Adsorption of arsenate on Fe-(hydr)oxide

Adsorption using metal oxide materials has been demonstrated to be an effective technique to remove hazardous materials from water, due to its easy operation, low cost, and high efficiency. The high number of oxyanions in aquatic ecosystems causes serious pollution problems. Removal of arsenate (H2AsO4 -), is one of the major concerns, since it is a highly toxic anion for life. Within the metal oxides, the iron oxide is considered as a suitable material for the elimination of oxyanions. The adsorption of H2AsO4 - on Fe-(hydr)oxide is through the formation of inner or outer sphere complexes. In this work, through computational methods, a complete characterization of the adsorbed surface complexes was performed. Three different pH conditions were simulated (acidic, intermediate and basic), and it was found that, the thermodynamic favourability of the different adsorbed complexes was directly related to the pH. Monodentate complex (MM1) was the most thermodynamically favourable complex with an adsorption energy of -96.0kJ/mol under intermediate pH conditions. © Published under licence by IOP Publishing Ltd

Evaporation kinetics of Mg2SiO4 crystals and melts from molecular dynamics simulations

Computer simulations based on the molecular dynamics (MD) technique were used to study the mechanisms and kinetics of free evaporation from crystalline and molten forsterite (i.e., Mg2SiO4) on an atomic level. The interatomic potential employed for these simulations reproduces the energetics of bonding in forsterite and in gas-phase MgO and SiO2 reasonably accurately. Results of the simulation include predicted evaporation rates, diffusion rates, and reaction mechanisms for Mg2SiO4(s or l) yields 2Mg(g) + 20(g) + SiO2(g)

4-(4-Methylbenzoyl)-6-(4-methylbenzylidene)-3-phenyl-2-oxa-3-azabicyclo 3. 3.0-oct-7-ene

The title compound, C28H25NO2, is a minor product resulting from a 1,3-dipolar nitrone-fulvene 3+2 cyclo-addition

4-Benzoyl-6-(4-methoxybenzylidene)-3-phenyl-2-oxa-3-azabicyclo3.3.0]oct-7-ene

The title compound, C27H23NO3, consists of a fulvene-1,3-dipolar-nitrone adduct with a five-membered C3NO saturated heterocycle

New dipeptides containing thiazolidine-4-carboxylic acid derivatives: Synthesis and characterization using NMR techniques and X-ray data

New dipeptides, structural analogues of known immunomodulating agents, were prepared by stereospecific condensation between 2-substituted thiazolidine-4-carboxylate esters with N-substituted L-proline or L- thiaproline. The structure of these compounds has been elucidated by combination of NMR methods and X-ray analysis. In addition, NMR measurements on dipeptides indicated the presence of S-cis and S-trans conformers around the amide bonds

A global atmospheric electricity monitoring network for climate and geophysical research

The Global atmospheric Electric Circuit (GEC) is a fundamental coupling network of the climate system connecting electrically disturbed weather regions with fair weather regions across the planet. The GEC sustains the fair weather electric field (or potential gradient, PG) which is present globally and can be measured routinely at the surface using durable instrumentation such as modern electric field mills, which are now widely deployed internationally. In contrast to lightning or magnetic fields, fair weather PG cannot be measured remotely. Despite the existence of many PG datasets (both contemporary and historical), few attempts have been made to coordinate and integrate these fragmented surface measurements within a global framework. Such a synthesis is important elvinin order to fully study major influences on the GEC such as climate variations and space weather effects, as well as more local atmospheric electrical processes such as cloud electrification, lightning initiation, and dust and aerosol charging. The GloCAEM (Global Coordination of Atmospheric Electricity Measurements) project has brought together experts in atmospheric electricity to make the first steps towards an effective global network for atmospheric electricity monitoring, which will provide data in near real time. Data from all sites are available in identically-formatted files, at both one second and one minute temporal resolution, along with meteorological data (wherever available) for ease of interpretation of electrical measurements. This work describes the details of the GloCAEM database and presents what is likely to be the largest single analysis of PG data performed from multiple datasets at geographically distinct locations. Analysis of the diurnal variation in PG from all 17 GloCAEM sites demonstrates that the majority of sites show two daily maxima, characteristic of local influences on the PG, such as the sunrise effect. Data analysis methods to minimise such effects are presented and recommendations provided on the most suitable GloCAEM sites for the study of various scientific phenomena. The use of the dataset for a further understanding of the GEC is also demonstrated, in particular for more detailed characterization of day-to-day global circuit variability. Such coordinated effort enables deeper insight into PG phenomenology which goes beyond single-location PG measurements, providing a simple measurement of global thunderstorm variability on a day-to-day timescale. The creation of the GloCAEM database is likely to enable much more effective study of atmospheric electricity variables than has ever been possible before, which will improve our understanding of the role of atmospheric electricity in the complex processes underlying weather and climate

Joint generative model for fMRI/DWI and its application to population

Author Manuscript 2011 March 12. 13th International Conference, Beijing, China, September 20-24, 2010, Proceedings, Part IWe propose a novel probabilistic framework to merge information from DWI tractography and resting-state fMRI correlations. In particular, we model the interaction of latent anatomical and functional connectivity templates between brain regions and present an intuitive extension to population studies. We employ a mean-field approximation to fit the new model to the data. The resulting algorithm identifies differences in latent connectivity between the groups. We demonstrate our method on a study of normal controls and schizophrenia patients.National Alliance for Medical Image Computing (U.S.) (NIH NIBIBNAMICU54-EB005149)Neuroimaging Analysis Center (U.S.) (NIH NCRR NAC P41-RR13218)National Institutes of Health (U.S.) (Grant R01MH074794)National Defense Science and Engineering Graduate FellowshipNational Science Foundation (U.S.) (CAREER Grant 0642971