exercise.
Publisher: Wiley
Date: 10-2022
DOI: 10.1111/PAI.13862
Abstract: While the relationship between pollen and respiratory allergies is well‐documented, the role of short‐term pollen exposure in food allergy and eczema flares has not previously been explored. We aimed to investigate these associations in a population‐based s le of children. We investigated 1‐ ( n = 1108) and 6‐year‐old ( n = 675) children in the grass pollen season from the HealthNuts cohort. Grass pollen concentrations were considered on the day of testing (lag 0), up to three days before (lag 1‐lag 3) and cumulatively (lag 0–3). Associations between grass pollen and food skin‐prick test reactivity (SPT ≥ 2 mm at age 1 year and ≥ 3 mm at age 6 years), eczema flares, challenge‐confirmed food allergy, reaction threshold to oral food challenges (OFC), and serum food‐specific IgE levels were analyzed using either logistic or quantile regression models. Atopy and family history of allergic disease were considered as potent effect modifiers. Grass pollen at lag 0–3 (every 20 grains/m 3 increase) was associated with an up to 1.2‐fold increased odds of food SPT reactivity and eczema flares in 6‐year‐olds. In 1‐year‐olds, the associations were only observed for peanut in those with a family history of food allergy. Increasing grass pollen concentrations were associated with a lower reaction threshold to OFC and higher serum IgE levels in peanut‐allergic 1‐year‐olds only. Increasing grass pollen concentration was associated with increased risk of food SPT reactivity and eczema flares in children. The associations in peanut‐allergic infants may be related to immune activation and/or peanut and grass pollen cross‐reactivity leading to a lower reaction threshold.
Publisher: American Geophysical Union (AGU)
Date: 17-01-2018
DOI: 10.1002/2017GL076031
Publisher: American Geophysical Union (AGU)
Date: 06-2016
DOI: 10.1002/2015JB012764
Publisher: American Chemical Society (ACS)
Date: 17-07-2017
Publisher: American Geophysical Union (AGU)
Date: 22-11-2015
DOI: 10.1002/2015GL065868
Publisher: Acoustical Society of America (ASA)
Date: 10-2014
DOI: 10.1121/1.4899490
Abstract: This paper develops a self-parametrized Bayesian inversion to infer the spatio-temporal evolution of tsunami sources (initial sea state) due to megathrust earthquakes. To date, tsunami-source uncertainties are poorly understood, and the effect of choices such as discretization have not been studied. The approach developed here is based on a trans-dimensional self-parametrization of the sea surface, avoids regularization constraints and provides rigorous uncertainty estimation that accounts for model-selection ambiguity associated with the source discretization. The sea surface is parametrized using self-adapting irregular grids, which match the local resolving power of the data and provide parsimonious solutions for complex source characteristics. Source causality is ensured by including rupture-velocity and obtaining delay times from the Eikonal equation. The data are recorded on ocean-bottom pressure and coastal wave gauges and predictions are based on Green-function libraries computed from ocean-basin scale tsunami models for cases that include/exclude dispersion effects. The inversion is applied to tsunami waveforms from the great 2011 Tohoku-Oki (Japan) earthquake. The tsunami source is strongest near the Japan trench with posterior mean litudes of ~5 m. In addition, the data appear sensitive to rupture velocity, which is part of our kinematic source model.
Publisher: Frontiers Media SA
Date: 30-06-2015
Publisher: American Geophysical Union (AGU)
Date: 12-12-2018
DOI: 10.1029/2018JB016439
Publisher: Springer Science and Business Media LLC
Date: 05-02-2020
Publisher: Springer Science and Business Media LLC
Date: 11-02-2015
Publisher: American Geophysical Union (AGU)
Date: 09-2015
DOI: 10.1002/2015JB011942
Publisher: American Geophysical Union (AGU)
Date: 05-10-2017
DOI: 10.1002/2017GL074528
Publisher: MDPI AG
Date: 07-12-2021
DOI: 10.3390/JCM10245727
Abstract: Background: Some but not all previous studies report that pneumonia in children aged less than five years is associated with lower lung function and elevated risk of respiratory disease. To date, none have explored these associations in at-risk populations such as First Nations Australians, whose incidence of early childhood pneumonia is among the highest reported in the world. Methods: This cross-sectional study included 1276 First Nations Australian children/young adults aged 5–25 years recruited from regional/remote Queensland and Northern Territory communities and schools. Associations between pneumonia and both spirometry values and asthma were investigated using linear and logistic regression. Results: Early childhood pneumonia was associated with lower FEV1 and FVC Z-scores, but not FEV1/FVC% Z-scores, when occurring before age three (FEV1 β = −0.42, [95%CI −0.79, −0.04] FVC β = −0.62, [95%CI −1.14, −0.09]), and between three and five years (β = −0.50, [95%CI −0.88, −0.12] β = −0.63, [95%CI −1.17, −0.10]), compared to those who never had pneumonia. Similarly, pneumonia occurring when aged before age three years (OR = 3.68, 95%CI 1.96–6.93) and three to five years (OR = 4.81, 95%CI 1.46–15.8) was associated with increased risk of asthma in later childhood. Conclusions: Early childhood pneumonia is associated with lung function deficits and increased asthma risk in later childhood/early adulthood in First Nations Australians. The disproportionate impact of pneumonia on at-risk children must be addressed as a priority.
Publisher: Elsevier BV
Date: 03-2017
Publisher: Wiley
Date: 07-12-2011
DOI: 10.1002/FLD.2736
Publisher: American Geophysical Union (AGU)
Date: 03-2021
DOI: 10.1029/2020EA001390
Abstract: An efficient and cost‐effective near‐field tsunami warning system is crucial for coastal communities. The existing tsunami forecasting system is based on offshore Deep‐Ocean Assessment and Reporting of Tsunamis and Global Navigation Satellite System (GNSS) buoys which are not affordable for many countries. A potential cost‐effective solution is to utilize position data from ships traveling in coastal and offshore regions. In this study, we examine the feasibility of using ship‐borne GNSS data in tsunami forecasting. We carry out synthetic experiments by applying a data assimilation (DA) method with ship position (elevation and velocity) data. Our findings show that the DA method can recover the reference model with high accuracy if a dense network of ship elevation data is used. However, the use of ship velocity data alone is unable to recover the reference model. In addition, we carried out sensitivity studies of the DA method to the ship spatial distribution. We find that a 20 km gap between the ships works well in terms of accuracy and computational time for the ex le source model that we explored. The highest accuracy is obtained when data from a sufficient number of ships traveling in and around the tsunami source area are available.
Publisher: Wiley
Date: 02-03-2011
DOI: 10.1002/FLD.2545
No related grants have been discovered for Md Jakir Hossen.