Recent applications of Chemical Imaging to pharmaceutical process monitoring and quality control

Chemical Imaging (CI) is an emerging platform technology that integrates conventional imaging and spectroscopy to attain both spatial and spectral information from an object. Vibrational spectroscopic methods, such as Near Infrared (NIR) and Raman spectroscopy, combined with imaging are particularly useful for analysis of biological/pharmaceutical forms. The rapid, non-destructive and non-invasive features of CI mark its potential suitability as a process analytical tool for the pharmaceutical industry, for both process monitoring and quality control in the many stages of drug production. This paper provides an overview of CI principles, instrumentation and analysis. Recent applications of Raman and NIR-CI to pharmaceutical quality and process control are presented; challenges facing Cl implementation and likely future developments in the technology are also discussed. (C) 2007 Elsevier B.V. All rights reserved.

Introduction to Domain-Driven Data Mining Special Section

In the last decade, data mining has emerged as one of the most dynamic and lively areas in information technology. Although many algorithms and techniques for data mining have been proposed, they either focus on domain independent techniques or on very specific domain problems. A general requirement in bridging the gap between academia and business is to cater to general domain-related issues surrounding real-life applications, such as constraints, organizational factors, domain expert knowledge, domain adaption, and operational knowledge. Unfortunately, these either have not been addressed, or have not been sufficiently addressed, in current data mining research and development.Domain-Driven Data Mining (D3M) aims to develop general principles, methodologies, and techniques for modeling and merging comprehensive domain-related factors and synthesized ubiquitous intelligence surrounding problem domains with the data mining process, and discovering knowledge to support business decision-making. This paper aims to report original, cutting-edge, and state-of-the-art progress in D3M. It covers theoretical and applied contributions aiming to: 1) propose next-generation data mining frameworks and processes for actionable knowledge discovery, 2) investigate effective (automated, human and machine-centered and/or human-machined-co-operated) principles and approaches for acquiring, representing, modelling, and engaging ubiquitous intelligence in real-world data mining, and 3) develop workable and operational systems balancing technical significance and applications concerns, and converting and delivering actionable knowledge into operational applications rules to seamlessly engage application processes and systems.

Internet use and psychological wellbeing among 10 and 11 year old children

This paper uses data from the 2009 Kids’ Life and Times Survey, involving 3657 children aged 10 or 11 years old in Northern Ireland. The survey indicated high levels of use of Internet applications, including social-networking sites and online games. Using the KIDSCREEN-27 instrument, the data indicate that the use of social-networking sites and online games is related to poorer psychological well-being among girls, but not boys. Boys and girls who experience “cyberbullying” have poorer psychological well-being. This association between psychological well-being and some Internet applications merits more attention in future research and policy development.

Internet Use and Psychological Well-being among 10-year-old and 11-year-old Children

This paper uses data from the 2009 Kids’ Life and Times Survey, involving 3657 children aged 10 or 11 years old in Northern Ireland. The survey indicated high levels of use of Internet applications, including social-networking sites and online games. Using the KIDSCREEN-27 instrument, the data indicate that the use of social-networking sites and online games is related to poorer psychological well-being among girls, but not boys. Boys and girls who experience “cyberbullying” have poorer psychological well-being. This association between psychological well-being and some Internet applications merits more attention in future research and policy development.

Surveillance for ocular hypertension: An evidence synthesis and economic evaluation

OBJECTIVES: To determine effective and efficient monitoring criteria for ocular hypertension [raised intraocular pressure (IOP)] through (i) identification and validation of glaucoma risk prediction models; and (ii) development of models to determine optimal surveillance pathways.

DESIGN: A discrete event simulation economic modelling evaluation. Data from systematic reviews of risk prediction models and agreement between tonometers, secondary analyses of existing datasets (to validate identified risk models and determine optimal monitoring criteria) and public preferences were used to structure and populate the economic model.

SETTING: Primary and secondary care.

PARTICIPANTS: Adults with ocular hypertension (IOP > 21 mmHg) and the public (surveillance preferences).

INTERVENTIONS: We compared five pathways: two based on National Institute for Health and Clinical Excellence (NICE) guidelines with monitoring interval and treatment depending on initial risk stratification, 'NICE intensive' (4-monthly to annual monitoring) and 'NICE conservative' (6-monthly to biennial monitoring); two pathways, differing in location (hospital and community), with monitoring biennially and treatment initiated for a ≥ 6% 5-year glaucoma risk; and a 'treat all' pathway involving treatment with a prostaglandin analogue if IOP > 21 mmHg and IOP measured annually in the community.

MAIN OUTCOME MEASURES: Glaucoma cases detected; tonometer agreement; public preferences; costs; willingness to pay and quality-adjusted life-years (QALYs).

RESULTS: The best available glaucoma risk prediction model estimated the 5-year risk based on age and ocular predictors (IOP, central corneal thickness, optic nerve damage and index of visual field status). Taking the average of two IOP readings, by tonometry, true change was detected at two years. Sizeable measurement variability was noted between tonometers. There was a general public preference for monitoring; good communication and understanding of the process predicted service value. 'Treat all' was the least costly and 'NICE intensive' the most costly pathway. Biennial monitoring reduced the number of cases of glaucoma conversion compared with a 'treat all' pathway and provided more QALYs, but the incremental cost-effectiveness ratio (ICER) was considerably more than £30,000. The 'NICE intensive' pathway also avoided glaucoma conversion, but NICE-based pathways were either dominated (more costly and less effective) by biennial hospital monitoring or had a ICERs > £30,000. Results were not sensitive to the risk threshold for initiating surveillance but were sensitive to the risk threshold for initiating treatment, NHS costs and treatment adherence.

LIMITATIONS: Optimal monitoring intervals were based on IOP data. There were insufficient data to determine the optimal frequency of measurement of the visual field or optic nerve head for identification of glaucoma. The economic modelling took a 20-year time horizon which may be insufficient to capture long-term benefits. Sensitivity analyses may not fully capture the uncertainty surrounding parameter estimates.

CONCLUSIONS: For confirmed ocular hypertension, findings suggest that there is no clear benefit from intensive monitoring. Consideration of the patient experience is important. A cohort study is recommended to provide data to refine the glaucoma risk prediction model, determine the optimum type and frequency of serial glaucoma tests and estimate costs and patient preferences for monitoring and treatment.

FUNDING: The National Institute for Health Research Health Technology Assessment Programme.

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

Dataflow toolset for soft-core processors on FPGA for image processing applications

With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

Exercise rehabilitation following intensive care unit discharge for recovery from critical illness

Background: Skeletal muscle wasting and weakness are significant complications of critical illness, associated with the degree of illness severity and periods of reduced mobility during mechanical ventilation. They contribute to the profound physical and functional deficits observed in survivors. These impairments may persist for many years following discharge from the intensive care unit (ICU) and may markedly influence health-related quality of life. Rehabilitation is a key strategy in the recovery of patients following critical illness. Exercise based interventions are aimed at targeting this muscle wasting and weakness. Physical rehabilitation delivered during ICU admission has been systematically evaluated and shown to be beneficial. However its effectiveness when initiated after ICU discharge has yet to be established. Objectives: To assess the effectiveness of exercise rehabilitation programmes, initiated after ICU discharge, on functional exercise capacity and health-related quality of life in adult ICU survivors who have been mechanically ventilated for more than 24 hours. Search methods:We searched the following databases: the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library), OvidSP MEDLINE, Ovid SP EMBASE, and CINAHL via EBSCO host to 15th May 2014. We used a specific search strategy for each database. This included synonyms for ICU and critical illness, exercise training and rehabilitation. We searched the reference lists of included studies and contacted primary authors to obtain further information regarding potentially eligible studies. We also searched major clinical trials registries (Clinical Trials and Current Controlled Trials) and the personal libraries of the review authors. We applied no language or publication restriction. We reran the search in February 2015. We will deal with any studies of interest when we update the review.  Selection criteria:We included randomized controlled trials (RCTs), quasi-RCTs, and controlled clinical trials (CCTs) that compared an exercise interventioninitiated after ICU discharge to any other intervention or a control or ‘usual care’ programme in adult (≥18years) survivors ofcritical illness. Data collection and analysis:We used standard methodological procedures expected by The Cochrane Collaboration. Main results:We included six trials (483 adult ICU participants). Exercise-based interventions were delivered on the ward in two studies; both onthe ward and in the community in one study; and in the community in three studies. The duration of the intervention varied according to the length of stay in hospital following ICU discharge (up to a fixed duration of 12 weeks).Risk of bias was variable for all domains across all trials. High risk of bias was evident in all studies for performance bias, although blinding of participants and personnel in therapeutic rehabilitation trials can be pragmatically challenging. Low risk of bias was at least 50% for all other domains across all trials, although high risk of bias was present in one study for random sequence generation (selection bias), incomplete outcome data (attrition bias) and other sources. Risk of bias was unclear for remaining studies across the domains.All six studies measured effect on the primary outcome of functional exercise capacity, although there was wide variability in natureof intervention, outcome measures and associated metrics, and data reporting. Overall quality of the evidence was very low. Only two studies using the same outcome measure for functional exercise capacity, had the potential for pooling of data and assessment of heterogeneity. On statistical advice, this was considered inappropriate to perform this analysis and study findings were therefore qualitatively described. Individually, three studies reported positive results in favour of the intervention. A small benefit (versus. control)was evident in anaerobic threshold in one study (mean difference, MD (95% confidence interval, CI), 1.8 mlO2/kg/min (0.4 to 3.2),P value = 0.02), although this effect was short-term, and in a second study, both incremental (MD 4.7 (95% CI 1.69 to 7.75) Watts, P value = 0.003) and endurance (MD 4.12 (95% CI 0.68 to 7.56) minutes, P value = 0.021) exercise testing demonstrated improvement.Finally self-reported physical function increased significantly following a rehabilitation manual (P value = 0.006). Remaining studies found no effect of the intervention.Similar variability in with regard findings for the primary outcome of health-related quality of life were also evident. Only two studies evaluated this outcome. Following statistical advice, these data again were considered inappropriate for pooling to determine overall effect and assessment of heterogeneity. Qualitative description of findings was therefore undertaken. Individually, neither study reported differences between intervention and control groups for health-related quality of life as a result of the intervention. Overall quality of the evidence was very low.Mortality was reported by all studies, ranging from 0% to 18.8%. Only one non-mortality adverse event was reported across all patients in all studies (a minor musculoskeletal injury). Withdrawals, reported in four studies, ranged from 0% to 26.5% in control groups,and 8.2% to 27.6% in intervention groups. Loss to follow-up, reported in all studies, ranged from 0% to 14% in control groups, and 0% to 12.5% in intervention groups. Authors’ conclusions:We are unable, at this time, to determine an overall effect on functional exercise capacity, or health-related quality of life, of an exercise based intervention initiated after ICU discharge in survivors of critical illness. Meta-analysis of findings was not appropriate. This was due to insufficient study number and data. Individual study findings were inconsistent. Some studies reported a beneficial effect of the intervention on functional exercise capacity, and others not. No effect was reported on health-related quality of life. Methodological rigour was lacking across a number of domains influencing quality of the evidence. There was also wide variability in the characteristics of interventions, outcome measures and associated metrics, and data reporting.If further trials are identified, we may be able to determine the effect of exercise-based interventions following ICU discharge, on functional exercise capacity and health-related quality of life in survivors of critical illness.

Aspirin therapy in patients with acute respiratory distress syndrome (ARDS) is associated with reduced intensive care unit mortality: a prospective analysis

INTRODUCTION: Acute respiratory distress syndrome (ARDS) is a common clinical syndrome with high mortality and long-term morbidity. To date there is no effective pharmacological therapy. Aspirin therapy has recently been shown to reduce the risk of developing ARDS, but the effect of aspirin on established ARDS is unknown.

METHODS: In a single large regional medical and surgical ICU between December 2010 and July 2012, all patients with ARDS were prospectively identified and demographic, clinical, and laboratory variables were recorded retrospectively. Aspirin usage, both pre-hospital and during intensive care unit (ICU) stay, was included. The primary outcome was ICU mortality. We used univariate and multivariate logistic regression analyses to assess the impact of these variables on ICU mortality.

RESULTS: In total, 202 patients with ARDS were included; 56 (28%) of these received aspirin either pre-hospital, in the ICU, or both. Using multivariate logistic regression analysis, aspirin therapy, given either before or during hospital stay, was associated with a reduction in ICU mortality (odds ratio (OR) 0.38 (0.15 to 0.96) P = 0.04). Additional factors that predicted ICU mortality for patients with ARDS were vasopressor use (OR 2.09 (1.05 to 4.18) P = 0.04) and APACHE II score (OR 1.07 (1.02 to 1.13) P = 0.01). There was no effect upon ICU length of stay or hospital mortality.

CONCLUSION: Aspirin therapy was associated with a reduced risk of ICU mortality. These data are the first to demonstrate a potential protective role for aspirin in patients with ARDS. Clinical trials to evaluate the role of aspirin as a pharmacological intervention for ARDS are needed.

PESSTO: Survey description and products from the first data release by the Public ESO Spectroscopic Survey of Transient Objects

Context. The Public European Southern Observatory Spectroscopic Survey of Transient Objects (PESSTO) began as a public spectroscopic survey in April 2012. PESSTO classifies transients from publicly available sources and wide-field surveys, and selects science targets for detailed spectroscopic and photometric follow-up. PESSTO runs for nine months of the year, January - April and August - December inclusive, and typically has allocations of 10 nights per month. 

Aims. We describe the data reduction strategy and data products that are publicly available through the ESO archive as the Spectroscopic Survey data release 1 (SSDR1). 

Methods. PESSTO uses the New Technology Telescope with the instruments EFOSC2 and SOFI to provide optical and NIR spectroscopy and imaging. We target supernovae and optical transients brighter than 20.5^m for classification. Science targets are selected for follow-up based on the PESSTO science goal of extending knowledge of the extremes of the supernova population. We use standard EFOSC2 set-ups providing spectra with resolutions of 13-18 Å between 3345-9995 Å. A subset of the brighter science targets are selected for SOFI spectroscopy with the blue and red grisms (0.935-2.53 μm and resolutions 23-33 Å) and imaging with broadband JHK<inf>s</inf> filters. 

Results. This first data release (SSDR1) contains flux calibrated spectra from the first year (April 2012-2013). A total of 221 confirmed supernovae were classified, and we released calibrated optical spectra and classifications publicly within 24 h of the data being taken (via WISeREP). The data in SSDR1 replace those released spectra. They have more reliable and quantifiable flux calibrations, correction for telluric absorption, and are made available in standard ESO Phase 3 formats. We estimate the absolute accuracy of the flux calibrations for EFOSC2 across the whole survey in SSDR1 to be typically ∼15%, although a number of spectra will have less reliable absolute flux calibration because of weather and slit losses. Acquisition images for each spectrum are available which, in principle, can allow the user to refine the absolute flux calibration. The standard NIR reduction process does not produce high accuracy absolute spectrophotometry but synthetic photometry with accompanying JHK<inf>s</inf> imaging can improve this. Whenever possible, reduced SOFI images are provided to allow this. 

Conclusions. Future data releases will focus on improving the automated flux calibration of the data products. The rapid turnaround between discovery and classification and access to reliable pipeline processed data products has allowed early science papers in the first few months of the survey.

An iterative longest matching segment approach to speech enhancement with additive noise and channel distortion

This paper presents a new approach to speech enhancement from single-channel measurements involving both noise and channel distortion (i.e., convolutional noise), and demonstrates its applications for robust speech recognition and for improving noisy speech quality. The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise for speech estimation. Third, we present an iterative algorithm which updates the noise and channel estimates of the corpus data model. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement.

Developing an information booklet to meet the needs of intensive care patients and relatives

Changes in the economic climate and the delivery of health care require that pre-operative information programmes are effective and efficiently implemented. In order to be effective the pre-operative programme must meet the information needs of intensive care unit (ICU) patients and their relatives. Efficiency can be achieved through a structured pre-operative programme which provides a framework for teaching. The need to develop an ICU information booklet in a large teaching hospital in Northern Ireland has become essential to provide relevant information and improve the quality of service for patients and relatives, as set out in the White Paper, ‘Working for Patients’, (DoH, 1989). The first step in establishing a patient education programme was to ascertain patients' and relatives' informational needs. A ‘needs assessment’ identified the pre-operative information needs of ICU patients and their relatives (McGaughey, 1994) and the findings were used to plan and publish an information booklet. The ICU booklet provides a structure for pre-operative visits to ensure that patients and relatives information needs are met.

A realistic evaluation of track and trigger systems and acute care training for early recognition and treatment of deteriorating ward-based patients: research protocol.

Aim The aim of the study is to evaluate factors that enable or constrain the implementation and service delivery of early warnings systems or acute care training in practice. Background To date there is limited evidence to support the effectiveness of acute care initiatives (early warning systems, acute care training, outreach) in reducing the number of adverse events (cardiac arrest, death, unanticipated Intensive Care admission) through increased recognition and management of deteriorating ward based patients in hospital [1-3]. The reasons posited are that previous research primarily focused on measuring patient outcomes following the implementation of an intervention or programme without considering the social factors (the organisation, the people, external influences) which may have affected the process of implementation and hence measured end-points. Further research which considers the social processes is required in order to understand why a programme works, or does not work, in particular circumstances [4]. Method The design is a multiple case study approach of four general wards in two acute hospitals where Early Warning Systems (EWS) and Acute Life-threatening Events Recognition and Treatment (ALERT) course have been implemented. Various methods are being used to collect data about individual capacities, interpersonal relationships and institutional balance and infrastructures in order to understand the intended and unintended process outcomes of implementing EWS and ALERT in practice. This information will be gathered from individual and focus group interviews with key participants (ALERT facilitators, nursing and medical ALERT instructors, ward managers, doctors, ward nurses and health care assistants from each hospital); non-participant observation of ward organisation and structure; audit of patients' EWS charts and audit of the medical notes of patients who deteriorated during the study period to ascertain whether ALERT principles were followed. Discussion & progress to date This study commenced in January 2007. Ethical approval has been granted and data collection is ongoing with interviews being conducted with key stakeholders. The findings from this study will provide evidence for policy-makers to make informed decisions regarding the direction for strategic and service planning of acute care services to improve the level of care provided to acutely ill patients in hospital. References 1. Esmonde L, McDonnell A, Ball C, Waskett C, Morgan R, Rashidain A et al. Investigating the effectiveness of Critical Care Outreach Services: A systematic review. Intensive Care Medicine 2006; 32: 1713-1721 2. McGaughey J, Alderdice F, Fowler R, Kapila A, Mayhew A, Moutray M. Outreach and Early Warning Systems for the prevention of Intensive Care admission and death of critically ill patients on general hospital wards. Cochrane Database of Systematic Reviews 2007, Issue 3. www.thecochranelibrary.com 3. Winters BD, Pham JC, Hunt EA, Guallar E, Berenholtz S, Pronovost PJ (2007) Rapid Response Systems: A systematic review. Critical Care Medicine 2007; 35 (5): 1238-43 4. Pawson R and Tilley N. Realistic Evaluation. London; Sage: 1997