Differentiating first episode substance induced and primary psychotic disorders with concurrent substance use in young people

Objective: Substance use is common in first-episode psychosis, and complicates the accurate diagnosis and treatment of the disorder. The differentiation of substance-induced psychotic disorders (SIPD) from primary psychotic disorders (PPD) is particularly challenging. This cross-sectional study compares the clinical, substance use and functional characteristics of substance using first episode psychosis patients diagnosed with a SIPD and PPD. Method: Participants were 61 young people (15-24 years) admitted to a psychiatric inpatient service with first episode psychosis, reporting substance use in the past month. Diagnosis was determined using the Psychiatric Research Interview for DSM-IV Substance and Mental disorders (PRISM-IV). Measures of clinical (severity of psychotic symptoms, level of insight, history of trauma), substance use (frequency/quantity, severity) and social and occupational functioning were also administered. Results: The PRISM-IV differentially diagnosed 56% of first episode patients with a SIPD and 44% with a PPD. Those with a SIPD had higher rates of substance use and disorders, higher levels of insight, were more likely to have a forensic and trauma history and had more severe hostility and anxious symptoms than those with a PPD. Logistic regression analysis indicated a family history of psychosis, trauma history and current cannabis dependence were the strongest predictors of a SIPD. Almost 80% of diagnostic predictions of a SIPD were accurate using this model. Conclusions: This clinical profile of SIPD could help to facilitate the accurate diagnosis and treatment of SIPD versus PPD in young people with first episode psychosis admitted to an inpatient psychiatric service.

Behaviour and design of cold-formed steel beams subject to lateral-torsional buckling at elevated temperatures

Cold-formed steel beams are increasingly used as floor joists and bearers in buildings and often their behaviour and moment capacities are influenced by lateral-torsional buckling. With increasing usage of cold-formed steel beams their fire safety design has become an important issue. Fire design rules are commonly based on past research on hot-rolled steel beams. Hence a detailed parametric study was undertaken using validated finite element models to investigate the lateral-torsional buckling behaviour of simply supported cold-formed steel lipped channel beams subjected to uniform bending at uniform elevated temperatures. The moment capacity results were compared with the predictions from the available ambient temperature and fire design rules and suitable recommendations were made. European fire design rules were found to be over-conservative while the ambient temperature design rules could not be used based on single buckling curve. Hence a new design method was proposed that includes the important non-linear stress-strain characteristics observed for cold-formed steels at elevated temperatures. Comparison with numerical moment capacities demonstrated the accuracy of the new design method. This paper presents the details of the parametric study, comparisons with current design rules and the new design rules proposed in this research for lateral-torsional buckling of cold-formed steel lipped channel beams at elevated temperatures.

Flexural-torsional buckling tests of cold-formed steel compression members at elevated temperatures

Current design standards do not provide adequate guidelines for the fire design of cold-formed steel compression members subject to flexural-torsional buckling. Eurocode 3 Part 1.2 (2005) recommends the same fire design guidelines for both hot-rolled and cold-formed steel compression members subject to flexural-torsional buckling although considerable behavioural differences exist between cold-formed and hot-rolled steel members. Past research has recommended the use of ambient temperature cold-formed steel design rules for the fire design of cold-formed steel compression members provided appropriately reduced mechanical properties are used at elevated temperatures. To assess the accuracy of flexural-torsional buckling design rules in both ambient temperature cold-formed steel design and fire design standards, an experimental study of slender cold-formed steel compression members was undertaken at both ambient and elevated temperatures. This paper presents the details of this experimental study, its results, and their comparison with the predictions from the current design rules. It was found that the current ambient temperature design rules are conservative while the fire design rules are overly conservative. Suitable recommendations have been made in relation to the currently available design rules for flexural-torsional buckling including methods of improvement. Most importantly, this paper has addressed the lack of experimental results for slender cold-formed steel columns at elevated temperatures.

Observed family interaction and outcome in patients with first-admission psychoses

Families of 52 first-admission patients diagnosed with a severe psychiatric disorder were videotaped interacting with the patient. Behavioral coding was used to derive several indices of interaction: base rates of positive and negative behavior by patients and relatives, cumulative affect of patients and relatives (the difference between the rates of positive and negative behaviors), and classification of families as affect-regulated or unregulated. Family-affect regulation reflects positive cumulative affect by both people in a given interaction. Six months after hospital discharge patients were assessed on occurrence of relapse, global functioning, severity of psychiatric symptoms, and quality of life. Relative to affect-unregulated family interaction, affect-regulated interaction predicted significantly fewer relapses, better global functioning, fewer positive and negative psychiatric symptoms, and higher patient quality of life. Most of the predictions by family-affect regulation were independent of

Carers' hope, wellbeing and attitudes regarding recovery

Carers are important to the recovery of their relatives with serious mental disorder however, it is unclear whether they are aware of, or endorse recent conceptualisations of recovery. This study compared carers’ and mental health workers’ recovery attitudes, and undertook multivariate predictions of carers’ wellbeing, hopefulness and recovery attitudes. Participants were 82 Australian family members caring for a relative with psychosis. Carers’ average recovery attitudes were less optimistic than for previously surveyed staff. Carers’ recovery attitudes were predicted by perceptions that their relative’s negative symptoms were more severe. Hopefulness and wellbeing was predicted by more positive and less negative caregiving experiences. Hopefulness was also predicted by less frequent contacts with their affected relative, and unexpectedly, by perceptions of more severe psychotic symptoms. Carers’ wellbeing was further predicted by having a partner and having no lifetime history of a mental disorder. Hope and wellbeing are affected by everyday challenges and positive experiences of caregiving.

Application of a digital elevation model for flood modeling for the Pagsangaan River in Leyte

Flood related scientific and community-based data are rarely systematically collected and analysed in the Philippines. Over the last decades the Pagsangaan River Basin, Leyte, has experienced several flood events. However, documentation describing flood characteristics such as extent, duration or height of these floods are close to non-existing. To address this issue, computerized flood modelling was used to reproduce past events where there was data available for at least partial calibration and validation. The model was also used to provide scenario-based predictions based on A1B climate change assumptions for the area. The most important input for flood modelling is a Digital Elevation Model (DEM) of the river basin. No accurate topographic maps or Light Detection And Ranging (LIDAR)-generated data are available for the Pagsangaan River. Therefore, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Map (GDEM), Version 1, was chosen as the DEM. Although the horizontal spatial resolution of 30 m is rather desirable, it contains substantial vertical errors. These were identified, different correction methods were tested and the resulting DEM was used for flood modelling. The above mentioned data were combined with cross-sections at various strategic locations of the river network, meteorological records, river water level, and current velocity to develop the 1D-2D flood model. SOBEK was used as modelling software to create different rainfall scenarios, including historic flooding events. Due to the lack of scientific data for the verification of the model quality, interviews with local stakeholders served as the gauge to judge the quality of the generated flood maps. According to interviewees, the model reflects reality more accurately than previously available flood maps. The resulting flood maps are now used by the operations centre of a local flood early warning system for warnings and evacuation alerts. Furthermore these maps can serve as a basis to identify flood hazard areas for spatial land use planning purposes.

Essential elements for recruitment and retention : Generation Y

Purpose: Generation Y (Gen Y) is the newest and largest generation entering the workforce. Gen Y may differ from previous generations in work-related characteristics which may have recruitment and retention repercussions. Currently, limited theoretically-based research exists regarding Gen Y’s work expectations and goals in relation to undergraduate students and graduates. Design/methodology/approach: This study conducted a theoretically-based investigation of the work expectations and goals of student- and working-Gen Y individuals based within a framework incorporating both expectancy-value and goal setting theories. N = 398 provided useable data via an on-line survey. Findings: Overall, some support was found for predictions with career goals loading on a separate component to daily work expectations and significant differences between student- and working- Gen Y on career goals. No significant differences were found, however, between the two groups in daily work expectations. Research limitations/implications: Future research may benefit from adopting a theoretical framework which assesses both daily work expectations and career goals when examining the factors which motivate Gen Y’s decisions to join and remain at a particular organisation. Practical implications: At a practical level, based on the findings, some examples are provided of the means by which organisations may draw upon daily work expectations and career goals of importance to Gen Y and, in doing so, influence the likelihood that a Gen Y individual will join and remain at their particular organisation. Originality/value: This research has demonstrated the utility of adopting a sound theoretical framework in furthering understanding about the motivations which influence organisations’ ability to recruit and retain Gen Y, among both student Gen Y as well as those Gen Y individuals who are already working.

Simulation of phosphine flow in vertical grain storage : a preliminary numerical study

To fumigate grain stored in a silo, phosphine gas is distributed by a combination of diffusion and fan-forced advection. This initial study of the problem mainly focuses on the advection, numerically modelled as fluid flow in a porous medium. We find satisfactory agreement between the flow predictions of two Computational Fluid Dynamics packages, Comsol and Fluent. The flow predictions demonstrate that the highest velocity (>0.1 m/s) occurs less than 0.2m from the inlet and reduces drastically over one metre of silo height, with the flow elsewhere less than 0.002 m/s or 1% of the velocity injection. The flow predictions are examined to identify silo regions where phosphine dosage levels are likely to be too low for effective grain fumigation.

Effect of attitudes, subjective norms and perceived control on nurses' intention to assess patients' pain

This study examines the underlying determinants of nurses' behaviour regarding the conduct of pain assessments. One hundred nurses in a variety of health care facilities were invited to complete an Attitude Intention Questionnaire based upon the theory of planned action which is an extension of the theory of reasoned action. Results provide some support for the theory of planned action, as nurses' intention to conduct pain assessment was shown to be predicted by attitude, subjective norms and perceived control, although the latter was the only variable to make an independent contribution to intention. Additional support for the importance of perceived control was provided by the analysis of 'intenders' and 'non-intenders' (to conduct pain assessments), as perceived control was the only variable which differed significantly between the groups. The findings are consistent with earlier studies which showed that the variables in the theory of planned behaviour provided reasonably accurate predictions of behavioural intention.

Asset health prediction using the explicit hazard model

The ability to estimate the asset reliability and the probability of failure is critical to reducing maintenance costs, operation downtime, and safety hazards. Predicting the survival time and the probability of failure in future time is an indispensable requirement in prognostics and asset health management. In traditional reliability models, the lifetime of an asset is estimated using failure event data, alone; however, statistically sufficient failure event data are often difficult to attain in real-life situations due to poor data management, effective preventive maintenance, and the small population of identical assets in use. Condition indicators and operating environment indicators are two types of covariate data that are normally obtained in addition to failure event and suspended data. These data contain significant information about the state and health of an asset. Condition indicators reflect the level of degradation of assets while operating environment indicators accelerate or decelerate the lifetime of assets. When these data are available, an alternative approach to the traditional reliability analysis is the modelling of condition indicators and operating environment indicators and their failure-generating mechanisms using a covariate-based hazard model. The literature review indicates that a number of covariate-based hazard models have been developed. All of these existing covariate-based hazard models were developed based on the principle theory of the Proportional Hazard Model (PHM). However, most of these models have not attracted much attention in the field of machinery prognostics. Moreover, due to the prominence of PHM, attempts at developing alternative models, to some extent, have been stifled, although a number of alternative models to PHM have been suggested. The existing covariate-based hazard models neglect to fully utilise three types of asset health information (including failure event data (i.e. observed and/or suspended), condition data, and operating environment data) into a model to have more effective hazard and reliability predictions. In addition, current research shows that condition indicators and operating environment indicators have different characteristics and they are non-homogeneous covariate data. Condition indicators act as response variables (or dependent variables) whereas operating environment indicators act as explanatory variables (or independent variables). However, these non-homogenous covariate data were modelled in the same way for hazard prediction in the existing covariate-based hazard models. The related and yet more imperative question is how both of these indicators should be effectively modelled and integrated into the covariate-based hazard model. This work presents a new approach for addressing the aforementioned challenges. The new covariate-based hazard model, which termed as Explicit Hazard Model (EHM), explicitly and effectively incorporates all three available asset health information into the modelling of hazard and reliability predictions and also drives the relationship between actual asset health and condition measurements as well as operating environment measurements. The theoretical development of the model and its parameter estimation method are demonstrated in this work. EHM assumes that the baseline hazard is a function of the both time and condition indicators. Condition indicators provide information about the health condition of an asset; therefore they update and reform the baseline hazard of EHM according to the health state of asset at given time t. Some examples of condition indicators are the vibration of rotating machinery, the level of metal particles in engine oil analysis, and wear in a component, to name but a few. Operating environment indicators in this model are failure accelerators and/or decelerators that are included in the covariate function of EHM and may increase or decrease the value of the hazard from the baseline hazard. These indicators caused by the environment in which an asset operates, and that have not been explicitly identified by the condition indicators (e.g. Loads, environmental stresses, and other dynamically changing environment factors). While the effects of operating environment indicators could be nought in EHM; condition indicators could emerge because these indicators are observed and measured as long as an asset is operational and survived. EHM has several advantages over the existing covariate-based hazard models. One is this model utilises three different sources of asset health data (i.e. population characteristics, condition indicators, and operating environment indicators) to effectively predict hazard and reliability. Another is that EHM explicitly investigates the relationship between condition and operating environment indicators associated with the hazard of an asset. Furthermore, the proportionality assumption, which most of the covariate-based hazard models suffer from it, does not exist in EHM. According to the sample size of failure/suspension times, EHM is extended into two forms: semi-parametric and non-parametric. The semi-parametric EHM assumes a specified lifetime distribution (i.e. Weibull distribution) in the form of the baseline hazard. However, for more industry applications, due to sparse failure event data of assets, the analysis of such data often involves complex distributional shapes about which little is known. Therefore, to avoid the restrictive assumption of the semi-parametric EHM about assuming a specified lifetime distribution for failure event histories, the non-parametric EHM, which is a distribution free model, has been developed. The development of EHM into two forms is another merit of the model. A case study was conducted using laboratory experiment data to validate the practicality of the both semi-parametric and non-parametric EHMs. The performance of the newly-developed models is appraised using the comparison amongst the estimated results of these models and the other existing covariate-based hazard models. The comparison results demonstrated that both the semi-parametric and non-parametric EHMs outperform the existing covariate-based hazard models. Future research directions regarding to the new parameter estimation method in the case of time-dependent effects of covariates and missing data, application of EHM in both repairable and non-repairable systems using field data, and a decision support model in which linked to the estimated reliability results, are also identified.

Quantifying the roles of cell motility and cell proliferation in a circular barrier assay

Moving fronts of cells are essential features of embryonic development, wound repair and cancer metastasis. This paper describes a set of experiments to investigate the roles of random motility and proliferation in driving the spread of an initially confined cell population. The experiments include an analysis of cell spreading when proliferation was inhibited. Our data have been analysed using two mathematical models: a lattice-based discrete model and a related continuum partial differential equation model. We obtain independent estimates of the random motility parameter, D, and the intrinsic proliferation rate, λ, and we confirm that these estimates lead to accurate modelling predictions of the position of the leading edge of the moving front as well as the evolution of the cell density profiles. Previous work suggests that systems with a high λ/D ratio will be characterized by steep fronts, whereas systems with a low λ/D ratio will lead to shallow diffuse fronts and this is confirmed in the present study. Our results provide evidence that continuum models, based on the Fisher–Kolmogorov equation, are a reliable platform upon which we can interpret and predict such experimental observations.

Growth of confined cancer spheroids : a combined experimental marker, critical modelling approach

A critical step in the dissemination of ovarian cancer is the formation of multicellular spheroids from cells shed from the primary tumour. The objectives of this study were to apply bioengineered three-dimensional (3D) microenvironments for culturing ovarian cancer spheroids in vitro and simultaneously to build on a mathematical model describing the growth of multicellular spheroids in these biomimetic matrices. Cancer cells derived from human epithelial ovarian carcinoma were embedded within biomimetic hydrogels of varying stiffness and grown for up to 4 weeks. Immunohistochemistry, imaging and growth analyses were used to quantify the dependence of cell proliferation and apoptosis on matrix stiffness, long-term culture and treatment with the anti-cancer drug paclitaxel. The mathematical model was formulated as a free boundary problem in which each spheroid was treated as an incompressible porous medium. The functional forms used to describe the rates of cell proliferation and apoptosis were motivated by the experimental work and predictions of the mathematical model compared with the experimental output. This work aimed to establish whether it is possible to simulate solid tumour growth on the basis of data on spheroid size, cell proliferation and cell death within these spheroids. The mathematical model predictions were in agreement with the experimental data set and simulated how the growth of cancer spheroids was influenced by mechanical and biochemical stimuli including matrix stiffness, culture duration and administration of a chemotherapeutic drug. Our computational model provides new perspectives on experimental results and has informed the design of new 3D studies of chemoresistance of multicellular cancer spheroids.

Business research in virtual worlds : possibilities and practicalities

Purpose – It is predicted that virtual business and related research possibilities will expand significantly. In this context, the aim of this paper is to use insights from a virtual research project to present a theoretically-informed toolbox of practical suggestions to guide the conduct of virtual world business research. Design/methodology/approach – Archival evidence is presented, and data from a study conducted in Second Lifew in 2007 is interpreted through Llewellyn’s framework (physical, structural, agential, cultural and mental dimensions). Findings – With the burgeoning of virtual business applications, appropriate systems that encompass the dynamics of both the real and the virtual will need to be developed by and for accountants, auditors and business professionals. Researchers of virtual business activities will need to adapt to the physical, structural, agential, cultural and mental dimensions unique to virtual worlds. Research limitations/implications – While based on reflections from a single study in Second Life, this paper identifies possibilities for future virtual research on issues of accountability and accounting relating to virtual worlds. Practical implications – The practical toolbox will assist virtual researchers to deal with the possibilities and practicalities of conducting research in virtual worlds. Originality/value – Despite the proliferation of virtual worlds, predictions of virtual business applications, and consequent accountability and accounting implications, there is a paucity of academic literature on conducting business research in virtual settings. This prescient paper develops a conceptual framework to guide the conduct of research in virtual worlds, and identifies the unique opportunities and challenges they present.

Prediction of multilocus identity-by-descent

Previous studies have enabled exact prediction of probabilities of identity-by-descent (IBD) in randommating populations for a few loci (up to four or so), with extension to more using approximate regression methods. Here we present a precise predictor of multiple-locus IBD using simple formulas based on exact results for two loci. In particular, the probability of non-IBD X ABC at each of ordered loci A, B, and C can be well approximated by XABC = XABXBC/XB and generalizes to X123. . .k = X12X23. . .Xk-1,k/ Xk-2, where X is the probability of non-IBD at each locus. Predictions from this chain rule are very precise with population bottlenecks and migration, but are rather poorer in the presence of mutation. From these coefficients, the probabilities of multilocus IBD and non-IBD can also be computed for genomic regions as functions of population size, time, and map distances. An approximate but simple recurrence formula is also developed, which generally is less accurate than the chain rule but is more robust with mutation. Used together with the chain rule it leads to explicit equations for non-IBD in a region. The results can be applied to detection of quantitative trait loci (QTL) by computing the probability of IBD at candidate loci in terms of identity-by-state at neighboring markers.

On the prediction of simultaneous inbreeding coefficients at multiple loci

A new deterministic method for predicting simultaneous inbreeding coefficients at three and four loci is presented. The method involves calculating the conditional probability of IBD (identical by descent) at one locus given IBD at other loci, and multiplying this probability by the prior probability of the latter loci being simultaneously IBD. The conditional probability is obtained applying a novel regression model, and the prior probability from the theory of digenic measures of Weir and Cockerham. The model was validated for a finite monoecious population mating at random, with a constant effective population size, and with or without selfing, and also for an infinite population with a constant intermediate proportion of selfing. We assumed discrete generations. Deterministic predictions were very accurate when compared with simulation results, and robust to alternative forms of implementation. These simultaneous inbreeding coefficients were more sensitive to changes in effective population size than in marker spacing. Extensions to predict simultaneous inbreeding coefficients at more than four loci are now possible.