Flight IV technical report for experiment 74-37 contained polycrystalline solidification in low-G

Experiments were performed to study the effect of a low-gravity environment on the columnar-to-equiaxed transition (CET) during polycrystalline solidification. Solutions of H2O-30 wt% NH4Cl and H2O-37 wt% NH4Cl were solidified in semicylindrical molds with radial heat extraction. Both solutions were quenched from the same soak temperature (90 C); the respective superheat temperatures were, therefore, approximately 57 and 23 C. The lower superheat resulted in a completely columnar structure, and the higher superheat resulted in a 1/3 columnar - 2/3 equiaxed microstructure; these results were independent of the relationship between heat flow direction and gravity. Grain multiplication mechanisms observed were showering, thermal inversion driven convection cells, and compositionally induced density inversion driven convection cells

Remarks on Bootstrap Percolation in Metric Networks

We examine bootstrap percolation in d-dimensional, directed metric graphs in the context of recent measurements of firing dynamics in 2D neuronal cultures. There are two regimes, depending on the graph size N. Large metric graphs are ignited by the occurrence of critical nuclei, which initially occupy an infinitesimal fraction, f_* -> 0, of the graph and then explode throughout a finite fraction. Smaller metric graphs are effectively random in the sense that their ignition requires the initial ignition of a finite, unlocalized fraction of the graph, f_* >0. The crossover between the two regimes is at a size N_* which scales exponentially with the connectivity range \lambda like_* \sim \exp\lambda^d. The neuronal cultures are finite metric graphs of size N \simeq 10^5-10^6, which, for the parameters of the experiment, is effectively random since N<< N_*. This explains the seeming contradiction in the observed finite f_* in these cultures. Finally, we discuss the dynamics of the firing front

Collaboration in the Semantic Grid: a Basis for e-Learning

The CoAKTinG project aims to advance the state of the art in collaborative mediated spaces for the Semantic Grid. This paper presents an overview of the hypertext and knowledge based tools which have been deployed to augment existing collaborative environments, and the ontology which is used to exchange structure, promote enhanced process tracking, and aid navigation of resources before, after, and while a collaboration occurs. While the primary focus of the project has been supporting e-Science, this paper also explores the similarities and application of CoAKTinG technologies as part of a human-centred design approach to e-Learning

Hydrogel-based scaffolds to support intrathecal stem cell transplantation as a gateway to the spinal cord: clinical needs, biomaterials, and imaging technologies

The prospects for cell replacement in spinal cord diseases are impeded by inefficient stem cell delivery. The deep location of the spinal cord and complex surgical access, as well as densely packed vital structures, question the feasibility of the widespread use of multiple spinal cord punctures to inject stem cells. Disorders characterized by disseminated pathology are particularly appealing for the distribution of cells globally throughout the spinal cord in a minimally invasive fashion. The intrathecal space, with access to a relatively large surface area along the spinal cord, is an attractive route for global stem cell delivery, and, indeed, is highly promising, but the success of this approach relies on the ability of cells 1) to survive in the cerebrospinal fluid (CSF), 2) to adhere to the spinal cord surface, and 3) to migrate, ultimately, into the parenchyma. Intrathecal infusion of cell suspension, however, has been insufficient and we postulate that embedding transplanted cells within hydrogel scaffolds will facilitate reaching these goals. In this review, we focus on practical considerations that render the intrathecal approach clinically viable, and then discuss the characteristics of various biomaterials that are suitable to serve as scaffolds. We also propose strategies to modulate the local microenvironment with nanoparticle carriers to improve the functionality of cellular grafts. Finally, we provide an overview of imaging modalities for in vivo monitoring and characterization of biomaterials and stem cells. This comprehensive review should serve as a guide for those planning pre-clinical and clinical studies on intrathecal stem cell transplantation.Funds provided under the project NanoTech4ALS (ref. ENMed/0008/2015, 13/EuroNanoMed/2016), funded under the EU FP7 M-ERA.NET program, Strategmed 1/233209/12/NCBIR/2015, and NIH R01 NS091100. The FCT distinction attributed to J.M.O. under the Investigator FCT program (IF/01285/2015) is also gratefully acknowledgedinfo:eu-repo/semantics/publishedVersio

A Metaheuristic Framework for Bi-level Programming Problems with Multi-disciplinary Applications

Bi-level programming problems arise in situations when the decision maker has to take into account the responses of the users to his decisions. Several problems arising in engineering and economics can be cast within the bi-level programming framework. The bi-level programming model is also known as a Stackleberg or leader-follower game in which the leader chooses his variables so as to optimise his objective function, taking into account the response of the follower(s) who separately optimise their own objectives, treating the leader’s decisions as exogenous. In this chapter, we present a unified framework fully consistent with the Stackleberg paradigm of bi-level programming that allows for the integration of meta-heuristic algorithms with traditional gradient based optimisation algorithms for the solution of bi-level programming problems. In particular we employ Differential Evolution as the main meta-heuristic in our proposal.We subsequently apply the proposed method (DEBLP) to a range of problems from many fields such as transportation systems management, parameter estimation and game theory. It is demonstrated that DEBLP is a robust and powerful search heuristic for this class of problems characterised by non smoothness and non convexity