Computing and Information Systems - Research Publications
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ItemNo Preview AvailableEthical frameworks should be applied to computational modelling of infectious disease interventions(PUBLIC LIBRARY SCIENCE, 2024-03)This perspective is part of an international effort to improve epidemiological models with the goal of reducing the unintended consequences of infectious disease interventions. The scenarios in which models are applied often involve difficult trade-offs that are well recognised in public health ethics. Unless these trade-offs are explicitly accounted for, models risk overlooking contested ethical choices and values, leading to an increased risk of unintended consequences. We argue that such risks could be reduced if modellers were more aware of ethical frameworks and had the capacity to explicitly account for the relevant values in their models. We propose that public health ethics can provide a conceptual foundation for developing this capacity. After reviewing relevant concepts in public health and clinical ethics, we discuss examples from the COVID-19 pandemic to illustrate the current separation between public health ethics and infectious disease modelling. We conclude by describing practical steps to build the capacity for ethically aware modelling. Developing this capacity constitutes a critical step towards ethical practice in computational modelling of public health interventions, which will require collaboration with experts on public health ethics, decision support, behavioural interventions, and social determinants of health, as well as direct consultation with communities and policy makers.
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ItemNo Preview AvailableA Novel Blended Transdiagnostic Intervention (eOrygen) for Youth Psychosis and Borderline Personality Disorder: Uncontrolled Single-Group Pilot Study(JMIR PUBLICATIONS, INC, 2024)BACKGROUND: Integrating innovative digital mental health interventions within specialist services is a promising strategy to address the shortcomings of both face-to-face and web-based mental health services. However, despite young people's preferences and calls for integration of these services, current mental health services rarely offer blended models of care. OBJECTIVE: This pilot study tested an integrated digital and face-to-face transdiagnostic intervention (eOrygen) as a blended model of care for youth psychosis and borderline personality disorder. The primary aim was to evaluate the feasibility, acceptability, and safety of eOrygen. The secondary aim was to assess pre-post changes in key clinical and psychosocial outcomes. An exploratory aim was to explore the barriers and facilitators identified by young people and clinicians in implementing a blended model of care into practice. METHODS: A total of 33 young people (aged 15-25 years) and 18 clinicians were recruited over 4 months from two youth mental health services in Melbourne, Victoria, Australia: (1) the Early Psychosis Prevention and Intervention Centre, an early intervention service for first-episode psychosis; and (2) the Helping Young People Early Clinic, an early intervention service for borderline personality disorder. The feasibility, acceptability, and safety of eOrygen were evaluated via an uncontrolled single-group study. Repeated measures 2-tailed t tests assessed changes in clinical and psychosocial outcomes between before and after the intervention (3 months). Eight semistructured qualitative interviews were conducted with the young people, and 3 focus groups, attended by 15 (83%) of the 18 clinicians, were conducted after the intervention. RESULTS: eOrygen was found to be feasible, acceptable, and safe. Feasibility was established owing to a low refusal rate of 25% (15/59) and by exceeding our goal of young people recruited to the study per clinician. Acceptability was established because 93% (22/24) of the young people reported that they would recommend eOrygen to others, and safety was established because no adverse events or unlawful entries were recorded and there were no worsening of clinical and social outcome measures. Interviews with the young people identified facilitators to engagement such as peer support and personalized therapy content, as well as barriers such as low motivation, social anxiety, and privacy concerns. The clinician focus groups identified evidence-based content as an implementation facilitator, whereas a lack of familiarity with the platform was identified as a barrier owing to clinicians' competing priorities, such as concerns related to risk and handling acute presentations, as well as the challenge of being understaffed. CONCLUSIONS: eOrygen as a blended transdiagnostic intervention has the potential to increase therapeutic continuity, engagement, alliance, and intensity. Future research will need to establish the effectiveness of blended models of care for young people with complex mental health conditions and determine how to optimize the implementation of such models into specialized services.
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ItemNo Preview AvailableUser-oriented metrics for search engine deterministic sort orders(ELSEVIER SCI LTD, 2024-01)
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ItemNo Preview AvailableModeling of microalgal shear-induced flocculation and sedimentation using a coupled CFD-population balance approach.(Wiley, 2018)In this study, shear-induced flocculation modeling of Chlorella sp. microalgae was conducted by combination of population balance modeling and CFD. The inhomogeneous Multiple Size Group (MUSIG) and the Euler-Euler two fluid models were coupled via Ansys-CFX-15 software package to achieve both fluid and particle dynamics during the flocculation. For the first time, a detailed model was proposed to calculate the collision frequency and breakage rate during the microalgae flocculation by means of the response surface methodology as a tool for optimization. The particle size distribution resulted from the model was in good agreement with that of the jar test experiment. Furthermore, the subsequent sedimentation step was also examined by removing the shear rate in both simulations and experiments. Consequently, variation in the shear rate and its effects on the flocculation behavior, sedimentation rate and recovery efficiency were evaluated. Results indicate that flocculation of Chlorella sp. microalgae under shear rates of 37, 182, and 387 s-1 is a promising method of pre-concentration which guarantees the cost efficiency of the subsequent harvesting process by recovering more than 90% of the biomass.
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ItemNye tray vs sieve tray: A comparison based on computational fluid dynamics and tray efficiency(Wiley, 2021-10)Nye and sieve trays were hydrodynamically simulated and compared. The simulations were performed in a Eulerian‐Eulerian framework under unsteady (transient) conditions at industrial scale. Conducted on an air‐water system, the simulations included three dimensions and two phases. The velocity distribution across the tray, the height of clear liquid, the froth height, and the pressure drop were investigated and compared with experimental data. Péclet number was calculated using hydrodynamic and geometric parameters. The tray efficiencies were also predicted to further compare the two trays. The results showed that the liquid flow was steadier on the Nye tray rather than the sieve tray, possibly because of the special structure of the liquid and gas inlets for the Nye tray.
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ItemComputational Fluid Dynamics versus Experiment: An Investigation on Liquid Weeping of Nye Trays(Wiley, 2021-01)The weeping phenomenon was investigated using some experimental tests and a numerical model. The tests were performed within a 1.22‐m‐diameter pilot‐scale column including two chimney trays and two Nye test trays with an air‐water system. The rates of weeping were measured in the Nye trays with two heights of the weir and a hole area of 5 %. Moreover, the weeping rates in the outlet and inlet halves of the Nye tray and the total weeping rate were calculated. In the next step, an Eulerian‐Eulerian computational fluid dynamics (CFD) technique was used. The results show good agreement between the attained CFD findings and the experimental data.
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ItemExperimental investigation, numerical simulation and RSM modelling of the freezing and thawing of Mozzarella cheese(Elsevier, 2024-01)Freezing can be used to preserve functionality of Mozzarella cheese allowing export to distant markets but limited tools are available for prediction of freezing and thawing times as a function of composition and processing variables. Freezing and thawing processes were experimentally and numerically assessed for six Mozzarella samples, differing significantly in block size and composition. Numerical simulations using an enthalpy method were developed to build a validated and robust model for solving heat and mass transfer equations. A decrease in salt (NaCl) content from 1.34 % w/w to 0.07 % significantly altered the temperature of phase change from ∼–4.5 °C to –3 °C. Simulations showed minimal impact of salt migration on the salt in free moisture content deeper than ∼1–2 centimeters from the surface during freezing, with a slight increase of 8–10 % salt in free moisture at the block center. A response surface methodology (RSM) model was fit to the simulated data providing a useful tool for predicting freezing and thawing times for block sizes and a wider range of operating conditions enabling future process optimization. The RSM model indicated that increased salt content increased freezing time but decreased thawing time.
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ItemMachine learning for the prediction of proteolysis in Mozzarella and Cheddar cheese(Elsevier, 2024-03)Proteolysis is a complex biochemical event during cheese storage that affects both functionality and quality, yet there are few tools that can accurately predict proteolysis for Mozzarella and Cheddar cheese across a range of parameters and storage conditions. Machine learning models were developed with input features from the literature. A gradient boosting method outperformed random forest and support vector regression methods in predicting proteolysis for both Mozzarella (R2 = 92%) and Cheddar (R2 = 97%) cheese. Storage time was the most important input feature for both cheese types, followed by coagulating enzyme concentration and calcium content for Mozzarella cheese and fat or moisture content for Cheddar cheese. The ability to predict proteolysis could be useful for manufacturers, assisting in inventory management to ensure optimum Mozzarella functionality and Cheddar with a desired taste, flavor and texture; this approach may also be extended to other types of cheese.