Distributed temperature sensor based on Brillouin loss in an optical fibre for transient threshold monitoring

A distributed temperature sensor for transient threshold monitoring with a 22 km sensing length, based on the Brillouin loss in standard communications fibre, is demonstrated. The system can be used for real-time monitoring of a preset temperature threshold. Good S/N ratios were achieved with only 8–16 sample averages giving a response time of 2 to 4 s with a temperature uncertainty of ±1 °C.

Distributed temperature sensor based on Brillouin loss in an optical fibre for transient threshold monitoring

A distributed temperature sensor for transient threshold monitoring with a 22 km sensing length, based on the Brillouin loss in standard communications fibre, is demonstrated. The system can be used for real-time monitoring of a preset temperature threshold. Good S/N ratios were achieved with only 8–16 sample averages giving a response time of 2 to 4 s with a temperature uncertainty of ±1 °C.

Toward prediction of class II mouse major histocompatibility complex peptide binding affinity:in silico bioinformatic evaluation using partial least squares, a robust multivariate statistical technique

The accurate identification of T-cell epitopes remains a principal goal of bioinformatics within immunology. As the immunogenicity of peptide epitopes is dependent on their binding to major histocompatibility complex (MHC) molecules, the prediction of binding affinity is a prerequisite to the reliable prediction of epitopes. The iterative self-consistent (ISC) partial-least-squares (PLS)-based additive method is a recently developed bioinformatic approach for predicting class II peptide−MHC binding affinity. The ISC−PLS method overcomes many of the conceptual difficulties inherent in the prediction of class II peptide−MHC affinity, such as the binding of a mixed population of peptide lengths due to the open-ended class II binding site. The method has applications in both the accurate prediction of class II epitopes and the manipulation of affinity for heteroclitic and competitor peptides. The method is applied here to six class II mouse alleles (I-Ab, I-Ad, I-Ak, I-As, I-Ed, and I-Ek) and included peptides up to 25 amino acids in length. A series of regression equations highlighting the quantitative contributions of individual amino acids at each peptide position was established. The initial model for each allele exhibited only moderate predictivity. Once the set of selected peptide subsequences had converged, the final models exhibited a satisfactory predictive power. Convergence was reached between the 4th and 17th iterations, and the leave-one-out cross-validation statistical terms - q2, SEP, and NC - ranged between 0.732 and 0.925, 0.418 and 0.816, and 1 and 6, respectively. The non-cross-validated statistical terms r2 and SEE ranged between 0.98 and 0.995 and 0.089 and 0.180, respectively. The peptides used in this study are available from the AntiJen database (http://www.jenner.ac.uk/AntiJen). The PLS method is available commercially in the SYBYL molecular modeling software package. The resulting models, which can be used for accurate T-cell epitope prediction, will be made freely available online (http://www.jenner.ac.uk/MHCPred).

Glasgow antipsychotic side-effects scale for Clozapine - development and validation of a clozapine-specific side-effects scale

OBJECTIVE: The authors developed and validated a clozapine-specific side-effects scale capable of eliciting the subjectively unpleasant side-effects of clozapine. METHODS: Questions from the original Glasgow Antipsychotic Side-effects Scale (GASS) were compared to a list of the most commonly reported clozapine side-effects and those with a significant subjective burden were included in the GASS for Clozapine (GASS-C). The original authors of the GASS and a group of mental health professionals from the UK and Ireland were enlisted to comment on the questions in the GASS-C based on their clinical experience. 110 clozapine outpatients from two sites completed the GASS-C, the original GASS and a repeat GASS-C. Statistical analyses were performed using SPSS for Windows version 19. RESULTS: The GASS-C was shown to have construct validity, in that Spearman's correlation coefficient was 0.816 (p<0.001) with the original GASS, whilst Cohen's kappa coefficient was >0.77 (p<0.001) for one question and >0.81 (p<0.001) for remaining relevant questions. GASS-C was also shown to have strong test-retest reliability, in that Cronbach's alpha coefficient was >0.907 (p<0.001), whilst Cohen's kappa coefficient was >0.81 (p<0.001) for 12 questions and >0.61 (p<0.001) for the remaining four questions. CONCLUSION: The GASS-C is a valid and reliable clinical tool to enable a systematic assessment of the subjectively unpleasant side-effects of clozapine. Future research should focus on how the scale can be utilised as a clinical tool to improve real-world outcomes such as adherence to clozapine therapy and quality of life.

Electronic information sharing in local government authorities:factors influencing the decision-making process

Local Government Authorities (LGAs) are mainly characterised as information-intensive organisations. To satisfy their information requirements, effective information sharing within and among LGAs is necessary. Nevertheless, the dilemma of Inter-Organisational Information Sharing (IOIS) has been regarded as an inevitable issue for the public sector. Despite a decade of active research and practice, the field lacks a comprehensive framework to examine the factors influencing Electronic Information Sharing (EIS) among LGAs. The research presented in this paper contributes towards resolving this problem by developing a conceptual framework of factors influencing EIS in Government-to-Government (G2G) collaboration. By presenting this model, we attempt to clarify that EIS in LGAs is affected by a combination of environmental, organisational, business process, and technological factors and that it should not be scrutinised merely from a technical perspective. To validate the conceptual rationale, multiple case study based research strategy was selected. From an analysis of the empirical data from two case organisations, this paper exemplifies the importance (i.e. prioritisation) of these factors in influencing EIS by utilising the Analytical Hierarchy Process (AHP) technique. The intent herein is to offer LGA decision-makers with a systematic decision-making process in realising the importance (i.e. from most important to least important) of EIS influential factors. This systematic process will also assist LGA decision-makers in better interpreting EIS and its underlying problems. The research reported herein should be of interest to both academics and practitioners who are involved in IOIS, in general, and collaborative e-Government, in particular. © 2013 Elsevier Ltd. All rights reserved.

Some extended psychological benefits of challenging social stereotypes:decreased dehumanization and a reduced reliance on heuristic thinking

One way to promote equality is to encourage people to generate counterstereotypic role models. In two experiments, we demonstrate that such interventions have much broader benefits than previously thoughtreducing a reliance on heuristic thinking and decreasing tendencies to dehumanize outgroups. In Experiment 1, participants who thought about a gender counterstereotype (e.g., a female mechanic) demonstrated a generalized decrease in dehumanization towards a range of unrelated target groups (including asylum seekers and the homeless). In Experiment 2 we replicated these findings using alternative targets and measures of dehumanization. Furthermore, we found the effect was mediated by a reduced reliance on heuristic thinking. The findings suggest educational initiatives that aim to challenge social stereotypes may not only have societal benefits (generalized tolerance), but also tangible benefits for individuals (enhanced cognitive flexibility).