Search

Your search keyword '"Bell, Jonathan"' showing total 1,503 results
Start Over Author "Bell, Jonathan"

Refine your results

more »

more »

more »

more »

more »

more »
1,503 results on '"Bell, Jonathan"'

2. NNsight and NDIF: Democratizing Access to Open-Weight Foundation Model Internals

Author

Fiotto-Kaufman, Jaden, Loftus, Alexander R., Todd, Eric, Brinkmann, Jannik, Pal, Koyena, Troitskii, Dmitrii, Ripa, Michael, Belfki, Adam, Rager, Can, Juang, Caden, Mueller, Aaron, Marks, Samuel, Sharma, Arnab Sen, Lucchetti, Francesca, Prakash, Nikhil, Brodley, Carla, Guha, Arjun, Bell, Jonathan, Wallace, Byron C., and Bau, David

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence
Abstract

We introduce NNsight and NDIF, technologies that work in tandem to enable scientific study of very large neural networks. NNsight is an open-source system that extends PyTorch to introduce deferred remote execution. NDIF is a scalable inference service that executes NNsight requests, allowing users to share GPU resources and pretrained models. These technologies are enabled by the intervention graph, an architecture developed to decouple experiment design from model runtime. Together, this framework provides transparent and efficient access to the internals of deep neural networks such as very large language models (LLMs) without imposing the cost or complexity of hosting customized models individually. We conduct a quantitative survey of the machine learning literature that reveals a growing gap in the study of the internals of large-scale AI. We demonstrate the design and use of our framework to address this gap by enabling a range of research methods on huge models. Finally, we conduct benchmarks to compare performance with previous approaches. Code documentation, and materials are available at https://nnsight.net/., Comment: Code at https://nnsight.net

Published
2024

3. LLMorpheus: Mutation Testing using Large Language Models

Author

Tip, Frank, Bell, Jonathan, and Schäfer, Max

Subjects
Computer Science - Software Engineering
Abstract

In mutation testing, the quality of a test suite is evaluated by introducing faults into a program and determining whether the program's tests detect them. Most existing approaches for mutation testing involve the application of a fixed set of mutation operators, e.g., replacing a "+" with a "-" or removing a function's body. However, certain types of real-world bugs cannot easily be simulated by such approaches, limiting their effectiveness. This paper presents a technique where a Large Language Model (LLM) is prompted to suggest mutations by asking it what placeholders that have been inserted in source code could be replaced with. The technique is implemented in LLMorpheus, a mutation testing tool for JavaScript, and evaluated on 13 subject packages, considering several variations on the prompting strategy, and using several LLMs. We find LLMorpheus to be capable of producing mutants that resemble existing bugs that cannot be produced by StrykerJS, a state-of-the-art mutation testing tool. Moreover, we report on the running time, cost, and number of mutants produced by LLMorpheus, demonstrating its practicality.

Published
2024

4. 230,439 Test Failures Later: An Empirical Evaluation of Flaky Failure Classifiers

Author

Alshammari, Abdulrahman, Ammann, Paul, Hilton, Michael, and Bell, Jonathan

Subjects
Computer Science - Software Engineering
Abstract

Flaky tests are tests that can non-deterministically pass or fail, even in the absence of code changes.Despite being a source of false alarms, flaky tests often remain in test suites once they are detected, as they also may be relied upon to detect true failures. Hence, a key open problem in flaky test research is: How to quickly determine if a test failed due to flakiness, or if it detected a bug? The state-of-the-practice is for developers to re-run failing tests: if a test fails and then passes, it is flaky by definition; if the test persistently fails, it is likely a true failure. However, this approach can be both ineffective and inefficient. An alternate approach that developers may already use for triaging test failures is failure de-duplication, which matches newly discovered test failures to previously witnessed flaky and true failures. However, because flaky test failure symptoms might resemble those of true failures, there is a risk of missclassifying a true test failure as a flaky failure to be ignored. Using a dataset of 498 flaky tests from 22 open-source Java projects, we collect a large dataset of 230,439 failure messages (both flaky and not), allowing us to empirically investigate the efficacy of failure de-duplication. We find that for some projects, this approach is extremely effective (with 100\% specificity), while for other projects, the approach is entirely ineffective. By analyzing the characteristics of these flaky and non-flaky failures, we provide useful guidance on how developers should rely on this approach.

Published
2024

5. The Effects of Computational Resources on Flaky Tests

Author

Silva, Denini, Gruber, Martin, Gokhale, Satyajit, Arteca, Ellen, Turcotte, Alexi, d'Amorim, Marcelo, Lam, Wing, Winter, Stefan, and Bell, Jonathan

Subjects
Computer Science - Software Engineering
Abstract

Flaky tests are tests that nondeterministically pass and fail in unchanged code. These tests can be detrimental to developers' productivity. Particularly when tests run in continuous integration environments, the tests may be competing for access to limited computational resources (CPUs, memory etc.), and we hypothesize that resource (in)availability may be a significant factor in the failure rate of flaky tests. We present the first assessment of the impact that computational resources have on flaky tests, including a total of 52 projects written in Java, JavaScript and Python, and 27 different resource configurations. Using a rigorous statistical methodology, we determine which tests are RAFT (Resource-Affected Flaky Tests). We find that 46.5% of the flaky tests in our dataset are RAFT, indicating that a substantial proportion of flaky-test failures can be avoided by adjusting the resources available when running tests. We report RAFTs and configurations to avoid them to developers, and received interest to either fix the RAFTs or to improve the specifications of the projects so that tests would be run only in configurations that are unlikely to encounter RAFT failures. Our results also have implications for researchers attempting to detect flaky tests, e.g., reducing the resources available when running tests is a cost-effective approach to detect more flaky failures., Comment: This work has been submitted to the IEEE for possible publication

Published
2023

6. 'Always Nice and Confident, Sometimes Wrong': Developer's Experiences Engaging Large Language Models (LLMs) Versus Human-Powered Q&A Platforms for Coding Support

Author

Li, Jiachen, Mynatt, Elizabeth, Mishra, Varun, and Bell, Jonathan

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Software Engineering
Abstract

Software engineers have historically relied on human-powered Q&A platforms like Stack Overflow (SO) as coding aids. With the rise of generative AI, developers have started to adopt AI chatbots, such as ChatGPT, in their software development process. Recognizing the potential parallels between human-powered Q&A platforms and AI-powered question-based chatbots, we investigate and compare how developers integrate this assistance into their real-world coding experiences by conducting a thematic analysis of 1700+ Reddit posts. Through a comparative study of SO and ChatGPT, we identified each platform's strengths, use cases, and barriers. Our findings suggest that ChatGPT offers fast, clear, comprehensive responses and fosters a more respectful environment than SO. However, concerns about ChatGPT's reliability stem from its overly confident tone and the absence of validation mechanisms like SO's voting system. Based on these findings, we synthesized the design implications for future GenAI code assistants and recommend a workflow leveraging each platform's unique features to improve developer experiences.

Published
2023

7. npm-follower: A Complete Dataset Tracking the NPM Ecosystem

Author

Pinckney, Donald, Cassano, Federico, Guha, Arjun, and Bell, Jonathan

Subjects
Computer Science - Software Engineering
Abstract

Software developers typically rely upon a large network of dependencies to build their applications. For instance, the NPM package repository contains over 3 million packages and serves tens of billions of downloads weekly. Understanding the structure and nature of packages, dependencies, and published code requires datasets that provide researchers with easy access to metadata and code of packages. However, prior work on NPM dataset construction typically has two limitations: 1) only metadata is scraped, and 2) packages or versions that are deleted from NPM can not be scraped. Over 330,000 versions of packages were deleted from NPM between July 2022 and May 2023. This data is critical for researchers as it often pertains to important questions of security and malware. We present npm-follower, a dataset and crawling architecture which archives metadata and code of all packages and versions as they are published, and is thus able to retain data which is later deleted. The dataset currently includes over 35 million versions of packages, and grows at a rate of about 1 million versions per month. The dataset is designed to be easily used by researchers answering questions involving either metadata or program analysis. Both the code and dataset are available at https://dependencies.science.

Published
2023

9. A Large Scale Analysis of Semantic Versioning in NPM

Author

Pinckney, Donald, Cassano, Federico, Guha, Arjun, and Bell, Jonathan

Subjects
Computer Science - Software Engineering
Abstract

The NPM package repository contains over two million packages and serves tens of billions of downloads per-week. Nearly every single JavaScript application uses the NPM package manager to install packages from the NPM repository. NPM relies on a "semantic versioning" ('semver') scheme to maintain a healthy ecosystem, where bug-fixes are reliably delivered to downstream packages as quickly as possible, while breaking changes require manual intervention by downstream package maintainers. In order to understand how developers use semver, we build a dataset containing every version of every package on NPM and analyze the flow of updates throughout the ecosystem. We build a time-travelling dependency resolver for NPM, which allows us to determine precisely which versions of each dependency would have been resolved at different times. We segment our analysis to allow for a direct analysis of security-relevant updates (those that introduce or patch vulnerabilities) in comparison to the rest of the ecosystem. We find that when developers use semver correctly, critical updates such as security patches can flow quite rapidly to downstream dependencies in the majority of cases (90.09%), but this does not always occur, due to developers' imperfect use of both semver version constraints and semver version number increments. Our findings have implications for developers and researchers alike. We make our infrastructure and dataset publicly available under an open source license.

Published
2023

13. Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets

Author

Zhao, Jing Hua, Stacey, David, Eriksson, Niclas, Macdonald-Dunlop, Erin, Hedman, Åsa K., Kalnapenkis, Anette, Enroth, Stefan, Cozzetto, Domenico, Digby-Bell, Jonathan, Marten, Jonathan, Folkersen, Lasse, Herder, Christian, Jonsson, Lina, Bergen, Sarah E., Gieger, Christian, Needham, Elise J., Surendran, Praveen, Paul, Dirk S., Polasek, Ozren, Thorand, Barbara, Grallert, Harald, Roden, Michael, Võsa, Urmo, Esko, Tonu, Hayward, Caroline, Johansson, Åsa, Gyllensten, Ulf, Powell, Nick, Hansson, Oskar, Mattsson-Carlgren, Niklas, Joshi, Peter K., Danesh, John, Padyukov, Leonid, Klareskog, Lars, Landén, Mikael, Wilson, James F., Siegbahn, Agneta, Wallentin, Lars, Mälarstig, Anders, Butterworth, Adam S., and Peters, James E.

Published
2023
Full Text
View/download PDF

16. Leaf segmentation through the classification of edges

Author

Bell, Jonathan and Dee, Hannah M.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We present an approach to leaf level segmentation of images of Arabidopsis thaliana plants based upon detected edges. We introduce a novel approach to edge classification, which forms an important part of a method to both count the leaves and establish the leaf area of a growing plant from images obtained in a high-throughput phenotyping system. Our technique uses a relatively shallow convolutional neural network to classify image edges as background, plant edge, leaf-on-leaf edge or internal leaf noise. The edges themselves were found using the Canny edge detector and the classified edges can be used with simple image processing techniques to generate a region-based segmentation in which the leaves are distinct. This approach is strong at distinguishing occluding pairs of leaves where one leaf is largely hidden, a situation which has proved troublesome for plant image analysis systems in the past. In addition, we introduce the publicly available plant image dataset that was used for this work.

Published
2019

17. Combined PI3Kα-mTOR Targeting of Glioma Stem Cells

Author

Eckerdt, Frank D, Bell, Jonathan B, Gonzalez, Christopher, Oh, Michael S, Perez, Ricardo E, Mazewski, Candice, Fischietti, Mariafausta, Goldman, Stewart, Nakano, Ichiro, and Platanias, Leonidas C

Subjects
Biomedical and Clinical Sciences, Oncology and Carcinogenesis, Rare Diseases, Stem Cell Research - Nonembryonic - Non-Human, Clinical Research, Stem Cell Research - Nonembryonic - Human, Brain Cancer, Stem Cell Research, Brain Disorders, Cancer, Neurosciences, Brain Neoplasms, Cell Line, Tumor, Glioma, Humans, Neoplastic Stem Cells, Phosphatidylinositol 3-Kinases, Proto-Oncogene Proteins c-akt, Spheroids, Cellular, TOR Serine-Threonine Kinases, Thiazoles
Abstract

Glioblastoma (GBM) is the most common and lethal primary intrinsic tumour of the adult brain and evidence indicates disease progression is driven by glioma stem cells (GSCs). Extensive advances in the molecular characterization of GBM allowed classification into proneural, mesenchymal and classical subtypes, and have raised expectations these insights may predict response to targeted therapies. We utilized GBM neurospheres that display GSC characteristics and found activation of the PI3K/AKT pathway in sphere-forming cells. The PI3Kα selective inhibitor alpelisib blocked PI3K/AKT activation and inhibited spheroid growth, suggesting an essential role for the PI3Kα catalytic isoform. p110α expression was highest in the proneural subtype and this was associated with increased phosphorylation of AKT. Further, employing the GBM BioDP, we found co-expression of PIK3CA with the neuronal stem/progenitor marker NES was associated with poor prognosis in PN GBM patients, indicating a unique role for PI3Kα in PN GSCs. Alpelisib inhibited GSC neurosphere growth and these effects were more pronounced in GSCs of the PN subtype. The antineoplastic effects of alpelisib were substantially enhanced when combined with pharmacologic mTOR inhibition. These findings identify the alpha catalytic PI3K isoform as a unique therapeutic target in proneural GBM and suggest that pharmacological mTOR inhibition may sensitize GSCs to selective PI3Kα inhibition.

Published
2020

20. Obfuscation Resilient Search through Executable Classification

Author

Su, Fang-Hsiang, Bell, Jonathan, Kaiser, Gail, and Ray, Baishakhi

Subjects
Computer Science - Software Engineering, Computer Science - Cryptography and Security
Abstract

Android applications are usually obfuscated before release, making it difficult to analyze them for malware presence or intellectual property violations. Obfuscators might hide the true intent of code by renaming variables and/or modifying program structures. It is challenging to search for executables relevant to an obfuscated application for developers to analyze efficiently. Prior approaches toward obfuscation resilient search have relied on certain structural parts of apps remaining as landmarks, un-touched by obfuscation. For instance, some prior approaches have assumed that the structural relationships between identifiers are not broken by obfuscators; others have assumed that control flow graphs maintain their structures. Both approaches can be easily defeated by a motivated obfuscator. We present a new approach,Macneto, to search for programs relevant to obfuscated executables leveraging deep learning and principal components on instructions. Macneto makes few assumptions about the kinds of modifications that an obfuscator might perform. We show that it has high search precision for executables obfuscated by a state-of-the-art obfuscator that changes control flow. Further, we also demonstrate the potential of Macneto to help developers understand executables, where Macneto infers keywords (which are from the relevant unobfuscated program) for obfuscated executables., Comment: MAPL, 2018 (Workshop co-located with PLDI 2018)

Published
2018

21. Use of Machine Learning-Based Software for the Screening of Thyroid Cytopathology Whole Slide Images

Author

Dov, David, Kovalsky, Shahar Z., Feng, Qizhang, Assaad, Serge, Cohen, Jonathan, Bell, Jonathan, Henao, Ricardo, Carin, Lawrence, and Range, Danielle Elliott

Subjects
Diagnosis, Usage, Methods, Algorithm, Image processing software, Image processing software -- Usage, Algorithms -- Usage, Needle biopsy -- Methods, Machine learning -- Usage, Thyroid diseases -- Diagnosis, Cytodiagnosis -- Methods, Image processing -- Computer programs, Biopsy, Needle -- Methods
Abstract

Thyroid nodules are common, and an estimated 10% of the US population will have one in their lifetime. The majority of thyroid nodules are benign. (1) The routine evaluation of [...], Context.-The use of whole slide images (WSIs) in diagnostic pathology presents special challenges for the cytopathologist. Informative areas on a direct smear from a thyroid fine-needle aspiration biopsy (FNAB) smear may be spread across a large area comprising blood and dead space. Manually navigating through these areas makes screening and evaluation of FNA smears on a digital platform time-consuming and laborious. We designed a machine learning algorithm that can identify regions of interest (ROIs) on thyroid fine-needle aspiration biopsy WSIs. Objective.-To evaluate the ability of the machine learning algorithm and screening software to identify and screen for a subset of informative ROIs on a thyroid FNA WSI that can be used for final diagnosis. Design.-A representative slide from each of 109 consecutive thyroid fine-needle aspiration biopsies was scanned. A cytopathologist reviewed each WSI and recorded a diagnosis. The machine learning algorithm screened and selected a subset of 100 ROIs from each WSI to present as an image gallery to the same cytopathologist after a washout period of 117 days. Results.-Concordance between the diagnoses using WSIs and those using the machine learning algorithmgenerated ROI image gallery was evaluated using pairwise weighted k statistics. Almost perfect concordance was seen between the 2 methods with a k score of 0.924. Conclusions.-Our results show the potential of the screening software as an effective screening tool with the potential to reduce cytopathologist workloads.

Published
2022
Full Text
View/download PDF

22. A Hybrid Human-Machine Learning Approach for Screening Prostate Biopsies Can Improve Clinical Efficiency Without Compromising Diagnostic Accuracy

Author

Dov, David, Assaad, Serge, Syedibrahim, Ameer, Bell, Jonathan, Huang, Jiaoti, Madden, John, Bentley, Rex, McCall, Shannon, Henao, Ricardo, Carin, Lawrence, and Foo, Wen-Chi

Subjects
Diagnosis, Usage, Methods, Human-machine systems -- Usage, Machine learning -- Usage, Prostate biopsy -- Methods, Prostate cancer -- Diagnosis, Computer aided medical diagnosis -- Methods, Prostate -- Biopsy, Computer-aided medical diagnosis -- Methods
Abstract

Prostate cancer is one of the most common malignancies in the developed world and is projected to account for more than 190 000 new cancer diagnoses in the United States [...], * Context.--Prostate cancer is a common malignancy, and accurate diagnosis typically requires histologic review of multiple prostate core biopsies per patient. As pathology volumes and complexity increase, new tools to improve the efficiency of everyday practice are keenly needed. Deep learning has shown promise in pathology diagnostics, but most studies silo the efforts of pathologists from the application of deep learning algorithms. Very few hybrid pathologist-deep learning approaches have been explored, and these typically require complete review of histologic slides by both the pathologist and the deep learning system. Objective.--To develop a novel and efficient hybrid human-machine learning approach to screen prostate biopsies. Design.--We developed an algorithm to determine the 20 regions of interest with the highest probability of malignancy for each prostate biopsy; presenting these regions to a pathologist for manual screening limited the initial review by a pathologist to approximately 2% of the tissue area of each sample. We evaluated this approach by using 100 biopsies (29 malignant, 60 benign, 11 other) that were reviewed by 4 pathologists (3 urologic pathologists, 1 general pathologist) using a custom-designed graphical user interface. Results.--Malignant biopsies were correctly identified as needing comprehensive review with high sensitivity (mean, 99.2% among all pathologists); conversely, most benign prostate biopsies (mean, 72.1%) were correctly identified as needing no further review. Conclusions.--This novel hybrid system has the potential to efficiently triage out most benign prostate core biopsies, conserving time for the pathologist to dedicate to detailed evaluation of malignant biopsies.

Published
2022
Full Text
View/download PDF

24. New methods for the stereoselective synthesis of fluorescent amino acids, natural products and biomolecules

Author

Bell, Jonathan D.

Subjects
547, QD Chemistry
Abstract

The stereoselective synthesis of fluorescent amino acids, biomolecules and natural products was achieved using a chiral pool strategy with α-amino acids. The use of L-aspartic acid gave access to a small library of enone derived amino acids via a Horner-Wadsworth-Emmons (HWE) reaction. Transformation of the enones via a number of steps gave a series of pyrazoloquinazoline derived amino acids. Due to the rigid structure of these amino acids, high quantum yields were observed. The lead compound from this series, a dimethylamino substituted pyrazoloquinazoline also displayed high excitation and emission wavelengths. It was found that this compound could be excited either by a one or a two-photon process. This amino acid was also incorporated into a short cell-penetrating pentapeptide in high yield, with no loss of fluorescence. A second series of fluorescent amino acids bearing benzotriazole side-chains was synthesised from L-asparagine in five steps. The conjugation of these was extended using a Suzuki-Miyaura reaction that led to a highly fluorescent 4-methoxyphenyl substituted analogue. This new chromophore was also rigidified using a copper-catalysed C-H insertion reaction, which yielded a new carbazole derived amino acid. The HWE reaction used in the first project was investigated as a new approach for bioconjugation. The aspartic acid derived phosphonate ester was coupled with alanine, and this model dipeptide was subjected to successful HWE reactions with various aldehydes, showing this as a possible new method for incorporating chromophores within peptides and proteins. Finally, L-aspartic acid was also used as a starting material to synthesis a small library of enones, using a HWE reaction. These were found to be excellent substrates for an acid-mediated 6-endo-trig¬¬ cyclisation for the stereoselective synthesis of a series of 2,6-dialkyl-4-oxopiperidines. This transformation was then used as the key step for the synthesis of the alkaloids, (+)-myrtine and (−)-solenopsin A.

Published
2019
Full Text
View/download PDF

25. PATENT PROPHYLAXIS: EXPANDING ACCESS TO PREP THROUGH 28 U.S.C. [section] 1498.

Author

Bell, Jonathan A.

Subjects
Government litigation -- Analysis, Patent licenses -- Laws, regulations and rules, Antiviral agents -- Intellectual property -- Access control -- Laws, regulations and rules, Eminent domain (Law) -- Laws, regulations and rules, Anti-HIV agents -- Intellectual property -- Access control -- Laws, regulations and rules, Prescription pricing -- Analysis -- Control -- Laws, regulations and rules, Patent infringement -- Analysis -- Remedies -- Laws, regulations and rules, Price gouging -- Prevention -- Remedies -- Laws, regulations and rules, Government regulation, Judicial Code (28 U.S.C. 1498), Bayh-Dole Act (35 U.S.C. 202(c)(4)) (35 U.S.C. 203), United States Constitution (U.S. Const. amend. 5)
Abstract

TABLE OF CONTENTS Introduction 2058 I. Patent Infringement Litigation Is Unlikely to Expand Patient Access to PrEP 2063 A. The Development of Truvada for PrEP 2063 B. CDC's Patents-in-Suit 2064 [...]

Published
2022

26. Countering Swarms: Strategic Considerations and Opportunities in Drone Warfare

Author

Bell, Jonathan B.

Subjects
Drone aircraft -- Usage, Military art and science -- Technology application, Swarm intelligence -- Usage, Technology application, Military and naval science
Abstract

One of our most important duties as professionals is to think clearly about the problem of future armed conflict. --General David Perkins (1) The Department of Defense (DOD) and the [...]

Published
2022

27. Author Correction: Genetics of circulating inflammatory proteins identifies drivers of immune-mediated disease risk and therapeutic targets

Author

Zhao, Jing Hua, Stacey, David, Eriksson, Niclas, Macdonald-Dunlop, Erin, Hedman, Åsa K., Kalnapenkis, Anette, Enroth, Stefan, Cozzetto, Domenico, Digby-Bell, Jonathan, Marten, Jonathan, Folkersen, Lasse, Herder, Christian, Jonsson, Lina, Bergen, Sarah E., Gieger, Christian, Needham, Elise J., Surendran, Praveen, Paul, Dirk S., Polasek, Ozren, Thorand, Barbara, Grallert, Harald, Roden, Michael, Võsa, Urmo, Esko, Tonu, Hayward, Caroline, Johansson, Åsa, Gyllensten, Ulf, Powell, Nick, Hansson, Oskar, Mattsson-Carlgren, Niklas, Joshi, Peter K., Danesh, John, Padyukov, Leonid, Klareskog, Lars, Landén, Mikael, Wilson, James F., Siegbahn, Agneta, Wallentin, Lars, Mälarstig, Anders, Butterworth, Adam S., and Peters, James E.

Published
2023
Full Text
View/download PDF

29. Interleukin-22 regulates neutrophil recruitment in ulcerative colitis and is associated with resistance to ustekinumab therapy

Author

Pavlidis, Polychronis, Tsakmaki, Anastasia, Pantazi, Eirini, Li, Katherine, Cozzetto, Domenico, Digby- Bell, Jonathan, Yang, Feifei, Lo, Jonathan W., Alberts, Elena, Sa, Ana Caroline Costa, Niazi, Umar, Friedman, Joshua, Long, Anna K., Ding, Yuchun, Carey, Christopher D., Lamb, Christopher, Saqi, Mansoor, Madgwick, Matthew, Gul, Leila, Treveil, Agatha, Korcsmaros, Tamas, Macdonald, Thomas T., Lord, Graham M., Bewick, Gavin, and Powell, Nick

Published
2022
Full Text
View/download PDF

30. The BabelBox: An Embedded System for Score Distribution on Raspberry Pi with INScore, SmartVox and BabelScores

Author

Bell, Jonathan, Fober, Dominique, Fígols-Cuevas, Daniel, Garcia-Velasquez, Pedro, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Kronland-Martinet, Richard, editor, Ystad, Sølvi, editor, and Aramaki, Mitsuko, editor

Published
2021
Full Text
View/download PDF

34. The subset-matched Jaccard index for evaluation of Segmentation for Plant Images

Author

Bell, Jonathan and Dee, Hannah M.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We describe a new measure for the evaluation of region level segmentation of objects, as applied to evaluating the accuracy of leaf-level segmentation of plant images. The proposed approach enforces the rule that a region (e.g. a leaf) in either the image being evaluated or the ground truth image evaluated against can be mapped to no more than one region in the other image. We call this measure the subset-matched Jaccard index.

Published
2016

36. Reactogenicity and immunogenicity after a late second dose or a third dose of ChAdOx1 nCoV-19 in the UK: a substudy of two randomised controlled trials (COV001 and COV002)

Author

Adlou, Syed, Aley, Robert, Ali, Aabidah, Anslow, Rachel, Baker, Megan, Baker, Phillip, Barrett, Jordan R., Bates, Louise, Beadon, Kirsten, Beckley, Rebecca, Bell, Jonathan, Bellamy, Duncan, Beveridge, Amy, Bissett, Cameron, Blackwell, Luke, Bletchly, Heather, Boyd, Amy, Bridges-Webb, Alice, Brown, Charlie, Byard, Nicholas, Camara, Susana, Cifuentes Gutierrez, Liliana, Collins, Andrea M., Cooper, Rachel, Crocker, Wendy E.M., Darton, Thomas C., Davies, Hannah, Davies, Judith, Demissie, Tesfaye, Di Maso, Claudio, Dinesh, Tanya, Donnellan, Francesca R., Douglas, Alexander D., Drake-Brockman, Rachael, Duncan, Christopher J.A., Elias, Sean C., Emary, Katherine R.W., Ghulam Farooq, Mutjaba, Faust, Saul N., Felle, Sally, Ferreira, Daniela, Ferreira Da Silva, Carla, Finn, Adam, Ford, Karen J., Francis, Emma, Furze, Julie, Fuskova, Michelle, Galiza, Eva, Gibertoni Cruz, Ana, Godfrey, Leila, Goodman, Anna L., Green, Catherine, Green, Christopher A., Greenwood, Nicola, Harrison, Daisy, Hart, Thomas C., Hawkins, Sophia, Heath, Paul T., Hill, Helen, Hillson, Kushalinii, Horsington, Bryn, Hou, Mimi M., Howe, Elizabeth, Howell, Nicola, Joe, Carina, Jones, Elizabeth, Kasanyinga, Mwila, Keen, Jade, Kelly, Sarah, Kerr, David, Khan, Liaquat, Khozoee, Baktash, Kinch, Jasmin, Kinch, Patrick, Koleva, Stanislava, Kwok, Jonathan, Larkworthy, Colin W., Lawrie, Alison M., Lazarus, Rajeka, Lees, Emily A., Li, Grace, Libri, Vincenzo, Lillie, Patrick J., Linder, Aline, Long, Fei, Lopez Ramon, Raquel, Mabbett, Reece, Makinson, Rebecca, Marinou, Spyridoula, Marlow, Emma, Marshall, Julia L., Mazur, Olga, McEwan, Joanne, McGregor, Alastair C., Mokaya, Jolynne, Morey, Ella, Morshead, Gertraud, Morter, Richard, Muller, Jilly, Mweu, Philomena, Noristani, Rabiullah, Owino, Nelly, Polo Peralta Alvarez, Marco, Platt, Abigail, Pollock, Katrina M., Poulton, Ian, Provstgaard-Morys, Samuel, Pulido-Gomez, David, Rajan, Matthew, Ramos Lopez, Fernando, Ritchie, Adam, Roberts, Hannah, Rollier, Christine, Rudiansyah, Indra, Sanders, Katherine, Saunders, Jack E., Seddiqi, Samiullah, Sharpe, Hannah R., Shaw, Robert, Silva-Reyes, Laura, Singh, Nisha, Smith, David J., Smith, Catherine C., Smith, Andrew, Spencer, Alexandra J., Stuart, Arabella S.V., Sutherland, Rebecca, Szigeti, Anna, Tang, Karly, Thomas, Merin, Thomas, Tonia M., Thompson, Amber, Thomson, Emma C., Török, Estée M., Toshner, Mark, Tran, Nguyen, Trivett, Rose, Turnbull, Iain, Turner, Cheryl, Turner, David P.J., Ulaszewska, Marta, Vichos, Iason, Walker, Laura, Watson, Marion E., Whelan, Conor, White, Rachel, Williams, Sarah J., Williams, Christopher J.A., Wright, Daniel, Yao, Andy, Flaxman, Amy, Marchevsky, Natalie G, Jenkin, Daniel, Aboagye, Jeremy, Aley, Parvinder K, Angus, Brian, Belij-Rammerstorfer, Sandra, Bibi, Sagida, Bittaye, Mustapha, Cappuccini, Federica, Cicconi, Paola, Clutterbuck, Elizabeth A, Davies, Sophie, Dejnirattisai, Wanwisa, Dold, Christina, Ewer, Katie J, Folegatti, Pedro M, Fowler, Jamie, Hill, Adrian V S, Kerridge, Simon, Minassian, Angela M, Mongkolsapaya, Juthathip, Mujadidi, Yama F, Plested, Emma, Ramasamy, Maheshi N, Robinson, Hannah, Sanders, Helen, Sheehan, Emma, Smith, Holly, Snape, Matthew D, Song, Rinn, Woods, Danielle, Screaton, Gavin, Gilbert, Sarah C, Voysey, Merryn, Pollard, Andrew J, and Lambe, Teresa

Published
2021
Full Text
View/download PDF

37. The Effects of Computational Resources on Flaky Tests

Author

Silva, Denini, Gruber, Martin, Gokhale, Satyajit, Arteca, Ellen, Turcotte, Alexi, dAmorim, Marcelo, Lam, Wing, Winter, Stefan, and Bell, Jonathan

Abstract

Flaky tests are tests that non-deterministically pass and fail in unchanged code. These tests can be detrimental to developers’ productivity. Particularly when tests run in continuous integration environments, the tests may be competing for access to limited computational resources (CPUs, memory etc.), and we hypothesize that resource (un)-availability may be a significant factor in the failure rate of flaky tests. We present the first assessment of the impact that computational resources have on flaky tests, including a total of 52 projects written in Java, JavaScript and Python, and 27 different resource configurations. Using a rigorous statistical methodology, we determine which tests are RAFTs (Resource-Affected Flaky Tests). We find that 46.5% of the flaky tests in our dataset are RAFTs, indicating that a substantial proportion of flaky-test failures happen depending on the resources available when running tests. We report RAFTs and configurations to avoid them to developers, and received interest to either fix the RAFTs or to improve the specifications of the projects so that tests would be run only in configurations that are unlikely to encounter RAFT failures. Although most test suites in our dataset are executed quite quickly (under one minute) in a baseline configuration, our results highlight the possibility of using this methodology to detect RAFT to reduce the cost of cloud infrastructure for reliably running larger test suites.

Published
2024
Full Text
View/download PDF

38. GENERIC DRUGS AND THE FUTURE OF 'SKINNY LABELS'.

Author

Bell, Jonathan A.

Subjects
Generic drugs -- Intellectual property -- Labeling -- Laws, regulations and rules, Patient package inserts -- Laws, regulations and rules, Patent licenses -- Laws, regulations and rules, GlaxoSmithKline L.L.C. v. Teva Pharmaceuticals USA, Inc. (7 F. 4th 1320 (Fed. Cir. 2021)), Government regulation, Drug Price Competition and Patent Term Restoration Act of 1984
Abstract

I. INTRODUCTION 660 II. PHARMACEUTICALS AND PATENT LAW 661 A. The Patent Bargain 661 B. The Hatch-Waxman Act's Dual Purposes 663 C. Skinny Labels 665 III. CARVEDILOL, THE PATENTS-IN-SUIT, AND [...]

Published
2022

39. Single-dose administration and the influence of the timing of the booster dose on immunogenicity and efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine: a pooled analysis of four randomised trials

Author

Aban, Marites, Abeyskera, Kushala W.M., Aboagye, Jeremy, Adam, Matthew, Adams, Kirsty, Adamson, James P., Adewatan, Gbadebo, Adlou, Syed, Ahmed, Khatija, Akhalwaya, Yasmeen, Akhalwaya, Saajida, Alcock, Andrew, Ali, Aabidah, Allen, Elizabeth R., Allen, Lauren, Alvernaz, Felipe B., Amorim, Fabio Santos, Andrade, Claudia Sala, Andritsou, Foteini, Anslow, Rachel, Arbe-Barnes, Edward H., Ariaans, Mark P., Arns, Beatriz, Arruda, Laiana, Assad, Luiza, Azi, Paula De Almeida, Azi, Lorena De Almeida, Babbage, Gavin, Bailey, Catherine, Baker, Kenneth F., Baker, Megan, Baker, Natalie, Baker, Philip, Baleanu, Ioana, Bandeira, Danieli, Bara, Anna, Barbosa, Marcella A.S., Barker, Debbie, Barlow, Gavin D., Barnes, Eleanor, Barr, Andrew S., Barrett, Jordan R., Barrett, Jessica, Barrett, Kelly, Bates, Louise, Batten, Alexander, Beadon, Kirsten, Beales, Emily, Beckley, Rebecca, Belij-Rammerstorfer, Sandra, Bell, Jonathan, Bellamy, Duncan, Belton, Sue, Berg, Adam, Bermejo, Laura, Berrie, Eleanor, Berry, Lisa, Berzenyi, Daniella, Beveridge, Amy, Bewley, Kevin R., Bharaj, Inderjeet, Bhikha, Sutika, Bhorat, Asad E., Bhorat, Zaheda E., Bijker, Else Margreet, Birch, Sarah, Birch, Gurpreet, Birchall, Kathryn, Bird, Adam, Bird, Olivia, Bisnauthsing, Karen, Bittaye, Mustapha, Blackwell, Luke, Blacow, Rachel, Bletchly, Heather, Blundell, Caitlin L., Blundell, Susannah R., Bodalia, Pritesh, Bolam, Emma, Boland, Elena, Bormans, Daan, Borthwick, Nicola, Bowring, Francesca, Boyd, Amy, Bradley, Penny, Brenner, Tanja, Bridges-Webb, Alice, Brown, Phillip, Brown, Claire, Brown-O'Sullivan, Charlie, Bruce, Scott, Brunt, Emily, Budd, William, Bulbulia, Yusuf A., Bull, Melanie, Burbage, Jamie, Burn, Aileen, Buttigieg, Karen R., Byard, Nicholas, Cabrera Puig, Ingrid, Calvert, Anna, Camara, Susana, Cao, Michelangelo, Cappuccini, Federica, Cardona, Rita, Cardoso, João R., Carr, Melanie, Carroll, Miles W., Carson-Stevens, Andrew, Carvalho, Yasmin de M., Casey, Helen R., Cashen, Paul, Castro, Thais R.Y., Castro, Lucia Carratala, Cathie, Katrina, Cavey, Ana, Cerbino-Neto, José, Cezar, Luiz Fernando F., Chadwick, Jim, Chanice, Chanice, Chapman, David, Charlton, Sue, Cheliotis, Katerina S., Chelysheva, Irina, Chester, Oliver, Chiplin, Emily, Chita, Sunder, Cho, Jee-Sun, Cifuentes, Liliana, Clark, Elizabeth, Clark, Matthew, Colin-Jones, Rachel, Collins, Sarah L.K., Colton, Hayley, Conlon, Christopher P., Connarty, Sean, Coombes, Naomi, Cooper, Cushla, Cooper, Rachel, Cornelissen, Lynne, Corrah, Tumena, Cosgrove, Catherine A., Costa, Fernanda Barroso, Cox, Tony, Crocker, Wendy E.M., Crosbie, Sarah, Cullen, Dan, Cunha, Debora R.M.F., Cunningham, Christina J., Cuthbertson, Fiona C., da Costa, Daniel Marinho, Da Guarda, Suzete N. Farias, da Silva, Larissa P., da Silva Moraes, Antonio Carlos, Damratoski, Brad E., Danos, Zsofia, Dantas, Maria T.D.C., Datoo, Mehreen S., Datta, Chandrabali, Davids, Malika, Davies, Sarah L., Davies, Kelly, Davies, Hannah, Davies, Sophie, Davies, Judith, Davis, Elizabeth J., Davis, John, de Carvalho, José A.M., De Jager, Jeanne, de Jesus Jnr, Sergio, De Oliveira Kalid, Lis Moreno, Dearlove, David, Demissie, Tesfaye, Desai, Amisha, Di Marco, Stefania, Di Maso, Claudio, Dinesh, Tanya, Docksey, Claire, Dong, Tao, Donnellan, Francesca R., Dos Santos, Tannyth Gomes, Dos Santos, Thainá G., Dos Santos, Erika Pachecho, Douglas, Naomi, Downing, Charlotte, Drake, Jonathan, Drake-Brockman, Rachael, Drury, Ruth, Du Plessis, Joan, Dunachie, Susanna J., Duncan, Andrew, Easom, Nicholas J.W., Edwards, Mandy, Edwards, Nick J., Edwards, Frances, El Muhanna, Omar M., Elias, Sean C., Ellison-Handley, Branwen, Elmore, Michael J., English, Marcus Rex, Esmail, Alisgair, Essack, Yakub Moosa, Farooq, Mutjaba, Fedosyuk, Sofiya, Felle, Sally, Ferguson, Susie, Ferreira Da Silva, Carla, Field, Samantha, Fisher, Richard, Fletcher, James, Fofie, Hazel, Fok, Henry, Ford, Karen J., Fothergill, Ross, Fowler, Jamie, Fraiman, Pedro H.A., Francis, Emma, Franco, Marilia M., Frater, John, Freire, Marilúcia S.M., Fry, Samantha H., Fudge, Sabrina, Furlan Filho, Renato, Furze, Julie, Fuskova, Michelle, Galian-Rubio, Pablo, Garlant, Harriet, Gavrila, Madita, Gibbons, Karyna A., Gilbride, Ciaran, Gill, Hardeep, Godwin, Kerry, Gokani, Karishma, Gonçalves, Maria Luisa Freire, Gonzalez, Isabela G.S., Goodall, Jack, Goodwin, Jayne, Goondiwala, Amina, Gordon-Quayle, Katherine, Gorini, Giacomo, Goyanna, Alvaro, Grab, Janet, Gracie, Lara, Green, Justin, Greenwood, Nicola, Greffrath, Johann, Groenewald, Marisa M., Gunawardene, Anishka, Gupta, Gaurav, Hackett, Mark, Hallis, Bassam, Hamaluba, Mainga, Hamilton, Elizabeth, Hamlyn, Joseph, Hammersley, Daniel, Hanrath, Aidan T., Hanumunthadu, Brama, Harris, Stephanie A., Harris, Clair, Harrison, Thomas D., Harrison, Daisy, Harris-Wright, Tara A., Hart, Thomas C., Hartnell, Birgit, Haughney, John, Hawkins, Sophia, Hayano, Laís Y.M., Head, Ian, Heath, Paul T., Henry, John Aaron, Hermosin Herrera, Macarena, Hettle, David B., Higa, Cristhiane, Hill, Jennifer, Hodges, Gina, Hodgson, Susanne, Horne, Elizea, Hou, Mimi M., Houlihan, Catherine F., Howe, Elizabeth, Howell, Nicola, Humphreys, Jonathan, Humphries, Holly E., Hurley, Katrina, Huson, Claire, Hyams, Catherine, Hyder-Wright, Angela, Ikram, Sabina, Ishwarbhai, Alka, Iveson, Poppy, Iyer, Vidyashankara, Jackson, Frederic, Jackson, Susan, Jaumdally, Shameem, Jeffers, Helen, Jesudason, Natasha, Jones, Carina, Jones, Christopher, Jones, Kathryn, Jones, Elizabeth, Jorge, Marianna Rocha, Joshi, Amar, Júnior, Eduardo A.M.S., Kailath, Reshma, Kana, Faeeza, Kar, Arnab, Karampatsas, Konstantinos, Kasanyinga, Mwila, Kay, Linda, Keen, Jade, Kellett Wright, Johanna, Kelly, Elizabeth J., Kelly, Debbie, Kelly, Dearbhla M., Kelly, Sarah, Kerr, David, Khan, Liaquat, Khozoee, Baktash, Khurana, Ankush, Kidd, Sarah, Killen, Annabel, Kinch, Jasmin, Kinch, Patrick, King, Lloyd D.W., King, Thomas B., Kingham, Lucy, Klenerman, Paul, Kluczna, Diana M., Knapper, Francesca, Knight, Julian C., Knott, Daniel, Koleva, Stanislava, Lages, Pedro M., Lang, Matilda, Lang, Gail, Larkworthy, Colin W., Larwood, Jessica P.J., Law, Rebecca, Lawrie, Alison M., Lazarus, Erica M., Leach, Amanda, Lees, Emily A., Lelliott, Alice, Lemm, Nana-Marie, Lessa, Alvaro Edson Ramos, Leung, Stephanie, Li, Yuanyuan, Lias, Amelia M., Liatsikos, Konstantinos, Linder, Aline, Lipworth, Samuel, Liu, Shuchang, Liu, Xinxue, Lloyd, Adam, Lloyd, Stephanie, Loew, Lisa, Lopez Ramon, Raquel, Lora, Leandro Bonecker, Luz, Kleber Giovanni, MacDonald, Jonathan C., MacGregor, Gordon, Madhavan, Meera, Mainwaring, David O., Makambwa, Edson, Makinson, Rebecca, Malahleha, Mookho, Malamatsho, Ross, Mallett, Garry, Manning, Nicola, Mansatta, Kushal, Maoko, Takalani, Marinou, Spyridoula, Marlow, Emma, Marques, Gabriela N., Marriott, Paula, Marshall, Richard P., Marshall, Julia L., Masenya, Masebole, Masilela, Mduduzi, Masters, Shauna K., Mathew, Moncy, Matlebjane, Hosea, Matshidiso, Kedidimetse, Mazur, Olga, Mazzella, Andrea, McCaughan, Hugh, McEwan, Joanne, McGlashan, Joanna, McInroy, Lorna, McRobert, Nicky, McSwiggan, Steve, Megson, Clare, Mehdipour, Savviz, Meijs, Wilma, Mendonça, Renata N.Õ., Mentzer, Alexander J., Mesquita, Ana Carolina F., Miralhes, Patricia, Mirtorabi, Neginsadat, Mitton, Celia, Mnyakeni, Sibusiso, Moghaddas, Fiona, Molapo, Kgaogelo, Moloi, Mapule, Moore, Maria, Moran, Marni, Morey, Ella, Morgans, Róisín, Morris, Susan J., Morris, Sheila, Morrison, Hazel, Morselli, Franca, Morshead, Gertraud, Morter, Richard, Mottay, Lynelle, Moultrie, Andrew, Moyo, Nathifa, Mpelembue, Mushiya, Msomi, Sibekezelo, Mugodi, Yvonne, Mukhopadhyay, Ekta, Muller, Jilly, Munro, Alasdair, Murphy, Sarah, Mweu, Philomena, Myerscough, Christopher, Naik, Gurudutt, Naker, Kush, Nastouli, Eleni, Ndlovu, Bongani, Nikolaou, Elissavet, Njenga, Cecilia, Noal, Helena C., Noé, Andrés, Novaes, Gabrielle, Nugent, Fay L., Nunes, Géssika Lanzillo A., O'Brien, Katie, O'Connor, Daniel, Oelofse, Suzette, Oguti, Blanche, Olchawski, Victoria, Oldfield, Neil J., Oliveira, Marianne G., Oliveira, Catarina, Oliveira, Isabelle Silva Queiroz, Oommen-Jose, Aylin, Oosthuizen, Angela, O'Reilly, Paula, O'Reilly, Peter J., Osborne, Piper, Owen, David R.J., Owen, Lydia, Owens, Daniel, Owino, Nelly, Pacurar, Mihaela, Paiva, Brenda V.B., Palhares, Edna M.F., Palmer, Susan, Parracho, Helena M. R.T., Parsons, Karen, Patel, Dipak, Patel, Bhumika, Patel, Faeezah, Patrick-Smith, Maia, Payne, Ruth O., Peng, Yanchun, Penn, Elizabeth J., Pennington, Anna, Peralta Alvarez, Marco Polo, Pereira Stuchi, Bruno Pereira, Perez, Ana Luiza, Perinpanathan, Tanaraj, Perring, James, Perumal, Rubeshan, Petkar, Sahir Yusuf, Philip, Tricia, Phillips, Jennifer, Phohu, Mary Kgomotso, Pickup, Lorinda, Pieterse, Sonja, Pinheiro, Jessica Morgana, Piper, Jo, Pipini, Dimitra, Plank, Mary, Plant, Sinéad, Pollard, Samuel, Pooley, Jennifer, Pooran, Anil, Poulton, Ian, Powers, Claire, Presa, Fernando B., Price, David A., Price, Vivien, Primeira, Marcelo R., Proud, Pamela C., Provstgaard-Morys, Samuel, Pueschel, Sophie, Pulido, David, Quaid, Sheena, Rabara, Ria, Radia, Kajal, Rajapaska, Durga, Rajeswaran, Thurkka, Ramos, Leonardo, Ramos, Alberto San Francisco, Ramos Lopez, Fernando, Rampling, Tommy, Rand, Jade, Ratcliffe, Helen, Rawlinson, Tom, Rea, David, Rees, Byron, Resuello-Dauti, Mila, Reyes Pabon, Emilia, Rhead, Sarah, Riaz, Tawassal, Ricamara, Marivic, Richards, Alexander, Richter, Alex, Ritchie, Neil, Ritchie, Adam J., Robbins, Alexander J., Roberts, Hannah, Robinson, Ryan E., Roche, Sophie, Rollier, Christine, Rose, Louisa, Ross Russell, Amy L., Rossouw, Lindie, Royal, Simon, Rudiansyah, Indra, Ryalls, Kim, Sabine, Charlotte, Saich, Stephen, Sale, Jessica C., Salman, Ahmed M., Salvador, Natalia, Salvador, Stephannie, Sampaio, Milla Dias, Samson, Annette D., Sanchez-Gonzalez, Amada, Sanders, Helen, Sanders, Katherine, Santos, Erika, Santos Guerra, Mayara F.S., Satti, Iman, Saunders, Jack E., Saunders, Caroline, Sayed, Aakifah Bibi Arif, Schim van der Loeff, Ina, Schmid, Annina B., Schofield, Ella, Screaton, Gavin R., Seddiqi, Samiullah, Segireddy, Rameswara R., Senger, Roberta, Serrano, Sonia, Shaik, Imam, Sharpe, Hannah R., Sharrocks, Katherine, Shaw, Robert, Shea, Adam, Sheehan, Emma, Shepherd, Amy, Shiham, Farah, Silk, Sarah E., Silva-Reyes, Laura, Silveira, Lidiana B. T.D., Silveira, Mariana B.V., Singh, Nisha, Sinha, Jaisi, Skelly, Donal T., Smith, Daniel C., Smith, Nick, Smith, Holly E., Smith, David J., Smith, Catherine C., Soares, Airanuédida S., Solórzano, Carla, Sorio, Guilherme L., Sorley, Kim, Sosa-Rodriguez, Tiffany, Souza, Cinthia M.C.D.L., Souza, Bruno S.D.F., Souza, Alessandra R., Souza Lopez, Thamyres, Sowole, Luciana, Spencer, Alexandra J., Spoors, Louise, Stafford, Lizzie, Stamford, Imogen, Stein, Ricardo, Stockdale, Lisa, Stockwell, Lisa V., Strickland, Louise H., Stuart, Arabella, Sturdy, Ann, Sutton, Natalina, Szigeti, Anna, Tahiri-Alaoui, Abdessamad, Tanner, Rachel, Taoushanis, Carol, Tarr, Alexander W., Tarrant, Richard, Taylor, Keja, Taylor, Ursula, Taylor, Iona Jennifer, Taylor, Justin, te Water Naude, Rebecca, Templeton, Kate, Themistocleous, Yrene, Themistocleous, Andreas, Thomas, Merin, Thomas, Kelly, Thomas, Tonia M., Thombrayil, Asha, Thompson, Julia, Thompson, Fawziyah, Thompson, Ameeka, Thompson, Amber, Thompson, Kevin, Thornton-Jones, Viv, Thotusi, Larissa H.S., Tighe, Patrick J., Tinoco, Lygia Accioly, Tiongson, Gerlynn Ferreras, Tladinyane, Bonolo, Tomasicchio, Michele, Tomic, Adriana, Tonks, Susan, Towner, James, Tran, Nguyen, Tree, Julia A., Trillana, Gerry, Trinham, Charlotte, Trivett, Rose, Truby, Adam, Tsheko, Betty Lebogang, Tubb, Philippa, Turabi, Aadil, Turner, Richard, Turner, Cheryl, Turner, Nicola, Tyagi, Bhavya, Ulaszewska, Marta, Underwood, Benjamin R., van Eck, Samual, Varughese, Rachel, Verbart, Dennis, Verheul, Marije K., Vichos, Iason, Vieira, Taiane A., Walker, Gemma, Walker, Laura, Wand, Matthew E., Wardell, Theresa, Warimwe, George M., Warren, Sarah C., Watkins, Bridget, Watson, Marion E.E., Watson, Ekaterina, Webb, Stewart, Webster, Angela, Welch, Jessica, Wellbelove, Zoe, Wells, Jeanette H., West, Alison J., White, Beth, White, Caroline, White, Rachel, Williams, Paul, Williams, Rachel L., Willingham, Silvia, Winslow, Rebecca, Woods, Danielle, Woodyer, Mark, Worth, Andrew T., Wright, Danny, Wroblewska, Marzena, Yao, Andy, Yim, Yee Ting Nicole, Zambrano, Marina Bauer, Zimmer, Rafael Leal, Zizi, Dalila, Zuidewind, Peter, Voysey, Merryn, Costa Clemens, Sue Ann, Madhi, Shabir A, Weckx, Lily Y, Folegatti, Pedro M, Aley, Parvinder K, Angus, Brian, Baillie, Vicky L, Barnabas, Shaun L, Bhorat, Qasim E, Bibi, Sagida, Briner, Carmen, Cicconi, Paola, Clutterbuck, Elizabeth A, Collins, Andrea M, Cutland, Clare L, Darton, Thomas C, Dheda, Keertan, Dold, Christina, Duncan, Christopher J A, Emary, Katherine R W, Ewer, Katie J, Flaxman, Amy, Fairlie, Lee, Faust, Saul N, Feng, Shuo, Ferreira, Daniela M, Finn, Adam, Galiza, Eva, Goodman, Anna L, Green, Catherine M, Green, Christopher A, Greenland, Melanie, Hill, Catherine, Hill, Helen C, Hirsch, Ian, Izu, Alane, Jenkin, Daniel, Joe, Carina C D, Kerridge, Simon, Koen, Anthonet, Kwatra, Gaurav, Lazarus, Rajeka, Libri, Vincenzo, Lillie, Patrick J, Marchevsky, Natalie G, Marshall, Richard P, Mendes, Ana V A, Milan, Eveline P, Minassian, Angela M, McGregor, Alastair, Mujadidi, Yama F, Nana, Anusha, Padayachee, Sherman D, Phillips, Daniel J, Pittella, Ana, Plested, Emma, Pollock, Katrina M, Ramasamy, Maheshi N, Ritchie, Adam J, Robinson, Hannah, Schwarzbold, Alexandre V, Smith, Andrew, Song, Rinn, Snape, Matthew D, Sprinz, Eduardo, Sutherland, Rebecca K, Thomson, Emma C, Török, M Estée, Toshner, Mark, Turner, David P J, Vekemans, Johan, Villafana, Tonya L, White, Thomas, Williams, Christopher J, Douglas, Alexander D, Hill, Adrian V S, Lambe, Teresa, Gilbert, Sarah C, and Pollard, Andrew J

Published
2021
Full Text
View/download PDF

40. Cross-Chemotaxis System Derived from an Atherosclerotic Plaque Model

Author

Bell, Jonathan and Biswas, Animikh

Subjects
Mathematics - Analysis of PDEs, 35Q92, 35K40, 35A01, 92C17
Abstract

In modeling the inflammatory response to a lesion in an artery wall, there are a number of chemotactic mechanisms going on within the wall layer that lead to an arterial plaque. We introduce a rather reduced model of these dynamic processes, but the focus of this paper is a subsystem of the full model system that has independent interest. Namely, the system here consists of two cell densities, each producing a chemical that is a chemoattractant for the other cell type. Then we prove positivity, local and global existence, and discuss some qualitative behavior of solutions.

Published
2015

41. Teaching Social Studies amid Ecological Crisis

Author

Kissling, Mark T. and Bell, Jonathan T.

Abstract

We live in ecological crisis. While understanding the human-made crisis requires scientific expertise, addressing it requires active, informed citizens. Thus, the crisis is a matter for the field of social studies education, the subject area foremost tasked with teaching students to become effective citizens of their many communities. However, environmental issues (EI) have been marginal in the highly anthropocentric field. Through an online survey, this study investigated public-school secondary social studies teaching in the U.S. state of Pennsylvania at a time when powerful political forces have downplayed or refuted the ecological crisis. A strong majority of 1,174 responding teachers believed that it is important for social studies teachers to teach EI yet most did not teach EI often in the 2017-8 school year on account of four main barriers: perception that EI are more the domain of science than social studies; lack of comfort, preparation, and knowledge for teaching EI; political controversy surrounding EI; and already-crowded, non-EI-focused social studies curricula. Despite these barriers, there are encouraging signs for teachers teaching "earthen social studies" and addressing the crisis--but the field must support it.

Published
2020
Full Text
View/download PDF

42. Safety and efficacy of the ChAdOx1 nCoV-19 vaccine (AZD1222) against SARS-CoV-2: an interim analysis of four randomised controlled trials in Brazil, South Africa, and the UK

Author

Aban, Marites, Abayomi, Fatola, Abeyskera, Kushala, Aboagye, Jeremy, Adam, Matthew, Adams, Kirsty, Adamson, James, Adelaja, Yemi A., Adewetan, Gbadebo, Adlou, Syed, Ahmed, Khatija, Akhalwaya, Yasmeen, Akhalwaya, Saajida, Alcock, Andrew, Ali, Aabidah, Allen, Elizabeth R., Allen, Lauren, Almeida, Thamires C. D. S. C, Alves, Mariana P.S., Amorim, Fabio, Andritsou, Foteini, Anslow, Rachel, Appleby, Matthew, Arbe-Barnes, Edward H., Ariaans, Mark P., Arns, Beatriz, Arruda, Laiana, Azi, Paula, Azi, Lorena, Babbage, Gavin, Bailey, Catherine, Baker, Kenneth F., Baker, Megan, Baker, Natalie, Baker, Philip, Baldwin, Lisa, Baleanu, Ioana, Bandeira, Danieli, Bara, Anna, Barbosa, Marcella A.S., Barker, Debbie, Barlow, Gavin D., Barnes, Eleanor, Barr, Andrew S., Barrett, Jordan R., Barrett, Jessica, Bates, Louise, Batten, Alexander, Beadon, Kirsten, Beales, Emily, Beckley, Rebecca, Belij-Rammerstorfer, Sandra, Bell, Jonathan, Bellamy, Duncan, Bellei, Nancy, Belton, Sue, Berg, Adam, Bermejo, Laura, Berrie, Eleanor, Berry, Lisa, Berzenyi, Daniella, Beveridge, Amy, Bewley, Kevin R., Bexhell, Helen, Bhikha, Sutika, Bhorat, Asad E., Bhorat, Zaheda E., Bijker, Else, Birch, Geeta, Birch, Sarah, Bird, Adam, Bird, Olivia, Bisnauthsing, Karen, Bittaye, Mustapha, Blackstone, Katherine, Blackwell, Luke, Bletchly, Heather, Blundell, Caitlin L., Blundell, Susannah R., Bodalia, Pritesh, Boettger, Bruno C., Bolam, Emma, Boland, Elena, Bormans, Daan, Borthwick, Nicola, Bowring, Francesca, Boyd, Amy, Bradley, Penny, Brenner, Tanja, Brown, Phillip, Brown, Claire, Brown-O'Sullivan, Charlie, Bruce, Scott, Brunt, Emily, Buchan, Ruaridh, Budd, William, Bulbulia, Yusuf A., Bull, Melanie, Burbage, Jamie, Burhan, Hassan, Burn, Aileen, Buttigieg, Karen R., Byard, Nicholas, Cabera Puig, Ingrid, Calderon, Gloria, Calvert, Anna, Camara, Susana, Cao, Michelangelo, Cappuccini, Federica, Cardoso, João R., Carr, Melanie, Carroll, Miles W., Carson-Stevens, Andrew, Carvalho, Yasmin de M., Carvalho, José A.M., Casey, Helen R., Cashen, Paul, Castro, Thais, Castro, Lucia Carratala, Cathie, Katrina, Cavey, Ana, Cerbino-Neto, José, Chadwick, Jim, Chapman, David, Charlton, Sue, Chelysheva, Irina, Chester, Oliver, Chita, Sunder, Cho, Jee-Sun, Cifuentes, Liliana, Clark, Elizabeth, Clark, Matthew, Clarke, Andrea, Clutterbuck, Elizabeth A., Collins, Sarah L.K., Conlon, Christopher P., Connarty, Sean, Coombes, Naomi, Cooper, Cushla, Cooper, Rachel, Cornelissen, Lynne, Corrah, Tumena, Cosgrove, Catherine, Cox, Tony, Crocker, Wendy E.M., Crosbie, Sarah, Cullen, Lorraine, Cullen, Dan, Cunha, Debora R.M.F., Cunningham, Christina, Cuthbertson, Fiona C., Da Guarda, Suzete N. Farias, da Silva, Larissa P., Damratoski, Brad E., Danos, Zsofia, Dantas, Maria T.D.C., Darroch, Paula, Datoo, Mehreen S., Datta, Chandrabali, Davids, Malika, Davies, Sarah L., Davies, Hannah, Davis, Elizabeth, Davis, Judith, Davis, John, De Nobrega, Maristela M.D., De Oliveira Kalid, Lis Moreno, Dearlove, David, Demissie, Tesfaye, Desai, Amisha, Di Marco, Stefania, Di Maso, Claudio, Dinelli, Maria I.S., Dinesh, Tanya, Docksey, Claire, Dold, Christina, Dong, Tao, Donnellan, Francesca R., Dos Santos, Tannyth, dos Santos, Thainá G., Dos Santos, Erika Pachecho, Douglas, Naomi, Downing, Charlotte, Drake, Jonathan, Drake-Brockman, Rachael, Driver, Kimberley, Drury, Ruth, Dunachie, Susanna J., Durham, Benjamin S., Dutra, Lidiana, Easom, Nicholas J.W., van Eck, Samual, Edwards, Mandy, Edwards, Nick J., El Muhanna, Omar M., Elias, Sean C., Elmore, Mike, English, Marcus, Esmail, Alisgair, Essack, Yakub Moosa, Farmer, Eoghan, Farooq, Mutjaba, Farrar, Madi, Farrugia, Leonard, Faulkner, Beverley, Fedosyuk, Sofiya, Felle, Sally, Feng, Shuo, Ferreira Da Silva, Carla, Field, Samantha, Fisher, Richard, Flaxman, Amy, Fletcher, James, Fofie, Hazel, Fok, Henry, Ford, Karen J., Fowler, Jamie, Fraiman, Pedro H.A., Francis, Emma, Franco, Marilia M., Frater, John, Freire, Marilúcia S.M., Fry, Samantha H., Fudge, Sabrina, Furze, Julie, Fuskova, Michelle, Galian-Rubio, Pablo, Galiza, Eva, Garlant, Harriet, Gavrila, Madita, Geddes, Ailsa, Gibbons, Karyna A., Gilbride, Ciaran, Gill, Hardeep, Glynn, Sharon, Godwin, Kerry, Gokani, Karishma, Goldoni, Ursula Carvalho, Goncalves, Maria, Gonzalez, Isabela G.S., Goodwin, Jayne, Goondiwala, Amina, Gordon-Quayle, Katherine, Gorini, Giacomo, Grab, Janet, Gracie, Lara, Greenland, Melanie, Greenwood, Nicola, Greffrath, Johann, Groenewald, Marisa M., Grossi, Leonardo, Gupta, Gaurav, Hackett, Mark, Hallis, Bassam, Hamaluba, Mainga, Hamilton, Elizabeth, Hamlyn, Joseph, Hammersley, Daniel, Hanrath, Aidan T., Hanumunthadu, Brama, Harris, Stephanie A., Harris, Clair, Harris, Tara, Harrison, Thomas D., Harrison, Daisy, Hart, Thomas C., Hartnell, Birgit, Hassan, Shadin, Haughney, John, Hawkins, Sophia, Hay, Jodie, Head, Ian, Henry, John, Hermosin Herrera, Macarena, Hettle, David B., Hill, Jennifer, Hodges, Gina, Horne, Elizea, Hou, Mimi M., Houlihan, Catherine, Howe, Elizabeth, Howell, Nicola, Humphreys, Jonathan, Humphries, Holly E., Hurley, Katrina, Huson, Claire, Hyder-Wright, Angela, Hyams, Catherine, Ikram, Sabina, Ishwarbhai, Alka, Ivan, Monica, Iveson, Poppy, Iyer, Vidyashankara, Jackson, Frederic, De Jager, Jeanne, Jaumdally, Shameem, Jeffers, Helen, Jesudason, Natasha, Jones, Bryony, Jones, Kathryn, Jones, Elizabeth, Jones, Christopher, Jorge, Marianna Rocha, Jose, Aylin, Joshi, Amar, Júnior, Eduardo A.M.S., Kadziola, Joanne, Kailath, Reshma, Kana, Faeeza, Karampatsas, Konstantinos, Kasanyinga, Mwila, Keen, Jade, Kelly, Elizabeth J., Kelly, Dearbhla M., Kelly, Debbie, Kelly, Sarah, Kerr, David, Kfouri, Renato de Ávila, Khan, Liaquat, Khozoee, Baktash, Kidd, Sarah, Killen, Annabel, Kinch, Jasmin, Kinch, Patrick, King, Lloyd D.W., King, Thomas B., Kingham, Lucy, Klenerman, Paul, Knapper, Francesca, Knight, Julian C., Knott, Daniel, Koleva, Stanislava, Lang, Matilda, Lang, Gail, Larkworthy, Colin W., Larwood, Jessica P.J., Law, Rebecca, Lazarus, Erica M., Leach, Amanda, Lees, Emily A., Lemm, Nana-Marie, Lessa, Alvaro, Leung, Stephanie, Li, Yuanyuan, Lias, Amelia M., Liatsikos, Kostas, Linder, Aline, Lipworth, Samuel, Liu, Shuchang, Liu, Xinxue, Lloyd, Adam, Lloyd, Stephanie, Loew, Lisa, Lopez Ramon, Raquel, Lora, Leandro, Lowthorpe, Vicki, Luz, Kleber, MacDonald, Jonathan C., MacGregor, Gordon, Madhavan, Meera, Mainwaring, David O., Makambwa, Edson, Makinson, Rebecca, Malahleha, Mookho, Malamatsho, Ross, Mallett, Garry, Mansatta, Kushal, Maoko, Takalani, Mapetla, Katlego, Marchevsky, Natalie G., Marinou, Spyridoula, Marlow, Emma, Marques, Gabriela N., Marriott, Paula, Marshall, Richard P., Marshall, Julia L., Martins, Flávia J., Masenya, Masebole, Masilela, Mduduzi, Masters, Shauna K., Mathew, Moncy, Matlebjane, Hosea, Matshidiso, Kedidimetse, Mazur, Olga, Mazzella, Andrea, McCaughan, Hugh, McEwan, Joanne, McGlashan, Joanna, McInroy, Lorna, McIntyre, Zoe, McLenaghan, Daniela, McRobert, Nicky, McSwiggan, Steve, Megson, Clare, Mehdipour, Savviz, Meijs, Wilma, Mendonça, Renata N.Á., Mentzer, Alexander J., Mirtorabi, Neginsadat, Mitton, Celia, Mnyakeni, Sibusiso, Moghaddas, Fiona, Molapo, Kgaogelo, Moloi, Mapule, Moore, Maria, Moraes-Pinto, M. Isabel, Moran, Marni, Morey, Ella, Morgans, Róisín, Morris, Susan, Morris, Sheila, Morris, Helen C., Morselli, Franca, Morshead, Gertraud, Morter, Richard, Mottal, Lynelle, Moultrie, Andrew, Moya, Nathifa, Mpelembue, Mushiya, Msomi, Sibekezelo, Mugodi, Yvonne, Mukhopadhyay, Ekta, Muller, Jilly, Munro, Alasdair, Munro, Claire, Murphy, Sarah, Mweu, Philomena, Myasaki, Celia Hatsuko, Naik, Gurudutt, Naker, Kush, Nastouli, Eleni, Nazir, Abida, Ndlovu, Bongani, Neffa, Fabio, Njenga, Cecilia, Noal, Helena, Noé, Andrés, Novaes, Gabrielle, Nugent, Fay L., Nunes, Géssika, O'Brien, Katie, O'Connor, Daniel, Odam, Miranda, Oelofse, Suzette, Oguti, Blanche, Olchawski, Victoria, Oldfield, Neil J., Oliveira, Marianne G., Oliveira, Catarina, Oosthuizen, Angela, O'Reilly, Paula, Osborne, Piper, Owen, David R.J., Owen, Lydia, Owens, Daniel, Owino, Nelly, Pacurar, Mihaela, Paiva, Brenda V.B., Palhares, Edna M.F., Palmer, Susan, Parkinson, Sivapriyai, Parracho, Helena M.R.T., Parsons, Karen, Patel, Dipak, Patel, Bhumika, Patel, Faeezah, Patel, Kelly, Patrick-Smith, Maia, Payne, Ruth O., Peng, Yanchun, Penn, Elizabeth J., Pennington, Anna, Peralta Alvarez, Marco Polo, Perring, James, Perry, Nicola, Perumal, Rubeshan, Petkar, Sahir, Philip, Tricia, Phillips, Daniel J., Phillips, Jennifer, Phohu, Mary Kgomotso, Pickup, Lorinda, Pieterse, Sonja, Piper, Jo, Pipini, Dimitra, Plank, Mary, Du Plessis, Joan, Pollard, Samuel, Pooley, Jennifer, Pooran, Anil, Poulton, Ian, Powers, Claire, Presa, Fernando B., Price, David A., Price, Vivien, Primeira, Marcelo, Proud, Pamela C., Provstgaard-Morys, Samuel, Pueschel, Sophie, Pulido, David, Quaid, Sheena, Rabara, Ria, Radford, Alexandra, Radia, Kajal, Rajapaska, Durga, Rajeswaran, Thurkka, Ramos, Alberto San Francisco, Ramos Lopez, Fernando, Rampling, Tommy, Rand, Jade, Ratcliffe, Helen, Rawlinson, Tom, Rea, David, Rees, Byron, Reiné, Jesús, Resuello-Dauti, Mila, Reyes Pabon, Emilia, Ribiero, Carla M., Ricamara, Marivic, Richter, Alex, Ritchie, Neil, Ritchie, Adam J., Robbins, Alexander J., Roberts, Hannah, Robinson, Ryan E., Robinson, Hannah, Rocchetti, Talita T., Rocha, Beatriz Pinho, Roche, Sophie, Rollier, Christine, Rose, Louisa, Ross Russell, Amy L., Rossouw, Lindie, Royal, Simon, Rudiansyah, Indra, Ruiz, Sarah, Saich, Stephen, Sala, Claudia, Sale, Jessica, Salman, Ahmed M., Salvador, Natalia, Salvador, Stephannie, Sampaio, Milla, Samson, Annette D., Sanchez-Gonzalez, Amada, Sanders, Helen, Sanders, Katherine, Santos, Erika, Santos Guerra, Mayara F.S., Satti, Iman, Saunders, Jack E., Saunders, Caroline, Sayed, Aakifah, Schim van der Loeff, Ina, Schmid, Annina B., Schofield, Ella, Screaton, Gavin, Seddiqi, Samiullah, Segireddy, Rameswara R., Senger, Roberta, Serrano, Sonia, Shah, Rajiv, Shaik, Imam, Sharpe, Hannah E., Sharrocks, Katherine, Shaw, Robert, Shea, Adam, Shepherd, Amy, Shepherd, James G., Shiham, Farah, Sidhom, Emad, Silk, Sarah E., da Silva Moraes, Antonio Carlos, Silva-Junior, Gilberto, Silva-Reyes, Laura, Silveira, Anderson D., Silveira, Mariana B.V., Sinha, Jaisi, Skelly, Donal T., Smith, Daniel C., Smith, Nick, Smith, Holly E., Smith, David J., Smith, Catherine C., Soares, Airanuédida, Soares, Tiago, Solórzano, Carla, Sorio, Guilherme L., Sorley, Kim, Sosa-Rodriguez, Tiffany, Souza, Cinthia M.C.D.L., Souza, Bruno S.D.F., Souza, Alessandra R., Spencer, Alexandra J., Spina, Fernanda, Spoors, Louise, Stafford, Lizzie, Stamford, Imogen, Starinskij, Igor, Stein, Ricardo, Steven, Jill, Stockdale, Lisa, Stockwell, Lisa V., Strickland, Louise H., Stuart, Arabella C., Sturdy, Ann, Sutton, Natalina, Szigeti, Anna, Tahiri-Alaoui, Abdessamad, Tanner, Rachel, Taoushanis, Carol, Tarr, Alexander W., Taylor, Keja, Taylor, Ursula, Taylor, Iona Jennifer, Taylor, Justin, te Water Naude, Rebecca, Themistocleous, Yrene, Themistocleous, Andreas, Thomas, Merin, Thomas, Kelly, Thomas, Tonia M., Thombrayil, Asha, Thompson, Fawziyah, Thompson, Amber, Thompson, Kevin, Thompson, Ameeka, Thomson, Julia, Thornton-Jones, Viv, Tighe, Patrick J., Tinoco, Lygia Accioly, Tiongson, Gerlynn, Tladinyane, Bonolo, Tomasicchio, Michele, Tomic, Adriana, Tonks, Susan, Towner, James, Tran, Nguyen, Tree, Julia, Trillana, Gerry, Trinham, Charlotte, Trivett, Rose, Truby, Adam, Tsheko, Betty Lebogang, Turabi, Aadil, Turner, Richard, Turner, Cheryl, Ulaszewska, Marta, Underwood, Benjamin R., Varughese, Rachel, Verbart, Dennis, Verheul, Marije, Vichos, Iason, Vieira, Taiane, Waddington, Claire S., Walker, Laura, Wallis, Erica, Wand, Matthew, Warbick, Deborah, Wardell, Theresa, Warimwe, George, Warren, Sarah C., Watkins, Bridget, Watson, Ekaterina, Webb, Stewart, Webb-Bridges, Alice, Webster, Angela, Welch, Jessica, Wells, Jeanette, West, Alison, White, Caroline, White, Rachel, Williams, Paul, Williams, Rachel L., Winslow, Rebecca, Woodyer, Mark, Worth, Andrew T., Wright, Danny, Wroblewska, Marzena, Yao, Andy, Zimmer, Rafael, Zizi, Dalila, Zuidewind, Peter, Voysey, Merryn, Clemens, Sue Ann Costa, Madhi, Shabir A, Weckx, Lily Y, Folegatti, Pedro M, Aley, Parvinder K, Angus, Brian, Baillie, Vicky L, Barnabas, Shaun L, Bhorat, Qasim E, Bibi, Sagida, Briner, Carmen, Cicconi, Paola, Collins, Andrea M, Colin-Jones, Rachel, Cutland, Clare L, Darton, Thomas C, Dheda, Keertan, Duncan, Christopher J A, Emary, Katherine R W, Ewer, Katie J, Fairlie, Lee, Faust, Saul N, Ferreira, Daniela M, Finn, Adam, Goodman, Anna L, Green, Catherine M, Green, Christopher A, Heath, Paul T, Hill, Catherine, Hill, Helen, Hirsch, Ian, Hodgson, Susanne H C, Izu, Alane, Jackson, Susan, Jenkin, Daniel, Joe, Carina C D, Kerridge, Simon, Koen, Anthonet, Kwatra, Gaurav, Lazarus, Rajeka, Lawrie, Alison M, Lelliott, Alice, Libri, Vincenzo, Lillie, Patrick J, Mallory, Raburn, Mendes, Ana V A, Milan, Eveline P, Minassian, Angela M, McGregor, Alastair, Morrison, Hazel, Mujadidi, Yama F, Nana, Anusha, O’Reilly, Peter J, Padayachee, Sherman D, Pittella, Ana, Plested, Emma, Pollock, Katrina M, Ramasamy, Maheshi N, Rhead, Sarah, Schwarzbold, Alexandre V, Singh, Nisha, Smith, Andrew, Song, Rinn, Snape, Matthew D, Sprinz, Eduardo, Sutherland, Rebecca K, Tarrant, Richard, Thomson, Emma C, Török, M Estée, Toshner, Mark, Turner, David P J, Vekemans, Johan, Villafana, Tonya L, Watson, Marion E E, Williams, Christopher J, Douglas, Alexander D, Hill, Adrian V S, Lambe, Teresa, Gilbert, Sarah C, and Pollard, Andrew J

Published
2021
Full Text
View/download PDF

46. Audio-scores : a resource for composition and computer-aided performance

Author

Bell, Jonathan

Subjects
781.3, M Music
Abstract

This submission investigates computer-aided performances in which musicians receive auditory information via earphones. The interaction between audio-scores (musical material sent through earpieces to performers) and visual input (musical notation) changes the traditional relationship between composer, conductor, performer and listener. Audio-scores intend to complement and transform the printed score. They enhance the accuracy of execution of difficult rhythmic or pitch relationships, increase the specificity of instructions given to the performer (for example, in the domain of timbre), and may elicit original and spontaneous responses from the performer in real-time. The present research is inspired by, and positions itself within traditional European notational practices. Through a reflection on the nature and function of notation in a variety of repertoires, this study examines how my own compositional research – and its reliance on audio-scores— relates to and differs from the models considered. Following the realisation of pieces investigating complex rhythms and the use of recorded samples as borrowed/found material, results have proven to be highly effective with a group of vocalists, with works in which audio-scores facilitated the precise realisation of microtonal material. Audio-scores also proved particularly useful in sitespecific ‘immersive’ concerts/installations. In these settings, audio-scores mitigate challenges associated with placing musicians at an unusual distances from one another, e.g. around the audience. This submission constitutes an original contribution to knowledge in the field of computer-aided performance in that it demonstrates how musical notation and current ubiquitous audio technologies may be used in tandem in the conception and performance of new works. Recent findings include a Web application currently being developed at IRCAM. The application is based on a local server and allows the synchronous delivery of audio/screen-scores via the browser of the performers’ smartphones, tablets, or computers. Keywords: audio-score, click track, composition, computeraided performance, earpiece, microtonality, music, notation, performance, screen-score, server, voice.

Published
2016

47. Utah State Budget Report, FY 2016

Author

Robinson, Jennifer, Bell, Jonathan, and Samuelsen, Tucker

Subjects
Budget, State Politics, Utah
Abstract

Utah political observers thought in the 2015 legislative session legislators addressed somemajor issues, while leaving some, including Medicaid expansion and the relocation of the stateprison, to be handled later. The 2015 legislature did address several significant public policy issuesthat will have long-term impacts. Two tax increases passed, an increase in the fuel tax andan increase in property taxes with the goal of reducing disparities in education funding across thestate.Lawmakers focused heavily on criminal justice reform, passing legislation that significantlyimpacts policy. Relocation of the state prison was also discussed at length, though ultimately legislatorsopted to hold off on a final decision. The Prison Relocation Commission tackled the issueduring the year. A final policy issue that will catch the attention of those living outside thestate is the passage of the LGBT nondiscrimination law.

Published
2016

49. Thick Description as Pedagogical Tool: Considering Bowers' Inspiration for Our Work

Author

Bell, Jonathan T. and Kissling, Mark T.

Abstract

This article begins with deep appreciation of Chet Bowers' powerful charge to take up thick description as a pedagogical tool, while also acknowledging the unpleasant manner in which he offered this charge in response to Gruenewald's notion of a critical pedagogy of place. The article, then, prompted by Bowers' charge, is a story and analysis of our 'rush of descriptions' about a controversial issue in the community where we reside. To better understand how thick description might contribute to EcoJustice pedagogy we present excerpts of our rush of descriptions and analyze them using Bowers' 5 themes of language, commodification, tradition, science, and technology. In doing so, we found that our in-depth examination does, indeed, make apparent these themes, suggesting thick description could be a promising component of EcoJustice pedagogy.

Published
2019
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results