A Hybrid Method Based on Quantum-enhanced RNN and Data Integration for the Prediction of COVID-19 Outbreak

Due to the continuous spread of COVID-19 worldwide, it is urgent, especially in the data science era, to develop accurate data driven decision-aided method to early detect its outbreak. Currently, Deep Learning and especially Recurrent Neural Networks (RNN) are one of the promising methods to accurately predict COVID-19 outbreak. However, designing an accurate RNN is always a challenging task because RNN often require big data and computational cost. To overcome these challenges, we propose in this paper a novel method to predict daily COVID-19 positive cases that consists of two steps: 1) data integration where medical data and weather data are integrated to improve both data quantity and quality especially when we deal with countries with less facilities of collecting data and 2) quantum improvement where quantum and classical RNN are integrated to provide super-calculator for the prediction. Experiments on six countries from Africa (Tunisia, Algeria, Senegal, Cameron, Niger, and Nigeria) indicate two main results. First, through data integration, a correlation between medical and weather data is detected where we note a real impact of the weather on COVID-19 outbreak. Second, compared with classical RNN, quantum-enhanced RNN trained on augmented data achieved the best results in terms of accuracy as well as root mean square error (RMSE) and it required the lowest time for training. Thus, our main contributions are i) to enrich medical data by weather data to improve data quality and quantity and ii) to enhance RNN by quantum layers to accurately and speedily forecast COVID-19 outbreak. All implementations and datasets are available online to the scientific community at https://github.com/nasriAhmed/Master_Covid.git

The RadioP1 – An Integrative Web Resource for Radioresistant Prokaryotes

The extremely radioresistant eubacterium Deinococcus radiodurans and the phenotypically related prokaryotes, whose genomes have been completely sequenced, are presently used as model species in several laboratories to study the lethal effects of DNA-damaging and protein-oxidizing agents, particularly the effects of ionizing radiation (IR). Unfortunately, providing relevant information about radioresistant prokaryotes (RP) in a neatly centralized and organized manner still remains a need. In this study, we designed RadioP1 Web resource (www.radiop.org.tn) to gather information about RP defined by the published literature with specific emphasis on (i) predicted genes that produce and protect against oxidative stress, (ii) predicted proteins involved in DNA repair mechanisms and (iii) potential uses of RP in biotechnology. RadioP1 allows the complete RP proteogenomes to be queried using various patterns in a user-friendly and interactive manner. The output data can be saved in plain text, Excel or HyperText Markup Language (HTML) formats for subsequent analyses. Moreover, RadioP1 provides for users a tool “START ANALYSIS”, including the previously described R-packages “drc” and “lethal”, to generate exponential or sigmoid survival curves with D10 and D50 values. Furthermore, when accessible, links to external databases are provided. Supplementary data will be included in the future when the sequences of other RP genomes will become available

Modélisation d'une population de mérous, effets du braconnage et de la migration

The aim of our work is to model the dynamics of a grouper population in a fishing zone, by holding account at the same time : the natural growth, the predation and the migrations, and to study the impact of the poaching on this populationL'objectif est de modéliser la dynamique d'une population de mérous dans un territoire de pêche d'une côte marine, en tenant compte à la fois de la croissance naturelle, de la pêche et des migrations, et d'étudier l'effet du braconnage sur cette populatio

Modélisation en dynamique des populations : Impacts des changements climatiques sur les populations de tiques

Epidemiology had an important development these last years allowing the resolution of a large number of problems and had good prediction on disease evolution. However, the transmission of several vector-borne diseases is closely connected to environmental protagonists, specially in the parasite-host interaction. Moreover, understanding the disease transmission is related to studying the ecology of all protagonists. These two levels of complexity(epidemiology and ecology) cannot be separated and have to be studied as a whole in a systematic way. Our goal is to understand the interaction of climate change on the evolution of a disease when the vector has ecological niche that depends on physiological state of development. We are particularly interested in tick vector diseases which are serious health problem affecting humans as well as domestic animals in many parts of the world. These infections are transmitted through a bite of an infected tick, and it appears that most of these infections are widely present in some wildlife species.L'épidémiologie a connu un développement important ces dernières années. Cette discipline a permis une meilleure compréhension del'évolution de maladies. Cependant, plusieurs maladies à transmission vectorielle sont étroitement liées aux protagonistes environnementaux. Ce constat est particulièrement vrai dans le contexte des interactions du parasite avec son hôte. De plus, comprendre la transmission de maladie est lié à l'étude de l'écologie de tous les protagonistes. Notre objectif est de comprendre l'influence du changement climatique sur l'évolution des maladies lorsque la niche écologique du vecteur dépend de l'état de développement physiologique de son hôte. Nous sommes particulièrement intéressés par les maladies vectorielles à tiques qui constituent un grave problème de santé touchant l'être humain et les animaux domestiques dans de nombreuses régions du monde. Ces infections sont généralement transmises par la piqûre d'une tique infectée et il apparaît que la plupart de ces infections sont largement présentées dans certaines espèces faunique

Modélisation en dynamique des populations: Impacts des changements climatiques sur les populations de tiques

International audienceEpidemiology had an important development these last years allowing the resolution of a large number of problems and had good prediction on disease evolution. However, the transmission of several vector-borne diseases is closely connected to environmental protagonists, specially in the parasite-host interaction. Moreover, understanding the disease transmission is related to studying the ecology of all protagonists. These two levels of complexity(epidemiology and ecology) cannot be separated and have to be studied as a whole in a systematic way. Our goal is to understand the interaction of climate change on the evolution of a disease when the vector has ecological niche that depends on physiological state of development. We are particularly interested in tick vector diseases which are serious health problem affecting humans as well as domestic animals in many parts of the world. These infections are transmitted through a bite of an infected tick, and it appears that most of these infections are widely present in some wildlife species.L'épidémiologie a connu un développement important ces dernières années. Cette discipline a permis une meilleure compréhension del'évolution de maladies. Cependant, plusieurs maladies à transmission vectorielle sont étroitement liées aux protagonistes environnementaux. Ce constat est particulièrement vrai dans le contexte des interactions du parasite avec son hôte. De plus, comprendre la transmission de maladie est lié à l'étude de l'écologie de tous les protagonistes. Notre objectif est de comprendre l'influence du changement climatique sur l'évolution des maladies lorsque la niche écologique du vecteur dépend de l'état de développement physiologique de son hôte. Nous sommes particulièrement intéressés par les maladies vectorielles à tiques qui constituent un grave problème de santé touchant l'être humain et les animaux domestiques dans de nombreuses régions du monde. Ces infections sont généralement transmises par la piqûre d'une tique infectée et il apparaît que la plupart de ces infections sont largement présentées dans certaines espèces faunique

Understanding hermaphrodite species through game theory

International audienceWe investigate the existence and stability of sexual strategies (sequential hermaphrodite, successive hermaphrodite or gonochore) at a proximate level. To accomplish this, we constructed and analyzed a general dynamical game model structured by size and sex. Our main objective is to study how costs of changing sex and of sexual competition should shape the sexual behavior of a hermaphrodite. We prove that, at the proximate level, size alone is insufficient to explain the tendency for a pair of prospective copulants to elect the male sexual role by virtue of the disparity in the energetic costs of eggs and sperm. In fact, we show that the stability of sequential vs. simultaneous hermaphrodite depends on sex change costs, while the stability of protandrous vs. protogynous strategies depends on competition cost

A general structured model of a hermaphrodite population.

International audienceBoth empirical and theoretical studies, have dealt with the question how to best optimize reproductive fitness for hermaphrodites, using models such as game theory or complicated energetic costs and benefits of mating displays. However, hermaphrodites exhibit a broad spectrum of sexual behaviors like simultaneous, sequential or lifetime gonochorist that cannot be explained using a unique formalism. A possible explanation of this diversity relies on the way these species maximize their fitness: Does the individual hermaphrodite split its time between strategies maximizing its instantaneous reproductive fitness or its evolutionary fitness? Here, we compare these two points of view and extend a game theoretical formalism to a sex allocation model that underlies all sexual behaviors as a result of a dynamic game whose payoff depends on the costs and benefits of sexual reproduction. Using this formalism, we prove that a simultaneous hermaphrodites strategy is stable even for high values of sex changing costs. Moreover, we prove that the stability of a sequential hermaphrodite is linked to the average energy allocated to the pure female strategy

In silico prediction of protein-protein interactions in human macrophages

International audienceBACKGROUND: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. RESULTS: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. CONCLUSION: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level

Smart Homes and Sensors for Surveillance and Preventive Education at Home: Example of Obesity

(1) Background: The aim of this paper is to show that e-health tools like smart homes allow the personalization of the surveillance and preventive education of chronic patients, such as obese persons, in order to maintain a comfortable and preventive lifestyle at home. (2) Technologies and methods: Several types of sensors allow coaching the patient at home, e.g., the sensors recording the activity and monitoring the physiology of the person. All of this information serves to personalize serious games dedicated to preventive education, for example in nutrition and vision. (3) Results: We built a system of personalized preventive education at home based on serious games, derived from the feedback information they provide through a monitoring system. Therefore, it is possible to define (after clustering and personalized calibration) from the at home surveillance of chronic patients different comfort zones where their behavior can be estimated as normal or abnormal and, then, to adapt both alarm levels for surveillance and education programs for prevention, the chosen example of application being obesity