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1. Thermodynamics and transport in molten chloride salts and their mixtures

Author

Cockrell, Cillian, Withington, Margaret-Ann, Devereux, Harvey L., Elena, Alin M., Todorov, Ilian T., Liu, Zi-Kui, Shang, Shun-Li, McCloy, James S., Bingham, Paul A., and Trachenko, Kostya

Subjects
Physics - Chemical Physics, Condensed Matter - Statistical Mechanics
Abstract

Molten salts are important in a number of energy applications, but the fundamental mechanisms operating in ionic liquids are poorly understood, particularly at higher temperatures. This is despite their candidacy for deployment in solar cells, next-generation nuclear reactors, and nuclear pyroprocessing. We perform extensive molecular dynamics simulations over a variety of molten chloride salt compositions at varying temperature and pressures to calculate the thermodynamic and transport properties of these liquids. Using recent developments in the theory of liquid thermophysical properties, we interpret our results on the basis of collective atomistic dynamics (phonons). We find that the properties of ionic liquids well explained by their collective dynamics, as in simple liquids. In particular, we relate the decrease of heat capacity, viscosity, and thermal conductivity to the loss of transverse phonons from the liquid spectrum. We observe the singular dependence of the isochoric heat capacity on the mean free path of phonons, and the obeyance of the Stokes-Einstein equation relating the viscosity to the mass diffusion. The transport properties of mixtures are more complicated compared to simple liquids, however viscosity and thermal conductivity are well guided by fundamental bounds proposed recently. The kinematic viscosity and thermal diffusivity lie very close to one another and obey the theoretical fundamental bounds determined solely by fundamental physical constants. Our results show that recent advances in the theoretical physics of liquids are applicable to molten salts mixtures, and therefore that the evolution and interplay of properties common to all liquids may act as a guide to a deeper understanding of these mixtures.

Published
2024
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2. Heat Transport in Ionic Liquids

Author

Cockrell, Cillian

Subjects
Condensed Matter - Materials Science, Condensed Matter - Statistical Mechanics
Abstract

Heat transfer in liquids is a very challenging problem as it combines the competing effect of high frequency oscillations, which dominate liquid heat capacity, and diffusive motion, which enables transport macroscopic flow. This issue is compounded by the relatively junior state of dynamical theories of liquid thermodynamics. Nevertheless, molten salts are playing an increasingly important role in industrial and energy applications and there is a pressing need to understand the mechanisms behind their irreversible transport processes. Here we use molecular dynamics simulations to investigate the heat transport of three different molten salts: LiCl, KCl, and the eutectic point of their mixture. While all simulations consider the properties of the liquid within the frame of its centre of mass, we calculate different susceptibilities which implicitly include and explicitly exclude the heat carried by partial mass currents within this frame. We find that, while the heat advected by partial mass currents in the mixture increases with increasing temperature, the heat transferred by collective vibrational motion (phonons) decreases with increasing temperature. This causes a maximum in the heat conductance with temperature in the mixtures only - in pure salts each contribution decreases monotonically with temperature. We attribute this anomaly to the extra freedom afforded to ionic motion in mixtures - in pure salts the motion of cations and anions is bound due to conservation of linear momentum. In mixtures, a coherent but diffusive collective motion is enabled by the release of Li ions from this condition by the introduction of a third species. We tentatively ascribe this coherent collective motion to the ``diffusive" phonons that have been used to explain a similar anomaly in the thermal conductivity of solids., Comment: 11 pages, 6 figures

Published
2024

3. Performance of the MACE-MP-0 potential for calculating viscosity in LiF molten salt

Author

Devereux, Harvey L., Withington, Margaret-Ann, Cockrell, Cillian, Trachenko, Kostya, and Elena, Alin Marin

Subjects
Condensed Matter - Materials Science
Abstract

We perform molecular dynamics simulations of molten Lithium Fluoride using the MACE-MP-0 (small) machine learnt interatomic potential and the classical Buckingham and Born-Huggins-Mayer potentials. We find that the MACE-MP-0, out-of-the-box, is able to accurately reproduce the experimental viscosity across the liquid state. Whilst the previous predicted viscosities from classical potentials are under-predicted, which has previously been attributed to a suppressed melting temperature. We find that the melting temperature simulated by MACE-MP-0, simply by heating a crystal structure, is significantly closer to the experimental melting temperature of LiF., Comment: 7 pages, 5 figures

Published
2024

4. MLPerf Power: Benchmarking the Energy Efficiency of Machine Learning Systems from Microwatts to Megawatts for Sustainable AI

Author

Tschand, Arya, Rajan, Arun Tejusve Raghunath, Idgunji, Sachin, Ghosh, Anirban, Holleman, Jeremy, Kiraly, Csaba, Ambalkar, Pawan, Borkar, Ritika, Chukka, Ramesh, Cockrell, Trevor, Curtis, Oliver, Fursin, Grigori, Hodak, Miro, Kassa, Hiwot, Lokhmotov, Anton, Miskovic, Dejan, Pan, Yuechao, Manmathan, Manu Prasad, Raymond, Liz, John, Tom St., Suresh, Arjun, Taubitz, Rowan, Zhan, Sean, Wasson, Scott, Kanter, David, and Reddi, Vijay Janapa

Subjects
Computer Science - Hardware Architecture, Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Machine Learning
Abstract

Rapid adoption of machine learning (ML) technologies has led to a surge in power consumption across diverse systems, from tiny IoT devices to massive datacenter clusters. Benchmarking the energy efficiency of these systems is crucial for optimization, but presents novel challenges due to the variety of hardware platforms, workload characteristics, and system-level interactions. This paper introduces MLPerf Power, a comprehensive benchmarking methodology with capabilities to evaluate the energy efficiency of ML systems at power levels ranging from microwatts to megawatts. Developed by a consortium of industry professionals from more than 20 organizations, MLPerf Power establishes rules and best practices to ensure comparability across diverse architectures. We use representative workloads from the MLPerf benchmark suite to collect 1,841 reproducible measurements from 60 systems across the entire range of ML deployment scales. Our analysis reveals trade-offs between performance, complexity, and energy efficiency across this wide range of systems, providing actionable insights for designing optimized ML solutions from the smallest edge devices to the largest cloud infrastructures. This work emphasizes the importance of energy efficiency as a key metric in the evaluation and comparison of the ML system, laying the foundation for future research in this critical area. We discuss the implications for developing sustainable AI solutions and standardizing energy efficiency benchmarking for ML systems., Comment: 16 pages, 11 figures, 1 table

Published
2024

5. Thermal conductivity and thermal diffusivity of molten salts: insights from molecular dynamics simulations and fundamental bounds

Author

Cockrell, C., Withington, M., Devereux, H. L., Elena, A. M., Todorov, I. T., Liu, Z. K., Shang, S. L., McCloy, J. S., Bingham, P. A., and Trachenko, K.

Subjects
Condensed Matter - Soft Condensed Matter, Condensed Matter - Materials Science
Abstract

We use extensive molecular dynamics simulations to calculate thermal conductivity and thermal diffusivity in two common molten salts, LiF and KCl. Our analysis includes the total thermal conductivity and intrinsic conductivity involving mass currents measured experimentally. The latter shows good agreement with the experimental data. We also calculate their key thermodynamic properties such as constant-pressure and constant-volume specific heats. We subsequently compare the results to the lower bound for thermal diffusivity expressed in terms of fundamental physical constants. Using this comparison and recent theoretical insights into thermodynamic and transport properties in liquids, we interpret thermal properties on the basis of atomistic dynamics and phonon excitations. We finally find that thermal diffusivity of molten salts is close to their kinematic viscosity., Comment: 8 pages, 4 figures

Published
2024

6. Thermodynamic modeling of the LiCl-KCl-LaCl$_3$ system with Bayesian model selection and uncertainty quantification

Author

Gong, Rushi, Shang, Shun-Li, Goncharov, Vitaliy G., Cockrell, Cillian, Trachenko, Kostya, Bingham, Paul A., Guo, Xiaofeng, and Liu, Zi-Kui

Subjects
Condensed Matter - Materials Science, Condensed Matter - Statistical Mechanics, Physics - Computational Physics
Abstract

Chloride molten salts are increasingly used in pyroprocessing techniques for the separation of lanthanides. Understanding thermodynamic properties of these salts is essential to predict their critical characteristics and optimize the separation process. Several thermodynamic models, including the associate model, the two-sublattice ionic model, and the modified quasichemical model with quadruplet approximation (MQMQA), have been utilized in the literature to capture the complexity of molten salts. In the present work, the Bayes factor is used to guide the model selection process for thermodynamic modeling of the KCl-LaCl3 system and provide statistical comparison of various models. The results indicate that the MQMQA model is the most favorable one based on available data. The LiCl-KCl-LaCl3 system has been further modelled with uncertainty quantification (UQ) using MQMQA with the thermodynamic properties of compounds in KCl-LaCl3 predicted by the quasiharmonic approach in terms of first-principles phonon calculations as a function of temperature. The calculated phase stability shows excellent agreement with experimental data, indicating that an appropriate thermodynamic model is important for accurately predicting critical characteristics of complex molten salts., Comment: 40 pages, 8 figures, 7 tables. Submitted to peer-reviewed journal

Published
2024

7. A design specification for Critical Illness Digital Twins to cure sepsis: responding to the National Academies of Sciences, Engineering and Medicine Report: Foundational Research Gaps and Future Directions for Digital Twins

Author

An, Gary and Cockrell, Chase

Subjects
Quantitative Biology - Other Quantitative Biology
Abstract

On December 15, 2023, The National Academies of Sciences, Engineering and Medicine (NASEM) released a report entitled: Foundational Research Gaps and Future Directions for Digital Twins. The ostensible purpose of this report was to bring some structure to the burgeoning field of digital twins by providing a working definition and a series of research challenges that need to be addressed to allow this technology to fulfill its full potential. In the work presented herein we focus on five specific findings from the NASEM Report: 1) definition of a Digital Twin, 2) using fit-for-purpose guidance, 3) developing novel approaches to Verification, Validation and Uncertainty Quantification (VVUQ) of Digital Twins, 4) incorporating control as an explicit purpose for a Digital Twin and 5) using a Digital Twin to guide data collection and sensor development, and describe how these findings are addressed through the design specifications for a Critical Illness Digital Twin (CIDT) aimed at curing sepsis., Comment: 31 pages, 13 Figures, 1 Table

Published
2024

8. Viscosity bounds in liquids with different structure and bonding types

Author

Withington, M., Devereux, H. L., Cockrell, C., Elena, A. M., Todorov, I. T., Liu, Z. K., Shang, S. L., McCloy, J. S., Bingham, P. A., and Trachenko, K.

Subjects
Condensed Matter - Soft Condensed Matter, Physics - Computational Physics
Abstract

Recently, it was realised that liquid viscosity has a lower bound which is nearly constant for all liquids and is governed by fundamental physical constants. This was supported by experimental data in noble and molecular liquids. Here, we perform large-scale molecular dynamics simulations to ascertain this bound in two other important liquid types: the ionic molten salt system LiF and metallic Pb. We find that these ionic and metallic systems similarly have lower viscosity bounds corresponding to the minimum of kinematic viscosity of about 10$^{-7}$ $\frac{{\rm m}^2}{\rm s}$. We show that this agrees with experimental data in other systems with different structures and bonding types, including noble, molecular, metallic and covalent liquids. This expands the universality of viscosity bounds into the main system types known., Comment: 6 pages, 7 figures

Published
2024
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9. Configurational and Vibrational Entropy in Hydrogen-bonded Fluids

Author

Cockrell, Cillian and Dragović, Aleksandra

Subjects
Condensed Matter - Soft Condensed Matter, Condensed Matter - Statistical Mechanics
Abstract

The thermodynamics of liquids and supercritical fluids is notorious for eluding a general theory, as can be done for crystalline solids on the basis of phonons and crystal symmetry. The extension of solid state notions such as configurational entropy and phonons to the liquid state remains an intriguing but challenging topic. This is particularly true for liquids like water whose many structural anomalies give it unique properties. Here, for simple fluids, we specify the thermodynamics across the liquid, supercritical, and gaseous states using the spectrum of propagating phonons, thereby determining the non-ideal entropy of the fluid using a single parameter arising from this phonon spectrum. This identifies a marked distinction between these "simple" fluids, and hydrogen bonded fluids whose non-ideal entropy cannot be determined by the phonon spectrum alone. We relate this phonon theory of thermodynamics to the previously observed excess entropy scaling in liquids and how the phonon spectrum creates corresponding states across the fluid phase diagram. These results provide important theoretical understanding to supercritical fluid, whose properties are still poorly understood despite widespread deployment in environmental and energy applications., Comment: 10 pages, 6 figures

Published
2023

11. Immune digital twins for complex human pathologies: applications, limitations, and challenges

Author

Anna Niarakis, Reinhard Laubenbacher, Gary An, Yaron Ilan, Jasmin Fisher, Åsmund Flobak, Kristin Reiche, María Rodríguez Martínez, Liesbet Geris, Luiz Ladeira, Lorenzo Veschini, Michael L. Blinov, Francesco Messina, Luis L. Fonseca, Sandra Ferreira, Arnau Montagud, Vincent Noël, Malvina Marku, Eirini Tsirvouli, Marcella M. Torres, Leonard A. Harris, T. J. Sego, Chase Cockrell, Amanda E. Shick, Hasan Balci, Albin Salazar, Kinza Rian, Ahmed Abdelmonem Hemedan, Marina Esteban-Medina, Bernard Staumont, Esteban Hernandez-Vargas, Shiny Martis B, Alejandro Madrid-Valiente, Panagiotis Karampelesis, Luis Sordo Vieira, Pradyumna Harlapur, Alexander Kulesza, Niloofar Nikaein, Winston Garira, Rahuman S. Malik Sheriff, Juilee Thakar, Van Du T. Tran, Jose Carbonell-Caballero, Soroush Safaei, Alfonso Valencia, Andrei Zinovyev, and James A. Glazier

Subjects
Biology (General), QH301-705.5
Abstract

Abstract Digital twins represent a key technology for precision health. Medical digital twins consist of computational models that represent the health state of individual patients over time, enabling optimal therapeutics and forecasting patient prognosis. Many health conditions involve the immune system, so it is crucial to include its key features when designing medical digital twins. The immune response is complex and varies across diseases and patients, and its modelling requires the collective expertise of the clinical, immunology, and computational modelling communities. This review outlines the initial progress on immune digital twins and the various initiatives to facilitate communication between interdisciplinary communities. We also outline the crucial aspects of an immune digital twin design and the prerequisites for its implementation in the clinic. We propose some initial use cases that could serve as “proof of concept” regarding the utility of immune digital technology, focusing on diseases with a very different immune response across spatial and temporal scales (minutes, days, months, years). Lastly, we discuss the use of digital twins in drug discovery and point out emerging challenges that the scientific community needs to collectively overcome to make immune digital twins a reality.

Published
2024
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12. Dental team barriers and enablers for the dental management of adults with severe obesity: a qualitative analysis

Author

Zanab Malik, Kate A. McBride, Kathryn Williams, Deborah Cockrell, and Clare E. Collins

Subjects
Dentistry, RK1-715
Abstract

Abstract Background Broad challenges regarding the dental management of people with severe obesity experienced by general dentists have been minimally explored. The perspectives of the dental team regarding these multifaceted issues are currently unknown and they potentially impede the delivery of optimal dental care to this population and contribute to poor oral and general health. Aims Our qualitative study aimed to identify and explore barriers and enablers in the dental management of adults with severe obesity among dental professionals and support staff in Australia. Methods Focus groups and semi-structured interviews (n = 34 participants) were conducted with dental professionals (n = 23) and support staff (n = 11). Recordings were transcribed verbatim and synthesised using thematic, inductive analysis. Results Multiple barriers to adequate provision of dental care for people living with severe obesity in both general and specialist dental settings were identified. Key themes emerged related to the clinical challenges reported by participants in providing dental management for people living with severe obesity, appropriateness of existing bariatric dental service provision and safety of care. Enablers to access were identified, including increased availability of bariatric dental chairs, environmental modifications, education of both patients and the entire dental team and for guideline development. Conclusion The current study explored multiple barriers to optimal dental management of people living with severe obesity in both general and specialist dental settings. Enablers should be used to inform future practice. The optimisation of existing bariatric dental service provision requires urgent review with solutions guided by systemic change. Study findings suggest a review of current health systems, economics, access barriers, policies and procedures and education and training beyond the individual level are needed. Future directions to improve the dental management of people living with severe obesity are proposed.

Published
2024
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13. A compendium of multi-omics data illuminating host responses to lethal human virus infections

Author

Eisfeld, Amie J., Anderson, Lindsey N., Fan, Shufang, Walters, Kevin B., Halfmann, Peter J., Westhoff Smith, Danielle, Thackray, Larissa B., Tan, Qing, Sims, Amy C., Menachery, Vineet D., Schäfer, Alexandra, Sheahan, Timothy P., Cockrell, Adam S., Stratton, Kelly G., Webb-Robertson, Bobbie-Jo M., Kyle, Jennifer E., Burnum-Johnson, Kristin E., Kim, Young-Mo, Nicora, Carrie D., Peralta, Zuleyma, N’jai, Alhaji U., Sahr, Foday, van Bakel, Harm, Diamond, Michael S., Baric, Ralph S., Metz, Thomas O., Smith, Richard D., Kawaoka, Yoshihiro, and Waters, Katrina M.

Published
2024
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16. The Evolution of Introductory Financial Accounting Labs Using Monopoly® and Excel--Is Student Performance Improved?

Author

Cockrell, Susan R., Harrison, Brandon M. Di Paolo, Davidson, Lesley, Brown, Pennye, Thayer, Jennifer, and Meyer, Pamela Sharp

Abstract

This paper examines the use of Monopoly® accompanied by Microsoft Excel to assess whether an active learning activity has an impact on the DFW rates in an introductory financial accounting course. (The DFW rate is the percentage of students who earn a grade of D or F or withdraw (W) from the course.) A zero credit hour Monopoly® Lab (which physically meets one hour per week during the semester) was created to enhance introductory business students' understanding of difficult accounting concepts by providing a means to record transactions and prepare financial statements. The objective is to engage students and link together the foundational aspects of accounting in a more realistic, understandable manner. The paper examined the DFW rates of the course over a ten-year period. Results of the study revealed a consistent lower DFW rate after the introduction of Monopoly® as compared to previous labs without the use of Monopoly®.

Published
2022

17. Fast dynamics and high effective dimensionality of liquid fluidity

Author

Cockrell, Cillian, Dicks, Oliver, Todorov, Ilian T., Elena, Alin M., and Trachenko, Kostya

Subjects
Condensed Matter - Statistical Mechanics
Abstract

Fluidity, the ability of liquids to flow, is the key property distinguishing liquids from solids. This fluidity is set by the mobile transit atoms moving from one quasi-equilibrium point to the next. The nature of this transit motion is unknown. Here, we show that flow-enabling transits form a dynamically distinct sub-ensemble where atoms move on average faster than the overall system, with a manifestly non-Maxwellian velocity distribution. This is in contrast to solids and gases where no distinction of different ensembles can be made and where the distribution is always Maxwellian. The non-Maxwellian distribution is described by an exponent $\alpha$ corresponding to high dimensionality of space. This is generally similar to extra synthetic dimensions in topological quantum matter, albeit higher dimensionality in liquids is not integer but is fractional. The dimensionality is close to 4 at melting and exceeds 4 at high temperature. $\alpha$ has a maximum as a function of temperature and pressure in liquid and supercritical states, returning to its Maxwell value in the solid and gas states., Comment: 6 pages, 4 figures

Published
2023
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18. MERS-CoV spike vaccine-induced N-terminal domain-specific antibodies are more protective than receptor binding domain-specific antibodies

Author

Olubukola M. Abiona, Nianshuang Wang, Sarah R. Leist, Alexandra Schäfer, Adam S. Cockrell, Lingshu Wang, Sandhya Bangaru, Laura Stevens, Rachel L. Graham, Jacob F. Kocher, Yaroslav Tsybovsky, Masaru Kanekiyo, Azad Kumar, Kaitlyn M. Morabito, Osnat Rosen, Wei Shi, Anne Werner, Yi Zhang, Cynthia Ziwawo, Christian K.O. Dzuvor, Charis Palandjian, Connor Eastman, Hannah R. Matthews, Jeswin Joseph, James D. Chappell, Wing-Pui Kong, John R. Mascola, Andrew B. Ward, Mark R. Denison, Ralph Baric, Jason S. McLellan, Barney S. Graham, and Kizzmekia S. Corbett-Helaire

Subjects
Immunology, Immunity, Virology, Science
Abstract

Summary: The COVID-19 pandemic underscores the need to prepare for future emerging coronavriuses (CoVs) by understanding the principles behind effective CoV vaccine design such as protective immunity and antibody responses. To study which epitopes and subdomains contribute to in vivo protection, we utilized the prefusion-stabilized spike protein of MERS-CoV, MERS S-2P, as a vaccine immunogen. Vaccination with MERS S-2P elicited both receptor-binding domain (RBD)- and non-RBD-specific antibodies, including N-terminal domain (NTD)-specific G2-and CDC2-A2-like antibodies. Intriguingly, the immunogen MERS S-2P_ΔRBD, MERS S-2P with the RBDs removed, protects comparably to S1 and S-2P immunogens against MERS-CoV challenge. Moreover, passive transfer studies of polyclonal IgG from MERS S-2P immunized mice depleted of subdomain-specific antibodies demonstrated that non-RBD antibodies protected more than non-NTD antibodies. Altogether, these findings illustrate that in-vivo protection is not solely driven by RBD-specific antibodies and highlights the importance of targeting non-RBD sites in future CoV vaccine designs.

Published
2025
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19. Generating synthetic multi-dimensional molecular-mediator time series data for artificial intelligence-based disease trajectory forecasting and drug development digital twins: Considerations

Author

An, Gary and Cockrell, Chase

Subjects
Computer Science - Artificial Intelligence, I.2.m, J.3
Abstract

The use of synthetic data is recognized as a crucial step in the development of neural network-based Artificial Intelligence (AI) systems. While the methods for generating synthetic data for AI applications in other domains have a role in certain biomedical AI systems, primarily related to image processing, there is a critical gap in the generation of time series data for AI tasks where it is necessary to know how the system works. This is most pronounced in the ability to generate synthetic multi-dimensional molecular time series data (SMMTSD); this is the type of data that underpins research into biomarkers and mediator signatures for forecasting various diseases and is an essential component of the drug development pipeline. We argue the insufficiency of statistical and data-centric machine learning (ML) means of generating this type of synthetic data is due to a combination of factors: perpetual data sparsity due to the Curse of Dimensionality, the inapplicability of the Central Limit Theorem, and the limits imposed by the Causal Hierarchy Theorem. Alternatively, we present a rationale for using complex multi-scale mechanism-based simulation models, constructed and operated on to account for epistemic incompleteness and the need to provide maximal expansiveness in concordance with the Principle of Maximal Entropy. These procedures provide for the generation of SMMTD that minimizes the known shortcomings associated with neural network AI systems, namely overfitting and lack of generalizability. The generation of synthetic data that accounts for the identified factors of multi-dimensional time series data is an essential capability for the development of mediator-biomarker based AI forecasting systems, and therapeutic control development and optimization through systems like Drug Development Digital Twins., Comment: 16 pages, 2 Figures

Published
2023

21. Analyzing Robustness in Water Distribution Networks Using Temporal Complex Networks and Optimization

Author

Montes-Orozco, Edwin, Mora-Gutiérrez, Roman Anselmo, de-los-Cobos-Silva, Sergio Gerardo, Torres-Cockrell, Gilberto Sinuhé, Rincón-García, Eric Alfredo, Gutiérrez-Andrade, Miguel Ángel, Velázquez, Pedro Lara, Chlamtac, Imrich, Series Editor, Marmolejo-Saucedo, José Antonio, editor, De La Mota, Idalia Flores, editor, Rodriguez-Aguilar, Roman, editor, Marmolejo-Saucedo, Liliana, editor, Rodriguez-Aguilar, Miriam, editor, Litvinchev, Igor, editor, Vasant, Pandian, editor, and Kose, Utku, editor

Published
2024
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23. Stratified analyses refine association between TLR7 rare variants and severe COVID-19

Author

Jannik Boos, Caspar I. van der Made, Gayatri Ramakrishnan, Eamon Coughlan, Rosanna Asselta, Britt-Sabina Löscher, Luca V.C. Valenti, Rafael de Cid, Luis Bujanda, Antonio Julià, Erola Pairo-Castineira, J. Kenneth Baillie, Sandra May, Berina Zametica, Julia Heggemann, Agustín Albillos, Jesus M. Banales, Jordi Barretina, Natalia Blay, Paolo Bonfanti, Maria Buti, Javier Fernandez, Sara Marsal, Daniele Prati, Luisa Ronzoni, Nicoletta Sacchi, Joachim L. Schultze, Olaf Riess, Andre Franke, Konrad Rawlik, David Ellinghaus, Alexander Hoischen, Axel Schmidt, Kerstin U. Ludwig, Valeria Rimoldi, Elvezia M. Paraboschi, Alessandra Bandera, Flora Peyvandi, Giacomo Grasselli, Francesco Blasi, Francesco Malvestiti, Serena Pelusi, Cristiana Bianco, Lorenzo Miano, Angela Lombardi, Pietro Invernizzi, Alessio Gerussi, Giuseppe Citerio, Andrea Biondi, Maria Grazia Valsecchi, Marina Elena Cazzaniga, Giuseppe Foti, Ilaria Beretta, Mariella D'Angiò, Laura Rachele Bettini, Xavier Farré, Susana Iraola-Guzmán, Manolis Kogevinas, Gemma Castaño-Vinyals, Koldo Garcia-Etxebarria, Beatriz Nafria, Mauro D'Amato, Adriana Palom, Colin Begg, Sara Clohisey, Charles Hinds, Peter Horby, Julian Knight, Lowell Ling, David Maslove, Danny McAuley, Johnny Millar, Hugh Montgomery, Alistair Nichol, Peter J.M. Openshaw, Alexandre C. Pereira, Chris P. Ponting, Kathy Rowan, Malcolm G. Semple, Manu Shankar-Hari, Charlotte Summers, Timothy Walsh, Latha Aravindan, Ruth Armstrong, Heather Biggs, Ceilia Boz, Adam Brown, Richard Clark, Audrey Coutts, Judy Coyle, Louise Cullum, Sukamal Das, Nicky Day, Lorna Donnelly, Esther Duncan, Angie Fawkes, Paul Fineran, Max Head Fourman, Anita Furlong, James Furniss, Bernadette Gallagher, Tammy Gilchrist, Ailsa Golightly, Fiona Griffiths, Katarzyna Hafezi, Debbie Hamilton, Ross Hendry, Andy Law, Dawn Law, Rachel Law, Sarah Law, Rebecca Lidstone-Scott, Louise Macgillivray, Alan Maclean, Hanning Mal, Sarah McCafferty, Ellie Mcmaster, Jen Meikle, Shona C. Moore, Kirstie Morrice, Lee Murphy, Sheena Murphy, Mybaya Hellen, Wilna Oosthuyzen, Chenqing Zheng, Jiantao Chen, Nick Parkinson, Trevor Paterson, Katherine Schon, Andrew Stenhouse, Mihaela Das, Maaike Swets, Helen Szoor-McElhinney, Filip Taneski, Lance Turtle, Tony Wackett, Mairi Ward, Jane Weaver, Nicola Wrobel, Marie Zechner, Gill Arbane, Aneta Bociek, Sara Campos, Neus Grau, Tim Owen Jones, Rosario Lim, Martina Marotti, Marlies Ostermann, Christopher Whitton, Zoe Alldis, Raine Astin-Chamberlain, Fatima Bibi, Jack Biddle, Sarah Blow, Matthew Bolton, Catherine Borra, Ruth Bowles, Maudrian Burton, Yasmin Choudhury, David Collier, Amber Cox, Amy Easthope, Patrizia Ebano, Stavros Fotiadis, Jana Gurasashvili, Rosslyn Halls, Pippa Hartridge, Delordson Kallon, Jamila Kassam, Ivone Lancoma-Malcolm, Maninderpal Matharu, Peter May, Oliver Mitchelmore, Tabitha Newman, Mital Patel, Jane Pheby, Irene Pinzuti, Zoe Prime, Oleksandra Prysyazhna, Julian Shiel, Melanie Taylor, Carey Tierney, Suzanne Wood, Anne Zak, Olivier Zongo, Stephen Bonner, Keith Hugill, Jessica Jones, Steven Liggett, Evie Headlam, Nageswar Bandla, Minnie Gellamucho, Michelle Davies, Christopher Thompson, Marwa Abdelrazik, Dhanalakshmi Bakthavatsalam, Munzir Elhassan, Arunkumar Ganesan, Anne Haldeos, Jeronimo Moreno-Cuesta, Dharam Purohit, Rachel Vincent, Kugan Xavier, Kumar Rohit, Frater Alasdair, Malik Saleem, Carter David, Jenkins Samuel, Zoe Lamond, Wall Alanna, Jaime Fernandez-Roman, David O. Hamilton, Emily Johnson, Brian Johnston, Maria Lopez Martinez, Suleman Mulla, David Shaw, Alicia A.C. Waite, Victoria Waugh, Ingeborg D. Welters, Karen Williams, Anna Cavazza, Maeve Cockrell, Eleanor Corcoran, Maria Depante, Clare Finney, Ellen Jerome, Mark McPhail, Monalisa Nayak, Harriet Noble, Kevin O'Reilly, Evita Pappa, Rohit Saha, Sian Saha, John Smith, Abigail Knighton, David Antcliffe, Dorota Banach, Stephen Brett, Phoebe Coghlan, Ziortza Fernandez, Anthony Gordon, Roceld Rojo, Sonia Sousa Arias, Maie Templeton, Megan Meredith, Lucy Morris, Lucy Ryan, Amy Clark, Julia Sampson, Cecilia Peters, Martin Dent, Margaret Langley, Saima Ashraf, Shuying Wei, Angela Andrew, Archana Bashyal, Neil Davidson, Paula Hutton, Stuart McKechnie, Jean Wilson, David Baptista, Rebecca Crowe, Rita Fernandes, Rosaleen Herdman-Grant, Anna Joseph, Denise O'Connor, Meryem Allen, Adam Loveridge, India McKenley, Eriko Morino, Andres Naranjo, Richard Simms, Kathryn Sollesta, Andrew Swain, Harish Venkatesh, Jacyntha Khera, Jonathan Fox, Gillian Andrew, Lucy Barclay, Marie Callaghan, Rachael Campbell, Sarah Clark, Dave Hope, Lucy Marshall, Corrienne McCulloch, Kate Briton, Jo Singleton, Sohphie Birch, Lutece Brimfield, Zoe Daly, David Pogson, Steve Rose, Ceri Battle, Elaine Brinkworth, Rachel Harford, Carl Murphy, Luke Newey, Tabitha Rees, Marie Williams, Sophie Arnold, Petra Polgarova, Katerina Stroud, Eoghan Meaney, Megan Jones, Anthony Ng, Shruti Agrawal, Nazima Pathan, Deborah White, Esther Daubney, Kay Elston, Lina Grauslyte, Musarat Hussain, Mandeep Phull, Tatiana Pogreban, Lace Rosaroso, Erika Salciute, George Franke, Joanna Wong, Aparna George, Laura Ortiz-Ruiz de Gordoa, Emily Peasgood, Claire Phillips, Michelle Bates, Jo Dasgin, Jaspret Gill, Annette Nilsson, James Scriven, Carlos Castro Delgado, Deborah Dawson, Lijun Ding, Georgia Durrant, Obiageri Ezeobu, Sarah Farnell-Ward, Abiola Harrison, Rebecca Kanu, Susannah Leaver, Elena Maccacari, Soumendu Manna, Romina Pepermans Saluzzio, Joana Queiroz, Tinashe Samakomva, Christine Sicat, Joana Texeira, Edna Fernandes Da Gloria, Ana Lisboa, John Rawlins, Jisha Mathew, Ashley Kinch, William James Hurt, Nirav Shah, Victoria Clark, Maria Thanasi, Nikki Yun, Kamal Patel, Sara Bennett, Emma Goodwin, Matthew Jackson, Alissa Kent, Clare Tibke, Wiesia Woodyatt, Ahmed Zaki, Azmerelda Abraheem, Peter Bamford, Kathryn Cawley, Charlie Dunmore, Maria Faulkner, Rumanah Girach, Helen Jeffrey, Rhianna Jones, Emily London, Imrun Nagra, Farah Nasir, Hannah Sainsbury, Clare Smedley, Tahera Patel, Matthew Smith, Srikanth Chukkambotla, Aayesha Kazi, Janice Hartley, Joseph Dykes, Muhammad Hijazi, Sarah Keith, Meherunnisa Khan, Janet Ryan-Smith, Philippa Springle, Jacqueline Thomas, Nick Truman, Samuel Saad, Dabheoc Coleman, Christopher Fine, Roseanna Matt, Bethan Gay, Jack Dalziel, Syamlan Ali, Drew Goodchild, Rhiannan Harling, Ravi Bhatterjee, Wendy Goddard, Chloe Davison, Stephen Duberly, Jeanette Hargreaves, Rachel Bolton, Miriam Davey, David Golden, Rebecca Seaman, Shiney Cherian, Sean Cutler, Anne Emma Heron, Anna Roynon-Reed, Tamas Szakmany, Gemma Williams, Owen Richards, Yusuf Cheema, Hollie Brooke, Sarah Buckley, Jose Cebrian Suarez, Ruth Charlesworth, Karen Hansson, John Norris, Alice Poole, Alastair Rose, Rajdeep Sandhu, Brendan Sloan, Elizabeth Smithson, Muthu Thirumaran, Veronica Wagstaff, Alexandra Metcalfe, Mark Brunton, Jess Caterson, Holly Coles, Matthew Frise, Sabi Gurung Rai, Nicola Jacques, Liza Keating, Emma Tilney, Shauna Bartley, Parminder Bhuie, Sian Gibson, Amanda Lyle, Fiona McNeela, Jayachandran Radhakrishnan, Alistair Hughes, Bryan Yates, Jessica Reynolds, Helen Campbell, Maria Thompsom, Steve Dodds, Stacey Duffy, Sandra Greer, Karen Shuker, Ascanio Tridente, Reena Khade, Ashok Sundar, George Tsinaslanidis, Isobel Birkinshaw, Joseph Carter, Kate Howard, Joanne Ingham, Rosie Joy, Harriet Pearson, Samantha Roche, Zoe Scott, Hollie Bancroft, Mary Bellamy, Margaret Carmody, Jacqueline Daglish, Faye Moore, Joanne Rhodes, Mirriam Sangombe, Salma Kadiri, Maria Croft, Ian White, Victoria Frost, Maia Aquino, Rajeev Jha, Vinodh Krishnamurthy, Lai Lim, Li Lim, Edward Combes, Teishel Joefield, Sonja Monnery, Valerie Beech, Sallyanne Trotman, Christine Almaden-Boyle, Pauline Austin, Louise Cabrelli, Stephen Cole, Matt Casey, Susan Chapman, Clare Whyte, Yolanda Baird, Aaron Butler, Indra Chadbourn, Linda Folkes, Heather Fox, Amy Gardner, Raquel Gomez, Gillian Hobden, Luke Hodgson, Kirsten King, Michael Margarson, Tim Martindale, Emma Meadows, Dana Raynard, Yvette Thirlwall, David Helm, Jordi Margalef, Kristine Criste, Rebecca Cusack, Kim Golder, Hannah Golding, Oliver Jones, Samantha Leggett, Michelle Male, Martyna Marani, Kirsty Prager, Toran Williams, Belinda Roberts, Karen Salmon, Peter Anderson, Katie Archer, Karen Austin, Caroline Davis, Alison Durie, Olivia Kelsall, Jessica Thrush, Charlie Vigurs, Laura Wild, Hannah-Louise Wood, Helen Tranter, Alison Harrison, Nicholas Cowley, Michael McAlindon, Andrew Burtenshaw, Stephen Digby, Emma Low, Aled Morgan, Naiara Cother, Tobias Rankin, Sarah Clayton, Alex McCurdy, Cecilia Ahmed, Balvinder Baines, Sarah Clamp, Julie Colley, Risna Haq, Anne Hayes, Jonathan Hulme, Samia Hussain, Sibet Joseph, Rita Kumar, Zahira Maqsood, Manjit Purewal, Leonie Benham, Zena Bradshaw, Joanna Brown, Melanie Caswell, Jason Cupitt, Sarah Melling, Stephen Preston, Nicola Slawson, Emma Stoddard, Scott Warden, Bethan Deacon, Ceri Lynch, Carla Pothecary, Lisa Roche, Gwenllian Sera Howe, Jayaprakash Singh, Keri Turner, Hannah Ellis, Natalie Stroud, Jodie Hunt, Joy Dearden, Emma Dobson, Andy Drummond, Michelle Mulcahy, Sheila Munt, Grainne O'Connor, Jennifer Philbin, Chloe Rishton, Redmond Tully, Sarah Winnard, Susanne Cathcart, Katharine Duffy, Alex Puxty, Kathryn Puxty, Lynne Turner, Jane Ireland, Gary Semple, Kate Long, Simon Whiteley, Elizabeth Wilby, Bethan Ogg, Amanda Cowton, Andrea Kay, Melanie Kent, Kathryn Potts, Ami Wilkinson, Suzanne Campbell, Ellen Brown, Julie Melville, Jay Naisbitt, Rosane Joseph, Maria Lazo, Olivia Walton, Alan Neal, Peter Alexander, 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Webster, Anne Hudson, Andrea Webster, Elaine Stephenson, Louise McCormack, Victoria Slater, Rachel Nixon, Helen Hanson, Maggie Fearby, Sinead Kelly, Victoria Bridgett, Philip Robinson, Julie Camsooksai, Charlotte Humphrey, Sarah Jenkins, Henrik Reschreiter, Beverley Wadams, Yasmin Death, Victoria Bastion, Daphene Clarke, Beena David, Harriet Kent, Rachel Lorusso, Gamu Lubimbi, Sophie Murdoch, Melchizedek Penacerrada, Alastair Thomas, Jennifer Valentine, Ana Vochin, Retno Wulandari, Brice Djeugam, Gillian Bell, Katy English, Amro Katary, Louise Wilcox, Michelle Bruce, Karen Connolly, Tracy Duncan, Helen T-Michael, Gabriella Lindergard, Samuel Hey, Claire Fox, Jordan Alfonso, Laura Jayne Durrans, Jacinta Guerin, Bethan Blackledge, Jade Harris, Martin Hruska, Ayaa Eltayeb, Thomas Lamb, Tracey Hodgkiss, Lisa Cooper, Joanne Rothwell, Angela Allan, Felicity Anderson, Callum Kaye, Jade Liew, Jasmine Medhora, Teresa Scott, Erin Trumper, Adriana Botello, Liana Lankester, Nikitas Nikitas, Colin Wells, Bethan Stowe, Kayleigh Spencer, Craig Brandwood, Lara Smith, Katie Birchall, Laurel Kolakaluri, Deborah Baines, Anila Sukumaran, Elena Apetri, Cathrine Basikolo, Laura Catlow, Bethan Charles, Paul Dark, Reece Doonan, Alice Harvey, Daniel Horner, Karen Knowles, Stephanie Lee, Diane Lomas, Chloe Lyons, Tracy Marsden, Danielle McLaughlan, Liam McMorrow, Jessica Pendlebury, Jane Perez, Maria Poulaka, Nicola Proudfoot, Melanie Slaughter, Kathryn Slevin, Vicky Thomas, Danielle Walker, Angiy Michael, Matthew Collis, Tracey Cosier, Gemma Millen, Neil Richardson, Natasha Schumacher, Heather Weston, James Rand, Nicola Baxter, Steven Henderson, Sophie Kennedy-Hay, Christopher McParland, Laura Rooney, Malcolm Sim, Gordan McCreath, Louise Akeroyd, Shereen Bano, Matt Bromley, Lucy Gurr, Tom Lawton, James Morgan, Kirsten Sellick, Deborah Warren, Brian Wilkinson, Janet McGowan, Camilla Ledgard, Amelia Stacey, Kate Pye, Ruth Bellwood, Michael Bentley, Jeremy Bewley, Zoe Garland, Lisa Grimmer, Bethany Gumbrill, Rebekah Johnson, Katie Sweet, Denise Webster, Georgia Efford, Karen Convery, Deirdre Fottrell-Gould, Lisa Hudig, Jocelyn Keshet-Price, Georgina Randell, Katie Stammers, Maria Bokhari, Vanessa Linnett, Rachael Lucas, Wendy McCormick, Jenny Ritzema, Amanda Sanderson, Helen Wild, Anthony Rostron, Alistair Roy, Lindsey Woods, Sarah Cornell, Fiona Wakinshaw, Kimberley Rogerson, Jordan Jarmain, Robert Parker, Amie Reddy, Ian Turner-Bone, Laura Wilding, Peter Harding, Caroline Abernathy, Louise Foster, Andrew Gratrix, Vicky Martinson, Priyai Parkinson, Elizabeth Stones, Llucia Carbral-Ortega, Georgia Bercades, David Brealey, Ingrid Hass, Niall MacCallum, Gladys Martir, Eamon Raith, Anna Reyes, Deborah Smyth, Letizia Zitter, Sarah Benyon, Suzie Marriott, Linda Park, Samantha Keenan, Elizabeth Gordon, Helen Quinn, Kizzy Baines, Lenka Cagova, Adama Fofano, Lucie Garner, Helen Holcombe, Sue Mepham, Alice Michael Mitchell, Lucy Mwaura, Krithivasan Praman, Alain Vuylsteke, Julie Zamikula, Bally Purewal, Vanessa Rivers, Stephanie Bell, Hayley Blakemore, Borislava Borislavova, Beverley Faulkner, Emma Gendall, Elizabeth Goff, Kati Hayes, Matt Thomas, Ruth Worner, Kerry Smith, Deanna Stephens, Louise Mew, Esther Mwaura, Richard Stewart, Felicity Williams, Lynn Wren, Sara-Beth Sutherland, Emily Bevan, Jane Martin, Dawn Trodd, Geoff Watson, Caroline Wrey Brown, Amy Collins, Waqas Khaliq, Estefania Treus Gude, Olugbenga Akinkugbe, Alasdair Bamford, Emily Beech, Holly Belfield, Michael Bell, Charlene Davies, Gareth A.L. Jones, Tara McHugh, Hamza Meghari, Lauran O'Neill, Mark J. Peters, Samiran Ray, Ana Luisa Tomas, Iona Burn, Geraldine Hambrook, Katarina Manso, Ruth Penn, Pradeep Shanmugasundaram, Julie Tebbutt, Danielle Thornton, Jade Cole, Rhys Davies, Donna Duffin, Helen Hill, Ben Player, Emma Thomas, Angharad Williams, Denise Griffin, Nycola Muchenje, Mcdonald Mupudzi, Richard Partridge, Jo-Anna Conyngham, Rachel Thomas, Mary Wright, Maria Alvarez Corral, Reni Jacob, Cathy Jones, Craig Denmade, Sarah Beavis, Katie Dale, Rachel Gascoyne, Joanne Hawes, Kelly Pritchard, Lesley Stevenson, Amanda Whileman, Patricia Doble, Joanne Hutter, Corinne Pawley, Charmaine Shovelton, Marius Vaida, Deborah Butcher, Susie O'Sullivan, Nicola Butterworth-Cowin, Norfaizan Ahmad, Joann Barker, Kris Bauchmuller, Sarah Bird, Kay Cawthron, Kate Harrington, Yvonne Jackson, Faith Kibutu, Becky Lenagh, Shamiso Masuko, Gary H. 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Zborowski, John Allan, Tim Geary, Gordon Houston, Alistair Meikle, Peter O'Brien, Miranda Forsey, Agilan Kaliappan, Anne Nicholson, Joanne Riches, Mark Vertue, Elizabeth Allan, Kate Darlington, Ffyon Davies, Jack Easton, Sumit Kumar, Richard Lean, Daniel Menzies, Richard Pugh, Xinyi Qiu, Llinos Davies, Hannah Williams, Jeremy Scanlon, Gwyneth Davies, Callum Mackay, Joannne Lewis, Stephanie Rees, Metod Oblak, Monica Popescu, Mini Thankachen, Andrew Higham, Kerry Simpson, Jayne Craig, Rosie Baruah, Sheila Morris, Susie Ferguson, Amy Shepherd, Luke Stephen Prockter Moore, Marcela Paola Vizcaychipi, Laura Gomes de Almeida Martins, Jaime Carungcong, Inthakab Ali Mohamed Ali, Karen Beaumont, Mark Blunt, Zoe Coton, Hollie Curgenven, Mohamed Elsaadany, Kay Fernandes, Sameena Mohamed Ally, Harini Rangarajan, Varun Sarathy, Sivarupan Selvanayagam, Dave Vedage, Matthew White, Mandy Gill, Paul Paul, Valli Ratnam, Sarah Shelton, Inez Wynter, Siobhain Carmody, Valerie Joan Page, Claire Marie Beith, Karen Black, Suzanne Clements, Alan Morrison, Dominic Strachan, Margaret Taylor, Michelle Clarkson, Stuart D'Sylva, Kathryn Norman, Fiona Auld, Joanne Donnachie, Ian Edmond, Lynn Prentice, Nikole Runciman, Dario Salutous, Lesley Symon, Anne Todd, Patricia Turner, Abigail Short, Laura Sweeney, Euan Murdoch, Dhaneesha Senaratne, Michaela Hill, Thogulava Kannan, Wild Laura, Rikki Crawley, Abigail Crew, Mishell Cunningham, Allison Daniels, Laura Harrison, Susan Hope, Ken Inweregbu, Sian Jones, Nicola Lancaster, Jamie Matthews, Alice Nicholson, Gemma Wray, Helen Langton, Rachel Prout, Malcolm Watters, Catherine Novis, Anthony Barron, Ciara Collins, Sundeep Kaul, Heather Passmore, Claire Prendergast, Anna Reed, Paula Rogers, Rajvinder Shokkar, Meriel Woodruff, Hayley Middleton, Oliver Polgar, Claire Nolan, Kanta Mahay, Dawn Collier, Anil Hormis, Victoria Maynard, Cheryl Graham, Rachel Walker, Ellen Knights, Alicia Price, Alice Thomas, Chris Thorpe, Teresa Behan, Caroline Burnett, Jonathan Hatton, Elaine Heeney, Atideb Mitra, Maria Newton, Rachel Pollard, Rachael Stead, Vishal Amin, Elena Anastasescu, Vikram Anumakonda, Komala Karthik, Rizwana Kausar, Karen Reid, Jacqueline Smith, Janet Imeson-Wood, Denise Skinner, Jane Gaylard, Dee Mullan, Julie Newman, Alison Brown, Vikki Crickmore, Gabor Debreceni, Joy Wilkins, Liz Nicol, Rosie Reece-Anthony, Mark Birt, Alison Ghosh, Emma Williams, Louise Allen, Eva Beranova, Nikki Crisp, Joanne Deery, Tracy Hazelton, Alicia Knight, Carly Price, Sorrell Tilbey, Salah Turki, Sharon Turney, Joshua Cooper, Cheryl Finch, Sarah Liderth, Alison Quinn, Natalia Waddington, Tina Coventry, Susan Fowler, Michael MacMahon, Amanda McGregor, Anne Cowley, Judith Highgate, Jane Gregory, Susan O'Connell, Tim Smith, Luigi Barberis, Shameer Gopal, Nichola Harris, Victoria Lake, Stella Metherell, Elizabeth Radford, Amelia Daniel, Joanne Finn, Rajnish Saha, Nikki White, Phil Donnison, Fiona Trim, Beena Eapen, Jenny Birch, Laura Bough, Josie Goodsell, Rebecca Tutton, Patricia Williams, Sarah Williams, Barbara Winter-Goodwin, Ailstair Nichol, Kathy Brickell, Michelle Smyth, Lorna Murphy, Samantha Coetzee, Alistair Gales, Igor Otahal, Meena Raj, Craig Sell, Paula Hilltout, Jayne Evitts, Amanda Tyler, Joanne Waldron, Kate Beesley, Sarah Board, Agnieszka Kubisz-Pudelko, Alison Lewis, Jess Perry, Lucy Pippard, Di Wood, Clare Buckley, Peter Barry, Neil Flint, Patel Rekha, Dawn Hales, Lara Bunni, Claire Jennings, Monica Latif, Rebecca Marshall, Gayathri Subramanian, Peter J. McGuigan, Christopher Wasson, Stephanie Finn, Jackie Green, Erin Collins, Bernadette King, Andy Campbell, Sara Smuts, Joseph Duffield, Oliver Smith, Lewis Mallon, Watkins Claire, Liam Botfield, Joanna Butler, Catherine Dexter, Jo Fletcher, Atul Garg, Aditya Kuravi, Poonam Ranga, Emma Virgilio, Zakaula Belagodu, Bridget Fuller, Anca Gherman, Olumide Olufuwa, Remi Paramsothy, Carmel Stuart, Naomi Oakley, Charlotte Kamundi, David Tyl, Katy Collins, Pedro Silva, June Taylor, Laura King, Charlotte Coates, Maria Crowley, Phillipa Wakefield, Jane Beadle, Laura Johnson, Janet Sargeant, Madeleine Anderson, Ailbhe Brady, Rebekah Chan, Jeff Little, Shane McIvor, Helena Prady, Helen Whittle, Bijoy Mathew, Ben Attwood, Penny Parsons, Geraldine Ward, Pamela Bremmer, West Joe, Baird Tracy, Ruddy Jim, Ellie Davies, Sonia Sathe, Catherine Dennis, Alastair McGregor, Victoria Parris, Sinduya Srikaran, Anisha Sukha, Noreen Clarke, Jonathan Whiteside, Mairi Mascarenhas, Avril Donaldson, Joanna Matheson, Fiona Barrett, Marianne O'Hara, Laura Okeefe, Clare Bradley, Christine Eastgate-Jackson, Helder Filipe, Daniel Martin, Amitaa Maharajh, Sara Mingo Garcia, Glykeria Pakou, Mark De Neef, Kathy Dent, Elizabeth Horsley, Muhmmad Nauman Akhtar, Sandra Pearson, Dorota Potoczna, Sue Spencer, Melanie Clapham, Rosemary Harper, Una Poultney, Polly Rice, Rachel Mutch, Lisa Armstrong, Hayley Bates, Emma Dooks, Fiona Farquhar, Brigid Hairsine, Chantal McParland, Sophie Packham, Rehana Bi, Barney Scholefield, Lydia Ashton, Linsha George, Sophie Twiss, David Wright, Manish Chablani, Amy Kirkby, Kimberley Netherton, Kim Davies, Linda O'Brien, Zohra Omar, Emma Perkins, Tracy Lewis, Isobel Sutherland, Karen Burns, Dr Ben Chandler, Kerry Elliott, Janine Mallinson, Alison Turnbull, Prisca Gondo, Bernard Hadebe, Abdul Kayani, Bridgett Masunda, Taya Anderson, Dan Hawcutt, Laura O'Malley, Laura Rad, Naomi Rogers, Paula Saunderson, Kathryn Sian Allison, Deborah Afolabi, Jennifer Whitbread, Dawn Jones, Rachael Dore, Matthew Halkes, Pauline Mercer, Lorraine Thornton, Joy Dawson, Sweyn Garrioch, Melanie Tolson, Jonathan Aldridge, Ritoo Kapoor, David Loader, Karen Castle, Sally Humphreys, Ruth Tampsett, Katherine Mackintosh, Amanda Ayers, Wendy Harrison, Julie North, Suzanne Allibone, Roman Genetu, Vidya Kasipandian, Amit Patel, Ainhi Mac, Anthony Murphy, Parisa Mahjoob, Roonak Nazari, Lucy Worsley, Andrew Fagan, Thomas Bemand, Ethel Black, Arnold Dela Rosa, Ryan Howle, Shaman Jhanji, Ravishankar Rao Baikady, Kate Colette Tatham, Benjamin Thomas, Dina Bell, Rosalind Boyle, Katie Douglas, Lynn Glass, Emma Lee, Liz Lennon, Austin Rattray, Abigail Taylor, Rachel Anne Hughes, Helen Thomas, Alun Rees, Michaela Duskova, Janet Phipps, Suzanne Brooks, Michelle Edwards, Sheena Quaid, Ekaterina Watson, Adam Brayne, Emma Fisher, Jane Hunt, Peter Jackson, Duncan Kaye, Nicholas Love, Juliet Parkin, Victoria Tuckey, Lynne Van Koutrik, Sasha Carter, Benedict Andrew, Louise Findlay, Katie Adams, Jen Service, Alison Williams, Claire Cheyne, Anne Saunderson, Sam Moultrie, Miranda Odam, Kathryn Hall, Isheunesu Mapfunde, Charlotte Willis, Alex Lyon, Chunda Sri-Chandana, Joslan Scherewode, Lorraine Stephenson, Sarah Marsh, John Hardy, Henry Houlden, Eleanor Moncur, Ambreen Tariq, Arianna Tucci, Maria Hobrok, Ronda Loosley, Heather McGuinness, Helen Tench, Rebecca Wolf-Roberts, Val Irvine, Benjamin Shelley, Claire Gorman, Abhinav Gupta, Elizabeth Timlick, Rebecca Brady, Barry Milligan, Arianna Bellini, Jade Bryant, Anton Mayer, Amy Pickard, Nicholas Roe, Jason Sowter, Alex Howlett, Katy Fidler, Emma Tagliavini, and Kevin Donnelly

Subjects
SARS-CoV-2, host genetics, toll-like receptor 7, targeted sequencing, rare variants, variant collapsing analysis, Genetics, QH426-470
Abstract

Summary: Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (

Published
2024
Full Text
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24. Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort CollaborativeResearch in context

Author

Timothy Bergquist, Johanna Loomba, Emily Pfaff, Fangfang Xia, Zixuan Zhao, Yitan Zhu, Elliot Mitchell, Biplab Bhattacharya, Gaurav Shetty, Tamanna Munia, Grant Delong, Adbul Tariq, Zachary Butzin-Dozier, Yunwen Ji, Haodong Li, Jeremy Coyle, Seraphina Shi, Rachael V. Philips, Andrew Mertens, Romain Pirracchio, Mark van der Laan, John M. Colford, Jr., Alan Hubbard, Jifan Gao, Guanhua Chen, Neelay Velingker, Ziyang Li, Yinjun Wu, Adam Stein, Jiani Huang, Zongyu Dai, Qi Long, Mayur Naik, John Holmes, Danielle Mowery, Eric Wong, Ravi Parekh, Emily Getzen, Jake Hightower, Jennifer Blase, Ataes Aggarwal, Joseph Agor, Amera Al-Amery, Oluwatobiloba Aminu, Adit Anand, Corneliu Antonescu, Mehak Arora, Sayed Asaduzzaman, Tanner Asmussen, Mahdi Baghbanzadeh, Frazier Baker, Bridget Bangert, Laila Bekhet, Jenny Blase, Brian Caffo, Hao Chang, Zeyuan Chen, Jiandong Chen, Jeffrey Chiang, Peter Cho, Robert Cockrell, Parker Combs, Ciara Crosby, Ran Dai, Anseh Danesharasteh, Elif Yildirim, Ryan Demilt, Kaiwen Deng, Sanjoy Dey, Rohan Dhamdhere, Andrew Dickson, Phoebe Dijour, Dong Dinh, Richard Dixon, Albi Domi, Souradeep Dutta, Mirna Elizondo, Zeynep Ertem, Solomon Feuerwerker, Danica Fliss, Jennifer Fowler, Sunyang Fu, Kelly Gardner, Neil Getty, Mohamed Ghalwash, Logan Gloster, Phil Greer, Yuanfang Guan, Colby Ham, Samer Hanoudi, Jeremy Harper, Nathaniel Hendrix, Leeor Hershkovich, Junjie Hu, Yu Huang, Tongtong Huang, Junguk Hur, Monica Isgut, Hamid Ismail, Grant Izmirlian, Kuk Jang, Christianah Jemiyo, Hayoung Jeong, Xiayan Ji, Ming Jiang, Sihang Jiang, Xiaoqian Jiang, Yuye Jiang, Akin Johnson, Zach Analyst, Saarthak Kapse, Uri Kartoun, Dukka KC, Zahra Fard, Tim Kosfeld, Spencer Krichevsky, Mike Kuo, Dale Larie, Lauren Lederer, Shan Leng, Hongyang Li, Jianfu Li, Tiantian Li, Xinwen Liang, Hengyue Liang, Feifan Liu, Daniel Liu, Gang Luo, Ravi Madduri, Vithal Madhira, Shivali Mani, Farzaneh Mansourifard, Robert Matson, Vangelis Metsis, Pablo Meyer, Catherine Mikhailova, Dante Miller, Christopher Milo, Gourav Modanwal, Ronald Moore, David Morgenthaler, Rasim Musal, Vinit Nalawade, Rohan Narain, Saideep Narendrula, Alena Obiri, Satoshi Okawa, Chima Okechukwu, Toluwanimi Olorunnisola, Tim Ossowski, Harsh Parekh, Jean Park, Saaya Patel, Jason Patterson, Chetan Paul, Le Peng, Diana Perkins, Suresh Pokharel, Dmytro Poplavskiy, Zach Pryor, Sarah Pungitore, Hong Qin, Salahaldeen Rababa, Mahbubur Rahman, Elior Rahmani, Gholamali Rahnavard, Md Raihan, Suraj Rajendran, Sarangan Ravichandran, Chandan Reddy, Abel Reyes, Ali Roghanizad, Sean Rouffa, Xiaoyang Ruan, Arpita Saha, Sahil Sawant, Melody Schiaffino, Diego Seira, Saurav Sengupta, Ruslan Shalaev, Linh Shinguyen, Karnika Singh, Soumya Sinha, Damien Socia, Halen Stalians, Charalambos Stavropoulos, Jan Strube, Devika Subramanian, Jiehuan Sun, Ju Sun, Chengkun Sun, Prathic Sundararajan, Salmonn Talebi, Edward Tawiah, Jelena Tesic, Mikaela Thiess, Raymond Tian, Luke Torre-Healy; Ming-Tse Tsai, David Tyus, Madhurima Vardhan, Benjamin Walzer, Jacob Walzer, Junda Wang, Lu Wang, Will Wang, Jonathan Wang, Yisen Wang, Chad Weatherly, Fanyou Wu, Yifeng Wu, Hao Yan, Zhichao Yang, Biao Ye, Rui Yin, Changyu Yin, Yun Yoo, Albert You, June Yu, Martin Zanaj, Zachary Zaiman, Kai Zhang, Xiaoyi Zhang, Tianmai Zhang, Degui Zhi, Yishan Zhong, Huixue Zhou, Andrea Zhou, Yuanda Zhu, Sophie Zhu, Meredith Adams, Caleb Alexander, Benjamin Amor, Alfred Anzalone, Benjamin Bates, Will Beasley, Tellen Bennett, Mark Bissell, Eilis Boudreau, Samuel Bozzette, Katie Bradwell, Carolyn Bramante, Don Brown, Penny Burgoon, John Buse, Tiffany Callahan, Kenrick Cato, Scott Chapman, Christopher Chute, Jaylyn Clark, Marshall Clark, Will Cooper, Lesley Cottrell, Karen Crowley, Mariam Deacy, Christopher Dillon, David Eichmann, Mary Emmett, Rebecca Erwin-Cohen, Patricia Francis, Evan French, Rafael Fuentes, Davera Gabriel, Joel Gagnier, Nicole Garbarini, Jin Ge, Kenneth Gersing, Andrew Girvin, Valery Gordon, Alexis Graves, Justin Guinney, Melissa Haendel, J.W. Hayanga, Brian Hendricks, Wenndy Hernandez, Elaine Hill, William Hillegass, Stephanie Hong, Dan Housman, Robert Hurley, Jessica Islam, Randeep Jawa, Steve Johnson, Rishi Kamaleswaran, Warren Kibbe, Farrukh Koraishy, Kristin Kostka, Michael Kurilla, Adam Lee, Harold Lehmann, Hongfang Liu, Charisse Madlock-Brown; Sandeep Mallipattu, Amin Manna, Federico Mariona, Emily Marti, Greg Martin, Jomol Mathew, Diego Mazzotti, Julie McMurry, Hemalkumar Mehta, Sam Michael, Robert Miller, Leonie Misquitta, Richard Moffitt, Michele Morris, Kimberly Murray, Lavance Northington, Shawn O’Neil, Amy Olex, Matvey Palchuk, Brijesh Patel, Rena Patel, Philip Payne, Jami Pincavitch, Lili Portilla, Fred Prior, Saiju Pyarajan, Lee Pyles, Nabeel Qureshi, Peter Robinson, Joni Rutter, Ofer Sadan, Nasia Safdar, Amit Saha, Joel Saltz, Mary Saltz, Clare Schmitt, Soko Setoguchi, Noha Sharafeldin, Anjali Sharathkumar, Usman Sheikh, Hythem Sidky, George Sokos, Andrew Southerland, Heidi Spratt, Justin Starren, Vignesh Subbian, Christine Suver, Cliff Takemoto, Meredith Temple-O'Connor, Umit Topaloglu, Satyanarayana Vedula, Anita Walden, Kellie Walters, Cavin Ward-Caviness, Adam Wilcox, Ken Wilkins, Andrew Williams, Chunlei Wu, Elizabeth Zampino, Xiaohan Zhang, and Richard Zhu

Subjects
Long COVID, PASC, Machine learning, COVID-19, Evaluation, Community challenge, Medicine, Medicine (General), R5-920
Abstract

Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Published
2024
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25. Stigmatizing attitudes and beliefs about obesity among dental team members

Author

Zanab Malik, Kathryn Williams, Deborah Cockrell, and Clare E. Collins

Subjects
attitudes, beliefs about obesity, dental professionals, knowledge, support staff, weight stigma, Internal medicine, RC31-1245
Abstract

Abstract Background Weight stigma is prevalent within healthcare settings and is an aspect of the lived experience of people living with obesity. There is international evidence of weight stigma in the dental setting, where currently there is also evidence indicating limited training amongst dental professionals regarding obesity or obesity‐related stigma. There has been Australian research and none have included dental support staff. Aims This cross‐sectional survey aimed to assess stigmatizing attitudes and beliefs of dental professionals (registered general dentists, oral health therapists) and support staff (dental assistants, dental receptionists) working in private and public regional practices in New South Wales and specialists in Special Needs Dentistry across Australia toward people living with obesity. Methods An anonymous electronic validated survey was administered through REDCap™ to assess stigmatizing attitudes and beliefs held amongst respondents in relation to people living with obesity. Results Fifty‐three participants completed the survey (n = 33 clinicians, n = 20 support staff). The majority 47/53 (88.7%) held positive attitudes toward people living with obesity. Of the clinicians, 15/33 (45.5%) reported 1 hour or less and 14/33 (42.4%) reported two to 5 hours of obesity‐related education. 14/20 (70%) of the support staff reported no prior education or training about obesity. Of responses reflecting weight stigma, only three clinicians reported negative reactions toward the appearance, or discomfort during examination, of a patient with obesity, or a perception of laziness, compared with normal weight individuals. A higher proportion 4/20 (20%) of support staff reported responses indicating negative attitudes for people with obesity compared with normal weight individuals. Conclusion Survey responses reflected evidence of weight stigma in both dental professionals and support staff. Professional development targeting weight stigma reduction in the dental setting is needed for both clinicians and support staff.

Published
2024
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26. Double universality of the transition in the supercritical state

Author

Cockrell, Cillian and Trachenko, Kostya

Subjects
Condensed Matter - Statistical Mechanics, Condensed Matter - Disordered Systems and Neural Networks, Condensed Matter - Soft Condensed Matter
Abstract

Universality aids consistent understanding of physical properties. This includes understanding the states of matter where a theory predicts how a property of a phase (solid, liquid, gas) changes with temperature or pressure. Here, we show that the matter above the critical point has a remarkable double universality not limited by pressure and temperature. The first universality is the transition between the liquidlike and gaslike states seen in the crossover of the specific heat on the dynamical length scale in deeply supercritical state and characterised by a fixed inversion point. The second universality is the operation of this effect in many supercritical fluids, including N$_2$, CO$_2$, Pb, H$_2$0 and Ar. Despite the differences in structure and chemical bonding in these fluids, the transition has the same fixed inversion point deep in the supercritical state. This provides new understanding of the supercritical state previously considered to be a featureless area on the phase diagram and a theoretical guide for improved and more efficient deployment of supercritical fluids in green and environmental applications.

Published
2022
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27. Facilitating automated conversion of scientific knowledge into scientific simulation models with the Machine Assisted Generation, Calibration, and Comparison (MAGCC) Framework

Author

Cockrell, Chase, Christley, Scott, and An, Gary

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

The Machine Assisted Generation, Comparison, and Calibration (MAGCC) framework provides machine assistance and automation of recurrent crucial steps and processes in the development, implementation, testing, and use of scientific simulation models. MAGCC bridges systems for knowledge extraction via natural language processing or extracted from existing mathematical models and provides a comprehensive workflow encompassing the composition of scientific models and artificial intelligence (AI) assisted code generation. MAGCC accomplishes this through: 1) the development of a comprehensively expressive formal knowledge representation knowledgebase, the Structured Scientific Knowledge Representation (SSKR) that encompasses all the types of information needed to make any simulation model, 2) the use of an artificially intelligent logic reasoning system, the Computational Modeling Assistant (CMA), that takes information from the SSKR and generates, in a traceable fashion, model specifications across a range of simulation modeling methods, and 3) the use of the CMA to generate executable code for a simulation model from those model specifications. The MAGCC framework can be customized any scientific domain, and future work will integrate newly developed code-generating AI systems., Comment: 20 Pages, 8 Figures, 5 Tables

Published
2022

28. A Five-Step Stakeholder Communication Plan for More Effective Natural Resource Management

Author

Brown, Hannah O., Jacobson, Susan K., Cockrell, Marcy, Sutt, Jessica, Allen, Katherine, and Copeland, Amy

Abstract

Effectively communicating with diverse groups involved in environmental management is critical to facilitating successful projects. This five-step communication plan is designed to enable resource managers and extension professionals to successfully engage their stakeholders. This plan, which uses oyster reef management as an example, was informed by two primary sources: an expert meeting with stakeholder leaders and coastal residents and a review of relevant literature. By incorporating stakeholder input throughout the planning and implementation of natural resource management projects, new and innovative ideas emerge, and relationships between stakeholders, managers, and extension agents are strengthened.

Published
2021

29. Stochastic Thermodynamics in a Non-Markovian Dynamical System

Author

Cockrell, Cillian and Ford, Ian J

Subjects
Condensed Matter - Statistical Mechanics
Abstract

The developing field of stochastic thermodynamics extends concepts of macroscopic thermodynamics such as entropy production and work to the microscopic level of individual trajectories taken by a system through phase space. The scheme involves coupling the system to an environment - typically a source of Markovian noise that affects the dynamics of the system. Here we extend this framework to consider a non-Markovian environment, one whose dynamics have memory and which create additional correlations with the system variables, and illustrate this with a selection of simple examples. Such an environment produces a rich variety of behaviours. In particular, for a case of thermal relaxation, the distributions of entropy produced under the non-Markovian dynamics differ from the equivalent case of Markovian dynamics only by a delay time. When a time-dependent external work protocol is turned on, the system's correlations with the environment can either assist or hinder its approach to equilibrium, and affect its production of entropy, depending on the coupling strength between the system and environment., Comment: 13 pages, 9 figures

Published
2022
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33. Bi-objective model for community detection in weighted complex networks

Author

Gilberto Sinuhe Torres-Cockrell, Roman Anselmo Mora-Gutiérrez, Eric Alfredo Rincón-García, Edwin Montes-Orozco, Sergio Gerardo de-los-Cobos-Silva, Pedro Lara-Velazquez, and Miguel Ángel Gutiérrez-Andrade

Subjects
complex networks, k_core, multi-objective, NSGAII, MOSA, Computer engineering. Computer hardware, TK7885-7895, Systems engineering, TA168
Abstract

In this study, we introduce an innovative approach that utilizes complex networks and the k_core method to address community detection in weighted networks. Our proposed bi-objective model aims to simultaneously discover non-overlapping communities while ensuring that the degree of similarity remains below a critical threshold to prevent network degradation. We leverage the k_core structure to detect tightly interconnected node groups, a concept particularly valuable in edge-weighted networks where different edge weights indicate the strength or importance of node relationships. Beyond maximizing the count of k_core communities, our model seeks a homogeneous weight distribution across edges within these communities, promoting stronger cohesion. To tackle this challenge, we implement two multi-target algorithms: Non-dominated Sorting Genetic Algorithm II (NSGAII) and a Multi-Objective Simulated Annealing (MOSA) algorithm. Both algorithms efficiently identify non-overlapping communities with a specified degree 'k'. The results of our experiments reveal a trade-off between maximizing the number of k_core communities and enhancing the homogeneity of these communities in terms of their minimum weighted interconnections. Notably, the MOSA algorithm outperforms NSGAII in both small and large instances, demonstrating its effectiveness in achieving this balance. This approach sheds light on effective strategies for resolving conflicting goals in community detection within weighted networks.

Published
2024
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34. Regulators of rDNA array morphology in fission yeast.

Author

Alexandria J Cockrell, Jeffrey J Lange, Christopher Wood, Mark Mattingly, Scott M McCroskey, William D Bradford, Juliana Conkright-Fincham, Lauren Weems, Monica S Guo, and Jennifer L Gerton

Subjects
Genetics, QH426-470
Abstract

Nucleolar morphology is a well-established indicator of ribosome biogenesis activity that has served as the foundation of many screens investigating ribosome production. Missing from this field of study is a broad-scale investigation of the regulation of ribosomal DNA morphology, despite the essential role of rRNA gene transcription in modulating ribosome output. We hypothesized that the morphology of rDNA arrays reflects ribosome biogenesis activity. We established GapR-GFP, a prokaryotic DNA-binding protein that recognizes transcriptionally-induced overtwisted DNA, as a live visual fluorescent marker for quantitative analysis of rDNA organization in Schizosaccharomyces pombe. We found that the morphology-which we refer to as spatial organization-of the rDNA arrays is dynamic throughout the cell cycle, under glucose starvation, RNA pol I inhibition, and TOR activation. Screening the haploid S. pombe Bioneer deletion collection for spatial organization phenotypes revealed large ribosomal protein (RPL) gene deletions that alter rDNA organization. Further work revealed RPL gene deletion mutants with altered rDNA organization also demonstrate resistance to the TOR inhibitor Torin1. A genetic analysis of signaling pathways essential for this resistance phenotype implicated many factors including a conserved MAPK, Pmk1, previously linked to extracellular stress responses. We propose RPL gene deletion triggers altered rDNA morphology due to compensatory changes in ribosome biogenesis via multiple signaling pathways, and we further suggest compensatory responses may contribute to human diseases such as ribosomopathies. Altogether, GapR-GFP is a powerful tool for live visual reporting on rDNA morphology under myriad conditions.

Published
2024
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35. Exploring Nurse Educators' Self-Reflections of Simulation Facilitator Competency

Author

Rebecca Kaye Cockrell

Abstract

The purpose of this study was to explore nurse educators' self-reflections of simulation facilitator competency. Additionally, the study explored nurse educators' self-reflections of a simulation experience using reflection on action. The study was designed using a phenomenological qualitative approach. Data were obtained by purposive sampling using guided semi-structured interviews online. Data were auto-coded using NVivo software and hand-coded using an adapted coding process. Seven nurse educators participated. All participants self-assessed personal simulation facilitator competency at a level of competent or higher. Three themes emerged: (a) simulation facilitator competency self-assessment is related to the simulation facilitator management of the student learner, (b) simulation facilitator competency is related to the management of self, and (c) simulation challenges communication. Simulation facilitators' challenges center around communication issues, specifically communication with self, student learners, and others. The study findings highlight the importance of communication, although study results did not indicate that initial or ongoing simulation facilitator training was something the participants verbally recommended. It is crucial to prioritize communication skills, as even trained and seasoned facilitators face obstacles in this area. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2023

36. Exploring Experiences of African American Women Ascending to Leadership Positions in Higher Education

Author

Jordan A. Cockrell

Abstract

African American women have been underrepresented in top leadership positions in colleges and universities, facing social challenges and systems of oppression related to race, class, gender, and marginalization as they strived to advance to top leadership positions. This basic qualitative study, investigating the perceptions of 12 African American women from various parts of the United States who have attained leadership positions in higher education, helped to identify the contributing factors to the disproportionate representation of African American women in leadership roles. Black feminist thought, as outlined by Collins, served as the conceptual framework for this research, focusing specifically on the journeys of Black women into top leadership positions and their experiences upon securing these roles. Semi-structured interviews were conducted to gather data and interpret the findings using Merriam and Tisdell's six-step approach. The African American women participating in this research identified several factors contributing to the underrepresentation of African American women in top leadership positions. These included experiences related to visibility, institutional practices, management of external expectations, encounters with discrimination, and the receipt of various types of support. The insights derived from this research can guide institutional leaders in reassessing and refining their practices, policies, and strategies, thereby fostering more equitable and inclusive leadership experiences and opportunities for African American women aspiring to top leadership positions. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2023

37. Teachers' Perceptions of Teacher Incentives on District Attendance Incentive Programs and Their Impact on Improving Overall Teacher Attendance

Author

Ginger Hearon Cockrell

Abstract

Teacher absenteeism is a problem that needs a solution. It is imperative that teachers come to work each day to prepare their students for academic achievement. If teachers are chronically absent from work, the students' academic achievement suffers. There needs to be a way to minimize teacher absences. School districts must track data that shows teacher absences in order to get a clear picture of when and where the absences are the greatest problem. A review of the literature identified several studies conducted over the years that document the effects of teacher absenteeism. With this in mind, it is recommended that incentives be put in place to reduce the absences of the teachers. I furthered the research to include data from a school district by researching teacher perceptions of the use of teacher attendance incentives in the school district. The purpose of this study was to determine which schools within the school district have Incentive programs in place to motivate teachers to come to work. Existing attendance data was obtained to analyze the attendance of the teachers at each building. The teachers were then surveyed to identify the incentives that are in place at each building and the teachers' perceptions of those incentives. The surveys conducted also assisted in determining if the attendance incentives that are used as motivation are effective to motivate teachers to attend work. The results of the teachers' perceptions of the incentive program at each school will be compared with the teacher attendance data to determine which teacher attendance incentives are effective in motivating teachers to attend work as scheduled. The incentives that are the most effective will be shared with each principal in the district to utilize in maintaining better teacher attendance throughout the school district. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]

Published
2023

39. Six-Month Outcomes of Mechanical Thrombectomy for Treating Deep Vein Thrombosis: Analysis from the 500-Patient CLOUT Registry

Author

Shaikh, Abdullah, Zybulewski, Adam, Paulisin, Joseph, Bisharat, Mohannad, Mouawad, Nicolas J., Raskin, Adam, Ichinose, Eugene, Abramowitz, Steven, Lindquist, Jonathan, Azene, Ezana, Shah, Neil, Nguyen, James, Cockrell, Josh, Khalsa, Bhavraj, Khetarpaul, Vipul, Murrey, Jr., Douglas A., Veerina, Kalyan, Skripochnik, Edvard, Maldonado, Thomas S., Bunte, Matthew C., Annambhotla, Suman, Schor, Jonathan, Kado, Herman, Mojibian, Hamid, and Dexter, David

Published
2023
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41. Transition in the supercritical state of matter: experimental evidence

Author

Cockrell, Cillian, Brazhkin, Vadim V., and Trachenko, Kostya

Subjects
Condensed Matter - Soft Condensed Matter
Abstract

A large and mostly unexplored part of the phase diagram lies above the critical point. The supercritical matter was traditionally believed to be physically homogeneous with no discernible differences between liquidlike and gaslike states. More recently, several proposals have been put forward challenging this view, and here we review the history of this research. Close to the critical point, persisting critical anomalies enable the separation of the supercritical state into two different states. About a decade ago, it was proposed that the Frenkel line (FL), corresponding to the dynamical transition of particle motion and related thermodynamic and structural transitions, gives a unique and path-independent way to separate the supercritical states into two qualitatively different states and extends to arbitrarily high pressure and temperature on the phase diagram. Here, we review several lines of enquiry that followed. We focus on the experimental evidence of transitions in deeply supercritical Ne, N$_2$, CH$_4$, C$_2$H$_6$, CO$_2$ and H$_2$O at the FL detected by a number of techniques including X-ray, neutron and Raman scattering experiments. %Except for H$_2$O, these experiments were stimulated by the FL and followed the state points of the FL mapped in preceding calculations. We subsequently summarise other developments in the field, including recent extensions of analysis of dynamics at the FL, quantum simulations, topological and geometrical approaches as well as universality of properties at the FL. Finally, we review current theoretical understanding of the supercritical state and list open problems in the field.

Published
2021
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42. Mathematics Enrichment Camp Experiences Amid the COVID-19 Pandemic: Teacher Voices and Perspectives

Author

Grossie, Elizabeth, Cockrell, Lerri, Davis, Natalie, and Beaulieu, Patricia

Abstract

This article discusses how mathematics teachers seized the opportunity to keep the mathematics component of STEM camp on track by transforming the camp into a virtual camp themed "Out of this World." Teachers and camp interns encountered technical, social, and instructional challenges in transitioning to a digital platform while preserving the integrity of the prior learning experiences. Such challenges presented opportunities for collaborative and innovative resolutions as well as personal and professional growth. The lived experiences presented a need for a vector from instructional theory to practice and resulted in the development of an authentic professional learning community. The voices of these educators speak hope and promise for mathematics teachers answering the call to remote learning.

Published
2020

44. Mechanical Thrombectomy vs. Pharmacomechanical Catheter Directed Thrombolysis for the Treatment of Iliofemoral Deep Vein Thrombosis: A Propensity Score Matched Exploratory Analysis of 12 Month Clinical Outcomes

Author

Dexter, David, Beasley, Robert, Zybulewski, Adam, Ayo, Diego, Cosme-Montalvo, Octavio, King, Christopher, Cockrell, Joshua, Hnath, Jeffery, Shaikh, Abdullah, Paulisin, Joseph, Shah, Neil, Skripochnik, Edvard, Trestman, Eric, Schutzer, Richard, Azene, Ezana, O’Connor, David, Lodha, Ankur, Elmasri, Fakhir, Moomey, Charles, Annambhotla, Suman, Nguyen, James, Mouawad, Nicolas, Abramowitz, Steven, Bisharat, Mohannad, Raskin, Adam, Angel, Wesley, Roberts, Jon, Kado, Herman, Schor, Jonathan, Zia, Saqib, Maldonado, Thomas, Ichinose, Eugene, Veerina, Kaylan, Gandhi, Sagar, Murrey, Douglas, Bunte, Matthew, Khalsa, Bhavraj, Jung, Matthew, Long, Daniel, Ford, Robert, Winokur, Ronald, Noor, Sonya, Plotnik, Adam, Lindquist, Jonathan, Bhat, Ambarish, Harlin, Stuart, Khetarpaul, Vipul, Sanchez, Luis, Li, Shuo, Long, Graham, Mojibian, Hamid, Bunte, Matthew C., Maldonado, Thomas S., Mouawad, Nicolas J., and Dexter, David J.

Published
2024
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45. Universal interrelation between dynamics and thermodynamics of fluids: dynamically-driven 'c'-transition

Author

Cockrell, Cillian, Brazhkin, Vadim V., and Trachenko, Kostya

Subjects
Condensed Matter - Statistical Mechanics
Abstract

Our first very wide survey of the supercritical phase diagram and its key properties reveals a universal interrelation between dynamics and thermodynamics and an unambiguous transition between liquidlike and gaslike states. This is seen in the master plot showing a collapse of the data representing the dependence of specific heat on key dynamical parameters in the system for many different paths on the phase diagram. As a result, the observed transition is path-independent. We call it a "c"-transition due to the "c"-shaped curve parameterizing the dependence of the specific heat on key dynamical parameters. The "c"-transition has a fixed inversion point and provides a new structure to the phase diagram, operating deep in the supercritical state (up to at least 2000 times the critical pressure and 50 times the critical temperature). The data collapse and path independence as well as the existence of a special inversion point on the phase diagram are indicative of either of a sharp crossover or a new phase transition in the deeply supercritical state., Comment: 9 pages, 8 figures

Published
2021
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46. Children are small adults (when properly normalized): Transferrable/generalizable sepsis prediction

Author

Caitlin Marassi, BA, Damien Socia, MS, Dale Larie, BS, Gary An, MD, and R. Chase Cockrell, PhD

Subjects
Machine learning, Sepsis, Pediatric sepsis, Surgery, RD1-811
Abstract

Background: Though governed by the same underlying biology, the differential physiology of children causes the temporal evolution from health to a septic/diseased state to follow trajectories that are distinct from adult cases. As pediatric sepsis data sets are less readily available than for adult sepsis, we aim to leverage this shared underlying biology by normalizing pediatric physiological data such that it would be directly comparable to adult data, and then develop machine-learning (ML) based classifiers to predict the onset of sepsis in the pediatric population. We then externally validated the classifiers in an independent adult dataset. Methods: Vital signs and laboratory observables were obtained from the Pediatric Intensive Care (PIC) database. These data elements were normalized for age and placed on a continuous scale, termed the Continuous Age-Normalized SOFA (CAN-SOFA) score. The XGBoost algorithm was used to classify pediatric patients that are septic. We tested the trained model using adult data from the MIMIC-IV database. Results: On the pediatric population, the sepsis classifier has an accuracy of 0.84 and an F1-Score of 0.867. On the adult population, the sepsis classifier has an accuracy of 0.80 and an F1-score of 0.88; when tested on the adult population, the model showed similar performance degradation (“data drift”) as in the pediatric population. Conclusions: In this work, we demonstrate that, using a straightforward age-normalization method, EHR's can be generalizable compared (at least in the context of sepsis) between the pediatric and adult populations.

Published
2023
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47. Managing comorbidities in chronic kidney disease reduces utilization and costs

Author

Yong Li, Kanchan Barve, Meghan Cockrell, Amal Agarwal, Adrianne Casebeer, Suzanne W. Dixon, and Insiya Poonawalla

Subjects
Chronic kidney disease, Healthcare resource utilization, Diabetes care, Hypertension, Care coordination, Managed care, Public aspects of medicine, RA1-1270
Abstract

Abstract Background Effective management of comorbid diabetes and hypertension in patients with chronic kidney disease (CKD) is important for optimal outcomes. However, little is known about this relationship from a health plan perspective. The objective of this study was to evaluate the association of effective management of comorbid diabetes and/or hypertension with healthcare resource utilization (HCRU) in patients with chronic kidney disease (CKD). Methods This retrospective cohort study used the Humana Research Database to identify patients with CKD Stage ≥ 3a in 2017. Eligible patients were enrolled in a Medicare Advantage Prescription Drug plan for ≥ 12 months before and after the index date (first observed evidence of CKD). Patients with end-stage renal disease, kidney transplant, or hospice election preindex were excluded. Recommended comorbid disease management included hemoglobin A1c monitoring; adherence to glucose-lowering, cardiovascular, and angiotensin-converting enzyme inhibitors/angiotensin receptor blocker medications; and nephrologist/primary care provider (PCP) visits. HCRU was evaluated for 12 months postindex. Results The final cohort of 241,628 patients was 55% female and 77% White, with an average age of 75 years. Approximately 90% of patients had Stage 3 CKD. Half had both diabetes and hypertension, and most of the remaining half had hypertension without diabetes. Patients meeting the criteria for good disease management, compared with patients not meeting those criteria, were less likely to experience an inpatient hospitalization, by as much as 40% depending on the criterion and the comorbidities present, or an emergency department visit, by as much as 30%. Total monthly healthcare costs were as much as 17% lower. Conclusions Management of comorbid diabetes and hypertension in patients with CKD was associated with lower HCRU and costs. Care coordination programs targeting patients with CKD must give careful attention to glucose and blood pressure control. Trial registration Not applicable.

Published
2023
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