Predictability of unplanned extubations

Acute life threatening events such as cardiac/respiratory arrests are often predictable in adults and children. However critical events such as unplanned extubations are considered as not predictable. This paper seeks to evaluate the ability of automated prediction systems based on feature space embedding and time series methods to predict unplanned extubations in paediatric intensive care patients. We try to exploit the trends in the physiological signals such as Heart Rate, Respiratory Rate, Systolic Blood Pressure and Oxygen saturation levels in the blood using signal processing aspects of a frame-based approach of expanding signals using a nonorthogonal basis derived from the data. We investigate the significance of the trends in a computerised prediction system. The results are compared with clinical observations of predictability. We will conclude by investigating whether the prediction capability of the system could be exploited to prevent future unplanned extubations. © 2014 IEEE.

Exchange controls and European stock market integration

This paper examines the impact on stock price predictability that the removal of exchange controls had on major European countries during the late 1970s and 1980s. It is found that for Germany, Switzerland and France, the removal of exchange controls led to an increase in the interdependence between these and other markets. In contrast, there is little evidence of an increase in interdependence for the UK and Italy.

Formulation of multiparticulate systems as lyophilised orally disintegrating tablets

The current study aimed to exploit the electrostatic associative interaction between carrageenan and gelatin to optimise a formulation of lyophilised orally disintegrating tablets (ODTs) suitable for multiparticulate delivery. A central composite face centred (CCF) design was applied to study the influence of formulation variables (gelatin, carrageenan and alanine concentrations) on the crucial responses of the formulation (disintegration time, hardness, viscosity and pH). The disintegration time and viscosity were controlled by the associative interaction between gelatin and carrageenan upon hydration which forms a strong complex that increases the viscosity of the stock solution and forms tablet with higher resistant to disintegration in aqueous medium. Therefore, the levels of carrageenan, gelatin and their interaction in the formulation were the significant factors. In terms of hardness, increasing gelatin and alanine concentration was the most effective way to improve tablet hardness. Accordingly, optimum concentrations of these excipients were needed to find the best balance that fulfilled all formulation requirements. The revised model showed high degree of predictability and optimisation reliability and therefore was successful in developing an ODT formulation with optimised properties that were able deliver enteric coated multiparticulates of omeprazole without compromising their functionality.

A method for systematic artifact selection decision making

Artifact selection decisions typically involve the selection of one from a number of possible/candidate options (decision alternatives). In order to support such decisions, it is important to identify and recognize relevant key issues of problem solving and decision making (Albers, 1996; Harris, 1998a, 1998b; Jacobs & Holten, 1995; Loch & Conger, 1996; Rumble, 1991; Sauter, 1999; Simon, 1986). Sauter classifies four problem solving/decision making styles: (1) left-brain style, (2) right-brain style, (3) accommodating, and (4) integrated (Sauter, 1999). The left-brain style employs analytical and quantitative techniques and relies on rational and logical reasoning. In an effort to achieve predictability and minimize uncertainty, problems are explicitly defined, solution methods are determined, orderly information searches are conducted, and analysis is increasingly refined. Left-brain style decision making works best when it is possible to predict/control, measure, and quantify all relevant variables, and when information is complete. In direct contrast, right-brain style decision making is based on intuitive techniques—it places more emphasis on feelings than facts. Accommodating decision makers use their non-dominant style when they realize that it will work best in a given situation. Lastly, integrated style decision makers are able to combine the left- and right-brain styles—they use analytical processes to filter information and intuition to contend with uncertainty and complexity.

Automatic identification of best answers in online enquiry communities

Online communities are prime sources of information. The Web is rich with forums and Question Answering (Q&A) communities where people go to seek answers to all kinds of questions. Most systems employ manual answer-rating procedures to encourage people to provide quality answers and to help users locate the best answers in a given thread. However, in the datasets we collected from three online communities, we found that half their threads lacked best answer markings. This stresses the need for methods to assess the quality of available answers to: 1) provide automated ratings to fill in for, or support, manually assigned ones, and; 2) to assist users when browsing such answers by filtering in potential best answers. In this paper, we collected data from three online communities and converted it to RDF based on the SIOC ontology. We then explored an approach for predicting best answers using a combination of content, user, and thread features. We show how the influence of such features on predicting best answers differs across communities. Further we demonstrate how certain features unique to some of our community systems can boost predictability of best answers.

Interpreting adverse signals in diabetes drug development programs

Detection and interpretation of adverse signals during preclinical and clinical stages of drug development inform the benefit-risk assessment that determines suitability for use in real-world situations. This review considers some recent signals associated with diabetes therapies, illustrating the difficulties in ascribing causality and evaluating absolute risk, predictability, prevention, and containment. Individual clinical trials are necessarily restricted for patient selection, number, and duration; they can introduce allocation and ascertainment bias and they often rely on biomarkers to estimate long-term clinical outcomes. In diabetes, the risk perspective is inevitably confounded by emergent comorbid conditions and potential interactions that limit therapeutic choice, hence the need for new therapies and better use of existing therapies to address the consequences of protracted glucotoxicity. However, for some therapies, the adverse effects may take several years to emerge, and it is evident that faint initial signals under trial conditions cannot be expected to foretell all eventualities. Thus, as information and experience accumulate with time, it should be accepted that benefit-risk deliberations will be refined, and adjustments to prescribing indications may become appropriate. © 2013 by the American Diabetes Association.

A method for systematic artifact selection decision making

Artifact selection decisions typically involve the selection of one from a number of possible/candidate options (decision alternatives). In order to support such decisions, it is important to identify and recognize relevant key issues of problem solving and decision making (Albers, 1996; Harris, 1998a, 1998b; Jacobs & Holten, 1995; Loch & Conger, 1996; Rumble, 1991; Sauter, 1999; Simon, 1986). Sauter classifies four problem solving/decision making styles: (1) left-brain style, (2) right-brain style, (3) accommodating, and (4) integrated (Sauter, 1999). The left-brain style employs analytical and quantitative techniques and relies on rational and logical reasoning. In an effort to achieve predictability and minimize uncertainty, problems are explicitly defined, solution methods are determined, orderly information searches are conducted, and analysis is increasingly refined. Left-brain style decision making works best when it is possible to predict/control, measure, and quantify all relevant variables, and when information is complete. In direct contrast, right-brain style decision making is based on intuitive techniques—it places more emphasis on feelings than facts. Accommodating decision makers use their non-dominant style when they realize that it will work best in a given situation. Lastly, integrated style decision makers are able to combine the left- and right-brain styles—they use analytical processes to filter information and intuition to contend with uncertainty and complexity.

Anticipatory control of long-range phase synchronization

Everyday human behaviour relies on our ability to predict outcomes on the basis of moment by moment information. Long-range neural phase synchronization has been hypothesized as a mechanism by which ‘predictions’ can exert an effect on the processing of incoming sensory events. Using magnetoencephalography (MEG) we have studied the relationship between the modulation of phase synchronization in a cerebral network of areas involved in visual target processing and the predictability of target occurrence. Our results reveal a striking increase in the modulation of phase synchronization associated with an increased probability of target occurrence. These observations are consistent with the hypothesis that long-range phase synchronization plays a critical functional role in humans' ability to effectively employ predictive heuristics.

Towards the in silico identification of class II restricted T-cell epitopes:a partial least squares iterative self-consistent algorithm for affinity prediction

Motivation: The immunogenicity of peptides depends on their ability to bind to MHC molecules. MHC binding affinity prediction methods can save significant amounts of experimental work. The class II MHC binding site is open at both ends, making epitope prediction difficult because of the multiple binding ability of long peptides. Results: An iterative self-consistent partial least squares (PLS)-based additive method was applied to a set of 66 pep- tides no longer than 16 amino acids, binding to DRB1*0401. A regression equation containing the quantitative contributions of the amino acids at each of the nine positions was generated. Its predictability was tested using two external test sets which gave r pred =0.593 and r pred=0.655, respectively. Furthermore, it was benchmarked using 25 known T-cell epitopes restricted by DRB1*0401 and we compared our results with four other online predictive methods. The additive method showed the best result finding 24 of the 25 T-cell epitopes. Availability: Peptides used in the study are available from http://www.jenner.ac.uk/JenPep. The PLS method is available commercially in the SYBYL molecular modelling software package. The final model for affinity prediction of peptides binding to DRB1*0401 molecule is available at http://www.jenner.ac.uk/MHCPred. Models developed for DRB1*0101 and DRB1*0701 also are available in MHC- Pred

Whether social schema violations help or hurt creativity depends on need for structure

Although people and events that disconfirm observers' expectancies can increase their creativity, sometimes such social schema violations increase observers' rigidity of thought and undermine creative cognition. Here we examined whether individual differences in the extent to which people prefer structure and predictability determine whether social schema violations facilitate or hamper creativity. Participants in Study 1 formed impressions of a schema-inconsistent female mechanic (vs. a schema-consistent male mechanic). Following schema-inconsistent rather than -consistent information, participants low (high) in need for structure showed better (impeded) creative performance. Participants in Study 2 memorized a series of images in which individuals were placed on a schema-inconsistent (vs. consistent) background (e.g., an Eskimo on the desert vs. on a snowy landscape). Following schema-inconsistent imagery, participants low (high) in need for structure increased (decreased) divergent thinking. © 2014 by the Society for Personality and Social Psychology, Inc.

Formal methods for the development and verification of autonomic IT systems

This chapter explores ways in which rigorous mathematical techniques, termed formal methods, can be employed to improve the predictability and dependability of autonomic computing. Model checking, formal specification, and quantitative verification are presented in the contexts of conflict detection in autonomic computing policies, and of implementation of goal and utility-function policies in autonomic IT systems, respectively. Each of these techniques is illustrated using a detailed case study, and analysed to establish its merits and limitations. The analysis is then used as a basis for discussing the challenges and opportunities of this endeavour to transition the development of autonomic IT systems from the current practice of using ad-hoc methods and heuristic towards a more principled approach. © 2012, IGI Global.

Can we predict dividend cuts?

I examine the predictability of dividend cuts based on the time interval between dividend announcement dates using a large dataset of US firms from 1971 to 2014. The longer the time interval between dividend announcements, the larger the probability of a cut in the dividend per share, consistent with the view that firms delay the release of bad news.

Design of experiments to study the impact of process parameters on droplet size and development of non-invasive imaging techniques in tablet coating

Atomisation of an aqueous solution for tablet film coating is a complex process with multiple factors determining droplet formation and properties. The importance of droplet size for an efficient process and a high quality final product has been noted in the literature, with smaller droplets reported to produce smoother, more homogenous coatings whilst simultaneously avoiding the risk of damage through over-wetting of the tablet core. In this work the effect of droplet size on tablet film coat characteristics was investigated using X-ray microcomputed tomography (XμCT) and confocal laser scanning microscopy (CLSM). A quality by design approach utilising design of experiments (DOE) was used to optimise the conditions necessary for production of droplets at a small (20 μm) and large (70 μm) droplet size. Droplet size distribution was measured using real-time laser diffraction and the volume median diameter taken as a response. DOE yielded information on the relationship three critical process parameters: pump rate, atomisation pressure and coating-polymer concentration, had upon droplet size. The model generated was robust, scoring highly for model fit (R2 = 0.977), predictability (Q2 = 0.837), validity and reproducibility. Modelling confirmed that all parameters had either a linear or quadratic effect on droplet size and revealed an interaction between pump rate and atomisation pressure. Fluidised bed coating of tablet cores was performed with either small or large droplets followed by CLSM and XμCT imaging. Addition of commonly used contrast materials to the coating solution improved visualisation of the coating by XμCT, showing the coat as a discrete section of the overall tablet. Imaging provided qualitative and quantitative evidence revealing that smaller droplets formed thinner, more uniform and less porous film coats.