Finding within-organisation spatial information on the web

Information available on company websites can help people navigate to the offices of groups and individuals within the company. Automatically retrieving this within-organisation spatial information is a challenging AI problem This paper introduces a novel unsupervised pattern-based method to extract within-organisation spatial information by taking advantage of HTML structure patterns, together with a novel Conditional Random Fields (CRF) based method to identify different categories of within-organisation spatial information. The results show that the proposed method can achieve a high performance in terms of F-Score, indicating that this purely syntactic method based on web search and an analysis of HTML structure is well-suited for retrieving within-organisation spatial information.

Pathophysiology team teaching: Bioscientist contribution to knowledge integration in a nursing subject

Bioscience content within undergraduate nursing degrees provides foundational knowledge of pathophysiology, anatomy, physiology, microbiology and pharmacology. However, nursing students often find studying the bioscience components of undergraduate nursing program daunting (Friedel & Treagust 2005, Craft et al. 2013). This is related to factors such as the volume of content, degree of difficulty and insufficient linkage between bioscience concepts and nurses' clinical practice. Students who are unable to conceptualise the relevance of bioscience with nursing subjects and subsequent nursing practice may not appreciate the broader importance of bioscience, and hence may adopt a surface approach to learning (Craft et al. 2013). The aim of this study was to develop a model within Nursing Practice in the Context theory subject, to include a bioscientist lecturing to complement the nursing lecturer, in order to explicitly demonstrate links between physiology, pathophysiology and nursing practice.

Serum immunoreactive pancreatic lipase and cationic trypsinogen for the assessment of exocrine pancreatic function in older patients with cystic fibrosis

Indirect and qualitative tests of pancreatic function are commonly used to screen patients with cystic fibrosis for pancreatic insufficiency. In an attempt to develop a more quantitative assessment, we compared the usefulness of measuring serum pancreatic lipase using a newly developed enzyme-linked immunosorbent immunoassay with that of cationic trypsinogen using a radioimmunoassay in the assessment of exocrine pancreatic function in patients with cystic fibrosis. Previously, we have shown neither lipase nor trypsinogen to be of use in assessing pancreatic function prior to 5 years of age because the majority of patients with cystic fibrosis in early infancy have elevated serum levels regardless of pancreatic function. Therefore, we studied 77 patients with cystic fibrosis older than 5 years of age, 41 with steatorrhea and 36 without steatorrhea. In addition, 28 of 77 patients consented to undergo a quantitative pancreatic stimulation test. There was a significant difference between the steatorrheic and nonsteatorrheic patients with the steatorrheic group having lower lipase and trypsinogen values than the nonsteatorrheic group (P < .001). Sensitivities and specificities in detecting steatorrhea were 95% and 86%, respectively, for lipase and 93% and 92%, respectively, for trypsinogen. No correlations were found between the serum levels of lipase and trypsinogen and their respective duodenal concentrations because of abnormally high serum levels of both enzymes found in some nonsteatorrheic patients. We conclude from this study that both serum lipase and trypsinogen levels accurately detect steatorrhea in patients with cystic fibrosis who are older than 5 years but are imprecise indicators of specific pancreatic exocrine function above the level needed for normal fat absorption.

Age-related alterations in immunoreactive pancreatic lipase and cationic trypsinogen in young children with cystic fibrosis

Serum immunoreactive pancreatic lipase and cationic trypsinogen are elevated in young infants with cystic fibrosis (CF) and may be useful neonatal screening tests for CF. We compared lipase measured by a recently developed ELISA immunoassay with trypsinogen measured by radioimmunoassay in 70 children (ages 0.1 to 9.9 years) with CF who had various degrees of pancreatic dysfunction and in 79 similarly aged children without CF (controls). In the control children, lipase activity increased with advancing age, whereas trypsinogen showed no age-related trend. Lipase and trypsinogen were significantly elevated in the infants with CF who were younger than 1 year, irrespective of pancreatic function (trypsinogen, P<0.001; lipase, P<0.05). Sensitivities in detecting CF were 76% and 90% for lipase and trypsinogen, respectively. After the first year of life, lipase and trypsinogen values declined toward normal, the rate of decline of lipase being greater than that of trypsinogen; 67% of lipase values were within or below the normal range by 3 years, whereas 67% of trypsinogen values continued to be elevated. We conclude that trypsinogen is an excellent screening test for CF in young infants regardless of pancreatic function, and that the addition of a serum pancreatic lipase determination does not improve the accuracy of trypsinogen as a screening test for cystic fibrosis.

Repeatable Condition-Invariant Visual Odometry for Sequence-Based Place Recognition

This paper describes a vision-only system for place recognition in environments that are tra- versed at different times of day, when chang- ing conditions drastically affect visual appear- ance, and at different speeds, where places aren’t visited at a consistent linear rate. The ma- jor contribution is the removal of wheel-based odometry from the previously presented algo- rithm (SMART), allowing the technique to op- erate on any camera-based device; in our case a mobile phone. While we show that the di- rect application of visual odometry to our night- time datasets does not achieve a level of perfor- mance typically needed, the VO requirements of SMART are orthogonal to typical usage: firstly only the magnitude of the velocity is required, and secondly the calculated velocity signal only needs to be repeatable in any one part of the environment over day and night cycles, but not necessarily globally consistent. Our results show that the smoothing effect of motion constraints is highly beneficial for achieving a locally consis- tent, lighting-independent velocity estimate. We also show that the advantage of our patch-based technique used previously for frame recogni- tion, surprisingly, does not transfer to VO, where SIFT demonstrates equally good performance. Nevertheless, we present the SMART system us- ing only vision, which performs sequence-base place recognition in extreme low-light condi- tions where standard 6-DOF VO fails and that improves place recognition performance over odometry-less benchmarks, approaching that of wheel odometry.

Laughing with the lecturer: The use of humour in shaping university teaching

This paper addresses the ways in which humour is used by university academics to shape teaching personas. Based upon the work of Mauss and Foucault, and employing semi-structured, in-depth interviews with a range of university teachers, this research suggests that most tertiary teachers deliberately fashion various kinds of teaching persona, which they then perform in lectures and tutorials. The use of humour is widely seen as an important component within this form of self-shaping, as it fits within dominant frameworks of expectation regarding contemporary models of “edutainment”. This research demonstrates that a wide range of practices of the self—including physical, verbal, and relational elements—are employed by academics as part of shaping various humorous teaching personas. Some boundaries exist limiting the use of these pedagogic characters; for example, arguments about natural ability with humour prefigure who is most likely to deploy humour as a practice of professional self-formation. Also, professional concerns regarding seniority and job security are also factored into decision-making regarding those humorous personas likely to be considered appropriate within particular tertiary teaching contexts.

Reasoning about natural language phrases for semantic goal driven exploration

This paper presents a symbolic navigation system that uses spatial language descriptions to inform goal-directed exploration in unfamiliar office environments. An abstract map is created from a collection of natural language phrases describing the spatial layout of the environment. The spatial representation in the abstract map is controlled by a constraint based interpretation of each natural language phrase. In goal-directed exploration of an unseen office environment, the robot links the information in the abstract map to observed symbolic information and its grounded world representation. This paper demonstrates the ability of the system, in both simulated and real-world trials, to efficiently find target rooms in environments that it has never been to previously. In three unexplored environments, it is shown that on average the system travels only 8.42% further than the optimal path when using only natural language phrases to complete navigation tasks.

Making Sense of Mass Education, 2nd Edition

Making Sense of Mass Education provides an engaging and accessible analysis of traditional issues associated with mass education. The book challenges preconceptions about social class, gender and ethnicity discrimination; highlights the interplay between technology, media, popular culture and schooling; and inspects the relevance of ethics and philosophy in the modern classroom. This new edition has been comprehensively updated to provide current information regarding literature, statistics and legal policies, and significantly expands on the previous edition's structure of derailing traditional myths about education as a point of discussion. It also features two new chapters on Big Data and Globalisation and what they mean for the Australian classroom. Written for students, practising teachers and academics alike, Making Sense of Mass Education summarises the current educational landscape in Australia and looks at fundamental issues in society as they relate to education.

Big data

Making Sense of Mass Education provides an engaging and accessible analysis of traditional issues associated with mass education. The book challenges preconceptions about social class, gender and ethnicity discrimination; highlights the interplay between technology, media, popular culture and schooling; and inspects the relevance of ethics and philosophy in the modern classroom. This new edition has been comprehensively updated to provide current information regarding literature, statistics and legal policies, and significantly expands on the previous edition's structure of derailing traditional myths about education as a point of discussion. It also features two new chapters on Big Data and Globalisation and what they mean for the Australian classroom. Written for students, practising teachers and academics alike, Making Sense of Mass Education summarises the current educational landscape in Australia and looks at fundamental issues in society as they relate to education.

Normative values for corneal nerve morphology assessed using corneal confocal microscopy: A multinational normative data set

OBJECTIVE Corneal confocal microscopy is a novel diagnostic technique for the detection of nerve damage and repair in a range of peripheral neuropathies, in particular diabetic neuropathy. Normative reference values are required to enable clinical translation and wider use of this technique. We have therefore undertaken a multicenter collaboration to provide worldwide age-adjusted normative values of corneal nerve fiber parameters. RESEARCH DESIGN AND METHODS A total of 1,965 corneal nerve images from 343 healthy volunteers were pooled from six clinical academic centers. All subjects underwent examination with the Heidelberg Retina Tomograph corneal confocal microscope. Images of the central corneal subbasal nerve plexus were acquired by each center using a standard protocol and analyzed by three trained examiners using manual tracing and semiautomated software (CCMetrics). Age trends were established using simple linear regression, and normative corneal nerve fiber density (CNFD), corneal nerve fiber branch density (CNBD), corneal nerve fiber length (CNFL), and corneal nerve fiber tortuosity (CNFT) reference values were calculated using quantile regression analysis. RESULTS There was a significant linear age-dependent decrease in CNFD (-0.164 no./mm(2) per year for men, P < 0.01, and -0.161 no./mm(2) per year for women, P < 0.01). There was no change with age in CNBD (0.192 no./mm(2) per year for men, P = 0.26, and -0.050 no./mm(2) per year for women, P = 0.78). CNFL decreased in men (-0.045 mm/mm(2) per year, P = 0.07) and women (-0.060 mm/mm(2) per year, P = 0.02). CNFT increased with age in men (0.044 per year, P < 0.01) and women (0.046 per year, P < 0.01). Height, weight, and BMI did not influence the 5th percentile normative values for any corneal nerve parameter. CONCLUSIONS This study provides robust worldwide normative reference values for corneal nerve parameters to be used in research and clinical practice in the study of diabetic and other peripheral neuropathies.

Harnessing information from injury narrative in the 'big data' era: Understanding and applying machine learning for injury surveillance

Objective Vast amounts of injury narratives are collected daily and are available electronically in real time and have great potential for use in injury surveillance and evaluation. Machine learning algorithms have been developed to assist in identifying cases and classifying mechanisms leading to injury in a much timelier manner than is possible when relying on manual coding of narratives. The aim of this paper is to describe the background, growth, value, challenges and future directions of machine learning as applied to injury surveillance. Methods This paper reviews key aspects of machine learning using injury narratives, providing a case study to demonstrate an application to an established human-machine learning approach. Results The range of applications and utility of narrative text has increased greatly with advancements in computing techniques over time. Practical and feasible methods exist for semi-automatic classification of injury narratives which are accurate, efficient and meaningful. The human-machine learning approach described in the case study achieved high sensitivity and positive predictive value and reduced the need for human coding to less than one-third of cases in one large occupational injury database. Conclusion The last 20 years have seen a dramatic change in the potential for technological advancements in injury surveillance. Machine learning of ‘big injury narrative data’ opens up many possibilities for expanded sources of data which can provide more comprehensive, ongoing and timely surveillance to inform future injury prevention policy and practice.

Understanding mental toughness in Australian soccer: Perceptions of players, parents, and coaches

We explored mental toughness in soccer using a triangulation of data capture involving players (n = 6), coaches (n = 4), and parents (n = 5). Semi-structured interviews, based on a personal construct psychology (Kelly, 1955/1991) framework, were conducted to elicit participants' perspectives on the key characteristics and their contrasts, situations demanding mental toughness, and the behaviours displayed and cognitions employed by mentally tough soccer players. The results from the research provided further evidence that mental toughness is conceptually distinct from other psychological constructs such as hardiness. The findings also supported Gucciardi, Gordon, and Dimmock's (2009) process model of mental toughness. A winning mentality and desire was identified as a key attribute of mentally tough soccer players in addition to other previously reported qualities such as self-belief, physical toughness, work ethic/motivation, and resilience. Key cognitions reported by mentally tough soccer players enabled them to remain focused and competitive during training and matches and highlighted the adoption of several forms of self-talk in dealing with challenging situations. Minor revisions to Gucciardi and colleagues' definition of mental toughness are proposed.