Faddeev calculations of break-up reactions with realistic experimental constraints

We present a method to integrate predictions from a theoretical model of a reaction with three bodies in the final state over the region of phase space covered by a given experiment. The method takes into account the true experimental acceptance, as well as variations of detector efficiency, and eliminates the need for a Monte-Carlo simulation of the detector setup. The method is applicable to kinematically complete experiments. Examples for the use of this method include several polarization observables in dp break-up at 270 MeV. The calculations are carried out in the Faddeev framework with the CD Bonn nucleon-nucleon interaction, with or without the inclusion of an additional three-nucleon force.Comment: 18 pages, 9 figure

Host and Distribution Lists of Chiggers (Trombiculidae and Leeuwenhoekiidae), of North American Wild Vertebrates North of Mexico

Information concerning chiggers found on wild vertebrates of North America north of Mexico is summarized. Included are lists a) of the chiggers organized taxonomically, b) hosts from which each species has been reported, and c) states and provinces with references for each separate recor

Hydrodynamic dispersion within porous biofilms

Many microorganisms live within surface-associated consortia, termed biofilms, that can form intricate porous structures interspersed with a network of fluid channels. In such systems, transport phenomena, including flow and advection, regulate various aspects of cell behavior by controlling nutrient supply, evacuation of waste products, and permeation of antimicrobial agents. This study presents multiscale analysis of solute transport in these porous biofilms. We start our analysis with a channel-scale description of mass transport and use the method of volume averaging to derive a set of homogenized equations at the biofilm-scale in the case where the width of the channels is significantly smaller than the thickness of the biofilm. We show that solute transport may be described via two coupled partial differential equations or telegrapher's equations for the averaged concentrations. These models are particularly relevant for chemicals, such as some antimicrobial agents, that penetrate cell clusters very slowly. In most cases, especially for nutrients, solute penetration is faster, and transport can be described via an advection-dispersion equation. In this simpler case, the effective diffusion is characterized by a second-order tensor whose components depend on (1) the topology of the channels' network; (2) the solute's diffusion coefficients in the fluid and the cell clusters; (3) hydrodynamic dispersion effects; and (4) an additional dispersion term intrinsic to the two-phase configuration. Although solute transport in biofilms is commonly thought to be diffusion dominated, this analysis shows that hydrodynamic dispersion effects may significantly contribute to transport

Experimental search for evidence of the three-nucleon force and a new analysis method

A research program with the aim of investigating the spin dependence of the three-nucleon continuum in pd collisions at intermediate energies was carried out at IUCF using the Polarized INternal Target EXperiments (PINTEX) facility. In the elastic scattering experiment at 135 and 200 MeV proton beam energies a total of 15 independent spin observables were obtained. The breakup experiment was done with a vector and tensor polarized deuteron beam of 270 MeV and an internal polarized hydrogen gas target. We developed a novel technique for the analysis of the breakup observables, the sampling method. The new approach takes into account acceptance and non-uniformities of detection efficiencies and is suitable for any kinematically complete experiment with three particles in the final state.Comment: Contribution to the 19th European Few-Body Conference, Groningen Aug. 23-27, 200

Analyzing Powers and Spin Correlation Coefficients for p+d Elastic Scattering at 135 and 200 MeV

The proton and deuteron analyzing powers and 10 of the possible 12 spin correlation coefficients have been measured for p+d elastic scattering at proton bombarding energies of 135 and 200 MeV. The results are compared with Faddeev calculations using two different NN potentials. The qualitative features of the extensive data set on the spin dependence in p+d elastic scattering over a wide range of angles presented here are remarkably well explained by two-nucleon force predictions without inclusion of a three-nucleon force. The remaining discrepancies are, in general, not alleviated when theoretical three-nucleon forces are included in the calculations.Comment: 43 pages, 12 figures, accepted for publication by Phys. Rev.

Comparing the health and welfare of refugees and non-refugees at the outset of the COVID-19 pandemic: the results of a community needs assessment.

Refugees are a vulnerable population who experience significant health disparities. They may also be at disproportionately high risk of adverse outcomes due to the COVID-19 pandemic. This paper presents the results of a community needs assessment to investigate the impact of the pandemic on health and welfare in a refugee relocation community in the United States. A multilingual data collection team made up of refugees surveyed 179 participants (128 refugees vs. 51 non-refugees). Only 55.9% of refugee respondents said they would be able to provide enough food for their family this week, compared with 84.0% of non-refugees (p \u3c 0.01), and this difference was even greater for food next week (29.4% vs. 76.0%, p \u3c 0.01). A non-significantly smaller proportion of refugees reported knowing where to go if they were sick (69.1% vs. 81.6%, χ2 = 2.8, p = 0.10), and being able to get the medicine they need (75.0% vs. 87.8%, p = 0.07), while significantly fewer refugees reported feeling safe at home (72.8 vs. 87.8%, χ2 = 4.5, p = 0.04). Overall, refugees fared worse on nearly every measure. These findings should motivate further observational research and inform clinicians about the significant disparities in social determinants of health that refugees may experience during the pandemic

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more interindividual variability. METHODS: Patient-specific models were constructed for 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, and 16 long-standing persistent), undergoing first ablation. Patients were followed for 1 year using ambulatory ECG monitoring. Each patient-specific biophysical model combined differing fibrosis patterns, fiber orientation maps, electrical properties, and ablation patterns to capture uncertainty in atrial properties and to test the ability of the tissue to sustain fibrillation. These simulation stress tests of different model variants were postprocessed to calculate atrial fibrillation simulation metrics. Machine learning classifiers were trained to predict atrial fibrillation recurrence using features from the patient history, imaging, and atrial fibrillation simulation metrics. RESULTS: We performed 1100 atrial fibrillation ablation simulations across 100 patient-specific models. Models based on simulation stress tests alone showed a maximum accuracy of 0.63 for predicting long-term fibrillation recurrence. Classifiers trained to history, imaging, and simulation stress tests (average 10-fold cross-validation area under the curve, 0.85±0.09; recall, 0.80±0.13; precision, 0.74±0.13) outperformed those trained to history and imaging (area under the curve, 0.66±0.17) or history alone (area under the curve, 0.61±0.14). CONCLUSION: A novel computational pipeline accurately predicted long-term atrial fibrillation recurrence in individual patients by combining outcome data with patient-specific acute simulation response. This technique could help to personalize selection for atrial fibrillation ablation