Reimagining the General Health Questionnaire as a measure of emotional wellbeing: A study of postpartum women in Malta

Background: Postpartum health has been subject to a focus on psychological morbidity, despite positive associations between postpartum recovery and maternal emotional wellbeing. There are currently many validated tools to measure wellbeing and related concepts, including non-psychiatric morbidity. The General Health Questionnaire, 12 items (GHQ-12) is one such instrument, widely used and validated in several languages. Its use in postpartum settings has been documented with disagreement about the instrument's utility in this population, particularly in relation to scoring method and threshold. The GHQ-12 has never been translated into Maltese. This study explored the psychometric properties of the GHQ-12 in a Maltese postpartum population to consider if the use of a different scoring method (visual analogue scale) in the GHQ-12 can determine postpartum wellbeing. Methods: One hundred and twenty-four postpartum women recruited from one hospital in Malta completed the translated and adapted GHQ-12 as a wellbeing measure (GHQ-12(WB)) at four postpartum time points. The psychometric properties of the GHQ-12(WB) were explored using confirmatory factor analysis, discriminant and divergent validity and reliability analysis. Results: The GHQ-12(WB) demonstrated good divergent and known-groups validity and internal consistency. No models offered a good fit to the data. The overall consistent best-fit to the data was an eight item, two factor model (GHQ-8). Model fit improved across all models in terms of CFI at 13 weeks. Conclusion: Findings generally support the reliability and validity of the Maltese version of the GHQ-12(WB). Model fit changes over time reflect the dynamic nature of postpartum recovery. Further evaluation of the GHQ-8(WB) is recommended. © 2013 Australian College of Midwives

How linear features alter predator movement and the functional\ud response

In areas of oil and gas exploration, seismic lines have been reported to alter the movement patterns of wolves (Canis lupus). We developed a mechanistic first passage time model, based on an anisotropic elliptic partial differential equation, and used this to explore how wolf movement responses to seismic lines influence the encounter rate of the wolves with their prey. The model was parametrized using 5 min GPS location data. These data showed that wolves travelled faster on seismic lines and had a higher probability of staying on a seismic line once they were on it. We simulated wolf movement on a range of seismic line densities and drew implications for the rate of predator–prey interactions as described by the functional response. The functional response exhibited a more than linear increase with respect to prey density (type III) as well as interactions with seismic line density. Encounter rates were significantly higher in landscapes with high seismic line density and were most pronounced at low prey densities. This suggests that prey at low population densities are at higher risk in environments with a high seismic line density unless they learn to avoid them

What do older people learn from young people? : Intergenerational learning in ‘day centre’ community settings in Malta

This study analyses what motivates older people to attend ‘day centres’ in Malta and what they believe that they derive from young people who carry out their placements at these day ‘centres’ These young people, who are aged 16–17, attend a vocational college in Malta and are studying health and social care. The study is based on a qualitative approach and employs the usage of focus groups. The main findings are that the elderly see the students as helping them on an emotional level by giving them encouragement, and on a practical level, by offering them insights that help them in modern-day life

Salt forms of sulfadiazine with alkali metal and organic cations

The structures of four salt forms of sulfadiazine (SDH) with alkali metal cations are presented. Three contain the deprotonated SD anion. These are the discrete complex [Li(SD)(OH2)2], (I), and the coordination polymers [Na(SD)]n, (II), and [K(SD)(OH2)2]n, (III). The Na complex (II) is a three-dimensional coordination polymer whilst the K complex (III) has two crystallographically independent [K(SD)(OH2)2] units per asymmetric unit, Z′ = 2, and gives a two dimensional coordination polymer whose layers propagate parallel to the crystallographic ab plane. The different bonding modes of the SD anion in these three complexes is discussed. Structure (IV) contains protonated SDH2 cations and the Orange G (OG), C16H10N2O7S2, dianion in a structure with formula [SDH2]2[Na(OG)(OH2)4]2·3H2O. The [Na(OG)(OH2)4]2 dimers have antiparallel naphthol ring structures joined through two Na centres that bond to the hydrazone anions through the O atoms of the ketone and sulfonate substituents. The structures of the salts formed on reaction of SDH with 2-aminopyridine and ethanolamine are also presented as [C5H7N2][SD], (V), and [HOCH2CH2NH3][SD]·H2O, (VI), respectively. Structure (V) features a heterodimeric R2 2(8) hydrogen bond motif between the cation and the anion whilst structure (VI) has a tetrameric core of two cations linked by a central R2 2(10) hydrogen bonded motif which supports two anions linked to this core by R3 3(8) motifs

Three-dimensional CFD simulations with large displacement of the geometries using a connectivity-change moving mesh approach

This paper deals with three-dimensional (3D) numerical simulations involving 3D moving geometries with large displacements on unstructured meshes. Such simulations are of great value to industry, but remain very time-consuming. A robust moving mesh algorithm coupling an elasticity-like mesh deformation solution and mesh optimizations was proposed in previous works, which removes the need for global remeshing when performing large displacements. The optimizations, and in particular generalized edge/face swapping, preserve the initial quality of the mesh throughout the simulation. We propose to integrate an Arbitrary Lagrangian Eulerian compressible flow solver into this process to demonstrate its capabilities in a full CFD computation context. This solver relies on a local enforcement of the discrete geometric conservation law to preserve the order of accuracy of the time integration. The displacement of the geometries is either imposed, or driven by fluid–structure interaction (FSI). In the latter case, the six degrees of freedom approach for rigid bodies is considered. Finally, several 3D imposed-motion and FSI examples are given to validate the proposed approach, both in academic and industrial configurations

Differential evolution for the offline and online optimization of fed-batch fermentation processes

The optimization of input variables (typically feeding trajectories over time) in fed-batch fermentations has gained special attention, given the economic impact and the complexity of the problem. Evolutionary Computation (EC) has been a source of algorithms that have shown good performance in this task. In this chapter, Differential Evolution (DE) is proposed to tackle this problem and quite promising results are shown. DE is tested in several real world case studies and compared with other EC algorihtms, such as Evolutionary Algorithms and Particle Swarms. Furthermore, DE is also proposed as an alternative to perform online optimization, where the input variables are adjusted while the real fermentation process is ongoing. In this case, a changing landscape is optimized, therefore making the task of the algorithms more difficult. However, that fact does not impair the performance of the DE and confirms its good behaviour.(undefined

Neurobehavioral consequences of chronic intrauterine opioid exposure in infants and preschool children: a systematic review and meta-analysis

<b>Background</b><p></p> It is assumed within the accumulated literature that children born of pregnant opioid dependent mothers have impaired neurobehavioral function as a consequence of chronic intrauterine opioid use.<p></p> <b>Methods</b><p></p> Quantitative and systematic review of the literature on the consequences of chronic maternal opioid use during pregnancy on neurobehavioral function of children was conducted using the Meta-analysis of Observational Studies in Epidemiology (MOOSE) and the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. We searched Cinahl, EMBASE, PsychINFO and MEDLINE between the periods of January 1995 to January 2012.<p></p> <b>Results</b><p></p> There were only 5 studies out of the 200 identified that quantitatively reported on neurobehavioral function of children after maternal opioid use during pregnancy. All 5 were case control studies with the number of exposed subjects within the studies ranging from 33–143 and 45–85 for the controls. This meta-analysis showed no significant impairments, at a non-conservative significance level of p < 0.05, for cognitive, psychomotor or observed behavioural outcomes for chronic intra-uterine exposed infants and pre-school children compared to non-exposed infants and children. However, all domains suggested a trend to poor outcomes in infants/children of opioid using mothers. The magnitude of all possible effects was small according to Cohen’s benchmark criteria.<p></p> <b>Conclusions</b><p></p> Chronic intra-uterine opioid exposed infants and pre-school children experienced no significant impairment in neurobehavioral outcomes when compared to non-exposed peers, although in all domains there was a trend to poorer outcomes. The findings of this review are limited by the small number of studies analysed, the heterogenous populations and small numbers within the individual studies. Longitudinal studies are needed to determine if any neuropsychological impairments appear after the age of 5 years and to help investigate further the role of environmental risk factors on the effect of ‘core’ phenotypes

Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype.

BACKGROUND: MicroRNAs (miRNAs), a class of short non-coding RNAs found in many plants and animals, often act post-transcriptionally to inhibit gene expression. RESULTS: Here we report the analysis of miRNA expression in 93 primary human breast tumors, using a bead-based flow cytometric miRNA expression profiling method. Of 309 human miRNAs assayed, we identify 133 miRNAs expressed in human breast and breast tumors. We used mRNA expression profiling to classify the breast tumors as luminal A, luminal B, basal-like, HER2+ and normal-like. A number of miRNAs are differentially expressed between these molecular tumor subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumor subtypes in an independent data set. In some cases, changes in miRNA expression correlate with genomic loss or gain; in others, changes in miRNA expression are likely due to changes in primary transcription and or miRNA biogenesis. Finally, the expression of DICER1 and AGO2 is correlated with tumor subtype and may explain some of the changes in miRNA expression observed. CONCLUSION: This study represents the first integrated analysis of miRNA expression, mRNA expression and genomic changes in human breast cancer and may serve as a basis for functional studies of the role of miRNAs in the etiology of breast cancer. Furthermore, we demonstrate that bead-based flow cytometric miRNA expression profiling might be a suitable platform to classify breast cancer into prognostic molecular subtypes.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are