High-contrast imaging search for planets and brown dwarfs around the most massive stars in the solar neighborhood

There has been a long-standing discussion in the literature as to whether core accretion or disk instability is the dominant mode of planet formation. Over the last decade, several lines of evidence have been presented showing that core accretion is most likely the dominant mechanism for the close-in population of planets probed by radial velocity and transits. However, this does not by itself prove that core accretion is the dominant mode for the total planet population, since disk instability might conceivably produce and retain large numbers of planets in the far-out regions of the disk. If this is a relevant scenario, then the outer massive disks of B-stars should be among the best places for massive planets and brown dwarfs to form and reside. In this study, we present high-contrast imaging of 18 nearby massive stars of which 15 are in the B2-A0 spectral-type range and provide excellent sensitivity to wide companions. By comparing our sensitivities to model predictions of disk instability based on physical criteria for fragmentation and cooling, and using Monte Carlo simulations for orbital distributions, we find that ~85% of such companions should have been detected in our images on average. Given this high degree of completeness, stringent statistical limits can be set from the null-detection result, even with the limited sample size. We find that

Empowering the Shamed Self: Recognition and Critical Social Work

Summary: This article provides a review of the contribution of Axel Honneth’s model of recognition for critical social work. While Honneth’s tripartite conceptualisation of optimal identity-formation is positively appraised, his analysis of the link between misrecognition, the experience of shame and eventual sense of moral outrage, is contested. Drawing on a range of sources, including the sociology of shame, Honneth’s ideas about the emotional antecedents of emancipatory action are revised to guide critical social work with misrecognised service users.

Findings: The intellectual background to Honneth’s recognition model, emanating from leading German philosophers, is described and its application to social work set out. Even so, Honneth’s model is found to be deficient in one primary regard: its assumption about the emotional antecedents to quests for withheld recognition is misapprehended. In particular, the argument in this article is that the ubiquitous emotion of shame, which Honneth argues flows from misrecognition, must be carefully addressed through the medium of relationship, otherwise it might lead to repressed shame and frustrated attempts at social struggle. To this end, a social work process is delineated for dealing with shame, following episodes of misrecognition.

Applications: Honneth’s model of recognition, along with revised ideas about how to recognise and manage shame, is incorporated into a conceptual framework for critical social work practice. With this renewed understanding of the impact of shame, following misrecognition, social workers should be better equipped conceptually to enable service users to take action for empowerment.

Advanced materials for recognition and capture of whole cells and microorganisms

Selective cell recognition and capture has recently attracted significant interest due to its potential importance for clinical, diagnostic, environmental, and security applications. Current methods for cell isolation from complex samples are largely dependent on cell size and density, with limited application scope as many of the target cells do not exhibit appreciable differences in this respect. The most recent and forthcoming developments in the area of selective recognition and capture of whole cells, based on natural receptors, as well as synthetic materials utilising physical and chemical properties of the target cell or microorganism, are highlighted. Particular focus is given to the development of cell complementary surfaces using the cells themselves as templating agents, by means of molecular imprinting, and their combination with sensing platforms for rapid cell detection in complex media. The benefits and challenges of each approach are discussed and a perspective of the future of this research area is given.

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

An extended framework for evidential reasoning systems.

Use of the Dempster-Shafer (D-S) theory of evidence to deal with uncertainty in knowledge-based systems has been widely addressed. Several AI implementations have been undertaken based on the D-S theory of evidence or the extended theory. But the representation of uncertain relationships between evidence and hypothesis groups (heuristic knowledge) is still a major problem. This paper presents an approach to representing such knowledge, in which Yen’s probabilistic multi-set mappings have been extended to evidential mappings, and Shafer’s partition technique is used to get the mass function in a complex evidence space. Then, a new graphic method for describing the knowledge is introduced which is an extension of the graphic model by Lowrance et al. Finally, an extended framework for evidential reasoning systems is specified.

Human figure segmentation using independent component analysis

In this paper, we present a Statistical Shape Model for Human Figure Segmentation in gait sequences. Point Distribution Models (PDM) generally use Principal Component analysis (PCA) to describe the main directions of variation in the training set. However, PCA assumes a number of restrictions on the data that do not always hold. In this work, we explore the potential of Independent Component Analysis (ICA) as an alternative shape decomposition to the PDM-based Human Figure Segmentation. The shape model obtained enables accurate estimation of human figures despite segmentation errors in the input silhouettes and has really good convergence qualities.

Robust face recognition with partial occlusion, illumination variation and limited training data by optimal feature selection

This study investigates face recognition with partial occlusion, illumination variation and their combination, assuming no prior information about the mismatch, and limited training data for each person. The authors extend their previous posterior union model (PUM) to give a new method capable of dealing with all these problems. PUM is an approach for selecting the optimal local image features for recognition to improve robustness to partial occlusion. The extension is in two stages. First, authors extend PUM from a probability-based formulation to a similarity-based formulation, so that it operates with as little as one single training sample to offer robustness to partial occlusion. Second, they extend this new formulation to make it robust to illumination variation, and to combined illumination variation and partial occlusion, by a novel combination of multicondition relighting and optimal feature selection. To evaluate the new methods, a number of databases with various simulated and realistic occlusion/illumination mismatches have been used. The results have demonstrated the improved robustness of the new methods.

Dense pixel matching between unrectified and distorted images using dynamic programming

In this paper, a novel framework for dense pixel matching based on dynamic programming is introduced. Unlike most techniques proposed in the literature, our approach assumes neither known camera geometry nor the availability of rectified images. Under such conditions, the matching task cannot be reduced to finding correspondences between a pair of scanlines. We propose to extend existing dynamic programming methodologies to a larger dimensional space by using a 3D scoring matrix so that correspondences between a line and a whole image can be calculated. After assessing our framework on a standard evaluation dataset of rectified stereo images, experiments are conducted on unrectified and non-linearly distorted images. Results validate our new approach and reveal the versatility of our algorithm.