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Visual representation of product architecture models is crucial in complex engineering systems design. However, when the number of entities in a model is large and when multiple levels of hierarchies are included, visual representations currently in use need to be more intuitive. As such, improved visual representations that enable better system overview and better communication of essential product- related information among design participants are needed. This paper uses interactive information visualisation techniques – collapsible hierarchical tree, edge bundling and alluvial diagram – and provides the foundations of a computerised tool that improves the traceability of connections between design domains, including stakeholders, requirements, functions, behaviours and structure. The case of a cleaning robot is used as an illustrative example. The approach supports designers by providing an enhanced overview during the development of complex product architecture models, in particular in the communication with external stakeholders, in the identification of change propagation paths across several design domains, and in capturing the design rationale of previous design decisions.
An ageing population leading to more chronic disease is straining healthcare systems. This paper makes two core contributions to healthcare systems design research: Firstly, a systemic techno-behavioural approach is presented to support intervention design with value-effective health outcomes. The systemic techno-behavioural perspective takes into consideration the interaction between three angles: The current healthcare system in place, the technological opportunities for addressing an issue and a broader and deeper understanding of the behaviour of those involved. The purpose of considering these three angels is to create interventions that are more robust. This will help inform healthcare systems design researchers and other stakeholders. Secondly, it is proposed that interventions should be grounded in behavioural theory, a collection of theories are presented to be incorporated in the design process of interventions. The systemic techno-behavioural approach is applied to dementia care highlighting the need to understand the dynamic relationship between the context of the current healthcare delivery system, technology, and behaviour to improve quality of care during the progression of the disease.
The availability of genome-wide genetic data on hundreds of thousands of people has led to an equally rapid growth in methodologies available to analyse these data. While the motivation for undertaking genome-wide association studies (GWAS) is identification of genetic markers associated with complex traits, once generated these data can be used for many other analyses. GWAS have demonstrated that complex traits exhibit a highly polygenic genetic architecture, often with shared genetic risk factors across traits. New methods to analyse data from GWAS are increasingly being used to address a diverse set of questions about the aetiology of complex traits and diseases, including psychiatric disorders. Here, we give an overview of some of these methods and present examples of how they have contributed to our understanding of psychiatric disorders. We consider: (i) estimation of the extent of genetic influence on traits, (ii) uncovering of shared genetic control between traits, (iii) predictions of genetic risk for individuals, (iv) uncovering of causal relationships between traits, (v) identifying causal single-nucleotide polymorphisms and genes or (vi) the detection of genetic heterogeneity. This classification helps organise the large number of recently developed methods, although some could be placed in more than one category. While some methods require GWAS data on individual people, others simply use GWAS summary statistics data, allowing novel well-powered analyses to be conducted at a low computational burden.
Depression and obesity are highly prevalent, and major impacts on public health frequently co-occur. Recently, we reported that having depression moderates the effect of the FTO gene, suggesting its implication in the association between depression and obesity.
To confirm these findings by investigating the FTO polymorphism rs9939609 in new cohorts, and subsequently in a meta-analysis.
The sample consists of 6902 individuals with depression and 6799 controls from three replication cohorts and two original discovery cohorts. Linear regression models were performed to test for association between rs9939609 and body mass index (BMI), and for the interaction between rs9939609 and depression status for an effect on BMI. Fixed and random effects meta-analyses were performed using METASOFT.
In the replication cohorts, we observed a significant interaction between FTO, BMI and depression with fixed effects meta-analysis (β=0.12, P = 2.7 × 10−4) and with the Han/Eskin random effects method (P = 1.4 × 10−7) but not with traditional random effects (β = 0.1, P = 0.35). When combined with the discovery cohorts, random effects meta-analysis also supports the interaction (β = 0.12, P = 0.027) being highly significant based on the Han/Eskin model (P = 6.9 × 10−8). On average, carriers of the risk allele who have depression have a 2.2% higher BMI for each risk allele, over and above the main effect of FTO.
This meta-analysis provides additional support for a significant interaction between FTO, depression and BMI, indicating that depression increases the effect of FTO on BMI. The findings provide a useful starting point in understanding the biological mechanism involved in the association between obesity and depression.
In many engineering design contexts models are indispensable. They offer decision support and help tackle complex and interconnected design projects, capturing the underlying structure of development processes or resulting products. Because managers and engineers base many decisions on models, it is crucial to understand their properties and how these might influence their behaviour. The level of detail, or granularity, of a model is a key attribute that results from how reality is abstracted in the modelling process. Despite the direct impact granularity has on the use of a model, the general topic has so far only received limited attention and is therefore not well understood or documented. This article provides background on model theory, explores relevant terminology from a range of fields and discusses the implications for engineering design. Based on this, a classification framework is synthesised, which outlines the main manifestations of model granularity. This research contributes to theory by scrutinising the nature of model granularity. It also illustrates how this may manifest in engineering design models, using Design Structure Matrices as an example, and discusses associated challenges to provide a resource for modellers navigating decisions regarding granularity.
Models of products and design processes are key to interacting with engineering designs and managing the processes by which they are developed. In practice, companies maintain networks of many interrelated models which need to be synthesised in the minds of their users when considering issues that cut across them. This article considers how information from product and design process models can be integrated with a view to help manage these complex interrelationships. A framework highlighting key issues surrounding model integration is introduced and terminology for describing these issues is developed. To illustrate the framework and terminology, selected modelling approaches that integrate product and process information are discussed and organised according to their levels and forms of integration. Opportunities for further work to advance integrated modelling in engineering design research and practice are discussed.
Health nudge interventions to steer people into healthier lifestyles are increasingly applied by governments worldwide, and it is natural to look to such approaches to improve health by altering what people choose to eat. However, to produce policy recommendations that are likely to be effective, we need to be able to make valid predictions about the consequences of proposed interventions, and for this, we need a better understanding of the determinants of food choice. These determinants include dietary components (e.g. highly palatable foods and alcohol), but also diverse cultural and social pressures, cognitive-affective factors (perceived stress, health attitude, anxiety and depression), and familial, genetic and epigenetic influences on personality characteristics. In addition, our choices are influenced by an array of physiological mechanisms, including signals to the brain from the gastrointestinal tract and adipose tissue, which affect not only our hunger and satiety but also our motivation to eat particular nutrients, and the reward we experience from eating. Thus, to develop the evidence base necessary for effective policies, we need to build bridges across different levels of knowledge and understanding. This requires experimental models that can fill in the gaps in our understanding that are needed to inform policy, translational models that connect mechanistic understanding from laboratory studies to the real life human condition, and formal models that encapsulate scientific knowledge from diverse disciplines, and which embed understanding in a way that enables policy-relevant predictions to be made. Here we review recent developments in these areas.
Following the surface application of granulated urea to grassland, high ammonia (NH3) losses of up to 30% have been reported. The addition of a urease inhibitor (UI) to urea granules could be a way to abate these losses. Field experiments were conducted at two intensive grassland sites in 2007 and 2008 to evaluate the potential of the new UI N-(2-nitrophenyl) phosphoric triamide (2-NPT; concentrations of 0·75, 1·0 and 1·5 g N/kg) to reduce NH3 emissions resulting from the application of granulated urea. Ammonia losses were continuously measured on plots fertilized with urea, urea + 2-NPT, calcium ammonium nitrate and a control (0N). The measurements were made with a dynamic chamber system. All measurement periods were started after a period of precipitation with a following rainless period being forecasted. Results over measurement periods of 10 days following fertilization are presented. Ammonia losses following the application of granulated urea varied between 4·6 and 11·8 kg N/ha, corresponding to 4·2 up to 14·0% of the applied nitrogen. The addition of 2-NPT to urea granules at three concentrations significantly reduced NH3 losses by 69–100%. Comparable losses of NH3 were observed for urea containing the UI 2-NPT as well as calcium ammonium nitrate, and were not significantly different from the control treatment. No relationships between losses, meteorological factors and soil moisture were observed. The addition of the UI 2-NPT to urea granules applied on grassland effectively reduced NH3 losses.
Abnormalities in the anterior inter-hemispheric connectivity have previously been implicated in major depressive disorder. Disruptions in fractional anisotropy in the callosum and fornix have been reported in schizophrenia and major depressive disorder. Oligodendrocyte density and overall size of the callosum and fornix show no alteration in either illness, suggesting that gross morphology is unchanged but more subtle organizational disruption may exist within these brain regions in mood and affective disorders.
Using high-resolution oil-immersion microscopy we examined the cross-sectional area of the nerve fibre and the axonal myelin sheath, and using standard high-resolution light microscopy we measured the density of myelinated axons. These measurements were made in the genu of the corpus callosum and the medial body of the fornix at its most dorsal point. Measures were taken in the sagittal plane in the callosal genu and in the coronal plane at the most dorsal part of the fornix body.
Cases of major depressive disorder had significantly greater mean myelin cross-sectional area (p = 0.017) and myelin thickness (p = 0.004) per axon in the genu than in control or schizophrenia groups. There was no significant change in the density of myelinated axons, and no changes observed in the fornix.
The results suggest a clear increase of myelin in the axons of the callosal genu in MDD, although this type of neuropathological study is unable to clarify whether this is caused by changes during life or has a developmental origin.
Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).
For investigating familiality, we used 691 families with 2–5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.
Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.
AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.
We investigate the environmental dependence of the mass-metallicty (MZ) relation and its connection to galaxy stellar structures and morphologies. In our studies, we analyze galaxies in massive clusters at z ∼ 0.4 from the CLASH (HST) and CLASH-VLT surveys and measure their gas metallicities, star-formation rates, stellar structures and morphologies. We establish the MZ relation for 90 cluster and 40 field galaxies finding a shift of ∼ − 0.3 dex in comparison to the local trends seen in SDSS for the majority of galaxies with logM < 10.5. We do not find significant differences of the distribution of 4 distinct morphological types that we introduce by our classification scheme (smooth, disc-like, peculiar, compact). Some variations between cluster and field galaxies in the MZ relation are visible at the high mass end. However, obvious trends for cluster specific interactions (enhancements or quenching of SFRs) are missing. In particular, galaxies with peculiar stellar structures that hold signs for galaxy interactions, are distributed in a similar way as disc-like galaxies - in SFRs, masses and O/H abundances. We further show that our sample falls around an extrapolation of the star-forming main sequence (the SFR-M∗ relation) at this redshift, indicating that emission-line selected samples do not have preferentially high star-formation rates (SFRs). However, we find that half of the high mass cluster members (M∗ > 1010M⊙) lie below the main sequence which corresponds to the higher mass objects that reach solar abundances in the MZ diagram.
Clinical and ethical implications of personality and mood changes in Parkinson's disease (PD) patients treated with subthalamic deep brain stimulation (STN-DBS) are under debate. Although subjectively perceived personality changes are often mentioned by patients and caregivers, few empirical studies concerning these changes exist. Therefore, we analysed subjectively perceived personality and mood changes in STN-DBS PD patients.
In this prospective study of the ELSA-DBS group, 27 PD patients were assessed preoperatively and 1 year after STN-DBS surgery. Two categories, personality and mood changes, were analysed with semi-structured interviews. Patients were grouped into personality change yes/no, as well as positive/negative mood change groups. Caregivers were additionally interviewed about patients’ personality changes. Characteristics of each group were assessed with standard neurological and psychiatric measurements. Predictors for changes were analysed.
Personality changes were perceived by six of 27 (22%) patients and by 10 of 23 caregivers (44%). The preoperative hypomania trait was a significant predictor for personality change perceived by patients. Of 21 patients, 12 (57%) perceived mood as positively changed. Higher apathy and anxiety ratings were found in the negative change group.
Our results show that a high proportion of PD patients and caregivers perceived personality changes under STN-DBS, emphasizing the relevance of this topic. Mood changed in positive and negative directions. Standard measurement scales failed to adequately reflect personality or mood changes subjectively perceived by patients. A more individualized preoperative screening and preparation for patients and caregivers, as well as postoperative support, could therefore be useful.
Defect structures in Rubidium Titanyl Phosphate (RTP) crystals (non-doped and doped) grown by the Top Seeded Solution Growth (TSSG) method were characterized using Synchrotron White Beam X-ray Topography. Main defects observed in non-doped crystals are growth sector boundaries while both growth sector boundaries and growth striations are observed in the Nb single doped and (Nb,Yb)-codoped crystals with relatively few linear defects such as dislocations. Results show that the overall crystalline quality is lowered as more doping elements are incorporated. Details of defect distributions are correlated with the growth process to facilitate high quality growth of doped RTP.
To prepare cholesteric liquid crystalline nonlinear optical materials with ability to be vitrified on cooling and form long time stability cholesteric glasses at room temperature, a series of platinum acetylide complexes modified with cholesterol has been synthesized. The materials synthesized have the formula trans-Pt(PR3)(cholesterol (3 or 4)-ethynyl benzoate)(1-ethynyl-4-X-benzene), where R = Et, Bu or Oct and X = H, F, OCH3 and CN. A cholesteric liquid crystal phase was observed in the complexes R = Et, and X = F, OCH3 and CN but not in any of the other complexes. When X = CN, a cholesteric glass was observed at room temperature which remained stable up to 130 °C, then converted to a mixed crystalline/cholesteric phase and completely melted to an isotropic phase at 230 °C. When X = F or OCH3 the complexes were crystalline at room temperature with conversion to the cholesteric phase upon heating to 190 and 230 °C, respectively. In the series X = CN, OCH3 and F, the cholesteric pitch was determined to be 1.7, 3.4 and 9.0 µ, respectively.
As physical activity may modify the effect of the apolipoprotein E (APOE) ε4 allele on the risk of dementia and Alzheimer's disease (AD) dementia, we tested for such a gene–environment interaction in a sample of general practice patients aged ⩾75 years.
Data were derived from follow-up waves I–IV of the longitudinal German study on Ageing, Cognition and Dementia in Primary Care Patients (AgeCoDe). The Kaplan–Meier survival method was used to estimate dementia- and AD-free survival times. Multivariable Cox regression was used to assess individual associations of APOE ε4 and physical activity with risk for dementia and AD, controlling for covariates. We tested for gene–environment interaction by calculating three indices of additive interaction.
Among the randomly selected sample of 6619 patients, 3327 (50.3%) individuals participated in the study at baseline and 2810 (42.5%) at follow-up I. Of the 2492 patients without dementia included at follow-up I, 278 developed dementia (184 AD) over the subsequent follow-up interval of 4.5 years. The presence of the APOE ε4 allele significantly increased and higher physical activity significantly decreased risk for dementia and AD. The co-presence of APOE ε4 with low physical activity was associated with higher risk for dementia and AD and shorter dementia- and AD-free survival time than the presence of APOE ε4 or low physical activity alone. Indices of interaction indicated no significant interaction between low physical activity and the APOE ε4 allele for general dementia risk, but a possible additive interaction for AD risk.
Physical activity even in late life may be effective in reducing conversion to dementia and AD or in delaying the onset of clinical manifestations. APOE ε4 carriers may particularly benefit from increasing physical activity with regard to their risk for AD.
In human-centered design, user research drives design decisions by providing an understanding of end users. In practice, different people, teams, or even companies manage each step of the design process, making communication of user research results a critical activity. Based on an empirical study of current methods used by experts, this paper presents strategies for effectively communicating user research findings across organizational or corporate boundaries. To build researcher–client relationships, understand both user and client needs, and overcome institutional inertia, this paper proposes viewing user research clients as users of user research outcomes. This reframing of the crafting of communication across boundaries as a parallel internal human-centered design process we refer to as a double ethnography.