Different aspects of emotional processes in apathy: Application of the French translated dimensional apathy scale

Apathy is a behavioural symptom that occurs in neuropsychiatric, neurological and neurodegenerative disease. It is defined as a lack of motivation and/or a quantitative reduction of goal-directed behaviour. Levy and Dubois Cerebral Cortex, 16(7), 916–928 (2006) proposed a triadic substructure of apathy and similar subtypes can be assessed using the Dimensional Apathy Scale (DAS), via the Executive, Emotional and Initiation subscales. The aim of this study was to translate the DAS in to French (f-DAS), examine its psychometric properties and the substructure of apathy using Confirmatory Factor Analysis (CFA). The results showed an acceptable internal consistency reliability of the f-DAS and a similar relationship to depression as in the original DAS development study. The CFA supported a triadic dimensional substructure of the f-DAS, similar to the original DAS but suggested a more complex substructure, specifically, two further processes of the Emotional apathy dimension relating to “Social Emotional” and “Individual Emotional” aspects of demotivation. To conclude, the f-DAS is a robust and reliable tool for assessing multidimensional apathy. Further research should explore the utility of the f-DAS in patients with neuropsychiatric diseases in view of social emotional aspects in apathy

M2N: Mesh Movement Networks for PDE Solvers

Numerical Partial Differential Equation (PDE) solvers often require discretizing the physical domain by using a mesh. Mesh movement methods provide the capability to improve the accuracy of the numerical solution without introducing extra computational burden to the PDE solver, by increasing mesh resolution where the solution is not well-resolved, whilst reducing unnecessary resolution elsewhere. However, sophisticated mesh movement methods, such as the Monge-Ampère method, generally require the solution of auxiliary equations. These solutions can be extremely expensive to compute when the mesh needs to be adapted frequently. In this paper, we propose to the best of our knowledge the first learning-based end-to-end mesh movement framework for PDE solvers. Key requirements of learning-based mesh movement methods are: alleviating mesh tangling, boundary consistency, and generalization to mesh with different resolutions. To achieve these goals, we introduce the neural spline model and the graph attention network (GAT) into our models respectively. While the Neural-Spline based model provides more flexibility for large mesh deformation, the GAT based model can handle domains with more complicated shapes and is better at performing delicate local deformation. We validate our methods on stationary and time-dependent, linear and non-linear equations, as well as regularly and irregularly shaped domains. Compared to the traditional Monge-Ampère method, our approach can greatly accelerate the mesh adaptation process by three to four orders of magnitude, whilst achieving comparable numerical error reduction

Litter inputs, but not litter diversity, maintain soil processes in degraded tropical forests — a cross-continental comparison

Land-use change in tropical forests can reduce biodiversity and ecosystem carbon (C) storage, but although changes in aboveground biomass C in human-modified tropical forests are well-documented, patterns in the dynamics and storage of C belowground are less well characterised. To address this, we used a reciprocal litter transplant experiment to assess litter decomposition and soil respiration under distinct litter types in forested or converted habitats in Panama, Central America, and in Sabah, Malaysian Borneo. The converted habitats comprised a large clearing on the Panama Canal and oil palm plantation in Borneo; forested habitats comprised a 60-year old secondary forest in Panama and a disturbed forest in Borneo that was selectively logged until 2008. In each habitat, we installed mesocosms and litterbags with litter collected from old-growth forest, secondary forest or an introduced species: Elaeis guineensis in Borneo and Saccharum spontaneum in Panama. We measured litter mass loss, soil respiration, and soil microbial biomass during nine months at each site. Decomposition differed markedly between habitat types and between forest vs. introduced litter, but the decay rates and properties of old-growth and secondary forest litters in the forest habitats were remarkably similar, even across continents. Slower decomposition of all litter types in the converted habitats was largely explained by microclimate, but the faster decay of introduced litter was linked to lower lignin content compared to the forest litter. Despite marked differences in litter properties and decomposition, there was no effect of litter type on soil respiration or microbial biomass. However, regardless of location, litter type, and differences in soil characteristics, we measured a similar decline in microbial activity and biomass in the absence of litter inputs. Interestingly, whereas microbial biomass and soil respiration increased substantially in response to litter inputs in the forested habitats and the converted habitat in Panama, there was little or no corresponding increase in the converted habitat in Borneo, indicating that soil recovery capacity had declined substantially in oil palm plantations. Overall, our results suggest that litter inputs are essential to preserve key soil processes, but litter diversity may be less important, especially in highly disturbed habitats

M2N: Mesh movement networks for PDE solvers

Numerical Partial Differential Equation (PDE) solvers often require discretizing the physical domain by using a mesh. Mesh movement methods provide the capability to improve the accuracy of the numerical solution without introducing extra computational burden to the PDE solver, by increasing mesh resolution where the solution is not well-resolved, whilst reducing unnecessary resolution elsewhere. However, sophisticated mesh movement methods, such as the Monge-Ampère method, generally require the solution of auxiliary equations. These solutions can be extremely expensive to compute when the mesh needs to be adapted frequently. In this paper, we propose to the best of our knowledge the first learning-based end-to-end mesh movement framework for PDE solvers. Key requirements of learning-based mesh movement methods are: alleviating mesh tangling, boundary consistency, and generalization to mesh with different resolutions. To achieve these goals, we introduce the neural spline model and the graph attention network (GAT) into our models respectively. While the Neural-Spline based model provides more flexibility for large mesh deformation, the GAT based model can handle domains with more complicated shapes and is better at performing delicate local deformation. We validate our methods on stationary and time-dependent, linear and non-linear equations, as well as regularly and irregularly shaped domains. Compared to the traditional Monge-Ampère method, our approach can greatly accelerate the mesh adaptation process by three to four orders of magnitude, whilst achieving comparable numerical error reduction

International Olympic Committee consensus statement on pain management in elite athletes

Pain is a common problem among elite athletes and is frequently associated with sport injury. Both pain and injury interfere with the performance of elite athletes. There are currently no evidence-based or consensus-based guidelines for the management of pain in elite athletes. Typically, pain management consists of the provision of analgesics, rest and physical therapy. More appropriately, a treatment strategy should address all contributors to pain including underlying pathophysiology, biomechanical abnormalities and psychosocial issues, and should employ therapies providing optimal benefit and minimal harm. To advance the development of a more standardised, evidence-informed approach to pain management in elite athletes, an IOC Consensus Group critically evaluated the current state of the science and practice of pain management in sport and prepared recommendations for a more unified approach to this important topic

We are all in this together—whole of community pain science education campaigns to promote better management of persistent pain

Persistent pain is a major public health issue—estimated to affect a quarter of the world's population. Public understanding of persistent pain is based on outdated biomedical models, laden with misconceptions that are contrary to best evidence. This understanding is a barrier to effective pain management. Thus, there have been calls for public health-based interventions to address these misconceptions. Previous pain-focussed public education campaigns have targeted pain beliefs and behaviours that are thought to promote recovery, such as staying active. However, prevailing pain-related misconceptions render many of these approaches counter-intuitive, at best. Pain Science Education improves understanding of ‘how pain works’ and has been demonstrated to improve pain and disability outcomes. Extending Pain Science Education beyond the clinic to the wider community seems warranted. Learning from previous back pain-focussed and other public health educational campaigns could optimise the potential benefit of such a Pain Science Education campaign. Pain Science Education-grounded campaigns have been delivered in Australia and the UK and show promise, but robust evaluations are needed before any firm conclusions on their population impact can be made. Several challenges exist going forward. Not least is the need to ensure all stakeholders are involved in the development and implementation of Pain Science Education public messaging campaigns. Furthermore, it is crucial that campaigns are undertaken through a health equity lens, incorporating underrepresented communities to ensure that any intervention does not widen existing health inequalities associated with persistent pain. Perspective: Public misconceptions about pain are a significant public health challenge and a viable intervention target to reduce the personal, social, and economic burden of persistent pain. Adaptation of Pain Science Education, which improves misconceptions in a clinical setting, into the public health setting seems a promising approach to explore

11th International Wheat Genetics Symposium 2008 (IWGS 2008)

Soil Borne Pathogens (SBPs), including dryland cereal root rots and cereal nematodes are a major constraint to cereal production worldwide, particularly where cereals dominate rotations, and sub-optimal growing conditions and or cultural practices are common

Identification of multiple root disease resistant wheat germplasm against cereal nematodes and dryland root rot and their validation in regions of economic importance

História da literatura portuguesa coordenada por Giulia Lanciani - primeiras páginas de um total pp. 7-108)História literária do século XVIII portuguêsGoverno de Portuga