Stability and sensitivity analysis of Be-CoDiS, an epidemiological model to predict the spread of human diseases between countries. Validation with data from the 2014-16 West African Ebola Virus Disease epidemic.

Ebola virus disease is a lethal human and primate disease that requires a particular attention from the international health authorities due to important recent outbreaks in some Western African countries and isolated cases in European and North-America continents. Regarding the emergency of this situation, various decision tools, such as mathematical models, were developed to assist the authorities to focus their efforts in important factors to eradicate Ebola. In a previous work, we have proposed an original deterministic spatial-temporal model, called Be-CoDiS (Between-Countries Disease Spread), to study the evolution of human diseases within and between countries by taking into consideration the movement of people between geographical areas. This model was validated by considering numerical experiments regarding the 2014-16 West African Ebola Virus Disease epidemic. In this article, we propose to perform a stability analysis of Be-CoDiS. Our first objective is to study the equilibrium states of simplified versions of this model, limited to the cases of one an two countries, and to determine their basic reproduction ratios. Then, in order to give some recommendations for the allocation of resources used to control the disease, we perform a sensitivity analysis of those basic reproduction ratios regarding the model parameters. Finally, we validate the obtained results by considering numerical experiments based on data from the 2014-16 West African Ebola Virus Disease epidemic.

The SEIQS stochastic epidemic model with external source of infection

This paper deals with a stochastic epidemic model for computer viruses with latent and quarantine periods, and two sources of infection: internal and external. All sojourn times are considered random variables which are assumed to be independent and exponentially distributed. For this model extinction and hazard times are analyzed, giving results for their Laplace transforms and moments. The transient behavior is considered by studying the number of times that computers are susceptible, exposed, infectious and quarantined during a period of time (0, t] and results for their joint and marginal distributions, moments and cross moments are presented. In order to give light this analysis, some numerical examples are showed.

Designing Regularizers and Architectures for Recurrent Neural Networks

Cette thèse contribue a la recherche vers l'intelligence artificielle en utilisant des méthodes connexionnistes. Les réseaux de neurones récurrents sont un ensemble de modèles séquentiels de plus en plus populaires capable en principe d'apprendre des algorithmes arbitraires. Ces modèles effectuent un apprentissage en profondeur, un type d'apprentissage machine. Sa généralité et son succès empirique en font un sujet intéressant pour la recherche et un outil prometteur pour la création de l'intelligence artificielle plus générale. Le premier chapitre de cette thèse donne un bref aperçu des sujets de fonds: l'intelligence artificielle, l'apprentissage machine, l'apprentissage en profondeur et les réseaux de neurones récurrents. Les trois chapitres suivants couvrent ces sujets de manière de plus en plus spécifiques. Enfin, nous présentons quelques contributions apportées aux réseaux de neurones récurrents. Le chapitre \ref{arxiv1} présente nos travaux de régularisation des réseaux de neurones récurrents. La régularisation vise à améliorer la capacité de généralisation du modèle, et joue un role clé dans la performance de plusieurs applications des réseaux de neurones récurrents, en particulier en reconnaissance vocale. Notre approche donne l'état de l'art sur TIMIT, un benchmark standard pour cette tâche. Le chapitre \ref{cpgp} présente une seconde ligne de travail, toujours en cours, qui explore une nouvelle architecture pour les réseaux de neurones récurrents. Les réseaux de neurones récurrents maintiennent un état caché qui représente leurs observations antérieures. L'idée de ce travail est de coder certaines dynamiques abstraites dans l'état caché, donnant au réseau une manière naturelle d'encoder des tendances cohérentes de l'état de son environnement. Notre travail est fondé sur un modèle existant; nous décrivons ce travail et nos contributions avec notamment une expérience préliminaire.

Recurrent bacteremia with Streptococcus dysgalactiae: a case-control study.

Beta-hemolytic streptococci of groups C and G, designated as Streptococcus dysgalactiae (SD), can cause severe and recurring invasive infections. In this case-control study, we aimed to identify clinical and molecular risk factors for recurrence of SD bacteremia. Twenty-two cases of recurrent SD bacteremia were identified, and median time between episodes was 6 months. The most frequent clinical manifestation was skin and soft tissue infection. Cases and 92 controls, with single-episode SD bacteremia, showed similar demographics, had similar Charlson comorbidity scores, and had similar clinical presentations. Thirty-day fatality was 13% among controls, whereas none of 22 cases died. In 19 cases (86%), the same emm type was encountered in both episodes. SD isolates from recurrent episodes and from single episodes had a similar emm type distribution. Thus, we did not identify clinical risk factors for recurrences. The high proportion of identical emm types in recurrent episodes indicates a host-specific colonization.

Effect of Cage-Induced Stereotypies on Measures of Affective State and Recurrent Perseveration in CD-1 and C57BL/6 Mice.

Stereotypies are abnormal repetitive behaviour patterns that are highly prevalent in laboratory mice and are thought to reflect impaired welfare. Thus, they are associated with impaired behavioural inhibition and may also reflect negative affective states. However, in mice the relationship between stereotypies and behavioural inhibition is inconclusive, and reliable measures of affective valence are lacking. Here we used an exploration based task to assess cognitive bias as a measure of affective valence and a two-choice guessing task to assess recurrent perseveration as a measure of impaired behavioural inhibition to test mice with different forms and expression levels of stereotypic behaviour. We trained 44 CD- 1 and 40 C57BL/6 female mice to discriminate between positively and negatively cued arms in a radial maze and tested their responses to previously inaccessible ambiguous arms. In CD-1 mice (i) mice with higher stereotypy levels displayed a negative cognitive bias and this was influenced by the form of stereotypy performed, (ii) negative cognitive bias was evident in back-flipping mice, and (iii) no such effect was found in mice displaying bar-mouthing or cage-top twirling. In C57BL/6 mice neither route-tracing nor bar-mouthing was associated with cognitive bias, indicating that in this strain these stereotypies may not reflect negative affective states. Conversely, while we found no relation of stereotypy to recurrent perseveration in CD-1 mice, C57BL/6 mice with higher levels of route-tracing, but not bar-mouthing made more repetitive responses in the guessing task. Our findings confirm previous research indicating that the implications of stereotypies for animal welfare may strongly depend on the species and strain of animal as well as on the form and expression level of the stereotypy. Furthermore, they indicate that variation in stereotypic behaviour may represent an important source of variation in many animal experiments.

Designing Regularizers and Architectures for Recurrent Neural Networks

Cette thèse contribue a la recherche vers l'intelligence artificielle en utilisant des méthodes connexionnistes. Les réseaux de neurones récurrents sont un ensemble de modèles séquentiels de plus en plus populaires capable en principe d'apprendre des algorithmes arbitraires. Ces modèles effectuent un apprentissage en profondeur, un type d'apprentissage machine. Sa généralité et son succès empirique en font un sujet intéressant pour la recherche et un outil prometteur pour la création de l'intelligence artificielle plus générale. Le premier chapitre de cette thèse donne un bref aperçu des sujets de fonds: l'intelligence artificielle, l'apprentissage machine, l'apprentissage en profondeur et les réseaux de neurones récurrents. Les trois chapitres suivants couvrent ces sujets de manière de plus en plus spécifiques. Enfin, nous présentons quelques contributions apportées aux réseaux de neurones récurrents. Le chapitre \ref{arxiv1} présente nos travaux de régularisation des réseaux de neurones récurrents. La régularisation vise à améliorer la capacité de généralisation du modèle, et joue un role clé dans la performance de plusieurs applications des réseaux de neurones récurrents, en particulier en reconnaissance vocale. Notre approche donne l'état de l'art sur TIMIT, un benchmark standard pour cette tâche. Le chapitre \ref{cpgp} présente une seconde ligne de travail, toujours en cours, qui explore une nouvelle architecture pour les réseaux de neurones récurrents. Les réseaux de neurones récurrents maintiennent un état caché qui représente leurs observations antérieures. L'idée de ce travail est de coder certaines dynamiques abstraites dans l'état caché, donnant au réseau une manière naturelle d'encoder des tendances cohérentes de l'état de son environnement. Notre travail est fondé sur un modèle existant; nous décrivons ce travail et nos contributions avec notamment une expérience préliminaire.

A contribution to the natural history of scarlatina derived from observations on the London epidemic of 1887-1888 ...

Mode of access: Internet.

The recurrent shortage of registered nurses : a new look at the issues.

Mode of access: Internet.

Recurrent maladies in scholarly writing.

Mode of access: Internet.

The typhus epidemic in eastern Macedonia,

Mode of access: Internet.

The epidemic threshold and contact number with implications for optimal vaccination strategies /

Thesis (Ph.D.)--Cornell University, May, 2000.

A practical essay on the small-pox : wherein a method of preparing the body before the disease comes on, and of deriving the variolous matter from the vital to the remote parts of the body after the accession ... to which is added An account of the principal variations of the weather and the concomitant epidemic diseases ... /

Mode of access: Internet.

A brief history of epidemic and pestilential diseases : with the principal phenomena of the physical world, which precede and accompany them, and observations deduced from the facts stated : in two volumes /

Mode of access: Internet.

Sketches of the most prevalent diseases of India : comprising, a treatise on the epidemic cholera of the East, statistical and topographical reports of the diseases in the different divisions of the army under the Madras presidency ... : iullustrated by tables and plates /

Mode of access: Internet.