The structure of the Beck Hopelessness Scale: A confirmatory factor analysis in UK students

The aim of this paper was to confirm the factor structure of the 20-item Beck Hopelessness Scale in a non-clinical population. Previous research has highlighted a lack of clarity in its construct validity with regards to this population.

Based on previous factor analytic findings from both clinical and non-clinical studies, 13 separate confirmatory factor models were specified and estimated using LISREL 8.72 to test the one, two and three-factor models.

Psychology and medical students at Queen's University, Belfast (n = 581) completed both the BHS and the Beck Depression Inventory (BDI).

All models showed reasonable fit, but only one, a four-item single-factor model demonstrated a nonsignificant chi-squared statistic. These four items can be used to derive a Short-Form BHS (SBHS) in which increasing scores (0-4) corresponded with increasing scores in the BDI. The four items were also drawn from all three of Beck's proposed triad, and included both positively and negatively scored items.

This study in a UK undergraduate non-clinical population suggests that the BHS best measures a one-factor model of hopelessness. It appears that a shorter four-item scale can also measure this one-factor model. (C) 2011 Elsevier Ltd. All rights reserved.

Work-family characteristics as determinants of sickness absence: A large-scale cohort study of three occupational grades

This study examined the previously unexplored occupational grade-specific relationships of domestic responsibilities, the age of children, and work-family spillover, with registered sickness absence (>3 days' sick leave episodes, a mean follow-up of 17 months; n = 18,366 municipal employees; 76% women). The results showed that negative spillover from work into family life predicted a heightened rate of sickness absence spells among both women and men in all occupational categories (except upper white-collar men), but especially among blue-collar and lower white-collar employees. Furthermore, among all white-collar employees (except upper white-collar men), having young children (

Preliminary results from follow-up of a large-scale population survey of antibodies to gliadin, reticulin and endomysium

Coeliac disease is often under-diagnosed, particularly in cases which are atypical or asymptomatic.

Cognitive, global, and functional benefits of donepezil in Alzheimer's disease and vascular dementia:results from large-scale clinical trials

Alzheimer's disease (AD) and vascular dementia (VaD) are both associated with deficits in cholinergic neurotransmission that are amenable to therapeutic intervention. The cholinesterase inhibitor, donepezil, is clinically effective in both AD and VaD. Results from a 10-study metaanalysis of donepezil (5 or 10 mg/day) in AD and a two-study combined analysis of donepezil (5 or 10 mg/day) in VaD are presented to compare patient characteristics and donepezil treatment outcomes. The analyzed studies were randomized, placebo-controlled, and of up to 24 weeks duration. In both AD and VaD, donepezil provided significant benefits compared with placebo on measures of cognition and global function. Placebo-treated AD patients showed a decline in cognition and global function, whereas placebo-treated VaD patients remained stable, suggesting treatment effects of donepezil in VaD were driven by improvement rather than stabilization or reduced decline. More VaD patients than AD patients received concomitant medications. Cardiovascular adverse events were more common in VaD than AD patients but were not increased by donepezil. In conclusion, although there are differences between AD and VaD patients in comorbid conditions and concomitant medications, donepezil is effective and well tolerated in both types of dementia.

Collectives of diagnostic biomarkers identify high-risk subpopulations of hematuria patients: exploiting heterogeneity in large-scale biomarker data

Background: Ineffective risk stratification can delay diagnosis of serious disease in patients with hematuria. We applied a systems biology approach to analyze clinical, demographic and biomarker measurements (n = 29) collected from 157 hematuric patients: 80 urothelial cancer (UC) and 77 controls with confounding pathologies.

Methods: On the basis of biomarkers, we conducted agglomerative hierarchical clustering to identify patient and biomarker clusters. We then explored the relationship between the patient clusters and clinical characteristics using Chi-square analyses. We determined classification errors and areas under the receiver operating curve of Random Forest Classifiers (RFC) for patient subpopulations using the biomarker clusters to reduce the dimensionality of the data.

Results: Agglomerative clustering identified five patient clusters and seven biomarker clusters. Final diagnoses categories were non-randomly distributed across the five patient clusters. In addition, two of the patient clusters were enriched with patients with ‘low cancer-risk’ characteristics. The biomarkers which contributed to the diagnostic classifiers for these two patient clusters were similar. In contrast, three of the patient clusters were significantly enriched with patients harboring ‘high cancer-risk” characteristics including proteinuria, aggressive pathological stage and grade, and malignant cytology. Patients in these three clusters included controls, that is, patients with other serious disease and patients with cancers other than UC. Biomarkers which contributed to the diagnostic classifiers for the largest ‘high cancer- risk’ cluster were different than those contributing to the classifiers for the ‘low cancer-risk’ clusters. Biomarkers which contributed to subpopulations that were split according to smoking status, gender and medication were different.

Conclusions: The systems biology approach applied in this study allowed the hematuric patients to cluster naturally on the basis of the heterogeneity within their biomarker data, into five distinct risk subpopulations. Our findings highlight an approach with the promise to unlock the potential of biomarkers. This will be especially valuable in the field of diagnostic bladder cancer where biomarkers are urgently required. Clinicians could interpret risk classification scores in the context of clinical parameters at the time of triage. This could reduce cystoscopies and enable priority diagnosis of aggressive diseases, leading to improved patient outcomes at reduced costs. © 2013 Emmert-Streib et al; licensee BioMed Central Ltd.

Large-scale spatial patterns in the distribution of Collembola (Hexapoda) species in Antarctic terrestrial ecosystems

We tested whether the distribution of three common springtail species (Gressittacantha terranova, Gomphiocephalus hodgsoni and Friesea grisea) in Victoria Land (Antarctica) could be modelled as a function of latitude, longitude, altitude and distance from the sea.

Victoria Land, Ross Dependency, Antarctica.

Generalized linear models were constructed using species presence/absence data relative to geographical features (latitude, longitude, altitude, distance from sea) across the species' entire ranges. Model results were then integrated with the known phylogeography of each species and hypotheses were generated on the role of climate as a major driver of Antarctic springtail distribution.

Based on model selection using Akaike's information criterion, the species' distributions were: hump-shaped relative to longitude and monotonic with altitude for Gressittacantha terranova; hump-shaped relative to latitude and monotonic with altitude for Gomphiocephalus hodgsoni; and hump-shaped relative to longitude and monotonic with latitude, altitude and distance from the sea for Friesea grisea.

No single distributional pattern was shared by the three species. While distributions were partially a response to climatic spatial clines, the patterns observed strongly suggest that past geological events have influenced the observed distributions. Accordingly, present-day spatial patterns are likely to have arisen from the interaction of historical and environmental drivers. Future studies will need to integrate a range of spatial and temporal scales to further quantify their respective roles.

Coordinated Design of Phase Measurement Unit and Power System Stabilisers in Large Scale Power System

This paper presents a case-study of a PMU application with PSS support in a real large scale Chinese power system to suppress inter-area oscillations. The paper uses PMU measured feedback signals from a PSS input signal for dynamic torque analysis (DTA). In the paper, a mathematical model of multi-machine power system is described, followed by formation of the residue and DTA indices. Simulations of the model are used with a large-scale power system model to demonstrate the role of PSS and the equivalence of DTA residue indices.

CHARACTERIZATION OF THE AU SURFACE-STRUCTURE OF AL-L-AU LIGHT-EMITTING TUNNEL-JUNCTIONS

Visible light is emitted from the Au-air interface of Al-I-Au thin-film tunnel junctions (deposited over a thin layer of CaF2 on glass) as a result of the decay of surface plasmon polaritons (SPPs). We show the surface topography of such a Au film and relate its large-scale features to the outcoupling of fast SPP's to photons. The absence of short-scale roughness features is explained by thier disappearance through surface diffusion. To confirm this a controlled sequence of 5-nm, 20-ms scanning tunneling microscope (STM) W tip crashes has been used to produce indentations 3 nm deep with a lateral dimension of 5-7 nm on a Au crystal in air at room temperature. Four sequences of indentations were drawn in the form of a square box. Right from the start, feature decay is observed and over a period of 2 h a succession of images shows that the structure disappears into the background as a result of surface diffusion. The surface diffusion constant is estimated to be 10(-18) cm2 s-1. The lack of light output via slow mode SPPs is an inevitable consequence of surface annealing.

Optimizing the efficiency of the sub-map technique for large-scale simultaneous localization and mapping

A technique for optimizing the efficiency of the sub-map method for large-scale simultaneous localization and mapping (SLAM) is proposed. It optimizes the benefits of the sub-map technique to improve the accuracy and consistency of an extended Kalman filter (EKF)-based SLAM. Error models were developed and engaged to investigate some of the outstanding issues in employing the sub-map technique in SLAM. Such issues include the size (distance) of an optimal sub-map, the acceptable error effect caused by the process noise covariance on the predictions and estimations made within a sub-map, when to terminate an existing sub-map and start a new one and the magnitude of the process noise covariance that could produce such an effect. Numerical results obtained from the study and an error-correcting process were engaged to optimize the accuracy and convergence of the Invariant Information Local Sub-map Filter previously proposed. Applying this technique to the EKF-based SLAM algorithm (a) reduces the computational burden of maintaining the global map estimates and (b) simplifies transformation complexities and data association ambiguities usually experienced in fusing sub-maps together. A Monte Carlo analysis of the system is presented as a means of demonstrating the consistency and efficacy of the proposed technique.