Safety and efficacy of routine postoperative ibuprofen for pain and disability related to ectopic bone formation after hip replacement surgery (HIPAID): a randomised control trial

Objectives To determine the benefits and risks of a non-steroidal anti-inflammatory drug (NSAID) as prophylaxis for ectopic bone formation in patients undergoing total hip replacement (or revision) surgery.
Design Double blind randomised placebo controlled clinical trial, stratified by treatment site and surgery (primary or revision).
Setting 20 orthopaedic surgery centres in Australia and New Zealand.
Participants 902 patients undergoing elective primary or revision total hip replacement surgery.
Intervention 14 days' treatment with ibuprofen (1200 mg daily) or matching placebo started within 24 hours of surgery.
Main outcome measures Changes in self reported hip pain and physical function 6 to 12 months after surgery (Western Ontario and McMaster University Arthritis index).
Results There were no significant differences between the groups for improvements in hip pain (mean difference -0.1, 95% confidence interval -0.4 to 0.2, P = 0.6) or physical function (-0.1, -0.4 to 0.2, P = 0.5), despite a decreased risk of ectopic bone formation (relative risk 0.69, 0.56 to 0.83) associated with ibuprofen. There was a significantly increased risk of major bleeding complications in the ibuprofen group during the admission period (2.09, 1.00 to 4.39).
Conclusions These data do not support the use of routine prophylaxis with NSAIDs in patients undergoing total hip replacement surgery.
Trial registration NCT00145730.

Graph matching with subdivision surfaces for texture synthesis on surfaces

Existing texture synthesis-from-example strategies for polygon meshes typically make use of three components: a multi-resolution mesh hierarchy that allows the overall nature of the pattern to be reproduced before filling in detail; a matching strategy that extends the synthesized texture using the best fit from a texture sample; and a transfer mechanism that copies the selected portion of the texture sample to the target surface. We introduce novel alternatives for each of these components. Use of p2-subdivision surfaces provides the mesh hierarchy and allows fine control over the surface complexity. Adaptive subdivision is used to create an even vertex distribution over the surface. Use of the graph defined by a surface region for matching, rather than a regular texture neighbourhood, provides for flexible control over the scale of the texture and allows simultaneous matching against multiple levels of an image pyramid created from the texture sample. We use graph cuts for texture transfer, adapting this scheme to the context of surface synthesis. The resulting surface textures are realistic, tolerant of local mesh detail and are comparable to results produced by texture neighbourhood sampling approaches.

Malware variant detection using similarity search over sets of control flow graphs

Static detection of polymorphic malware variants plays an important role to improve system security. Control flow has shown to be an effective characteristic that represents polymorphic malware instances. In our research, we propose a similarity search of malware using novel distance metrics of malware signatures. We describe a malware signature by the set of control flow graphs the malware contains. We propose two approaches and use the first to perform pre-filtering. Firstly, we use a distance metric based on the distance between feature vectors. The feature vector is a decomposition of the set of graphs into either fixed size k-sub graphs, or q-gram strings of the high-level source after decompilation. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flow graphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms.

Malwise-an effective and efficient classification system for packed and polymorphic malware

Signature-based malware detection systems have been a much used response to the pervasive problem of malware. Identification of malware variants is essential to a detection system and is made possible by identifying invariant characteristics in related samples. To classify the packed and polymorphic malware, this paper proposes a novel system, named Malwise, for malware classification using a fast application-level emulator to reverse the code packing transformation, and two flowgraph matching algorithms to perform classification. An exact flowgraph matching algorithm is employed that uses string-based signatures, and is able to detect malware with near real-time performance. Additionally, a more effective approximate flowgraph matching algorithm is proposed that uses the decompilation technique of structuring to generate string-based signatures amenable to the string edit distance. We use real and synthetic malware to demonstrate the effectiveness and efficiency of Malwise. Using more than 15,000 real malware, collected from honeypots, the effectiveness is validated by showing that there is an 88 percent probability that new malware is detected as a variant of existing malware. The efficiency is demonstrated from a smaller sample set of malware where 86 percent of the samples can be classified in under 1.3 seconds.

Control of excitation and quenching in multi-colour electrogenerated chemiluminescence systems through choice of co-reactant

We demonstrate a new approach to manipulate the selective emission in mixed electrogenerated chemiluminescence (ECL) systems, where subtle changes in co-reactant properties are exploited to control the relative electron-transfer processes of excitation and quenching. Two closely related tertiary-amine co-reactants, tri-n-propylamine and N,N-diisopropylethylamine, generate remarkably different emission profiles: one provides distinct green and red ECL from [Ir(ppy)3] (ppy=2-phenylpyridinato-C2,N) and a [Ru(bpy)3](2+) (bpy=2,2'-bipyridine) derivative at different applied potentials, whereas the other generates both emissions simultaneously across a wide potential range. These phenomena can be rationalized through the relative exergonicities of electron-transfer quenching of the excited states, in conjunction with the change in concentration of the quenchers over the applied potential range.

Control flow-based malware variant detection

Static detection of malware variants plays an important role in system security and control flow has been shown as an effective characteristic that represents polymorphic malware. In our research, we propose a similarity search of malware to detect these variants using novel distance metrics. We describe a malware signature by the set of control flowgraphs the malware contains. We use a distance metric based on the distance between feature vectors of string-based signatures. The feature vector is a decomposition of the set of graphs into either fixed size k-subgraphs, or q-gram strings of the high-level source after decompilation. We use this distance metric to perform pre-filtering. We also propose a more effective but less computationally efficient distance metric based on the minimum matching distance. The minimum matching distance uses the string edit distances between programs' decompiled flowgraphs, and the linear sum assignment problem to construct a minimum sum weight matching between two sets of graphs. We implement the distance metrics in a complete malware variant detection system. The evaluation shows that our approach is highly effective in terms of a limited false positive rate and our system detects more malware variants when compared to the detection rates of other algorithms. © 2013 IEEE.

Clinical trial adaptation by matching evidence in complementary patient sub-groups of auxiliary blinding questionnaire responses

Clinical trial adaptation refers to any adjustment of the trial protocol after the onset of the trial. Such adjustment may take on various forms, including the change in the dose of administered medicines, the frequency of administering an intervention, the number of trial participants, or the duration of the trial, to name just some possibilities. The main goal is to make the process of introducing new medical interventions to patients more efficient, either by reducing the cost or the time associated with evaluating their safety and efficacy. The principal challenge, which is an outstanding research problem, is to be found in the question of how adaptation should be performed so as to minimize the chance of distorting the outcome of the trial. In this paper we propose a novel method for achieving this. Unlike most of the previously published work, our approach focuses on trial adaptation by sample size adjustment i.e. by reducing the number of trial participants in a statistically informed manner. We adopt a stratification framework recently proposed for the analysis of trial outcomes in the presence of imperfect blinding and based on the administration of a generic auxiliary questionnaire that allows the participants to express their belief concerning the assigned intervention (treatment or control). We show that this data, together with the primary measured variables, can be used to make the probabilistically optimal choice of the particular sub-group a participant should be removed from if trial size reduction is desired. Extensive experiments on a series of simulated trials are used to illustrate the effectiveness of our method.

Auditor client specific knowledge and internal control weakness: some evidence on the role of auditor tenure and geographic distance

In this paper we draw on the audit quality and cluster theory literature to examine whether auditor tenure and auditor's geographic proximity to the client (proxies for auditor client specific knowledge) are associated with the incidence of Section 404 internal control weakness (ICW) under the Sarbanes-Oxley Act (2002). Using a large sample of 24,217 firm-year observations for the period 2004-2012, we show that firms with long auditor tenure and in closer geographic proximity to auditors have lower incidence of ICW. Furthermore, we find that the positive association between auditor-client geographic distance and ICW is weaker for firms with longer auditor tenure. Our results suggest that auditor rotation policies could deprive the auditor of client specific knowledge, especially for auditors located further away from their clients. Our results are robust to propensity score matching method and endogenous effects.

Low control and high demands at work as risk factors for suicide: An Australian national population-level case-control study

OBJECTIVES: Previous research suggests that psychosocial job stressors may be plausible risk factors for suicide. This study assessed the relationship between psychosocial job stressors and suicide mortality across the Australian population. METHODS: We developed a job exposure matrix to objectively measure job stressors across the working population. Suicide data came from a nationwide coronial register. Living controls were selected from a nationally representative cohort study. Incidence density sampling was used to ensure that controls were sampled at the time of death of each case. The period of observation for both cases and controls was 2001 to 2012. We used multilevel logistic regression to assess the odds of suicide in relation to 2 psychosocial job stressors (job control and job demands), after matching for age, sex, and year of death/survey and adjusting for socioeconomic status. RESULTS: Across 9,010 cases and 14,007 matched controls, our results suggest that low job control (odds ratio [OR], 1.35; 95% confidence interval [CI], 1.26-1.44; p < .001) and high job demands (OR, 1.36; 95% CI, 1.26-1.46; p < .001) were associated with increased odds of male suicide after adjusting for socioeconomic status. High demands were associated with lower odds of female suicide (OR, 0.81; 95% CI, 0.72-0.92; p = .002). CONCLUSIONS: It seems that adverse experiences at work are a risk factor for male suicide while not being associated with an elevated risk among females. Future studies on job stressors and suicide are needed, both to further understand the biobehavioral mechanisms explaining the link between job stress and suicide, and to inform targeted prevention initiatives.