A corporate failure prediction model for non-financial South African corporates incorporating best practices used by the credit industry

In the context of the current macroeconomic environment there is an expectation of an increase in South African non-financial corporate failure, where advance prediction thereof will become even more important. A number of South African non-financial corporate failures have occurred following the financial crisis. In addition, South Africa experienced a watershed moment with the first default on a non-financial corporate bond in 2013. At the same time, with the adoption of the International Financial Reporting Standards (IFRS) framework there have been significant advances in the quality of financial information which should improve its usage in predicting corporate failure. This study used the latest sample to date of listed South African non-financial corporates that met the definition of failure but limited the universe of financial information to that which was prepared under IFRS. At the same time, adjustments were made to the financial data based upon pre-selection of independent credit statistic variables most commonly used in ranking relative credit risk for non-financial corporates. Additionally, equity market price data was introduced into the model to add a forward-looking information consideration. This resulted in an eleven variable model where differentiation of corporate failure was facilitated through the use of multiple discriminant analysis

Social Insect-Inspired Adaptive Hardware

Modern VLSI transistor densities allow large systems to be implemented within a single chip. As technologies get smaller, fundamental limits of silicon devices are reached resulting in lower design yields and post-deployment failures. Many-core systems provide a platform for leveraging the computing resource on offer by deep sub-micron technologies and also offer high-level capabilities for mitigating the issues with small feature sizes. However, designing for many-core systems that can adapt to in-field failures and operation variability requires an extremely large multi-objective optimisation space. When a many-core reaches the size supported by the densities of modern technologies (thousands of processing cores), finding design solutions in this problem space becomes extremely difficult. Many biological systems show properties that are adaptive and scalable. This thesis proposes a self-optimising and adaptive, yet scalable, design approach for many-core based on the emergent behaviours of social-insect colonies. In these colonies there are many thousands of individuals with low intelligence who contribute, without any centralised control, to complete a wide range of tasks to build and maintain the colony. The experiments presented translate biological models of social-insect intelligence into simple embedded intelligence circuits. These circuits sense low-level system events and use this manage the parameters of the many-core's Network-on-Chip (NoC) during runtime. Centurion, a 128-node many-core, was created to investigate these models at large scale in hardware. The results show that, by monitoring a small number of signals within each NoC router, task allocation emerges from the social-insect intelligence models that can self-configure to support representative applications. It is demonstrated that emergent task allocation supports fault tolerance with no extra hardware overhead. The response-threshold decision making circuitry uses a negligible amount of hardware resources relative to the size of the many-core and is an ideal technology for implementing embedded intelligence for system runtime management of large-complexity single-chip systems

Quantifying N2O and CO2 emissions from subtropical pasture

Greenhouse gas emissions from a well established, unfertilized tropical grass-legume pasture were monitored over two consecutive years using high resolution automatic sampling. Nitrous oxide emissions were highest during the summer months and were highly episodic, related more to the size and distribution of rain events than WFPS alone. Mean annual emissions were significantly higher during 2008 (5.7 ± 1.0 g N2O-N/ha/day) than 2007 (3.9 ± 0.4 and g N2O-N/ha/day) despite receiving nearly 500 mm less rain. Mean CO2 (28.2 ± 1.5 kg CO2 C/ha/day) was not significantly different (P 70% indicated a threshold for soil conditions favouring denitrification. The use of automatic chambers for high resolution greenhouse gas sampling can greatly reduce emission estimation errors associated with temperature and WFPS changes

Nitrous oxide emissions from irrigated cotton soils of northern Australia

An automated gas sampling methodology has been used to estimate nitrous oxide (N2O) emissions from heavy black clay soil in northern Australia where split applications of urea were applied to furrow irrigated cotton. Nitrous oxide emissions from the beds were 643 g N/ha over the 188 day measurement period (after planting), whilst the N2O emissions from the furrows were significantly higher at 967 g N/ha. The DNDC model was used to develop a full season simulation of N2O and N2 emissions. Seasonal N2O emissions were equivalent to 0.83% of applied N, with total gaseous N losses (excluding NH3) estimated to be 16% of the applied N

Embedded Social Insect-Inspired Intelligence Networks for System-level Runtime Management

Large-scale distributed computing architectures such as, e.g. systems on chip or many-core devices, offer advantages over monolithic or centralised single-core systems in terms of speed, power/thermal performance and fault tolerance. However, these are not implicit properties of such systems and runtime management at software or hardware level is required to unlock these features. Biological systems naturally present such properties and are also adaptive and scalable. To consider how these can be similarly achieved in hardware may be beneficial. We present Social Insect behaviours as a suitable model for enabling autonomous runtime management (RTM) in many-core architectures. The emergent properties sought to establish are self-organisation of task mapping and systemlevel fault tolerance. For example, large social insect colonies accomplish a wide range of tasks to build and maintain the colony. Many thousands of individuals, each possessing relatively little intelligence, contribute without any centralised control. Hence, it would seem that social insects have evolved a scalable approach to task allocation, load balancing and robustness that can be applied to large many-core computing systems. Based on this, a self-optimising and adaptive, yet fundamentally scalable, design approach for many-core systems based on the emergent behaviours of social-insect colonies are developed. Experiments capture decision-making processes of each colony member to exhibit such high-level behaviours and embed these decision engines within the routers of the many-core system

Social-Insect-Inspired Adaptive Task Allocation for Many-Core Systems

Large social insect colonies require a wide range of important tasks to be undertaken to build and maintain the colony. Fortunately, in most nests there are many thousands of workers available to offer their assistance to ensure the expansion and survival of the colony. However, there is a crucial equilibrium between the number of workers performing each task that must not only be maintained but must also continuously adapt to sudden changes in environment and colony need. What is most fascinating is that social insects can sustain this balance without any centralised control and with colony members that have relatively little intelligence when considered on their own. Due to this simplicity and evident scalability it would seem that social insects have evolved an interesting scalable approach to task allocation that could be applied to very large many-core systems. To investigate this we have explored biological models of task allocation in ant colonies and applied this to a 36-core Network on Chip. This paper not only shows that effective decentralised task allocation is achieved, but also that such a scheme can adapt to faults and alter its behaviour to meet soft real-time constraints. Therefore, it is established that social insect inspired intelligence models offer a suitable metaphor and development direction for tackling the challenges introduced by dark silicon and in-field faults in a decentralised and adaptive fashion

The long haul: Caring for bone marrow transplant patients in regional Australia

Objective To evaluate the experience of, and services to, patients from rural and regional Australia referred to a large urban tertiary referral hospital for allogeneic haematopoietic cell transplantation (allo‑HCT) and to compare their quality of life with similar populations. Design and setting A cross‑sectional survey of allo‑HCT recipients referred from the Calvary Mater Newcastle to Westmead Hospital, Sydney, NSW. Subjects Thirty‑seven of forty adult survivors of allo‑HCT (92.5%) who underwent transplant between 1999 and 2008 and were at least three months post transplant. Intervention All subjects completed a validated measure of quality‑of‑life (QoL) in bone marrow transplant recipients ( FACT‑BMT Version 4) and the Regional/Rural BMT Needs Assessment Survey. Results Most patients (79%) were between one and five years post transplant. Almost all reported having been sufficiently prepared for transplant and received most information and support from the Nurse Coordinator. Despite the fact that 89% of patients reported significant adverse effects of allo‑HCT, >60% still reported an acceptable quality of life. Importantly, however, about a third of patients experienced financial difficulties associated with transplantation and felt pressure to return to work. Conclusion Patients referred for allo‑HCT should be advised about the arduousness of transplant but also reassured that most survivors will experience acceptable levels of functioning and QoL one to two years after transplant. With sufficient local support and with appropriate nursing care and coordination the experiences of regional/rural patients is comparable with other allo‑HCT patient populations. Further investigation into vocational rehabilitation is warranted due to the significant financial and occupational pressures reported by survivors of allo‑HC

The long haul: Caring for bone marrow transplant patients in regional Australia

Objective To evaluate the experience of, and services to, patients from rural and regional Australia referred to a large urban tertiary referral hospital for allogeneic haematopoietic cell transplantation (allo‑HCT) and to compare their quality of life with similar populations. Design and setting A cross‑sectional survey of allo‑HCT recipients referred from the Calvary Mater Newcastle to Westmead Hospital, Sydney, NSW. Subjects Thirty‑seven of forty adult survivors of allo‑HCT (92.5%) who underwent transplant between 1999 and 2008 and were at least three months post transplant. Intervention All subjects completed a validated measure of quality‑of‑life (QoL) in bone marrow transplant recipients ( FACT‑BMT Version 4) and the Regional/Rural BMT Needs Assessment Survey. Results Most patients (79%) were between one and five years post transplant. Almost all reported having been sufficiently prepared for transplant and received most information and support from the Nurse Coordinator. Despite the fact that 89% of patients reported significant adverse effects of allo‑HCT, >60% still reported an acceptable quality of life. Importantly, however, about a third of patients experienced financial difficulties associated with transplantation and felt pressure to return to work. Conclusion Patients referred for allo‑HCT should be advised about the arduousness of transplant but also reassured that most survivors will experience acceptable levels of functioning and QoL one to two years after transplant. With sufficient local support and with appropriate nursing care and coordination the experiences of regional/rural patients is comparable with other allo‑HCT patient populations. Further investigation into vocational rehabilitation is warranted due to the significant financial and occupational pressures reported by survivors of allo‑HC

Sunset haematology: improving the end-of-life journey for patients and caregivers, in patients with haematologic malignancies

BACKGROUND AND AIM Haematologic Malignancies (HM) are diverse diseases with differing illness trajectories and therapeutic pathways. Unfortunately HM patients may rapidly and unexpectedly clinically deteriorate, resulting in suboptimal engagement of palliative and end-of-life (EOL) care.  Compared to patients with solid tumours, HM patients have many different factors affecting their end-of-life (EOL) journey. Uniquely, a subset of HM patients with bone marrow failure (BMF) can be supported for significant, but highly variable, periods of time with red blood cell transfusions (RBCT), platelet transfusions (PT) and prophylactic antibiotics.  Availability of chronic RBCTs and PTs make HM patients with BMF similar to elderly and poor prognosis patients with end stage kidney disease (ESKD). Multidisciplinary Palliative Supportive Care programs have been shown to be effective for these EKSD patients and may serve as supportive care models for EOL journey in HM patients. This project is  a pilot study aiming to provide a template for management of EOL for patients with HM with BMF, and their care-givers. METHODS Three components are being developed: 1) Survey of patient opinions around treatment decision-making. 2) Analyses of the impact of patient, disease and treatment factors on the probability of survival from start of PT, to inform patients. 3) Collaborative involvement between Haematology and Palliative Care staff involved in the local ESKD program, to develop a template for earlier EOL pathway planning in HM patients. CONCLUSION Progress of work to date will be presented including preliminary findings and next steps