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

Fully-automated identification of imaging biomarkers for post-operative cerebellar mutism syndrome using longitudinal paediatric MRI

Post-operative cerebellar mutism syndrome (POPCMS) in children is a post- surgical complication which occurs following the resection of tumors within the brain stem and cerebellum. High resolution brain magnetic resonance (MR) images acquired at multiple time points across a patient’s treatment allow the quantification of localized changes caused by the progression of this syndrome. However, MR images are not necessarily acquired at regular intervals throughout treatment and are often not volumetric. This restricts the analysis to 2D space and causes difficulty in intra- and inter-subject comparison. To address these challenges, we have developed an automated image processing and analysis pipeline. Multi-slice 2D MR image slices are interpolated in space and time to produce a 4D volumetric MR image dataset providing a longitudinal representation of the cerebellum and brain stem at specific time points across treatment. The deformations within the brain over time are represented using a novel metric known as the Jacobian of deformations determinant. This metric, together with the changing grey-level intensity of areas within the brain over time, are analyzed using machine learning techniques in order to identify biomarkers that correspond with the development of POPCMS following tumor resection. This study makes use of a fully automated approach which is not hypothesis-driven. As a result, we were able to automatically detect six potential biomarkers that are related to the development of POPCMS following tumor resection in the posterior fossa

A simple, efficient, mass-conservative approach to solving Richards' equation (openRE, v1.0)

A simple numerical solution procedure – namely the method of lines combined with an off-the-shelf ordinary differential equation (ODE) solver – was shown in previous work to provide efficient, mass-conservative solutions to the pressure-head form of Richards' equation. We implement such a solution in our model openRE. We developed a novel method to quantify the boundary fluxes that reduce water balance errors without negative impacts on model runtimes – the solver flux output method (SFOM). We compare this solution with alternatives, including the classic modified Picard iteration method and the Hydrus 1D model. We reproduce a set of benchmark solutions with all models. We find that Celia's solution has the best water balance, but it can incur significant truncation errors in the simulated boundary fluxes, depending on the time steps used. Our solution has comparable runtimes to Hydrus and better water balance performance (though both models have excellent water balance closure for all the problems we considered). Our solution can be implemented in an interpreted language, such as MATLAB or Python, making use of off-the-shelf ODE solvers. We evaluated alternative SciPy ODE solvers that are available in Python and make practical recommendations about the best way to implement them for Richards' equation. There are two advantages of our approach: (i) the code is concise, making it ideal for teaching purposes; and (ii) the method can be easily extended to represent alternative properties (e.g., novel ways to parameterize the K(ψ) relationship) and processes (e.g., it is straightforward to couple heat or solute transport), making it ideal for testing alternative hypotheses

Analysis of periosteal lesions from commingled human remains at the Xagħra Circle hypogeum reveals the first case of probable scurvy from Neolithic Malta

Abstract Objectives Palaeopathological analysis is key for characterising population health at the individual level and across large assemblages but is rarely exploited to unite the remains of disarticulated individuals. This study explores the potential for individual identification through differential diagnosis of periosteal lesions in a commingled deposit, both to ascertain the number of individuals represented and provide a differential diagnosis. Materials and Methods The late Neolithic Xag?ra Circle hypogeum on Gozo contains the remains of more than 800 individuals, most of which were transformed to a collective disarticulated assemblage. Across the excavated population, pathological observations are strikingly low. In one specific 1???1-m area in a single stratigraphic context, fragmented and disarticulated cranial and post-cranial non-adult bones were identified that displayed periosteal new bone formation. To aid differential diagnosis, macroscopic analysis, taphonomic analysis and micro-computed tomography (?CT) imaging were integrated. Results This approach, when combined with osteobiographical analyses, reveals that the elements most likely derive from one individual, a young child, who presents a probable case of scurvy. The potential for micronutrient co-morbidities are explored, but without further microscopic study it cannot be determined if this individual also experienced iron-deficiency anaemia and/or rickets. Discussion In the context of the Mediterranean and Europe in later prehistory, reported cases of scurvy are currently low and often reveal periods of environmental instability and resource insufficiency. Our finding of non-adult scurvy in late 3rd millennium BC Malta contributes to a developing picture of an increasingly unstable palaeoenvironment and declining population health at this time, although it may also indicate an individual case of poor childhood health within this broader context.1 Introduction 1.1 Archaeological context of the Xagħra Circle hypogeum 2 Materials and methods 2.1 Remains presenting periosteal lesions 2.2 Macroscopic and micro-CT analysis 3 Macroscopic and radiological observations of pathology 3.1 Frontal bone (FB0039, FB0040) and zygoma (FB0041) 3.2 Mandible (FB0042) 3.3 Left rib (FB0043) and right rib (FB0044) 3.4 Ulna (FB0045) 4 Differential diagnosis 4.1 Frontal bone (FB0039, FB0040) and zygoma (FB0041) 4.2 Mandible (FB0042) 4.3 Left rib (FB0043) and right rib (FB0044) 4.4 Ulna (FB0045) 5 Discussion 5.1 Scurvy: Causes, consequences and comorbidities 5.2 Scurvy in prehistory 5.3 The Maltese context 6 Conclusio

Elucidation of critical pH-dependent structural changes in Botulinum Neurotoxin E

Botulinum Neurotoxins (BoNT) are the most potent toxins currently known. However, they also have therapeutic applications for an increasing number of motor related conditions due to their specificity, and low diffusion into the system. Although the start- and end- points for the BoNT mechanism of action are well-studied, a critical step remains poorly understood. It is theorised that BoNTs undergo a pH-triggered conformational shift, activating the neurotoxin by priming it to form a transmembrane (TM) channel. To test this hypothesis, we combined molecular dynamic (MD) simulations and small-angle x-ray scattering (SAXS), revealing a new conformation of BoNT/E. This conformation was exclusively observed in simulations below pH 5.5, as determined by principal component analysis (PCA), and its theoretical SAXS profile matched an experimental SAXS profile obtained at pH 4. Additionally, a localised secondary structural change was observed in MD simulations below pH 5.5, in a region previously identified as instrumental for membrane insertion for BoNT/A. These changes were found at a critical pH value for BoNTs in vivo, and may be relevant for their therapeutic use

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