Endometriosis, an unknown entity: the consumer`s perspective

This paper reports the findings of a consumer-driven investigation conducted by the Centre for Clinical Nursing Research at Epworth Hospital in conjunction with the Endometriosis Association (Victoria, Australia) aimed at identifying the information and support needs of women experiencing endometriosis. Women's experiences of endometriosis and laparoscopy were examined. A questionnaire was designed to explore women's experiences of, and informational need for, the four categories of: diagnosis of endometriosis, endometriosis, laparoscopy and managing at home. A total of 465 women who had a positive diagnosis of endometriosis, including patients at the Epworth Endometriosis Centre and members of the Endometriosis Association, were included. The data were analysed in terms of frequency of responses and themes that arose from the research. Five main themes consistently emerged from the overall analysis of the questionnaire; these included: lack of communication, no-one listens, the emotional turmoil, expressions of gratitude to the Endometriosis Association and being young and helpless. Also identified was a lack of understanding of endometriosis and laparoscopy, on behalf of both the patient and the practitioner, which has led to communication of misinformation, extended physical pain and emotional distress. Based on these findings, recommendations were made for education strategies to be focused towards increasing awareness of endometriosis and for information to be disseminated using the preferred printed format and to be made available from gynaecologists, hospitals and schools. Through consumer participation, the information obtained in this study is of benefit to all women who come in contact with endometriosis by (a) validating women's experiences of endometriosis and (b) identifying women's needs in relation to the disease.

Emergence of the individual as an international juristic entity: enforcement of International Human Rights

In this article it is contended that state practice, as evidenced in the  declarations of the judiciary and the many treaties and conventions  guaranteeing human rights, reveals a consensus of opinion acknowledging the individual to be an international juristic entity. So extensive is this practice that it could be seen as marking the emergence of a new customary international norm; or at least a general principle of international law, yet to crystallise into a custom; acknowledging the individual as the beneficiary of international rights. This is important for individuals and minority groups because if they possess international rights independently of the State, enforcement of their rights will no longer depend on the interests of the State. Where the State is often the offender of human rights, international law will not effectively confer any real rights unless the individual is so recognised as an international juristic entity.

Nocodazole inhibits insulin-stimulated glusocs transport in 3T3-L1 adipocytes via a microtubule independant mechanism

Insulin stimulates glucose transport in adipocytes and muscle cells by triggering redistribution of the GLUT4 glucose transporter from an intracellular perinuclear location to the cell surface. Recent reports have shown that the microtubule-depolymerizing agent nocodazole inhibits insulin-stimulated glucose transport, implicating an important role for microtubules in this process. In the present study we show that 2 µM nocodazole completely depolymerized microtubules in 3T3-L1 adipocytes, as determined morphologically and biochemically, resulting in dispersal of the perinuclear GLUT4 compartment and the Golgi apparatus. However, 2 µM nocodazole did not significantly effect either the kinetics or magnitude of insulin-stimulated glucose transport. Consistent with previous studies, higher concentrations of nocodazole (10-33 µM) significantly inhibited basal and insulin-stimulated glucose uptake in adipocytes. This effect was not likely the result of microtubule depolymerization because in the presence of taxol, which blocked nocodazole-induced depolymerization of microtubules as well as the dispersal of the perinuclear GLUT4 compartment, the inhibitory effect of 10-33 µM nocodazole on insulin-stimulated glucose uptake prevailed. Despite the decrease in insulin-stimulated glucose transport with 33 µM nocodazole we did not observe inhibition of insulin-stimulated GLUT4 translocation to the cell surface under these conditions. Consistent with a direct effect of nocodazole on glucose transporter function we observed a rapid inhibitory effect of nocodazole on glucose transport activity when added to either 3T3-L1 adipocytes or to Chinese hamster ovary cells at 4 °C. These studies reveal a new and unexpected effect of nocodazole in mammalian cells which appears to occur independently of its microtubule-depolymerizing effects.

A generic classifier-ensemble approach for biomedical named entity recognition

In named entity recognition (NER) for biomedical literature, approaches based on combined classifiers have demonstrated great performance improvement compared to a single (best) classifier. This is mainly owed to sufficient level of diversity exhibited among classifiers, which is a selective property of classifier set. Given a large number of classifiers, how to select different classifiers to put into a classifier-ensemble is a crucial issue of multiple classifier-ensemble design. With this observation in mind, we proposed a generic genetic classifier-ensemble method for the classifier selection in biomedical NER. Various diversity measures and majority voting are considered, and disjoint feature subsets are selected to construct individual classifiers. A basic type of individual classifier – Support Vector Machine (SVM) classifier is adopted as SVM-classifier committee. A multi-objective Genetic algorithm (GA) is employed as the classifier selector to facilitate the ensemble classifier to improve the overall sample classification accuracy. The proposed approach is tested on the benchmark dataset – GENIA version 3.02 corpus, and compared with both individual best SVM classifier and SVM-classifier ensemble algorithm as well as other machine learning methods such as CRF, HMM and MEMM. The results show that the proposed approach outperforms other classification algorithms and can be a useful method for the biomedical NER problem.

Application of the reporting entity concept and lodgement of special purpose financial statements

This Research Report analyses the application of the reporting entity concept and the adoption of special purpose financial reporting, particularly by entities lodging financial statements with the Australian Securities and Investments Commission (ASIC) and with state-based regulators in Australia’s three most populous states, namely, Consumer Affairs Victoria, NSW Fair Trading and Queensland Office of Fair Trading. This Report does not cover entities that have their equity interests traded in a public market, such as listed companies, and some other entities with ‘public accountability’.

A hybrid model for named entity recognition using unstructured medical text

Named entity recognition (NER) is an essential step in the process of information extraction within text mining. This paper proposes a technique to extract drug named entities from unstructured and informal medical text using a hybrid model of lexicon-based and rule-based techniques. In the proposed model, a lexicon is first used as the initial step to detect drug named entities. Inference rules are then deployed to further extract undetected drug names. The designed rules employ part of speech tags and morphological features for drug name detection. The proposed hybrid model is evaluated using a benchmark data set from the i2b2 2009 medication challenge, and is able to achieve an f-score of 66.97%.

Enhancing medical named entity recognition with an extended segment representation technique

Objective : The objective of this paper is to formulate an extended segment representation (SR) technique to enhance named entity recognition (NER) in medical applications.

Methods : An extension to the IOBES (Inside/Outside/Begin/End/Single) SR technique is formulated. In the proposed extension, a new class is assigned to words that do not belong to a named entity (NE) in one context but appear as an NE in other contexts. Ambiguity in such cases can negatively affect the results of classification-based NER techniques. Assigning a separate class to words that can potentially cause ambiguity in NER allows a classifier to detect NEs more accurately; therefore increasing classification accuracy.

Results : The proposed SR technique is evaluated using the i2b2 2010 medical challenge data set with eight different classifiers. Each classifier is trained separately to extract three different medical NEs, namely treatment, problem, and test. From the three experimental results, the extended SR technique is able to improve the average F1-measure results pertaining to seven out of eight classifiers. The kNN classifier shows an average reduction of 0.18% across three experiments, while the C4.5 classifier records an average improvement of 9.33%.

Classification ensemble to improve medical named entity recognition

An accurate Named Entity Recognition (NER) is important for knowledge discovery in text mining. This paper proposes an ensemble machine learning approach to recognise Named Entities (NEs) from unstructured and informal medical text. Specifically, Conditional Random Field (CRF) and Maximum Entropy (ME) classifiers are applied individually to the test data set from the i2b2 2010 medication challenge. Each classifier is trained using a different set of features. The first set focuses on the contextual features of the data, while the second concentrates on the linguistic features of each word. The results of the two classifiers are then combined. The proposed approach achieves an f-score of 81.8%, showing a considerable improvement over the results from CRF and ME classifiers individually which achieve f-scores of 76% and 66.3% for the same data set, respectively.

Enhancement of medical named entity recognition using graph-based features

Named Entity Recognition (NER) is a crucial step in text mining. This paper proposes a new graph-based technique for representing unstructured medical text. The new representation is used to extract discriminative features that are able to enhance the NER performance. To evaluate the usefulness of the proposed graph-based technique, the i2b2 medication challenge data set is used. Specifically, the 'treatment' named entities are extracted for evaluation using six different classifiers. The F-measure results of five classifiers are enhanced, with an average improvement of up to 26% in performance.

Named entity recognition in unstructured text.

The thesis introduces a set of machine learning techniques that enhance the extraction of Named Entities from informal and unstructured free text.

C-direct: a family business

A business is a multifaceted organism; made up of mutually dependent employees whose connection to each other is largely dependant on their role within the entity. Being in a family is a very similar experience. So when family and business interact, managing both can be a challenge. This case study focuses on issues that contribute to a successful family business infrastructure, and the issues and trends that they identify as significant - for example, the importance of a succession plan within the family business environment.

Impact of the new business tax system (alienation of personal services income) Act 2000

The implications of categorising income as "personal services income" and the actual meaning of this term have been marked with uncertainty. The Commissioner of Taxation has long asserted that "personal services income" inherently may not be derived by an entity other than the person whose exertions produce the income. In Liedig v FCT (1994) 28 ATR 141, however, Hill J held that in the absence of a specific legislative provision, there was no basis for the Commissioner's doctrine. The specific legislative measures Hill J required were put in place through the New Business Tax System (Alienation of Personal Services Income) Act 2000. In certain circumstances this Act prevents interposed entities from deriving personal services income. Such payments are attributed instead to the individual who performs the services.

It will also be seen, however, that these provisions do not apply to entities that are conducting a "personal services business". It is submitted that the combined effect of, inter alia, the Act's definition of "personal services income" and "personal services business" is to give the Act a narrower scope than the Commissioner's personal services doctrine. Moreover, it will be submitted that the statutory definition of personal services income also suffers from the same flaws that Hill J identified as relevant to the Commissioner's personal services doctrine.