Social categorizations, social comparisons and stigma: Presentations of self in people with learning difficulties

Self-categorization theory stresses the importance of the context in which the metacontrast principle is proposed to operate. This study is concerned with how 'the pool of psychologically relevant stimuli' (Turner, Hogg, Oakes, Reicher & Wetherell, 1987, p. 47) comprising the context is determined. Data from interviews with 33 people with learning difficulties were used to show how a positive sense of self might be constructed by members of a stigmatized social category through the social worlds that they describe, and therefore the social comparisons and categorizations that are made possible. Participants made downward comparisons which focused on people with learning difficulties who were less able or who displayed challenging behaviour, and with people who did not have learning difficulties but who, according to the participants, behaved badly, such as beggars, drunks and thieves. By selection of dimensions and comparison others, a positive sense of self and a particular set of social categorizations were presented. It is suggested that when using self-categorization theory to study real-world social categories, more attention needs to be paid to the involvement of the perceiver in determining which stimuli are psychologically relevant since this is a crucial determinant of category salience.

Imitating micelles as a way to control coordination self-assembly: cage-polymer switching directed rationally by solvent polarity or pH

Disguising a metal complex as a micelle by using amphiphilic phosphine ligands enables it to switch between a coordination polymer and a discrete cage in response to solvent polarity or pH; this medium-dependent behaviour of the complex is rational because it parallels that of true micelles.

Directed self-assembly of nanorod networks: bringing the top down to the bottom up

Self-assembled electrodeposited nanorod materials have been shown to offer an exciting landscape for a wide array of research ranging from nanophotonics through to biosening and magnetics. However, until now, the scope for site-specific preparation of the nanorods on wafers is limited to local area definition. Further there is little or no lateral control of nanorod height. In this work we present a scalable method for controlling the growth of the nanorods in the vertical direction as well as their lateral position. A focused ion beam (FIB) pre-patterns the Au cathode layer prior to the creation of the Anodized Aluminium Oxide (AAO) template on top. When the pre-patterning is of the same dimension to the pore spacing of the AAO template, lines of single nanorods are successfully grown. Further, for sub-200 nm wide features a relationship between the nanorod height and distance from non-patterned cathode can be seen to follow a quadratic growth rate obeying Faradays law of electrodeposition. This facilitates lateral control of nanorod height combined with localised growth of the nanorods.

A self-learning algorithm for biased molecular dynamics

A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally valid collective coordinates. These collective coordinates are obtained from trajectory analyses so that they adapt to any new features encountered during the simulation. We show how this methodology can be used to enhance sampling in real chemical systems citing examples both from the physics of clusters and from the biological sciences.

A self-learning teaching-learning based optimization for dynamic economic/environmental dispatch considering multiple plug-in electric vehicle loads

Economic and environmental load dispatch aims to determine the amount of electricity generated from power plants to meet load demand while minimizing fossil fuel costs and air pollution emissions subject to operational and licensing requirements. These two scheduling problems are commonly formulated with non-smooth cost functions respectively considering various effects and constraints, such as the valve point effect, power balance and ramp rate limits. The expected increase in plug-in electric vehicles is likely to see a significant impact on the power system due to high charging power consumption and significant uncertainty in charging times. In this paper, multiple electric vehicle charging profiles are comparatively integrated into a 24-hour load demand in an economic and environment dispatch model. Self-learning teaching-learning based optimization (TLBO) is employed to solve the non-convex non-linear dispatch problems. Numerical results on well-known benchmark functions, as well as test systems with different scales of generation units show the significance of the new scheduling method.

A new self-learning TLBO algorithm for RBF neural modelling of batteries in electric vehicles

One of the main purposes of building a battery model is for monitoring and control during battery charging/discharging as well as for estimating key factors of batteries such as the state of charge for electric vehicles. However, the model based on the electrochemical reactions within the batteries is highly complex and difficult to compute using conventional approaches. Radial basis function (RBF) neural networks have been widely used to model complex systems for estimation and control purpose, while the optimization of both the linear and non-linear parameters in the RBF model remains a key issue. A recently proposed meta-heuristic algorithm named Teaching-Learning-Based Optimization (TLBO) is free of presetting algorithm parameters and performs well in non-linear optimization. In this paper, a novel self-learning TLBO based RBF model is proposed for modelling electric vehicle batteries using RBF neural networks. The modelling approach has been applied to two battery testing data sets and compared with some other RBF based battery models, the training and validation results confirm the efficacy of the proposed method.

Directed Selection using Reinforcement Learning for the Examination Timetabling Problem

Traditional heuristic approaches to the Examination Timetabling Problem normally utilize a stochastic method during Optimization for the selection of the next examination to be considered for timetabling within the neighbourhood search process. This paper presents a technique whereby the stochastic method has been augmented with information from a weighted list gathered during the initial adaptive construction phase, with the purpose of intelligently directing examination selection. In addition, a Reinforcement Learning technique has been adapted to identify the most effective portions of the weighted list in terms of facilitating the greatest potential for overall solution improvement. The technique is tested against the 2007 International Timetabling Competition datasets with solutions generated within a time frame specified by the competition organizers. The results generated are better than those of the competition winner in seven of the twelve examinations, while being competitive for the remaining five examinations. This paper also shows experimentally how using reinforcement learning has improved upon our previous technique.

The impact of nurse-directed protocolised-weaning from mechanical ventilation on nursing practice: A quasi-experimental study

Background:
Internationally, nurse-directed protocolised-weaning has been evaluated by measuring its impact on patient outcomes. The impact on nurses’ views and perceptions has been largely ignored.

Aim:
To determine the change in intensive care nurses’ perceptions, satisfaction, knowledge and attitudes following the introduction of nurse-directed weaning. Additionally, views were obtained on how useful protocolised-weaning was to practice.

Methods:
The sample comprised nurses working in general intensive care units in three university-affiliated hospitals. Nurse-directed protocolised-weaning was implemented in one unit (intervention group); two ICUs continued with usual doctor-led practice (control group). Nurses’ perceptions, satisfaction, knowledge and attitudes were measured by self-completed questionnaires before (Phase I) and after the implementation of nurse-directed weaning (Phase II) in all units.

Results:
Response rates were 79% (n=140n=140) for Phase 1 and 62% (n=132n=132) for Phase II. Regression-based analyses showed that changes from Phase I to Phase II were not significantly different between the intervention and control groups. Sixty-nine nurses responded to both Phase I and II questionnaires. In the intervention group, these nurses scored their mean perceived level of knowledge higher in Phase II (6.39 vs 7.17, p=0.01p=0.01). In the control group, role perception (4.41 vs 4.22, p=0.01p=0.01) was lower and, perceived knowledge (6.03 vs 6.63, p=0.04p=0.04), awareness of weaning plans (6.09 vs 7.06, p=0.01p=0.01) and satisfaction with communication (5.28 vs 6.19, p=0.01p=0.01) were higher in Phase II. The intervention group found protocolised weaning useful in their practice (75%): this was scored significantly higher by junior and senior nurses than middle grade nurses (p=0.02p=0.02).

Conclusion

We conclude that nurse-directed protocolised-weaning had no effect on nurses’ views and perceptions due to the high level of satisfaction which encouraged nurses’ participation in weaning throughout. Control group changes are attributed to a ‘reactive effect’ from being study participants. Weaning protocols provide a uniform method of weaning practice and are particularly beneficial in providing safe guidance for junior staff.

Organisational Self-Evaluation and Teacher Education for Community Relations in a Transforming Society?

During 2004, the School of Education at the University of Ulster embarked on an innovative three-year project designed to embed community relations objectives within initial teacher education. With the advent of more peaceful times in Northern Ireland, this was a precipitous time for initial teacher educators to review the preparation given to beginner teachers for teaching in an increasingly pluralist society emerging from conflict. The present paper reports on one very specific and time-limited element of the broader project. That is, development work designed to investigate the possibilities of using processes of self-review and evaluation as a lever for improvements in initial teacher education for community relations. Following a brief contextualisation, the background to, and the development of, a set of materials designed to support rigorous and systematic self-review of all aspects of provision in a university-based initial teacher education department is described. The Community Relations Index for Initial Teacher Education (Cr-ITE) was envisaged as being of use to initial teacher education establishments in order to help teacher educators take responsibility for rigorous learning from their practice, whilst placing inclusive values at the centre of organisational development. The final section includes further critical reflection on the role of organisational self-review in transforming teacher education for inclusion in a society emerging from longstanding communal conflict.

The mental health needs of people with a learning disability detained in police custody

Few research studies examine the prevalence or mental health needs of people with a Learning Disability (LD) detained in police custody. This paper describes the population of detainees with an LD who presented to an inner city inter-agency police liaison service during a three-year period. Two forensically trained Community Mental Health Nurses (CMHNs) screened all custody record forms (n=9014) for evidence of a mental health problem or LD. The CMHNs interviewed positively screened detainees (n=1089) using a battery of measures designed to assess mental health status, risk-related behaviour and alcohol or drug abuse. Almost one-in-ten of those interviewed (95/1089) were judged to have a possible or definite LD. Fifty-two per cent were cases on the General Health Questionnaire (GHQ) whilst 61% attained 'above threshold' Brief Psychiatric Rating Scale (BPRS) scores. The majority (63%) had a history of causing harm to others while 56 per cent had a history of self-harm. More than half (56%) regularly consumed harmful levels of alcohol while one-in-four (27%) reported abusing drugs. Higher than expected numbers of detainees have a learning disability and most have complex mental health needs. A police liaison service offers a way of identifying people with LD and connecting them with appropriate health and social care agencies.