Deconstructing national leadership: Politicians’ accounts of electoral success and failure in the Irish Lisbon Treaty referenda

The Self Categorization approach to national leadership proposes that leaders rhetorically construct national identity as essentialized and inevitable in order to consensualize and mobilize the population. In contrast, discursive studies have demonstrated how national politicians flexibly construct the nation to manage their own accountability in local interactions, though this in turn has neglected broader leadership processes. The present paper brings both approaches together to examine how and when national politicians construct versions of national identity in order to account for their failure as well as success in mobilizing the electorate. Eight semi-structured conversational style interviews were conducted with a strategic sample of eight leading Irish politicians on the subject of the 2008/2009 Irish Lisbon Treaty referenda. Using a Critical Discourse Psychology approach, the hegemonic repertoire of the ‘settled will’
of the informed and consensualized Irish nation was identified across all interviews. Politicians either endorsed the ‘settled will’ repertoire as evidence of their successful leadership, or rejected the repertoire by denying the rationality or unity of the populace to account for their failure. Our results suggest national identity is only constructed as essentialized and inevitable to the extent that it serves a strategic political purpose.

Characteristics and outcomes of haematology patients admitted to the intensive care unit

To profile the characteristics and outcomes of adult haematology patients admitted to the intensive care unit (ICU).

Predictors of PTSD Symptoms in Response to Psychosis and Psychiatric Admission

The experiences of psychosis and psychiatric admission have the potential to act as events precipitating posttraumatic stress disorder (PTSD) symptoms. Known risk factors for the development of PTSD symptoms in adults were identified. These included childhood trauma, current psychiatric symptoms, perceived coercion, and relationships with mental health service providers. These factors were analyzed to determine if they were important in the development of PTSD symptoms in response to psychosis and admission. We used a cross-sectional design with a sample of 47 participants recruited from a service in Northern Ireland who had experienced psychosis and been discharged from inpatient treatment within 12 months of data collection. The main outcome measure was the impact of events scale-revised. Data was subject to correlation analyses. A cut-off point of r = +/- 0.25 was used to select variables for inclusion in hierarchical regression analyses. Forty-five percent and 31% of the sample had moderate to severe PTSD symptoms related to psychosis and admission, respectively. The majority of participants identified positive symptoms and the first admission as the most distressing aspects of psychosis and admission. Childhood sexual and physical traumas were significant predictors of some PTSD symptoms. Strong association was found between current affective symptoms and PTSD symptoms. A reduced sense of availability of mental health service providers was also associated with PTSD symptoms and depression. Awareness of risk factors for the development of PTSD symptoms in response to admission and psychosis raises important issues for services and has implications for interventions provided.

Demonstrating the Transferability and the Descriptive Power of Sketch-Map

Increasingly, it is recognized that new automated forms of analysis are required to understand the high-dimensional output obtained from atomistic simulations. Recently, we introduced a new dimensionality reduction algorithm, sketch-map, that was designed specifically to work with data from molecular dynamics trajectories. In what follows, we provide more details on how this algorithm works and on how to set its parameters. We also test it on two well-studied Lennard-Jones clusters and show that the coordinates we extract using this algorithm are extremely robust. In particular, we demonstrate that the coordinates constructed for one particular Lennard-Jones cluster can be used to describe the configurations adopted by a second, different cluster and even to tell apart different phases of bulk Lennard-Jonesium.

Using sketch-map coordinates to analyze and bias molecular dynamics simulations

When examining complex problems, such as the folding of proteins, coarse grained descriptions of the system drive our investigation and help us to rationalize the results. Oftentimes collective variables (CVs), derived through some chemical intuition about the process of interest, serve this purpose. Because finding these CVs is the most difficult part of any investigation, we recently developed a dimensionality reduction algorithm, sketch-map, that can be used to build a low-dimensional map of a phase space of high-dimensionality. In this paper we discuss how these machine-generated CVs can be used to accelerate the exploration of phase space and to reconstruct free-energy landscapes. To do so, we develop a formalism in which high-dimensional configurations are no longer represented by low-dimensional position vectors. Instead, for each configuration we calculate a probability distribution, which has a domain that encompasses the entirety of the low-dimensional space. To construct a biasing potential, we exploit an analogy with metadynamics and use the trajectory to adaptively construct a repulsive, history-dependent bias from the distributions that correspond to the previously visited configurations. This potential forces the system to explore more of phase space by making it desirable to adopt configurations whose distributions do not overlap with the bias. We apply this algorithm to a small model protein and succeed in reproducing the free-energy surface that we obtain from a parallel tempering calculation.