Do academic laboratories correspond to scientific communities? Evidence from a large European university.

Although acknowledged as central in the economic literature, the issue of intra academic collaboration has been, insofar, relatively overlooked. This paper fills this gap by stressing the importance of communities in academic research. By analysing the publication behavior of researchers from a large European scientific university, we argue that in certain cases, the community level constitutes a relevant level for analysing the collaborative nature of scientific investigation. Indeed, the reality of research collaborations doesn’t always fit the institutional division of academic work provided by laboratories.Economics of Science, Knowledge Intensive Communities, Academic Collaborations, Social Network Analysis.

Critical Team Composition Issues for Long-Distance and Long-Duration Space Exploration: A Literature Review, an Operational Assessment, and Recommendations for Practice and Research

Prevailing team effectiveness models suggest that teams are best positioned for success when certain enabling conditions are in place (Hackman, 1987; Hackman, 2012; Mathieu, Maynard, Rapp, & Gilson, 2008; Wageman, Hackman, & Lehman, 2005). Team composition, or the configuration of member attributes, is an enabling structure key to fostering competent teamwork (Hackman, 2002; Wageman et al., 2005). A vast body of research supports the importance of team composition in team design (Bell, 2007). For example, team composition is empirically linked to outcomes such as cooperation (Eby & Dobbins, 1997), social integration (Harrison, Price, Gavin, & Florey, 2002), shared cognition (Fisher, Bell, Dierdorff, & Belohlav, 2012), information sharing (Randall, Resick, & DeChurch, 2011), adaptability (LePine, 2005), and team performance (e.g., Bell, 2007). As such, NASA has identified team composition as a potentially powerful means for mitigating the risk of performance decrements due to inadequate crew cooperation, coordination, communication, and psychosocial adaptation in future space exploration missions. Much of what is known about effective team composition is drawn from research conducted in conventional workplaces (e.g., corporate offices, production plants). Quantitative reviews of the team composition literature (e.g., Bell, 2007; Bell, Villado, Lukasik, Belau, & Briggs, 2011) are based primarily on traditional teams. Less is known about how composition affects teams operating in extreme environments such as those that will be experienced by crews of future space exploration missions. For example, long-distance and long-duration space exploration (LDSE) crews are expected to live and work in isolated and confined environments (ICEs) for up to 30 months. Crews will also experience communication time delays from mission control, which will require crews to work more autonomously (see Appendix A for more detailed information regarding the LDSE context). Given the unique context within which LDSE crews will operate, NASA identified both a gap in knowledge related to the effective composition of autonomous, LDSE crews, and the need to identify psychological and psychosocial factors, measures, and combinations thereof that can be used to compose highly effective crews (Team Gap 8). As an initial step to address Team Gap 8, we conducted a focused literature review and operational assessment related to team composition issues for LDSE. The objectives of our research were to: (1) identify critical team composition issues and their effects on team functioning in LDSE-analogous environments with a focus on key composition factors that will most likely have the strongest influence on team performance and well-being, and 1 Astronaut diary entry in regards to group interaction aboard the ISS (p.22; Stuster, 2010) 2 (2) identify and evaluate methods used to compose teams with a focus on methods used in analogous environments. The remainder of the report includes the following components: (a) literature review methodology, (b) review of team composition theory and research, (c) methods for composing teams, (d) operational assessment results, and (e) recommendations

Robust Temporally Coherent Laplacian Protrusion Segmentation of 3D Articulated Bodies

In motion analysis and understanding it is important to be able to fit a suitable model or structure to the temporal series of observed data, in order to describe motion patterns in a compact way, and to discriminate between them. In an unsupervised context, i.e., no prior model of the moving object(s) is available, such a structure has to be learned from the data in a bottom-up fashion. In recent times, volumetric approaches in which the motion is captured from a number of cameras and a voxel-set representation of the body is built from the camera views, have gained ground due to attractive features such as inherent view-invariance and robustness to occlusions. Automatic, unsupervised segmentation of moving bodies along entire sequences, in a temporally-coherent and robust way, has the potential to provide a means of constructing a bottom-up model of the moving body, and track motion cues that may be later exploited for motion classification. Spectral methods such as locally linear embedding (LLE) can be useful in this context, as they preserve "protrusions", i.e., high-curvature regions of the 3D volume, of articulated shapes, while improving their separation in a lower dimensional space, making them in this way easier to cluster. In this paper we therefore propose a spectral approach to unsupervised and temporally-coherent body-protrusion segmentation along time sequences. Volumetric shapes are clustered in an embedding space, clusters are propagated in time to ensure coherence, and merged or split to accommodate changes in the body's topology. Experiments on both synthetic and real sequences of dense voxel-set data are shown. This supports the ability of the proposed method to cluster body-parts consistently over time in a totally unsupervised fashion, its robustness to sampling density and shape quality, and its potential for bottom-up model constructionComment: 31 pages, 26 figure

Blazing the trailway: Nuclear electric propulsion and its technology program plans

An overview is given of the plans for a program in nuclear electric propulsion (NEP) technology for space applications being considered by NASA, DOE, and DOD. Possible missions using NEP are examined, and NEP technology plans are addressed regarding concept development, systems engineering, nuclear fuels, power conversion, thermal management, power management and distribution, electric thrusters, facilities, and issues related to safety and environment. The programmatic characteristics are considered

Adherence to 6-Mercaptopurine in children and adolescents with Acute Lymphoblastic Leukemia

OBJECTIVE: Studies on children with Acute Lymphoblastic Leukemia (ALL) reported non-adherence in 2–54% of cases. The primary objective of this study was to assess rates of adherence to 6-MP using two different methods in children and adolescents with ALL. Secondary aim was to identify factors that influence adherence to 6-MP in children with ALL. METHODS: All eligible children with ALL who are (≤ 19) years old and receive 6-MP therapy for at least 1 month were approached to participate in the study. A total of 52 children with ALL and their primary caregivers were recruited. Adherence measures included an objective method (measuring 6-MP metabolites in packed Red Blood Cells (RBCs)) and a subjective method (using parent and child self-report via the Medication Adherence Report Scale; MARS; Adherence was defined as 90% or greater). RESULTS: Rates of adherence varied across the measurement methods. Packed RBCs sample analysis indicated forty-four patients (84.6%) to be adherent. Using the MARS questionnaires, a total of 49 children (94.2%) were classified as being adherent according to the parental MARS questionnaire scores, while all the 15 children (100%) who answered the MARS (child) questionnaire were classified as adherent. Overall adherence rate was 80.8% within the studied population. CONCLUSION: MARS scale was shown to overestimate adherence compared to measurement of 6-MP metabolites in the blood. A combination of both methods led to increased detection of non-adherence to thiopurine in children with ALL

Partial Likelihood Estimation of a Cox Model with Random Effects: an EM Algorithm based on Penalized Likelihood.

The aim of this paper is to present a general EM algorithm to estimate Mixed Proportional Hazard models including more than one random effect, through partial likelihood. We assume only that the mixing distributions admit Laplace transforms. We show how to transform inference in a single complicated model in the estimation of MPH models involving only a single frailty, which are easily manageable. We then face on gamma unobserved heterogeneity. This choice is a weak assumption as the heterogeneity distribution among survivors converges to a gamma distribution, often quickly, for many types of unobserved heterogeneity distributions. The proposed approach can thus be used to estimate a wide class of models. We describe how to use the penalized partial likelihood within the EM algorithm, to improve speed and stability. The behaviour of the estimator on different clusterings and sample sizes is assessed through a Monte Carlo study. We also provide an application on the ratiffcation of ILO conventions by developing countries over the period 1975-1995. Both the simulations and the empirical results indicate an important decrease in computing time. Furthermore, our procedure converges in settings where a standard EM algorithm does not.Random Effects, Duration analysis, Dynamic model

Segregation in Networks.

Schelling (1969, 1971a,b, 1978) considered a simple model with individual agents who only care about the types of people living in their own local neighborhood. The spatial structure was represented by a one- or two-dimensional lattice. Schelling showed that an integrated society will generally unravel into a rather segregated one even though no individual agent strictly prefers this. We make a first step to generalize the spatial proximity model to a proximity model of segregation. That is, we examine models with individual agents who interact ’locally’ in a range of network structures with topological properties that are different from those of regular lattices. Assuming mild preferences about with whom they interact, we study best-response dynamics in random and regular non-directed graphs as well as in small-world and scale-free networks. Our main result is that the system attains levels of segregation that are in line with those reached in the lattice-based spatial proximity model. In other words, mild proximity preferences can explain segregation not just in regular spatial networks but also in more general social networks. Furthermore, segregation levels do not dramatically vary across different network structures. That is, Schelling’s original results seem to be robust also to the structural properties of the network.Spatial proximity model, Social segregation, Schelling, Proximity preferences, Social networks, Undirected graphs, Best-response dynamics.