4,025 research outputs found
Epidemic risk from friendship network data: an equivalence with a non-uniform sampling of contact networks
Contacts between individuals play an important role in determining how
infectious diseases spread. Various methods to gather data on such contacts
co-exist, from surveys to wearable sensors. Comparisons of data obtained by
different methods in the same context are however scarce, in particular with
respect to their use in data-driven models of spreading processes. Here, we use
a combined data set describing contacts registered by sensors and friendship
relations in the same population to address this issue in a case study. We
investigate if the use of the friendship network is equivalent to a sampling
procedure performed on the sensor contact network with respect to the outcome
of simulations of spreading processes: such an equivalence might indeed give
hints on ways to compensate for the incompleteness of contact data deduced from
surveys. We show that this is indeed the case for these data, for a
specifically designed sampling procedure, in which respondents report their
neighbors with a probability depending on their contact time. We study the
impact of this specific sampling procedure on several data sets, discuss
limitations of our approach and its possible applications in the use of data
sets of various origins in data-driven simulations of epidemic processes
Estimating the epidemic risk using non-uniformly sampled contact data
Many datasets describing contacts in a population suffer from incompleteness
due to population sampling and underreporting of contacts. Data-driven
simulations of spreading processes using such incomplete data lead to an
underestimation of the epidemic risk, and it is therefore important to devise
methods to correct this bias. We focus here on a non-uniform sampling of the
contacts between individuals, aimed at mimicking the results of diaries or
surveys, and consider as case studies two datasets collected in different
contexts. We show that using surrogate data built using a method developed in
the case of uniform population sampling yields an improvement with respect to
the use of the sampled data but is strongly limited by the underestimation of
the link density in the sampled network. We put forward a second method to
build surrogate data that assumes knowledge of the density of links within one
of the groups forming the population. We show that it gives very good results
when the population is strongly structured, and discuss its limitations in the
case of a population with a weaker group structure. These limitations highlight
the interest of measurements using wearable sensors able to yield accurate
information on the structure and durations of contacts
Contact patterns among high school students
Face-to-face contacts between individuals contribute to shape social networks
and play an important role in determining how infectious diseases can spread
within a population. It is thus important to obtain accurate and reliable
descriptions of human contact patterns occurring in various day-to-day life
contexts. Recent technological advances and the development of wearable sensors
able to sense proximity patterns have made it possible to gather data giving
access to time-varying contact networks of individuals in specific
environments. Here we present and analyze two such data sets describing with
high temporal resolution the contact patterns of students in a high school. We
define contact matrices describing the contact patterns between students of
different classes and show the importance of the class structure. We take
advantage of the fact that the two data sets were collected in the same setting
during several days in two successive years to perform a longitudinal analysis
on two very different timescales. We show the high stability of the contact
patterns across days and across years: the statistical distributions of numbers
and durations of contacts are the same in different periods, and we observe a
very high similarity of the contact matrices measured in different days or
different years. The rate of change of the contacts of each individual from one
day to the next is also similar in different years. We discuss the interest of
the present analysis and data sets for various fields, including in social
sciences in order to better understand and model human behavior and
interactions in different contexts, and in epidemiology in order to inform
models describing the spread of infectious diseases and design targeted
containment strategies.Comment: Supplementary Information at
http://s3-eu-west-1.amazonaws.com/files.figshare.com/1677807/File_S1.pd
Crypto-Verifying Protocol Implementations in ML
We intend to narrow the gap between concrete
implementations and verified models of cryptographic protocols.
We consider protocols implemented in F#, a variant of ML, and
verified using CryptoVerif, Blanchet's protocol verifier for
computational cryptography.
We experiment with compilers from F# code to CryptoVerif processes,
and from CryptoVerif declarations to F# code.
We present two case studies: an implementation of the Otway-Rees
protocol, and an implementation of a simplified password-based
authentication protocol. In both cases, we obtain concrete security
guarantees for a computational model closely related to
executable code
Contact patterns in a high school: a comparison between data collected using wearable sensors, contact diaries and friendship surveys
Given their importance in shaping social networks and determining how
information or diseases propagate in a population, human interactions are the
subject of many data collection efforts. To this aim, different methods are
commonly used, from diaries and surveys to wearable sensors. These methods show
advantages and limitations but are rarely compared in a given setting. As
surveys targeting friendship relations might suffer less from memory biases
than contact diaries, it is also interesting to explore how daily contact
patterns compare with friendship relations and with online social links. Here
we make progresses in these directions by leveraging data from a French high
school: face-to-face contacts measured by two concurrent methods, sensors and
diaries; self-reported friendship surveys; Facebook links. We compare the data
sets and find that most short contacts are not reported in diaries while long
contacts have larger reporting probability, with a general tendency to
overestimate durations. Measured contacts corresponding to reported friendship
can have durations of any length but all long contacts correspond to reported
friendships. Online links not associated to reported friendships correspond to
short face-to-face contacts, highlighting the different nature of reported
friendships and online links. Diaries and surveys suffer from a low sampling
rate, showing the higher acceptability of sensor-based platform. Despite the
biases, we found that the overall structure of the contact network, i.e., the
mixing patterns between classes, is correctly captured by both self-reported
contacts and friendships networks. Overall, diaries and surveys tend to yield a
correct picture of the structural organization of the contact network, albeit
with much less links, and give access to a sort of backbone of the contact
network corresponding to the strongest links in terms of cumulative durations
Encapsulation and Dynamic Modularity in the Pi-Calculus
We describe a process calculus featuring high level constructs for
component-oriented programming in a distributed setting. We propose an
extension of the higher-order pi-calculus intended to capture several important
mechanisms related to component-based programming, such as dynamic update,
reconfiguration and code migration. In this paper, we are primarily concerned
with the possibility to build a distributed implementation of our calculus.
Accordingly, we define a low-level calculus, that describes how the high-level
constructs are implemented, as well as details of the data structures
manipulated at runtime. We also discuss current and future directions of
research in relation to our analysis of component-based programming
Linguistics during the 19th century between description and norm: a study of the patois boulonnais by Daniel Haigneré
L’article s’intéresse aux deux tomes écrits par Daniel Haigneré (1824-1893) sur son patois natal bas-boulonnais (Pas-de-Calais) publiés en 1901 et 1903. La première partie s’intéresse à l’approche suivie par Haigneré dans son entreprise descriptive et montre qu’il s’est comporté en grammairien plutôt qu’en linguiste. La deuxième partie est une étude comparée de deux traductions de la Parabole de l’enfant retrouvé en patois boulonnais, publiées en 1807 et 1888, la deuxième étant de Haigneré lui-même.The paper deals with the two tomes by Daniel Haigneré (1824-1893) on his native “basboulonnais” dialect (Pas-de-Calais) published in 1901 and 1903. The first part focuses on the approach applied by Haigneré in his descriptive undertaking and shows that he reasoned as a grammarian rather than a linguist. The second part is a comparative study of two translations of the Parable of the Prodigal Son in Boulonnais dialect, published in 1807 and 1888, the latter due to Haigneré himself
- …