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

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 17 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

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

Network Analysis: Overview

Non peer reviewe

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