Porous 'Ouzo-effect' silica-ceria composite colloids and their application to aluminium corrosion protection.

By exploiting spontaneous emulsification to prepare porous SiO(2) particles, we report the formation of porous CeO(2)@SiO(2) hybrid colloids and their incorporation into a silica-zirconia coating to improve the corrosion protection of aluminium

Learning why things change: The Difference-Based Causality Learner

In this paper, we present the Difference-Based Causality Learner (DBCL), an algorithm for learning a class of discrete-time dynamic models that represents all causation across time by means of difference equations driving change in a system. We motivate this representation with real-world mechanical systems and prove DBCL's correctness for learning structure from time series data, an endeavour that is complicated by the existence of latent derivatives that have to be detected. We also prove that, under common assumptions for causal discovery, DBCL will identify the presence or absence of feedback loops, making the model more useful for predicting the effects of manipulating variables when the system is in equilibrium. We argue analytically and show empirically the advantages of DBCL over vector autoregression (VAR) and Granger causality models as well as modified forms of Bayesian and constraintbased structure discovery algorithms. Finally, we show that our algorithm can discover causal directions of alpha rhythms in human brains from EEG data

Improving the quality of mental health services using patient outcome data: Making the most of HoNOS

Efforts to assess and improve the quality of mental health services are often hampered by a lack of information on patient outcomes. Most mental health services in England have been routinely collecting Health of the Nation Outcome Scales (HoNOS) data for some time. In this article we illustrate how clinical teams have used HoNOS data to identify areas where performance could be improved. HoNOS data have the potential to give clinical teams the information they need to assess the quality of care they deliver, as well as develop and test initiatives aimed at improving the services they provide

Building thermal performance, extreme heat, and climate change

The leading source of weather-related deaths in the United States is heat, and future projections show that the frequency, duration, and intensity of heat events will increase in the Southwest. Presently, there is a dearth of knowledge about how infrastructure may perform during heat waves or could contribute to social vulnerability. To understand how buildings perform in heat and potentially stress people, indoor air temperature changes when air conditioning is inaccessible are modeled for building archetypes in Los Angeles, California, and Phoenix, Arizona, when air conditioning is inaccessible is estimated. An energy simulation model is used to estimate how quickly indoor air temperature changes when building archetypes are exposed to extreme heat. Building age and geometry (which together determine the building envelope material composition) are found to be the strongest indicators of thermal envelope performance. Older neighborhoods in Los Angeles and Phoenix (often more centrally located in the metropolitan areas) are found to contain the buildings whose interiors warm the fastest, raising particular concern because these regions are also forecast to experience temperature increases. To combat infrastructure vulnerability and provide heat refuge for residents, incentives should be adopted to strategically retrofit buildings where both socially vulnerable populations reside and increasing temperatures are forecast

Adipokines and body fat composition in South Asians: results of the Metabolic Syndrome and Atherosclerosis in South Asians Living in America (MASALA) study.

ObjectiveTo investigate whether leptin and adiponectin are associated with body fat composition in a South Asian population independent of metabolic variables.DesignCross-sectional study.Subjects150 South Asian men and women, between the ages of 45-79 years, in the San Francisco Bay Area without pre-existing clinical cardiovascular disease.MeasurementsBlood samples were obtained to measure glucose metabolism variables, lipid profiles and adipokines. Total body fat was determined using dual-energy X-ray absorptiometry. Abdominal computed tomography was used to measure subcutaneous, visceral and hepatic fat.ResultsAverage body mass index (BMI) was overweight at 26.1±4.6 kg m(-2) and did not differ by sex. However, women had significantly more total body fat (P<0.001) and subcutaneous fat (P<0.001) than men, whereas men had significantly more visceral fat (P<0.001) and hepatic fat (P=0.04) than women. Women had significantly higher levels of adiponectin (P<0.01) and leptin (P<0.01). In sex-stratified analyses, leptin was strongly associated with all-body composition measures in women (P<0.05) as well as in men (P<0.05 except for hepatic fat), whereas there was an insignificant trend towards an inverse association between adiponectin and body composition in both women and men, which was significant in combined bivariate analyses. In multivariate analyses, leptin was strongly associated with all measures of adiposity, including BMI (P<0.001), total body fat (P<0.001), visceral fat (P<0.001) and hepatic fat (P=0.01). However, adiponectin's inverse association with adiposity was significantly attenuated by high-density lipoprotein (HDL), triglycerides and insulin resistance. The association between adipokines and diabetes was markedly attenuated after adjusting for body composition.ConclusionDespite only modestly elevated BMI, South Asians have elevated levels of total and regional adiposity. Leptin is strongly associated with adiposity, whereas adiponectin's association with adiposity is attenuated by metabolic variables in South Asians. Adipokines in association with adiposity have an important role in the development of diabetes

Comparison of predictive scores of symptomatic intracerebral haemorrhage after stroke thrombolysis in a single centre

Peer reviewedPublisher PD

When is general wariness favored in avoiding multiple predator types?

Free access to article and electronic appendices via DOI.Adaptive responses to predation are generally studied assuming only one predator type exists, but most prey species are depredated by multiple types. When multiple types occur, the optimal antipredator response level may be determined solely by the probability of attack by the relevant predator: "specific responsiveness." Conversely, an increase in the probability of attack by one predator type might increase responsiveness to an alternative predator type: "general wariness." We formulate a mathematical model in which a prey animal perceives a cue providing information on the probability of two predator types being present. It can perform one of two evasive behaviors that vary in their suitability as a response to the "wrong" predator type. We show that general wariness is optimal when incorrect behavioral decisions have differential fitness costs. Counterintuitively, difficulty in discriminating between predator types does not favor general wariness. We predict that where responses to predator types are mutually exclusive (e.g., referential alarm-calling), specific responsiveness will occur; we suggest that prey generalize their defensive responses based on cue similarity due to an assumption of response utility; and we predict, with relevance to conservation, that habituation to human disturbance should generalize only to predators that elicit the same antipredator response as humans

Maize silage for dairy cows: mitigation of methane emissions can be offset bij and use change

Increasing the digestibility of cattle rations by feeding grains and whole plant silages from maize have been identified as effective options to mitigate greenhouse gas emissions. The effect of ploughing grassland for maize crops have not been taken into account yet. A intensive dairy farm is used as an example to demonstrate the trade offs by this type of land use change when more maize silage is fed to dairy cows. The model DAIRY WISE has been used to calculate the mitigation by the changed ration, the Introductory Carbon Balance Model to calculate the changes in soil organic carbon and nitrogen caused by ploughing grassland for maize crops. The losses of soil carbon and the loss of sequestration potential are much larger than the annual mitigation by feeding more maize. The ecosystem carbon payback time defines the years of mitigation that are needed before the emissions due to land use change are compensated. For ploughing grassland on sandy soils, the carbon payback time is 60 years. A higher global warming potential for methane can reduce the carbon payback time with 30%. Ploughing clay soils with a higher equilibrium level of soil organic matter increases the payback time by maximally 70%. The payback times occur only in the case of permanent maize cropping, grass maize rotations cause annual losses of nitrous oxide that are larger than the mitigation by feeding more maize

Support during birth interacts with prior trauma and birth intervention to predict postnatal post-traumatic stress symptoms

Background: Many women experience childbirth as traumatic and 2% develop post-traumatic stress disorder (PTSD). This study examined the role of health practitioner support and personal control during birth as predictors of PTS symptoms, adjusting for vulnerability factors of prior trauma, depression, control beliefs and birth intervention. It also investigated interactions between support, prior trauma and birth intervention and their association with PTS symptoms. Methods: A prospective longitudinal survey of 138 women recruited from UK NHS maternity clinics. Measures were taken in pregnancy, three-weeks and three-months after the birth. Results: Support and control during birth were not predictive of postnatal PTS symptoms. However, support was predictive of PTS symptoms in a subset of women with prior trauma (beta = -.41, R2 = 16%) at both three-weeks and three-months postpartum. The interaction of birth intervention and support was associated with PTS symptoms three-months after birth, the relationship between support and PTS symptoms was stronger in women experiencing more intervention. Conclusions: Low support from health practitioners is predictive of postnatal PTS symptoms in women who have a history of trauma. Longer-term effects of low support on postnatal PTS symptoms are also found in women who had more intervention during birth

Shallow vs deep learning architectures for white matter lesion segmentation in the early stages of multiple sclerosis

In this work, we present a comparison of a shallow and a deep learning architecture for the automated segmentation of white matter lesions in MR images of multiple sclerosis patients. In particular, we train and test both methods on early stage disease patients, to verify their performance in challenging conditions, more similar to a clinical setting than what is typically provided in multiple sclerosis segmentation challenges. Furthermore, we evaluate a prototype naive combination of the two methods, which refines the final segmentation. All methods were trained on 32 patients, and the evaluation was performed on a pure test set of 73 cases. Results show low lesion-wise false positives (30%) for the deep learning architecture, whereas the shallow architecture yields the best Dice coefficient (63%) and volume difference (19%). Combining both shallow and deep architectures further improves the lesion-wise metrics (69% and 26% lesion-wise true and false positive rate, respectively).Comment: Accepted to the MICCAI 2018 Brain Lesion (BrainLes) worksho