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)

Network Analysis: Overview

Non peer reviewe

Timing interactions in social simulations: The voter model

The recent availability of huge high resolution datasets on human activities has revealed the heavy-tailed nature of the interevent time distributions. In social simulations of interacting agents the standard approach has been to use Poisson processes to update the state of the agents, which gives rise to very homogeneous activity patterns with a well defined characteristic interevent time. As a paradigmatic opinion model we investigate the voter model and review the standard update rules and propose two new update rules which are able to account for heterogeneous activity patterns. For the new update rules each node gets updated with a probability that depends on the time since the last event of the node, where an event can be an update attempt (exogenous update) or a change of state (endogenous update). We find that both update rules can give rise to power law interevent time distributions, although the endogenous one more robustly. Apart from that for the exogenous update rule and the standard update rules the voter model does not reach consensus in the infinite size limit, while for the endogenous update there exist a coarsening process that drives the system toward consensus configurations.Comment: Book Chapter, 23 pages, 9 figures, 5 table

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

Arthroscopic partial meniscectomy versus placebo surgery for a degenerative meniscus tear : a 2-year follow-up of the randomised controlled trial

Objective To assess if arthroscopic partial meniscectomy (APM) is superior to placebo surgery in the treatment of patients with degenerative tear of the medial meniscus. Methods In this multicentre, randomised, participant-blinded and outcome assessor-blinded, placebo-surgery controlled trial, 146 adults, aged 35-65 years, with knee symptoms consistent with degenerative medial meniscus tear and no knee osteoarthritis were randomised to APM or placebo surgery. The primary outcome was the between-group difference in the change from baseline in the Western Ontario Meniscal Evaluation Tool (WOMET) and Lysholm knee scores and knee pain after exercise at 24 months after surgery. Secondary outcomes included the frequency of unblinding of the treatment-group allocation, participants' satisfaction, impression of change, return to normal activities, the incidence of serious adverse events and the presence of meniscal symptoms in clinical examination. Two subgroup analyses, assessing the outcome on those with mechanical symptoms and those with unstable meniscus tears, were also carried out. Results In the intention-to-treat analysis, there were no significant between-group differences in the mean changes from baseline to 24 months in WOMET score: 27.3 in the APM group as compared with 31.6 in the placebo-surgery group (between-group difference, -4.3; 95% CI, -11.3 to 2.6); Lysholm knee score: 23.1 and 26.3, respectively (-3.2; -8.9 to 2.4) or knee pain after exercise, 3.5 and 3.9, respectively (-0.4; -1.3 to 0.5). There were no statistically significant differences between the two groups in any of the secondary outcomes or within the analysed subgroups. Conclusions In this 2-year follow-up of patients without knee osteoarthritis but with symptoms of a degenerative medial meniscus tear, the outcomes after APM were no better than those after placebo surgery. No evidence could be found to support the prevailing ideas that patients with presence of mechanical symptoms or certain meniscus tear characteristics or those who have failed initial conservative treatment are more likely to benefit from APM.Peer reviewe

Mediation and the Best Interests of the Child from the Child Law Perspective

What is the best interests of the child in family mediation and is mediation in the best interests of the child? In this article, I use child law and the United Nations Convention on the Rights of the Child combined with mediation theory to discuss these questions. Both mediation and the best interests of the child are open for multiple interpretations. Using facilitative and evaluative mediation theory and the legal concept ‘the best interests of the child’, I explore and compare the understandings of these concepts as they apply to family mediation. This includes a discussion of the advantages and disadvantages of facilitative as well as evaluative mediation orientations in terms of protecting the best interests of the child. Finnish court-connected family mediation is a combination of both mediation orientations, and the mediator is obliged to secure the best interests of the child. From a theoretical point of view, this seems to be a challenging combination.Peer reviewe

Dronedarone in high-risk permanent atrial fibrillation

BACKGROUND: Dronedarone restores sinus rhythm and reduces hospitalization or death in intermittent atrial fibrillation. It also lowers heart rate and blood pressure and has antiadrenergic and potential ventricular antiarrhythmic effects. We hypothesized that dronedarone would reduce major vascular events in high-risk permanent atrial fibrillation. METHODS: We assigned patients who were at least 65 years of age with at least a 6-month history of permanent atrial fibrillation and risk factors for major vascular events to receive dronedarone or placebo. The first coprimary outcome was stroke, myocardial infarction, systemic embolism, or death from cardiovascular causes. The second coprimary outcome was unplanned hospitalization for a cardiovascular cause or death. RESULTS: After the enrollment of 3236 patients, the study was stopped for safety reasons. The first coprimary outcome occurred in 43 patients receiving dronedarone and 19 receiving placebo (hazard ratio, 2.29; 95% confidence interval [CI], 1.34 to 3.94; P = 0.002). There were 21 deaths from cardiovascular causes in the dronedarone group and 10 in the placebo group (hazard ratio, 2.11; 95% CI, 1.00 to 4.49; P = 0.046), including death from arrhythmia in 13 patients and 4 patients, respectively (hazard ratio, 3.26; 95% CI, 1.06 to 10.00; P = 0.03). Stroke occurred in 23 patients in the dronedarone group and 10 in the placebo group (hazard ratio, 2.32; 95% CI, 1.11 to 4.88; P = 0.02). Hospitalization for heart failure occurred in 43 patients in the dronedarone group and 24 in the placebo group (hazard ratio, 1.81; 95% CI, 1.10 to 2.99; P = 0.02). CONCLUSIONS: Dronedarone increased rates of heart failure, stroke, and death from cardiovascular causes in patients with permanent atrial fibrillation who were at risk for major vascular events. Our data show that this drug should not be used in such patients. (Funded by Sanofi-Aventis; PALLAS ClinicalTrials.gov number, NCT01151137.) Copyright © 2011 Massachusetts Medical Society. All rights reserved.published_or_final_versio

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