1,406 research outputs found
Myths of a Near Past: Envisioning Finance Capitalism anno 2007
This paper seeks to extend earlier work on particular features and manifestations of capitalism (De Cock et al., 2001). Our 2001 Myths of a Near Future paper offered ephemera readers a large depository of images concerning the New Economy. Eight years later our focus has shifted to Finance Capitalism. Over the course of the year 2007 we cut out and scanned 81 ads placed by financial institutions in the Financial Times. Our analysis of these aims to provide a sense of how the financial world ?showed up? in this pivotal year, whilst illustrating how its representations were interwoven with fantasy throughout. We also hope that the ensemble of images associated with the paper will be creatively reassembled by its readers and possibly provide a useful teaching aid
Organization/Literature: Exploring the Seam
In this paper we develop a particular way of understanding literature and organization with the aim of drawing on and extending the relationship between the two. Hence our subtitle: exploring the seam. Although the use of literary concepts and theories within our discipline is now well established, the way in which such ideas are taken up often neglects debate and contestation by treating ?literature? as a relatively homogeneous field. By following some of the ardent debates relating to issues of representation, the relation between text and extra-textual reality, and literature?s disclosure of its status as fiction, we find a discussion of (social) organization at the heart of contemporary literary theory. It is the oscillation between literature and organization that structures this paper and gives us our argument: that ?organization? and ?literature? are mutually co-articulating and interdependent concepts and fields of enquiry
Weakly supervised deep learning for the detection of domain generation algorithms
Domain generation algorithms (DGAs) have become commonplace in malware that seeks to establish command and control communication between an infected machine and the botmaster. DGAs dynamically and consistently generate large volumes of malicious domain names, only a few of which are registered by the botmaster, within a short time window around their generation time, and subsequently resolved when the malware on the infected machine tries to access them. Deep neural networks that can classify domain names as benign or malicious are of great interest in the real-time defense against DGAs. In contrast with traditional machine learning models, deep networks do not rely on human engineered features. Instead, they can learn features automatically from data, provided that they are supplied with sufficiently large amounts of suitable training data. Obtaining cleanly labeled ground truth data is difficult and time consuming. Heuristically labeled data could potentially provide a source of training data for weakly supervised training of DGA detectors. We propose a set of heuristics for automatically labeling domain names monitored in real traffic, and then train and evaluate classifiers with the proposed heuristically labeled dataset. We show through experiments on a dataset with 50 million domain names that such heuristically labeled data is very useful in practice to improve the predictive accuracy of deep learning-based DGA classifiers, and that these deep neural networks significantly outperform a random forest classifier with human engineered features
PHS83 Potential Time Savings With Rituximab Subcutaneous (SC) Injection Versus Rituximab Intravenous (IV) Infusion: Results from Interviews at 13 European Sites As Part of a Time and Motion Study (T&M)
Dose rationale and pharmacokinetics of dexmedetomidine in mechanically ventilated new-borns : impact of design optimisation
Purpose: There is a need for alternative analgosedatives such as dexmedetomidine in neonates. Given the ethical and practical difficulties, protocol design for clinical trials in neonates should be carefully considered before implementation. Our objective was to identify a protocol design suitable for subsequent evaluation of the dosing requirements for dexmedetomidine in mechanically ventilated neonates.
Methods: A published paediatric pharmacokinetic model was used to derive the dosing regimen for dexmedetomidine in a first-in-neonate study. Optimality criteria were applied to optimise the blood sampling schedule. The impact of sampling schedule optimisation on model parameter estimation was assessed by simulation and re-estimation procedures for different simulation scenarios. The optimised schedule was then implemented in a neonatal pilot study.
Results: Parameter estimates were more precise and similarly accurate in the optimised scenarios, as compared to empirical sampling (normalised root mean square error: 1673.1% vs. 13,229.4% and relative error: 46.4% vs. 9.1%). Most importantly, protocol deviations from the optimal design still allowed reasonable parameter estimation. Data analysis from the pilot group (n = 6) confirmed the adequacy of the optimised trial protocol. Dexmedetomidine pharmacokinetics in term neonates was scaled using allometry and maturation, but results showed a 20% higher clearance in this population compared to initial estimates obtained by extrapolation from a slightly older paediatric population. Clearance for a typical neonate, with a post-menstrual age (PMA) of 40 weeks and weight 3.4 kg, was 2.92 L/h. Extension of the study with 11 additional subjects showed a further increased clearance in pre-term subjects with lower PMA.
Conclusions: The use of optimal design in conjunction with simulation scenarios improved the accuracy and precision of the estimates of the parameters of interest, taking into account protocol deviations, which are often unavoidable in this event-prone population
Financial phantasmagoria: corporate image-work in times of crisis
Our purpose in this article is to relate the real movements in the economy during 2008 to the ?image-work? of financial institutions. Over the period January?December 2008 we collected 241 separate advertisements from 61 financial institutions published in the Financial Times. Reading across the ensemble of advertisements for themes and evocative images provides an impression of the financial imaginaries created by these organizations as the global financial crisis unfolded. In using the term ?phantasmagoria? we move beyond its colloquial sense of a set of strange images designed to dazzle towards the more technical connotation used by Ranci�re (2004) who suggested that words and images can offer a trace of an overall determining set-up if they are torn from their obviousness so they become phantasmagoric figures. The key phantasmagoric figure we identify here is that of the financial institution as timeless, immortal and unchanging; a coherent and autonomous entity amongst other actors. This notion of uniqueness belies the commonality of thinking which precipitated the global financial crisis as well as the limited capacity for control of financial institutions in relation to market events. It also functions as a powerful naturalizing force, making it hard to question certain aspects of the recent period of ?capitalism in crisis?
Mobile apps for health behaviour change in physical activity, diet, drug and alcohol use, and mental health: a systematic review
Background: With a growing focus on patient interaction with health management, mobile apps are increasingly used to deliver behavioural health interventions. The large variation in these mobile health apps - their target patient group, health behaviour, and behavioural change strategies - has resulted in a large but incohesive body of literature. Objective: The purpose of this systematic review was to assess the effectiveness of mobile apps at improving health behaviours and outcomes, and to examine the inclusion and effectiveness of Behaviour Change Techniques in mobile health apps. Methods: Medline, EMBASE, CINAHL, and Web of Science were systematically searched for articles published between 2014 and 2019 that evaluated mobile apps for health behaviour change. Two authors independently screened and selected studies according to the eligibility criteria. Data was extracted and risk of bias assessed by one reviewer and validated by a second reviewer. Results: 52 randomized controlled trials met the inclusion criteria and were included in analysis - 37 studies focused on physical activity, diet, or a combination of both, 11 on drug and alcohol use, and 4 on mental health. Participant perceptions were generally positive - only one app was rated as less helpful and satisfactory than the control - and the studies that measured engagement and usability found relatively high study completion rates (mean = 83.3%, n = 18) and ease of use ratings (3 significantly better than control, 9/15 rated >70%) . However, there was little evidence of changed behaviour or health outcomes. Conclusions: There was not strong evidence found to support the effectiveness of mobile apps at improving health behaviours or outcomes because few studies found significant differences between the app and control groups. Further research is needed to identify the behaviour change techniques that are most effective at promoting behaviour change. Improved reporting is necessary to accurately evaluate the mobile health app effectiveness and risk of bias
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