Experimental investigation and theoretical modelling of induced anisotropy during stress-softening of rubber

International audienceThe Mullins effect refers to a stress-softening phenomenon of rubber-like materials during cyclic loading. Anisotropy of the material behaviour is generally observed after stretching. In this paper, a large set of original suitable experiments are reported to characterise this effect under several deformation conditions. Then, a phenomenological model is derived to capture the anisotropic distribution. For that, the affine micro-sphere model (Miehe et al., 2004) is amended with a directional network alteration in order to describe anisotropy. The alteration process, involving the breakage and the slippage of the links embedded in the macromolecular network, is modeled by the evolution of the average number of monomer segments per chain during stretching. The average chain length and the chain density are incrementally described by functions to allow both softening and stiffening, depending to the maximum and the minimum stretch rates and levels endured in each direction. The good capacity of the model to reproduce experimental observations validates the above assumptions

Fluctuación poblacional del ácaro de la yema Colomerus vitis pgst. y control químico en vid cv. red globe en Ica

Universidad Nacional Agraria La Molina. Facultad de Agronomía. Departamento Académico de EntomologíaColomerus vitis Pgst. conocido también como el ácaro de la yema de la vid se ubica generalmente dentro de las yemas de la vid, entre las escamas y en el meristema de las yemas, lo cual hace que complicado su control al ser difícilmente evaluable. Para su control se tienen diferentes ingredientes activos y no se ha visto la presencia de controladores biológicos. Este trabajo evaluó la fluctuación poblacional de Colomerus vitis Pgst. en tres campos de vid de la empresa PROAGRO en el fundo Qolca en Ica, los campos denominados 4A, 4C y 6F comenzaron a ser evaluados cuando éstos tenían diferencias en sus estados fenológicos debido a la diferentes fechas de aplicación de cianamida y de poda, encontrándose disminuciones ante la aplicación de ingredientes activos como el azufre y variaciones debido al estado fenológico de la planta, temperatura y prácticas culturales. Asimismo, se evaluó la presencia de ácaros en los cargadores de diferente vigor durante las primeras nueve semanas que corresponden a los cargadores de la campaña anterior y en donde no se encontraron diferencias significativas. Adicionalmente, se hizo un ensayo con productos químicos no registrados para Colomerus vitis Pgst. en el parrón 4 del fundo María Manuela perteneciente a la misma empresa, en éste ensayo se probaron 4 productos a 5 dosis diferentes y con un testigo absoluto en un total de 60 plantas distribuidas al azar dentro del campo pero de baja eficacia de control.Colomerus vitis Pgst. also known as the grapevine bud mite is generally located within the buds of the vine, between the scales and in the meristem of the buds, which makes its control complicated by being difficult to assess. For its control there are different active ingredients and there haven´t been seen biological controllers. This work evaluated the population fluctuation of Colomerus vitis Pgst. In three vine fields from the company PROAGRO in the Qolca farm in Ica, the fields called 4A, 4C and 6F began to be evaluated when they had differences in their phenological conditions due to the different dates of application of cyanamide and pruning, with decreases being found before the application of active ingredients such as sulfur and variations due to the phenological state of the plant, temperature and cultural practices. Likewise, the presence of mites in shoots of different vigor was evaluated during the first nine weeks corresponding to the chargers of the previous campaign and where no significant differences were found. Additionally, a trial was made with unregistered chemicals for Colomerus vitis Pgst. in field 4 of the María Manuela estate belonging to the same company, in this trial 4 products were tested at 5 different doses and with an absolute control in a total of 60 plants distributed randomly within the field but with low control efficiency.Tesi

Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study

Background Weight loss trajectories after bariatric surgery vary widely between individuals, and predicting weight loss before the operation remains challenging. We aimed to develop a model using machine learning to provide individual preoperative prediction of 5-year weight loss trajectories after surgery. Methods In this multinational retrospective observational study we enrolled adult participants (aged $\ge$18 years) from ten prospective cohorts (including ABOS [NCT01129297], BAREVAL [NCT02310178], the Swedish Obese Subjects study, and a large cohort from the Dutch Obesity Clinic [Nederlandse Obesitas Kliniek]) and two randomised trials (SleevePass [NCT00793143] and SM-BOSS [NCT00356213]) in Europe, the Americas, and Asia, with a 5 year followup after Roux-en-Y gastric bypass, sleeve gastrectomy, or gastric band. Patients with a previous history of bariatric surgery or large delays between scheduled and actual visits were excluded. The training cohort comprised patients from two centres in France (ABOS and BAREVAL). The primary outcome was BMI at 5 years. A model was developed using least absolute shrinkage and selection operator to select variables and the classification and regression trees algorithm to build interpretable regression trees. The performances of the model were assessed through the median absolute deviation (MAD) and root mean squared error (RMSE) of BMI. Findings10 231 patients from 12 centres in ten countries were included in the analysis, corresponding to 30 602 patient-years. Among participants in all 12 cohorts, 7701 (75$\bullet$3%) were female, 2530 (24$\bullet$7%) were male. Among 434 baseline attributes available in the training cohort, seven variables were selected: height, weight, intervention type, age, diabetes status, diabetes duration, and smoking status. At 5 years, across external testing cohorts the overall mean MAD BMI was 2$\bullet$8 kg/m${}^2$ (95% CI 2$\bullet$6-3$\bullet$0) and mean RMSE BMI was 4$\bullet$7 kg/m${}^2$ (4$\bullet$4-5$\bullet$0), and the mean difference between predicted and observed BMI was-0$\bullet$3 kg/m${}^2$ (SD 4$\bullet$7). This model is incorporated in an easy to use and interpretable web-based prediction tool to help inform clinical decision before surgery. InterpretationWe developed a machine learning-based model, which is internationally validated, for predicting individual 5-year weight loss trajectories after three common bariatric interventions.Comment: The Lancet Digital Health, 202

Repertoire of Intensive Care Unit Pneumonia Microbiota

Despite the considerable number of studies reported to date, the causative agents of pneumonia are not completely identified. We comprehensively applied modern and traditional laboratory diagnostic techniques to identify microbiota in patients who were admitted to or developed pneumonia in intensive care units (ICUs). During a three-year period, we tested the bronchoalveolar lavage (BAL) of patients with ventilator-associated pneumonia, community-acquired pneumonia, non-ventilator ICU pneumonia and aspiration pneumonia, and compared the results with those from patients without pneumonia (controls). Samples were tested by amplification of 16S rDNA, 18S rDNA genes followed by cloning and sequencing and by PCR to target specific pathogens. We also included culture, amoeba co-culture, detection of antibodies to selected agents and urinary antigen tests. Based on molecular testing, we identified a wide repertoire of 160 bacterial species of which 73 have not been previously reported in pneumonia. Moreover, we found 37 putative new bacterial phylotypes with a 16S rDNA gene divergence ≥98% from known phylotypes. We also identified 24 fungal species of which 6 have not been previously reported in pneumonia and 7 viruses. Patients can present up to 16 different microorganisms in a single BAL (mean ± SD; 3.77±2.93). Some pathogens considered to be typical for ICU pneumonia such as Pseudomonas aeruginosa and Streptococcus species can be detected as commonly in controls as in pneumonia patients which strikingly highlights the existence of a core pulmonary microbiota. Differences in the microbiota of different forms of pneumonia were documented

Détermination des paramètres d'interaction non-covalente en solution par les méthodes électrophorétiques capillaires (champ d'application et performances. Rationalisation des protocoles)

PARIS-BIUSJ-Thèses (751052125) / SudocPARIS-BIUSJ-Physique recherche (751052113) / SudocSudocFranceF

Extraction et implémentation de stratégies expertes (application au contrôle de processus industriels)

VANNES-BU Sciences (562602102) / SudocPARIS3-BU (751052102) / SudocPARIS-Fondation MSH (751062301) / SudocSudocFranceF