Publications by authors named "Sang Phan"

4 Publications

  • Page 1 of 1

Impact of an extreme monsoon on CO and CH fluxes from mangrove soils of the Ayeyarwady Delta, Myanmar.

Sci Total Environ 2021 Mar 4;760:143422. Epub 2020 Nov 4.

School of Biological Sciences, The University of Queensland, St Lucia, QLD 4067, Australia.

Mangrove ecosystems can be both significant sources and sinks of greenhouse gases (GHGs). Understanding variability in flux and the key factors controlling emissions in these ecosystems are therefore important in the context of accounting for GHG emissions. The current study is the first to quantify GHG emissions using static chamber measurements from soils in disused aquaculture ponds, planted mangroves, and mature mangroves from the Ayeyarwady Delta, Myanmar. Soil properties, biomass and estimated net primary productivity were also assessed. Field assessments were conducted at the same sites during the middle of the dry season in February and end of the wet season in October 2019. Rates of soil CO efflux were among the highest yet recorded from mangrove ecosystems, with CO efflux from the 8 year old site reaching 86.8 ± 17 Mg CO ha yr during February, an average of 862% more than all other sites assessed during this period. In October, all sites had significant rates of soil CO efflux, with rates ranging from 31.9 ± 4.4 Mg CO ha yr in a disused pond to 118.9 ± 24.3 Mg CO ha yr in the 8 year old site. High soil CO efflux from the 8 year old site in February is most likely attributable to high rates of primary production and belowground carbon allocation. Elevated CO efflux from all sites during October was likely associated with the extreme 2019 South Asian monsoon season which lowered soil pore salinity and deposited new alluvium, stimulating both autotrophic and heterotrophic activity. Methane efflux increased significantly (50-400%) during the wet season from all sites with mangrove cover, although was a small overall component of soil GHG effluxes during both measurement periods. Our results highlight the critical importance of assessing GHG flux in-situ in order to quantify variability in carbon dynamics over time.
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http://dx.doi.org/10.1016/j.scitotenv.2020.143422DOI Listing
March 2021

Conformational Free-Energy Differences of Large Solvated Systems with the Focused Confinement Method.

J Chem Theory Comput 2020 Aug 7;16(8):5163-5173. Epub 2020 Jul 7.

Department of Chemistry, University of South Florida, Tampa, Florida 33620, United States.

The focused confinement method (FCM) is a reaction coordinate-free simulation approach for the calculation of conformational free-energy differences in explicit solvent. The method uses reference states for the conformations of interest, partitions the solute into conformationally active and inactive regions, and requires the calculation of desolvation free energies of mixed harmonic-anharmonic states as part of its procedure. The reference states and partitioning affect the speed of convergence of FCM's constituent simulations in opposing manners, but in the thermodynamic limit, they have no effect on calculated conformational free-energy differences. To aid fast convergence of large systems, a general procedure to quickly partition and construct reference states is introduced. With this, two sets of reference states and associated partitionings were constructed for the closed and open conformation of triosephosphate isomerase (TIM). Despite TIM's size, highly converged desolvation free energies were readily obtained from standard free-energy perturbation simulations because the mixed harmonic-anharmonic states are heavily rigidified. FCM-calculated free-energy differences for loop closing matched the experimental value for both reference sets. The insensitivity to reference states and associated partitionings favors reference states that merely reflect main structural differences for which convergence is faster. The calculations demonstrate the accuracy and robustness of FCM for large systems.
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http://dx.doi.org/10.1021/acs.jctc.0c00403DOI Listing
August 2020

Calculation of Conformational Free Energies with the Focused Confinement Method.

J Chem Theory Comput 2019 Dec 4;15(12):6760-6768. Epub 2019 Nov 4.

Department of Chemistry , University of South Florida , Tampa , Florida 33620 , United States.

We introduce the focused confinement method, a reaction coordinate-free simulation approach for the calculation of conformational free energies. These are obtained in a series of restrained simulations that transform part of the molecule of interest to independent harmonic oscillators resulting in mixed harmonic-anharmonic states. It is shown that the free energy difference between these mixed states can be readily calculated through the construction of chimeric trajectories. By focusing the confinement to the conformationally active region, the method requires fewer restrained simulations than the traditional confinement method, which eases the treatment of large systems. The accuracy and efficiency of the method is demonstrated for implicitly and explicitly solvated systems.
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http://dx.doi.org/10.1021/acs.jctc.9b00590DOI Listing
December 2019

Evaluation of deep convolutional neural networks for glaucoma detection.

Jpn J Ophthalmol 2019 May 24;63(3):276-283. Epub 2019 Feb 24.

Department of Ophthalmology, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan.

Purpose: To investigate the performance of deep convolutional neural networks (DCNNs) for glaucoma discrimination using color fundus images STUDY DESIGN: A retrospective study PATIENTS AND METHODS: To investigate the discriminative ability of 3 DCNNs, we used a total of 3312 images consisting of 369 images from glaucoma-confirmed eyes, 256 images from glaucoma-suspected eyes diagnosed by a glaucoma expert, and 2687 images judged to be nonglaucomatous eyes by a glaucoma expert. We also investigated the effects of image size on the discriminative ability and heatmap analysis to determine which parts of the image contribute to the discrimination. Additionally, we used 465 poor-quality images to investigate the effect of poor image quality on the discriminative ability.

Results: Three DCNNs showed areas under the curve (AUCs) of 0.9 or more. The AUC of the DCNN using glaucoma-confirmed eyes against nonglaucomatous eyes was higher than that using glaucoma-suspected eyes against nonglaucomatous eyes by approximately 0.1. The image size did not affect the discriminative ability. Heatmap analysis showed that the optic disc area was the most important area for the discrimination of glaucoma. The image quality affected the discriminative ability, and the inclusion of poor-quality images in the analysis reduced the AUC by 0.1 to 0.2.

Conclusions: DCNNs may be a useful tool for detecting glaucoma or glaucoma-suspected eyes by use of fundus color images. Proper preprocessing and collection of qualified images are essential to improving the discriminative ability.
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http://dx.doi.org/10.1007/s10384-019-00659-6DOI Listing
May 2019
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