Theoretical analysis of uranium-doped thorium dioxide: Introduction of a thoria force field with explicit polarization

Thorium dioxide is used industrially in high temperature applications, but more insight is needed into the behavior of the material as part of a mixed-oxide (MOX) nuclear fuel, incorporating uranium. We have developed a new interatomic potential model including polarizability via a shell model, and commensurate with a prominent existing UO2 potential, to conduct configurational analyses and to investigate the thermophysical properties of uranium-doped ThO2. Using the GULP and Site Occupancy Disorder (SOD) computational codes, we have analyzed the distribution of low concentrations of uranium in the bulk material, where we have not observed the formation of uranium clusters or the dominance of a single preferred configuration. We have calculated thermophysical properties of pure thorium dioxide and Th(1−x)UxO2 which generated values in very good agreement with experimental data

Novel Approaches towards Highly Selective Self-Powered Gas Sensors

The prevailing design approaches of semiconductor gas sensors struggle to overcome most of their current limitations such as poor selectivity, and high power consumption. Herein, a new sensing concept based on devices that are capable of detecting gases without the need of any external power sources required to activate interaction of gases with sensor or to generate the sensor read out signal. Based on the integration of complementary functionalities (namely; powering and sensing) in a singular nanostructure, self-sustained gas sensors will be demonstrated. Moreover, a rational methodology to design organic surface functionalization that provide high selectivity towards single gas species will also be discussed. Specifically, theoretical results, confirmed experimentally, indicate that precisely tuning of the sterical and electronic structure of sensor material/organic interfaces can lead to unprecedented selectivity values, comparable to those typical of bioselective processes. Finally, an integrated gas sensor that combine both the self-powering and selective detection strategies in one single device will also be presented. © 2015 Published by Elsevier Ltd.Peer ReviewedPostprint (published version

Derivation and validation of a multivariate model to predict mortality from pulmonary embolism with cancer: The POMPE-C tool

BackgroundClinical guidelines recommend risk stratification of patients with acute pulmonary embolism (PE). Active cancer increases risk of PE and worsens prognosis, but also causes incidental PE that may be discovered during cancer staging. No quantitative decision instrument has been derived specifically for patients with active cancer and PE. Methods Classification and regression technique was used to reduce 25 variables prospectively collected from 408 patients with AC and PE. Selected variables were transformed into a logistic regression model, termed POMPE-C, and compared with the pulmonary embolism severity index (PESI) score to predict the outcome variable of death within 30 days. Validation was performed in an independent sample of 182 patients with active cancer and PE. Results POMPE-C included eight predictors: body mass, heart rate > 100, respiratory rate, SaO2%, respiratory distress, altered mental status, do not resuscitate status, and unilateral limb swelling. In the derivation set, the area under the ROC curve for POMPE-C was 0.84 (95% CI: 0.82-0.87), significantly greater than PESI (0.68, 0.60-0.76). In the validation sample, POMPE-C had an AUC of 0.86 (0.78-0.93). No patient with POMPE-C estimate ≤ 5% died within 30 days (0/50, 0-7%), whereas 10/13 (77%, 46-95%) with POMPE-C estimate > 50% died within 30 days. Conclusion In patients with active cancer and PE, POMPE-C demonstrated good prognostic accuracy for 30 day mortality and better performance than PESI. If validated in a large sample, POMPE-C may provide a quantitative basis to decide treatment options for PE discovered during cancer staging and with advanced cancer

Na+/K+-ATPase is a new interacting partner for the neuronal glycine transporter GlyT2 that downregulates its expression in vitro and in vivo

The neuronal glycine transporter GlyT2 plays a fundamental role in the glycinergic neurotransmission by recycling the neurotransmitter to the presynaptic terminal. GlyT2 is the main supplier of glycine for vesicle refilling, a process that is absolutely necessary to preserve quantal glycine content in synaptic vesicles. Alterations in GlyT2 activity modify glycinergic neurotransmission and may underlie several neuromuscular disorders, such as hyperekplexia, myoclonus, dystonia, and epilepsy. Indeed, mutations in the gene encoding GlyT2 are the main presynaptic cause of hyperekplexia in humans and produce congenital muscular dystonia type 2 (CMD2) in Belgian Blue cattle. GlyT2 function is strictly coupled to the sodium electrochemical gradient actively generated by the Na+/K+-ATPase (NKA). GlyT2 cotransports 3Na+/Cl-/glycine generating large rises of Na+ inside the presynaptic terminal that must be efficiently reduced by the NKA to preserve Na+ homeostasis. In this work, we have used high-throughput mass spectrometry to identify proteins interacting with GlyT2 in the CNS. NKA was detected as a putative candidate and through reciprocal coimmunoprecipitations and immunocytochemistry analyses the association between GlyT2 and NKA was confirmed. NKA mainly interacts with the raft-associated active pool of GlyT2, and low and high levels of the specific NKA ligand ouabain modulate the endocytosis and total expression of GlyT2 in neurons. The ouabain-mediated downregulation of GlyT2 also occurs in vivo in two different systems: zebrafish embryos and adult rats, indicating that this NKA-mediated regulatory mechanism is evolutionarily conserved and may play a relevant role in the physiological control of inhibitory glycinergic neurotransmission

Distributed flow optimization and cascading effects in weighted complex networks

We investigate the effect of a specific edge weighting scheme $\sim (k_i k_j)^{\beta}$ on distributed flow efficiency and robustness to cascading failures in scale-free networks. In particular, we analyze a simple, yet fundamental distributed flow model: current flow in random resistor networks. By the tuning of control parameter $\beta$ and by considering two general cases of relative node processing capabilities as well as the effect of bandwidth, we show the dependence of transport efficiency upon the correlations between the topology and weights. By studying the severity of cascades for different control parameter $\beta$, we find that network resilience to cascading overloads and network throughput is optimal for the same value of $\beta$ over the range of node capacities and available bandwidth

Expansion algorithm for the density matrix

A purification algorithm for expanding the single-particle density matrix in terms of the Hamiltonian operator is proposed. The scheme works with a predefined occupation and requires less than half the number of matrix-matrix multiplications compared to existing methods at low (90%) occupancy. The expansion can be used with a fixed chemical potential in which case it is an asymmetric generalization of and a substantial improvement over grand canonical McWeeny purification. It is shown that the computational complexity, measured as number of matrix multiplications, essentially is independent of system size even for metallic materials with a vanishing band gap.Comment: 5 pages, 4 figures, to appear in Phys. Rev.

Direct Observation of Shock-Induced Disordering of Enstatite Below the Melting Temperature

We report in situ structural measurements of shock-compressed single crystal orthoenstatite up to 337 ± 55 GPa on the Hugoniot, obtained by coupling ultrafast X-ray diffraction to laser-driven shock compression. Shock compression induces a disordering of the crystalline structure evidenced by the appearance of a diffuse X-ray diffraction signal at nanosecond timescales at 80 ± 13 GPa on the Hugoniot, well below the equilibrium melting pressure (>170 GPa). The formation of bridgmanite and post-perovskite have been indirectly reported in microsecond-scale plate-impact experiments. Therefore, we interpret the high-pressure disordered state we observed at nanosecond scale as an intermediate structure from which bridgmanite and post-perovskite crystallize at longer timescales. This evidence of a disordered structure of MgSiO3 on the Hugoniot indicates that the degree of polymerization of silicates is a key parameter to constrain the actual thermodynamics of shocks in natural environments. © 2020. The Authors

Study of the D^0 \to pi^-pi^+pi^-pi^+ decay

Using data from the FOCUS (E831) experiment at Fermilab, we present new measurements for the Cabibbo-suppressed decay mode $D^0 \to \pi^-\pi^+\pi^-\pi^+$. We measure the branching ratio $\Gamma(D^0 \to\pi^+\pi^- \pi^+\pi^-)/\Gamma(D^0 \to K^-\pi^+\pi^-\pi^+) = 0.0914 \pm 0.0018 \pm 0.0022$. An amplitude analysis has been performed, a first for this channel, in order to determine the resonant substructure of this decay mode. The dominant component is the decay $D^0 \to a_1(1260)^+ \pi^-$, accounting for 60% of the decay rate. The second most dominant contribution comes from the decay $D^0 \to \rho(770)^0\rho(770)^0$, with a fraction of 25%. We also study the $a_1(1260)$ line shape and resonant substructure. Using the helicity formalism for the angular distribution of the decay $D^0 \to \rho(770)^0\rho(770)^0$, we measure a longitudinal polarization of $P_L = (71 \pm 4\pm 2)$%.Comment: 38 pages, 8 figures. accepted for publication in Physical Review

Search for Λc+→pK+π−\Lambda_c^+ \to p K^+ \pi^- and Ds+→K+K+π−D_s^+ \to K^+ K^+ \pi^- Using Genetic Programming Event Selection

We apply a genetic programming technique to search for the double Cabibbo suppressed decays $\Lambda_c^+ \to p K^+ \pi^-$ and $D_s^+ \to K^+ K^+ \pi^-$. We normalize these decays to their Cabibbo favored partners and find $\text{BR}($\Lambda_c^+ \to p K^+ \pi^-$)/\text{BR}($\Lambda_c^+ \to p K^- \pi^+$) = (0.05 \pm 0.26 \pm 0.02)$ and $\text{BR}($D_s^+ \to K^+ K^+ \pi^-$)/\text{BR}($D_s^+ \to K^+ K^- \pi^+$) = (0.52\pm 0.17\pm 0.11)$ where the first errors are statistical and the second are systematic. Expressed as 90% confidence levels (CL), we find $< 0.46$ and $< 0.78$ respectively. This is the first successful use of genetic programming in a high energy physics data analysis.Comment: 10 page

Measurement of the D+ and Ds+ decays into K+K-K+

We present the first clear observation of the doubly Cabibbo suppressed decay D+ --> K-K+K+ and the first observation of the singly Cabibbo suppressed decay Ds+ --> K-K+K+. These signals have been obtained by analyzing the high statistics sample of photoproduced charm particles of the FOCUS(E831) experiment at Fermilab. We measure the following relative branching ratios: Gamma(D+ --> K-K+K+)/Gamma(D+ --> K-pi+pi+) = (9.49 +/- 2.17(statistical) +/- 0.22(systematic))x10^-4 and Gamma(Ds+ --> K-K+K+)/Gamma(Ds+ --> K-K+pi+) = (8.95 +/- 2.12(statistical) +2.24(syst.) -2.31(syst.))x10^-3.Comment: 10 pages, 8 figure