Chemical and Biomedical Engineering - Research Publications
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ItemNo Preview AvailableWildfire-related PM2.5 and DNA methylation: An Australian twin and family study(PERGAMON-ELSEVIER SCIENCE LTD, 2023-01-01)BACKGROUND: Wildfire-related fine particulate matter (PM2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM2.5. METHODS: We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant's home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate. RESULTS: The 3-year average wildfire-related PM2.5 (range: 0.3 to 7.6 µg/m3, mean: 1.6 µg/m3) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM2.5 (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM2.5. CONCLUSIONS: Long-term exposure to wildfire-related PM2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM2.5.
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ItemThe impact of inter-observer variation in delineation on robustness of radiomics features in non-small cell lung cancer(NATURE PORTFOLIO, 2022-07-27)Artificial intelligence and radiomics have the potential to revolutionise cancer prognostication and personalised treatment. Manual outlining of the tumour volume for extraction of radiomics features (RF) is a subjective process. This study investigates robustness of RF to inter-observer variation (IOV) in contouring in lung cancer. We utilised two public imaging datasets: 'NSCLC-Radiomics' and 'NSCLC-Radiomics-Interobserver1' ('Interobserver'). For 'NSCLC-Radiomics', we created an additional set of manual contours for 92 patients, and for 'Interobserver', there were five manual and five semi-automated contours available for 20 patients. Dice coefficients (DC) were calculated for contours. 1113 RF were extracted including shape, first order and texture features. Intraclass correlation coefficient (ICC) was computed to assess robustness of RF to IOV. Cox regression analysis for overall survival (OS) was performed with a previously published radiomics signature. The median DC ranged from 0.81 ('NSCLC-Radiomics') to 0.85 ('Interobserver'-semi-automated). The median ICC for the 'NSCLC-Radiomics', 'Interobserver' (manual) and 'Interobserver' (semi-automated) were 0.90, 0.88 and 0.93 respectively. The ICC varied by feature type and was lower for first order and gray level co-occurrence matrix (GLCM) features. Shape features had a lower median ICC in the 'NSCLC-Radiomics' dataset compared to the 'Interobserver' dataset. Survival analysis showed similar separation of curves for three of four RF apart from 'original_shape_Compactness2', a feature with low ICC (0.61). The majority of RF are robust to IOV, with first order, GLCM and shape features being the least robust. Semi-automated contouring improves feature stability. Decreased robustness of a feature is significant as it may impact upon the features' prognostic capability.
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ItemPlease Place Your Seat in the Full Upright Position: A Technical Framework for Landing Upright Radiation Therapy in the 21(st) Century(FRONTIERS MEDIA SA, 2022-03-03)Delivering radiotherapy to patients in an upright position can allow for increased patient comfort, reduction in normal tissue irradiation, or reduction of machine size and complexity. This paper gives an overview of the requirements for the delivery of contemporary arc and modulated radiation therapy to upright patients. We explore i) patient positioning and immobilization, ii) simulation imaging, iii) treatment planning and iv) online setup and image guidance. Treatment chairs have been designed to reproducibly position seated patients for treatment and can be augmented by several existing immobilisation systems or promising emerging technologies such as soft robotics. There are few solutions for acquiring CT images for upright patients, however, cone beam computed tomography (CBCT) scans of upright patients can be produced using the imaging capabilities of standard Linacs combined with an additional patient rotation device. While these images will require corrections to make them appropriate for treatment planning, several methods indicate the viability of this approach. Treatment planning is largely unchanged apart from translating gantry rotation to patient rotation, allowing for a fixed beam with a patient rotating relative to it. Rotation can be provided by a turntable during treatment delivery. Imaging the patient with the same machinery as used in treatment could be advantageous for online plan adaption. While the current focus is using clinical linacs in existing facilities, developments in this area could also extend to lower-cost and mobile linacs and heavy ion therapy.
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ItemMajor Trends in the Mineral Processing Industry(Springer Science and Business Media LLC, 2013-02)
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ItemNo Preview AvailableAdsorption Behavior of Divalent Metal Ions onto Surface-functionalized Mesoporous Silicate MCM-41 Having Schiff Base Structure(SPRINGERNATURE, 2021-04-01)Surface functionalized mesoporous silicates, MCM-41s, having 3-(2-pyridylmethylideneimino)propyl group (PI-MCM-41) or 3-(2-quinolylmethylideneimino)propyl group (QI-MCM-41) were prepared via Schiff base reaction, and the adsorption behavior of metal ions onto the modified MCM-41s was investigated. The function groups on the modified MCM-41 surface were confirmed by Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and elemental analysis. The metal ions examined, Co2+, Ni2+, Cu2+, Zn2+, Cd2+, and Pb2+, were quantitatively adsorbed on the PI-MCM-41 and QI-MCM-41, except for Mn2+. In the complexation with these metal ions, it was suggested that imine-N and heterocyclic-N atoms act as donor atoms. In addition, it was considered that the hydrophobicity derived from the organo-functional groups modified on MCM-41 contributed to improving the adsorption ability.
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ItemAdvanced natural language processing technique to predict patient disposition based on emergency triage notes(WILEY, 2020-10-11)OBJECTIVE: To demonstrate the potential of machine learning and capability of natural language processing (NLP) to predict disposition of patients based on triage notes in the ED. METHODS: A retrospective cohort of ED triage notes from St Vincent's Hospital (Melbourne) was used to develop a deep-learning algorithm that predicts patient disposition. Bidirectional Encoder Representations from Transformers, a recent language representation model developed by Google, was utilised for NLP. Eighty percent of the dataset was used for training the model and 20% was used to test the algorithm performance. Ktrain library, a wrapper for TensorFlow Keras, was employed to develop the model. RESULTS: The accuracy of the algorithm was 83% and the area under the curve was 0.88. Sensitivity, specificity, precision and F1-score of the algorithm were 72%, 86%, 56% and 63%, respectively. CONCLUSION: Machine learning and NLP can be together applied to the ED triage note to predict patient disposition with a high level of accuracy. The algorithm can potentially assist ED clinicians in early identification of patients requiring admission by mitigating the cognitive load, thus optimises resource allocation in EDs.
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ItemClean Power Technology(Gaodeng Jiaoyu Chubanshe, 2020-12-01)It is timely that Engineering should devote a special issue to the topic of clean energy. The authors of the research articles and the views and comments cover much of what is a very diverse and controversial field. Responses to this topic cover a spectrum ranging from those that argue for emergency action to prevent the extinction of the human race to those that deny the existence of climate change. Before dismissing any group, it is informative for engineers and technologists to note that there is a fairly even distribution across this spectrum
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ItemCODE STROKE ALERT-Concept and Development of a Novel Open-Source Platform to Streamline Acute Stroke Management(FRONTIERS MEDIA SA, 2019-07-31)Introduction: Effective, time-critical intervention in acute stroke is crucial to mitigate mortality rate and morbidity, but delivery of reperfusion treatments is often hampered by pre-, in-, or inter-hospital system level delays. Disjointed, repetitive, and inefficient communication is a consistent contributor to avoidable treatment delay. In the era of rapid reperfusion therapy for ischemic stroke, there is a need for a communication system to synchronize the flow of clinical information across the entire stroke journey. Material/Methods: A multi-disciplinary development team designed an electronic communications platform, integrated between web browsers and a mobile application, to link all relevant members of the stroke treatment pathway. The platform uses tiered notifications, geotagging, incorporates multiple clinical score calculators, and is compliant with security regulations. The system safely saves relevant information for audit and research. Results: Code Stroke Alert is a platform that can be accessed by emergency medical services (EMS) and hospital staff, coordinating the flow of information during acute stroke care, reducing duplication, and error in clinical information handover. Electronic data logs provide an auditable trail of relevant quality improvement metrics, facilitating quality improvement, and research. Discussion: Code Stroke Alert will be freely available to health networks globally. The open-source nature of the software offers valuable potential for future development of plug-ins and add-ons, based on individual institutional needs. Prospective, multi-site implementation, and measurement of clinical impact are underway.
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ItemCFD Simulation of Two-Phase Flow in a Hybrid Pulsed Sieve-Plate Solvent Extraction Column: Prediction of Holdup and Axial-dispersion Coefficients(Taylor & Francis, 2020-01-02)Two-phase computational fluid dynamics (CFD) models for a hybrid pulsed sieve-plate solvent extraction column, as well as a standard pulsed sieve-plate column, have been developed with commercial software ANSYS FLUENT. Hydrodynamic performance including two-phase distribution and velocity fields are generated with the models and comparisons are made between two columns. Important parameters including holdup and axial-dispersion coefficients are studied systematically, and CFD successfully predicts the higher holdup and lower axial-dispersion coefficients for the hybrid pulsed sieve-plate column as measured in the experiments. CFD also gives reasonable predictions for the effect of pulsation intensity, dispersed-phase velocity, and continuous-phase velocity on holdup, except for the effect of pulsation intensity in low pulsation region, and the cause has been discussed from the perspective of droplet breakage and coalescence. Comparison with literature data shows that CFD underestimates the holdup of hybrid pulsed sieve-plate column and standard pulsed sieve-plate column by 23.3% and 31.4%, respectively, and the cause has been discussed from the perspective of drag law. CFD gives good prediction of axial-dispersion coefficients for the hybrid pulsed sieve-plate column and the standard pulsed sieve-plate column with ARD of 12.0% and 14.3%, respectively. This study shows CFD to be a useful tool to predict performance for the novel hybrid pulsed sieve-plate column as well as the standard pulsed sieve-plate column.