590 results for Chase, J.G.

  • Composite slab effects on beam-column subassemblies: Further development

    Chaudhari, T.; MacRae, G.A.; Bull, D.; Chase, J.G.; Hobbs, M. (2014)


    University of Canterbury Library

    Composite slab construction is gaining popularity in New Zealand. These slabs may influence the beam column joint subassemblies as they exposed to earthquake induced shaking. However several design issues with composite slabs need to be addressed so that they can be used to their full advantage in design. These relate to the ability to consider the slab effect on the beam design strength, the likely statistical variation of beam and slab under strong seismic shocks that will affect the column joint demand and the resistance of the panel zone. In this paper, the experimental test setups are described which considers slab isolation, beam overstrength, full depth slab around the column, low damage connection, and demand on the panel zone. A new concept of slab confinement using a shear key will be presented to form a force transfer mechanism to avoid failure of concrete either in crushing or spalling. Also the development of a non-prying sliding hinge joint low damage connection and its performance under composite slab is discussed. The outcome of this will be useful to develop simple design recommendations for the New Zealand steel standard.

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  • Intenzív osztályon ápolt betegek szoros vércukorszabályozása

    Benyo, B.; Homlok, J.; Ilyes, A.; Szabo Nemedi, N.; Shaw, G.M.; Chase, J.G. (2014)

    Conference Contributions - Other
    University of Canterbury Library

    Invited presentation, abstract made of presentation notes by organisers - Thus, the presentation IS the abstract

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  • Clinical Results From a Glycaemic Control Protocol Implementation in Neonatal Care

    Dickson, J.L.; LeCompte, A.J.; Lynn, A.M.; Desaive, T.; Benyo, B.; Chase, J.G. (2014)

    Conference Contributions - Other
    University of Canterbury Library

    Hyperglycaemia is associated with increased mortality and morbidity in neonatal intensive care. STAR-GRYPHON is a model-based glycaemic control protocol, which uses insulin sensitivity to tailor insulin treatments to patients and changing patient condition. It is implemented as a standard of care in a neonatal intensive care unit in Christchurch, New Zealand.

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  • Technologies for semi-automated glucose control, and the impact of the human in the loop

    Chase, J.G.; Shaw, G.M. (2015)

    Conference Contributions - Other
    University of Canterbury Library

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  • Insulin sensitivity as a marker for reduced outcome in the NICU

    Uyttendaele, V.; Dickson, J.L.; Lynn, A.; Chase, J.G.; Desaive, T. (2015)

    Conference Contributions - Other
    University of Canterbury Library

    Hyperglycemia in neonatal intensive care units (NICUs) is associated with mortality and morbidity. This research aims to use machine learning methods to provide a prediction of outcomes in hyperglycemic neonates, based on model-based metabolic (glycemic control) data as a non-invasive marker.

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  • Respiratory mechanics variation during partially supported ventilation

    Kim, K.T.; Chiew, Y.S.; Redmond, D.; Pretty, C.G.; Shaw, G.M.; Desaive, T.; Chase, J.G. (2015)

    Conference Contributions - Other
    University of Canterbury Library

    Respiratory mechanics vary breath-to-breath during mechanical ventilation (MV), and increases during partially supported ventilation modes when patients exhibit spontaneous breathing (SB). While increased variability is associated with patient recovery, SB efforts hinder the application of respiratory mechanics metrics to guide MV. This study quantifies the natural variability of respiratory mechanics during partially supported ventilation.

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  • Respiratory mechanics assessment for reverse-triggered breathing cycles using pressure reconstruction

    Major, V.; Corbett, S.; Redmond, D.; Beatson, A.; Glassenbury, D.; Chiew, Y.S.; Pretty, C.G.; Desaive, T.; Szlávecz, A.; Benyo, B.; Shaw, G.M.; Chase, J.G. (2016)

    Journal article
    University of Canterbury Library

    Monitoring patient-specific respiratory mechanics can be used to guide mechanical ventilation (MV) therapy in critically ill patients. However, many patients can exhibit spontaneous breathing (SB) efforts during ventilator supported breaths, altering airway pressure waveforms and hindering model-based (or other) identification of the true, underlying respiratory mechanics necessary to guide MV. This study aims to accurately assess respiratory mechanics for breathing cycles masked by SB efforts. A cumulative pressure reconstruction method is used to ameliorate SB by identifying SB affected waveforms and reconstructing unaffected pressure waveforms for respiratory mechanics identification using a single-compartment model. Performance is compared to conventional identification without reconstruction, where identified values from reconstructed waveforms should be less variable. Results are validated with 9485 breaths affected by SB, including periods of muscle paralysis that eliminates SB, as a validation test set where reconstruction should have no effect. In this analysis, the patients are their own control, with versus without reconstruction, as assessed by breath-to-breath variation using the non-parametric coefficient of variation (CV) of respiratory mechanics. Pressure reconstruction successfully estimates more consistent respiratory mechanics. CV of estimated respiratory elastance is reduced up to 78% compared to conventional identification (p < 0.05). Pressure reconstruction is comparable (p > 0.05) to conventional identification during paralysis, and generally performs better as paralysis weakens, validating the algorithm’s purpose. Pressure reconstruction provides less-affected pressure waveforms, ameliorating the effect of SB, resulting in more accurate respiratory mechanics identification. Thus providing the opportunity to use respiratory mechanics to guide mechanical ventilation without additional muscle relaxants, simplifying clinical care and reducing risk.

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  • Smart Semi-Active MR Damper to Control the Structural Response

    Hazaveh, N.K.; Chase, J.G.; Rodgers, G.W.; Pampanin, S. (2015)

    Journal Articles
    University of Canterbury Library

    One advanced means of protecting structures against earthquake ground motions is the use of semi-active devices to customise and limit structural response. Thus, the design, modelling and analysis of different semi-active control devices have received increasing research attention. This study presents a method to determine optimal control forces for magneto-rheological (MR) dampers, using three algorithms: a discrete wavelet transform (DWT), a linear quadratic regulator (LQR), and a clipped-optimal control algorithm. DWT is used to obtain the local energy distribution of the motivation over the frequency bands to modify conventional LQR. The clipped-optimal control algorithm is used to get the MR damper control force to approach the desired optimal force obtained from modified LQR. A Bouc-Wen phenomenological model is utilized to capture the observed nonlinear behaviour of MR dampers. Time history analysis for a single degree of freedom (SDOF) with periods of T= 0.2-5.0 sec is utilized to compare the impact of using classic and modified LQR in controlling the MR damper force under 20 design level earthquakes of the SAC (SEAOC-ATC-CUREE) project. Performance is assessed by comparing the maximum displacement (Sd), total base shear (Fb) and the controller energy. This study shows the proposed modified LQR is more effective at reducing displacement response than conventional LQR. The modified LQR method reduces the median value of uncontrolled Sd by approximately 40% to 88%, over all periods to 5.0 seconds. Moreover, the modified LQR uses about 45% less energy than conventional LQR. Overall, these results indicate the robustness of the proposed method to mitigate structural response and damage using MR devices.

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  • Performance Evaluation of CWH Base Isolated Building During Two Major Earthquakes in Christchurch

    Zhou, C.; Chase, J.G.; Rodgers, G.W.; Kuang, A.; Gutschmidt, S.; Xu, C. (2015)

    Journal Articles
    University of Canterbury Library

    The seismic performance and parameter identification of the base isolated Christchurch Women’s Hospital (CWH) building are investigated using the recorded seismic accelerations during the two large earthquakes in Christchurch. A four degrees of freedom shear model is applied to characterize the dynamic behaviour of the CWH building during these earthquakes. A modified Gauss-Newton method is employed to identify the equivalent stiffness and Rayleigh damping coefficients of the building. The identification method is first validated using a simulated example structure and finally applied to the CWH building using recorded measurements from the Mw 6.0 and Mw 5.8 Christchurch earthquakes on December 23, 2011. The estimated response and recorded response for both earthquakes are compared with the cross correlation coefficients and the mean absolute percentage errors reported. The results indicate that the dynamic behaviour of the superstructure and base isolator was essentially within elastic range and the proposed shear linear model is sufficient for the prediction of the structural response of the CWH Hospital during these events.

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  • External validation and sub-cohort analysis of stochastic forecasting models in NICU cohorts

    Dickson, J.L.; Floyd, R.P.; LeCompte, A.J.; Fisk, L.M.; Chase, J.G.; Lynn, A.; Shaw, G.M. (2013)

    Journal Articles
    University of Canterbury Library

    Hyperglycaemia is a prevalent complication in the neonatal intensive care unit (NICU) and is associated with worsened outcomes. It occurs as a result of prematurity, under-developed endogenous glucose regulatory systems, and clinical stress. The stochastic targeting (STAR) framework provides patient-specific, model-based glycaemic control with a clinically proven level of confidence on the outcome of treatment interventions, thus directly managing the risk of hypo- and hyper- glycaemia. However, stochastic models that are over conservative can limit control performance. Retrospective clinical data from 61 episodes (25 retrospective to STAR, and 36 from a prospective-STAR blood glucose control study) of insulin therapy in very-low birth weight (VLBW) and extremely-low birth weight (ELBW) neonates are used to create a new stochastic model of model-based insulin sensitivity (SI [L/mU/min]). Sub-cohort models based on gestational age (GA) and birth weight (BW) are also created. Performance is assessed by the percentage of patients who have 90% of actual intra-patient variability in SI captured by the 90% confidence bands of the cohort based (inter-patient) stochastic variability model created. This assessment measures per-patient accuracy for any given cohort model. Per-patient coverage trends were very similar between prospective and retrospective cohorts, providing a measure of external validation of cohort similarity. Per-patient coverage was improved though the use of BW and GA dependent stochastic models, which ensures that the stochastic models more accurately capture both inter- and intra- patient variability. Stochastic models based on insulin sensitivities during insulin treatment periods are tighter, and give better and safer glycaemic control. Overall it seems that inter-patient variation is more significant than intra-patient variation as a limiting factor in this stochastic forecasting model, and a small number of patients are essentially different in behaviour. More patient specific methods, particularly in the modelling of endogenous insulin and glucose production, will be required to further improve forecasting and glycaemic control.

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  • Beyond ductility: parametric testing of a jointed rocking beam-column connection designed for damage avoidance

    Rodgers, G.W.; Mander, J.B.; Chase, J.G.; Dhakal, R.P. (2016)

    Journal Articles
    University of Canterbury Library

    Despite their good performance in terms of their design objectives, many modern code-prescriptive buildings built in Christchurch, New Zealand had to be razed after the 2010-2011 Canterbury earthquakes because repairs were deemed too costly due to widespread sacrificial damage. Clearly a more effective design paradigm is needed to create more resilient structures. Rocking, post-tensioned connections with supplemental energy dissipation can contribute to a damage avoidance designs (DAD). However, few have achieved all three key design objectives of damage-resistant rocking, inherent recentering ability, and repeatable, damage-free energy dissipation for all cycles, which together offer a response which is independent of loading history. Results of experimental tests are presented for a near full-scale rocking beam-column sub-assemblage. A matrix of test results is presented for the system under varying levels of posttensioning, with and without supplemental dampers. Importantly, this parametric study delineates each contribution to response. Practical limitations on posttensioning are identified: a minimum to ensure static structural re-centering, and a maximum to ensure deformability without threadbar yielding. Good agreement between a mechanistic model and experimental results over all parameters and inputs indicates the model is robust and accurate for design. The overall results indicate that it is possible to create a DAD connection where the non-linear force-deformation response is loading history independent and repeatable over numerous loading cycles, without damage, creating the opportunity for the design and implementation of highly resilient structures.

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  • Novel Stroke Volume Estimation Method from Aortic Pressure Measurements and Aortic Diameter

    Kamoi, S.; Pretty, C.G.; Davidson, S.M.; Chiew, Y.S.; Balmer, J.; Chase, J.G. (2015)

    Conference Contributions - Other
    University of Canterbury Library

    Stroke Volume (SV) is an essential cardiac parameter in assessing and treating patients with cardiovascular dysfunction. However, direct SV measurement are not clinically feasible, requiring highly invasive procedures. Currently, devices for indirect monitoring of SV can be inaccurate during sudden hemodynamic changes, leading to sub-optimal clinical treatment. Thus, there is a need for an accurate, practical monitoring system to estimate SV from available clinical measurements. This work presents a novel SV estimation method using two spatially separated aortic pressure measurements and aortic diameter. Pressure contours from the spatially separated sensors are used to calculate the Pulse Wave Velocity (PWV) in the aorta. PWV combined with a patient-specific estimate of the aortic diameter allow the aortic characteristic impedance to be determined. A three-element Windkessel model uses the characteristic impedance to identify the resistance and compliance of the aorta from pressure contours. Flow rates can then be calculated and integrated to deliver a beat-to-beat estimate of SV. Currently, the method has been validated using data from five porcine experiments where rapid SV changes were made by changing positive end-expiratory pressure on the mechanical ventilator. The result showed high agreement and correlation between model-based estimates of SV and measured SV using an admittance catheter. This novel SV estimation method accurately captures dynamics during sudden changes made in the hemodynamic conditions, as well as changes due to breathing, providing crucial information for optimizing treatment. The method has great potential for improving cardiac and circulatory treatment in the critical care environment.

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  • Seismic performance of slender rocking wall-frames

    Kordani, R.; Rodgers, G.W.; MacRae, G.A.; Chase, J.G. (2015)

    Conference Contributions - Other
    University of Canterbury Library

    Design and development of rocking frames is an advanced method to ensure the seismic resilience of structures by creating a non-linear elastic response. Dissipating significant amounts of energy without sacrificing structural components is the key objective of implementing rocking frames. However there are some issues that need to be addressed to enable designers to consider these systems without the need for full time-history analysis. For instance building response prediction and the implications of impact loads induced during rocking on horizontal and vertical floor accelerations and the resulting effects of building contents must be fully characterised. In this study higher mode effects are identified and their influence on moment and shear demands on rocking frames of different aspect ratios is highlighted. Simplified design methods are also developed to capture the important dynamics without the need for engineers to develop dynamic structural models and time-history analysis. These methods can be used by designers to develop quick, robust designs of rocking frame systems.

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  • Insulin Sensitivity Profile as a Marker for Reduced Outcome in the Neonatal Intensive Care Unit

    Uyttendaele, V.; Dickson, J.L.; Lynn, A.; Chase, J.G.; Desaive, T. (2015)

    Conference Contributions - Other
    University of Canterbury Library

    Objective: Hyperglycemia in neonatal intensive care units is associated with mortality and morbidity. This trial aims to use machine learning methods to provide a prediction of outcomes in hyperglycemic neonates, based on model-based metabolic (glycemic control) data as a non-invasive marker. Method: Glycemic control data from 44 patients (4499 hours) under the STAR-NICU or STAR-GRYPHON model-based glycemic controllers from Christchurch Women’s Hospital were used. Predictive models were built using attributes from hourly, patient-specific, model-based insulin sensitivity. Among these patients, 12 contracted sepsis, 8 suffered from intraventricular hemorrhage (IVH), and 8 died. The methods used were classification trees and K-nearest neighbors. The efficacy of the models was assessed evaluating sensitivity, specificity and accuracy. Result: Mean insulin sensitivity was different among different sub-groups: 7.51×10-4, 5.47×10-4, 2.42×10-4, and 7.50×10-4L/mU/min for patients who were septic, had IVH>grade 1, non-survivors, and survivors respectively. Variability assessed as IQR range was also different between groups, with 1.00×10-4, 4.99×10-5, 4.22×10-5, and 9.09×10-5L/mU/min respectively. It was possible to predict mortality with 85% sensitivity after the first 15 hours, and (later proven) sepsis with sensitivity of 80% within 20 hours. Conclusion: A clinically validated model-based insulin sensitivity measure and its variability, may provide information about patient condition and possible outcome, despite modeling limitations. This study emphasized the potential of machine learning to provide information on degrading patient condition and worsened outcome, as an alert to provide more intensive care.

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  • Is the Asymmetrical Friction Connection (AFC) a low damage dissipater?

    Chanchi Golondrino, J.; MacRae, G.A.; Chase, J.G.; Rodgers, G.W.; Clifton, C. (2015)

    Conference Contributions - Published
    University of Canterbury Library

    Asymmetrical Friction Connections (AFC) are used in structures in earthquake zones to dissipate energy without causing major damage to the structural members. This means that the structure itself does not require replacement after a major seismic event. Testing of these connections has been undertaken and degradation in strength has been observed. However, (i) reasons for this degradation have not been clear, (ii) a means of assessing the strength degradation has not been available, (iii) the importance of the strength degradation (which is related to the amount of strength degradation) has not been described, (iv) the ability to reinstate the joint using new bolts is not known, and (v) effective friction factors for the connection after connection reinstatement are not known. This paper describes the testing of AFC specimens with high hardness shims (i.e. Bisalloy 500) under increasing cyclic displacements to address the issues stated above. Tests were conducted twice with the same setup. In the second test, the change in performance as a result of the first test was able to be observed. Then the bolts were replaced and tests were conducted twice more.

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  • Development and optimisation of stochastic targeted (STAR) glycaemic control for pre-term infants in neonatal intensive care

    Dickson, J.L.; Le Compte, A.J.; Floyd, R.P.; Chase, J.G.; Lynn, A.; Shaw, G.M. (2013)

    Journal Articles
    University of Canterbury Library

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  • Basal Glucose is just the first measured point ... right?

    Docherty, P.D.; Othman, N.A.; Chase, J.G.; Bell, D.A.; Krebs, J.D. (2015)

    Conference Contributions - Other
    University of Canterbury Library

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  • Identifying pressure dependent elastance in lung mechanics with reduced influence of unmodelled effects

    Laufer, B.; Docherty, P.D.; Chiew, Y.S.; Moeller, K.; Chase, J.G. (2015)

    Conference Contributions - Other
    University of Canterbury Library

    The selection of optimal positive end expiratory pressure (PEEP) levels during ventilation therapy of patients with ARDS (acute respiratory distress syndrome) remains a problem for clinicians. One particular mooted strategy states that minimizing the energy transferred to the lung by mechanical ventilation could potentially be used to determine the optimal PEEP level. This minimization could potentially be undertaken by finding the minimum range of dynamic elastance. In this study, we compare an adapted Gauss-Newton method with the typical gauss newton method in terms of the level of agreement obtained in elastance-pressure curves across different PEEP levels in 10 patients. The Gauss-Newton adaptation effectively ignored characteristics in the data that are un-modelled. The adapted method successfully determined regions of the data that were un-modelled, as expected. In ignoring this un-modelled behavior, the adapted method captured the desired elastance-pressure curves with more consistency than the typical least-squares Gauss Newton method.

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  • Complexity of Continuous Glucose Monitoring Data in Critically Ill Patients: CGM Devices, Sensor Locations, and DFA Methods

    Signal, M.; Thomas, F.; Shaw, G.M.; Chase, J.G. (2013)

    Journal Articles
    University of Canterbury Library

    BACKGROUND: Critically ill patients often experience high levels of insulin resistance and stress-induced hyperglycemia, which may negatively impact outcomes. However, evidence surrounding the causes of negative outcomes remains inconclusive. Continuous glucose monitoring (CGM) devices allow researchers to investigate glucose complexity, using detrended fluctuation analysis (DFA), to determine whether it is associated with negative outcomes. AIM: The aim of this study was to investigate the effects of CGM device type/calibration and CGM sensor location on results from DFA. METHODS: This study uses CGM data from critically ill patients who were each monitored concurrently using Medtronic iPro2’s on the thigh and abdomen, and a Medtronic Guardian Real-Time on the abdomen. This allowed inter-device/calibration type and inter-sensor site variation to be assessed. DFA is a technique that has previously been used to determine the complexity of CGM data in critically ill patients. Two variants of DFA, monofractal and multifractal, were used to assess the complexity of sensor glucose (SG) data, as well as the pre-calibration raw sensor current. Monofractal DFA produces a scaling exponent (H), where H is inversely related to complexity. The results of multifractal DFA are presented graphically, by the multifractal spectrum. RESULTS: From the 10 patients recruited, 26 CGM devices produced data suitable for analysis. The values of H from abdominal iPro2 data were 0.10 [0.03 – 0.20] higher than those from Guardian Real-Time data, indicating consistently lower complexities in iPro2 data. However, repeating the analysis on the raw sensor current showed little or no difference in complexity. Sensor site had little effect on the scaling exponents in this data set. Finally, multi-fractal DFA revealed no significant associations between the multifractal spectrums and CGM device type/calibration or sensor location. CONCLUSIONS: Monofractal DFA results are dependent on the device/calibration used to obtain CGM data, but sensor location has little impact. Future studies of glucose complexity should consider the findings presented here when designing their investigations.

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  • Multiplicative Surrogate Standard Deviation: A Group Metric for the Glycemic Variability of Individual Hospitalized Patients

    Braithwaite, S.S.; Umpierrez, G.E.; Chase, J.G. (2013)

    Journal Articles
    University of Canterbury Library

    Objective: Group metrics are described to quantify blood glucose (BG) variability of hospitalized patients. Methods: The “multiplicative surrogate standard deviation” (MSSD) is the reverse-transformed group mean of the standard deviations (SD) of the logarithmically-transformed blood glucose (BG) data set of each patient. The “geometric group mean” (GGM) is the reverse-transformed group mean of the means of the logarithmically-transformed BG data set of each patient. Before reverse-transformation is performed, the mean of means and mean of SD’s each has its own SD, which becomes a multiplicative standard deviation (MSD) after reverse-transformation. Statistical predictions and comparisons of parametric or nonparametric tests remain valid after reverse-transformation. A subset of a previously-published BG data set of 20 critically ill patients from the first 72 hr of treatment under the SPRINT protocol was transformed logarithmically. After rank-ordering according to the mean of the SD of the logarithmically-transformed BG data of each patient, the cohort was divided into 2 equal groups, those having lower or higher variability. Results: For the entire cohort, the GGM was 106 mg/dL (÷/× 1.07), and MSSD was 1.24 (÷/× 1.07). For the subgroups having lower and higher variability respectively, the GGM in mg/dL did not differ, 104(÷/× 1.07) vs. 109 (÷/× 1.07), but the MSSD differed, 1.17 (÷/× 1.03) vs. 1.31 (÷/× 1.05), p = 0.00004. Conclusion: By using the MSSD with its MSD, groups can be characterized and compared according to glycemic variability of individual patient members.

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