Swollen Micelles Plus Hydrophobically Modified Hydrosoluble Polymers in Aqueous Solutions: Decoration Versus Bridging. a Small Angle Neutron Scattering Study

In this paper we examine the effective interactions introduced between the droplets of an oil in water microemulsion upon progressive addition of hydrophobically modified water soluble poly(ethylene oxide)-PEO using essentially small angle neutron scattering. To discuss the relative importance of decoration and bridging of the droplets we compare analogous samples with addition of a PEO grafted at both extremities with hydrophobic C12H 25 chains (PEO-2m) or addition of a PEO grafted at one extremity only with a C12H 25 chain (PEO-m). PEO-m or PEO-2m adsorb onto the droplets via their hydrophobic extremities and the droplets are found to retain their form and size upon addition of up to 40 hydrophobic C12H 25 chains per droplet. When the volume fraction of droplets is less than about 10%, the effective interactions introduced by PEO-m or PEO-2m are found to be very different: PEO-m introduces a repulsive interaction while PEO-2m introduces an effective attractive interaction. This attractive interaction leads to an associative phase separation in the range of low volume fraction when a sufficient amount of PEO-2m is added

Inversion utérine: à propos d’un cas

Une inversion utérine est une complication rare de l’accouchement potentiellement grave, dans laquelle le corps utérin se retourne en doigt de gant et fait saillie dans le vagin ou hors de la vulve. Cette pathologie se manifeste en général juste après l’accouchement, par une douleur importante dans un tableau de choc hémorragique. Le diagnostic est essentiellement clinique et impose d’être immédiat afin de permettre une réinversion rapide avant la formation d’un anneau de striction. En effet, la mortalité est aujourd’hui faible si le diagnostic et la prise en charge sont précoces. L’inversion utérine ne semble pas non plus grever le pronostic obstétrical. Parmi les facteurs favorisants, on retrouve avant tout une hypotonie utérine associée à une insertion fundique du placenta, ce qui provoque une dépression du fond utérin en cas de manoeuvres intempestives (traction sur le cordon, expression utérine). La réinversion doit être rapide, menée de façon conjointe aux mesures de réanimation (traitement du choc). Elle fait appel à plusieurs méthodes manuelles consistant à retourner l’utérus après éventuelle utilisation de procédés myorelaxants (dérivés nitrés, bêtamimétiques, anesthésie générale). L’échec conduit à un traitement chirurgical par voie haute ou voie basse. Nous rapportons le cas d’une inversion utérine totale qui s’est produite avant la délivrance, lors d’un accouchement par voie haute

Percolation in a Model Transient Network: Rheology and Dynamic Light Scattering

Step strain experiments and dynamic light scattering measurements are perfomed to characterize the dynamic behavior of an o/w droplet microemulsion into which is incorporated a telechelic polymer. At sufficient droplet and polymer concentrations, above the percolation threshold, the system is viscoelastic and its dynamic structure factor shows up two steps for the relaxation of concentration fluctuations: the fast one is dominated by the diffusion but the slower one is almost independent of the wave vector. The terminal time of the stress relaxation tR and the slow time of the dynamic structure factor tS are both presumably controlled by the residence time of a sticker in a droplet: consistently, tR and tS are of the same order, they both vanishes at the percolation threshold according to power laws but with different exponents. We discuss these features in terms of deviations at the transition, from the usual mean field description of the dynamics of transient networks.Comment: mars 200

Eigenvalues of an Operator Homogeneous at the Infinity

In this paper, we show the existence of a sequences of eigenvalues for an operator homogenous at the infinity, we give his variational formulation and we establish the simplicity of all eigenvalues in the case N = 1. Finally we study thesolvability of the problemA(u) := −div(A(x,∇u)) = f(x, u) + h in Ω,u = 0 on ∂Ω,as well as the spectrum ofG_0'(u) = λm|u|^{p−2}u in Ω,u = 0 on ∂Ω

Breast Cancer Prediction and Diagnosis through a New Approach based on Majority Voting Ensemble Classifier

peer reviewedResearchers have extensively used machine learning techniques and data mining methods to build prediction models and classify data in various domains such as aviation, computer science, education, finance, marketing and particularly in medical field where those methods are applied as support systems for diagnosis and analysis in order to make better decisions. On this subject, our research paper attempts to assess the performance of Individual and Ensemble machine learning techniques based on the effectiveness and the efficiently, in terms of accuracy, specificity, sensitivity and precision to choose the most effective. The main object of our research paper is to define the best and effective machine learning approach for the Breast Cancer diagnosis and prediction. To achieve our objective, we applied individual based level machine learning algorithms Support Vector Machine (SVM), K-Nearest Neighbors (KNN), Naïve Bayes (NB), Decision tree (C4.5), Simple Logistic and well known ensembles methods like Majority Voting and Random Forest with 10 cross field technique on the Breast Cancer Diagnosis Dataset obtained from UCI Repository. The experimental results show that the Majority Voting Ensemble technique based on 3 top classifiers SVM, K-NN, Simple Logistic gives the highest accuracy 98.1% with the lowest error rate 0.01% and outperformed all other individual classifiers. This study demonstrates that our proposal approach based on Majority Voting Ensemble technique was the best classification machine learning model with the highest level of accuracy for breast cancer prediction and diagnosis. All experiments are effectuated within a simulation environment and realized in Weka data mining tool

Machine Learning Algorithms For Breast Cancer Prediction And Diagnosis

peer reviewedEach year number of deaths is increasing extremely because of breast cancer. It is the most frequent type of all cancers and the major cause of death in women worldwide. Any development for prediction and diagnosis of cancer disease is capital important for a healthy life. Consequently, high accuracy in cancer prediction is important to update the treatment aspect and the survivability standard of patients. Machine learning techniques can bring a large contribute on the process of prediction and early diagnosis of breast cancer, became a research hotspot and has been proved as a strong technique. In this study, we applied five machine learning algorithms: Support Vector Machine (SVM), Random Forest, Logistic Regression, Decision tree (C4.5) and K-Nearest Neighbours (KNN) on the Breast Cancer Wisconsin Diagnostic dataset, after obtaining the results, a performance evaluation and comparison is carried out between these different classifiers. The main objective of this research paper is to predict and diagnosis breast cancer, using machine-learning algorithms, and find out the most effective whit respect to confusion matrix, accuracy and precision. It is observed that Support vector Machine outperformed all other classifiers and achieved the highest accuracy (97.2%).All the work is done in the Anaconda environment based on python programming language and Scikit-learn library

Les dyspareunies du post partum: un sujet non négligeable

La dyspareunie est une douleur éprouvée lors du rapport sexuel. Elle peut être superficielle ou profonde. Elle est fréquente en post partum et donc non négligeable. Elle a fait l’objet de plusieurs descriptions et plusieurs classifications.  Les étiologies sont nombreuses : infectieuses, traumatiques, hormonales, psychiques et autres. Le traitement de la dyspareunie se base sur le traitement de la cause organique et le traitement psychologique du conditionnement à la douleur qui persiste après le traitement médical