title: Artificial neural network is highly predictive of outcome in paediatric acute liver failure

authors: Rajanayagam, J.

subjects: acute liver failure

abstract: Current prognostic models in PALF are unreliable, failing to account for complex, non-linear relationships existing between multiple prognostic factors. A computational approach using ANN should provide superior modelling to PELD-MELD scores. We assessed the prognostic accuracy of PELD-MELD scores and ANN in PALF in children presenting to the QLTS, Australia. A comprehensive registry-based data set was evaluated in 54 children (32M, 22F, median age 17 month) with PALF. PELD-MELD scores calculated at (i) meeting PALF criteria and (ii) peak. ANN was evaluated using stratified 10-fold cross-validation. Outcomes were classified as good (transplant-free survival) or poor (death or LT) and predictive accuracy compared using AUROC curves. Mean PELD-MELD scores were significantly higher in non-transplanted non-survivors (i) 37 and (ii) 46 and transplant recipients (i) 32 and (ii) 43 compared to transplant-free survivors (i) 26 and (ii) 30. Threshold PELD-MELD scores ≥27 and ≥42, at meeting PALF criteria and peak, gave AUROC 0.71 and 0.86, respectively, for poor outcome. ANN showed superior prediction for poor outcome with AUROC 0.96, sensitivity 82.6%, specificity 96%, PPV 96.2% and NPV 85.7% (cut-off 0.5). ANN is superior to PELD-MELD for predicting poor outcome in PALF.

text: Artificial neural network is highly predictive of outcome in paediatric acute liver failure Current prognostic models in PALF are unreliable, failing to account for complex, non-linear relationships existing between multiple prognostic factors. A computational approach using ANN should provide superior modelling to PELD-MELD scores. We assessed the prognostic accuracy of PELD-MELD scores and ANN in PALF in children presenting to the QLTS, Australia. A comprehensive registry-based data set was evaluated in 54 children (32M, 22F, median age 17 month) with PALF. PELD-MELD scores calculated at (i) meeting PALF criteria and (ii) peak. ANN was evaluated using stratified 10-fold cross-validation. Outcomes were classified as good (transplant-free survival) or poor (death or LT) and predictive accuracy compared using AUROC curves. Mean PELD-MELD scores were significantly higher in non-transplanted non-survivors (i) 37 and (ii) 46 and transplant recipients (i) 32 and (ii) 43 compared to transplant-free survivors (i) 26 and (ii) 30. Threshold PELD-MELD scores ≥27 and ≥42, at meeting PALF criteria and peak, gave AUROC 0.71 and 0.86, respectively, for poor outcome. ANN showed superior prediction for poor outcome with AUROC 0.96, sensitivity 82.6%, specificity 96%, PPV 96.2% and NPV 85.7% (cut-off 0.5). ANN is superior to PELD-MELD for predicting poor outcome in PALF.

year: 2013

title: Intelligence agencies in cyberspace: Adapting the intelligence cycle to cyber threats and opportunities

authors: Greenwood, Jedediah Warwick

abstract: Intelligence has grown and changed dramatically over the past hundred years with the advent of cyberspace. This thesis will begin by examining how the intelligence cycle has adapted to accommodate cyber threats and opportunities, before conducting three national case studies examining the organisational changes in the signals intelligence agencies in New Zealand, the United Kingdom, and the United States of America. It will utilise the analysis of how the intelligence cycle and States have grown to accommodate cyber phenomenon and will conduct two case studies on the recent events concerning Huawei and the hacking of the 2016 US Election. Through this, this thesis will ultimately show that one of the main responses to cyber by intelligence agencies has been increased social engagement, through interaction with the general public in a familiar cyber environment, such as Twitter, in an endeavour to combat the rise in cyber crime by promoting awareness of cyber security issues and ensuring people have the knowledge and means to keep themselves safe in cyber space. This has also involved the monitoring and combatting of extremist propaganda material disseminated online for the purposes of promoting extremist ideologies and indoctrinating vulnerable people.

text: Intelligence agencies in cyberspace: Adapting the intelligence cycle to cyber threats and opportunities Intelligence has grown and changed dramatically over the past hundred years with the advent of cyberspace. This thesis will begin by examining how the intelligence cycle has adapted to accommodate cyber threats and opportunities, before conducting three national case studies examining the organisational changes in the signals intelligence agencies in New Zealand, the United Kingdom, and the United States of America. It will utilise the analysis of how the intelligence cycle and States have grown to accommodate cyber phenomenon and will conduct two case studies on the recent events concerning Huawei and the hacking of the 2016 US Election. Through this, this thesis will ultimately show that one of the main responses to cyber by intelligence agencies has been increased social engagement, through interaction with the general public in a familiar cyber environment, such as Twitter, in an endeavour to combat the rise in cyber crime by promoting awareness of cyber security issues and ensuring people have the knowledge and means to keep themselves safe in cyber space. This has also involved the monitoring and combatting of extremist propaganda material disseminated online for the purposes of promoting extremist ideologies and indoctrinating vulnerable people.

year: 2020

title: Dating of recent low sea level and Maori rock carvings Ongari Point

authors: Schofield, J.C.

subjects: carving

abstract: A sea level of at least 1.5ft below the present one, and contemporaneous rock carvings have a radiocarbon date of 180±50 years B.P.

text: Dating of recent low sea level and Maori rock carvings Ongari Point A sea level of at least 1.5ft below the present one, and contemporaneous rock carvings have a radiocarbon date of 180±50 years B.P.

year: 1968