Failed states and the rule of law

The last decade has seen an emerging consensus that the rule of law is critical in both domestic and international affairs. ‘Failed’ states generate important issues for both the rule of law and, importantly, for their intersection or interaction. A ‘failed’ state almost inevitably involves a breakdown of the domestic rule of law. When international intervention occurs, it raises concerns over substantive issues. Among these is the application of international law and international norms, including among other, the conventions and treaties, the responsibility to protect and protection of civilians. Where international missions seek to assist the people of ‘failed’ states in rebuilding their nations, establishing the rule of law is often the primary or initial pursuit. Any such international assistance/intervention is more effective if it is clearly subject to the rule of law and provides an exemplar/demonstration of how power should be exercised

Evidence for u.v. induction of CDKN2 mutations in melanoma cell lines

The CDKN2 gene, encoding the cyclin dependent kinase inhibitor p16, is a tumour suppressor gene involved in melanoma and maps to chromosome band 9p22. Mutations or interstitial deletions of this gene have been found both in the germline of familial melanoma cases and somatically in melanoma cell lines. Previous mutation analyses of melanoma cell lines have indicated a high frequency of C:G to T:A transitions, with all of these mutations occurring at dipyrimidine sites. Including three melanoma cell lines carrying tandem CC to TT mutations, the spectrum of mutations so far reported indicates a possible role for u.v. radiation in the mutagenesis of this gene in some tumours. To further examine this hypothesis we have characterised mutations of the CDKN2 gene in 30 melanoma cell lines. Nineteen lines carried complete or partial homozygous deletions of the gene. Of the remaining cell lines, eight were shown by direct sequencing of PCR products from exon 1 and exon 2 to carry a total of nine different mutations of CDKN2. Two cell lines carried tandem CC to TT mutations and a high rate of C:G to T:A transitions was observed. This study provides further evidence for the role of u.v. light in the genesis of melanoma, with one target being the CDKN2 tumour suppressor gene.

p53-independent NOXA induction overcomes apoptotic resistance of malignant melanomas

Once melanoma metastasizes, no effective treatment modalities prolong survival in most patients. This notorious refractoriness to therapy challenges investigators to identify agents that overcome melanoma resistance to apoptosis. Whereas many survival pathways contribute to the death-defying phenotype in melanoma, a defect in apoptotic machinery previously highlighted inactivation of Apaf-1, an apoptosome component engaged after mitochondrial damage. During studies involving Notch signaling in melanoma, we observed a gamma-secretase tripeptide inhibitor (GSI; z-Leu-Leu-Nle-CHO), selected from a group of compounds originally used in Alzheimer's disease, induced apoptosis in nine of nine melanoma lines. GSI only induced G2-M growth arrest (but not killing) in five of five normal melanocyte cultures tested. Effective killing of melanoma cells by GSI involved new protein synthesis and a mitochondrial-based pathway mediated by up-regulation of BH3-only members (Bim and NOXA). p53 activation was not necessary for up-regulation of NOXA in melanoma cells. Blocking GSI-induced NOXA using an antisense (but not control) oligonucleotide significantly reduced the apoptotic response. GSI also killed melanoma cell lines with low Apaf-1 levels. We conclude that GSI is highly effective in killing melanoma cells while sparing normal melanocytes. Direct enhancement of BH3-only proteins executes an apoptotic program overcoming resistance of this lethal tumor. Identification of a p53-independent apoptotic pathway in melanoma cells, including cells with low Apaf-1, bypasses an impediment to current cytotoxic therapy and provides new targets for future therapeutic trials involving chemoresistant tumors.

Non-redundant sequential association rule mining based on closed sequential patterns

In many applications, e.g., bioinformatics, web access traces, system utilisation logs, etc., the data is naturally in the form of sequences. People have taken great interest in analysing the sequential data and finding the inherent characteristics or relationships within the data. Sequential association rule mining is one of the possible methods used to analyse this data. As conventional sequential association rule mining very often generates a huge number of association rules, of which many are redundant, it is desirable to find a solution to get rid of those unnecessary association rules. Because of the complexity and temporal ordered characteristics of sequential data, current research on sequential association rule mining is limited. Although several sequential association rule prediction models using either sequence constraints or temporal constraints have been proposed, none of them considered the redundancy problem in rule mining. The main contribution of this research is to propose a non-redundant association rule mining method based on closed frequent sequences and minimal sequential generators. We also give a definition for the non-redundant sequential rules, which are sequential rules with minimal antecedents but maximal consequents. A new algorithm called CSGM (closed sequential and generator mining) for generating closed sequences and minimal sequential generators is also introduced. A further experiment has been done to compare the performance of generating non-redundant sequential rules and full sequential rules, meanwhile, performance evaluation of our CSGM and other closed sequential pattern mining or generator mining algorithms has also been conducted. We also use generated non-redundant sequential rules for query expansion in order to improve recommendations for infrequently purchased products.

Psychosocial predictors of rule following in hostels for women experiencing homelessness

This study examined the psychosocial factors impacting upon the rule-following behaviour of residents of a hostel providing crisis accommodation to women who are homeless. After their arrival, residents of a women’s hostel (N = 83) completed questionnaires assessing the Theory of Planned Behaviour constructs of attitude, subjective norm, perceived behavioural control (PBC), and intentions related to rule-following while residing at the hostel. Perceived resident group norms for rule-following were assessed also. Follow-up staff evaluations of the target behaviour were completed after participants ceased their hostel residence. As expected, attitude, subjective norm, PBC, and group norm significantly predicted intention to follow hostel rules, and intention and PBC predicted rule following behaviour. As rule following is a crucial requirement for continuation of their stay, these findings can inform strategies to improve the experiences and outcomes of women’s short-term hostel stays.

Transfer of Title by a Non-Owner : Personal Property Securities Act 2009 (Cth) exceptions to the nemo dat quod non habet rule

The fundamental personal property rule – no one can transfer a better title to property than they had – is subject to exceptions in the Sale of Goods legislation, which aim to protect innocent buyers who are deceived by a seller’s apparent physical possession of property. These exceptions cover a limited range of transactions and are restrictive in their operation. Australia now has national legislation - the Personal Property Securities Act 2009 (Cth) - which will apply to many transactions outside the scope of the Sale of Goods Act and which includes rules for sales by non-owners which will provide exceptions to the nemo dat quod non habet rule for many common commercial transactions. This article explores the effect of the Personal Property Securities Act 2009 (Cth) on the Sale of Goods exceptions, explains that the new provisions are so wide that there is little continuing relevance for the Sale of Goods Act exceptions, and indicates where they may still apply.

Load modelling : induction motors

Modelling the power systems load is a challenge since the load level and composition varies with time. An accurate load model is important because there is a substantial component of load dynamics in the frequency range relevant to system stability. The composition of loads need to be charaterised because the time constants of composite loads affect the damping contributions of the loads to power system oscillations, and their effects vary with the time of the day, depending on the mix of motors loads. This chapter has two main objectives: 1) describe the load modelling in small signal using on-line measurements; and 2) present a new approach to develop models that reflect the load response to large disturbances. Small signal load characterisation based on on-line measurements allows predicting the composition of load with improved accuracy compared with post-mortem or classical load models. Rather than a generic dynamic model for small signal modelling of the load, an explicit induction motor is used so the performance for larger disturbances can be more reliably inferred. The relation between power and frequency/voltage can be explicitly formulated and the contribution of induction motors extracted. One of the main features of this work is the induction motor component can be associated to nominal powers or equivalent motors

Quo Vadis? Reliable and Practical Rule Extraction from Neural Networks

Rule extraction from neural network algorithms have been investigated for two decades and there have been significant applications. Despite this level of success, rule extraction from neural network methods are generally not part of data mining tools, and a significant commercial breakthrough may still be some time away. This paper briefly reviews the state-of-the-art and points to some of the obstacles, namely a lack of evaluation techniques in experiments and larger benchmark data sets. A significant new development is the view that rule extraction from neural networks is an interactive process which actively involves the user. This leads to the application of assessment and evaluation techniques from information retrieval which may lead to a range of new methods.

Topological map induction using neighbourhood information of places

In topological mapping, perceptual aliasing can cause different places to appear indistinguishable to the robot. In case of severely corrupted or non-available odometry information, topological mapping is difficult as the robot is challenged with the loop-closing problem; that is to determine whether it has visited a particular place before. In this article we propose to use neighbourhood information to disambiguate otherwise indistinguishable places. Using neighbourhood information for place disambiguation is an approach that neither depends on a specific choice of sensors nor requires geometric information such as odometry. Local neighbourhood information is extracted from a sequence of observations of visited places. In experiments using either sonar or visual observations from an indoor environment the benefits of using neighbourhood clues for the disambiguation of otherwise identical vertices are demonstrated. Over 90% of the maps we obtain are isomorphic with the ground truth. The choice of the robot’s sensors does not impact the results of the experiments much.

Rule-based approach for identifying assertions in clinical free-text data

A rule-based approach for classifying previously identified medical concepts in the clinical free text into an assertion category is presented. There are six different categories of assertions for the task: Present, Absent, Possible, Conditional, Hypothetical and Not associated with the patient. The assertion classification algorithms were largely based on extending the popular NegEx and Context algorithms. In addition, a health based clinical terminology called SNOMED CT and other publicly available dictionaries were used to classify assertions, which did not fit the NegEx/Context model. The data for this task includes discharge summaries from Partners HealthCare and from Beth Israel Deaconess Medical Centre, as well as discharge summaries and progress notes from University of Pittsburgh Medical Centre. The set consists of 349 discharge reports, each with pairs of ground truth concept and assertion files for system development, and 477 reports for evaluation. The system’s performance on the evaluation data set was 0.83, 0.83 and 0.83 for recall, precision and F1-measure, respectively. Although the rule-based system shows promise, further improvements can be made by incorporating machine learning approaches.

Induction motor load impact on power system eigenvalue sensitivity analysis

Load modelling plays an important role in power system dynamic stability assessment. One of the widely used methods in assessing load model impact on system dynamic response is parametric sensitivity analysis. A composite load model-based load sensitivity analysis framework is proposed. It enables comprehensive investigation into load modelling impacts on system stability considering the dynamic interactions between load and system dynamics. The effect of the location of individual as well as patches of composite loads in the vicinity on the sensitivity of the oscillatory modes is investigated. The impact of load composition on the overall sensitivity of the load is also investigated.