Doctor of Philosophy

dissertationThe optimization of novel stretchable fingernail sensors for detecting fingertip touch force direction is introduced. The fingernail sensor uses optical reflectance photoplethysmography to measure the change in blood perfusion in the fingernail bed when the finger pad touches a surface with various forces. This "fingernail sensing" technique involves mounting an array of LEDs (Light Emitting Diodes) and photodetectors on the fingernail surface to detect changes in the reflection intensity as a function of applied force. The intensity changes correspond to changes in blood volume underneath the fingernail and allow for fingertip force detection without haptic obstruction, which has several applications in the area of human-machine interaction. This dissertation experimentally determines the optimal optical parameters for the transmittance of light through the human fingernail bed. Specifically, the effect of varying the wavelength and optical path length on light transmittance through the nail bed are thoroughly investigated. Light transmittance through the human fingernail is optimized when using green light (525nm) and when placing optoelectronic pairs as close together as possible. The optimal locations of the optoelectronic devices are predicted by introducing an optical model that describes light transmittance between an LED and a photodiode in the fingernail area based on optical experimentation. A reduced configuration is derived from the optimal optoelectronic locations in order to facilitate iv the fabrication of the optimized fingernail sensor without significantly compromising the recognition accuracy. This results in an overall force direction recognition accuracy of 95%. Using novel fabrication techniques, we successfully build a stretchable fingernail sensor prototype, which fully conforms to the two-dimensional fingernail surface and is independent of its geometry. Namely, we overcome the challenges of patterning conductive lines on a stretchable substrate, and embedding rigid optical components in a stretchable platform while maintaining electrical conductivity. A finite element analysis is conducted to optimize the electrical contact resistance between the optoelectronic components and underlying stretchable conductors, as a function of the bending curvature and substrate thickness. The functionality of the stretchable sensor is tested in relation to the design parameters. Finally, applications and potential impacts of this work are discussed

Applying robust control theory to solve problems in bio-medical sciences: study of an apoptotic model

Biological models of an apoptotic process are studied using models describing a system of differential equations derived from reaction kinetics information. The mathematical model is re-formulated in a state-space robust control theory framework where parametric and dynamic uncertainty can be modelled to account for variations naturally occurring in biological processes. We propose to handle the nonlinearities using neural networks

ECU-MSS-2 dataset, a new multi-species seagrass dataset

The ECU-MSS-2\u27 dataset contains four different habitats, \u27Amphibolis\u27 spp (hereafter \u27Amphibolis ), \u27Halophila\u27 spp (hereafter \u27Halophila\u27), \u27Posidonia\u27 spp (hereafter \u27Posidonia\u27) and \u27Background\u27. We compiled this image dataset from different sources. The \u27Halophila\u27 images were collected by the Centre for Marine Ecosystems Research, Edith Cowan University, Western Australia. The \u27Amphibolis\u27 \u27Background\u27 and \u27Posidonia\u27 images were collected by the Department of Biodiversity, Conservation and Attractions (DBCA), Australia. The \u27Amphibolis\u27 class includes the seagrass species Amphibolis griffithii and Amphibolis Antarctica. The \u27Halophila\u27 class includes Halophila ovalis, while the \u27Posidonia\u27 class includes Posidonia sinuosa, Posidonia coriacea, and Posidonia Australis. The \u27Background\u27 class includes coral, sand, sponge, seaweeds, fish and other benthic debris. The dataset contained total 5,201 images, where the \u27Amphibolis\u27 class has 1304 images, the \u27Background\u27 class has 1237 images, the \u27Halophila\u27 class has 1315 images and the \u27Posidonia\u27 class has 1345 images. The total images were divided into training and test sets. The training set has 4,161 images and the test set has 1,040 images. All four classes have the same 260 images in the test set

Improving accuracy and efficiency in seagrass detection using state-of-the-art AI techniques

Seagrasses provide a wide range of ecosystem services in coastal marine environments. Despite their ecological and economic importance, these species are declining because of human impact. This decline has driven the need for monitoring and mapping to estimate the overall health and dynamics of seagrasses in coastal environments, often based on underwater images. However, seagrass detection from underwater digital images is not a trivial task; it requires taxonomic expertise and is time-consuming and expensive. Recently automatic approaches based on deep learning have revolutionised object detection performance in many computer vision applications, and there has been interest in applying this to automated seagrass detection from imagery. Deep learning–based techniques reduce the need for hardcore feature extraction by domain experts which is required in machine learning-based techniques. This study presents a YOLOv5-based one-stage detector and an EfficientDetD7–based two-stage detector for detecting seagrass, in this case, Halophila ovalis, one of the most widely distributed seagrass species. The EfficientDet-D7–based seagrass detector achieves the highest mAP of 0.484 on the ECUHO-2 dataset and mAP of 0.354 on the ECUHO-1 dataset, which are about 7% and 5% better than the state-of-the-art Halophila ovalis detection performance on those datasets, respectively. The proposed YOLOv5-based detector achieves an average inference time of 0.077 s and 0.043 s respectively which are much lower than the state-of-the-art approach on the same datasets

Intrasplenic Arterial Aneurysms during Pregnancy

Splenic artery aneurysms account for about 60% of all visceral aneurysms. Pregnancy is a risk factor for splenic artery aneurysms rupture with high maternal mortality and fetal loss. Intrasplenic arterial aneurysms are extremely rare and have not been reported to be associated with pregnancy. This report presents a 34-year-old woman during the second trimester, admitted with severe left upper quadrant and left shoulder pain. She had two uncomplicated intrasplenic aneurysms. Splenectomy was done. She delivered a full term healthy girl. This is the first report of acute abdomen during pregnancy caused by intrasplenic artery aneurysms with maternal and fetal survival

Sect and House in Syria: History, Architecture, and Bayt Amongst the Druze in Jaramana

This paper explores the connections between the architecture and materiality of houses and the social idiom of bayt (house, family). The ethnographic exploration is located in the Druze village of Jaramana, on the outskirts of the Syrian capital Damascus. It traces the histories, genealogies, and politics of two families, bayt Abud-Haddad and bayt Ouward, through their houses. By exploring the two families and the architecture of their houses, this paper provides a detailed ethnographic account of historical change in modern Syria, internal diversity, and stratification within the intimate social fabric of the Druze neighbourhood at a time of war, and contributes a relational approach to the anthropological understanding of houses

AKT/mTOR Signaling Modulates Resistance to Endocrine Therapy and CDK4/6 Inhibition in Metastatic Breast Cancers

Endocrine therapy (ET) in combination with CDK4/6 inhibition is routinely used as first-line treatment for HR+/HER2− metastatic breast cancer (MBC) patients. However, 30–40% of patients quickly develop disease progression. In this open-label multicenter clinical trial, we utilized a hypothesis-driven protein/phosphoprotein-based approach to identify predictive markers of response to ET plus CDK4/6 inhibition in pre-treatment tissue biopsies. Pathway-centered signaling profiles were generated from microdissected tumor epithelia and surrounding stroma/immune cells using the reverse phase protein microarray. Phosphorylation levels of the CDK4/6 downstream substrates Rb (S780) and FoxM1 (T600) were higher in patients with progressive disease (PD) compared to responders (p = 0.02). Systemic PI3K/AKT/mTOR activation in tumor epithelia and stroma/immune cells was detected in patients with PD. This activation was not explained by underpinning genomic alterations alone. As the number of FDA-approved targeted compounds increases, functional protein-based signaling analyses may become a critical component of response prediction and treatment selection for MBC patients

In vitro activity of pertuzumab in combination with trastuzumab in uterine serous papillary adenocarcinoma

BACKGROUND: Uterine serous papillary adenocarcinoma (USPC) is a rare but highly aggressive variant of endometrial cancer. Pertuzumab is a new humanised monoclonal antibody (mAb) targeting the epidermal growth factor type II receptor (HER2/neu). We evaluated pertuzumab activity separately or in combination with trastuzumab against primary USPC cell lines expressing different levels of HER2/neu. METHODS: Six USPC cell lines were assessed by immunohistochemistry (IHC), flow cytometry, and real-time PCR for HER2/neu expression. c-erbB2 gene amplification was evaluated using fluorescent in situ hybridisation (FISH). Sensitivity to pertuzumab and trastuzumab-induced antibody-dependent cell-mediated cytotoxicity (ADCC) and complement-dependent cytotoxicity (CDC) was evaluated in 5 h chromium release assays. Pertuzumab cytostatic activity was evaluated using proliferation-based assays. RESULTS: Three USPC cell lines stained heavily for HER2/neu by IHC and showed amplification of the c-erbB2 gene by FISH. The remaining FISH-negative USPCs expressed HER2/neu at 0/1\ufe levels. In cytotoxicity experiments against USPC with a high HER2/neu expression, pertuzumab and trastuzumab were similarly effective in inducing strong ADCC. The addition of complementcontaining plasma and interleukin-2 increased the cytotoxic effect induced by both mAbs. In low HER2/neu USPC expressors, trastuzumab was more potent than pertuzumab in inducing ADCC. Importantly, in this setting, the combination of pertuzumab with trastuzumab significantly increased the ADCC effect induced by trastuzumab alone (P\ubc0.02). Finally, pertuzumab induced a significant inhibition in the proliferation of all USPC cell lines tested, regardless of their HER-2/neu expression. CONCLUSION: Pertuzumab and trastuzumab induce equally strong ADCC and CDC in FISH-positive USPC cell lines. Pertuzumab significantly increases tratuzumab-induced ADCC against USPC with a low HER2/neu expression and may represent a new therapeutic agent in patients harbouring advanced/recurrent and/or refractory USPC