Use of thermodynamic properties of metal-gas systems as low-pressure standards

Modified version of Sievert's apparatus accurately calibrates low pressure measuring instruments. Metal-gas system is composed of hydrogen in two-phase equilibrium with erbium to obtain reproducible hydrogen pressures

A study of metal oxygen and metal nitrogen systems for use as reduced pressure standards

Metal-oxygen and metal-nitrogen systems for use as reduced pressure standards using Sieverts apparatu

Land Use Planning after a Natural Disaster

Recovery from a natural disaster is difficult, expensive, and can take ten years or more. Many contend that recovery planning can be ordered, knowable, and predictable and that the destruction of buildings and displacement of the population provide an opportunity to build back better. This thesis examines the complexity of recovery through the lens of land use planning. Land use planning serves as the central focus because land provides an individual or family their livelihood and its use underlies the economy. The thesis considers two planning models -- rational comprehensive and incremental. The thesis concludes that incremental planning is more appropriate for recovery planning, but that even during recovery the community needs post recovery goals and objectives to provide context to their day-to-day decisions. A more comprehensive planning process is better suited for developing and articulating post recovery goals and objectives

Land Use Planning after a Natural Disaster

Recovery from a natural disaster is difficult, expensive, and can take ten years or more. Many contend that recovery planning can be ordered, knowable, and predictable and that the destruction of buildings and displacement of the population provide an opportunity to build back better. This thesis examines the complexity of recovery through the lens of land use planning. Land use planning serves as the central focus because land provides an individual or family their livelihood and its use underlies the economy. The thesis considers two planning models -- rational comprehensive and incremental. The thesis concludes that incremental planning is more appropriate for recovery planning, but that even during recovery the community needs post recovery goals and objectives to provide context to their day-to-day decisions. A more comprehensive planning process is better suited for developing and articulating post recovery goals and objectives

Implementation and impact of pediatric antimicrobial stewardship programs: a systematic scoping review.

Background: Antibiotics are the most common medicines prescribed to children in hospitals and the community, with a high proportion of potentially inappropriate use. Antibiotic misuse increases the risk of toxicity, raises healthcare costs, and selection of resistance. The primary aim of this systematic review is to summarize the current state of evidence of the implementation and outcomes of pediatric antimicrobial stewardship programs (ASPs) globally. Methods: MEDLINE, Embase and Cochrane Library databases were systematically searched to identify studies reporting on ASP in children aged 0-18 years and conducted in outpatient or in-hospital settings. Three investigators independently reviewed identified articles for inclusion and extracted relevant data. Results: Of the 41,916 studies screened, 113 were eligible for inclusion in this study. Most of the studies originated in the USA (52.2%), while a minority were conducted in Europe (24.7%) or Asia (17.7%). Seventy-four (65.5%) studies used a before-and-after design, and sixteen (14.1%) were randomized trials. The majority (81.4%) described in-hospital ASPs with half of interventions in mixed pediatric wards and ten (8.8%) in emergency departments. Only sixteen (14.1%) studies focused on the costs of ASPs. Almost all the studies (79.6%) showed a significant reduction in inappropriate prescriptions. Compliance after ASP implementation increased. Sixteen of the included studies quantified cost savings related to the intervention with most of the decreases due to lower rates of drug administration. Seven studies showed an increased susceptibility of the bacteria analysed with a decrease in extended spectrum beta-lactamase producers E. coli and K. pneumoniae; a reduction in the rate of P. aeruginosa carbapenem resistance subsequent to an observed reduction in the rate of antimicrobial days of therapy; and, in two studies set in outpatient setting, an increase in erythromycin-sensitive S. pyogenes following a reduction in the use of macrolides. Conclusions: Pediatric ASPs have a significant impact on the reduction of targeted and empiric antibiotic use, healthcare costs, and antimicrobial resistance in both inpatient and outpatient settings. Pediatric ASPs are now widely implemented in the USA, but considerable further adaptation is required to facilitate their uptake in Europe, Asia, Latin America and Africa

Analytic continuation by averaging Pad\'e approximants

The ill-posed analytic continuation problem for Green's functions and self-energies is investigated by revisiting the Pad\'{e} approximants technique. We propose to remedy the well-known problems of the Pad\'{e} approximants by performing an average of several continuations, obtained by varying the number of fitted input points and Pad\'{e} coefficients independently. The suggested approach is then applied to several test cases, including Sm and Pr atomic self-energies, the Green's functions of the Hubbard model for a Bethe lattice and of the Haldane model for a nano-ribbon, as well as two special test functions. The sensitivity to numerical noise and the dependence on the precision of the numerical libraries are analysed in detail. The present approach is compared to a number of other techniques, i.e. the non-negative least-square method, the non-negative Tikhonov method and the maximum entropy method, and is shown to perform well for the chosen test cases. This conclusion holds even when the noise on the input data is increased to reach values typical for quantum Monte Carlo simulations. The ability of the algorithm to resolve fine structures is finally illustrated for two relevant test functions.Comment: 10 figure

The RHIC Zero Degree Calorimeter

High Energy collisions of nuclei usually lead to the emission of evaporation neutrons from both ``beam'' and ``target'' nuclei. At the RHIC heavy ion collider with 100GeV/u beam energy, evaporation neutrons diverge by less than $~2$ milliradians from the beam axis Neutral beam fragments can be detected downstream of RHIC ion collisions (and a large aperture Accelerator dipole magnet) if $\theta\leq$ 4 mr but charged fragments in the same angular range are usually too close to the beam trajectory. In this 'zero degree' region produced particles and other secondaries deposit negligible energy when compared with that of beam fragmentation neutrons. The purpose of the RHIC zero degree calorimeters (ZDC's) is to detect neutrons emitted within this cone along both beam directions and measure their total energy (from which we calculate multiplicity). The ZDC coincidence of the 2 beam directions is a minimal bias selection of heavy ion collisions. This makes it useful as an event trigger and a luminosity monitor\cite{baltz} and for this reason we built identical detectors for all 4 RHIC experiments. The neutron multiplicity is also known to be correlated with event geometry \cite{appel} and will be used to measure collision centrality in mutual beam int eractions.Comment: 18 pages, 12 figure

Deep learning based tissue analysis predicts outcome in colorectal cancer

Image-based machine learning and deep learning in particular has recently shown expert-level accuracy in medical image classification. In this study, we combine convolutional and recurrent architectures to train a deep network to predict colorectal cancer outcome based on images of tumour tissue samples. The novelty of our approach is that we directly predict patient outcome, without any intermediate tissue classification. We evaluate a set of digitized haematoxylin-eosin-stained tumour tissue microarray (TMA) samples from 420 colorectal cancer patients with clinicopathological and outcome data available. The results show that deep learning-based outcome prediction with only small tissue areas as input outperforms (hazard ratio 2.3; CI 95% 1.79-3.03; AUC 0.69) visual histological assessment performed by human experts on both TMA spot (HR 1.67; CI 95% 1.28-2.19; AUC 0.58) and whole-slide level (HR 1.65; CI 95% 1.30-2.15; AUC 0.57) in the stratification into low-and high-risk patients. Our results suggest that state-of-the-art deep learning techniques can extract more prognostic information from the tissue morphology of colorectal cancer than an experienced human observer.Peer reviewe