A dynamic physical energy model of the United Kingdom

This report describes the structure and simulation results of a dynamic physical model of the UK energy system. The model traces the hourly flows of energy from energy sources through various energy converters and stores to useful energy demands. Effects such as the temporal and climatic dependence of demands have been accounted for. Technical data has been collected so that it is possible to simulate the performance of the system as it was in 1976 or as it might be at some future date. The model has been validated against measured data and has been used to simulate the UK system with changed demands and new conservation and supply technologies

Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

Iterative image reconstruction algorithms for optoacoustic tomography (OAT), also known as photoacoustic tomography, have the ability to improve image quality over analytic algorithms due to their ability to incorporate accurate models of the imaging physics, instrument response, and measurement noise. However, to date, there have been few reported attempts to employ advanced iterative image reconstruction algorithms for improving image quality in three-dimensional (3D) OAT. In this work, we implement and investigate two iterative image reconstruction methods for use with a 3D OAT small animal imager: namely, a penalized least-squares (PLS) method employing a quadratic smoothness penalty and a PLS method employing a total variation norm penalty. The reconstruction algorithms employ accurate models of the ultrasonic transducer impulse responses. Experimental data sets are employed to compare the performances of the iterative reconstruction algorithms to that of a 3D filtered backprojection (FBP) algorithm. By use of quantitative measures of image quality, we demonstrate that the iterative reconstruction algorithms can mitigate image artifacts and preserve spatial resolution more effectively than FBP algorithms. These features suggest that the use of advanced image reconstruction algorithms can improve the effectiveness of 3D OAT while reducing the amount of data required for biomedical applications

NOAH-H, a deep-learning, terrain classification system for Mars: Results for the ExoMars Rover candidate landing sites

In this investigation a deep learning terrain classification system, the “Novelty or Anomaly Hunter – HiRISE” (NOAH-H), was used to classify High Resolution Imaging Science Experiment (HiRISE) images of Oxia Planum and Mawrth Vallis. A set of ontological classes was developed that covered the variety of surface textures and aeolian bedforms present at both sites. Labelled type-examples of these classes were used to train a Deep Neural Network (DNN) to perform semantic segmentation in order to identify these classes in further HiRISE images. This contribution discusses the methods and results of the study from a geomorphologists perspective, providing a case study applying machine learning to a landscape classification task. Our aim is to highlight considerations about how to compile training datasets, select ontological classes, and understand what such systems can and cannot do. We highlight issues that arise when adapting a traditional planetary mapping workflow to the production of training data. We discuss both the pixel scale accuracy of the model, and how qualitative factors can influence the reliability and usability of the output. We conclude that “landscape level” reliability is critical for the use of the output raster by humans. The output can often be more useful than pixel scale accuracy statistics would suggest, however the product must be treated with caution, and not considered a final arbiter of geological origin. A good understanding of how and why the model classifies different landscape features is vital to interpreting it reliably. When used appropriately the classified raster provides a good indication of the prevalence and distribution of different terrain types, and informs our understanding of the study areas. We thus conclude that it is fit for purpose, and suitable for use in further work

Applying SMT Solvers to the Test Template Framework

The Test Template Framework (TTF) is a model-based testing method for the Z notation. In the TTF, test cases are generated from test specifications, which are predicates written in Z. In turn, the Z notation is based on first-order logic with equality and Zermelo-Fraenkel set theory. In this way, a test case is a witness satisfying a formula in that theory. Satisfiability Modulo Theory (SMT) solvers are software tools that decide the satisfiability of arbitrary formulas in a large number of built-in logical theories and their combination. In this paper, we present the first results of applying two SMT solvers, Yices and CVC3, as the engines to find test cases from TTF's test specifications. In doing so, shallow embeddings of a significant portion of the Z notation into the input languages of Yices and CVC3 are provided, given that they do not directly support Zermelo-Fraenkel set theory as defined in Z. Finally, the results of applying these embeddings to a number of test specifications of eight cases studies are analysed.Comment: In Proceedings MBT 2012, arXiv:1202.582

Incidence, Risk Factors, and Outcomes of Incidental Durotomy during Lumbar Spine Decompression with or without Fusion

STUDY DESIGN: Retrospective cohort study. PURPOSE: The primary objective of this study was to determine the incidence and risk factors for incidental durotomies during lumbar decompression surgeries. In addition, we aimed to determine the changes in patient-reported outcome measures (PROMs) based on incidental durotomy status. OVERVIEW OF LITERATURE: There is limited literature investigating the affect of incidental durotomy on patient reported outcome measures. While the majority of research does not suggest differences in complications, readmission, or revision rates, many studies rely on public databases, and their sensitivity and specificity for identifying incidental durotomies is unknown. METHODS: Patients undergoing lumbar decompression with or without fusion at a single tertiary care center were grouped based on the presence of a durotomy. Multivariate analysis was performed for length of stay (LOS), hospital readmissions, and changes in PROMs. To identify surgical risk factors for durotomy, 3:1 propensity matching was performed using stepwise logistic regression. The sensitivity and specificity of the International Classification of Disease, 10th revision (ICD-10) codes (G96.11 and G97.41) were also assessed. RESULTS: Of the 3,684 consecutive patients who underwent lumbar decompressions, 533 (14.5%) had durotomies, and a complete set of PROMs (preoperative and 1-year postoperative) were available for 737 patients (20.0%). Incidental durotomy was an independent predictor of increased LOS but not hospital readmission or worse PROMs. The durotomy repair method was not associated with hospital readmission or LOS. However, repair with collagen graft and suture predicted reduced improvement in Visual Analog Scale back (β =2.56, p=0.004). Independent risk factors for incidental durotomies included revisions (odds ratio [OR], 1.73; p CONCLUSIONS: The durotomy rate for lumbar decompressions was 14.5%. No differences in outcomes were detected except for increased LOS. Database studies relying on ICD codes should be interpreted with caution due to the limited sensitivity in identifying incidental durotomies

Reference Array and Design Consideration for the next-generation Event Horizon Telescope

We describe the process to design, architect, and implement a transformative enhancement of the Event Horizon Telescope (ngEHT). This program - the next-generation Event Horizon Telescope (ngEHT) - will form a networked global array of radio dishes capable of making high-fidelity real-time movies of supermassive black holes (SMBH) and their emanating jets. This builds upon the EHT principally by deploying additional modest-diameter dishes to optimized geographic locations to enhance the current global mm/submm wavelength Very Long Baseline Interferometric (VLBI) array, which has, to date, utilized mostly pre-existing radio telescopes. The ngEHT program further focuses on observing at three frequencies simultaneously for increased sensitivity and Fourier spatial frequency coverage. Here, the concept, science goals, design considerations, station siting and instrument prototyping are discussed, and a preliminary reference array to be implemented in phases is described.Comment: Submitted to the journal Galaxie

Socio-Technical Innovation Bundles for Agri-Food Systems Transformation

This open access book is the result of an expert panel convened by the Cornell Atkinson Center for Sustainability and Nature Sustainability. The panel tackled the seventeen UN Sustainable Development Goals (SDGs) for 2030 head-on, with respect to the global systems that produce and distribute food. The panel’s rigorous synthesis and analysis of existing research leads compellingly to multiple actionable recommendations that, if adopted, would simultaneously lead to healthy and nutritious diets, equitable and inclusive value chains, resilience to shocks and stressors, and climate and environmental sustainability

Articulating the effect of food systems innovation on the Sustainable Development Goals

Food system innovations will be instrumental to achieving multiple Sustainable Development Goals (SDGs). However, major innovation breakthroughs can trigger profound and disruptive changes, leading to simultaneous and interlinked reconfigurations of multiple parts of the global food system. The emergence of new technologies or social solutions, therefore, have very different impact profiles, with favourable consequences for some SDGs and unintended adverse side-effects for others. Stand-alone innovations seldom achieve positive outcomes over multiple sustainability dimensions. Instead, they should be embedded as part of systemic changes that facilitate the implementation of the SDGs. Emerging trade-offs need to be intentionally addressed to achieve true sustainability, particularly those involving social aspects like inequality in its many forms, social justice, and strong institutions, which remain challenging. Trade-offs with undesirable consequences are manageable through the development of well planned transition pathways, careful monitoring of key indicators, and through the implementation of transparent science targets at the local level

Serotonin Reuptake Inhibitor Increases Pseudarthrosis Rates in Anterior Cervical Discectomy and Fusions

STUDY DESIGN: Retrospective cohort. PURPOSE: To determine (1) the effects of serotonin reuptake inhibitors in pseudarthrosis rates after anterior cervical decompression and fusion (ACDF) and (2) to identify patient-reported outcome measures in patients taking serotonin reuptake inhibitors. OVERVIEW OF LITERATURE: Recent literature suggests that selective serotonin reuptake inhibitors (SSRIs) may inhibit fracture healing via downregulation of osteoblast differentiation. Spinal fusion supplementation with osteoblast-rich substances enhances spinal fusion, thus SSRIs may be detrimental. METHODS: Patients with 1-year postoperative dynamic cervical spine radiographs following ACDF were grouped into serotonin reuptake inhibitor prescriptions (SSRI, serotonin-norepinephrine reuptake inhibitor [SNRI], or tricyclic antidepressant [TCA]) and no prescription (atypical antidepressant or no antidepressant). Pseudarthrosis was defined as ≥1 mm interspinous process motion on dynamic radiographs. Logistic regression models were controlled for confounding to analyze pseudarthrosis rates. Alpha was set at p - values of \u3c0.05. RESULTS: Of the 523 patients who meet the inclusion criteria, 137 (26.2%) were prescribed an SSRI, SNRI, or TCA. Patients with these prescriptions were more likely to have pseudarthrosis (p =0.008) but not a revision surgery due to pseudarthrosis (p =0.219). Additionally, these patients had worse 1-year postoperative mental component summary (MCS)-12 (p =0.015) and Neck Disability Index (NDI) (p =0.006). The multivariate logistic regression analysis identified SSRI/SNRI/TCA use (odds ratio [OR], 1.82; 95% confidence interval [CI], 1.11-2.99; p =0.018) and construct length (OR, 1.91; 95% CI, 1.50-2.44; p CONCLUSIONS: Patients taking serotonin reuptake-inhibiting antidepressants are at increased risk of worse postoperative outcome scores, including NDI and MCS-12, likely due to their underlying depression. This may contribute to their greater likelihood of having adjacent segment surgery. Additionally, preoperative use of serotonin reuptake inhibitors in patients undergoing an ACDF is a predictor of radiographic pseudarthrosis but not pseudarthrosis revision

Articulating the effect of food systems innovation on the Sustainable Development Goals

Acknowledgments MH, DM-D, JP, JRB, AH, GDB, CMG, CLM, and KR acknowledge funding from the Commonwealth Scientific and Industrial Research Organisation. PKT, BMC, AJ, and AML acknowledge funding from the CGIAR Research Program on Climate Change, Agriculture and Food Security, which is supported by the CGIAR Trust Fund and through bilateral funding agreements. PP acknowledges funding from the German Federal Ministry of Education and Research for the BIOCLIMAPATHS project.Peer reviewedPublisher PD