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1. Southern African synoptic climate dynamics and future change : tropical lows and the Congo Air Boundary

Author

Howard, Emma and Washington, Richard

Subjects
551.57, Climate Science, Atmospheric Science
Abstract

Southern Africa's development and economy is dependent on a rainfall resource that is projected to decline in coming decades as a result of anthropogenic climate change. This rainfall decline has been attributed to a half month delay in the onset of the wet season by the end of the \nth{21} century based on RCP8.5 projections, shortening the growing season and reducing the agricultural viability of the region. Yet many aspects of the basic climatological state of the southern African atmosphere remain chronically understudied. Rainfall onset and regional rainfall climate depend on the behaviour of day-to-day weather systems along the southern margin of the African rain belt. However, the dynamics of these systems are not well understood. This thesis addresses this problem by characterising the frequencies, spatial distributions, dynamics, interannual variability and future change of two classes of weather systems: tropical lows and the Congo Air Boundary (CAB). A vortex tracking algorithm is optimised to detect tropical lows in sub-daily reanalysis data and climate model output. It is found that tropical lows aggregate to form the synoptic expression of the summer Angola Low. Tropical lows are shown to exhibit a unique anchoring behaviour in Angola due to interactions with nocturnal low-level jets associated with differential surface heating. 70% of rainfall in south-east Angola and 31% of summer rainfall across the southern African tropical margin is attributed to tropical lows. Meanwhile, the majority of interannual rainfall variability in Angola, northern Namibia and western Zambia derives largely from tropical lows. Climate model projections indicate that tropical lows will become 15% less frequent by the end of the 21st century. Future change in the spatial distribution of tropical lows contributes to model disagreement over the spatial pattern of rainfall change in the summer season. Computational edge detection is applied to identify surface drylines and convergence lines associated with the CAB, a forgotten feature of the southern African climatology. The CAB is shown to be a sharp discontinuity which marks the southern edge of the African rain belt, and is detected on at least 80\% of days from August to October. Its seasonal southward progression over southern Africa is presented, and a close dynamic link between the CAB and the Angola Heat Low is demonstrated. Seasonal rainfall variability is closely linked to the CAB, since tropical rainfall does not occur to the south of the CAB, with CAB variability explaining at least 55% of local monthly rainfall variability. The projected delayed wet season onset is shown to be related to a projected 0.7° CAB latitude increase and a 13% CAB frequency increase from October to December, with inter-model CAB variability explaining 46% of inter-model variance in projected rainfall change.

Published
2019

3. Contrasting Prediction Methods for Early Warning Systems at Undergraduate Level

Author

Howard, Emma, Meehan, Maria, and Parnell, Andrew

Subjects
Mathematics - History and Overview
Abstract

In this study, we investigate prediction methods for an early warning system for a large STEM undergraduate course. Recent studies have provided evidence in favour of adopting early warning systems as a means of identifying at-risk students. Many of these early warning systems rely on data from students' engagement with Learning Management Systems (LMSs). Our study examines eight prediction methods, and investigates the optimal time in a course to apply an early warning system. We present findings from a statistics university course which has a large proportion of resources on the LMS Blackboard and weekly continuous assessment. We identify weeks 5-6 of our course (half way through the semester) as an optimal time to implement an early warning system, as it allows time for the students to make changes to their study patterns whilst retaining reasonable prediction accuracy. Using detailed (fine-grained) variables, clustering and our final prediction method of BART (Bayesian Additive Regressive Trees) we are able to predict students' final grade by week 6 based on mean absolute error (MAE) to 6.5 percentage points. We provide our R code for implementation of the prediction methods used in a GitHub repository.

Published
2016

7. The effect of effort and individual differences on the implicit sense of agency

Author

Howard, Emma

Subjects
616.85
Abstract

The experience of feeling responsible for the outcomes of one's actions is known as the sense of agency. The phenomenon of reduced perceived temporal proximity between actions and their effects is thought to implicitly index the sense of agency, and is known as temporal or intentional binding. The optimal cue integration account indicates that the sense of agency is dependent of the integration of several cues. This thesis uses temporal binding to investigate instances which afford cues that may hinder the generation of agency. Chapters 3 and 4 examine the modulatory roles of physical and mental effort finding that the implicit sense of agency reduced under physical and mental strain. In Chapter 5, electroencephalography was used to investigate the influence of mental effort on neural response to action outcomes. Concordant with previous findings, neural responses to self-generated outcomes were reduced (i.e. attenuated readiness potentials and N1 components), however, the effect of effort was less reliable, providing limited evidence for the role of individual task difficulty on the attenuation of the readiness potential. Chapter 6 found that high levels of (subclinical) schizotypy weakened the sense of agency, whereby temporal binding was less distinguished across conditions of agency and no agency. In Chapter 7, it was shown that the affective content of social stimuli did not modulate temporal binding, nor did individual differences in social anxiety. Overall, these findings support the notion that the sense of agency is dependent on the availability of cognitive resources, and in contexts in which agency cues concurrently deplete these resources, either by physical or mental effort, or in individuals with tendencies to attribute agency inappropriately, agency is weakened. Nevertheless, the lack of modulation by emotional stimuli and by anxiety provide informative boundary conditions for these effects. Beyond contributing to our understanding of this key aspect of human experience, work in this area could influence how society considers responsibility in everyday life and in law, and how aberrant experiences of agency can be understood in disease.

Published
2016

9. chapter 9: ON HIGH PRECIPITATION IN MOZAMBIQUE, ZIMBABWE, AND ZAMBIA IN FEBRUARY 2018: This multi-method study of high precipitation over parts of Mozambique, Zimbabwe, and parts of Zambia in February 2018 indicates decreased likelihood of such events due to climate change, but with substantial uncertainty based on the used observations and models

Author

Fuckar, Neven S., Otto, Friederike E.L., Lehner, Flavio, Pinto, Izidine, Howard, Emma, Sparrow, Sarah, Li, Sihan, and Wallom, David

Subjects
Precipitation (Meteorology) -- Environmental aspects, Business, Earth sciences
Abstract

Precipitation in southern Africa displays a notable zonal gradient (south of about 15[degrees]S there is a dominant contrast between dry west and wet east) and is characterized by a pronounced [...]

Published
2020
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10. Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1.

Author

Howard, Emma, Su, Chun-Hsu, Stassen, Christian, Naha, Rajashree, Ye, Harvey, Pepler, Acacia, Bell, Samuel S., Dowdy, Andrew J., Tucker, Simon O., and Franklin, Charmaine

Subjects
*ATMOSPHERIC models, *DOWNSCALING (Climatology), *CLIMATE change models, *EFFECT of human beings on climate change, *ATMOSPHERIC temperature, *TROPICAL cyclones
Abstract

Anthropogenic climate change is changing the Earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose of investigating future hazards. BARPA-R, a limited-area model, has a 17 km horizontal grid spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA5 reanalysis. Here, an assessment of this evaluation experiment is provided. Performance-based evaluation results are benchmarked against ERA5, with comparable performance between the free-running BARPA-R simulations and observationally constrained reanalysis interpreted as a good result. First, an examination of BARPA-R's representation of Australia's surface air temperature, precipitation, and 10 m winds finds good performance overall, with biases including a 1 ∘ C cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm per month in inland Australia. Recent trends in daily maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in precipitation show underestimated wetting in northern Australia. Precipitation and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10 m winds are improved over ERA5 in six out of eight of the Australian regions considered. Secondly, the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the South Pacific Convergence Zone (SPCZ), the Northwest Cloudband, and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extratropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 global climate models (GCMs). [ABSTRACT FROM AUTHOR]

Published
2024
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14. Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Akeredolu, Alimatu-Sadia, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Aojula, Sonam, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Chatterjee, Shaunak, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, De Waal, Hanelie, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Hussain, Ifrah, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Sopian, Aninditya Salma, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Van Den Tooren, Harriet, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Published
2020
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15. The Analysis of Teaching of Medical Schools (AToMS) survey: an analysis of 47,258 timetabled teaching events in 25 UK medical schools relating to timing, duration, teaching formats, teaching content, and problem-based learning

Author

Devine, Oliver Patrick, Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Akeredolu, Alimatu-Sadia, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Aojula, Sonam, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Chatterjee, Shaunak, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, De Waal, Hanelie, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Hussain, Ifrah, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Sopian, Aninditya Salma, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Van Den Tooren, Harriet, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and McManus, I. C.

Published
2020
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17. Evaluation of multi-season convection permitting atmosphere - mixed layer ocean simulations of the Maritime Continent.

Author

Howard, Emma, Woolnough, Steven, Klingaman, Nicholas, Shipley, Daniel, Sanchez, Claudio, Peatman, Simon C., Birch, Cathryn E., and Matthews, Adrian J.

Subjects
*MIXING height (Atmospheric chemistry), *OCEAN temperature, *OCEAN, *ATMOSPHERIC models, *ATMOSPHERE, *MARINE west coast climate, *MARITIME boundaries
Abstract

A multi-season convection permitting regional climate simulation of the Maritime Continent using the Met Office Unified Model with 2.2-km grid spacing is presented and evaluated. The simulations pioneer the use of atmosphere-ocean coupling with the multi-column K profile parametrisation (KPP) mixed layer ocean model in atmospheric convection permitting climate simulations. Comparisons are made against a convection parametrised simulation in which it is nested, and which in turn derives boundary conditions from ERA5 reanalysis. This paper describes the configuration, performance of the mean state and variability of the two simulations compared against observational datasets. The models both have minor sea surface temperature (SST) and wet precipitation biases. The diurnal cycle, representation of equatorial waves and relationship between SST and precipitation are all improved in the convection permitting model compared to the convection parametrised model. The MJO is present in both models with a faster than observed propagation speed. However, it is unclear whether fidelity of the MJO simulation is inherent to the model or whether it predominantly arises from the forcing at the boundaries. [ABSTRACT FROM AUTHOR]

Published
2023
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18. Performance and process-based evaluation of the BARPA-R Australasian regional climate model version 1.

Author

Howard, Emma, Chun-Hsu Su, Stassen, Christian, Naha, Rajashree, Ye, Harvey, Pepler, Acacia, Bell, Samuel S., Dowdy, Andrew J., Tucker, Simon O., and Franklin, Charmaine

Subjects
*ATMOSPHERIC models, *DOWNSCALING (Climatology), *EFFECT of human beings on climate change, *ATMOSPHERIC temperature, *ATMOSPHERIC circulation, *TROPICAL cyclones
Abstract

Anthropogenic climate change is changing the earth system processes that control the characteristics of natural hazards both globally and across Australia. Model projections of hazards under future climate change are necessary for effective adaptation. This paper presents BARPA-R (the Bureau of Meteorology Atmospheric Regional Projections for Australia), a regional climate model designed to downscale climate projections over the Australasian region with the purpose to investigate future hazards. BARPA-R, a limited area model, has a 17 km horizontal grid-spacing and makes use of the Met Office Unified Model (MetUM) atmospheric model and the Joint UK Land Environment Simulator (JULES) land surface model. To establish credibility and in compliance with the Coordinated Regional Climate Downscaling Experiment (CORDEX) experiment design, the BARPA-R framework has been used to downscale ERA-5 reanalysis. Here, an assessment of this evaluation experiment is provided. First, an examination of BARPA-R's representation of Australia's surface air temperature, rainfall and 10-m winds finds good performance overall, with biases including a 1K cold bias in daily maximum temperatures, reduced diurnal temperature range, and wet biases up to 25 mm/month in inland Australia. Recent trends in diurnal maximum temperatures are consistent with observational products, while trends in minimum temperatures show overestimated warming and trends in rainfall show underestimated wetting in northern Australia. Rainfall and temperature teleconnections are effectively represented in BARPA-R when present in the driving boundary conditions, while 10-metre winds are improved over ERA5 in six out of eight of the Australian regions considered. The second section of the paper considers the representation of large-scale atmospheric circulation features and weather systems. While generally well represented, convection-related features such as tropical cyclones, the SPCZ, Northwest Cloud-Bands and the monsoon westerlies show more divergence from observations and internal interannual variability than mid-latitude phenomena such as the westerly jets and extra-tropical cyclones. Having simulated a realistic Australasian climate, the BARPA-R framework will be used to downscale two climate change scenarios from seven CMIP6 GCMs. [ABSTRACT FROM AUTHOR]

Published
2023
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20. Students’ In-class and Out of Class Mathematical Activities

Author

Rasmussen, Chris, Fredriksen, Helge, Howard, Emma, Pepin, Birgit, Rämö, Johanna, Durand-Guerrier, Viviane, Hochmuth, Reinhard, Nardi, Elena, Winsløw, Carl, Department of Mathematics and Statistics, and Mathematics Education Research Group

Subjects
111 Mathematics, 516 Educational sciences
Abstract

In this chapter, the authors zoom in on students’ in-class and out-of-class practices, use of resources out-of-class, role in assessment practices, responses to active learning initiatives, and in-class mathematical practices. They do so with a sharp theoretical focus on situating students’ mathematical practices in relation to interactions with other students, the teacher, the mathematics, and resources. They conclude by considering how future research might engage in cross-pollination of the above themes and they highlight potential benefits from theoretical networking as well as from deploying theories that are appropriate for, but hitherto under-used in, examining students’ in-class and out-of-class practices in complementary ways.

Published
2021

23. The effectiveness of debt relief in mitigating the macroeconomic consequences of natural disasters

Author

Howard, Emma, Murphy, Kean, Nientker, Wouter, El-Ouaghlidi, Karim, and Schmidt, Harry

Subjects
Official development assistance, Deutes – Alleujament, Debt Relief, Natural disasters, Catàstrofes naturals, Treball de fi de màster – Curs 2019-2020
Abstract

Treball fi de màster de: Master's Degree in Specialized Economic Analysis Directors: Fernando Broner ; Manuel García-Santana We employ a dynamic panel fixed effects model to assess the macroeconomic consequences of natural disasters in Africa and the effectiveness of debt relief in promoting post-disaster recovery. Our results show that floods and droughts have a negative contemporaneous effect on GDP growth which, in the case of floods, is recovered at the second lag. General debt relief - consisting of debt forgiveness, rescheduling, and significant increases in ODA - has no impact on economic growth. However, significant increases in ODA in the aftermath of disasters have a positive effect that is increasing in disaster severity, suggesting that it is an effective post-disaster recovery instrument. Debt-to-GDP growth and crop production growth are also considered in the analysis. Las implicancias de los desastres naturales en África y el consecuente alivio de la deuda soberana son los objetos de estudio de este trabajo. Empleamos un modelo de efectos fijos de panel dinámico para evaluar las consecuencias macroeconómicas de los desastres y la eficacia del alivio de la deuda para facilitar la recuperación posterior a los mismos. El alivio general de la deuda - que consiste en la condonación de la deuda, el reescalonamiento y aumentos significativos de la AOD - no tiene repercusiones en el crecimiento económico. Sin embargo, los aumentos significativos de la AOD después de los desastres tienen un efecto positivo que aumenta de acuerdo a la gravedad de los desastres. Esto sugiere que es un instrumento eficaz de recuperación después de los desastres.

Published
2020

24. Additional file 4 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 4. Graphs 1 to 210 (pages 1 to 35).

Published
2020
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25. Additional file 7 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 7. Graphs 631 to 840 (pages 106 to 140).

Published
2020
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26. Additional file 6 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 6. Graphs 421 to 630 (pages 71 to 105).

Published
2020
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27. Additional file 8 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 8. Graphs 841 to 1050 (pages 141 to 175).

Published
2020
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28. Additional file 1 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 1. Figures S1 to S10, and additional text on the causal ordering of variables.

Published
2020
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29. Additional file 5 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 5. Graphs 211 to 420 (pages 36 to 70).

Published
2020
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30. Additional file 3 of Exploring UK medical school differences: the MedDifs study of selection, teaching, student and F1 perceptions, postgraduate outcomes and fitness to practise

Author

McManus, I. C., Harborne, Andrew Christopher, Horsfall, Hugo Layard, Joseph, Tobin, Smith, Daniel T., Marshall-Andon, Tess, Samuels, Ryan, Kearsley, Joshua William, Abbas, Nadine, Baig, Hassan, Beecham, Joseph, Benons, Natasha, Caird, Charlie, Clark, Ryan, Cope, Thomas, Coultas, James, Debenham, Luke, Douglas, Sarah, Eldridge, Jack, Hughes-Gooding, Thomas, Jakubowska, Agnieszka, Jones, Oliver, Lancaster, Eve, MacMillan, Calum, McAllister, Ross, Merzougui, Wassim, Phillips, Ben, Phillips, Simon, Risk, Omar, Sage, Adam, Sooltangos, Aisha, Spencer, Robert, Tajbakhsh, Roxanne, Adesalu, Oluseyi, Aganin, Ivan, Ahmed, Ammar, Aiken, Katherine, Alimatu-Sadia Akeredolu, Alam, Ibrahim, Ali, Aamna, Anderson, Richard, Ang, Jia Jun, Anis, Fady Sameh, Sonam Aojula, Arthur, Catherine, Ashby, Alena, Ashraf, Ahmed, Aspinall, Emma, Awad, Mark, Yahaya, Abdul-Muiz Azri, Badhrinarayanan, Shreya, Bandyopadhyay, Soham, Barnes, Sam, Bassey-Duke, Daisy, Boreham, Charlotte, Braine, Rebecca, Brandreth, Joseph, Carrington, Zoe, Cashin, Zoe, Shaunak Chatterjee, Chawla, Mehar, Chean, Chung Shen, Clements, Chris, Clough, Richard, Coulthurst, Jessica, Curry, Liam, Daniels, Vinnie Christine, Davies, Simon, Davis, Rebecca, Waal, Hanelie De, Desai, Nasreen, Douglas, Hannah, Druce, James, Ejamike, Lady-Namera, Esere, Meron, Eyre, Alex, Fazmin, Ibrahim Talal, Fitzgerald-Smith, Sophia, Ford, Verity, Freeston, Sarah, Garnett, Katherine, General, Whitney, Gilbert, Helen, Gowie, Zein, Grafton-Clarke, Ciaran, Gudka, Keshni, Gumber, Leher, Gupta, Rishi, Harlow, Chris, Harrington, Amy, Heaney, Adele, Ho, Wing Hang Serene, Holloway, Lucy, Hood, Christina, Houghton, Eleanor, Houshangi, Saba, Howard, Emma, Human, Benjamin, Hunter, Harriet, Ifrah Hussain, Hussain, Sami, Jackson-Taylor, Richard Thomas, Jacob-Ramsdale, Bronwen, Janjuha, Ryan, Jawad, Saleh, Jelani, Muzzamil, Johnston, David, Jones, Mike, Kalidindi, Sadhana, Kalsi, Savraj, Kalyanasundaram, Asanish, Kane, Anna, Kaur, Sahaj, Al-Othman, Othman Khaled, Khan, Qaisar, Khullar, Sajan, Kirkland, Priscilla, Lawrence-Smith, Hannah, Leeson, Charlotte, Lenaerts, Julius Elisabeth Richard, Long, Kerry, Lubbock, Simon, Burrell, Jamie Mac Donald, Maguire, Rachel, Mahendran, Praveen, Majeed, Saad, Malhotra, Prabhjot Singh, Mandagere, Vinay, Mantelakis, Angelos, McGovern, Sophie, Mosuro, Anjola, Moxley, Adam, Mustoe, Sophie, Myers, Sam, Nadeem, Kiran, Nasseri, Reza, Newman, Tom, Nzewi, Richard, Ogborne, Rosalie, Omatseye, Joyce, Paddock, Sophie, Parkin, James, Patel, Mohit, Pawar, Sohini, Pearce, Stuart, Penrice, Samuel, Purdy, Julian, Ramjan, Raisa, Randhawa, Ratan, Rasul, Usman, Raymond-Taggert, Elliot, Razey, Rebecca, Razzaghi, Carmel, Reel, Eimear, Revell, Elliot John, Rigbye, Joanna, Rotimi, Oloruntobi, Said, Abdelrahman, Sanders, Emma, Sangal, Pranoy, Grandal, Nora Sangvik, Shah, Aadam, Shah, Rahul Atul, Shotton, Oliver, Sims, Daniel, Smart, Katie, Smith, Martha Amy, Smith, Nick, Aninditya Salma Sopian, South, Matthew, Speller, Jessica, Syer, Tom J., Ta, Ngan Hong, Tadross, Daniel, Thompson, Benjamin, Trevett, Jess, Tyler, Matthew, Ullah, Roshan, Utukuri, Mrudula, Vadera, Shree, Tooren, Harriet Van Den, Venturini, Sara, Vijayakumar, Aradhya, Vine, Melanie, Wellbelove, Zoe, Wittner, Liora, Yong, Geoffrey Hong Kiat, Ziyada, Farris, and Devine, Oliver Patrick

Abstract

Additional file 3. Index and notes on supplementary graphs 1 to 205 (page 1 to 205).

Published
2020
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31. Effect of a Primary Care Walking Intervention with and without Nurse Support on Physical Activity Levels in 45- to 75-Year-Olds: The Pedometer And Consultation Evaluation (PACE-UP) Cluster Randomised Clinical Trial

Author

Harris, Tess, Kerry, Sally M., Limb, Elizabeth S., Victor, Christina R., Iliffe, Steve, Ussher, Michael, Whincup, Peter H., Ekelund, Ulf, Fox-Rushby, Julia, Furness, Cheryl, Anokye, Nana, Ibison, Judith, DeWilde, Steve, David, Lee, Howard, Emma, Dale, Rebecca, Smith, Jaime, and Cook, Derek G.

Subjects
Pedometers -- Usage, Physically disabled persons -- Physiological aspects, Primary health care -- Methods, Biological sciences
Abstract

Background Pedometers can increase walking and moderate-to-vigorous physical activity (MVPA) levels, but their effectiveness with or without support has not been rigorously evaluated. We assessed the effectiveness of a pedometer-based walking intervention in predominantly inactive adults, delivered by post or through primary care nurse-supported physical activity (PA) consultations. Methods and Findings A parallel three-arm cluster randomised trial was randomised by household, with 12-mo follow-up, in seven London, United Kingdom, primary care practices. Eleven thousand fifteen randomly selected patients aged 45-75 y without PA contraindications were invited. Five hundred forty-eight self-reporting achieving PA guidelines were excluded. One thousand twenty-three people from 922 households were randomised between 2012-2013 to one of the following groups: usual care (n = 338); postal pedometer intervention (n = 339); and nurse-supported pedometer intervention (n = 346). Of these, 956 participants (93%) provided outcome data (usual care n = 323, postal n = 312, nurse-supported n = 321). Both intervention groups received pedometers, 12-wk walking programmes, and PA diaries. The nurse group was offered three PA consultations. Primary and main secondary outcomes were changes from baseline to 12 mo in average daily step-counts and time in MVPA (in [greater than or equal to]10-min bouts), respectively, measured objectively by accelerometry. Only statisticians were masked to group. Analysis was by intention-to-treat. Average baseline daily step-count was 7,479 (standard deviation [s.d.] 2,671), and average time in MVPA bouts was 94 (s.d. 102) min/wk. At 12 mo, mean steps/d, with s.d. in parentheses, were as follows: control 7,246 (2,671); postal 8,010 (2,922); and nurse support 8,131 (3,228). PA increased in both intervention groups compared with the control group; additional steps/d were 642 for postal (95% CI 329-955) and 677 for nurse support (95% CI 365-989); additional MVPA in bouts (min/wk) were 33 for postal (95% CI 17-49) and 35 for nurse support (95% CI 19-51). There were no significant differences between the two interventions at 12 mo. The 10% (1,023/10,467) recruitment rate was a study limitation. Conclusions A primary care pedometer-based walking intervention in predominantly inactive 45- to 75-y-olds increased step-counts by about one-tenth and time in MVPA in bouts by about one-third. Nurse and postal delivery achieved similar 12-mo PA outcomes. A primary care pedometer intervention delivered by post or with minimal support could help address the public health physical inactivity challenge. Clinical Trial Registration isrctn.com ISRCTN98538934., Author(s): Tess Harris 1,*, Sally M. Kerry 2, Elizabeth S. Limb 1, Christina R. Victor 3, Steve Iliffe 4, Michael Ussher 1, Peter H. Whincup 1, Ulf Ekelund 5,6, Julia [...]

Published
2017
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36. An exploration of the relationship between continuous assessment and resource use in a service mathematics module

Author

Howard, Emma, Meehan, Maria, Parnell, Andrew, School of Mathematics and Statistics, University College Dublin, Hamilton Institute, Maynooth University, Ireland, National University of Ireland Maynooth (Maynooth University), Insight Centre for Data Analytics, Utrecht University, Uffe Thomas Jankvist, Marja van den Heuvel-Panhuizen, Michiel Veldhuis, and Veldhuis, Michiel

Subjects
Continuous assessment, service mathematics, undergraduate mathematics, [SHS.EDU]Humanities and Social Sciences/Education, [SHS.EDU] Humanities and Social Sciences/Education, student participation, remediation, ComputingMilieux_COMPUTERSANDEDUCATION, [MATH] Mathematics [math], [MATH]Mathematics [math]
Abstract

International audience; Previous research has shown that students’ use of module resources strongly relates to the timing of the module’s continuous assessment. In our case study of a large first-year mathematics module for Business students, Maths for Business, we examine this relationship and the resources relied on by students for completing their continuous assessment. In Maths for Business, students have the choice of using live lectures or online videos or a combination of both. We find that students who incorporate lectures into their approach engage consistently throughout each week with module resources, while others adopt a just-in-time approach for each weekly quiz. We also show that the introduction of remediation of quizzes can boost participation with resources, in particular feedback resources.

Published
2019

39. A pedometer-based walking intervention in 45- to 75-year-olds, with and without practice nurse support: the PACE-UP three-arm cluster RCT

Author

Harris, Tess, Kerry, Sally, Victor, Christina, Iliffe, Steve, Ussher, Michael, Fox-Rushby, Julia, Whincup, Peter, Ekelund, Ulf, Furness, Cheryl, Limb, Elizabeth, Anokye, Nana, Ibison, Judith, DeWilde, Stephen, David, Lee, and Howard, Emma

Subjects
Health Policy
Abstract

Background Guidelines recommend walking to increase moderate to vigorous physical activity (MVPA) for health benefits. Objectives To assess the effectiveness, cost-effectiveness and acceptability of a pedometer-based walking intervention in inactive adults, delivered postally or through dedicated practice nurse physical activity (PA) consultations. Design Parallel three-arm trial, cluster randomised by household. Setting Seven London-based general practices. Participants A total of 11,015 people without PA contraindications, aged 45–75 years, randomly selected from practices, were invited. A total of 6399 people were non-responders, and 548 people self-reporting achieving PA guidelines were excluded. A total of 1023 people from 922 households were randomised to usual care (n = 338), postal intervention (n = 339) or nurse support (n = 346). The recruitment rate was 10% (1023/10,467). A total of 956 participants (93%) provided outcome data. Interventions Intervention groups received pedometers, 12-week walking programmes advising participants to gradually add ‘3000 steps in 30 minutes’ most days weekly and PA diaries. The nurse group was offered three dedicated PA consultations. Main outcome measures The primary and main secondary outcomes were changes from baseline to 12 months in average daily step counts and time in MVPA (in ≥ 10-minute bouts), respectively, from 7-day accelerometry. Individual resource-use data informed the within-trial economic evaluation and the Markov model for simulating long-term cost-effectiveness. Qualitative evaluations assessed nurse and participant views. A 3-year follow-up was conducted. Results Baseline average daily step count was 7479 [standard deviation (SD) 2671], average minutes per week in MVPA bouts was 94 minutes (SD 102 minutes) for those randomised. PA increased significantly at 12 months in both intervention groups compared with the control group, with no difference between interventions; additional steps per day were 642 steps [95% confidence interval (CI) 329 to 955 steps] for the postal group and 677 steps (95% CI 365 to 989 steps) for nurse support, and additional MVPA in bouts (minutes per week) was 33 minutes per week (95% CI 17 to 49 minutes per week) for the postal group and 35 minutes per week (95% CI 19 to 51 minutes per week) for nurse support. Intervention groups showed no increase in adverse events. Incremental cost per step was 19p and £3.61 per minute in a ≥ 10-minute MVPA bout for nurse support, whereas the postal group took more steps and cost less than the control group. The postal group had a 50% chance of being cost-effective at a £20,000 per quality-adjusted life-year (QALY) threshold within 1 year and had both lower costs [–£11M (95% CI –£12M to –£10M) per 100,000 population] and more QALYs [759 QALYs gained (95% CI 400 to 1247 QALYs)] than the nurse support and control groups in the long term. Participants and nurses found the interventions acceptable and enjoyable. Three-year follow-up data showed persistent intervention effects (nurse support plus postal vs. control) on steps per day [648 steps (95% CI 272 to 1024 steps)] and MVPA bouts [26 minutes per week (95% CI 8 to 44 minutes per week)]. Limitations The 10% recruitment level, with lower levels in Asian and socioeconomically deprived participants, limits the generalisability of the findings. Assessors were unmasked to the group. Conclusions A primary care pedometer-based walking intervention in 45- to 75-year-olds increased 12-month step counts by around one-tenth, and time in MVPA bouts by around one-third, with similar effects for the nurse support and postal groups, and persistent 3-year effects. The postal intervention provides cost-effective, long-term quality-of-life benefits. A primary care pedometer intervention delivered by post could help address the public health physical inactivity challenge. Future work Exploring different recruitment strategies to increase uptake. Integrating the Pedometer And Consultation Evaluation-UP (PACE-UP) trial with evolving PA monitoring technologies.

Published
2018

40. Engaging with feedback: How do students remediate errors on their weekly quiz

Author

Copeland, Cillian, Howard, Emma, Meehan, Maria, Parnell, Andrew, University College Dublin [Dublin] (UCD), INDRUM Network, University of Agder, and Sciencesconf.org, CCSD

Subjects
remediation of errors, students' practices at university level, [SHS.EDU]Humanities and Social Sciences/Education, [MATH.MATH-HO]Mathematics [math]/History and Overview [math.HO], [SHS.EDU] Humanities and Social Sciences/Education, [MATH.MATH-HO] Mathematics [math]/History and Overview [math.HO], feedback, assessment practices in university mathematics education
Abstract

International audience; Maths for Business is a first-year mathematics module for approximately 500 non-mathematics specialists. It has continuous assessment consisting of ten weekly quizzes, worth 40% of the final mark. In 2016/17, students who did not receive the maximum five marks on their weekly quiz were offered the opportunity to resubmit their quiz, with correction(s) and an explanation of their error(s), for one additional mark. We refer to this process as ‘remediation'. In this paper, we examine how students remediate their errors in order to identify features of a ‘good' remediation. These features are identification, description, and correction of errors. By analysing a subset of students (n=31), we observe that a student's quiz mark, and the cognitive level of the quiz question may impact the nature of the remediation provided.

Published
2018

41. A Comprehensive Review of Various Substrates Commonly Encountered at Crime Scenes and their Fluorescence Characteristics using the Polilight Flare® Plus 2

Author

Chapman, Brendan, Howard, Emma, Chapman, Brendan, and Howard, Emma

Abstract

Biological fluids are often present within a crime scene and can be a valuable source of DNA evidence; therefore the detection and identification of these fluids is critical. Alternative light sources are a presumptive testing tool that can be used to detect and enhance potential biological and non-biological staining, through the exploitation of the ultraviolet, visible light and infrared portion of the electromagnetic spectrum. Most biological fluids will emit fluorescence when excited by light from an alternative light source; however previous research has demonstrated that a range of non-biological products will also display fluorescence when viewed under alternative light sources, potentially causing confusion within a crime scene. Further investigation is required to develop a better understanding of the fluorescence displayed by biological and nonbiological products under a wide range of wavelengths and interference filters. This review will assess the current literature regarding the use of alternative light sources for the detection and visualisation of biological fluids, focusing on past studies that have recognised potential complications, such as the fluorescence of non-biological materials and the influence of background substrates on the detection of stains.

Published
2018

42. Quantifying participation in, and the effectiveness of, remediating assessment in a university mathematics module

Author

Howard, Emma, Meehan, Maria, Parnell, Andrew, Howard, Emma, Meehan, Maria, and Parnell, Andrew

Abstract

In Maths for Business, a large first-year mathematics module, the continuous assessment component comprises 10 weekly quizzes which combine to contribute 40% of the final module mark. If students did not receive the full five marks on their weekly quiz, they were provided with the opportunity to resubmit their corrected weekly quiz with an explanation of their error(s) for one additional mark. We refer to this process as ‘remediation’. Of the students who had the opportunity to remediate, ∼70% did. Through examining learning management system data, we show that the remediation process encouraged students to access module resources. Furthermore, by using a Bayesian hierarchical model to account for students’ level of participation, achievement and prior knowledge, we show that participation in the remediation process positively impacted the final examination marks of moderate to high achieving students (based on initial continuous assessment marks). However, participation in the remediation process provided limited benefit to low-achieving students. We conjecture this is because these students had not achieved a level of understanding whereby participation in the remediation process could progress their knowledge.

Published
2018

43. Social networks, geographic proximity, and firm performance in Viet Nam

Author

Howard, Emma

Subjects
social networks, L14, geographic proximity, L20, Viet Nam, ddc:330, manufacturing firms, D22
Abstract

This paper uses panel data to assess the relative importance of social networks and geographic proximity to micro, small, and medium enterprises in Viet Nam. The results suggest that a larger social network, and hiring employees mainly through social networks, are both correlated with higher value added per worker. The number of government officials and civil servants in a firm's network emerges as particularly important. When the quality of contacts is controlled for, firms with tighter social networks have, on average, higher value added per worker. The analysis of spatial networks reveals that firms with a lower percentage of customers and suppliers in the same district actually have higher value added per worker. The results suggest that for micro, small, and medium firms in Viet Nam, strong social networks are much more important than geographic proximity.

Published
2017

44. Identifying the reasons behind students’ engagement patterns

Author

Howard, Emma, Meehan, Maria, Parnell, Andrew, Dooley, Therese, and University College Dublin [Dublin] (UCD)

Subjects
ComputingMilieux_COMPUTERSANDEDUCATION, [MATH] Mathematics [math], [SHS] Humanities and Social Sciences, [MATH]Mathematics [math], ComputingMilieux_MISCELLANEOUS, [SHS]Humanities and Social Sciences
Abstract

This study focuses on identifying the reasons behind students’ specific engagement patterns in a large first year mathematics course in UCD. Maths for Business is a unique course in that students have a choice of whether to engage with the course material through lectures, videos or a combination of both. Cluster analysis of the engagement data (lecture attendance and video usage) has identified four distinct clusters of engagement. For explanations of resource use, surveys were distributed to the Maths for Business 2015/16 class (of approximately 550 students of mixed ability). 166 survey responses were received. Qualitative analysis is currently being performed on the survey responses in order to explain engagement patterns.

Published
2017

45. A pedometer-based walking intervention in 45- to 75-year-olds, with and without practice nurse support: the PACE-UP three-arm cluster RCT

Author

Harris, Tess, primary, Kerry, Sally, additional, Victor, Christina, additional, Iliffe, Steve, additional, Ussher, Michael, additional, Fox-Rushby, Julia, additional, Whincup, Peter, additional, Ekelund, Ulf, additional, Furness, Cheryl, additional, Limb, Elizabeth, additional, Anokye, Nana, additional, Ibison, Judith, additional, DeWilde, Stephen, additional, David, Lee, additional, Howard, Emma, additional, Dale, Rebecca, additional, Smith, Jaime, additional, Normansell, Rebecca, additional, Beighton, Carole, additional, Morgan, Katy, additional, Wahlich, Charlotte, additional, Sanghera, Sabina, additional, and Cook, Derek, additional

Published
2018
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46. Relating process evaluation measures to complex intervention outcomes: findings from the PACE-UP primary care pedometer-based walking trial

Author

Furness, Cheryl, primary, Howard, Emma, additional, Limb, Elizabeth, additional, Cook, Derek G., additional, Kerry, Sally, additional, Wahlich, Charlotte, additional, Victor, Christina, additional, Ekelund, Ulf, additional, Iliffe, Steve, additional, Ussher, Michael, additional, Whincup, Peter, additional, Fox-Rushby, Julia, additional, Ibison, Judith, additional, DeWilde, Stephen, additional, and Harris, Tess, additional

Published
2018
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49. Productivity-enhancing manufacturing clusters: Evidence from Vietnam

Author

Howard, Emma, Newman, Carol, Rand, John, and Tarp, Finn

Subjects
D2, productivity, Vietnam, L6, endogenous location choice, ddc:330, spillovers, L2, O1, clustering
Abstract

In this paper we explore the extent to which firms experience productivity spillovers from clustering using a rich data source from Vietnam for 2002 to 2007, a period of significant transition. We address issues of simultaneity, self-selection and endogenous location choice of firms in an estimation of firm level productivity. Controlling for competition effects and distinguishing between urbanization and localization economies, we find strong evidence for productivity spillovers from clustering. The effects of these spillovers are found to be particularly large for foreign-owned firms. Our results provide support for spatial clustering policies in developing countries aimed at attracting foreign investment.

Published
2014

50. The injection of zonal momentum by buoyancy forcing in a Southern Ocean Model

Author

Howard, Emma, Hogg, Andy, Waterman, Stephanie, Marshall, David P., Howard, Emma, Hogg, Andy, Waterman, Stephanie, and Marshall, David P.

Abstract

An overturning circulation, driven by prescribed buoyancy forcing, is used to set a zonal volume transport in a reentrant channel ocean model with three isopycnal layers. The channel is designed to represent the Southern Ocean such that the forced overturning resembles the lower limb of the meridional overturning circulation (MOC). The relative contributions of wind and buoyancy forcing to the zonal circulation are examined. It is found that the zonal volume transport is strongly dependent on the buoyancy forcing and that the eddy kinetic energy is primarily set by wind stress forcing. The zonal momentum budget integrated over each layer is considered in the buoyancy-forced, wind-forced, and combined forcing case. At equilibrium, sources and sinks of momentum are balanced, but the transient spinup reveals the source of momentum for the current. In the buoyancy-forced case, the forcing creates a baroclinic shear with westward flow in the lower layer, allowing topographic form stress and bottom friction to act as the initial sources of eastward momentum, with bottom friction acting over a longer time frame. In the wind-forced and combined forcing cases, the surface wind stress dominates the initial momentum budget, and the time to reach equilibration is shorter in the combined forcing simulation. These results imply that future changes in the rate of formation of Antarctic Bottom Water may alter the volume transport of the Antarctic Circumpolar Current.

Published
2015

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