Progress in multi-ion counting spark-source mass spectrometry (MIC-SSMS) for the analysis of geological samples

Spark source mass spectrometry (SSMS) has experienced important and significant improvements in nearly all analytical features by the use of a multiple ion counting (MIC) system. Two procedures have recently been developed to further increase the analytical capabilities of MIC-SSMS in geochemistry. These are a mathematical correction of interferences, which is often necessary for the ultra trace element analysis of Nb, Ta, Zr, Hf and Y, and the development of an autospark system to hold the total ion beam constant. New analytical data for geological samples, especially international reference materials, are presented using the improved MIC-SSMS technique. The data set consists of high precision and low abundance data for Zr, Nb and Y in depleted reference materials. The MIC-SSMS results are compared with those of conventional SSMS using photoplates for ion detection. The precision of the MIC-SSMS isotope ratio measurements (about 1%) is more than a factor of 3 better than that of conventional SSMS, as demonstrated by analyses of Hawaiian samples. Total uncertainties of MIC-SSMS concentration data including all sources of error are generally between 2 and 5% for concentrations higher than about 0.3 microg/g and about 10% for trace element abundances in the ng/g range.     

Vernetzung und Abbau von Polyäthylenterephthalat durch Elektronenbestrahlung

Zusammenfassung PÄT-Folien wurden in Luft, Stickstoff und Vakuum bei 20 °C mit 1 MeV-Elektronen bestrahlt. Untersucht wurden Löslichkeit und Viskosität von Proben, die unmittelbar nach der Bestrahlung gelöst wurden.In allen untersuchten Fällen trat bei hohen Bestrahlungsdosen ein unlöslicher, d. h. vernetzter Anteil auf, dessen Ausbildung jedoch durch in den Proben enthaltene Feuchtigkeit verzögert werden kann. Bei niedrigen Bestrahlungsdosen bewirkt Feuchtigkeit einen Abbau des Polymeren, wie durch Viskositätsmessungen gezeigt wird.Aus den Gel-Messungen wurde derp ₀/q ₀-Wert für Bestrahlung in Luft, Stickstoff und Vakuum zu 1,05 bestimmt.Die Änderung des Gel-Anteils bei Lagerung der Proben zwischen Bestrahlung und Lösung wird diskutiert.

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Summary Polyethyleneterephthalate samples were irradiated in air, nitrogen and vacuum at 20 °C with 1 MeV electrons. The solubility of the samples and the viscosity of the solutions were studied immediately after irradiation. At high doses an insoluble crosslinked part was always observed. Crosslinking was delayed by moisture in the samples. At low irradiation doses moisture causes chain scission as shown by viscosity measurements. The ratiop ₀/q ₀ of degradation to crosslinking in the case of irradiation in air, nitrogen and vacuum was found by gel measurements to be 1.05. The insoluble gel-part changes with increasing storage time of the samples between irradiation and solution.

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Herrn Diplom-PhysikerH. Fischer sei an dieser Stelle für wertvolle Anregungen und Diskussionen besonders gedankt.     

A new spark source mass spectrometric technique for the analysis of sub-ng amounts of trace elements

Summary Spark source mass spectrometric tip-top-technique (TTT) is a new method for the analysis of sub-ng amounts of chemically separated trace elements in geological material. Besides its application to dissolved samples, TTT differs from conventional spark source mass spectrometry in reduction of measuring time (few minutes), photoplate background, and interferences by isobars and cluster-ions, resulting in enhanced sensitivities. Detection limits range from about 5 to 20 pg for the rare earth elements, U and Th, and from about 10 to 100 pg for noble metals. Precisions and accuracies of 1 to 5% are gained for trace elements abundances about 1 ng.A potential and especially useful application of TTT is the analysis of rocks available only in very small sample sizes and/or with very low concentration levels of trace elements. An additional application is the determination of osmium isotopes in geological material.

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Neues funkenmassenspektrometrisches Verfahren für die Analyse von sub-ng-Mengen von Spurenelementen

     

Development of a New Class of Inhibitors for the Malarial Aspartic Protease Plasmepsin II Based on a Central 7‐Azabicyclo[2.2.1]heptane Scaffold

Plasmepsin II (PMII), a malarial aspartic protease involved in the catabolism of hemoglobin in parasites of the genus Plasmodium, and renin, a human aspartic protease, share 35% sequence identity in their mature chains. Structures of 4‐arylpiperidine inhibitors complexed to human renin were reported by Roche recently. The major conformational changes, compared to a structure of renin, with a peptidomimetic inhibitor were identified and subsequently modeled in a structure of PMII (Fig. 1). This distorted structure of PMII served as active‐site model for a novel class of PMII inhibitors, according to a structure‐based de novo design approach (Fig. 2). These newly designed inhibitors feature a rigid 7‐azabicyclo[2.2.1]heptane scaffold, which, in its protonated form, is assumed to undergo ionic H‐bonding with the two catalytic Asp residues at the active site of PMII. Two substituents depart from the scaffold for occupancy of either the S1/S3 or S2′‐pocket and the hydrophobic flap pocket, newly created by the conformational changes in PMII. The inhibitors synthesized starting from N‐Boc‐protected 7‐azabicyclo[2.2.1]hept‐2‐ene ( 6 ; Schemes 1–5) displayed up to single‐digit micromolar activity (IC₅₀ values) toward PMII and good selectivity towards renin. The clear structure? activity relationship (SAR; Table) provides strong validation of the proposed conformational changes in PMII and the occupancy of the resulting hydrophobic flap pocket by our new inhibitors.     

Regularity analysis for stochastic partial differential equations with nonlinear multiplicative trace class noise

In this article spatial and temporal regularity of the solution process of a stochastic partial differential equation (SPDE) of evolutionary type with nonlinear multiplicative trace class noise is analyzed.     

Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations

High-dimensional partial differential equations (PDEs) appear in a number of models from the financial industry, such as in derivative pricing models, credit valuation adjustment models, or portfolio optimization models. The PDEs in such applications are high-dimensional as the dimension corresponds to the number of financial assets in a portfolio. Moreover, such PDEs are often fully nonlinear due to the need to incorporate certain nonlinear phenomena in the model such as default risks, transaction costs, volatility uncertainty (Knightian uncertainty), or trading constraints in the model. Such high-dimensional fully nonlinear PDEs are exceedingly difficult to solve as the computational effort for standard approximation methods grows exponentially with the dimension. In this work, we propose a new method for solving high-dimensional fully nonlinear second-order PDEs. Our method can in particular be used to sample from high-dimensional nonlinear expectations. The method is based on (1) a connection between fully nonlinear second-order PDEs and second-order backward stochastic differential equations (2BSDEs), (2) a merged formulation of the PDE and the 2BSDE problem, (3) a temporal forward discretization of the 2BSDE and a spatial approximation via deep neural nets, and (4) a stochastic gradient descent-type optimization procedure. Numerical results obtained using TensorFlow in Python illustrate the efficiency and the accuracy of the method in the cases of a 100-dimensional Black–Scholes–Barenblatt equation, a 100-dimensional Hamilton–Jacobi–Bellman equation, and a nonlinear expectation of a 100-dimensional G-Brownian motion.

     

The influence of hyperoxia on regional cerebral blood flow (rCBF), regional cerebral blood volume (rCBV) and cerebral blood flow velocity in the middle cerebral artery (CBFVMCA) in human volunteers

Conflicting results reported on the effects of hyperoxia on cerebral hemodynamics have been attributed mainly to methodical and species differences. In the present study contrast-enhanced magnetic resonance imaging (MRI) perfusion measurement was used to analyze the influence of hyperoxia (fraction of inspired oxygen (FiO2) = 1.0) on regional cerebral blood flow (rCBF) and regional cerebral blood volume (rCBV) in awake, normoventilating volunteers (n = 19). Furthermore, the experiment was repeated in 20 volunteers for transcranial Doppler sonography (TCD) measurement of cerebral blood flow velocity in the middle cerebral artery (CBFV(MCA)). When compared to normoxia (FiO2 = 0.21), hyperoxia heterogeneously influenced rCBV (4.95 +/- 0.02 to 12.87 +/- 0.08 mL/100g (FiO2 = 0.21) vs. 4.50 +/- 0.02 to 13.09 +/- 0.09 mL/100g (FiO2 = 1.0). In contrast, hyperoxia diminished rCBF in all regions (68.08 +/- 0.38 to 199.58 +/- 1.58 mL/100g/min (FiO2 = 0.21) vs. 58.63 +/- 0.32 to 175.16 +/- 1.51 mL/100g/min (FiO2 = 1.0)) except in parietal and left frontal gray matter. CBFV(MCA) remained unchanged regardless of the inspired oxygen fraction (62 +/- 9 cm/s (FiO2 = 0.21) vs. 64 +/- 8 cm/s (FiO2 = 1.0)). Finding CBFV(MCA) unchanged during hyperoxia is consistent with the present study's unchanged rCBF in parietal and left frontal gray matter. In these fronto-parietal regions predominantly fed by the middle cerebral artery, the vasoconstrictor effect of oxygen was probably counteracted by increased perfusion of foci of neuronal activity controlling general behavior and arousal.