Towards a classification framework for social machines

The state of the art in human interaction with computational systems blurs the line between computations performed by machine logic and algorithms, and those that result from input by humans, arising from their own psychological processes and life experience. Current socio-technical systems, known as ‘social machines’ exploit the large-scale interaction of humans with machines. Interactions that are motivated by numerous goals and purposes including financial gain, charitable aid, and simply for fun. In this paper we explore the landscape of social machines, both past and present, with the aim of defining an initial classificatory framework. Through a number of knowledge elicitation and refinement exercises we have identified the polyarchical relationship between infrastructure, social machines, and large-scale social initiatives. Our initial framework describes classification constructs in the areas of contributions, participants, and motivation. We present an initial characterization of some of the most popular social machines, as demonstration of the use of the identified constructs. We believe that it is important to undertake an analysis of the behaviour and phenomenology of social machines, and of their growth and evolution over time. Our future work will seek to elicit additional opinions, classifications and validation from a wider audience, to produce a comprehensive framework for the description, analysis and comparison of social machines

Investigation of possible hydrogen shielding effect on epithermal neutron activation analysis - a computation and experimental approach

Neutron activation is a popular analytical technique used to determine the presence and concentration of certain elements. It has several variations, including thermal neutron, epithermal neutron, fast neutron activation, etc, for different applications; all of those variations are non-destructive, and sensitive to small quantity. While trying to determine the concentration of Cl and Br in the light water solution, Dr. Landsberger’s team found the epithermal neutron activation analysis results were 25% lower than the conventional chemical method. They were not able to determine the cause of such discrepancy. This study was motivated to re-examine such discrepancy, and to study its possible causes. Furthermore, the study tries to determine if such discrepancy, if it exists, was linked with thermal neutron cut off or hydrogen absorption of neutrons. A computer simulation using the Monte Carlo radiation transport software MCNPX was developed to radiate sample Cl & Br solutions of known mass concentrations in a simulated TRIGA reactor core at 500 KW steady state power. [1] The neutron activation rate of Br, Cl at each concentration was then calculated. Such procedure was then repeated for heavy water solutions. Finally, a cadmium shield was added to eliminate thermal neutrons; all samples were tested again using epithermal neutron activation. The actual neutron activation experiment was also carried out in the University of Texas’s TRIGA Mark II reactor. A total of 40 samples of Br & Cl solution (with and without Cd, in light water and in heavy water) were irradiated in the reactor at 500 KW steady state power.Physic

Novel Application Of Untargeted Metabolomics To Diseases Of Neurosurgical Significance

Metabolomics, an emerging technique to study hundreds of small-molecule metabolites simultaneously, has been seldom applied to diseases of neurosurgical significance. We utilized metabolomics to explore two distinct questions: 1. to identify global metabolic changes and metabolite predictors of long-term outcome in aneurysmal subarachnoid hemorrhage (SAH) patients, 2. to identify differential metabolites profiles of radiation necrosis vs. recurrent tumor of metastatic brain lesions post-Gamma Knife radiosurgery. The first study applied gas chromatography time-of-flight mass spectrometry (GC-TOF) to cerebrospinal fluid samples collected from 15 high-grade aSAH patients (modified Fisher grades 3 and 4). Analysis was performed at two time points; metabolite levels at each time point were correlated with Glasgow Outcome Scale (GOS) of patients at 1 year post-aSAH. Of 97 metabolites identified, 16 metabolites (primarily free amino acids) significantly changed between the two time points; these changes were magnified in modified Fisher grade 4 compared with grade 3. Six metabolites (2-hydroxyglutarate, tryptophan, glycine, proline, isoleucine, and alanine) correlated with GOS at 1 year post-aSAH. These results suggest that specific metabolite changes occur in the brain during the course of aSAH and that quantification of specific CSF metabolites may be used to predict long-term outcomes. This is the first study to implicate 2- hydroxyglutarate, a known marker of tissue hypoxia, in aSAH pathogenesis. The second study applied GC- TOF to histologically-validated specimens (7 each) of pure radiation necrosis and pure recurrent tumor obtained from patient brain biopsies. Of 141 metabolites identified, 17 were found to be statistically significantly different between comparison groups. Of these metabolites, 6 were increased in tumor, and 11 metabolites were increased in radiation necrosis. An unsupervised hierarchical clustering analysis found that tumor had elevated levels of metabolites associated with energy metabolism whereas radiation necrosis had elevated levels of metabolites that were fatty acids and antioxidants/cofactors. This is the first tissue- based metabolomics study of radiation necrosis and tumor. Radiation necrosis and recurrent tumor following Gamma Knife radiosurgery for brain metastases have unique metabolite profiles that may be targeted in the future to develop non-invasive metabolic imaging techniques