Liquid–Vapor Interface of Formic Acid Solutions in Salt Water: A Comparison of Macroscopic Surface Tension and Microscopic in Situ X-ray Photoelectron Spectroscopy Measurements

The liquid–vapor interface is difficult to access experimentally but is of interest from a theoretical and applied point of view and has particular importance in atmospheric aerosol chemistry. Here we examine the liquid–vapor interface for mixtures of water, sodium chloride, and formic acid, an abundant chemical in the atmosphere. We compare the results of surface tension and X-ray photoelectron spectroscopy (XPS) measurements over a wide range of formic acid concentrations. Surface tension measurements provide a macroscopic characterization of solutions ranging from 0 to 3 M sodium chloride and from 0 to over 0.5 mole fraction formic acid. Sodium chloride was found to be a weak salting out agent for formic acid with surface excess depending only slightly on salt concentration. In situ XPS provides a complementary molecular level description about the liquid–vapor interface. XPS measurements over an experimental probe depth of 51 Å gave the C 1s to O 1s ratio for both total oxygen and oxygen from water. XPS also provides detailed electronic structure information that is inaccessible by surface tension. Density functional theory calculations were performed to understand the observed shift in C 1s binding energies to lower values with increasing formic acid concentration. Part of the experimental −0.2 eV shift can be assigned to the solution composition changing from predominantly monomers of formic acid to a combination of monomers and dimers; however, the lack of an appropriate reference to calibrate the absolute BE scale at high formic acid mole fraction complicates the interpretation. Our data are consistent with surface tension measurements yielding a significantly more surface sensitive measurement than XPS due to the relatively weak propensity of formic acid for the interface. A simple model allowed us to replicate the XPS results under the assumption that the surface excess was contained in the top four angstroms of solution.

Stress-induced cortisol secretion impairs detection performance in x-ray baggage screening for hidden weapons by screening novices

Aviation security strongly depends on screeners' performance in the detection of threat objects in x-ray images of passenger bags. We examined for the first time the effects of stress and stress-induced cortisol increases on detection performance of hidden weapons in an x-ray baggage screening task. We randomly assigned 48 participants either to a stress or a nonstress group. The stress group was exposed to a standardized psychosocial stress test (TSST). Before and after stress/nonstress, participants had to detect threat objects in a computer-based object recognition test (X-ray ORT). We repeatedly measured salivary cortisol and X-ray ORT performance before and after stress/nonstress. Cortisol increases in reaction to psychosocial stress induction but not to nonstress independently impaired x-ray detection performance. Our results suggest that stress-induced cortisol increases at peak reactivity impair x-ray screening performance.

Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

Automatic X-ray landmark detection and shape segmentation via data-driven joint estimation of image displacements

In this paper, we propose a new method for fully-automatic landmark detection and shape segmentation in X-ray images. To detect landmarks, we estimate the displacements from some randomly sampled image patches to the (unknown) landmark positions, and then we integrate these predictions via a voting scheme. Our key contribution is a new algorithm for estimating these displacements. Different from other methods where each image patch independently predicts its displacement, we jointly estimate the displacements from all patches together in a data driven way, by considering not only the training data but also geometric constraints on the test image. The displacements estimation is formulated as a convex optimization problem that can be solved efficiently. Finally, we use the sparse shape composition model as the a priori information to regularize the landmark positions and thus generate the segmented shape contour. We validate our method on X-ray image datasets of three different anatomical structures: complete femur, proximal femur and pelvis. Experiments show that our method is accurate and robust in landmark detection, and, combined with the shape model, gives a better or comparable performance in shape segmentation compared to state-of-the art methods. Finally, a preliminary study using CT data shows the extensibility of our method to 3D data.

Evaluation and Comparison of Anatomical Landmark Detection Methods for Cephalometric X-Ray Images: A Grand Challenge

Cephalometric analysis is an essential clinical and research tool in orthodontics for the orthodontic analysis and treatment planning. This paper presents the evaluation of the methods submitted to the Automatic Cephalometric X-Ray Landmark Detection Challenge, held at the IEEE International Symposium on Biomedical Imaging 2014 with an on-site competition. The challenge was set to explore and compare automatic landmark detection methods in application to cephalometric X-ray images. Methods were evaluated on a common database including cephalograms of 300 patients aged six to 60 years, collected from the Dental Department, Tri-Service General Hospital, Taiwan, and manually marked anatomical landmarks as the ground truth data, generated by two experienced medical doctors. Quantitative evaluation was performed to compare the results of a representative selection of current methods submitted to the challenge. Experimental results show that three methods are able to achieve detection rates greater than 80% using the 4 mm precision range, but only one method achieves a detection rate greater than 70% using the 2 mm precision range, which is the acceptable precision range in clinical practice. The study provides insights into the performance of different landmark detection approaches under real-world conditions and highlights achievements and limitations of current image analysis techniques.

Crystalline, Mixed-Valence Manganese Analogue of Prussian Blue: Magnetic, Spectroscopic, X-ray and Neutron Diffraction Studies

The compound of stoichiometry Mn(II)3[Mn(III)(CN)6]2·zH2O (z = 12−16) (1) forms air-stable, transparent red crystals. Low-temperature single crystal optical spectroscopy and single crystal X-ray diffraction provide compelling evidence for N-bonded high-spin manganese(II), and C-bonded low-spin manganese(III) ions arranged in a disordered, face-centered cubic lattice analogous to that of Prussian Blue. X-ray and neutron diffraction show structured diffuse scattering indicative of partially correlated (rather than random) substitutions of [Mn(III)(CN)6] ions by (H2O)6 clusters. Magnetic susceptibility measurements and elastic neutron scattering experiments indicate a ferrimagnetic structure below the critical temperature Tc = 35.5 K.

High-Spin Molecules: Synthesis, X-ray Characterization, and Magnetic Behavior of Two New Cyano-Bridged Ni II 9 Mo V 6 and Ni II 9 W V 6 Clusters with a S = 12 Ground State

The preparations, X-ray structures, and magnetic characterizations are presented for two new pentadecanuclear cluster compounds:  [NiII{NiII(MeOH)3}8(μ-CN)30{MV(CN)3}6]·xMeOH·yH2O (MV = MoV (1) with x = 17, y = 1; MV = WV (2) with x = 15, y = 0). Both compounds crystallize in the monoclinic space group C2/c, with cell dimensions of a = 28.4957(18) Å, b = 19.2583(10) Å, c = 32.4279(17) Å, β = 113.155(6)°, and Z = 4 for 1 and a = 28.5278(16) Å, b = 19.2008(18) Å, c = 32.4072(17) Å, β = 113.727(6)°, and Z = 4 for 2. The structures of 1 and 2 consist of neutral cluster complexes comprising 15 metal ions, 9 NiII and 6 MV, all linked by μ-cyano ligands. Magnetic susceptibilities and magnetization measurements of compounds 1 and 2 in the crystalline and dissolved state indicate that these clusters have a S = 12 ground state, originating from intracluster ferromagnetic exchange interactions between the μ-cyano-bridged metal ions of the type NiII−NC−MV. Indeed, these data show clearly that the cluster molecules stay intact in solution. Ac magnetic susceptibility measurements reveal that the cluster compounds exhibit magnetic susceptibility relaxation phenomena at low temperatures since, with nonzero dc fields, χ‘ ‘M has a nonzero value that is frequency dependent. However, there appears no out-of-phase (χ‘ ‘M) signal in zero dc field down to 1.8 K, which excludes the expected signature for a single molecule magnet. This finding is confirmed with the small uniaxial magnetic anisotropy value for D of 0.015 cm-1, deduced from the high-field, high-frequency EPR measurement, which distinctly reveals a positive sign in D. Obviously, the overall magnetic anisotropy of the compounds is too low, and this may be a consequence of a small single ion magnetic anisotropy combined with the highly symmetric arrangement of the metal ions in the cluster molecule.

XMapTools: a MATLAB©-based program for electron microprobe X-ray image processing and geothermobarometry

XMapTools is a MATLAB©-based graphical user interface program for electron microprobe X-ray image processing, which can be used to estimate the pressure–temperature conditions of crystallization of minerals in metamorphic rocks. This program (available online at http://www.xmaptools.com) provides a method to standardize raw electron microprobe data and includes functions to calculate the oxide weight percent compositions for various minerals. A set of external functions is provided to calculate structural formulae from the standardized analyses as well as to estimate pressure–temperature conditions of crystallization, using empirical and semi-empirical thermobarometers from the literature. Two graphical user interface modules, Chem2D and Triplot3D, are used to plot mineral compositions into binary and ternary diagrams. As an example, the software is used to study a high-pressure Himalayan eclogite sample from the Stak massif in Pakistan. The high-pressure paragenesis consisting of omphacite and garnet has been retrogressed to a symplectitic assemblage of amphibole, plagioclase and clinopyroxene. Mineral compositions corresponding to ~165,000 analyses yield estimates for the eclogitic pressure–temperature retrograde path from 25 kbar to 9 kbar. Corresponding pressure–temperature maps were plotted and used to interpret the link between the equilibrium conditions of crystallization and the symplectitic microstructures. This example illustrates the usefulness of XMapTools for studying variations of the chemical composition of minerals and for retrieving information on metamorphic conditions on a microscale, towards computation of continuous pressure–temperature-and relative time path in zoned metamorphic minerals not affected by post-crystallization diffusion.

Dehydration of the zeolite merlinoite from the Khibiny massif, Russia: an in situ temperature-dependent single-crystal X-ray study

Dehydration behaviour of the zeolite merlinoite, NaK11[Al12Si20O64]·15H2O, from the Khibiny massif (Russia) was studied by means of single-crystal X-ray diffraction conjoined with step-wise heating to 225 C. At room temperature merlinoite has the space group Immm with a = 14.0312(5), b = 14.2675(6), c = 10.0874(4) Å, and V = 2019.40(14) Å3. At 75 °C the merlinoite structure undergoes pronounced dehydration accompanied by a phase transition to a structure that has the space group P42/nmc and remains consistent at elevated temperature. A fully dehydrated phase occurs at 200 °C (at 225 °C: a = 13.341(4), b = 13.341(4), c = 9.707(4) Å, V = 1727.7(12) Å3). Dehydration-induced framework distortion and symmetry were found to be different from those observed for synthetic potassium merlinoite with the K11.5[Al11.5Si20.5O64]·15H2O composition.