Chromatographic purification for the determination of dissolved silicon isotopic compositions in natural waters by high-resolution multicollector inductively coupled plasma mass spectrometry

A procedure is described for accurate Si isotope ratio measurements by multicollector inductively coupled plasma mass spectrometry (MC-ICPMS). Dissolved silicon was preconcentrated and separated from other elements present in natural surface waters using anion-exchange chromatography. The optimized procedure provides virtually complete elimination of major inorganic constituents while maintaining Si recovery in excess of 97%. High-resolution capabilities of MC-ICPMS used in this study allow interference-free measurements of 28Si and 29Si isotopes using conventional solution nebulization sample introduction without aerosol desolvation. Owing to the magnitude of polyatomic ion contributions in the region of mass 30, mostly from 14N16O+, measurements of the 30Si isotope can be affected by tailing of the interference signals, making exact matching of analyte and nitric acid concentrations in all measurement solutions mandatory. Isotope abundance ratio measurements were performed using the bracketing standards approach and on-line correction for mass-bias variations using an internal standard (Mg). Uncertainties, expressed as 95% confidence intervals, for replication of the entire procedure are better than +/-0.18/1000 for delta29Si and +/-0.5/1000 for delta30Si. For the first time with MC-ICPMS, the quality of Si isotope abundance ratio measurements could be verified using a three-isotope plot. All samples studied were isotopically heavier than the IRMM-018 Si isotopic reference material.     

Asymmetric phospholipid: lipopolysaccharide bilayers; a Gram-negative bacterial outer membrane mimic

The Gram-negative bacterial outer membrane (OM) is a complex and highly asymmetric biological barrier but the small size of bacteria has hindered advances in in vivo examination of membrane dynamics. Thus, model OMs, amenable to physical study, are important sources of data. Here, we present data from asymmetric bilayers which emulate the OM and are formed by a simple two-step approach. The bilayers were deposited on an SiO₂ surface by Langmuir–Blodgett deposition of phosphatidylcholine as the inner leaflet and, via Langmuir–Schaefer deposition, an outer leaflet of either Lipid A or Escherichia coli rough lipopolysaccharides (LPS). The membranes were examined using neutron reflectometry (NR) to examine the coverage and mixing of lipids between the bilayer leaflets. NR data showed that in all cases, the initial deposition asymmetry was mostly maintained for more than 16 h. This stability enabled the sizes of the headgroups and bilayer roughness of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine and Lipid A, Rc-LPS and Ra-LPS to be clearly resolved. The results show that rough LPS can be manipulated like phospholipids and used to fabricate advanced asymmetric bacterial membrane models using well-known bilayer deposition techniques. Such models will enable OM dynamics and interactions to be studied under in vivo-like conditions.     

Isotopic variations of Zn in biological materials

Variations in the isotopic composition of Zn present in various biological materials were determined using high-resolution multicollector inductively coupled plasma mass spectrometry (MC-ICPMS), following digestion and purification by anion exchange chromatography. To correct for differences in instrumental mass discrimination effects between samples and standards, Cu was employed as an elemental spike. Complementary analyses of Zn separates by sector field ICPMS instruments revealed that the concentrations of the majority of potentially interfering elements were reduced to negligible levels. Residual spectral interferences resulting from (35)Cl(16)O(2)(+), (40)Ar(14)N(2)(+), and (40)Ar(14)N(16)O(+) could be instrumentally resolved from the (67)Zn, (68)Zn, and (70)Zn ion beams, respectively, during measurement by MC-ICPMS. The only other observed interference in the Cu and Zn mass range that could not be effectively eliminated by high-resolution multicollection resulted from (35)Cl(2)(+), necessitating modification of the sample preparation procedure to allow accurate (70)Zn detection. Complete duplication of the entire analytical procedure for human whole blood and hair, as well as bovine liver and muscle, provided an external reproducibility of 0.05-0.12 per thousand (2sigma) for measured delta(66/64)Zn, delta(67/64)Zn, and delta(68/64)Zn values, demonstrating the utility of the method for the precise isotopic analysis of Zn in biological materials. Relative to the selected Zn isotopic standard, delta(66/64)Zn values for biological samples varied from -0.60 per thousand in human hair to +0.56 per thousand in human whole blood, identifying the former material as the isotopically lightest Zn source found in nature to date.     

Empirical evaluation of computational fear contagion models in crowd dispersions

In social psychology, emotional contagion describes the widely observed phenomenon of one person’s emotions being influenced by surrounding people’s emotions. While the overall effect is agreed upon, the underlying mechanism of the spread of emotions has seen little quantification and application to computational agents despite extensive evidence of its impacts in everyday life. In this paper, we examine computational models of emotional contagion by implementing two models (Bosse et al., European council on modeling and simulation, pp. 212–218, 2009) and Durupinar, From audiences to mobs: Crowd simulation with psychological factors, PhD dissertation, Bilkent University, 2010) that draw from two separate lines of contagion research: thermodynamics-based and epidemiological-based. We first perform sensitivity tests on each model in an evacuation simulation, ESCAPES, showing both models to be reasonably robust to parameter variations with certain exceptions. We then compare their ability to reproduce a real crowd panic scene in simulation, showing that the thermodynamics-style model (Bosse et al., European council on modeling and simulation, pp. 212–218, 2009) produces superior results due to the ill-suited contagion mechanism at the core of epidemiological models. We also identify that a graduated effect of fear and proximity-based contagion effects are key to producing the superior results. We then reproduce the methodology on a second video, showing that the same results hold, implying generality of the conclusions reached in the first scene.     

Diagnosability of star graphs under the comparison diagnosis model

In this paper, the diagnosability of n-dimensional star graph Sn under the comparison diagnosis model has been studied. It is proved that Sn is (n−1)-diagnosable under the comparison diagnosis model when n?4.     

Focal Flow: Velocity and Depth from Differential Defocus Through Motion

We present the focal flow sensor. It is an unactuated, monocular camera that simultaneously exploits defocus and differential motion to measure a depth map and a 3D scene velocity field. It does this using an optical-flow-like, per-pixel linear constraint that relates image derivatives to depth and velocity. We derive this constraint, prove its invariance to scene texture, and prove that it is exactly satisfied only when the sensor’s blur kernels are Gaussian. We analyze the inherent sensitivity of the focal flow cue, and we build and test a prototype. Experiments produce useful depth and velocity information for a broader set of aperture configurations, including a simple lens with a pillbox aperture.     

Innovation or Notoriety?

The purpose of this column is to give some perspective and words of advice to new inventors. When you choose to be an innovator, you will have lots of fun intellectually, but the road can be pretty bumpy when it comes to the politics of receiving proper credit for your ideas, and when it comes to "selling" your ideas and seeing them through to implementation. This column documents some of the possible bumps in the road, including the three stages toward acceptance of a new idea: ridicule, opposition, and obviousness.     

Automated strategies to identify compounds on the basis of GC/EI-MS and calculated properties

The identification of unknown compounds based on GC/EI-MS spectrum and structure generation techniques has been improved by combining a number of strategies into a programmed sequence. The program MOLGEN-MS is used to determine the molecular formula and incorporate substructural information to generate all structures matching the mass spectral information. Mass spectral fragments are then predicted for each structure and compared with the experimental spectrum using a match value. Additional data are then calculated automatically for each candidate to allow exclusion of candidates that did not match other analytical information. The effectiveness of these "exclusion criteria", as well as the programming sequence, was tested using a case study of 29 isomers of formula C(12)H(10)O(2). The default classifier precision resulted in the generation of too many structures in some cases, which was improved by up to several orders of magnitude by including additional classifiers or restrictions. Combining this with the exclusion of candidates based on a Lee retention index/boiling point correlation, octanol-water partitioning coefficients, steric energies, and finally spectral match values limited the number of candidate structures further from over 1 billion without any restrictions down to less than 6 structures in 10 cases and below 35 in all but 3 cases. This method can be used in the absence of matching database spectra and brings unknown identification based on MS interpretation and structure generation techniques a step closer to practical reality.