Search results for "RECOGNITION"
showing 10 items of 3607 documents
T Cells Integrate Local and Global Cues to Discriminate between Structurally Similar Antigens
2015
International audience; T lymphocytes' ability to discriminate between structurally related antigens has been attributed to the unique signaling properties of the T cell receptor. However, recent studies have suggested that the output of this discrimination process is conditioned by environmental cues. Here, we demonstrate how the IL-2 cytokine, collectively generated by strongly activated T cell clones, can induce weaker T cell clones to proliferate. We identify the PI3K pathway as being critical for integrating the antigen and cytokine responses and for controlling cell-cycle entry. We build a hybrid stochastic/deterministic computational model that accounts for such signal synergism and …
A Viscoelastic Model for the Long-Term Deflection of Segmental Prestressed Box Girders
2017
Most of segmental prestressed concrete box girders exhibit excessive multidecade deflections unforeseeable by past and current design codes. To investigate such a behavior, mainly caused by creep and shrinkage phenomena, an effective finite element (FE) formulation is presented in this article. This formulation is developed by invoking the stationarity of an energetic principle for linear viscoelastic problems and relies on the Bazant creep constitutive law. A case study representative of segmental prestressed concrete box girders susceptible to creep is also analyzed in the article, that is, the Colle Isarco viaduct. Its FE model, based on the aforementioned energetic formulation, was succ…
A Guide to Designing a Memory fMRI Paradigm for Pre-surgical Evaluation in Temporal Lobe Epilepsy
2020
There has been increasing interest in the clinical and experimental use of memory functional Magnetic Resonance Imaging (fMRI). The 2017 American Academy of Neurology practice guidelines on the use of pre-surgical cognitive fMRI suggests that verbal memory fMRI could be used to lateralize memory functions in people with Temporal Lobe Epilepsy (TLE) and should be used to predict post-operative verbal memory outcome. There are however technical and methodological considerations, to optimize both the sensitivity and specificity of this imaging modality. Below we discuss these constraints and suggest recommendations to consider when designing a memory fMRI paradigm.
Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps
2017
Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly diffe…
Ventricular Fibrillation and Tachycardia detection from surface ECG using time-frequency representation images as input dataset for machine learning
2017
Parameter-less ventricular fibrillation detection with time-frequency representation.Time-frequency representations are treated as images for a classifier.A comparison for four classifiers demonstrates the validity of the proposed method.The proposed technique could be applied to any signal and research field.This is a novel approach to signal analysis. Background and objectiveTo safely select the proper therapy for Ventricullar Fibrillation (VF) is essential to distinct it correctly from Ventricular Tachycardia (VT) and other rhythms. Provided that the required therapy would not be the same, an erroneous detection might lead to serious injuries to the patient or even cause Ventricular Fibr…
Multi-feature Counting of Dense Crowd Image Based on Multi-column Convolutional Neural Network
2020
The crowd counting task is an important research problem. Now more and more people are concerned about safety issues. When the population density reaches a very high peak, the population density counts, the alarm is sent out, and the crowds are diverted. The trampling of the Shanghai New Year’s stampede will not happen again. The final density map is produced by two steps: at first, extract feature maps from multiple layers, and then adjust their output so that they are all the same size, all these resized layers are combined into the final density map. We also used texture features and target edge detection to reduce the loss of density map detail to better integrate with our convolutional…
Perspectives on freedom : normative and political views on the preconditions of a free democratic society
2018
In today’s society we seem to be confronted with renewed struggles about the ideal of freedom. After decades of wide-spread belief in the benefits of globalization, marketization, open borders, and de-regulation, we are now facing a countermovement consisting of various forms of populism and nationalism that promise to restore borders, security and identity. Both movements seem to be informed by problematic conceptions of freedom: globalization and marketization are often accompanied by an ‘atomistic’ picture of society, whereby self-sufficient individuals compete in free markets, which neglects the social, political and cultural preconditions of individual freedom, and this can lead to fee…
Multiscale modeling of polycrystalline materials: A boundary element approach to material degradation and fracture
2015
Abstract In this work, a two-scale approach to degradation and failure in polycrystalline materials is proposed. The formulation involves the engineering component level (macro-scale) and the material grain level (micro-scale). The macro-continuum is modeled using a three-dimensional boundary element formulation in which the presence of damage is formulated through an initial stress approach to account for the local softening in the neighborhood of points experiencing degradation at the micro-scale. The microscopic degradation is explicitly modeled by associating Representative Volume Elements (RVEs) to relevant points of the macro continuum, for representing the polycrystalline microstruct…
Quantifying the Potential Economic Benefits of Flexible Industrial Demand in the European Power System
2018
The envisaged decarbonization of the European power system introduces complex techno-economic challenges to its operation and development. Demand flexibility can significantly contribute in addressing these challenges and enable a cost-effective transition to the low-carbon future. Although extensive previous work has analyzed the impacts of residential and commercial demand flexibility, the respective potential of the industrial sector has not yet been thoroughly investigated despite its large size. This paper presents a novel, whole-system modeling framework to comprehensively quantify the potential economic benefits of flexible industrial demand (FID) for the European power system. This …
When a new technological product launching fails: A multi-method approach of facial recognition and E-WOM sentiment analysis
2018
Abstract The dual aim of this research is, firstly, to analyze the physiological and unconscious emotional response of consumers to a new technological product and, secondly, link this emotional response to consumer conscious verbal reports of positive and negative product perceptions. In order to do this, biometrics and self-reported measures of emotional response are combined. On the one hand, a neuromarketing experiment based on the facial recognition of emotions of 10 subjects, when physical attributes and economic information of a technological product are exposed, shows the prevalence of the ambivalent emotion of surprise. On the other hand, a nethnographic qualitative approach of sen…