Less-structured time in children's daily lives predicts self-directed executive functioning.

Executive functions (EFs) in childhood predict important life outcomes. Thus, there is great interest in attempts to improve EFs early in life. Many interventions are led by trained adults, including structured training activities in the lab, and less-structured activities implemented in schools. Such programs have yielded gains in children's externally-driven executive functioning, where they are instructed on what goal-directed actions to carry out and when. However, it is less clear how children's experiences relate to their development of self-directed executive functioning, where they must determine on their own what goal-directed actions to carry out and when. We hypothesized that time spent in less-structured activities would give children opportunities to practice self-directed executive functioning, and lead to benefits. To investigate this possibility, we collected information from parents about their 6-7 year-old children's daily, annual, and typical schedules. We categorized children's activities as "structured" or "less-structured" based on categorization schemes from prior studies on child leisure time use. We assessed children's self-directed executive functioning using a well-established verbal fluency task, in which children generate members of a category and can decide on their own when to switch from one subcategory to another. The more time that children spent in less-structured activities, the better their self-directed executive functioning. The opposite was true of structured activities, which predicted poorer self-directed executive functioning. These relationships were robust (holding across increasingly strict classifications of structured and less-structured time) and specific (time use did not predict externally-driven executive functioning). We discuss implications, caveats, and ways in which potential interpretations can be distinguished in future work, to advance an understanding of this fundamental aspect of growing up

Degeneracy Algorithm for Random Magnets

It has been known for a long time that the ground state problem of random magnets, e.g. random field Ising model (RFIM), can be mapped onto the max-flow/min-cut problem of transportation networks. I build on this approach, relying on the concept of residual graph, and design an algorithm that I prove to be exact for finding all the minimum cuts, i.e. the ground state degeneracy of these systems. I demonstrate that this algorithm is also relevant for the study of the ground state properties of the dilute Ising antiferromagnet in a constant field (DAFF) and interfaces in random bond magnets.Comment: 17 pages(Revtex), 8 Postscript figures(5color) to appear in Phys. Rev. E 58, December 1st (1998

A distinct plasmablast and naive B-cell phenotype in primary immune thrombocytopenia

Obtained from the Haematologica Journal website http://www.haematologica.org/content/101/6/698.full.pdf+html Material published in Haematologica is covered by copyright. All rights reserved to Ferrata Storti Foundation. Copies of articles are allowed for personal or internal use. A permission in writing by the publisher is requested for any other use.Primary funding for this study was from GSK. SMF was funded by a Translational Medicine and Therapeutics PhD studentship jointly funded by the Wellcome Trust and GSK. The UK ITP Registry (www.ukitpregistry.com) is supported through unrestricted educational grants from GSK and Amgen

Ground Delay Program Analytics with Behavioral Cloning and Inverse Reinforcement Learning

We used historical data to build two types of model that predict Ground Delay Program implementation decisions and also produce insights into how and why those decisions are made. More specifically, we built behavioral cloning and inverse reinforcement learning models that predict hourly Ground Delay Program implementation at Newark Liberty International and San Francisco International airports. Data available to the models include actual and scheduled air traffic metrics and observed and forecasted weather conditions. We found that the random forest behavioral cloning models we developed are substantially better at predicting hourly Ground Delay Program implementation for these airports than the inverse reinforcement learning models we developed. However, all of the models struggle to predict the initialization and cancellation of Ground Delay Programs. We also investigated the structure of the models in order to gain insights into Ground Delay Program implementation decision making. Notably, characteristics of both types of model suggest that GDP implementation decisions are more tactical than strategic: they are made primarily based on conditions now or conditions anticipated in only the next couple of hours

IMF dependence of Saturn's auroras: modelling study of HST and Cassini data from 12–15 February 2008

To gain better understanding of auroral processes in Saturn's magnetosphere, we compare ultraviolet (UV) auroral images obtained by the Hubble Space Telescope (HST) with the position of the open-closed field line boundary in the ionosphere calculated using a magnetic field model that employs Cassini measurements of the interplanetary magnetic field (IMF) as input. Following earlier related studies of pre-orbit insertion data from January 2004 when Cassini was located ~ 1300 Saturn radii away from the planet, here we investigate the interval 12–15 February 2008, when UV images of Saturn's southern dayside aurora were obtained by the HST while the Cassini spacecraft measured the IMF in the solar wind just upstream of the dayside bow shock. This configuration thus provides an opportunity, unique to date, to determine the IMF impinging on Saturn's magnetosphere during imaging observations, without the need to take account of extended and uncertain interplanetary propagation delays. The paraboloid model of Saturn's magnetosphere is then employed to calculate the magnetospheric magnetic field structure and ionospheric open-closed field line boundary for averaged IMF vectors that correspond, with appropriate response delays, to four HST images. We show that the IMF-dependent open field region calculated from the model agrees reasonably well with the area lying poleward of the UV emissions, thus supporting the view that the poleward boundary of Saturn's auroral oval in the dayside ionosphere lies adjacent to the open-closed field line boundary

Population genetic analyses reveal distinct geographical blooms of the jellyfish Rhizostoma octopus (Scyphozoa)

Understanding the spatial integrity and connectivity of jellyfish blooms is important for ecologists and coastal stakeholders alike. Previous studies have shown that the distribution of jellyfish blooms can display a marked consistency in space and time, suggesting that such patterns cannot be attributed to passive processes alone. In the present study, we used a combination of microsatellite markers and mitochondrial cytochrome oxidase I sequences to investigate genetic structuring of the scyphozoan jellyfish Rhizostoma octopus in the Irish and Celtic Seas. The mitochondrial data indicated far higher levels of population differentiation than the microsatellites: ΦST[MT] = 0.300 vs. ΦST[NUC] = 0.013. Simulation studies indicated that the low levels of nuclear differentiation were not the result of limited power because of low levels of polymorphism. These findings, supported by palaeodistribution modelling and mismatch distribution analysis, are consistent with expansion of R. octopus from a single, limited refugium after the Last Glacial Maximum, followed by subsequent isolation, and that the discrepancy between the mitochondrial and nuclear markers is a result of the nuclear loci taking longer to reach mutation–drift equilibrium following the expansion as a result of their four-fold larger effective population size. The populations studied are probably not well connected via gene flow, and thus genetically as well as geographically distinct, although our findings also highlight the need to use a combination of organellar and nuclear markers to enable a more complete understanding of population demography and structure, particularly for species with large effective population sizes

An exploratory study on the potential of social enterprise to act as the institutional glue of network governance

This study combines two topics of contemporary salience for public administration: social enterprise and governance networks. While operating at different levels, both are institutions which attempt to draw together the three pillars of state, market, and civil society. Nevertheless, the respective literatures focus on particular aspects of the three pillars. We connect the two concepts and suggest that some social enterprises can act as the institutional glue of networks due to their ability to benefit organizations in each of the three sectors. This requires social enterprises to have the managerial capacity to diffuse social know-how, and is facilitated by the trust of other organizations and a supportive policy framework. The links are explicated at the conceptual level before providing evidence from South Korea and the UK. Finally, research propositions are offered, which suggest new avenues for future research