1,056 research outputs found
Innovation Labs: Leveraging Openness for Radical Innovation?
A growing range of public, private and civic organisations, from Unicef through Nesta to NHS, now run units known as “innovation labs”. The hopeful assumption they share is that labs, by building on openness among other features, can generate promising solutions to grand challenges of systemic nature. Despite their seeming proliferation and popularisation, the underlying innovation principles embodied by labs have, however, received scant academic attention. This is a missed opportunity, because innovation labs appear to leverage openness for radical innovation in an unusual fashion. Indeed, in this exploratory paper we draw on original interview data and online self-descriptions to illustrate that, beyond convening “uncommon partners” across organisational boundaries, labs apply the principle of openness throughout the innovation process, including the experimentation and development phases. While the emergence of labs clearly forms part of a broader trend towards openness, we show how it transcends established conceptualisations of open innovation (Chesbrough et al., 2006), open science (David, 1998) or open government (Janssen et al., 2012)
MCRapper: Monte-Carlo Rademacher Averages for Poset Families and Approximate Pattern Mining
We present MCRapper, an algorithm for efficient computation of Monte-Carlo
Empirical Rademacher Averages (MCERA) for families of functions exhibiting
poset (e.g., lattice) structure, such as those that arise in many pattern
mining tasks. The MCERA allows us to compute upper bounds to the maximum
deviation of sample means from their expectations, thus it can be used to find
both statistically-significant functions (i.e., patterns) when the available
data is seen as a sample from an unknown distribution, and approximations of
collections of high-expectation functions (e.g., frequent patterns) when the
available data is a small sample from a large dataset. This feature is a strong
improvement over previously proposed solutions that could only achieve one of
the two. MCRapper uses upper bounds to the discrepancy of the functions to
efficiently explore and prune the search space, a technique borrowed from
pattern mining itself. To show the practical use of MCRapper, we employ it to
develop an algorithm TFP-R for the task of True Frequent Pattern (TFP) mining.
TFP-R gives guarantees on the probability of including any false positives
(precision) and exhibits higher statistical power (recall) than existing
methods offering the same guarantees. We evaluate MCRapper and TFP-R and show
that they outperform the state-of-the-art for their respective tasks
A mutation in KVLQT1 causes decreased sinus rate without evidence of autonomic nervous abnormalities
Association between infant swimming and rhinovirus-induced wheezing.
AIM
Infant swimming has been considered as a risk factor for wheezing, but the role that respiratory viruses play is unclear. We explored the effects of infant swimming on the risk of all wheezing illnesses and wheezing associated with rhinoviruses.
METHODS
We followed up a birth cohort of 1827 children until 17Â months of age, collecting data on infant swimming, other risk factors and physician-diagnosed bronchiolitis or recurrent wheezing. Viral diagnostics were performed in a subset of children with all respiratory tract infections.
RESULTS
Data on infant swimming were obtained for 1038 children, with viral follow-up for 635 children. At least one wheezing illness was documented in 45/469 (9.6%) swimming children versus 39/569 (6.9%) nonswimming children (p = 0.11), and rhinoviruses were associated with wheezing in 11/296 (3.7%) swimming children versus 4/339 (1.2%) nonswimming children (p = 0.04). In adjusted logistic regression analyses, swimming had an odds ratio of 1.71 (p = 0.05) for bronchiolitis and 3.57 (p = 0.06) for rhinovirus-associated wheezing. An association between infant swimming and rhinovirus-associated wheezing was detected for children with atopic eczema (p = 0.006).
CONCLUSION
There may be a link between infant swimming and rhinovirus-induced wheezing illnesses in atopic infants.</p
Effects of Surface Treatments on Environmentally-Assisted Cracking Susceptibility of Alloy 182 in BWR Environment
A Markov Chain Approach To Reconstruction Of Long Haplotypes
Haplotypes are important for association based gene mapping, but there are no practical laboratory methods for obtaining them directly from DNA samples. We propose simple Markov models for reconstruction of haplotypes for a given sample of multilocus genotypes. The models are aimed specifically for long marker maps, where linkage disequilibrium between markers may vary and be relatively weak. Such maps are ultimately used in chromosome or genome-wide association studies. Haplotyp
New approaches to model and study social networks
We describe and develop three recent novelties in network research which are
particularly useful for studying social systems. The first one concerns the
discovery of some basic dynamical laws that enable the emergence of the
fundamental features observed in social networks, namely the nontrivial
clustering properties, the existence of positive degree correlations and the
subdivision into communities. To reproduce all these features we describe a
simple model of mobile colliding agents, whose collisions define the
connections between the agents which are the nodes in the underlying network,
and develop some analytical considerations. The second point addresses the
particular feature of clustering and its relationship with global network
measures, namely with the distribution of the size of cycles in the network.
Since in social bipartite networks it is not possible to measure the clustering
from standard procedures, we propose an alternative clustering coefficient that
can be used to extract an improved normalized cycle distribution in any
network. Finally, the third point addresses dynamical processes occurring on
networks, namely when studying the propagation of information in them. In
particular, we focus on the particular features of gossip propagation which
impose some restrictions in the propagation rules. To this end we introduce a
quantity, the spread factor, which measures the average maximal fraction of
nearest neighbors which get in contact with the gossip, and find the striking
result that there is an optimal non-trivial number of friends for which the
spread factor is minimized, decreasing the danger of being gossiped.Comment: 16 Pages, 9 figure
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