From SIR to SEAIRD: a novel data-driven modeling approach based on the Grey-box System Theory to predict the dynamics of COVID-19

Common compartmental modeling for COVID-19 is based on a priori knowledge and numerous assumptions. Additionally, they do not systematically incorporate asymptomatic cases. Our study aimed at providing a framework for data-driven approaches, by leveraging the strengths of the grey-box system theory or grey-box identification, known for its robustness in problem solving under partial, incomplete, or uncertain data. Empirical data on confirmed cases and deaths, extracted from an open source repository were used to develop the SEAIRD compartment model. Adjustments were made to fit current knowledge on the COVID-19 behavior. The model was implemented and solved using an Ordinary Differential Equation solver and an optimization tool. A cross-validation technique was applied, and the coefficient of determination $R^2$ was computed in order to evaluate the goodness-of-fit of the model. %to the data. Key epidemiological parameters were finally estimated and we provided the rationale for the construction of SEAIRD model. When applied to Brazil's cases, SEAIRD produced an excellent agreement to the data, with an %coefficient of determination $R^2$ $\geq 90\%$. The probability of COVID-19 transmission was generally high ($\geq 95\%$). On the basis of a 20-day modeling data, the incidence rate of COVID-19 was as low as 3 infected cases per 100,000 exposed persons in Brazil and France. Within the same time frame, the fatality rate of COVID-19 was the highest in France (16.4\%) followed by Brazil (6.9\%), and the lowest in Russia ($\leq 1\%$). SEAIRD represents an asset for modeling infectious diseases in their dynamical stable phase, especially for new viruses when pathophysiology knowledge is very limited

User-centered visual analysis using a hybrid reasoning architecture for intensive care units

One problem pertaining to Intensive Care Unit information systems is that, in some cases, a very dense display of data can result. To ensure the overview and readability of the increasing volumes of data, some special features are required (e.g., data prioritization, clustering, and selection mechanisms) with the application of analytical methods (e.g., temporal data abstraction, principal component analysis, and detection of events). This paper addresses the problem of improving the integration of the visual and analytical methods applied to medical monitoring systems. We present a knowledge- and machine learning-based approach to support the knowledge discovery process with appropriate analytical and visual methods. Its potential benefit to the development of user interfaces for intelligent monitors that can assist with the detection and explanation of new, potentially threatening medical events. The proposed hybrid reasoning architecture provides an interactive graphical user interface to adjust the parameters of the analytical methods based on the users' task at hand. The action sequences performed on the graphical user interface by the user are consolidated in a dynamic knowledge base with specific hybrid reasoning that integrates symbolic and connectionist approaches. These sequences of expert knowledge acquisition can be very efficient for making easier knowledge emergence during a similar experience and positively impact the monitoring of critical situations. The provided graphical user interface incorporating a user-centered visual analysis is exploited to facilitate the natural and effective representation of clinical information for patient care

Spatial Distribution of Norway Lobster Nephrops norvegicus (Linnaeus, 1758) Caught in Bouzedjar Bay and Associated Benthic Fauna.

Surveys were conducted in the field, near the port of Bouzedjar with fishermen, to acquire a knowledge of the spatial and depth distribution of the Norway lobster Nephrops norvegicus (Linneaus, 1758). To complete our investigations, we referred to the informations obtained during the Spanish trawling and acoustic survey which was carried out on the Algerian coast in 2004 aboard the Spanish research vessel R / V Vizconde de Eza. Analysis of the results reveals that the rich funds in norway lobster were located in the central area of the continental shelf between the immersions 250 and 400 m. It is thus observed very clearly that fish caught on these funds are mostly represented by Gadidae family; the most common species is the Greater forkbeard Phycis blennoides (B

Prenatal factors affecting the probability of survival between birth and weaning in rabbits

The aim of this study was to analyse the relationships between kit birth weight and litter size with kit survival from birth to weaning, and to estimate the effects of place of birth, nest quality, cannibalism, lactation, parity order, season and sex. A total of 1696 kits from 82 females of the ITLEV2006 synthetic line were used in this study. A logistic regression was performed. Kit birth weight was directly related to the probability of the kit’s survival from birth to weaning, and increasing birth weight by one gram increased the likelihood of kit survival by 8% to 10% (P<0.001). In line with the decrease in birth weight of kits as the number of kits at birth increases, litter size showed a negative relationship to the probability of survival from birth to weaning, and increasing the litter by one kit at birth decreased the probability of survival of the kits by 5% to 9% (P<0.05). Regarding effects, cannibalism events in the litter decreased the probability of survival of the kits in the first week of life (P<0.01). Being born in the cage decreased the probability of survival of the kits from birth to weaning, and kits born outside the nest had a lower chance of survival than those born inside the nest (P<0.01). The order of parturition had a positive effect on probability of survival of the kits from 5 days of age to weaning (P<0.05). Female kits had a lower chance of survival than male kits, but only until 5 days of age (P<0.01). The lactation status displayed a negative effect on the probability of survival of the kits in the first week of life, and kits gestated in lactating females had a lower chance of survival than those gestated in non-lactating females (P<0.05). In conclusion, the probability of kit survival in the first days after parturition was affected mainly by its weight at birth, litter size, cannibalism events, place of birth of kit, parity order, sex and lactation status, while the probability of kit survival at weaning was directly related to its weight at birth, litter size, place of birth of kit and parity order

De la modelisation au traitement de l'information médicale

L'unité de soins intensifs est un environnement complexe, l'exercice de la médecine y est spécifique. La prise en charge d'un patient pendant son séjour doit être suivie par des personnels de soins nombreux ayant une connaissance spécifique du domaine. Pour les aider, une pléthore d appareillages leur est dédiée. Ceux-ci sont en perpétuelle évolution. Dans la recherche d améliorations continues, la gestion automatisée de la pratique médicale se présente de plus en plus comme une évidence majeure et un enjeu d avenir. Au cours des trente dernière années, plusieurs tentatives de mise au point de suivis automatisés de protocoles ont été proposées. Cependant, la plupart de ces outils contiennent de nombreux problèmes non résolus, tant dans la traduction des protocoles textuels en forme formelle que dans le traitement des informations provenant des moniteurs biomédicaux. Pour palier aux biais des systèmes d aide au diagnostic, nous avons fait le choix d une approche différente. Nous avons défini un formalisme qui permet au personnel soignant de formaliser des connaissances aussi complexes et sensibles que les protocoles de soins. Nous avons travaillé pendant les trois dernières années avec le service d urgence des traumatisés crâniens du CHU de Fort-de-France afin d élaborer une chaîne complète de traitement en vue de l automatisation des guidelines en chambre, au chevet du patient. Nous proposons un ensemble de méthodes et d outils afin d établir la chaîne complète de traitement de suivi d un patient de son admission à sa sortie. Cette méthodologie est basée sur une station de chevet expérimentale (Aiddiag : AIDe aux DIAGnostic) centrée sur la patient et la pratique médicaleThe intensive care unit is a complex environment ; the practice of medicine is specific. The handling of a patient during his/her stay should be done by care staffs with specific knowledge. To help care staffs in their tasks, a plethora of equipment is dedicated to them. These equipments evolve constantly. In the search of a continuous improvement in this activity, the use of automated increasingly appears as a major support and a future challenge for medical practices. Over the last thirty years, several attempts have been made to develop automated guidelines. However, most of these tools are prone to numerous unsolved issues, both in the translation of textual protocols to formal forms and in the treatment of information coming from biomedical monitors. To overcome biases of diagnosis support systems, we chose a different approach. We have defined a formalism that allows caregivers formalizing medical knowledge. We spent the last three years in the intensive care unit of the university hospital of Fort de France with the aim to develop a complete chain of data processing. The final goal was the automation of guidelines in the room, at the patient s bedside. We propose a set of methods and tools to establish the complete chain of treatment follow-up for a patient, from admission to discharge. This methodology is based on a bedside experimental station: Aidiag (AIDe aux DIAGnostic). This station is a patient-centered tool that also adequately fits to medical routines. A genuine methodology for analyzing biomedical signals allows a first signal processing prior to their physiological interpretation. An artificial intelligence engine (Think!) and a new formalism (Oneah)SudocFranceF

Two-dimensional numerical study of temperature field in an anode supported planar SOFC: Effect of the chemical reaction

In the present work the effect of the chemical reaction on the temperature field in an anode supported planar SOFC is numerically studied by the aid of a two-dimensional mathematical model. For the model development the mass transport phenomena, the energy conservation, the species flow governed by Darcy's law and the electrochemistry are coupled. The finite difference method is used to solve numerically the system of the equations. The temperature field within each component of the SOFC (interconnection, cathode, anode and electrolyte) is calculated via the mathematical model which is implemented in FORTRAN language. The model results demonstrate the effect of different expressions of the chemical heat source, expressed in terms of enthalpy and entropy, on the temperature field and the location of the higher temperatures that occur within the SOFC during its operation. Copyright (C) 2010, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved

General analytical models characterizing MBOC modulated signal

International audienc

Genetic Analyses of Rabbit Survival and Individual Birth Weight

Genetic parameters of kit survival traits and birth weight were estimated on ITELV2006 synthetic line aimed at improving kit survival using a multiple trait linear and threshold model. Data on 1696 kits for survival at birth and at weaning, as well as individual birth weight and litter size were analysed. Genetic effects of kit survival traits and birth weight were estimated based on threshold and Gaussian models, respectively, using a Bayesian approach. The statistical model included, as fixed effects, parity, lactation status, season of farrowing, nest status, cannibalism in kit, place of kit&rsquo;s birth in the cage and gender, and adjustment for litter size. Posterior means of heritabilities for direct genetic effects of survival at birth and the entire nursing period, as well as birth weight, were 0.018, 0.023, and 0.088, respectively, and were increased when adjusted for litter size to 0.021, 0.027 and 0.146. Genetic correlation between survival traits was zero. Therefore, these traits can be treated genetically as different traits. Genetic correlation between direct effects of survival at birth and birth weight showed positive, but low, value (+0.134) and was increased to +0.535 when the traits were adjusted for litter size. No genetic correlation was found between survival at weaning and birth weight. These magnitudes of genetic parameter estimates suggested that there is substantial potential for the genetic improvement of kit survival at birth through selection for birth weight