Model calculations for copper clusters on Au(111) surfaces

Using the semi-empirical embedded-atom method, the structure of small copper clusters on Au(111) surfaces has been investigated both by static and dynamic calculations. By varying the size of roughly circular clusters, the edge energy per atom is obtained; it agrees quite well with estimates based on experimental results. Small three-dimensional clusters tend to have the shape of a pyramid, whose sides are oriented in the directions of small surface energy. The presence of a cluster is found to distort the underlying lattice of adsorbed copper atoms. (C) 2002 Published by Elsevier Science B.V.

General local and rectilinear vibrational coordinates consistent with Eckart's conditions

We present a general method to construct a set of local rectilinear vibrational coordinates for a nonlinear molecule whose reference structure does not necessarily correspond to a stationary point of the potential-energy surface. We show both analytically and with a numerical example that the vibrational coordinates satisfy Eckart's conditions. In addition, we find that the Watson Hamiltonian provides a fairly robust description even of highly excited vibrational states of triatomic molecules, except for a few states of large amplitude motion sampling the singular region of the Hamiltonian. These states can be identified through slow convergence.

Effect of tailored practice and patient care plans on secondary prevention of heart disease in general practice: cluster randomised controlled trial

Objective: To test the effectiveness of a complex intervention designed, within a theoretical framework, to improve outcomes for patients with coronary heart disease. Design: Cluster randomised controlled multicentre trial. Setting: General practices in Northern Ireland and the Republic of Ireland, regions with different healthcare systems. Participants: 903 patients with established coronary heart disease registered with one of 48 practices. Intervention: Tailored care plans for practices (practice based training in prescribing and behaviour change, administrative support, quarterly newsletter), and tailored care plans for patients (motivational interviewing, goal identification, and target setting for lifestyle change) with reviews every four months at the practices. Control practices provided usual care. Main outcome measures: The proportion of patients at 18 month follow-up above target levels for blood pressure and total cholesterol concentration, and those admitted to hospital, and changes in physical and mental health status (SF-12). Results: At baseline the numbers (proportions) of patients above the recommended limits were: systolic blood pressure greater than 140 mm Hg (305/899; 33.9%, 95% confidence interval 30.8% to 33.9%), diastolic blood pressure greater than 90 mm Hg (111/901; 12.3%, 10.2% to 14.5%), and total cholesterol concentration greater than 5 mmol/l (188/860; 20.8%, 19.1% to 24.6%). At the 18 month follow-up there were no significant differences between intervention and control groups in the numbers (proportions) of patients above the recommended limits: systolic blood pressure, intervention 98/360 (27.2%) v control, 133/405 (32.8%), odds ratio 1.51 (95% confidence interval 0.99 to 2.30; P=0.06); diastolic blood pressure, intervention 32/360 (8.9%) v control, 40/405 (9.9%), 1.40 (0.75 to 2.64; P=0.29); and total cholesterol concentration, intervention 52/342 (15.2%) v control, 64/391 (16.4%), 1.13 (0.63 to 2.03; P=0.65). The number of patients admitted to hospital over the 18 month study period significantly decreased in the intervention group compared with the control group: 107/415 (25.8%) v 148/435 (34.0%), 1.56 (1.53 to 2.60; P=0.03). Conclusions: Admissions to hospital were significantly reduced after an intensive 18 month intervention to improve outcomes for patients with coronary heart disease, but no other clinical benefits were shown, possibly because of a ceiling effect related to improved management of the disease. Trial registration: Current Controlled Trials ISRCTN24081411.

Outreach and Early Warning Systems (EWS) for the prevention of intensive care admission and death of critically ill adult patients on general hospital wards

BACKGROUND: Despite the fact that outreach and early warning systems (EWS) are an integral part of a hospital wide systems approach to improve the early identification and management of deteriorating patients on general hospital wards, the widespread implementation of these interventions in practice is not based on robust research evidence. OBJECTIVES: The primary objective was to determine the impact of critical care outreach services on hospital mortality rates. Secondary objectives included determining the effect of outreach services on intensive care unit (ICU) admission patterns, length of hospital stay and adverse events. SEARCH STRATEGY: The review authors searched the following electronic databases: EPOC Specialised Register, The Cochrane Central Register of Controlled Trials (CENTRAL) and other Cochrane databases (all on The Cochrane Library 2006, Issue 3), MEDLINE (1996-June week 3 2006), EMBASE (1974-week 26 2006), CINAHL (1982-July week 5 2006), First Search (1992-2005) and CAB Health (1990-July 2006); also reference lists of relevant articles, conference abstracts, and made contact with experts and critical care organisations for further information. SELECTION CRITERIA: Randomised controlled trials (RCTs), controlled clinical trials (CCTs), controlled before and after studies (CBAs) and interrupted time series designs (ITS) which measured hospital mortality, unanticipated ICU admissions, ICU readmissions, length of hospital stay and adverse events following implementation of outreach and EWS in a general hospital ward to identify deteriorating adult patients versus general hospital ward setting without outreach and EWS were included in the review. DATA COLLECTION AND ANALYSIS: Three review authors independently extracted data and two review authors assessed the methodological quality of the included studies. Meta-analysis was not possible due to heterogeneity. Summary statistics and descriptive summaries of primary and secondary outcomes are presented for each study. MAIN RESULTS: Two cluster-randomised control trials were included: one randomised at hospital level (23 hospitals in Australia) and one at ward level (16 wards in the UK). The primary outcome in the Australian trial (a composite score comprising incidence of unexpected cardiac arrests, unexpected deaths and unplanned ICU admissions) showed no statistical significant difference between control and medical emergency team (MET) hospitals (adjusted P value 0.640; adjusted odds ratio (OR) 0.98; 95% confidence interval (CI) 0.83 to 1.16). The UK-based trial found that outreach reduced in-hospital mortality (adjusted OR 0.52; 95% CI 0.32 to 0.85) compared with the control group. AUTHORS' CONCLUSIONS: The evidence from this review highlights the diversity and poor methodological quality of most studies investigating outreach. The results of the two included studies showed either no evidence of the effectiveness of outreach or a reduction in overall mortality in patients receiving outreach. The lack of evidence on outreach requires further multi-site RCT's to determine potential effectiveness.

A general framework for measuring inconsistency through minimal inconsistent sets

Hunter and Konieczny explored the relationships between measures of inconsistency for a belief base and the minimal inconsistent subsets of that belief base in several of their papers. In particular, an inconsistency value termed MIVC, defined from minimal inconsistent subsets, can be considered as a Shapley Inconsistency Value. Moreover, it can be axiomatized completely in terms of five simple axioms. MinInc, one of the five axioms, states that each minimal inconsistent set has the same amount of conflict. However, it conflicts with the intuition illustrated by the lottery paradox, which states that as the size of a minimal inconsistent belief base increases, the degree of inconsistency of that belief base becomes smaller. To address this, we present two kinds of revised inconsistency measures for a belief base from its minimal inconsistent subsets. Each of these measures considers the size of each minimal inconsistent subset as well as the number of minimal inconsistent subsets of a belief base. More specifically, we first present a vectorial measure to capture the inconsistency for a belief base, which is more discriminative than MIVC. Then we present a family of weighted inconsistency measures based on the vectorial inconsistency measure, which allow us to capture the inconsistency for a belief base in terms of a single numerical value as usual. We also show that each of the two kinds of revised inconsistency measures can be considered as a particular Shapley Inconsistency Value, and can be axiomatically characterized by the corresponding revised axioms presented in this paper.