Search results for "call"

In vitro biotechnology approaches now available for ‘beautiful’ vavilovia (Vavilovia formosa)

2014

BAP Pôle GEAPSI; Efficient in vitro propagation of Vavilovia formosa, plant regeneration from callus, protoplast isolation and culture to differentiated callus of V.formosa were developed and its relative nuclear DNA content by flow cytometry was established. The summation of biotechnology tools now available should foster evolutionary studies on the tribe Fabeae and, intime, V.formosa could be come a potential source of novel agronomic adaptive traits.

Des pierres pour une tombe princière

2022

Forgetting in immediate serial recall: time vs. interference. When the encoding rates determine the winner

2009

Study of acoustic properties and impact behavior of porous materials homogeneous type metal foams and inhomogeneous

2015

This work is concerned with the theoretical and experimental study of the acoustical properties of macroscopically homogenous and inhomogeneous porous media as well as their mechanical response to impacts. The model of Johnson - Champoux - Allard appeared adapted for the acoustical modeling. This model, associated with a recently developed approach involving the concept of parallel transfer matrices has lead to a new approach of macroscopically inhomogeneous porous materials based on “mixtures of materials”. Furthermore, a parametric study of the absorption coefficient as a function of porosity and frequency has been proposed. The maximums of absorption as well as the envelop of the absorpt…

Comparison of RK and confidence judgement ROCs in recognition memory.

2011

author cannot archive publisher's version/PDF; International audience; Several indicators have been used to differentiate familiarity and recollection processes. One dualist theory stipulates that it is possible to decide whether memories come from a feeling of knowing or from a conscious retrieval of the encoding and storage conditions (remembering). Another dualist theory is based on an indirect estimation of familiarity and recollection via the subjective confidence associated with recognition responses, and from an analysis of the derived receiver operating characteristics (ROC). In the present study, participants were presented with target words or faces that they subsequently had to r…

Evaluation Metric for Rate of Background Detection

2016

International audience; This paper proposes an evaluation metric which derive the effectiveness of background modeling algorithms. Background modeling is a key process on developing visual surveillance systems. The requirement of adapting to dynamic environments has motivated researchers to modify existing background modeling algorithms and develop new algorithms with better adaptability. Having the algorithms developed, credentials of each of the algorithms have to be assessed to exploit their effectiveness. Various evaluation metrics have been used for evaluating the rate of foreground extraction, foreground detection, and overall accuracy. However, the rate of background detection has no…

Relationships and linguistically sensitive teaching : Developing teacher practicum at Åbo Akademi University

2020

Project “Linguistically sensitive teaching in all classrooms” (Listiac) aims to make an impact on initial teacher education systems in Europe through action research. In line with European policies, the seven partner countries including Finland, Spain (the autonomous Basque country and Catalonia), Belgium, France, Slovenia, Lithuania and Portugal work together in providing competences and skills needed for handling linguistic diversity in our schools. Diversity education has been regarded nearly everywhere as an isolated ‘add-on’ course or study module (EC 2017). Thus, it has remained insufficiently mainstreamed as an integrated component of teaching practice. Listiac addresses this imbalan…

A novel homologous model for noninvasive monitoring of endometriosis progression.

2017

To date, several groups have generated homologous models of endometriosis through the implantation of endometrial tissue fluorescently labeled by green fluorescent protein (GFP) or tissue from luciferase-expressing transgenic mice into recipient animals, enabling noninvasive monitoring of lesion signal. These models present an advantage over endpoint models, but some limitations persist; use of transgenic mice is laborious and expensive, and GFP presents poor tissue penetration due to the relatively short emission wavelength. For this reason, a homologous mouse model of endometriosis that allows in vivo monitoring of generated lesions over time and mimics human lesions in recipient mice wou…

Obesity and cardiovascular risk: a call for action from the European Society of Hypertension Working Group of Obesity, Diabetes and the High-risk Pat…

2018

: Obesity predisposes for atrial fibrillation, heart failure, sudden cardiac death, renal disease and ischemic stroke, which are the main causes of cardiovascular hospitalization and mortality. As obesity and the cardiovascular effects on the vessels and the heart start early in life, even from childhood, it is important for health policies to prevent obesity very early before the disease manifestation emerge. Key roles in the prevention are strategies to increase physical exercise, reduce body weight and to prevent or treat hypertension, lipids disorders and diabetes earlier and efficiently to prevent cardiovascular complications.

A Deep Learning Model for Automatic Sleep Scoring using Multimodality Time Series

2021

Sleep scoring is a fundamental but time-consuming process in any sleep laboratory. Automatic sleep scoring is crucial and urgent to help address the increasing unmet need for sleep research. Therefore, this paper aims to develop an end-to-end deep learning architecture using raw polysomnographic recordings to automate sleep scoring. The proposed model adopts two-dimensional convolutional neural networks (2D-CNN) to automatically learn features from multi-modality signals, together with a "squeeze and excitation" block for recalibrating channel-wise feature responses. The learnt representations are finally fed to a softmax classifier to generate predictions for each sleep stage. The model pe…