Xanthoria parietina as a biomonitor of airborne heavy metal pollution in forest sites in the North East of Morocco

Xanthoria parietina, common foliose lichen, growing in its natural habitat, was analysed for the concentration of five heavy metals (Fe, Cr, Zn, Pb and Cu) from different forest sites of North East of Morocco (Kenitra, Sidi Boughaba, Mkhinza, Ceinture Verte near Temara city, Skhirate, Bouznika and Mohammedia). The quantification was carried out by inductively coupled plasma - atomic emission spectrometry (ICP-AES). Results were highly significant p<0,001. The concentration of metals is correlated with the vehicular activity and urbanization. The total metal concentration is highest at the Kenitra area, followed by Ceinture Verte site near Temara city, which experience heavy traffic throughout the year. Scanning electron microscopy (SEM) of particulate matter on lichen of Xanthoria parietina was assessed as a complementary technique to wet chemical analysis for source apportionment of airborne contaminant. Analysis revealed high level of Cu, Cr, Zn and Pb in samples near roads.  

Knowledge-based risk assessment under uncertainty in engineering projects

In this paper we describe how an evidential-reasoner can be used as a component of risk assessment of engineering projects using a direct way of reasoning. Guan & Bell (1991) introduced this method by using the mass functions to express rule strengths. Mass functions are also used to express data strengths. The data and rule strengths are combined to get a mass distribution for each rule; i.e., the first half of our reasoning process. Then we combine the prior mass and the evidence from the different rules; i.e., the second half of the reasoning process. Finally, belief intervals are calculated to help in identifying the risks. We apply our evidential-reasoner on an engineering project and the results demonstrate the feasibility and applicability of this system in this environment.

Value-oriented impact assessment: the economics of a new approach to impact assessment

Environmental Impact Assessment has gained a prominent position as a tool to evaluate the environmental effects of economic activities. However, all approaches proposed so far use a burden-oriented logic. They concentrate on the different environmental impacts in order to ascertain the overall environmental damage caused by economic activity. This paper argues that such a burden-oriented view is (a) hampered by a series of methodological shortcomings which hinders its widespread use in practice; and (b) is analytically incomplete. The paper proposes a value-oriented approach to impact assessment. For this purpose an economic analysis of the optimal use of environmental and social resources is conducted from both a burden-oriented and a value-oriented standpoint. The basic logic of a value-oriented impact assessment is explained, as well as the resulting economic conditions for an optimal use of resources. In addition, it is shown that value- and burden-oriented approaches are complementary to achieve optimality. Finally, the paper discusses the conditions under which the use of burden- or value-oriented impact assessments is appropriate, respectively.

A randomised, controlled trial of conventional versus automated weaning from mechanical ventilation using SmartcareTM/PS

Objective
Preliminary assessment of an automated weaning system (SmartCare™/PS) compared to usual management of weaning from mechanical ventilation performed in the absence of formal protocols.


Design and setting
A randomised, controlled pilot study in one Australian intensive care unit.


Patients
A total of 102 patients were equally divided between SmartCare/PS and Control.

Interventions
The automated system titrated pressure support, conducted a spontaneous breathing trial and provided notification of success (“separation potential”).

Measurements and results
The median time from the first identified point of suitability for weaning commencement to the state of “separation potential” using SmartCare/PS was 20 h (interquartile range, IQR, 2–40) compared to 8 h (IQR 2–43) with Control (log-rank P = 0.3). The median time to successful extubation was 43 h (IQR 6–169) using SmartCare/PS and 40 (14–87) with Control (log-rank P = 0.6). Unadjusted, the estimated probability of reaching “separation potential” was 21% lower (95% CI, 48% lower to 20% greater) with SmartCare/PS compared to Control. Adjusted for other covariates (age, gender, APACHE II, SOFAmax, neuromuscular blockade, corticosteroids, coma and elevated blood glucose), these estimates were 31% lower (95% CI, 56% lower to 9% greater) with SmartCare/PS. The study groups showed comparable rates of reintubation, non-invasive ventilation post-extubation, tracheostomy, sedation, neuromuscular blockade and use of corticosteroids.

Conclusions
Substantial reductions in weaning duration previously demonstrated were not confirmed when the SmartCare/PS system was compared to weaning managed by experienced critical care specialty nurses, using a 1:1 nurse-to-patient ratio. The effect of SmartCare/PS may be influenced by the local clinical organisational context.

Assessment of the benefits of Discrete Conditional Survival Models in modelling ambulance response times

Many of the challenges faced in health care delivery can be informed through building models. In particular, Discrete Conditional Survival (DCS) models, recently under development, can provide policymakers with a flexible tool to assess time-to-event data. The DCS model is capable of modelling the survival curve based on various underlying distribution types and is capable of clustering or grouping observations (based on other covariate information) external to the distribution fits. The flexibility of the model comes through the choice of data mining techniques that are available in ascertaining the different subsets and also in the choice of distribution types available in modelling these informed subsets. This paper presents an illustrated example of the Discrete Conditional Survival model being deployed to represent ambulance response-times by a fully parameterised model. This model is contrasted against use of a parametric accelerated failure-time model, illustrating the strength and usefulness of Discrete Conditional Survival models.

Measuring health-related quality of life after stroke: A brief tool.

Routine assessment of health-related quality of life (HRQoL) can be time consuming and burdensome for a person with stroke. Therefore the aim of this study was to develop and test a brief instrument for assessing HRQoL among people with stroke. The Quality of Life after Stroke Scale (QLASS) was constructed from items within the Quality of Life Index-Stroke Version and the Chronic Respiratory Disease Questionnaire. It was administered to 92 people with stroke at three points in time: immediately after discharge from hospital, 6 months and 12 months later. Results suggest that the QLASS has 19 items which represent three factors: emotional functioning, mastery and fatigue which correlate with valid measures of health status and activities of daily living. The QLASS is proposed as a brief, valid HRQoL tool for use among people with stroke.

Effect of a pharmacist-led multicomponent intervention focussing on the medication monitoring phase to prevent potential adverse drug events in nursing homes

OBJECTIVES: To determine the extent to which the use of a clinical informatics tool that implements prospective monitoring plans reduces the incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.

DESIGN: Randomized cluster trial.

SETTING: Twenty-five nursing homes serviced by two long-term care pharmacies.

PARTICIPANTS: Residents living in nursing homes during 2003 (1,711 in 12 intervention; 1,491 in 13 usual care) and 2004 (1,769 in 12 intervention; 1,552 in 13 usual care).

INTERVENTION: The pharmacy automatically generated Geriatric Risk Assessment MedGuide (GRAM) reports and automated monitoring plans for falls and delirium within 24 hours of admission or as part of the normal time frame of federally mandated drug regimen review.

MEASUREMENTS: Incidence of potential delirium, falls, hospitalizations potentially due to adverse drug events, and mortality.

RESULTS: GRAM triggered monitoring plans for 491 residents. Newly admitted residents in the intervention homes experienced a lower rate of potential delirium onset than those in usual care homes (adjusted hazard ratio (HR)=0.42, 95% confidence interval (CI)=0.35–0.52), overall hospitalization (adjusted HR=0.89, 95% CI=0.72–1.09), and mortality (adjusted HR=0.88, 95% CI=0.66–1.16). In longer stay residents, the effects of the intervention were attenuated, and all estimates included unity.

CONCLUSION: Using health information technology in long-term care pharmacies to identify residents who might benefit from the implementation of prospective medication monitoring care plans when complex medication regimens carry potential risks for falls and delirium may reduce adverse effects associated with appropriate medication use.

Home-Based Monitoring and Assessment of Parkinson's Disease

As a clinically complex neurodegenerative disease, Parkinson's disease (PD) requires regular assessment and close monitoring. In our current study, we have developed a home-based tool designed to monitor and assess peripheral motor symptoms. An evaluation of the tool was carried out over a period of ten weeks on ten people with idiopathic PD. Participants were asked to use the tool twice daily over four days, once when their medication was working at its best (

Assessing quality of life in cardiac rehabilitation: Choosing an appropriate tool

Quality of life is an important outcome for people undergoing cardiac rehabilitation. This paper discusses the difficulties with defining the concept of quality of life and how it might be distinct from the concept of health-related quality of life. Based on a review of the literature, a description is provided of health-related quality of life questionnaires that have been used in cardiac rehabilitation populations. Some criteria for choosing between these questionnaires are then discussed and, finally, a brief discussion is presented of the concept of response shift and how this might influence the assessment of health-related quality of life in a cardiac rehabilitation setting.

Automated versus non-automated weaning for reducing the duration of mechanical ventilation for critically ill adults and children (Review)

Abstract
Background: Automated closed loop systems may improve adaptation of the mechanical support to a patient's ventilatory needs and
facilitate systematic and early recognition of their ability to breathe spontaneously and the potential for discontinuation of
ventilation.

Objectives: To compare the duration of weaning from mechanical ventilation for critically ill ventilated adults and children when managed
with automated closed loop systems versus non-automated strategies. Secondary objectives were to determine differences
in duration of ventilation, intensive care unit (ICU) and hospital length of stay (LOS), mortality, and adverse events.

Search methods: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2011, Issue 2); MEDLINE (OvidSP) (1948 to August 2011); EMBASE (OvidSP) (1980 to August 2011); CINAHL (EBSCOhost) (1982 to August 2011); and the Latin American and Caribbean Health Sciences Literature (LILACS). In addition we received and reviewed auto-alerts for our search strategy in MEDLINE, EMBASE, and CINAHL up to August 2012. Relevant published reviews were sought using the Database of Abstracts of Reviews of Effects (DARE) and the Health Technology Assessment Database (HTA Database). We also searched the Web of Science Proceedings; conference proceedings; trial registration websites; and reference lists of relevant articles.

Selection criteria: We included randomized controlled trials comparing automated closed loop ventilator applications to non-automated weaning
strategies including non-protocolized usual care and protocolized weaning in patients over four weeks of age receiving invasive mechanical ventilation in an intensive care unit (ICU).

Data collection and analysis: Two authors independently extracted study data and assessed risk of bias. We combined data into forest plots using random-effects modelling. Subgroup and sensitivity analyses were conducted according to a priori criteria.

Main results: Pooled data from 15 eligible trials (14 adult, one paediatric) totalling 1173 participants (1143 adults, 30 children) indicated that automated closed loop systems reduced the geometric mean duration of weaning by 32% (95% CI 19% to 46%, P =0.002), however heterogeneity was substantial (I2 = 89%, P < 0.00001). Reduced weaning duration was found with mixed or
medical ICU populations (43%, 95% CI 8% to 65%, P = 0.02) and Smartcare/PS™ (31%, 95% CI 7% to 49%, P = 0.02) but not in surgical populations or using other systems. Automated closed loop systems reduced the duration of ventilation (17%, 95% CI 8% to 26%) and ICU length of stay (LOS) (11%, 95% CI 0% to 21%). There was no difference in mortality rates or hospital LOS. Overall the quality of evidence was high with the majority of trials rated as low risk.

Authors' conclusions: Automated closed loop systems may result in reduced duration of weaning, ventilation, and ICU stay. Reductions are more
likely to occur in mixed or medical ICU populations. Due to the lack of, or limited, evidence on automated systems other than Smartcare/PS™ and Adaptive Support Ventilation no conclusions can be drawn regarding their influence on these outcomes. Due to substantial heterogeneity in trials there is a need for an adequately powered, high quality, multi-centre randomized
controlled trial in adults that excludes 'simple to wean' patients. There is a pressing need for further technological development and research in the paediatric population.

Robust automated tumour segmentation on histological and immunohistochemical tissue images

Tissue microarray (TMA) is a high throughput analysis tool to identify new diagnostic and prognostic markers in human cancers. However, standard automated method in tumour detection on both routine histochemical and immunohistochemistry (IHC) images is under developed. This paper presents a robust automated tumour cell segmentation model which can be applied to both routine histochemical tissue slides and IHC slides and deal with finer pixel-based segmentation in comparison with blob or area based segmentation by existing approaches. The presented technique greatly improves the process of TMA construction and plays an important role in automated IHC quantification in biomarker analysis where excluding stroma areas is critical. With the finest pixel-based evaluation (instead of area-based or object-based), the experimental results show that the proposed method is able to achieve 80% accuracy and 78% accuracy in two different types of pathological virtual slides, i.e., routine histochemical H&E and IHC images, respectively. The presented technique greatly reduces labor-intensive workloads for pathologists and highly speeds up the process of TMA construction and provides a possibility for fully automated IHC quantification.

Critical assessment of two-qubit post-Markovian master equations

A post-Markovian master equation has been recently proposed as a tool to describe the evolution of a system coupled to a memory-keeping environment [A. Shabani and D. A. Lidar, Phys. Rev. A 71, 020101 ( R) ( 2005)]. For a single qubit affected by appropriately chosen environmental conditions, the corresponding dynamics is always legitimate and physical. Here we extend such a situation to the case of two qubits, only one of which experiences the environmental effects. We show how, despite the innocence of such an extension, the introduction of the second qubit should be done cum grano salis to avoid consequences such as the breaking of the positivity of the associated dynamical map. This hints at the necessity of using care when adopting phenomenologically derived models for evolutions occurring outside the Markovian framework.

An Integration Methodology for Automated Recurring Cost Prediction using Digital Manufacturing Technology

The need to account for the effect of design decisions on manufacture and the impact of manufacturing cost on the life cycle cost of any product are well established. In this context, digital design and manufacturing solutions have to be further developed to facilitate and automate the integration of cost as one of the major driver in the product life cycle management. This article is to present an integration methodology for implementing cost estimation capability within a digital manufacturing environment. A digital manufacturing structure of knowledge databases are set out and the ontology of assembly and part costing that is consistent with the structure is provided. Although the methodology is currently used for recurring cost prediction, it can be well applied to other functional developments, such as process planning. A prototype tool is developed to integrate both assembly time cost and parts manufacturing costs within the same digital environment. An industrial example is used to validate this approach.

Introducing Automated Management Through Iteratively Increased Automation and Indicators

Introducing automation into a managed environment includes significant initial overhead and abstraction, creating a disconnect between the administrator and the system. In order to facilitate the transition to automated management, this paper proposes an approach whereby automation increases gradually, gathering data from the task deployment process. This stored data is analysed to determine the task outcome status and can then be used for comparison against future deployments of the same task and alerting the administrator to deviations from the expected outcome. Using a machinelearning
approach, the automation tool can learn from the administrator's reaction to task failures and eventually react to faults autonomously.