570 research outputs found
Revealing the true partitioning character of zirconium in additively manufactured polycrystalline superalloys
International audienc
Probabilistic analysis of the upwind scheme for transport
We provide a probabilistic analysis of the upwind scheme for
multi-dimensional transport equations. We associate a Markov chain with the
numerical scheme and then obtain a backward representation formula of
Kolmogorov type for the numerical solution. We then understand that the error
induced by the scheme is governed by the fluctuations of the Markov chain
around the characteristics of the flow. We show, in various situations, that
the fluctuations are of diffusive type. As a by-product, we prove that the
scheme is of order 1/2 for an initial datum in BV and of order 1/2-a, for all
a>0, for a Lipschitz continuous initial datum. Our analysis provides a new
interpretation of the numerical diffusion phenomenon
Relation of C-reactive protein to body fat distribution and features of the metabolic syndrome in Europeans and South Asians.
OBJECTIVE: To investigate the association between circulating C-reactive protein (CRP) concentrations and indices of body fat distribution and the insulin resistance syndrome in South Asians and Europeans. DESIGN: : Cross-sectional study. SUBJECTS: A total of 113 healthy South Asian and European men and women in West London (age 40-55 y, body mass index (BMI) 17-34 kg/m(2)). MEASUREMENTS: Fatness and fat distribution parameters (by anthropometry, dual-energy X-ray absorptiometry and abdominal CT scan); oral glucose tolerance test with insulin response; modified fat tolerance test; and CRP concentration by sensitive ELISA. RESULTS: Median CRP level in South Asian women was nearly double that in European women (1.35 vs 0.70 mg/1, P=0.05). Measures of obesity and CRP concentration were significantly associated in both ethnic groups. The correlation to CRP was especially strong among South Asians (P0.15). CONCLUSION: We suggest that adiposity and in particular visceral adipose tissue is a key promoter of low-grade chronic inflammation. This observation may in part account for the association of CRP with markers of the metabolic syndrome. Future studies should confirm whether CRP concentrations are elevated in South Asians and whether losing weight by exercise or diet, or reduction in visceral fat mass, is associated with reduction in plasma CRP concentrations
Sooty mangabeys use auditory cues to scavenge on nuts cracked by chimpanzees and red river hogs:An investigation of inter-specific interactions around tropical nut trees
Inflammatory biomarkers and the prediction of coronary events among people at intermediate risk: the EPIC-Norfolk prospective population study
System integration of wind and solar power in Integrated Assessment Models: A cross-model evaluation of new approaches
Mitigation-Process Integrated Assessment Models (MP-IAMs) are used to analyze long-term transformation pathways of the energy system required to achieve stringent climate change mitigation targets. Due to their substantial temporal and spatial aggregation, IAMs cannot explicitly represent all detailed challenges of integrating the variable renewable energies (VRE) wind and solar in power systems, but rather rely on parameterized modeling approaches. In the ADVANCE project, six international modeling teams have developed new approaches to improve the representation of power sector dynamics and VRE integration in IAMs.
In this study, we qualitatively and quantitatively evaluate the last years' modeling progress and study the impact of VRE integration modeling on VRE deployment in IAM scenarios. For a comprehensive and transparent qualitative evaluation, we first develop a framework of 18 features of power sector dynamics and VRE integration. We then apply this framework to the newly-developed modeling approaches to derive a detailed map of strengths and limitations of the different approaches. For the quantitative evaluation, we compare the IAMs to the detailed hourly-resolution power sector model REMIX. We find that the new modeling approaches manage to represent a large number of features of the power sector, and the numerical results are in reasonable agreement with those derived from the detailed power sector model. Updating the power sector representation and the cost and resources of wind and solar substantially increased wind and solar shares across models: Under a carbon price of 30$/tCO2 in 2020 (increasing by 5% per year), the model-average cost-minimizing VRE share over the period 2050â2100 is 62% of electricity generation, 24%-points higher than with the old model version
Impact of a non-restrictive satiating diet on anthropometrics, satiety responsiveness and eating behaviour traits in obese men displaying a high or a low satiety phenotype
The aim of this study was to evaluate the impact of a non-restrictive satiating diet in men displaying various degrees of satiety efficiency. In all, sixty-nine obese men aged 41·5 (sd 5·7) years were randomly assigned to a control (10â15, 55â60 and 30 % energy as protein, carbohydrate and lipid, respectively; n 34) or satiating (20â25, 45â50 and 30â35 % energy as protein, carbohydrate and lipid, respectively; n 35) diet for 16 weeks, and were classified as having a low (LSP) or high (HSP) satiety phenotype. Both diets were consumed ad libitum. Changes in body weight, BMI, percent fat mass, waist circumference, satiety responsiveness and eating behaviour traits were assessed following the intervention. Dropout rates were higher in the control diet (44·1 %) compared with the satiating diet (8·6 %). Decreases in body weight, BMI and waist circumference were significant in both groups, yet HSP individuals lost more body weight than LSP individuals (P=0·048). Decreases in % fat mass were greater in the satiating diet (LSP: â2·1 (sd 2·1) %; P<0·01 and HSP: â3·0 (sd 2·5) %; P<0·001) compared with the control diet (LSP: â1·1 (sd 2·5) % and HSP: â1·3 (sd 2·6) %) (P=0·034). Satiety responsiveness was markedly improved in the satiating diet, whereas no significant changes were observed in the control group. Changes in dietary restraint (+3·3 (sd 2·9) to +7·2 (sd 5·5)), flexible control (+0·9 (sd 1·4) to +2·3 (sd 2·7)), rigid control (+2·2 (sd 1·5) to +2·5 (sd 2·8)), disinhibition (â2·8 (sd 3·7) to â3·2 (sd 2·6)) and susceptibility to hunger (â2·7 (sd 4·1) to â4·6 (sd 3·9)) were similar between the diets. Compared with the control diet, the satiating diet favoured adherence, decreased % fat mass and improved satiety responsiveness in both HSP and LSP individuals
Chimpanzee identification and social network construction through an online citizen science platform
Abstract Citizen science has grown rapidly in popularity in recent years due to its potential to educate and engage the public while providing a means to address a myriad of scientific questions. However, the rise in popularity of citizen science has also been accompanied by concerns about the quality of data emerging from citizen science research projects. We assessed data quality in the online citizen scientist platform Chimp&See, which hosts camera trap videos of chimpanzees (Pan troglodytes) and other species across Equatorial Africa. In particular, we compared detection and identification of individual chimpanzees by citizen scientists with that of experts with years of experience studying those chimpanzees. We found that citizen scientists typically detected the same number of individual chimpanzees as experts, but assigned far fewer identifications (IDs) to those individuals. Those IDs assigned, however, were nearly always in agreement with the IDs provided by experts. We applied the data sets of citizen scientists and experts by constructing social networks from each. We found that both social networks were relatively robust and shared a similar structure, as well as having positively correlated individual network positions. Our findings demonstrate that, although citizen scientists produced a smaller data set based on fewer confirmed IDs, the data strongly reflect expert classifications and can be used for meaningful assessments of group structure and dynamics. This approach expands opportunities for social research and conservation monitoring in great apes and many other individually identifiable species
Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases
The problem of classifying subjects into risk categories is a common challenge in medical research. Machine Learning (ML) methods are widely used in the areas of risk prediction and classification. The primary objective of these algorithms is to predict dichotomous responses (e.g. healthy/at risk) based on several features. Similarly to statistical inference models, also ML models are subject to the common problem of class imbalance. Therefore, they are affected by the majority class increasing the false-negative rate.
In this paper, we built and evaluated eighteen ML models classifying approximately 4300 female participants from the UK Biobank into three categorical risk statuses based on responses for the discretised visceral adipose tissue values from magnetic resonance imaging. We also examined the effect of sampling techniques on classification modelling when dealing with class imbalance.
Results showed that the use of sampling techniques had a significant impact. They not only drove an improvement in predicting patients risk status but also facilitated an increase in the information contained within each variable. Based on domain experts criteria, the three best models for classification were finally identified.
These encouraging results will guide further developments of classification models for predicting visceral adipose tissue without the need for a costly scan
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Mid-century emission pathways in Japan associated with the global 2 °C goal: national and global modelsâ assessments based on carbon budgets
This study assesses Japanâs mid-century low-emission pathways using both national and global integrated assessment models in the common mitigation scenario framework, based on the carbon budgets corresponding to the global 2 °C goal. We examine high and low budgets, equal to global cumulative 1600 and 1000 Gt-CO2 (2011â2100) for global models, and 36 and 31 Gt-CO2 (2011â2050) in Japan for national models, based on the cost-effectiveness allocation performed by the global models. The impacts of near-term policy assumption, including the implementation and enhancement of the 2030 target of the nationally determined contribution (NDC), are also considered. Our estimates show that the low budget scenarios require a 75% reduction of CO2 emissions by 2050 below the 2010 level, which is nearly the same as Japanâs governmental 2050 goal of reducing greenhouse gas emissions by 80%. With regard to near-term actions, Japanâs 2030 target included in the NDC is on track to meet the high budget scenario, whereas it is falling short for the low budget scenario, which would require emission reductions immediately after 2020. Whereas models differ in the type of energy source on which they foresee Japan basing its decarbonization process (e.g., nuclear- or variable renewable energy-dependent), the large-scale deployment of low-carbon energy (nuclear, renewable, and carbon capture and storage) is shared across most models in both the high and low budget scenarios. By 2050, low-carbon energy represents 44â54% of primary energy and 86â97% of electricity supply in the high and low budget scenarios, respectively
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