A Multifaceted Strategy for Implementation of the Ottawa Ankle Rules in Two Emergency Departments

Problem Despite widespread acceptance of the Ottawa ankle rules for assessment of acute ankle injuries, their application varies considerably. Design Before and after study. Background and setting Emergency departments of a tertiary teaching hospital and a community hospital in Australia. Key measures for improvement Documentation of the Ottawa ankle rules, proportion of patients referred for radiography, proportion of radiographs showing a fracture. Strategies for change Education, a problem specific radiography request form, reminders, audit and feedback, and using radiographers as “gatekeepers.” Effects of change Documentation of the Ottawa ankle rules improved from 57.5% to 94.7% at the tertiary hospital, and 51.6% to 80.8% at the community hospital (P<0.001 for both). The proportion of patients undergoing radiography fell from 95.8% to 87.2% at the tertiary hospital, and from 91.4% to 78.9% at the community hospital (P<0.001 for both). The proportion of radiographs showing a fracture increased from 20.4% to 27.1% at the tertiary hospital (P=0.069), and 15.2% to 27.2% (P=0.002) at the community hospital. The missed fracture rate increased from 0% to 2.9% at the tertiary hospital and from 0% to 1.6% at the community hospital compared with baseline (P=0.783 and P=0.747). Lessons learnt Assessment of case note documentation has limitations. Clinician groups seem to differ in their capacity and willingness to change their practice. A multifaceted change strategy including a problem specific radiography request form can improve the selection of patients for radiography.

FGFR2 mutations are rare across histologic subtypes of ovarian cancer

OBJECTIVE: Ovarian cancer is the leading cause of death from gynecologic malignancies in the Western world. Fibroblast growth factor receptor (FGFR) signaling has been implicated to play a role in ovarian tumorigenesis. Mutational activation of one member of this receptor family, FGFR2, is a frequent event in endometrioid endometrial cancer. Given the similarities in the histologic and molecular genetics of ovarian and endometrial cancers, we hypothesized that activating FGFR2 mutations may occur in a subset of endometrioid ovarian tumors, and possibly other histotypes. METHODS: Six FGFR2 exons were sequenced in 120 primary ovarian tumors representing the major histologic subtypes. RESULTS: FGFR2 mutation was detected at low frequency in endometrioid (1/46, 2.2%) and serous (1/41, 2.4%) ovarian cancer. No mutations were detected in clear cell, mucinous, or mixed histology tumors or in the ovarian cancer cell lines tested. Functional characterization of the FGFR2 mutations confirmed that the mutations detected in ovarian cancer result in receptor activation. CONCLUSIONS: Despite the low incidence of FGFR2 mutations in ovarian cancer, the two FGFR2 mutations identified in ovarian tumors (S252W, Y376C) overlap with the oncogenic mutations previously identified in endometrial tumors, suggesting activated FGFR2 may contribute to ovarian cancer pathogenesis in a small subset of ovarian tumors.

An approach to statistical lip modelling for speaker identification via chromatic feature extraction

This paper presents a novel technique for the tracking of moving lips for the purpose of speaker identification. In our system, a model of the lip contour is formed directly from chromatic information in the lip region. Iterative refinement of contour point estimates is not required. Colour features are extracted from the lips via concatenated profiles taken around the lip contour. Reduction of order in lip features is obtained via principal component analysis (PCA) followed by linear discriminant analysis (LDA). Statistical speaker models are built from the lip features based on the Gaussian mixture model (GMM). Identification experiments performed on the M2VTS¹ database, show encouraging results

David F. Treagust : congenial soul, science educator, and international research leader

For almost a half century David F. Treafust has been an exemplary science educator who has contributed through his dedication and commitments to students, curriculum development and collaboration with teachers, and cutting edge research in science education that has impacted the field globally, nationally and locally. A hallmark of his outstanding career is his collaborative style that inspires others to produce their best work.

Relationship to the bereaved and perceptions of severity of trauma differentiate elements of posttraumatic growth

The field of bereavement and grief has been expanding to recognise the potential for growth following the loss of a loved one. This study sought to examine the effect of the relationship to the deceased and perceptions of the severity of the trauma on dimensions of posttraumatic growth. Participants were 146 people who had lost either: a) a first degree relative, b) a second degree relative, or c) a non-related friend. Results demonstrated that both severity and the relationship to the bereaved differentiate posttraumatic growth outcomes. For example, participants who had lost a first degree relative reported higher levels of growth than those who had lost a second degree relative. Consistent with previous research in general trauma populations, the more severe the loss was rated, the higher the levels of growth. Implications for practice are discussed.

Tool-supported dataflow analysis of a security-critical embedded device

Defence organisations perform information security evaluations to confirm that electronic communications devices are safe to use in security-critical situations. Such evaluations include tracing all possible dataflow paths through the device, but this process is tedious and error-prone, so automated reachability analysis tools are needed to make security evaluations faster and more accurate. Previous research has produced a tool, SIFA, for dataflow analysis of basic digital circuitry, but it cannot analyse dataflow through microprocessors embedded within the circuit since this depends on the software they run. We have developed a static analysis tool that produces SIFA compatible dataflow graphs from embedded microcontroller programs written in C. In this paper we present a case study which shows how this new capability supports combined hardware and software dataflow analyses of a security critical communications device.

Data flow analysis of embedded program expressions

Data flow analysis techniques can be used to help assess threats to data confidentiality and integrity in security critical program code. However, a fundamental weakness of static analysis techniques is that they overestimate the ways in which data may propagate at run time. Discounting large numbers of these false-positive data flow paths wastes an information security evaluator's time and effort. Here we show how to automatically eliminate some false-positive data flow paths by precisely modelling how classified data is blocked by certain expressions in embedded C code. We present a library of detailed data flow models of individual expression elements and an algorithm for introducing these components into conventional data flow graphs. The resulting models can be used to accurately trace byte-level or even bit-level data flow through expressions that are normally treated as atomic. This allows us to identify expressions that safely downgrade their classified inputs and thereby eliminate false-positive data flow paths from the security evaluation process. To validate the approach we have implemented and tested it in an existing data flow analysis toolkit.

A taint marking approach to confidentiality violation detection

This article presents a novel approach to confidentiality violation detection based on taint marking. Information flows are dynamically tracked between applications and objects of the operating system such as files, processes and sockets. A confidentiality policy is defined by labelling sensitive information and defining which information may leave the local system through network exchanges. Furthermore, per application profiles can be defined to restrict the sets of information each application may access and/or send through the network. In previous works, we focused on the use of mandatory access control mechanisms for information flow tracking. In this current work, we have extended the previous information flow model to track network exchanges, and we are able to define a policy attached to network sockets. We show an example application of this extension in the context of a compromised web browser: our implementation detects a confidentiality violation when the browser attempts to leak private information to a remote host over the network.

Automata modeling for cognitive interference in users' relevance judgement

Quantum theory has recently been employed to further advance the theory of information retrieval (IR). A challenging research topic is to investigate the so called quantum-like interference in users’ relevance judgement process, where users are involved to judge the relevance degree of each document with respect to a given query. In this process, users’ relevance judgement for the current document is often interfered by the judgement for previous documents, due to the interference on users’ cognitive status. Research from cognitive science has demonstrated some initial evidence of quantum-like cognitive interference in human decision making, which underpins the user’s relevance judgement process. This motivates us to model such cognitive interference in the relevance judgement process, which in our belief will lead to a better modeling and explanation of user behaviors in relevance judgement process for IR and eventually lead to more user-centric IR models. In this paper, we propose to use probabilistic automaton(PA) and quantum finite automaton (QFA), which are suitable to represent the transition of user judgement states, to dynamically model the cognitive interference when the user is judging a list of documents.