The rights and responsibilites of Australian citizenship: a legislative analysis

This article tests claims about the legal significance of possessing Australian citizenship against the legal reality. Abstract The Preamble to the Australian Citizenship Act 2007 (Cth) makes three broad claims about Australian statutory citizenship: that it signifies ‘full and formal membership of the Australian community’; that it is characterised by the possession of ‘reciprocal rights and obligations’; and that it is a ‘bond’ that ‘unites all Australians’. This article examines the extent to which these claims accurately describe the legal implications of citizenship in Australia. In doing so, it looks in detail at the degree to which holding Australian statutory citizenship impacts upon the rights a person possesses in four broad categories that are intrinsically connected with citizenship: status protection rights, rights to entry and abode, rights to protection, and political rights

The legal parameters of Australian citizenship

Rhetoric on the topic of Australian citizenship has widely emphasised its significance, particularly as a source of important rights and corresponding obligations. Despite this, as many commentators have noted, the constitutional limits of Parliament’s power over citizenship remain unsettled, and the rights and obligations that legally distinguish citizens from non-citizens are not easy to identify. This thesis is motivated by a desire to determine the extent to which claims about the significance of Australian citizenship are reflected in its reality, as a legal concept. There are three dimensions in which the legal concept of Australian citizenship is shaped: constitutional law, statute law and the common law. The thesis conducts a doctrinal study driven by two questions: First, what are the parameters of citizenship, and what rights and obligations are generated for citizens, within each of the three dimensions identified? Secondly, to what extent do the three dimensions intersect in a manner that helps to inform the legal meaning of Australian citizenship? The study finds that, within each individual dimension, silences and ambiguities limit the potential for a cohesive notion of citizenship that gives rise to clear rights and obligations to emerge. However, it demonstrates that, by paying close attention to the intersections between the three dimensions, it is possible to arrive at a conceptualisation of Australian legal citizenship that is more cohesive than the law within any individual domain would suggest. The thesis illustrates one way in which the intersections between the different citizenship dimensions might be coherently resolved. This is by no means the only interpretation available, nor does it provide an answer to every question that has plagued citizenship law in Australia. However, it serves as an indication of the potential for a clearer notion of Australian legal citizenship than that which exists at present to be developed through focus on the connections between existing conceptualisations of citizenship. Note: There have been a number of very recent changes and proposals for change in the area of citizenship law, both in Australia and in foreign countries. I have endeavoured to incorporate these developments into this thesis, as far as possible. The state of the law reflected in the thesis is, to the best of my knowledge, correct as at March 10 2015

The disqualification of dual citizens from Parliament: Three problems and a solution

Since August 2017, the rule in s 44(i) of the Australian Constitution that dual citizens are incapable of being chosen for or sitting in federal Parliament has led to the disqualification or resignation of 15 parliamentarians. This disruption may yet continue, with outstanding questions remaining about several sitting members. In this article, we outline three key problems with s 44(i), as well as a durable solution

The histological differentiation of Tuberculosis from Crohn’s Disease in Mucosal Biopsies with Granulomatous Inflammation from the Upper Gastrointestinal Tract.

BACKGROUND : Tuberculosis and Crohn’s disease are both granulomatous diseases of the gastrointestinal tract with numerous overlapping features. Several studies have documented the differentiating clinical and histological features in the lower gastrointestinal tract. However, no studies have attempted to distinguish upper gastrointestinal Tuberculosis from Crohn’s disease. AIM : To identify the histopathological features useful in distinguishing Tuberculosis from Crohn’s disease in mucosal biopsies with granulomatous inflammation from the upper gastrointestinal tract. METHODS : A total of 40 cases (20 cases each of Tuberculosis and Crohn’s disease) with a minimum of one year clinical follow up was selected from a total of 98 cases, over a ten year period (January 2005-December 2014). The clinical, endoscopic and histopathological features were examined and entered into a database created in the Epidata software. The statistical methods used included frequency table, Chi square test, Mann-Whitney U test and a p value of <0.05 was considered significant. RESULTS AND CONCLUSIONS : Granulomatous inflammation of the upper gastrointestinal tract is more likely to be Crohn’s disease if the duration of the illness is longer, endoscopy is normal and intensity of granulomatous inflammation and other inflammatory changes is mild. Tuberculosis is more likely to be associated with shorter duration of symptoms, dyspepsia, endoscopic changes, significant lymph node involvement on CT, more severe granulomatous inflammation and other inflammatory changes. Involvement of the esophagus and duodenum by granulomatous inflammation is also more common in Tuberculosis

A hybrid extreme learning machine and sine cosine algorithm model for accurate electricity price forecasting

Electricity demand is continually rising due to the advancement of new technology, the switch to greener energy, and the popularity of electric vehicles over conventional ones. The proliferation of businesses in the generation and distribution sectors has increased competition in the electricity market. Forecasting electricity prices enables consumers to control their monthly electricity bills and consumer-owned distributed generation by knowing the forecasted hourly price. For demand management, generation scheduling, and bidding price quotations, electricity price forecasting is crucial for buyers, generation businesses, and bidders alike. Electricity price data is highly nonlinear and affected by numerous factors because of which EPF models are more complex, highly volatile and slow in convergence. A range of neural network models, training algorithms, and hybrid systems comprising two or more models have been suggested for precise and efficient electricity price forecasting by researchers over the decade. This study involves the development of a hybrid neural network model with two intelligent algorithms sine cosine algorithm (SCA) and extreme learning machine (ELM) to predict electricity price for a particular duration. The newly developed network model is trained and tested with real-time Indian electricity price data from the year 2022. The selected annual price data set is divided into three different sets to explore seasonal variations and all the sets are given as the input to the model for training and testing to obtain the effective price forecasting

ANTIDIABETIC AND ANTIDYSLIPIDEMIC PROPERTIES OF GOA-111, A MIXTURE OF GYMNEMA SYLVESTRAE, OCIMUM SANCTUM AND AZADIRACHTA INDICA EXTRACT IN THE RATIO OF 1:1:1 STUDIED IN HIGH FAT DIET FED- LOW DOSE STREPTOZOTOCIN INDUCED EXPERIMENTAL TYPE 2 DIABETES IN RAT

Diabetes mellitus emerges from multiple biochemical and cellular impairments, including decreased insulin secretion from the pancreatic β-cells and impaired insulin action in peripheral tissues. The present study was systematically carried out to evaluate antidiabetic and &nbsp;antidyslipidemic properties of GOA-111,a herbal extract containing a mixture of Gymnema sylvestrae, Ocimum sanctum leaves and seed kernel of Azadirachta indica &nbsp;in the ratio of 1:1:1 in ameliorating both the primary and secondary complications of type 2 diabetes mellitus in high fat diet fed low dose streptozotocin induced diabetic rats Experimental type 2 diabetes was induced with a low dose streptozotocin in rats &nbsp;fed on a high fat diet. Diabetic rats were treated with three different doses GOA 111&nbsp; (150,300 and 450 mg/Kg b.wt/rat/day) &nbsp;&nbsp;for 30 days. The toxicological parameters such as AST, ALT and ALP were assayed. Biochemical parameters such as fasting blood glucose, glycosylated hemoglobin, insulin, insulin resistance and lipid profile were measured. Oral treatment with GOA 111 significantly decreased the elevated levels of fasting glucose, glycosylated hemoglobin, AST, ALT and ALP. The insulin level was improved in insulin resistant diabetic rats.&nbsp; GOA 111 also normalized the lipid profile. Though the&nbsp; results showed a dose dependent impact on the parameters, a dose of &nbsp;300mg/Kg B/W/rat/day GOA 111 exerts maximum potential anti-hyperglycemic and antidyslipidemic effects in HFD/STZ-induced type 2 diabetic rats. Key words: GOA 111; High fat diet; Streptozotocin; antidiabetic; antidyslipidemi

Consistency, local stability, and approximation of Shapash explanation

Consistency, scalability, and local stability properties ensure that a model or method produces reliable and predictable outcomes. The Shapash helps users understand how the model makes its decisions. With machine learning (ML) system, healthcare experts can identify individuals at higher risk and implement interventions to reduce the occurrence and severity of disease. ML had achieved higher prediction accuracy even though the accuracy of their prediction depends on the quality and quantity of the data used for training. Despite the wider application and higher accuracy of different ML for disease prediction, the explanation of their predictive outcome is much more important to the healthcare professional, the patient, and even their developers. However, most of the ML systems do not explain their outcomes. To address the explainability issue various techniques such as local model agnostic explanation (LIME), and shapley additive explanation (SHAP) have been proposed over the recent years. Furthermore, the consistency, local stability, and approximation of the explanation remained one of the research topics in ML. This study investigated the consistency, stability, and approximation of LIME and SHAP in predicting heart disease (HD). The result suggested that LIME and SHAP generated a similar explanation (distance=0.35), compared to the active coalition of variable (ACV) explanation (distance=0.43)