Neoproterozoic glacial deposits of the Kimberly Region and northwestern Northern Territory, Australia

Neoproterozoic glacigenic formations are preserved in the Kimberley region and northwestern Northern Territory of northern Australia. They are distributed in the west Kimberley adjacent to the northern margins of the King Leopold Orogen, the Mt Ramsay area at the junction of the King Leopold and Halls Creek Orogens, and the east Kimberley, adjacent to the eastern margin of the Halls Creek Orogen. Small outlier glacigenic deposits are preserved in the Litchfield Province, Northern Territory (Uniya Formation) and Georgina Basin, western Queensland (Little Burke Formation). Glacigenic strata comprise diamictite, conglomerate, sandstone and pebbly mudstone and characterize the Walsh, Landrigan and Fargoo/Moonlight Valley formations. Thin units of laminated dolomite sit conformably at the top of the Walsh, Landrigan and Moonlight Valley formations. Glacigenic units are also interbedded with the carbonate platform deposits of the Egan Formation and Boonall Dolomite. δ13C data are available for all carbonate units. There is no direct chronological constraint on these successions. Dispute over regional correlation of the Neoproterozoic succession has been largely resolved through biostratigraphic, chemostratigraphic and lithostratigraphic analysis. However, palaeomagnetic results from the Walsh Formation are inconsistent with sedimentologically based correlations. Two stratigraphically defined glaciations are preserved in northwestern Australia: the ‘Landrigan Glaciation’, characterized by southwest-directed continental ice-sheet movement and correlated with late Cryogenian glaciation elsewhere in Australia and the world; and, the ‘Egan Glaciation’, a more localized glaciation of the Ediacaran Period. Future research focus should include chronology, palaeomagnetic constraint and tectonostratigraphic controls on deposition.

Human-centric process-aware information systems (HC-PAIS)

Process-Aware Information Systems (PAIS) support organizations in managing and automating their processes. A full automation of processes is in particular industries, such as service-oriented markets, not practicable. The integration of humans in PAIS is necessary to manage and perform processes that require human capabilities, judg- ments and decisions. A challenge of interdisciplinary PAIS research is to provide concepts and solutions that support human integration in PAIS and human orientation of PAIS in a way that provably increase the PAIS users' satisfaction and motivation with working with the Human-Centric Process Aware Information System (HC-PAIS) and consequently in uence users' performance of tasks. This work is an initial step of research that aims at providing a definition of Human-Centric Process Aware Information Systems (HC-PAIS) and future research challenges of HC-PAIS. Results of focus group research are presented.

Simplifying process model abstraction : techniques for generating model names

The increased adoption of business process management approaches, tools and practices, has led organizations to accumulate large collections of business process models. These collections can easily include hundred to thousand models, especially in the context of multinational corporations or as a result of organizational mergers and acquisitions. A concrete problem is thus how to maintain these large repositories in such a way that their complexity does not hamper their practical usefulness as a means to describe and communicate business operations. This paper proposes a technique to automatically infer suitable names for business process models and fragments thereof. This technique is useful for model abstraction scenarios, as for instance when user-specific views of a repository are required, or as part of a refactoring initiative aimed to simplify the repository’s complexity. The technique is grounded in an adaptation of the theory of meaning to the realm of business process models. We implemented the technique in a prototype tool and conducted an extensive evaluation using three process model collections from practice and a case study involving process modelers with different experience.

Generating natural language texts from business process models

Process Modeling is a widely used concept for understanding, documenting and also redesigning the operations of organizations. The validation and usage of process models is however affected by the fact that only business analysts fully understand them in detail. This is in particular a problem because they are typically not domain experts. In this paper, we investigate in how far the concept of verbalization can be adapted from object-role modeling to process models. To this end, we define an approach which automatically transforms BPMN process models into natural language texts and combines different techniques from linguistics and graph decomposition in a flexible and accurate manner. The evaluation of the technique is based on a prototypical implementation and involves a test set of 53 BPMN process models showing that natural language texts can be generated in a reliable fashion.

Supporting process model validation through natural language generation

The design and development of process-aware information systems is often supported by specifying requirements as business process models. Although this approach is generally accepted as an effective strategy, it remains a fundamental challenge to adequately validate these models given the diverging skill set of domain experts and system analysts. As domain experts often do not feel confident in judging the correctness and completeness of process models that system analysts create, the validation often has to regress to a discourse using natural language. In order to support such a discourse appropriately, so-called verbalization techniques have been defined for different types of conceptual models. However, there is currently no sophisticated technique available that is capable of generating natural-looking text from process models. In this paper, we address this research gap and propose a technique for generating natural language texts from business process models. A comparison with manually created process descriptions demonstrates that the generated texts are superior in terms of completeness, structure, and linguistic complexity. An evaluation with users further demonstrates that the texts are very understandable and effectively allow the reader to infer the process model semantics. Hence, the generated texts represent a useful input for process model validation.

Smell and taste dysfunction following minor stroke: A case report

Smell (olfactory) and taste (gustatory) are key senses in the regulation of nourishment and individual safety. Olfactory and gustatory dysfunctions have been infrequently reported together in patients following stroke (Landis et al., 2006; Leopold et al., 2006). This case report details two patients who experienced smell and taste dysfunction following minor stroke events. Symptoms reported included hyposmia (diminished sense of smell) and anosmia (complete loss of smell), and dysgeusia (distorted taste). Patients' sense of smell and taste were assessed in an ambulatory care stroke prevention clinic eight months following their strokes. Patient A presented with minor stroke due to a lesion in the anterior circulation, patient B with a lesion in the posterior circulation. Both patients reported intense olfactory and gustatory dysfunction immediately following their strokes. Examination revealed a general inability to detect subtle odours and the ability to identify only 'sweet' tastes for both patients. In addition, both patients reported heavily salting or sweetening their food to mask the distorted and unpleasant taste, which also impacted comorbid conditions such as hypertension and diabetes. Patients and their spouses reported a decrease in their appreciation of family-related activities due to the patients' olfactory and gustatory dysfunction. Patients reported weight loss, lack of energy and strength, likely due to poor nutrition. Olfactory and gustatory dysfunctions are potentially deleterious outcomes following minor stroke and should be assessed by health care professionals prior to patient discharge. Assistance may be required to promote the health and well-being of patients and their carers if smell and taste are impacted by the stroke event.