Enquiring about traumatic experiences in psychosis: A comparison of case notes and self-report questionnaires

Purpose: Studies have found an association between a history of trauma and the presence of psychotic symptoms. Despite the research evidence it appears to be the case that many clinicians are not routinely asking about traumatic experiences. This study aims to ascertain the level of agreement between rates of self-reported trauma and that which is recorded in case notes.

Methods: The study population was drawn from all individuals with a confirmed diagnosis of psychosis, residing within a defined catchment area. Rates of childhood trauma, lifetime trauma and trauma related to the Troubles in Northern Ireland recorded in participants’ case notes were compared to their responses on self-report questionnaires: THQ, CTQ and TREQ.

Results: Relatively high levels of trauma were reported by participants on the self-report measures that were administered. The rates of trauma recorded in case note records were similar to that found in other studies. Also in line with other research were poor levels of agreement between self-report and case note data.

Conclusion: High levels of lifetime, childhood and trauma related to the Troubles in Northern Ireland were found when the individuals in the sample were directly assessed for the purposes of this study. In contrast much lower rates were recorded in patient notes on routine clinical assessment. The results suggest that clinicians do not routinely enquire about trauma histories with this population and as a result, case notes underestimate trauma prevalence.

Infrared and Raman screening of seized novel psychoactive substances: A large scale study of >200 samples

The potential of IR absorption and Raman spectroscopy for rapid identification of novel psychoactive substances (NPS) has been tested using a set of 221 unsorted seized samples suspected of containing NPS. Both IR and Raman spectra showed large variation between the different sub-classifications of NPS and smaller, but still distinguishable, differences between closely related compounds within the same class. In initial tests, screening the samples using spectral searching against a limited reference library allowed only 41% of the samples to be fully identified. The limiting factor in the identification was the large number of active compounds in the seized samples for which no reference vibrational data were available in the libraries rather than poor spectral quality. Therefore, when 33 of these compounds were independently identified by NMR and mass spectrometry and their spectra used to extend the libraries, the percentage of samples identified by IR and Raman screening alone increased to 76%, with only 7% of samples having no identifiable constituents. This study, which is the largest of its type ever carried out, therefore demonstrates that this approach of detecting non-matching samples and then identifying them using standard analytical methods has considerable potential in NPS screening since it allows rapid identification of the constituents of the majority of street quality samples. Only one complete feedback cycle was carried out in this study but there is clearly the potential to carry out continuous identification/updating when this system is used in operational settings.

Slot width augmentation in a slotted-wall transonic linear cascade wind tunnel

Transonic tests in linear cascade wind tunnels can suffer
from significant test section boundary interference effects in pitch. A slotted tailboard has been designed and optimised with an in-house Euler numerical method to reduce such ef- fects. Wind tunnel measurements on an overspeed Mach 1.27 discharge from a Rolls-Royce T2 cascade, featuring strong end-wall shock-induced interference, showed a 77% reduction in the flow pitchwise periodicity error with the optimised tail- board, with respect to the baseline open-jet cascade flow. Two-dimensional Euler predictions were also cross-validated against a three-dimensional Reynolds averaged computation, to explore the three-dimensionality of the discharge

Statistical Tests for Joint Analysis of Performance Measures

Recently there has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and architectural complexity). Once one has learned a model based on their devised method, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Unfortunately, the standard tests used for this purpose are not able to jointly consider performance measures. The aim of this paper is to resolve this issue by developing statistical procedures that are able to account for multiple competing measures at the same time. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameter of such models, as usually the number of studied cases is very reduced in such comparisons. Real data from a comparison among general purpose classifiers is used to show a practical application of our tests.

60 Jahre Evangelische Fachhochschule Hannover : kleine Geschichte ihrer Vorgängereinrichtungen

Die Vorgängereinrichtungen der Evangelischen Fachhochschule Hannover. Hinweise zu ihrer Geschichte im Rahmen der Ausbildung für Sozialberufe.

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Micromorphology of the labellum and structure of the osmophore in a group of closely related species of the sexually deceptive Orchid genus Ophrys (orchidaceae)

Tese de doutoramento, Biologia (Biologia Celular), Universidade de Lisboa, Faculdade de Ciências, 2016

Image quality optimization, via application of contextual contrast sensitivity and discrimination functions

What is the best luminance contrast weighting-function for image quality optimization? Traditionally measured contrast sensitivity functions (CSFs), have been often used as weighting-functions in image quality and difference metrics. Such weightings have been shown to result in increased sharpness and perceived quality of test images. We suggest contextual CSFs (cCSFs) and contextual discrimination functions (cVPFs) should provide bases for further improvement, since these are directly measured from pictorial scenes, modeling threshold and suprathreshold sensitivities within the context of complex masking information. Image quality assessment is understood to require detection and discrimination of masked signals, making contextual sensitivity and discrimination functions directly relevant. In this investigation, test images are weighted with a traditional CSF, cCSF, cVPF and a constant function. Controlled mutations of these functions are also applied as weighting-functions, seeking the optimal spatial frequency band weighting for quality optimization. Image quality, sharpness and naturalness are then assessed in two-alternative forced-choice psychophysical tests. We show that maximal quality for our test images, results from cCSFs and cVPFs, mutated to boost contrast in the higher visible frequencies.

New insights into functional regulation in MS-based drug profiling

We present a novel data analysis strategy which combined with subcellular fractionation and liquid chromatography-mass spectrometry (LC-MS) based proteomics provides a simple and effective workflow for global drug profiling. Five subcellular fractions were obtained by differential centrifugation followed by high resolution LC-MS and complete functional regulation analysis. The methodology combines functional regulation and enrichment analysis into a single visual summary. The workflow enables improved insight into perturbations caused by drugs. We provide a statistical argument to demonstrate that even crude subcellular fractions leads to improved functional characterization. We demonstrate this data analysis strategy on data obtained in a MS-based global drug profiling study. However, this strategy can also be performed on other types of large scale biological data.