Multi-jet Production in Hadron Collisions

The advent of high-energy hadron colliders necessitates efficient and accurate computation of multi-jet production processes, both as QCD processes in their own right and as backgrounds for other physics. The algorithm that performs these tasks and a brief numerical study of multi-jet processes are presented.Comment: 21 pages, 9 figure

O VI and Multicomponent H I Absorption Associated with a Galaxy Group in the Direction of PG0953+415: Physical Conditions and Baryonic Content

We report the discovery of an O VI absorption system at z(abs) = 0.14232 in a high resolution FUV spectrum of PG0953+415 obtained with the Space Telescope Imaging Spectrograph (STIS). Both lines of the O VI 1032, 1038 doublet and multicomponent H I Lya absorption are detected, but the N V doublet and the strong lines of C II and Si III are not apparent. We examine the ionization mechanism of the O VI absorber and find that while theoretical considerations favor collisional ionization, it is difficult to observationally rule out photoionization. If the absorber is collisionally ionized, it may not be in equilibrium due to the rapid cooling of gas in the appropriate temperature range. Non-equilibrium collisionally ionized models are shown to be consistent with the observations. A WIYN survey of galaxy redshifts near the sight line has revealed a galaxy at a projected distance of 395 kpc separated by ~130 km/s from this absorber, and three additional galaxies are found within 130 km/s of this redshift with projected separations ranging from 1.0 Mpc to 3.0 Mpc. Combining the STIS observations of PG0953+415 with previous high S/N GHRS observations of H1821+643, we derive a large number of O VI absorbers per unit redshift, dN/dz ~20. We use this sample to obtain a first estimate of the cosmological mass density of the O VI systems at z ~ 0. If further observations confirm the large dN/dz derived for the O VI systems, then these absorbers trace a significant reservoir of baryonic matter at low redshift.Comment: Accepted for publication in Ap.J., vol. 542 (Oct. 10, 2000

Ultrasound increases the aqueous extraction of phenolic compounds with high antioxidant activity from olive pomace

Olive pomace is a waste produced by the olive oil industry in massive quantities each year. Disposal of olive pomace is difficult due to high concentrations of phenolic compounds, which is an environmental concern. However, phenolic compounds have applications in the health industry. Therefore, extraction of phenolic compounds from olive pomace has the potential to remove an environmentally hazardous portion of pomace while creating an additional source of income for farmers and producers. Using advanced technologies including Ultrasound Assisted Extraction (UAE), combined with water as an extraction solvent, has recently gained popularity. The present study outlines the optimal UAE conditions for the extraction of phenolic compounds with high antioxidant activity from olive pomace. Optimal conditions were developed using RSM for parameters power, time and sample-to-solvent ratio. Total phenolic compounds determined by Folin Ciocalteu method and total major bioactive compounds determined by HPLC as well as antioxidant capacity (DPPH and CUPRAC) were investigated. The optimal conditions for the extraction of phenolic compounds with high antioxidant activity were 2 g of dried pomace/100 mL of water at 250 W power for 75 min. UAE improved the extraction efficiency of water and yielded extracts with high levels of phenolic compounds and strong antioxidant activity

A proposed framework of an interactive semi-virtual environment for enhanced education of children with autism spectrum disorders

Education of people with special needs has recently been considered as a key element in the field of medical education. Recent development in the area of information and communication technologies may enable development of collaborative interactive environments which facilitate early stage education and provide specialists with robust tools indicating the person's autism spectrum disorder level. Towards the goal of establishing an enhanced learning environment for children with autism this paper attempts to provide a framework of a semi-controlled real-world environment used for the daily education of an autistic person according to the scenarios selected by the specialists. The proposed framework employs both real-world objects and virtual environments equipped with humanoids able to provide emotional feedback and to demonstrate empathy. Potential examples and usage scenarios for such environments are also described

Genome-scale mapping models and algorithms for stationary and instationary MFA-based metabolic flux elucidation

Metabolic models used in 13C metabolic flux analysis (13C-MFA) generally include a limited number of reactions primarily from central metabolism, neglecting degradation pathways and atom transition contributions for reactions outside central metabolism. This study addresses the impact on prediction fidelity of scaling-up core bacterial and cyanobacterial mapping models to a genome-scale carbon mapping (GSCM) models, imEco726 (668 reaction and 566 metabolites) and imSyn711 (731 reactions, 679 metabolites) for E. coli and Synechocystis PCC 6803, respectively, representing a ten-fold increase in model size. The GSCM models are constructed using the CLCA algorithm following reduction of the corresponding metabolic models, iAF1260 and iSyn731, using experimentally measured biomass and product yield during growth on glucose and CO2, respectively. The mapping models are then deployed for flux elucidation using isotopic steady-state MFA for E. coli to recapitulate experimentally observed labeling distributions of 12 measured amino acids, and isotopic instationary MFA for Synechocystis, to recapitulate labeling dynamics of 15 central metabolites. In both models, 80% of all fluxes varies less than onetenth of the basis carbon substrate uptake rate primarily due to the flux coupling with biomass production. Overall, we find that both the topology and estimated values of the metabolic fluxes remain largely consistent between the core and GSMM models for E. coli. Stepping up to a genome-scale mapping model leads to wider flux inference ranges for 20 key reactions present in the core model. The glycolysis flux range doubles due to the possibility of active gluconeogenesis, the TCA flux range expanded by 80% due to the availability of a bypass through arginine consistent with labeling data, and the transhydrogenase reaction flux was essentially unresolved due to the presence of as many as five routes for the inter-conversion of NADPH to NADH afforded by the genome-scale model. By globally accounting for ATP demands in the GSMM model the unused ATP decreased drastically with the lower bound matching the maintenance ATP requirement. A non-zero flux for the arginine degradation pathway was identified to meet biomass precursor demands as detailed in the iAF1260 model. Significant flux range shifts were observed using a GSCM model compared to a core model in Synechocystis arising from the inclusion of 18 novel carbon paths in the GSCM model. In particular, no flux is channeled through the oxidative pentose phosphate pathway, resulting in a reduced carbon fixation flux. In addition, a higher flux is seen through the Transaldolase reaction, serving as a bypass route to Fructose bisphosphatase. Serine and glycine are found to be synthesized from 3-phosphoglycerate and the photorespiratory pathway, respectively. Pyruvate is synthesized exclusively via the malate bypass with trace contributions from pyruvate kinase. Furthermore, trace flux is predicted through the lower TCA cycle indicating either pathway incompleteness or dispensability during photoautotrophic growth. Despite these differences, 80% of all reactions in both genome-scale models are resolved to within 10% of the respective substrate uptake rate due to the presence of 411 and 407 growth-coupled reactions in E. coli and Synechocystis, respectively. Flux ranges obtained with GSCM models are compared with those obtained upon projecting core model ranges on to a genome-scale metabolic model to elucidate the loss of information and erroneous biological inferences about pathway usage arising from assumptions contained within core models, reaffirming the importance of using mapping models with global carbon path coverage in 13C metabolic flux analysis