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We are interested in obtaining solutions to parameterized linear systems of the form A(mu)x(mu) = b for many values of the parameter mu. Here A(mu) is large, sparse, and nonsingular with a nonlinear, analytic dependence on mu. Our approach approximates the solution to a linearized system in a flexible GMRES setting [Y. Saad, SIAM J. Sci. Comput., 14 (1993), pp. 461-469], where the linearization is based on a companion matrix similar to the operator in the infinite Arnoldi method [E. Jarlebring, W. Michiels, and K. Meerbergen, Numer. Math., 122 (2012), pp. 169-195]. This novel approach applies the action of a preconditioner inexactly, providing performance improvement over the method infinite GMRES [Jarlebring and Correnty, SIAM J. Matrix Anal. Appl., 43 (2022), pp. 1382-1405] without a loss of accuracy in general. The method returns a function (x) over tilde(mu) which is cheap to evaluate for different mu. We show that the error of our method is estimated based on the magnitude of the parameter mu, the inexactness of the preconditioning, and the spectrum of the companion matrix. Numerical examples from a finite element discretization of a Helmholtz equation with a parameterized material coefficient illustrate the competitiveness of our approach. The software used in the simulations is publicly available online, and all the experiments are reproducible., QC 20240409

Disease surveillance data was critical in supporting public health decisions throughout the coronavirus disease 2019 (COVID-19) pandemic. At the same time, the unprecedented circumstances of the pandemic revealed many shortcomings of surveillance systems for viral respiratory pathogens. Strengthening of surveillance systems was identified as a priority for the recently established Australian Centre for Disease Control, which represents a critical opportunity to review pre-pandemic and pandemic surveillance practices, and to decide on future priorities, during both pandemic and inter-pandemic periods. On 20 October 2022, we ran a workshop with experts from the academic and government sectors who had contributed to the COVID-19 response in Australia on 'The role of surveillance in epidemic response', at the University of New South Wales, Sydney, Australia. Following the workshop, we developed five recommendations to strengthen respiratory virus surveillance systems in Australia, which we present here. Our recommendations are not intended to be exhaustive. We instead chose to focus on data types that are highly valuable yet typically overlooked by surveillance planners. Three of the recommendations focus on data collection activities that support the monitoring and prediction of disease impact and the effectiveness of interventions (what to measure) and two focus on surveillance methods and capabilities (how to measure). Implementation of our recommendations would enable more robust, timely, and impactful epidemic analysis.

The firn layer on the Greenland Ice Sheet (GrIS) plays a crucial role in buffering surface meltwater runoff, which is constrained by the available firn pore space and impermeable ice layers that limit deeper meltwater percolation. Understanding these firn properties is essential for predicting current and future meltwater runoff and its contribution to global sea-level rise. While very-high-frequency (VHF) radars have been extensively used for surveying the GrIS, their lower bandwidth restricts direct firn stratigraphy extraction. In this study, we use concurrent VHF airborne radar and laser altimetry data collected as part of Operation IceBridge over the 2011-2019 period to investigate our hypothesis that vertical heterogeneities in firn (i.e. ice layers) cause vertical offsets in the radar surface reflection (dz). Our results, corroborated by modelling and firn core analyses, show that a dz larger than 1m is strongly related to the vertical heterogeneity of a firn profile and effectively delineates between vertically homogeneous and vertically heterogeneous firn profiles over a depth range of ∼4m. Temporal variations in dz align with climatic events and reveal an expansion of heterogeneous firn between 2011-2013 covering an area of ∼350815km2, followed by firn replenishment over the years 2014-2019 spanning an area of ∼667725km2. Our approach reveals the firn evolution of key regions on the Greenland Ice Sheet, providing valuable insights for detecting potential alterations in meltwater runoff patterns.

Growing research evidence indicates student learning gains from guided representation construction/invention in school science and mathematics. In this inquiry approach, students address challenges around what features of a phenomenon/problem to attend to, what data to collect, how and why, and make collective judgments about multimodal accounts of phenomena. However, researchers to date have tended to focus on student learning rather than on the teacher’s role in guiding various phases of inquiry. In this paper we report on (a) analysis of Grade 1 students’ engagement in interdisciplinary mathematics and science inquiry practices in a classroom sequence in ecology; (b) the teacher’s role in guiding such inquiry; and (c) interpretation of these practices in terms of support of student transduction (connecting and remaking meanings across representations in different modes). Data from our study included video capture of two case study teachers’ guidance of tasks and classroom discussion and student artefacts. We examine the classroom processes through which the teachers used students’ invention and revision of data displays to teach the concepts of living things, diversity, distribution and adaptive features related to habitat in science. Mathematical processes included constructing and interpreting mapping, measurement and data modelling, sampling and using a scale. The analysis offers fresh insights into how teachers support student learning in these two subjects, through discrete stages of orienting, representation challenge, building consensus and applying and extending representational systems.

The use of mini-CT specimens for the fracture characterization of structural steels is currently a topic of great interest from both scientific and technical points of view, mainly driven by the needs and requirements of the nuclear industry. In fact, the long-term operation of nuclear plants requires accurate characterization of the reactor pressure vessel materials and evaluation of the embrittlement caused by neutron irradiation without applying excessive conservatism. However, the amount of material placed inside the surveillance capsules used to characterize the resulting degradation is generally small. Consequently, in order to increase the reliability of fracture toughness measurements and reduce the volume of material needed for the tests, it is necessary to develop innovative characterization techniques, among which the use of mini-CT specimens stands out. In this context, this paper provides a review of the use of mini-CT specimens for the fracture characterization of ferritic steels, with particular emphasis on those used by the nuclear industry. The main results obtained so far, revealing the potential of this technique, together with the main scientific and technical issues will be thoroughly discussed. Recommendations for several key topics for future research are also provided.

Circadian clocks temporally orchestrate biological processes critical for cellular/organ function. For example, the cardiomyocyte circadian clock modulates cardiac metabolism, signaling, and electrophysiology over the course of the day, such that, disruption of the clock leads to age-onset cardiomyopathy (through unknown mechanisms). Here, we report that genetic disruption of the cardiomyocyte clock results in chronic induction of the transcriptional repressor E4BP4. Importantly, E4BP4 deletion prevents age-onset cardiomyopathy following clock disruption. These studies also indicate that E4BP4 regulates both cardiac metabolism (eg, fatty acid oxidation) and electrophysiology (eg, QT interval). Collectively, these studies reveal that E4BP4 is a novel regulator of both cardiac physiology and pathophysiology.

We present a new Krylov subspace recycling method for solving a linear system of equations, or a sequence of slowly changing linear systems. Our new method, named GMRES-SDR, combines randomized sketching and deflated restarting in a way that avoids orthogononalizing a full Krylov basis. We provide new theory which characterizes sketched GMRES with and without augmentation as a projection method using a semi-inner product. We present results of numerical experiments demonstrating the effectiveness of GMRES-SDR over competitor methods such as GMRES-DR and GCRO-DR., Comment: 26 Pages; 9 Figures; 4 Tables

We consider approximating solutions to parameterized linear systems of the form $A(\mu_1,\mu_2) x(\mu_1,\mu_2) = b$, where $(\mu_1, \mu_2) \in \mathbb{R}^2$. Here the matrix $A(\mu_1,\mu_2) \in \mathbb{R}^{n \times n}$ is nonsingular, large, and sparse and depends nonlinearly on the parameters $\mu_1$ and $\mu_2$. Specifically, the system arises from a discretization of a partial differential equation and $x(\mu_1,\mu_2) \in \mathbb{R}^n$, $b \in \mathbb{R}^n$. This work combines companion linearization with the Krylov subspace method preconditioned bi-conjugate gradient (BiCG) and a decomposition of a tensor matrix of precomputed solutions, called snapshots. As a result, a reduced order model of $x(\mu_1,\mu_2)$ is constructed, and this model can be evaluated in a cheap way for many values of the parameters. Tensor decompositions performed on a set of snapshots can fail to reach a certain level of accuracy, and it is not known a priori if a decomposition will be successful. Moreover, the selection of snapshots can affect both the quality of the produced model and the computation time required for its construction. This new method offers a way to generate a new set of solutions on the same parameter space at little additional cost. An interpolation of the model is used to produce approximations on the entire parameter space, and this method can be used to solve a parameter estimation problem. Numerical examples of a parameterized Helmholtz equation show the competitiveness of our approach. The simulations are reproducible, and the software is available online.

The multigrid V-cycle method is a popular method for solving systems of linear equations. It computes an approximate solution by using smoothing on fine levels and solving a system of linear equations on the coarsest level. Solving on the coarsest level depends on the size and difficulty of the problem. If the size permits, it is typical to use a direct method based on LU or Cholesky decomposition. In settings with large coarsest-level problems, approximate solvers such as iterative Krylov subspace methods, or direct methods based on low-rank approximation, are often used. The accuracy of the coarsest-level solver is typically determined based on the experience of the users with the concrete problems and methods. In this paper we present an approach to analyzing the effects of approximate coarsest-level solves on the convergence of the V-cycle method for symmetric positive definite problems. Using these results, we derive coarsest-level stopping criterion through which we may control the difference between the approximation computed by a V-cycle method with approximate coarsest-level solver and the approximation which would be computed if the coarsest-level problems were solved exactly. The coarsest-level stopping criterion may thus be set up such that the V-cycle method converges to a chosen finest-level accuracy in (nearly) the same number of V-cycle iterations as the V-cycle method with exact coarsest-level solver. We also utilize the theoretical results to discuss how the convergence of the V-cycle method may be affected by the choice of a tolerance in a coarsest-level stopping criterion based on the relative residual norm., Comment: 26 pages, 8 figures

Implementation of many statistical methods for large, multivariate data sets requires one to solve a linear system that, depending on the method, is of the dimension of the number of observations or each individual data vector. This is often the limiting factor in scaling the method with data size and complexity. In this paper we illustrate the use of Krylov subspace methods to address this issue in a statistical solution to a source separation problem in cosmology where the data size is prohibitively large for direct solution of the required system. Two distinct approaches are described: one that uses the method of conjugate gradients directly to the Kronecker-structured problem and another that reformulates the system as a Sylvester matrix equation. We show that both approaches produce an accurate solution within an acceptable computation time and with practical memory requirements for the data size that is currently available., Comment: submitted for publication/title changes from v1

AbstractGrowing research evidence indicates student learning gains from guided representation construction/invention in school science and mathematics. In this inquiry approach, students address challenges around what features of a phenomenon/problem to attend to, what data to collect, how and why, and make collective judgments about multimodal accounts of phenomena. However, researchers to date have tended to focus on student learning rather than on the teacher’s role in guiding various phases of inquiry. In this paper we report on (a) analysis of Grade 1 students’ engagement in interdisciplinary mathematics and science inquiry practices in a classroom sequence in ecology; (b) the teacher’s role in guiding such inquiry; and (c) interpretation of these practices in terms of support of student transduction (connecting and remaking meanings across representations in different modes). Data from our study included video capture of two case study teachers’ guidance of tasks and classroom discussion and student artefacts. We examine the classroom processes through which the teachers used students’ invention and revision of data displays to teach the concepts of living things, diversity, distribution and adaptive features related to habitat in science. Mathematical processes included constructing and interpreting mapping, measurement and data modelling, sampling and using a scale. The analysis offers fresh insights into how teachers support student learning in these two subjects, through discrete stages of orienting, representation challenge, building consensus and applying and extending representational systems.

Three main points: 1. Data Science (DS) will be increasingly important to heliophysics; 2. Methods of heliophysics science discovery will continually evolve, requiring the use of learning technologies [e.g., machine learning (ML)] that are applied rigorously and that are capable of supporting discovery; and 3. To grow with the pace of data, technology, and workforce changes, heliophysics requires a new approach to the representation of knowledge., Comment: 4 pages; Heliophysics 2050 White Paper

We derive an augmented Krylov subspace method with subspace recycling for computing a sequence of matrix function applications on a set of vectors. The matrix is either fixed or changes as the sequence progresses. We assume consecutive matrices are closely related, but make no assumptions on the relationship between the vectors. We present three versions of the method with different practical implementations. We demonstrate the effectiveness of the method using a range of numerical experiments with a selection of functions and matrices. We primarily focus our attention on the sign function arising in the overlap formalism of lattice QCD., Comment: 22 pages, 5 figures

Building on one decade of theory and methodology maturation, we investigate the coherent and incoherent components of the response of the Martian surface to nadir-looking orbital radar. We apply a reflectometry technique known as radar statistical reconnaissance to Mars Reconnaissance Orbiter Shallow Radar data over a test region with a large dynamic range in echo strength. This technique provides a set of statistical parameters describing the heterogeneity of the surface and near-surface structure, presumably at a scale of ∼15 m. We discuss the physical meanings of these parameters related to surface and near-surface properties. Most (but not all) investigated terrains have a dominantly coherent surface return, a characteristic that is not necessarily indicative of a smooth surface. The observed behavior of the coherent and incoherent power components of the echo matches signal growth with increasing surface roughness. This finding allows us to identify smooth and level terrains that we use as a reference to approximate the surface height and slope variations of other regions. Nearly systematic mismatches between the SHARAD and MOLA-pulse-width roughness illustrate the complementarity of these data sets from their respective sensitivity range, and advocate for the use of self-affine radar backscattering models to account for roughness variations at different scales. Our methodology provides a wealth of surface properties assessment based on radar scattering with quasi-global coverage, without a dependence on other data, and at a decametric horizontal scale relevant to subregional geology investigation and landing site reconnaissance.

Conventional airborne radar sounding techniques are well suited to the detection and characterization of flat-lying, specular subglacial water bodies. However, topographically positive, diffusively scattering Röthlisberger (R-) channels are more difficult to image, while also exerting substantial control on basal friction and ice dynamics. As subglacial R-channels share geometrical similarities with targets of interest in polarimetric ground-penetrating radar studies (i.e., cylindrical pipes), in this article, we investigate whether similar concepts can be adapted to detect and characterize R-channels. While closed-form analytical solutions exist for the scattering widths (SWs) of perfect electrically conducting and dielectric circular cylinders, the insight they provide for the polarimetric response of half-cylinder R-channels is limited. As such, a series of modeling experiments have been performed to characterize the SWs of half cylinders. Our results demonstrate that scattering from subglacial R-channels depends on numerous factors including the polarization and frequency of the incident radar wave, the size of the R-channel, and the relative orientation of the R-channel to a pair of orthogonally oriented, linearly polarized radar antennas. The results imply that patterns in the like-polarized echo powers across the signal bandwidth may be useful in inferring R-channel existence and possibly estimate R-channel size. However, as differences in SW are small and decrease with increasing misalignment between the acquisition system antennas and R-channel strike, achieving a high degree of radiometric resolution and stability should be a driving factor in polarimetric radar system design.

In this paper, we consider the problem of reconstructing a galaxy's stellar population-kinematic distribution function from optical integral field unit measurements. These quantities are connected via a high-dimensional integral equation. To solve this problem, we propose a projected Nesterov-Kaczmarz reconstruction (PNKR) method, which efficiently leverages the problem structure and incorporates physical prior information such as smoothness and non-negativity constraints. To test the performance of our reconstruction approach, we apply it to a dataset simulated from a known ground truth density, and validate it by comparing our recoveries to those obtained by the widely used pPXF software., Comment: 34 pages, 8 figures

Augmented Krylov subspace methods aid in accelerating the convergence of a standard Krylov subspace method by including additional vectors in the search space. A residual projection framework based on residual (Petrov-) Galerkin constraints was presented in [Gaul et al. SIAM J. Matrix Anal. Appl 2013], and later generalised in a recent survey on subspace recycling iterative methods [Soodhalter et al. GAMM-Mitt. 2020]. The framework describes augmented Krylov subspace methods in terms of applying a standard Krylov subspace method to an appropriately projected problem. In this work we show that the projected problem has an equivalent unprojected formulation, and that viewing the framework in this way provides a similar description for the class of unprojected augmented Krylov subspace methods. We derive the first unprojected augmented Full Orthogonalization Method (FOM), and demonstrate its effectiveness as a recycling method. We then show how the R$^{3}$GMRES algorithm fits within the framework. We show that unprojected augmented short recurrence methods fit within the framework, but can only be implemented in practice under certain conditions on the augmentation subspace. We demonstrate this using the Augmented Conjugate Gradient (AugCG) algorithm as an example., Comment: 13 pages, 1 figure

We are interested in obtaining approximate solutions to parameterized linear systems of the form $A(\mu) x(\mu) = b$ for many values of the parameter $\mu$. Here $A(\mu)$ is large, sparse, and nonsingular, with a nonlinear analytic dependence on $\mu$. Our approach is based on a companion linearization for parameterized linear systems. The companion matrix is similar to the operator in the infinite Arnoldi method, and we use this to adapt the flexible GMRES setting. In this way, our method returns a function $\tilde{x}(\mu)$ which is cheap to evaluate for different $\mu$, and the preconditioner is applied only approximately. This novel approach leads to increased freedom to carry out the action of the operation inexactly, which provides performance improvement over the method infinite GMRES, without a loss of accuracy in general. We show that the error of our method is estimated based on the magnitude of the parameter $\mu$, the inexactness of the preconditioning, and the spectrum of the linear companion matrix. Numerical examples from a finite element discretization of a Helmholtz equation with a parameterized material coefficient illustrate the competitiveness of our approach. The simulations are reproducible and publicly available online.

Two new classes of near-infrared molecular probes were prepared and shown to exhibit “turn on” fluorescence when cleaved by the nitroreductase enzyme, a well-known biomarker of cell hypoxia. The fluorescent probes are heptamethine cyanine dyes with a central 4‘-carboxylic ester group on the heptamethine chain that is converted by a self-immolative fragmentation mechanism to a 4‘-caboxylate group that greatly enhances the fluorescence brightness. Each compound was prepared by ring opening of a Zincke salt. The chemical structures have either terminal benzoindolinenes or propargy-loxy auxochromes, which provide favorable red-shifted absorp-tion/emission wavelengths and a hyperchromic effect that enhances the photon output when excited by 808 nm light. A fluorescent probe with terminal propargyloxy-indolenines ex-hibited less self-aggregation and was rapidly activated by nitroreductase with large “turn on“ fluorescence; thus, it is the preferred choice for translation towards in vivo applications.

OBJECTIVES: The COVID-19 pandemic has changed the way people are accessing healthcare. The aim of this study was to examine the impact of COVID-19 on emergency department (ED) attendance for frequent attenders and to explore potential reasons for changes in attendance. DESIGN: This convergent parallel mixed methods study comprised two parts. SETTING: An interrupted time-series analysis evaluated changes in ED presentation rates; interviews investigated reasons for changes for frequent ED users in a culturally and linguistically diverse setting. PARTICIPANTS: A total of 4868 patients were included in the time series. A subgroup of 200 patients were interviewed, mean age 66 years (range 23-99). RESULTS: Interrupted time-series analysis from 4868 eligible participants showed an instantaneous decrease in weekly ED presentations by 36% (p<0.001), with reduction between 45% and 67% across emergency triage categories. 32% did not know they could leave home to seek care with differences seen in English versus non-English speakers (p<0.001). 35% reported postponing medical care. There was a high fear about the health system becoming overloaded (mean 4.2 (±2) on 6-point scale). Four key themes emerged influencing health-seeking behaviour: fear and/or avoidance of hospital care; use of telehealth for remote assessment; no fear or avoidance of hospital care; not leaving the house for any reason. CONCLUSIONS: This study demonstrated reduced ED use by a vulnerable population of previously frequent attenders. COVID-19 has resulted in some fear and avoidance of hospitals, but has also offered new opportunity for alternative care through telehealth.

Coronal holes are the observational manifestation of the solar magnetic field open to the heliosphere and are of pivotal importance for our understanding of the origin and acceleration of the solar wind. Observations from space missions such as the Solar Dynamics Observatory now allow us to study coronal holes in unprecedented detail. Instrumental effects and other factors, however, pose a challenge to automatically detect coronal holes in solar imagery. The science community addresses these challenges with different detection schemes. Until now, little attention has been paid to assessing the disagreement between these schemes. In this COSPAR ISWAT initiative, we present a comparison of nine automated detection schemes widely applied in solar and space science. We study, specifically, a prevailing coronal hole observed by the Atmospheric Imaging Assembly instrument on 2018 May 30. Our results indicate that the choice of detection scheme has a significant effect on the location of the coronal hole boundary. Physical properties in coronal holes such as the area, mean intensity, and mean magnetic field strength vary by a factor of up to 4.5 between the maximum and minimum values. We conclude that our findings are relevant for coronal hole research from the past decade, and are therefore of interest to the solar and space research community.

Discovered almost simultaneously with insulin, glucagon is a pleiotropic hormone with metabolic action that goes far beyond its classical role to increase blood glucose. Albeit best known for its ability to directly act on the liver to increase de novo glucose production and to inhibit glycogen breakdown, glucagon lowers body weight by decreasing food intake and by increasing metabolic rate. Glucagon further promotes lipolysis and lipid oxidation and has positive chronotropic and inotropic effects in the heart. Interestingly, recent decades have witnessed a remarkable renaissance of glucagon's biology with the acknowledgment that glucagon has pharmacological value beyond its classical use as rescue medication to treat severe hypoglycemia. In this article, we summarize the multifaceted nature of glucagon with a special focus on its hepatic action and discuss the pharmacological potential of either agonizing or antagonizing the glucagon receptor for health and disease.

Subspace recycling iterative methods and other subspace augmentation schemes are a successful extension to Krylov subspace methods in which a Krylov subspace is augmented with a fixed subspace spanned by vectors deemed to be helpful in accelerating convergence or conveying knowledge of the solution. Recently, a survey was published, in which a framework describing the vast majority of such methods was proposed [Soodhalter et al, GAMM-Mitt. 2020]. In many of these methods, the Krylov subspace is one generated by the system matrix composed with a projector that depends on the augmentation space. However, it is not a requirement that a projected Krylov subspace be used. There are augmentation methods built on using Krylov subspaces generated by the original system matrix, and these methods also fit into the general framework. In this note, we observe that one gains implementation benefits by considering such augmentation methods with unprojected Krylov subspaces in the general framework. We demonstrate this by applying the idea to the R$^3$GMRES method proposed in [Dong et al. ETNA 2014] to obtain a simplified implementation and to connect that algorithm to early augmentation schemes based on flexible preconditioning [Saad. SIMAX 1997]., Comment: 14 pages, 4 figures

AIMS: COVID-19 is now a global pandemic. At the time of survey, fewer than 150 children in Australia and New Zealand had documented infection. The aim of this study was to assess attitudes, readiness and confidence in the early stages of the COVID-19 pandemic through an online survey of paediatric physicians and sub-specialists across Australia and New Zealand. METHODS: Multiple email list groups were used to contact paediatric physicians to undertake an online Likert scale survey between 17 and 24 March. Respondents' specialty, experience and work setting were recorded. Ordinal logistic regression was used to determine respondent factors. RESULTS: There were 542 respondents from across Australia and New Zealand: an estimated 11% of the paediatric physician workforce. A minority (36.6%) agreed that their national response had been well coordinated; the majority (92.7%) agreed that senior-level hospital administrators were taking the situation seriously. Most reported a good understanding of the natural history of COVID-19 in children, and knowledge of where to find local information. A large proportion of physicians (86.1%) were worried about becoming infected through their work; few (5.8%) reported that they would not come to work to avoid infection. Closure of school and childcares would reduce the ability to continue work at current capacity for 23.6% of respondents. CONCLUSION: Despite limited experience in pandemics, most paediatric physicians felt informed. Concern about exposure at work is common; most were willing to work regardless. The closure of schools and daycares may have an impact on staffing. Coordination and leadership will be critical.

INTRODUCTION: A new healthcare standard (Standard 5: Comprehensive Care) has been introduced by the Australian Commission on Safety and Quality in Healthcare. Standard 5 advocates for organisational leadership to develop and maintain systems and processes to deliver patient-centred comprehensive care plans that include appropriate screening to identify and mitigate risks associated with hospitalisation. The aim of this study is to evaluate the effectiveness and cost effectiveness of a comprehensive care and risk evaluation (Comprehensive Assessment and Risk Evaluation (CARE)) plan to reduce hospital acquired complications (HACs) in an Australian hospital network. METHODS AND ANALYSIS: This study will comprise a mixed-method pre and post implementation concurrent triangulation evaluation design. The primary clinical outcome will assess the reduction of routinely reported HACs (pressure care and falls), selected based on the likely reliability of routinely collected data prior to implementation. Secondary clinical outcomes will include length of stay and activity-based costing data for each episode, in-hospital mortality, expected and unplanned readmissions within 28 days, compliance with CARE plan completion and referrals for at risk patients, staff satisfaction, patient satisfaction and barriers and enablers to implementation. We expect that the incidence of other HACs (malnutrition, delirium, violence and aggression, and suicide and self-harm) may increase as routine methods for assessing risk were not in place prior to implementation of the CARE plan. We will therefore collect data on incidence of these HACs as tertiary outcomes. Our primary cost-effectiveness outcome will be calculation of an incremental cost-effectiveness ratio. ETHICS AND DISSEMINATION: Ethics approval has been received from Northern Health Low Risk Ethics Committee. The results of this study will be published in peer-reviewed journals and presented at conferences.

Objective. This study determined the economic impact of 16 ‘high-priority’ hospital-acquired complications (HACs), as defined by the Australian Commission on Safety and Quality in Health Care, from the perspective of an individual Australian health service. Methods. A retrospective cohort study was performed using a deidentified patient dataset containing 93 056 inpatient separations in Northern Health (Victoria, Australia) from 1 July 2016 to 30 June 2017. Two log-linked generalised linear regression models were used to obtain additional costs and additional length of stay (LOS) for 16 different HACs, with the main outcome measures being the additional cost and LOS for all 16 HACs. Results. In all, 1700 separations involving HACs (1.83%) were identified. The most common HAC was health careassociated infections. Most HACs were associated with a statistically significant risk of increased cost (15/16 HACs) and LOS (11/16 HACs). HACs involving falls resulting in fracture or other intracranial injury were associated with the highest additional cost (A$17 173). The biggest increase in additional LOS was unplanned admissions to the intensive care unit (5.42 days). Conclusions. This study shows the economic impact of HACs from the perspective of an individual health service. The methodology used demonstrates how other health services could determine safety priorities corresponding to their own casemix.

This video recording is from the DroneTech Educator Workshop: Drones and Geospatial Applications series provided by the National Center for Autonomous Technologies. In this presentation, Kirk M. Stueve presents on the practical applications of remote sensing for use in agriculture, specifically for fungicide application. He provides an overview of variable rate application (VRA) fungicide, and discusses the challenges that farmers face, including variable weather and climatic conditions conducive to fungi, and expensive fungicide that yield inconsistent results. Stueve explains the opportunity for utilizing remote imagery, which enables farmers to collect and track ecological data like temperatures and rainfall, and inform fungicide application decisions. This presentation also includes a discussion about workflow considerations, including equipment and tools, as well as a tour of the software ArcMap. This video recording runs for 31:57 minutes in length. Additional videos in the series are available to view separately.

This survey concerns subspace recycling methods, a popular class of iterative methods that enable effective reuse of subspace information in order to speed up convergence and find good initial guesses over a sequence of linear systems with slowly changing coefficient matrices, multiple right-hand sides, or both. The subspace information that is recycled is usually generated during the run of an iterative method (usually a Krylov subspace method) on one or more of the systems. Following introduction of definitions and notation, we examine the history of early augmentation schemes along with deflation preconditioning schemes and their influence on the development of recycling methods. We then discuss a general residual constraint framework through which many augmented Krylov and recycling methods can both be viewed. We review several augmented and recycling methods within this framework. We then discuss some known effective strategies for choosing subspaces to recycle before taking the reader through more recent developments that have generalized recycling for (sequences of) shifted linear systems, some of them with multiple right-hand sides in mind. We round out our survey with a brief review of application areas that have seen benefit from subspace recycling methods., Comment: 21 pages of text plus pages for references (27 total)

Subspace recycling techniques have been used quite successfully for the acceleration of iterative methods for solving large-scale linear systems. These methods often work by augmenting a solution subspace generated iteratively by a known algorithm with a fixed subspace of vectors which are ``useful'' for solving the problem. Often, this has the effect of inducing a projected version of the original linear system to which the known iterative method is then applied, and this projection can act as a deflation preconditioner, accelerating convergence. Most often, these methods have been applied for the solution of well-posed problems. However, they have also begun to be considered for the solution of ill-posed problems. In this paper, we consider subspace augmentation-type iterative schemes applied to linear ill-posed problems in a continuous Hilbert space setting, based on a recently developed framework describing these methods. We show that under suitable assumptions, a recycling method satisfies the formal definition of a regularization, as long as the underlying scheme is itself a regularization. We then develop an augmented subspace version of the gradient descent method and demonstrate its effectiveness, both on an academic Gaussian blur model and on problems arising from the adaptive optics community for the resolution of large sky images by ground-based extremely large telescopes., Comment: 27 pages, 10 figures, in revision with journal

We present spectral energy distributions (SEDs) of 41 active galactic nuclei, derived from multiwavelength photometry and archival spectroscopy. All of the SEDs span at least 0.09 to 30 micron, but in some instances wavelength coverage extends into the X-ray, far-infrared and radio. For some AGNs we have fitted the measured far-infrared photometry with greybody models, while radio flux density measurements have been approximated by power-laws or polynomials. We have been able to fill some of the gaps in the spectral coverage using interpolation or extrapolation of simple models. In addition to the 41 individual AGN SEDs, we have produced 72 Seyfert SEDs by mixing SEDs of the central regions of Seyferts with galaxy SEDs. Relative to the literature, our templates have broader wavelength coverage and/or higher spectral resolution. We have tested the utility of our SEDs by using them to generate photometric redshifts for 0 < z < 6.12 AGNs in the Bootes field (selected with X-ray, IR and optical criteria) and, relative to SEDs from the literature, they produce comparable or better photometric redshifts with reduced flux density residuals., Comment: Accepted for publication in MNRAS. 19 pages, 14 figures, 4 tables. The AGN spectral energy distributions, photometry and images are available via https://archive.stsci.edu/hlsp/agnsedatlas

We give a comprehensive account of the flavour physics of Beyond-Standard-Model (BSM) effects in $b \to c \bar{c} s$ transitions, considering the full set of 20 four-quark operators. We discuss the leading-order structure of their RG mixing with each other as well as the QCD-penguin, dipole, and FCNC semileptonic operators they necessarily mix with, providing compact expressions. We also provide the first complete results for BSM effects in the lifetime observables $\Delta \Gamma_s$ and $\tau(B_s)/\tau(B_d)$, as well as for the semileptonic CP-asymmetry $a_{sl}^s$. From a global analysis, we obtain stringent constraints on 16 of the 20 BSM operators, including the 10 operators $Q^{c\prime }_{1 \dots 10}$ involving a right-handed strange quark. Focussing on CP-conserving new physics, the constraints correspond to NP scales of order 10 TeV in most cases, always dominated by exclusive and/or radiative $B$-decays via RGE mixing. For the remaining four operators, including the two Standard-Model (SM) ones, larger effects are experimentally allowed, as previously noted in arXiv:1701.09183. We extend that paper's scope to the CP-violating case, paying attention to the impact on the decay rate and time-dependent CP-violation in $B_d \to J/\psi K_S$. We show that quantifiable constraints arise for new physics in either of the two SM operators, with the uncertain non-perturbative matrix element of the colour-suppressed operator determined from the data. For new physics in the SM suppressed coefficient $C^c_1$ we find two perfectly viable, narrow bands of complex Wilson coefficients. Somewhat curiously, one of them contains a region where the fitted matrix element for the colour-suppressed operator is in agreement with naive factorization, contrarily to a widely held belief that large non-factorizable contributions to $B_d \to J/\psi K_S$ are implied by experimental data., Comment: 39 pages, 5 pdf figures, uses jheppub.sty. v2 adds ancillary Mathematica files. v3 matches journal version. v4 Add missing contributions to Gamma12, conclusions unchanged (see JHEP erratum), ancillary file updated

It is well-established that any non-increasing convergence curve is possible for GMRES and a family of pairs $(A,b)$ can be constructed for which GMRES exhibits a given convergence curve with $A$ having arbitrary spectrum. No analog of this result has been established for block GMRES, wherein multiple right-hand sides are considered. By reframing the problem as a single linear system over a ring of square matrices, we develop convergence results for block Arnoldi and block GMRES. In particular, we show what convergence behavior is admissible for block GMRES and how the matrices and right-hand sides producing any admissible behavior can be constructed. Moreover, we show that the convergence of the block Arnoldi method for eigenvalue approximation can be almost fully independent of the convergence of block GMRES for the same coefficient matrix and the same starting vectors., Comment: 23 pages

Glucagon’s ability to increase energy expenditure has been known for more than 60 years, yet the mechanisms underlining glucagon’s thermogenic effect still remain largely elusive. Over the last years, significant efforts were directed to unravel the physiological and cellular underpinnings of how glucagon regulates energy expenditure. In this review, we summarize the current knowledge on how glucagon regulates systems metabolism with a special emphasis on its acute and chronic thermogenic effects.

INTRODUCTION: The CampySource project aims to identify risk factors for human Campylobacter infection in Australia. We will investigate locally relevant risk factors and those significant in international studies in a case-control study. Case isolates and contemporaneous isolates from food and animal sources will be sequenced to conduct source attribution modelling, and findings will be combined with the case-control study in a source-assigned analysis. METHODS AND ANALYSIS: The case-control study will include 1200 participants (600 cases and 600 controls) across three regions in Australia. Cases will be recruited from campylobacteriosis notifications to health departments. Only those with a pure and viable Campylobacter isolate will be eligible for selection to allow for whole genome sequencing of isolates. Controls will be recruited from notified cases of influenza, frequency matched by sex, age group and geographical area of residence. All participants will be interviewed by trained telephone interviewers using a piloted questionnaire.We will collect Campylobacter isolates from retail meats and companion animals (specifically dogs), and all food, animal and human isolates will undergo whole genome sequencing. We will use sequence data to estimate the proportion of human infections that can be attributed to animal and food reservoirs (source attribution modelling), and to identify spatial clusters and temporal trends. Source-assigned analysis of the case-control study data will also be conducted where cases are grouped according to attributed sources. ETHICS AND DISSEMINATION: Human and animal ethics have been approved. Genomic data will be published in online archives accompanied by basic metadata. We anticipate several publications to come from this study.

BACKGROUND: Acute gastroenteritis illness is a common illness that causes considerable morbidity, but current estimates of the cost to the Australian healthcare system are unknown. OBJECTIVE: To estimate the current healthcare utilisation and direct public healthcare system costs attributable to acute gastroenteritis illness in Australia. METHODS: This is an incidence-based cost-of-illness study focused on quantifying direct health care costs using a bottom-up approach. Data on general practitioner consultations, prescribed medications, diagnostic tests, specialist consultations, emergency department visits and hospital admissions were collected from national reports. RESULTS: Using 2016 prices, the estimated annual direct per capita cost of acute gastroenteritis illness was AUD$14.87 (USD$10.71), equating to AUD$20.27 (USD$14.59) per case. The estimated overall economic burden in Australia was AUD$359 million (USD$258 million; AUD$1.5 million per 100,000 people). The major contributors to this cost were hospital admissions (57.1%), emergency department visits (17.7%), and general practitioner consultations (14.0%). Children under five years of age have the highest per capita rates of acute gastroenteritis illness; however, service utilisation rates vary by age group and both young children and older adults accounted for a substantial proportion of the overall economic burden attributable to acute gastroenteritis illness. CONCLUSIONS: Although chronic diseases comprise a large cost burden on the healthcare system, acute illnesses, including acute gastroenteritis illness, also impose substantial direct healthcare system costs. Providing data on current cost estimates is useful for prioritizing public health interventions, with our findings suggesting that it would be ideal if targeted interventions to reduce hospitalisation rates among young children and older adults were available.

OBJECTIVES: We aimed to describe mortality in a cohort of remote-living Aboriginal Australians using electronic record linkage. METHODS: Between 2004 and 2006, 363 Aboriginal people living in remote Western Australia (WA) completed a questionnaire assessing medical history and behavioural risk factors. We obtained mortality records for the cohort from the WA Data Linkage System and compared them to data for the general population. We used Cox proportional hazards regression to identify predictors of mortality over a 9-year follow-up period. RESULTS: The leading causes of mortality were diabetes, renal failure, and ischaemic heart disease. Diabetes and renal failure accounted for 28% of all deaths. This differed from both the Australian population as a whole, and the general Indigenous Australian population. The presence of chronic disease did not predict mortality, nor did behaviours such as smoking. Only age, male sex, poor mobility, and cognitive impairment were risk factors. CONCLUSIONS: To reduce premature mortality, public health practitioners should prioritise the prevention and treatment of diabetes and renal disease in Aboriginal people in remote WA. This will require a sustained and holistic approach.

Background: Workforce distribution has an important influence on the quality of healthcare delivered in a region, primarily because it impacts access to health services in the community and overall health equity in the population. Distribution of osteopaths in Australia does not appear to follow the Australian population with the majority of osteopaths located in Victoria. The implications of this imbalance on the osteopathic workforce have not yet been explored. Methods: A secondary analysis of data from a survey of 1531 members of Osteopathy Australia in 2013. The analysis focused on the practice and occupational characteristics associated with practice locality. Results: The survey was completed by a representative sample of 432 osteopaths. Respondents practicing outside Victoria were more likely to report higher income across all income brackets, and were less likely to report a preference for more patients. Conclusions: The Australian osteopathic profession should examine the issue of imbalanced workforce distribution as a priority. The results of this study are worth considering for all stakeholders as part of a coordinated approach to ensure the ongoing health of the Australian osteopathic workforce.

Popular deep neural networks (DNNs) spend the majority of their execution time computing convolutions. The Winograd family of algorithms can greatly reduce the number of arithmetic operations required and is present in many DNN software frameworks. However, the performance gain is at the expense of a reduction in floating point (FP) numerical accuracy. In this paper, we analyse the worst case FP error and prove the estimation of norm and conditioning of the algorithm. We show that the bound grows exponentially with the size of the convolution, but the error bound of the \textit{modified} algorithm is smaller than the original one. We propose several methods for reducing FP error. We propose a canonical evaluation ordering based on Huffman coding that reduces summation error. We study the selection of sampling "points" experimentally and find empirically good points for the most important sizes. We identify the main factors associated with good points. In addition, we explore other methods to reduce FP error, including mixed-precision convolution, and pairwise summation across DNN channels. Using our methods we can significantly reduce FP error for a given block size, which allows larger block sizes and reduced computation.

Introduction The CampySource project aims to identify risk factors for human Campylobacter infection in Australia. We will investigate locally relevant risk factors and those significant in international studies in a case-control study. Case isolates and contemporaneous isolates from food and animal sources will be sequenced to conduct source attribution modelling, and findings will be combined with the case-control study in a source-assigned analysis. Methods and analysis The case-control study will include 1200 participants (600 cases and 600 controls) across three regions in Australia. Cases will be recruited from campylobacteriosis notifications to health departments. Only those with a pure and viable Campylobacter isolate will be eligible for selection to allow for whole genome sequencing of isolates. Controls will be recruited from notified cases of influenza, frequency matched by sex, age group and geographical area of residence. All participants will be interviewed by trained telephone interviewers using a piloted questionnaire. We will collect Campylobacter isolates from retail meats and companion animals (specifically dogs), and all food, animal and human isolates will undergo whole genome sequencing. We will use sequence data to estimate the proportion of human infections that can be attributed to animal and food reservoirs (source attribution modelling), and to identify spatial clusters and temporal trends. Source-assigned analysis of the case-control study data will also be conducted where cases are grouped according to attributed sources. Ethics and dissemination Human and animal ethics have been approved. Genomic data will be published in online archives accompanied by basic metadata. We anticipate several publications to come from this study.

Background and objectives: Deep brain stimulation (DBS) of the thalamus is a promising therapeutic alternative for treating medically refractory Tourette syndrome (TS). However, few human studies have examined its mechanism of action. Therefore, the networks that mediate the therapeutic effects of thalamic DBS remain poorly understood., Methods: Five participants diagnosed with severe medically refractory TS underwent bilateral thalamic DBS stereotactic surgery. Intraoperative fMRI characterized the blood oxygen level-dependent (BOLD) response evoked by thalamic DBS and determined whether the therapeutic effectiveness of thalamic DBS, as assessed using the Modified Rush Video Rating Scale test, would correlate with evoked BOLD responses in motor and limbic cortical and subcortical regions., Results: Our results reveal that thalamic stimulation in TS participants has wide-ranging effects that impact the frontostriatal, limbic, and motor networks. Thalamic stimulation induced suppression of motor and insula networks correlated with motor tic reduction, while suppression of frontal and parietal networks correlated with vocal tic reduction. These regions mapped closely to major regions of interest (ROI) identified in a nonhuman primate model of TS., Conclusions: Overall, these findings suggest that a critical factor in TS treatment should involve modulation of both frontostriatal and motor networks, rather than be treated as a focal disorder of the brain. Using the novel combination of DBS-evoked tic reduction and fMRI in human subjects, we provide new insights into the basal ganglia-cerebellar-thalamo-cortical network-level mechanisms that influence the effects of thalamic DBS. Future translational research should identify whether these network changes are cause or effect of TS symptoms.

The hadronic matrix elements of dimension-six $\Delta F=0,2$ operators are crucial inputs for the theory predictions of mixing observables and lifetime ratios in the $B$ and $D$ system. We determine them using HQET sum rules for three-point correlators. The results of the required three-loop computation of the correlators and the one-loop computation of the QCD-HQET matching are given in analytic form. For mixing matrix elements we find very good agreement with recent lattice results and comparable theoretical uncertainties. For lifetime matrix elements we present the first ever determination in the $D$ meson sector and the first determination of $\Delta B=0$ matrix elements with uncertainties under control - superseeding preliminary lattice studies stemming from 2001 and earlier. With our state-of-the-art determination of the bag parameters we predict: $\tau(B^+)/\tau(B_d^0) = 1.082_{-0.026}^{+0.022}$, $\tau(B_s^0)/\tau(B_d^0) = 1.0007\pm0.0025$, $\tau(D^+)/\tau(D^0) = 2.7_{-0.8}^{+0.7}$ and the mixing-observables in the $B_s$ and $B_d$ system, in good agreement with the most recent experimental averages., Comment: 46 pages, 9 figures, Journal version. Minor changes to numerics, matrix elements and conclusions unchanged

Current proton techniques for left-sided breast cancer use an anterior or lateral anterior oblique (LAO) proton beam which places the distal edge of the beam immediately against the ipsilateral lung and the cardiac structures. Tangential proton modulated arc therapy (tPMAT) would place the distal edge within the target, reducing the dose and linear energy transfer (LET) to the lung, the heart or the left anterior descending (LAD) artery. Six patients treated with a single LAO proton beam (sLAO), were re-planned using a tPMAT beam extending from the left lateral to the mediastinal side of the patient. The plans consisted of fifty mono-energetic beams, separated by 2o each. A custom wedge was devised for each patient to enable full target coverage. Dose and volume constraints for PTV, heart, lung, LAD in both treatment modalities were reported, and the statistical significance of their difference was determined using the t-test. LET distributions were calculated and reported for all patients. The robustness of both plan modalities were tested by calculating perturbed doses with isocenter shiftsof 3mm in all 6 principal directions and considering ±3.5% range uncertainty. tPMAT showed equal or better capacity to cover the target with 95% of the dose while maintaining the dose below prescription for the organs at risk (OARs). The use of tPMAT reduces the LET in the OARs compared to the sLAO. tPMAT is also more robust to isocenter shifts and range uncertainties. A universal wedge can be used in tPMAT without changing the dosimetric or biophysical properties of the plan. tPMAT provides robust dosimetric and biophysical benefits over the current sLAO technique. The possibility of using universal wedges indicates the possibility of doing tPMAT without altering the current fast turnaround of PBS planning and delivery.

Purpose: Presentation of an enhanced robustness analysis and its application on single-field (SFO) and robust multi-field optimized (rMFO) plans for intensity modulated proton therapy (IMPT). Material/Methods: rMFO IMPT plans were optimized (Eclipse v13.7, Varian, Palo Alto, CA) for 11 oropharynx carcinoma patients, which had been treated post-surgery with SFO IMPT with simultaneous integrated boost prescription. Expected mean dose per voxel is calculated for minimal, 0% and maximal range uncertainty (RU), considering 19 setup error (SE) scenarios and their likelihood of occurrence. Voxel-wise boundary dose distributions are created from all 57 scenarios including systematic RU and random SE while also taking into account the averaging effect of fractionation to approximate realistic worst cases for the total treatment course. Dose error distributions for under- and overdosage with according ROI-specific metrics are derived from these boundary doses. Results: Nominal rMFO plans show improved CTV coverage and homogeneity while simultaneously reducing the average mean dose to the constrictor muscles, larynx and ipsilateral middle ear by 5.6Gy(RBE), 2.0Gy(RBE) and 3.9Gy(RBE), respectively. The comparison of SFO and rMFO boundary doses reveals slightly larger differences for these organs, and significantly lower brainstem maximum and ipsilateral parotid mean dose in rMFO plans. Many dose error metrics are significantly superior for rMFO plans. Conclusions: The nominal benefit of better CTV coverage and OAR dose sparing by rMFO compared to SFO plans is preserved under considerations of SE and RU. DVH bands and dose metrics from the boundary dose distributions will help to judge plan robustness in clinical routine.

Purpose: To compare the difference in robustness of single-field (SFO) and robust multi-field optimized (rMFO) proton plans for oropharynx carcinoma patients by improved robustness analysis. Methods: rMFO proton plans were generated for 11 oropharynx patients treated with SFO intensity modulated proton therapy (IMPT) with simultaneous integrated boost prescription. Doses from both planning approaches are compared for the initial plans and the worst cases from 20 optimization scenarios of setup errors (SE) and range uncertainties (RU). Expected average dose distributions per RU are obtained by adding the contributions from the respective scenarios with a weight according to their expected SE probability, and thus allowing quantification of the RU-related spread of dose parameters. Boundary dose distributions created from 56 combined SE and RU scenarios and considering the vanishing influence of SE after 30 fractions are used to approximate realistic worst case values for the total treatment course. Error bar distributions are derived from these boundary doses and error bar metrics are reported for the clinical target volumes (CTV) and organs at risk (OAR). Results: rMFO-plans show improved CTV coverage and homogeneity while simultaneously reducing the average mean dose to the constrictor muscles, larynx and ipsilateral middle ear by 5.6Gy(RBE), 2.0Gy(RBE) and 3.9Gy(RBE), respectively. This is also observed by the different robustness evaluation methods, where additionally the average maximum brainstem and mean ipsilateral parotid dose significantly lower. For rMFO-plans, the RU-related spread in OAR dose parameters is smaller and many error bar metrics are found to be superior. SFO-plans show lower global maximum dose for single-scenario worst cases and slightly lower mean oral cavity dose throughout. Conclusion: The benefit of better CTV coverage and OAR dose sparing by rMFO compared to SFO proton plans is preserved under considerations of SE and RU.

Contains fulltext : 165920.pdf (Publisher’s version ) (Open Access), BACKGROUND AND PURPOSE: In this multicentric in silico trial we compared photon, proton, and carbon-ion radiotherapy plans for re-irradiation of patients with squamous cell carcinoma of the head and neck (HNSCC) regarding dose to tumour and doses to surrounding organs at risk (OARs). MATERIAL AND METHODS: Twenty-five HNSCC patients with a second new or recurrent cancer after previous irradiation (70Gy) were included. Intensity-modulated proton therapy (IMPT) and ion therapy (IMIT) re-irradiation plans to a second subsequent dose of 70Gy were compared to photon therapy delivered with volumetric modulated arc therapy (VMAT). RESULTS: When comparing IMIT and IMPT to VMAT, the mean dose to all investigated 22 OARs was significantly reduced for IMIT and to 15 out of 22 OARs (68%) using IMPT. The maximum dose to 2% volume (D2) of the brainstem and spinal cord were significantly reduced using IMPT and IMIT compared to VMAT. The data are available on www.cancerdata.org. CONCLUSIONS: In this ROCOCO in silico trial, a reduction in mean dose to OARs was achieved using particle therapy compared to photons in the re-irradiation of HNSCC. There was a dosimetric benefit favouring carbon-ions above proton therapy. These dose reductions may potentially translate into lower severe complication rates related to the re-irradiation.

The urgent nature of epidemic infectious diseasesbring specific challenges in disease control. Epidemicscan cause immediate health, social and economicimpacts, and require complex cross-sectoral andglobal response as illustrated by the 2014 Ebolaepidemic. Travel and globalisation mean thatinfections spread rapidly around the world, so thatglobal solutions are required for epidemic control.Recent developments in artificially engineeredpathogens (dual-use research of concern) posean added complexity to global biosecurity. Globalsystems, thinking and capability in biosecurity haslagged behind quantum changes in science, leavingus more vulnerable than ever to infectious diseasesepidemics. This Centre addresses critical systems gaps in epidemic control.The NHMRC Centre for Research Excellence,Integrated Systems for Epidemic Response (ISER)conduct applied systems research, enhancecollaboration and build capacity in health systemsresearch for epidemic control. We bring togetherexperts in field epidemiology and epidemic response,military experts, international law and risk scienceexperts, and government and non-governmentagencies involved in epidemic response. The ARMNetwork for epidemic response is central to theCRE, with the co-founders all being part of theCRE. This Centre is international, with partnersin Australia, New Zealand, USA, China, Malaysiaand Indonesia who work together to solve globalproblems in epidemic response. A pillar of theCRE is ISER Academy, which is a think-tank andconvenor of important dialogue, capacity buildingand generation of ideas, between all stakeholdersand sectors involved in epidemic response.ISER is conducting research in three main areas:1) Epidemic response, control and prevention, 2)Epidemic intelligence and risk analysis and 3) theestablishment of the ISER academy, a think tank ofepidemic experts and stakeholders for the purposeof sharing information, collaboration and developingsolutions. This presentation will outline the workof ISER

© 2016 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Introduction To quantify the association between PPI use, type and dose and infectious gastroenteritis hospitalization in a population-based cohort of middle-aged and older adults. Methods Prospective study of 38,019 concession card holders followed up over 6 years in the Sax Institute's 45 and Up Study. Data from the baseline questionnaire were linked to prescription medication, hospitalization, notifiable disease, cancer registry and death datasets from 2006-2012. Associations between PPI use and gastroenteritis hospitalization were examined using Cox regressions with age as the underlying time variable. Results Among 38,019 participants, the median age was 69.7 years, and 57.3% were women. Compared to non-users, current PPI users were more likely to be older, and have a higher BMI. During follow-up there were 1,982 incident gastroenteritis hospitalizations (crude rate: 12.9 per 1000 person-years, 95% CI: 12.3-13.5). PPI use was significantly associated with infectious gastroenteritis hospitalization (aHR 1.4, 95% CI: 1.2-1.5). Among current users, a dose-response relationship was observed between the average daily dose (DDD) dispensed per day and infectious gastroenteritis hospitalization (Ptrend<0.001). We also observed higher rates of infectious gastroenteritis hospitalization and greater PPI use among participants with a history of chronic bowel problems (aHR 2.2, 95% CI: 1.9-2.5). There was no difference in risk by type of PPI. Recent use of H2 receptors was not associated with gastroenteritis hospitalization. Conclusion PPI use is associated with an increased risk of infectious gastroenteritis hospitalization. Clinicians should be aware of this risk when considering PPI therapy.

In October 2013, public health authorities were notified of a suspected outbreak of gastroenteritis in students and guests following a catered function at a university residential college. A retrospective cohort study was undertaken to examine whether foods served at the function caused illness. A total of 56 cases of gastroenteritis, including seven laboratory-confirmed cases of Campylobacter jejuni infection, were identified in 235 eligible respondents. Univariate analysis showed a significant association with a chicken liver pâté entrée [relative risk (RR) 3·64, 95% confidence interval (CI) 2·03–6·52, P < 0·001], which retained significance after adjustment for confounding via multivariable analysis (adjusted RR 2·80, 95% CI 1·26–6·19, P = 0·01). C. jejuni and C. coli were also isolated in chicken liver pâté recovered from the college’s kitchen. Subsequent whole genome multilocus sequence typing (wgMLST) of clinical and food-derived C. jejuni isolates showed three genetically distinct sequence types (STs) comprising ST528, ST535(both clinically derived) and ST991 (food derived). The study demonstrates the value of utilizing complementary sources of evidence, including genomic data, to support public health investigations. The use of wgMLST highlights the potential for significant C. jejuni diversity in epidemiologically related human and food isolates recovered during outbreaks linked to poultry liver.