Aaron Lim results 27
· Newest (Page 1/2, per page 25)
Author: Aaron Lim ×Clear All Filters
Search Results
Flow-aligned frameworks: linking benthic currents to cold-water coral mound development using 3D photogrammetry and ADCP dataNARA Subscribed
Scleractinian cold-water corals (CWC) rely on benthic currents for the delivery of food and other resources that support their growth and subsequent mound development in the deep sea. However, the CWC-current relationship remains poorly understood, as current knowledge is predominantly derived from spatially constrained ex-situ experimentation and coarse-scale modeling. Therefore, we combined long-term in situ acoustic Doppler...
Interpretable deep learning reveals spatiotemporal MRI features of brain aging that align with neurodegenerationNARA Subscribed
Cortical thinning and atrophy are hallmarks of brain aging that have been characterized using magnetic resonance imaging (MRI). Brain aging involves many neuroanatomic features whose effects on brain structure remain unexplored. To address this challenge, we trained interpretable deep neural networks (DNNs) to estimate brain age (BA) from T 1 -weighted ( T 1 w) MRI. By identifying MRI features unapparent to humans, DNNs can fi...
Alzheimer’s disease (AD) disproportionately affects women and carriers of the apolipoprotein E ε4 allele (APOE4), yet little is known about how sex and APOE interact to influence white matter (WM) integrity during disease progression. We integrated diffusion MRI and matched blood transcriptomic data to investigate these interactions and their underlying biological mechanisms. WM microstructure was quantified using diffusion te...
Enhanced angular range analysis: a novel object-based image analysis approach for seafloor characterisationNARA Subscribed
Multibeam backscatter has proven to be a useful tool in deciphering seabed sediments. While traditional image-based backscatter processing methods are commonly used, signal-based approaches such as Angular Range Analysis (ARA) offer a robust sediment-characterisation, albeit with a relatively low spatial-resolution. Thus, this research aims to improve the segmentation accuracy of ARA; and investigate influences on enhanced Ang...
Predicting the progression of MCI and Alzheimer’s disease on structural brain integrity and other features with machine learningNARA Subscribed
Machine learning (ML) on structural MRI data shows high potential for classifying Alzheimer’s disease (AD) progression, but the specific contribution of brain regions, demographics, and proteinopathy remains unclear. Using Alzheimer’s Disease Neuroimaging Initiative (ADNI) data, we applied an extreme gradient-boosting algorithm and SHAP (SHapley Additive exPlanations) values to classify cognitively normal (CN) older adults, th...
Development and physical characteristics of the Irish shelf-edge Macnas Mounds, Porcupine Seabight, NE AtlanticNARA Subscribed
Modern cold-water corals (CWCs) occur in a wide range of water depths, with Desmophyllum pertusum being one of the most common species. Pleistocene, Holocene, and modern coral mound formation by living CWC reefs have previously been described in the Porcupine Seabight from water depths greater than 700 m in the vicinity of the transitional zone between the Eastern North Atlantic Water and Mediterranean Outflow Water. Here we d...
The Irish continental margin (ICM) encompasses many complex sedimentary basins and diverse geomorphological features displaying bedrock outcrops where a large variety of habitats can be observed. This large area of seabed extends over >400,000 km 2 and cannot be mapped manually or in a standardized way. Novel bedrock suitability mapping is applied to the entire ICM to determine potential bedrock outcrop from shallow to deep se...
In this study we applied for the first time Fully Convolutional Neural Networks (FCNNs) to a marine bathymetric dataset to derive morphological classes over the entire Irish continental shelf. FCNNs are a set of algorithms within Deep Learning that produce pixel-wise classifications in order to create semantically segmented maps. While they have been extensively utilised on imagery for ecological mapping, their application on...
Benthic fauna form spatial patterns which are the result of both biotic and abiotic processes, which can be quantified with a range of landscape ecology descriptors. Fine- to medium-scale spatial patterns (<1–10 m) have seldom been quantified in deep-sea habitats, but can provide fundamental ecological insights into species’ niches and interactions. Cold-water coral reefs formed by Desmophyllum pertusum (syn. Lophelia pertusa...
Cold-water coral (CWC) reefs are complex structural habitats that are considered biodiversity “hotspots” in deep-sea environments and are subject to several climate and anthropogenic threats. As three-dimensional structural habitats, there is a need for robust and accessible technologies to enable more accurate reef assessments. Photogrammetry derived from remotely operated vehicle video data is an effective and non-destructiv...
Geomorphological and seismostratigraphic evidence for multidirectional polyphase glaciation of the northern Celtic SeaNARA Subscribed
High‐resolution seismic and bathymetric data offshore southeast Ireland and LIDaR data in County Waterford are presented that partially overlap previous studies. The observed Quaternary stratigraphic succession offshore southeast Ireland (between Dungarvan and Kilmore Quay) records a sequence of depositional and erosional events that supports regional glacial models derived from nearby coastal sediment stratigraphies and landf...