Conditional preparation of states containing a definite number of photons

A technique for conditionally creating single- or multimode photon-number states is analyzed using Bayesian theory. We consider the heralded N-photon states created from the photons produced by an unseeded optical parametric amplifier when the heralding detector is the time-multiplexed photon-number-resolving detector recently demonstrated by Fitch, et al. [Phys. Rev. A 68, 043814 (2003).] and simultaneously by Achilles, et al. [Opt. Lett. 28, 2387 (2003).]. We find that even with significant loss in the heralding detector, fields with sub-Poissonian photon-number distributions can be created. We also show that heralded multimode fields created using this technique are more robust against detector loss than are single-mode fields.Comment: 6 pages, 6 figures, reference added, typos corrected, content update

Self-field effects upon the critical current density of flat superconducting strips

We develop a general theory to account self-consistently for self-field effects upon the average transport critical current density Jc of a flat type-II superconducting strip in the mixed state when the bulk pinning is characterized by a field-dependent depinning critical current density Jp(B), where B is the local magnetic flux density. We first consider the possibility of both bulk and edge-pinning contributions but conclude that bulk pinning dominates over geometrical edge-barrier effects in state-of-the-art YBCO films and prototype second-generation coated conductors. We apply our theory using the Kim model, JpK(B) = JpK(0)/(1+|B|/B0), as an example. We calculate Jc(Ba) as a function of a perpendicular applied magnetic induction Ba and show how Jc(Ba) is related to JpK(B). We find that Jc(Ba) is very nearly equal to JpK(Ba) when Ba > Ba*, where Ba* is the value of Ba that makes the net flux density zero at the strip's edge. However, Jc(Ba) is suppressed relative to JpK(Ba) at low fields when Ba < Ba*, with the largest suppression occurring when Ba*/B0 is of order unity or larger.Comment: 9 pages, 4 figures, minor revisions to add four reference

Comparing predictions made by a prediction model, clinical score, and physicians Pediatric asthma exacerbations in the emergency department

Background: Asthma exacerbations are one of the most common medical reasons for children to be brought to the hospital emergency department (ED). Various prediction models have been proposed to support diagnosis of exacerbations and evaluation of their severity. Objectives: First, to evaluate prediction models constructed from data using machine learning techniques and to select the best performing model. Second, to compare predictions from the selected model with predictions from the Pediatric Respiratory Assessment Measure (PRAM) score, and predictions made by ED physicians. Design: A two-phase study conducted in the ED of an academic pediatric hospital. In phase 1 data collected prospectively using paper forms was used to construct and evaluate five prediction models, and the best performing model was selected. In phase 2, data collected prospectively using a mobile system was used to compare the predictions of the selected prediction model with those from PRAM and ED physicians. Measurements: Area under the receiver operating characteristic curve and accuracy in phase 1; accuracy, sensitivity, specificity, positive and negative predictive values in phase 2. Results: In phase 1 prediction models were derived from a data set of 240 patients and evaluated using 10-fold cross validation. A naive Bayes (NB) model demonstrated the best performance and it was selected for phase 2. Evaluation in phase 2 was conducted on data from 82 patients. Predictions made by the NB model were less accurate than the PRAM score and physicians (accuracy of 70.7%, 73.2% and 78.0% respectively), however, according to McNemar’s test it is not possible to conclude that the differences between predictions are statistically significant. Conclusion: Both the PRAM score and the NB model were less accurate than physicians. The NB model can handle incomplete patient data and as such may complement the PRAM score. However, it requires further research to improve its accuracy

Feasibility of direct digital sampling for diffuse optical frequency domain spectroscopy in tissue

Frequency domain optical spectroscopy in the diffusive regime is currently being investigated for biomedical applications including tumor detection, therapy monitoring, exercise metabolism, and others. Analog homodyne or heterodyne detection of sinusoidally modulated signals have been the predominant method for measuring phase and amplitude of photon density waves that have traversed through tissue. Here we demonstrate the feasibility of utilizing direct digital sampling of modulated signals using a 3.6 Gigasample/second 12 bit Analog to Digital Converter. Digitally synthesized modulated signals between 50MHz and 400MHz were measured on tissue simulating phantoms at six near-infrared wavelengths. An amplitude and phase precision of 1% and 0.6 degrees were achieved during drift tests. Amplitude, phase, scattering and absorption values were compared with a well-characterized network analyzer based diffuse optical device. Measured optical properties measured with both systems were within 3.6% for absorption and 2.8% for scattering over a range of biologically relevant values. Direct digital sampling represents a viable method for frequency domain diffuse optical spectroscopy and has the potential to reduce system complexity, size, and cost

Skeletons for Distributed Topological Computation

Parallel implementation of topological algorithms is highly desirable, but the challenges, from reconstructing algorithms around independent threads through to runtime load balancing, have proven to be formidable. This problem, made all the more acute by the diversity of hardware platforms, has led to new kinds of implementation platform for computational science, with sophisticated runtime systems managing and coordinating large threadcounts to keep processing elements heavily utilized. While simpler and more portable than direct management of threads, these approaches still entangle program logic with resource management. Similar kinds of highly parallel runtime system have also been developed for functional languages. Here, however, language support for higher-order functions allows a cleaner separation between the algorithm and `skeletons' that express generic patterns of parallel computation. We report results on using this technique to develop a distributed version of the Joint Contour Net, a generalization of the Contour Tree to multifields. We present performance comparisons against a recent Haskell implementation using shared-memory parallelism, and initial work on a skeleton for distributed memory implementation that utilizes an innovative strategy to reduce inter-process communication overheads

Observation of single collisionally cooled trapped ions in a buffer gas

Individual Ba ions are trapped in a gas-filled linear ion trap and observed with a high signal-to-noise ratio by resonance fluorescence. Single-ion storage times of ~5 min (~1 min) are achieved using He (Ar) as a buffer gas at pressures in the range 8e-5 - 4e-3 torr. Trap dynamics in buffer gases are experimentally studied in the simple case of single ions. In particular, the cooling effects of light gases such as He and Ar and the destabilizing properties of heavier gases such as Xe are studied. A simple model is offered to explain the observed phenomenology.Comment: 5 pages, 4 figures, accepted for publication in Phys. Rev. A. Minor text and figure change

A Task-based Support Architecture for Developing Point-of-care Clinical Decision Support Systems for the Emergency Department

Objectives: The purpose of this study was to create a task-based support architecture for developing clinical decision support systems (CDSSs) that assist physicians in making decisions at the point-of-care in the emergency department (ED). The backbone of the proposed architecture was established by a task-based emergency workflow model for a patient-physician encounter. Methods: The architecture was designed according to an agent-oriented paradigm. Specifically, we used the O-MaSE (Organization-based Multi-agent System Engineering) method that allows for iterative translation of functional requirements into architectural components (e.g., agents). The agent-oriented paradigm was extended with ontology-driven design to implement ontological models representing knowledge required by specific agents to operate. Results: The task-based architecture allows for the creation of a CDSS that is aligned with the task-based emergency workflow model. It facilitates decoupling of executable components (agents) from embedded domain knowledge (ontological models), thus supporting their interoperability, sharing, and reuse. The generic architecture was implemented as a pilot system, MET3-AE – a CDSS to help with the management of pediatric asthma exacerbation in the ED. The system was evaluated in a hospital ED. Conclusions: The architecture allows for the creation of a CDSS that integrates support for all tasks from the task-based emergency workflow model, and interacts with hospital information systems. Proposed architecture also allows for reusing and sharing system components and knowledge across disease-specific CDSSs

Increasing impact of warm droughts on northern ecosystem productivity over recent decades

This is the author accepted manuscript. The final version is available from Nature Research via the DOI in this recordData availability: The data to reproduce and further interpret the main results presented are publicly available at figshare. The TRENDY v.6 datasets applied in this study have been preprocessed by M.O. and are available from the University of Exeter (https://doi.org/10.24378/exe.2883) and on request. The original TRENDY v.6 datasets can be requested from S. Sitch ([email protected]) and P. Friedlingstein ([email protected]). The FLUXCOM dataset is publicly available through the FLUXCOM data portal (https://www.bgc-jena.mpg.de/geodb/projects/FileDetails.php). The LUE datasets are provided by W.K.S. and publicly available at https://wkolby.org/data-code/. The CRUNCEP reanalysis data are available through the Climatic Research Unit data portal (https://crudata.uea.ac.uk/cru/data/ncep/#dataset_access).Code availability: All relevant codes to reproduce the figures presented in this study are publicly available at figshare (https://doi.org/10.6084/m9.figshare.14845005). Further codes and materials are available from D.G. on request.Climate extremes such as droughts and heatwaves have a large impact on terrestrial carbon uptake by reducing gross primary production (GPP). While the evidence for increasing frequency and intensity of climate extremes over the last decades is growing, potential systematic adverse shifts in GPP have not been assessed. Using observationally-constrained and process-based model data, we estimate that particularly northern midlatitude ecosystems experienced a +10.6% increase in negative GPP extremes in the period 2000–2016 compared to 1982–1998. We attribute this increase predominantly to a greater impact of warm droughts, in particular over northern temperate grasslands (+95.0% corresponding mean increase) and croplands (+84.0%), in and after the peak growing season. These results highlight the growing vulnerability of ecosystem productivity to warm droughts, implying increased adverse impacts of these climate extremes on terrestrial carbon sinks as well as a rising pressure on global food security.Swiss National Science Foundation (SNSF)Helmholtz Initiative and Networking FundNewton FundNAS