International audience

This paper compares two statistical models of location within a smart flat during the day. The location is then identified with a task executed normally or repeated pathologically, e.g., in case of Alzheimer disease (AD), whereas a task persistence parameter assesses tendency to perseverate. Compared with a Pólya's urns derived approach, the Markovian one is more effective and offers up to 98 percent of good prediction using only the last known location but distinguishing days of week. To extend these results to a multisensor context, some difficulties must be overcome. An external knowledge is made from a set of observable random variables provided by body sensors and organized either in a Bayesian network or in a reference knowledge base system (KBS) containing the person's actimetric profile. When data missed or errors occurred, an estimate of the joint probabilities of these random variables and hence the probability of all events appearing in the network or the KBS was developed and corrects the bias of the Lancaster and Zentgraf classical approach which in certain circumstances provides negative estimates. Finally, we introduce a correction corresponding to a possible loss of the person's synchronization with the nycthemeral (day versus night) zeitgebers (synchronizers) to avoid false alarms.

Free of most social constraints, elderly people tend to perform activities of daily living following the same sequence. This paper proposes a method for medical telesurveillance to detect and quantify a nycthemeral shift in this daily routine. While this common phenomenon is mostly mild, in acute cases, however, it may reveal a pathological behavior requiring a rapid medical examination. This method allows to compare two sequences of activities using the Hamming distance and to interpret the result according to the Gumbel distribution. It may be used to compare either consecutive sequences thereby taking into account evolution in the habits or a sequence to the person's individual activity profile to detect dementia's onset. In this early stage, only elementary activities were considered. That is the reason why location data were used to monitor the person's nycthemeral rhythm of activity. IR sensors placed in her own flat allowed us to follow-up the inhabitant's successive activities. Improvements of this method have already been planned. They include the use of a multi-sensors network to monitor both actimetric (location, movement, posture) and physiological nycthemeral rhythms (ECG, respiratory frequency) and to detect the use of particular items (fridge, chairs, bed). This more sophisticated sensors network will allow us to monitor more complex tasks execution and then to detect pathological behaviors such as perseveration in a task or wandering. On the other hand, multiplying sensors will require more storage capacities and the use of time-consuming data fusion tools. Therefore, a classification phase will be necessary to reduce as possible the number of relevant sensors.

The paper deals with how a developing country like Iran can prevent socio-economic impacts of demographic and disability transition. This period started between 1991 and 1996 with a rapid decline of fertility and mortality rates and still continues today. This demographic stage constitutes the window or bonus of the best opportunity for Iranian policy makers to do their plan for rapid aging of population. So we developed DOPAMID as the first dynamic projection model from socio-demographic indicators such as fertility rate, mortality rate, sex and age and marriage date of Iranian people. DOPAMID is able to show the evolution of the numbers of dependent aged people. New theories about aging of population describe the importance of disability transition as well as health and demographic ones. So we carry out this study to know when disability transition happens in Iran, how many frail people will live in future and how many family and/or sociomedical carers they will need for ensuring a good quality of life.

T-Cell antigen Receptor (TR) repertoire is generated through rearrangements of V and J genes encoding alpha and beta chains. The quantification and frequency for every V-J combination during ontogeny and development of the immune system remain to be precisely established. We have addressed this issue by building a model able to account for Valpha-Jalpha gene rearrangements during thymus development of mice. So we developed a numerical model on the whole TRA/TRD locus, based on experimental data, to estimate how Valpha and Jalpha genes become accessible to rearrangements. The progressive opening of the locus to V-J gene recombinations is modeled through windows of accessibility of different sizes and with different speeds of progression. Furthermore, the possibility of successive secondary V-J rearrangements was included in the modelling. The model points out some unbalanced V-J associations resulting from a preferential access to gene rearrangements and from a non-uniform partition of the accessibility of the J genes, depending on their location in the locus. The model shows that 3 to 4 successive rearrangements are sufficient to explain the use of all the V and J genes of the locus. Finally, the model provides information on both the kinetics of rearrangements and frequencies of each V-J associations. The model accounts for the essential features of the observed rearrangements on the TRA/TRD locus and may provide a reference for the repertoire of the V-J combinatorial diversity.

The paper deals with medical temporal scales based on both the chronologic time of the physician who observes the patient, the proper inner time of the patient (related to the circadian rhythms of his major physiologic variables) and the disease duration, estimated here by using the hospital stay (for this pathology) duration. We show that patients inside homogeneous Diagnosis Related Groups can be treated through a network of co-expertise identified by using Internet facilities and based on medical co-publication networks.

This paper presents an approach of location model deriving from language models existing in speech recognition research. The purpose is to applicate existing model in speech recognition to predict location of an elderly person. Using statistics, the model offers up to 98.03% of good prediction location, considering only the last second of location but distinguishing days of week. Simpler than Polya's urns derived approach, this approach seems to be a good way of location modelling.

This paper describes a general random mechanism of vanishing the central part of a concatenated chain made of characters in an alphabet of cardinal 4. This mechanism allows to obtain chains shorter than the initial one with some constraint for the start and the end of the resulting chain. An application in immunology of this chain shortening procedure will be proposed, describing the genesis of new functional genes from the TCRAD locus on the chromosome 14 in mice and humans encoding immune receptors.

The paper deals with a methodology proposed to establish a community based information system from comprehensive geriatric assessment of community dwelling elderly in a developing country, to predict an early identification of frailty, and a risk stratification of future adverse outcomes in order to prevent and intervene diseases and disabilities of target population in home care health service schedule.

If we consider the regulatory networks used in systems biology (especially in neural and genetic networks), we observe certain regularities in their architecture, namely the occurrence of interaction motifs, i.e. of oriented sub-graphs relating their elements with the same interaction scheme. We propose here to describe some of these motifs we can consider as universal because they are often met in the regulatory networks architecture, and to study their main robustness properties (called also structural stability), i.e. their ability to keep after topological or dynamical perturbations, their essential asymptotic features, as their attractors number, shape and behaviour, like their periodicity.

This paper aims at giving a general and precise method to achieve a good understanding of discrete dynamical systems by focusing on their attraction basins. This work is the result of a previous one which has permitted to show that the structural changes introduced by fixed boundary conditions on regulatory networks could directly and strongly influence the properties of their attraction basins. In this paper, we give an exhaustive stochastic study protocol to understand what happens on attraction basins of dynamical systems when the latter are subjected to state perturbations. Then, we give an application of this protocol by giving the results obtained on a specific system which is a model of the Arabidopsis thaliana flower’s morphogenesis, depending on a specific boundary condition.

If we watch elderly people at home for health or security purposes, we need a reliable pervasive information from a domestic network of localizing sensors allowing to follow the different locations at which the dependent persons can be detected. The data recorded can be treated as the sequence of color coded numbers of balls (symbolizing rooms) taken in a Polya's urn, in which the persistence of the presence in a room is taken into account by adding a certain number of balls of the same color as the ball just drawn. We discuss the pertinency of such a procedure to early detect sudden or chronic changes in the parameters values of the random process made of the succession of ball numbers and we use it to trigger alarms, whose level depends on the real biological age of the elderly people watched at home.

If we consider the regulatory networks used in systems biology, we observe certain regularities in their architecture, namely the occurrence of interaction motifs, i.e. of oriented sub-graphs relating their elements with the same interaction scheme. We propose to describe some of these universal motifs and to study their main dynamical properties especially concerning their robustness (called also structural stability), i.e. their ability to keep after topological or dynamical perturbations, their essential asymptotic features, as their attractors number, shape and behavior, like their periodicity.

A biofeedback system whose underlying principle consists in supplying the user with supplementary sensory information related to foot sole pressure distribution through a tongue-placed tactile output device was recently developed for improving balance. The purpose of this study was to unravel the underlying control mechanisms involved in the regulation of the centre of foot pressure (CoP) displacements during upright quiet standing with this biofeedback system. Ten young healthy adults were asked to stand as immobile as possible with their eyes closed in two conditions of No-biofeedback and Biofeedback. CoP displacements, recorded using a force platform, were processed through a space-time domain analysis and modeled as fractional Brownian motions according to the procedure of stabilogram-diffusion analysis (SDA). The space-time domain analysis showed decreased CoP displacements in the Biofeedback relative to No-biofeedback condition. Complementary, the SDA showed decreased spatiotemporal threshold at which corrective mechanisms are called into play and an increased degree of control of the CoP displacements in the Biofeedback relative to No-biofeedback condition. The present findings evidence that the effectiveness of the biofeedback in decreasing the CoP displacements during upright quiet standing stems from an increased contribution and efficiency of anti-persistent mechanisms (feedback control) involved in the regulation of the CoP displacements.

BACKGROUND: Adaptative immune repertoire diversity in vertebrate species is generated by recombination of variable (V), diversity (D) and joining (J) genes in the immunoglobulin (IG) loci of B lymphocytes and in the T cell receptor (TR) loci of T lymphocytes. These V-J and V-D-J gene rearrangements at the DNA level involve recombination signal sequences (RSS). Whereas many data exist, they are scattered in non specialized resources with different nomenclatures (eg. flat files) and are difficult to extract. DESCRIPTION: IMGT/GeneInfo is an online information system that provides, through a user-friendly interface, exhaustive information resulting from the complex mechanisms of T cell receptor V-J and V-D-J recombinations. T cells comprise two populations which express the alphabeta and gammadelta TR, respectively. The first version of the system dealt with the Homo sapiens and Mus musculus TRA and TRB loci whose gene rearrangements allow the synthesis of the alphabeta TR chains. In this paper, we present the second version of IMGT/GeneInfo where we complete the database for the Homo sapiens and Mus musculus TRG and TRD loci along with the introduction of a quality control procedure for existing and new data. We also include new functionalities to the four loci analysis, giving, to date, a very informative tool which allows to work on V(D)J genes of all TR loci in both human and mouse species. IMGT/GeneInfo provides more than 59,000 rearrangement combinations with a full gene description which is freely available at http://imgt.cines.fr/GeneInfo. CONCLUSION: IMGT/GeneInfo allows all TR information sequences to be in the same spot, and are now available within two computer-mouse clicks. This is useful for biologists and bioinformaticians for the study of T lymphocyte V(D)J gene rearrangements and their applications in immune response analysis.

At the time of hospitalization, it is essential to evaluate the general health status of a patient and to follow up the trends during therapy. Our work is focused on a set of tools for the measurement of patient activity. In this paper, we propose a few indicators of the patient activities of daily living, such as mobility, agitation, repartitions of stays, and displacements. As a result of this work, a diagnostic system was developed that could lead to a deeper knowledge of human activity rhythms in normal situations.

We study the relationships between the positive and negative circuits of the connection graph and the fixed points of discrete neural networks (DNNs). As main results, we give necessary conditions and sufficient conditions for the existence of fixed points in a DNN. Moreover, we exhibit an upper bound for the number of fixed points in terms of the structure and number of positive circuits in the connection graph. This allows the determination of the maximum capacity for storing vectors in DNNs as fixed points, depending on the architecture of the network.

The human genome with its 23 pairs of chromosomes, is the result of evolution. This evolution has been ruled by the mutation process and also by the physiological and pathological reorganization of the genomic material inside or between the chromosomes, which are conditioning the genomic variability. This reorganization is starting at singular points on the short or long chromosomic arms, called crossing-over, or translocations, insertions, break points. In this paper, we will show that these points, also called weak points or hot spots of the genome are correlated, independently of their origin. In addition, we will give some properties of the genetic interaction matrices in terms of attractors of the genetic expression dynamics.

The human genome has evolved from a primitive genome to its present state dispatched along the 23 pairs of chromosomes. This evolution has been ruled by the mutation process and also by the physiological and pathological reorganization of the genomic material inside or between the chromosomes, which condition the genomic variability. This reorganization starts at singular points on the short or long chromosomic arms, called crossover, translocation, insertion or break-points. In this paper, we show that these points, also called "weak points" or "hot spots" of the genome, are correlated independently of their origin. In addition, we give some properties of the interaction matrices in terms of attractors (generalizing some earlier results to the discrete case).

A model of a neural network of the auditory system is presented; it is based on the representation of the temporal activity of N fibers by a random field defined on a finite set. Our simulations show the behavior of the network in response to different stimuli; we investigate the duration of the transient times of the output random field and establish the link between these durations and a context effect. The results are consistent with the characteristics of a speech signal, and we could compare some of them to typical perceptive measures made on stop consonnants.