Search results for "automatic"
showing 10 items of 730 documents
Modeling Energy Demand Aggregators for Residential Consumers
2013
International audience; Energy demand aggregators are new actors in the energy scenario: they gather a group of energy consumers and implement a demand- response paradigm. When the energy provider needs to reduce the current energy demand on the grid, it can pay the energy demand aggregator to reduce the load by turning off some of its consumers loads or postponing their activation. Currently this operation involves only greedy energy consumers like industrial plants. In this paper we want to study the potential of aggregating a large number of small energy consumers like home users as it may happen in smart grids. In particular we want to address the feasibility of such approach by conside…
A Hybrid Control Strategy for Quadratic Boost Converters with Inductor Currents Estimation
2020
International audience; This paper deals with a control strategy for a DC-DC quadratic boost converter. In particular, a hybrid control scheme is proposed to encompass a control law and an observer for the estimation of the system states, based only on the measurements of the input and output voltages. Differently from classical control methods, where the controller is designed from a small-signal model, here the real model of the system is examined without considering the average values of the discrete variables. Using hybrid dynamical system theory, asymptotic stability of a neighborhood of the equilibrium point is established, ensuring practical stability of the origin, which contains es…
A time-varying observer for linear systems with asynchronous discrete-time measurements
2017
International audience; In this paper we propose a time-varying observer for a linear continuous-time plant with asynchronous discrete-time measurements. The proposed observer is contextualized in the hybrid systems framework providing an elegant setting for the proposed solution. In particular some theoretical tools are provided, in terms of LMIs, certifying asymptotic stability of a certain compact set where the estimation error is zero. Moreover the case of asynchronous measurements is considered, i.e. when the measurements are not provided in well defined time instants, but they occur at an arbitrary time in a certain time interval. A design procedure based on the numerical solution of …
Predicting limiting 'free sugar' consumption using an integrated model of health behavior.
2019
Excess intake of 'free sugars' is a key predictor of chronic disease, obesity, and dental ill health. Given the importance of determining modifiable predictors of free sugar-related dietary behaviors, we applied the integrated behavior change model to predict free sugar limiting behaviors. The model includes constructs representing 'reasoned' or deliberative processes that lead to action (e.g., social cognition constructs, intentions), and constructs representing 'non-conscious' or implicit processes (e.g., implicit attitudes, behavioral automaticity) as predictors of behavior. Undergraduate students (N = 205) completed measures of autonomous and controlled motivation, the theory of planned…
Rocker: Open source, easy-to-use tool for AUC and enrichment calculations and ROC visualization
2016
Receiver operating characteristics (ROC) curve with the calculation of area under curve (AUC) is a useful tool to evaluate the performance of biomedical and chemoinformatics data. For example, in virtual drug screening ROC curves are very often used to visualize the efficiency of the used application to separate active ligands from inactive molecules. Unfortunately, most of the available tools for ROC analysis are implemented into commercially available software packages, or are plugins in statistical software, which are not always the easiest to use. Here, we present Rocker, a simple ROC curve visualization tool that can be used for the generation of publication quality images. Rocker also…
Molecular basis of SARS-CoV-2 infection and rational design of potential antiviral agents: Modeling and simulation approaches
2020
International audience; The emergence in late 2019 of the coronavirus SARS-CoV-2 has resulted in the breakthrough of the COVID-19 pandemic that is presently affecting a growing number of countries. The development of the pandemic has also prompted an unprecedented effort of the scientific community to understand the molecular bases of the virus infection and to propose rational drug design strategies able to alleviate the serious COVID-19 morbidity. In this context, a strong synergy between the structural biophysics and molecular modeling and simulation communities has emerged, resolving at the atomistic level the crucial protein apparatus of the virus and revealing the dynamic aspects of k…
Conventional and semi-automatic histopathological analysis of tumor cell content for multigene sequencing of lung adenocarcinoma
2021
BACKGROUND: Targeted genetic profiling of tissue samples is paramount to detect druggable genetic aberrations in patients with non-squamous non-small cell lung cancer (NSCLC). Accurate upfront estimation of tumor cell content (TCC) is a crucial pre-analytical step for reliable testing and to avoid false-negative results. As of now, TCC is usually estimated on hematoxylin-eosin (H&E) stained tissue sections by a pathologist, a methodology that may be prone to substantial intra- and interobserver variability. Here we the investigate suitability of digital pathology for TCC estimation in a clinical setting by evaluating the concordance between semi-automatic and conventional TCC quantification…
Automatic sleep scoring: A deep learning architecture for multi-modality time series
2020
Background: Sleep scoring is an essential but time-consuming process, and therefore automatic sleep scoring is crucial and urgent to help address the growing unmet needs for sleep research. This paper aims to develop a versatile deep-learning architecture to automate sleep scoring using raw polysomnography recordings. Method: The model adopts a linear function to address different numbers of inputs, thereby extending model applications. Two-dimensional convolution neural networks are used to learn features from multi-modality polysomnographic signals, a “squeeze and excitation” block to recalibrate channel-wise features, together with a long short-term memory module to exploit long-range co…
Chemotherapy-triggered cathepsin B release in myeloid-derived suppressor cells activates the Nlrp3 inflammasome and promotes tumor growth
2012
International audience; Chemotherapeutic agents are widely used for cancer treatment. In addition to their direct cytotoxic effects, these agents harness the host's immune system, which contributes to their antitumor activity. Here we show that two clinically used chemotherapeutic agents, gemcitabine (Gem) and 5-fluorouracil (5FU), activate the NOD-like receptor family, pyrin domain containing-3 protein (Nlrp3)-dependent caspase-1 activation complex (termed the inflammasome) in myeloid-derived suppressor cells (MDSCs), leading to production of interleukin-1β (IL-1β), which curtails anticancer immunity. Chemotherapy-triggered IL-1β secretion relied on lysosomal permeabilization and the relea…
Balance Perturbations as a Measurement Tool for Trunk Impairment in Cross-Country Sit Skiing
2018
In cross-country sit-skiing, the trunk plays a crucial role in propulsion generation and balance maintenance. Trunk stability is evaluated by automatic responses to unpredictable perturbations; however, electromyography is challenging. The aim of this study was to identify a measure to group sit-skiers according to their ability to control the trunk. Seated in their competitive sit-ski, 10 male and 5 female Paralympic sit-skiers received 6 forward and 6 backward unpredictable perturbations in random order. k-means clustered trunk position at rest, delay to invert the trunk motion, and trunk range of motion significantly into 2 groups. In conclusion, unpredictable perturbations might quantif…