Classification of Message Spreading in a Heterogeneous Social Network

Nowadays, social networks such as Twitter, Facebook and LinkedIn become increasingly popular. In fact, they introduced new habits, new ways of communication and they collect every day several information that have different sources. Most existing research works fo-cus on the analysis of homogeneous social networks, i.e. we have a single type of node and link in the network. However, in the real world, social networks offer several types of nodes and links. Hence, with a view to preserve as much information as possible, it is important to consider so-cial networks as heterogeneous and uncertain. The goal of our paper is to classify the social message based on its spreading in the network and the theory of belief functions. The proposed classifier interprets the spread of messages on the network, crossed paths and types of links. We tested our classifier on a real word network that we collected from Twitter, and our experiments show the performance of our belief classifier

Test of Information Theory on the Boltzmann Equation

We examine information theory using the steady-state Boltzmann equation. In a nonequilibrium steady-state system under steady heat conduction, the thermodynamic quantities from information theory are calculated and compared with those from the steady-state Boltzmann equation. We have found that information theory is inconsistent with the steady-state Boltzmann equation.Comment: 12 page

Dietary fatty acids: is it time to change the recommendations

Limiting the saturated fatty acid (SAFA) consumption forms the basis of dietary fat recommendations for heart health, despite several meta-analyses demonstrating no link be- tween dietary SAFA and the risk of cardiovascular disease (CVD). Three experts on dietary fat and health discussed the evidence of reducing SAFA intake at a symposium of the Federation of European Nutrition Societies in Berlin, Germany, October 23, 2015. Ronald P. Mensink, Maastricht University, the Netherlands, discussed the evidence linking dietary fatty acids and CVD risk. He emphasized the impor- tance of the replacement nutrient(s) when SAFA intake is re- duced. Julie Lovegrove, University of Reading, UK, addressed the question of whether higher intakes of unsaturated fatty acids are beneficial. She discussed the replacement of SAFA by polyunsaturated fatty acids (PUFA) and monounsaturat- ed fatty acids (MUFA), noting the reduction in CVD risk with PUFA replacement and in CVD risk markers with MUFA re- placement of SAFA. Ursula Schwab, University of Eastern Finland, Kuopio, Finland, discussed the importance of di- etary patterns in achieving reduced risk of CVD, observing that several dietary patterns following the principles of a health-promoting diet and adapted to local customs, food preferences and seasonality are effective in reducing the risk of CVD, type 2 diabetes and other chronic diseases. This pa- per summarizes the symposium presentations

Evidence for a change in the nuclear mass surface with the discovery of the most neutron-rich nuclei with 17<Z <25

The results of measurements of the production of neutron-rich nuclei by the fragmentation of a 76-Ge beam are presented. The cross sections were measured for a large range of nuclei including fifteen new isotopes that are the most neutron-rich nuclides of the elements chlorine to manganese (50-Cl, 53-Ar, 55,56-K, 57,58-Ca, 59,60,61-Sc, 62,63-Ti, 65,66-V, 68-Cr, 70-Mn). The enhanced cross sections of several new nuclei relative to a simple thermal evaporation framework, previously shown to describe similar production cross sections, indicates that nuclei in the region around 62-Ti might be more stable than predicted by current mass models and could be an indication of a new island of inversion similar to that centered on 31-Na.Comment: 4 pages, 3 figures, to be published in Physical Review Letters, 200

Information theory in the study of anisotropic radiation

Information theory is used to perform a thermodynamic study of non equilibrium anisotropic radiation. We limit our analysis to a second-order truncation of the moments, obtaining a distribution function which leads to a natural closure of the hierarchy of radiative transfer equations in the so-called variable Eddington factor scheme. Some Eddington factors appearing in the literature can be recovered as particular cases of our two-parameter Eddington factor. We focus our attention in the study of the thermodynamic properties of such systems and relate it to recent nonequilibrium thermodynamic theories. Finally we comment the possibility of introducing a nonequilibrium chemical potential for photons.Comment: 1 eps figure upon request by e-mail, to appear in Journal of Physics

Prevention is better than cure, but...: Preventive medication as a risk to ordinariness?

Preventive health remains at the forefront of public health concerns; recent initiatives, such as the NHS health check, may lead to recommendations for medication in response to the identification of 'at risk' individuals. Little is known about lay views of preventive medication. This paper uses the case of aspirin as a prophylactic against heart disease to explore views among people invited to screening for a trial investigating the efficacy of such an approach. Qualitative interviews (N=46) and focus groups (N=5, participants 31) revealed dilemmas about preventive medication in the form of clashes between norms: first, in general terms, assumptions about the benefit of prevention were complicated by dislike of medication; second, the individual duty to engage in prevention was complicated by the need not to be over involved with one's own health; third, the potential appeal of this alternative approach to health promotion was complicated by unease about the implications of encouraging irresponsible behaviour among others. Though respondents made different decisions about using the drug, they reported very similar ways of trying to resolve these conflicts, drawing upon concepts of necessity and legitimisation and the special ordinariness of the particular dru

Is socioeconomic status associated with biological aging as measured by telomere length?

It has been hypothesized that one way in which lower socioeconomic status (SES) affects health is by increasing the rate of biological aging. A widely used marker of biological aging is telomere length. Telomeres are structures at the ends of chromosomes that erode with increasing cell proliferation and genetic damage. We aimed to identify, through systematic review and meta-analysis, whether lower SES (greater deprivation) is associated with shorter telomeres. Thirty-one articles, including 29 study populations, were identified. We conducted 3 meta-analyses to compare the telomere lengths of persons of high and low SES with regard to contemporaneous SES (12 study populations from 10 individual articles), education (15 study populations from 14 articles), and childhood SES (2 study populations from 2 articles). For education, there was a significant difference in telomere length between persons of high and low SES in a random-effects model (standardized mean difference (SMD) = 0.060, 95% confidence interval (CI): 0.002, 0.118; P = 0.042), although a range of sensitivity analyses weakened this association. There was no evidence for an association between telomere length and contemporaneous SES (SMD = 0.104, 95% CI: −0.027, 0.236; P = 0.119) or childhood SES (SMD = −0.037, 95% CI: −0.143, 0.069; P = 0.491). These results suggest weak evidence for an association between SES (as measured by education) and biological aging (as measured by telomere length), although there was a lack of consistent findings across the SES measures investigated here

Compiling and using input-output frameworks through collaborative virtual laboratories

Compiling, deploying and utilising large-scale databases that integrate environmental and economic data have traditionally been labour- and cost-intensive processes, hindered by the large amount of disparate and misaligned data that must be collected and harmonised. The Australian Industrial Ecology Virtual Laboratory (IELab) is a novel, collaborative approach to compiling large-scale environmentally extended multi-region input-output (MRIO) models.The utility of the IELab product is greatly enhanced by avoiding the need to lock in an MRIO structure at the time the MRIO system is developed. The IELab advances the idea of the "mother-daughter" construction principle, whereby a regionally and sectorally very detailed "mother" table is set up, from which "daughter" tables are derived to suit specific research questions. By introducing a third tier - the "root classification" - IELab users are able to define their own mother-MRIO configuration, at no additional cost in terms of data handling. Customised mother-MRIOs can then be built, which maximise disaggregation in aspects that are useful to a family of research questions.The second innovation in the IELab system is to provide a highly automated collaborative research platform in a cloud-computing environment, greatly expediting workflows and making these computational benefits accessible to all users.Combining these two aspects realises many benefits. The collaborative nature of the IELab development project allows significant savings in resources. Timely deployment is possible by coupling automation procedures with the comprehensive input from multiple teams. User-defined MRIO tables, coupled with high performance computing, mean that MRIO analysis will be useful and accessible for a great many more research applications than would otherwise be possible. By ensuring that a common set of analytical tools such as for hybrid life-cycle assessment is adopted, the IELab will facilitate the harmonisation of fragmented, dispersed and misaligned raw data for the benefit of all interested parties. © 2014 Elsevier B.V

Ensemble of a subset of kNN classifiers

Combining multiple classifiers, known as ensemble methods, can give substantial improvement in prediction performance of learning algorithms especially in the presence of non-informative features in the data sets. We propose an ensemble of subset of kNN classifiers, ESkNN, for classification task in two steps. Firstly, we choose classifiers based upon their individual performance using the out-of-sample accuracy. The selected classifiers are then combined sequentially starting from the best model and assessed for collective performance on a validation data set. We use bench mark data sets with their original and some added non-informative features for the evaluation of our method. The results are compared with usual kNN, bagged kNN, random kNN, multiple feature subset method, random forest and support vector machines. Our experimental comparisons on benchmark classification problems and simulated data sets reveal that the proposed ensemble gives better classification performance than the usual kNN and its ensembles, and performs comparable to random forest and support vector machines

“Medically unexplained” symptoms and symptom disorders in primary care: prognosis-based recognition and classification

Background: Many patients consult their GP because they experience bodily symptoms. In a substantial proportion of cases, the clinical picture does not meet the existing diagnostic criteria for diseases or disorders. This may be because symptoms are recent and evolving or because symptoms are persistent but, either by their character or the negative results of clinical investigation cannot be attributed to disease: so-called “medically unexplained symptoms” (MUS). MUS are inconsistently recognised, diagnosed and managed in primary care. The specialist classification systems for MUS pose several problems in a primary care setting. The systems generally require great certainty about presence or absence of physical disease, they tend to be mind-body dualistic, and they view symptoms from a narrow specialty determined perspective. We need a new classification of MUS in primary care; a classification that better supports clinical decision-making, creates clearer communication and provides scientific underpinning of research to ensure effective interventions. Discussion: We propose a classification of symptoms that places greater emphasis on prognostic factors. Prognosis-based classification aims to categorise the patient’s risk of ongoing symptoms, complications, increased healthcare use or disability because of the symptoms. Current evidence suggests several factors which may be used: symptom characteristics such as: number, multi-system pattern, frequency, severity. Other factors are: concurrent mental disorders, psychological features and demographic data. We discuss how these characteristics may be used to classify symptoms into three groups: self-limiting symptoms, recurrent and persistent symptoms, and symptom disorders. The middle group is especially relevant in primary care; as these patients generally have reduced quality of life but often go unrecognised and are at risk of iatrogenic harm. The presented characteristics do not contain immediately obvious cut-points, and the assessment of prognosis depends on a combination of several factors. Conclusion: Three criteria (multiple symptoms, multiple systems, multiple times) may support the classification into good, intermediate and poor prognosis when dealing with symptoms in primary care. The proposed new classification specifically targets the patient population in primary care and may provide a rational framework for decision-making in clinical practice and for epidemiologic and clinical research of symptoms