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1. PMIF v1.0: assessing the potential of satellite observations to constrain CO2 emissions from large cities and point sources over the globe using synthetic data

Author

Y. Wang, G. Broquet, F.-M. Bréon, F. Lespinas, M. Buchwitz, M. Reuter, Y. Meijer, A. Loescher, G. Janssens-Maenhout, B. Zheng, and P. Ciais

Subjects
Geology, QE1-996.5
Abstract

This study assesses the potential of satellite imagery of vertically integrated columns of dry-air mole fractions of CO2 (XCO2) to constrain the emissions from cities and power plants (called emission clumps) over the whole globe during 1 year. The imagery is simulated for one imager of the Copernicus mission on Anthropogenic Carbon Dioxide Monitoring (CO2M) planned by the European Space Agency and the European Commission. The width of the swath of the CO2M instruments is about 300 km and the ground horizontal resolution is about 2 km resolution. A Plume Monitoring Inversion Framework (PMIF) is developed, relying on a Gaussian plume model to simulate the XCO2 plumes of each emission clump and on a combination of overlapping assimilation windows to solve for the inversion problem. The inversion solves for the 3 h mean emissions (during 08:30–11:30 local time) before satellite overpasses and for the mean emissions during other hours of the day (over the aggregation between 00:00–08:30 and 11:30–00:00) for each clump and for the 366 d of the year. Our analysis focuses on the derivation of the uncertainty in the inversion estimates (the “posterior uncertainty”) of the clump emissions. A comparison of the results obtained with PMIF and those from a previous study using a complex 3-D Eulerian transport model for a single city (Paris) shows that the PMIF system provides the correct order of magnitude for the uncertainty reduction of emission estimates (i.e., the relative difference between the prior and posterior uncertainties). Beyond the one city or few large cities studied by previous studies, our results provide, for the first time, the global statistics of the uncertainty reduction of emissions for the full range of global clumps (differing in emission rate and spread, and distance from other major clumps) and meteorological conditions. We show that only the clumps with an annual emission budget higher than 2 MtC yr−1 can potentially have their emissions between 08:30 and 11:30 constrained with a posterior uncertainty smaller than 20 % for more than 10 times within 1 year (ignoring the potential to cross or extrapolate information between 08:30–11:30 time windows on different days). The PMIF inversion results are also aggregated in time to investigate the potential of CO2M observations to constrain daily and annual emissions, relying on the extrapolation of information obtained for 08:30–11:30 time windows during days when clouds and aerosols do not mask the plumes, based on various assumptions regarding the temporal auto-correlations of the uncertainties in the emission estimates that are used as a prior knowledge in the Bayesian framework of PMIF. We show that the posterior uncertainties of daily and annual emissions are highly dependent on these temporal auto-correlations, stressing the need for systematic assessment of the sources of uncertainty in the spatiotemporally resolved emission inventories used as prior estimates in the inversions. We highlight the difficulty in constraining the total budget of CO2 emissions from all the cities and power plants within a country or over the globe with satellite XCO2 measurements only, and calls for integrated inversion systems that exploit multiple types of measurements.

Published
2020
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2. A global map of emission clumps for future monitoring of fossil fuel CO2 emissions from space

Author

Y. Wang, P. Ciais, G. Broquet, F.-M. Bréon, T. Oda, F. Lespinas, Y. Meijer, A. Loescher, G. Janssens-Maenhout, B. Zheng, H. Xu, S. Tao, K. R. Gurney, G. Roest, D. Santaren, and Y. Su

Subjects
Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

A large fraction of fossil fuel CO2 emissions emanate from “hotspots”, such as cities (where direct CO2 emissions related to fossil fuel combustion in transport, residential, commercial sectors, etc., excluding emissions from electricity-producing power plants, occur), isolated power plants, and manufacturing facilities, which cover a small fraction of the land surface. The coverage of all high-emitting cities and point sources across the globe by bottom-up inventories is far from complete, and for most of those covered, the uncertainties in CO2 emission estimates in bottom-up inventories are too large to allow continuous and rigorous assessment of emission changes (Gurney et al., 2019). Space-borne imagery of atmospheric CO2 has the potential to provide independent estimates of CO2 emissions from hotspots. But first, what a hotspot is needs to be defined for the purpose of satellite observations. The proposed space-borne imagers with global coverage planned for the coming decade have a pixel size on the order of a few square kilometers and a XCO2 accuracy and precision of  ppm for individual measurements of vertically integrated columns of dry-air mole fractions of CO2 (XCO2). This resolution and precision is insufficient to provide a cartography of emissions for each individual pixel. Rather, the integrated emission of diffuse emitting areas and intense point sources is sought. In this study, we characterize area and point fossil fuel CO2 emitting sources which generate coherent XCO2 plumes that may be observed from space. We characterize these emitting sources around the globe and they are referred to as “emission clumps” hereafter. An algorithm is proposed to identify emission clumps worldwide, based on the ODIAC global high-resolution 1 km fossil fuel emission data product. The clump algorithm selects the major urban areas from a GIS (geographic information system) file and two emission thresholds. The selected urban areas and a high emission threshold are used to identify clump cores such as inner city areas or large power plants. A low threshold and a random walker (RW) scheme are then used to aggregate all grid cells contiguous to cores in order to define a single clump. With our definition of the thresholds, which are appropriate for a space imagery with 0.5 ppm precision for a single XCO2 measurement, a total of 11 314 individual clumps, with 5088 area clumps, and 6226 point-source clumps (power plants) are identified. These clumps contribute 72 % of the global fossil fuel CO2 emissions according to the ODIAC inventory. The emission clumps is a new tool for comparing fossil fuel CO2 emissions from different inventories and objectively identifying emitting areas that have a potential to be detected by future global satellite imagery of XCO2. The emission clump data product is distributed from https://doi.org/10.6084/m9.figshare.7217726.v1.

Published
2019
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3. Retrieval and validation of carbon dioxide, methane and water vapor for the Canary Islands IR-laser occultation experiment

Author

V. Proschek, G. Kirchengast, S. Schweitzer, J. S. A. Brooke, P. F. Bernath, C. B. Thomas, J.-G. Wang, K. A. Tereszchuk, G. González Abad, R. J. Hargreaves, C. A. Beale, J. J. Harrison, P. A. Martin, V. L. Kasyutich, C. Gerbig, O. Kolle, and A. Loescher

Subjects
Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract

The first ground-based experiment to prove the concept of a novel space-based observation technique for microwave and infrared-laser occultation between low-Earth-orbit satellites was performed in the Canary Islands between La Palma and Tenerife. For two nights from 21 to 22 July 2011 the experiment delivered the infrared-laser differential transmission principle for the measurement of greenhouse gases (GHGs) in the free atmosphere. Such global and long-term stable measurements of GHGs, accompanied also by measurements of thermodynamic parameters and line-of-sight wind in a self-calibrating way, have become very important for climate change monitoring. The experiment delivered promising initial data for demonstrating the new observation concept by retrieving volume mixing ratios of GHGs along a ~144 km signal path at altitudes of ~2.4 km. Here, we present a detailed analysis of the measurements, following a recent publication that introduced the experiment's technical setup and first results for an example retrieval of CO2. We present the observational and validation data sets, the latter simultaneously measured at the transmitter and receiver sites; the measurement data handling; and the differential transmission retrieval procedure. We also determine the individual and combined uncertainties influencing the results and present the retrieval results for 12CO2, 13CO2, C18OO, H2O and CH4. The new method is found to have a reliable basis for monitoring of greenhouse gases such as CO2, CH4, and H2O in the free atmosphere.

Published
2015
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4. Greenhouse gas measurements over a 144 km open path in the Canary Islands

Author

J. S. A. Brooke, P. F. Bernath, G. Kirchengast, C. B. Thomas, J.-G. Wang, K. A. Tereszchuk, G. González Abad, R. J. Hargreaves, C. A. Beale, J. J. Harrison, S. Schweitzer, V. Proschek, P. A. Martin, V. L. Kasyutich, C. Gerbig, O. Kolle, and A. Loescher

Subjects
Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract

A new technique for the satellite remote sensing of greenhouse gases in the atmosphere via the absorption of short-wave infrared laser signals transmitted between counter-rotating satellites in low Earth orbit has recently been proposed; this would enable the acquisition of a long-term, stable, global set of altitude-resolved concentration measurements. We present the first ground-based experimental demonstration of this new infrared-laser occultation method, in which the atmospheric absorption of CO2 near 2.1 μm was measured over a ~144 km path length between two peaks in the Canary Islands (at an altitude of ~2.4 km), using relatively low power diode lasers (~4 to 10 mW). The retrieved CO2 volume mixing ratio of 400 ppm (±15 ppm) is consistent within experimental uncertainty with simultaneously recorded in situ validation measurements. We conclude that the new method has a sound basis for monitoring CO2 in the free atmosphere; other greenhouse gases such as methane, nitrous oxide and water vapour can be monitored in the same way.

Published
2012
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6. A simple, accurate, and explicit form of the Green–Ampt model to estimate infiltration, sorptivity, and hydraulic conductivity

Author

S. H. Sadeghi, H. W. Loescher, P. W. Jacoby, and P. L. Sullivan

Subjects
Environmental sciences, GE1-350, Geology, QE1-996.5
Abstract

Abstract Finding an explicit solution to the widely used Green–Ampt (G–A) one‐dimensional infiltration model has been subject of efforts for more than half a century. We derived an explicit semiempirical approach that combines accuracy with simplicity, a concept that has been generally neglected in previous studies. The equation is F=Kst(0.70635+0.324151+9.43456(S2Ks2t)), with F (L), Ks (L/T), S (L/T0.5) and t (T) being cumulative infiltration, saturated hydraulic conductivity, sorptivity, and time, respectively. Relative errors (ɛ) by the application of this equation generally do not exceed ±0.3% in most applied infiltration problems faced by water resources engineering today. We show both numerically and mathematically that │ɛ│> 0.3% could only occur if Kst/F > 0.904, a criterion that could apply to sand and loamy sand soils (i.e., coarse texture) and if they experience infiltration rates for over 6 h and 19 h, respectively. Hence, we also derived a simple linear adjustment in the model as Fadj ≅ 0.9796 F + 0.335 S2/Ks to address these longer infiltration rates, and to assure that ɛ remains within the expected ±0.3% range of uncertainty. A linearized regression technique was also developed to accurately estimate S and Ks when the G–A model is used. We numerically demonstrated that our fitting method could be used even when the G–A approach is less valid (diffusive soils), provided that the actual value of the capillary length (λ) is initially known. An added benefit of our approach is that by setting λ equal to 1/3 and 2/3, it can significantly limit the range of initializing, unknown, a priori values of S and Ks, as these two parameters are estimated through the inverse solution of implicit infiltration models. Due to the model's simplicity and accuracy, our solution should find application among hydrologists, natural resource scientists, and engineers who wish to easily derive accurate estimations from the G–A infiltration approach and/or estimate sorptivity and hydraulic conductivity without encountering divergence problems.

Published
2024
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7. Fifteen Years of Integrated Terrestrial Environmental Observatories (TERENO) in Germany: Functions, Services, and Lessons Learned

Author

Steffen Zacharias, Henry W. Loescher, Heye Bogena, Ralf Kiese, Martin Schrön, Sabine Attinger, Theresa Blume, Dietrich Borchardt, Erik Borg, Jan Bumberger, Christian Chwala, Peter Dietrich, Benjamin Fersch, Mark Frenzel, Jérôme Gaillardet, Jannis Groh, Irena Hajnsek, Sibylle Itzerott, Ralf Kunkel, Harald Kunstmann, Matthias Kunz, Susanne Liebner, Michael Mirtl, Carsten Montzka, Andreas Musolff, Thomas Pütz, Corinna Rebmann, Karsten Rinke, Michael Rode, Torsten Sachs, Luis Samaniego, Hans Peter Schmid, Hans‐Jörg Vogel, Ute Weber, Ute Wollschläger, and Harry Vereecken

Subjects
environmental observation, long‐term integrated observatories, research infrastructure, observation network, international collaboration, modeling and monitoring, Environmental sciences, GE1-350, Ecology, QH540-549.5
Abstract

Abstract The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long‐term research program to investigate the effects of global environmental change on terrestrial ecosystems and their socio‐economic consequences. State‐of‐the‐art methods from the field of environmental monitoring, geophysics, remote sensing, and modeling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long‐term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modeling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large‐scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO's key services and functions, presents the main lessons learned from this 15‐year effort, and emphasizes the need to continue long‐term integrated environmental monitoring programmes in the future.

Published
2024
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8. Use of the FallAkte Plus System as an IT Infrastructure for the North Rhine-Westphalian General Practice Research Network: Mixed Methods Usability Study

Author

Arezoo Bozorgmehr, Simon-Konstantin Thiem, Dorothea Wild, Melanie Reinsdorff, Horst Christian Vollmar, Annika Kappernagel, Kathrin Schloessler, Sabine Weissbach, Michael Pentzek, Dorothea Dehnen, Julia Drexler, Beate Sigrid Mueller, Larisa Pilic, Lion Lehmann, Susanne Loescher, Elena Darinka Hohmann, Friederike Frank, Gülay Ates, Susanne Kersten, Achim Mortsiefer, Benjamin Aretz, and Birgitta Weltermann

Subjects
Medicine
Abstract

BackgroundPrimary care research networks can generate important information in the setting where most patients are seen and treated. However, this requires a suitable IT infrastructure (ITI), which the North Rhine-Westphalian general practice research network is looking to implement. ObjectiveThis mixed methods research study aims to evaluate (study 1) requirements for an ITI and (study 2) the usability of an IT solution already available on the market, the FallAkte Plus (FA+) system for the North Rhine-Westphalian general practice research network, which comprises 8 primary care university institutes in Germany’s largest state. MethodsIn study 1, a survey was conducted among researchers from the institutes to identify the requirements for a suitable ITI. The questionnaire consisted of standardized questions with open-ended responses. In study 2, a mixed method approach combining a think-aloud approach and a quantitative survey was used to evaluate the usability and acceptance of the FA+ system among 3 user groups: researchers, general practitioners, and practice assistants. Respondents were asked to assess the usability with the validated system usability scale and to test a short questionnaire on vaccination management through FA+. ResultsIn study 1, five of 8 institutes participated in the requirements survey. A total of 32 user requirements related primarily to study management were identified, including data entry, data storage, and user access management. In study 2, a total of 36 participants (24 researchers and 12 general practitioners or practice assistants) were surveyed in the mixed methods study of an already existing IT solution. The tutorial video and handouts explaining how to use the FA+ system were well received. Researchers, unlike practice personnel, were concerned about data security and data protection regarding the system’s emergency feature, which enables access to all patient data. The median overall system usability scale rating was 60 (IQR 33.0-85.0), whereby practice personnel (median 82, IQR 58.0-94.0) assigned higher ratings than researchers (median 44, IQR 14.0-61.5). Users appreciated the option to integrate data from practices and other health care facilities. However, they voted against the use of the FA+ system due to a lack of support for various study formats. ConclusionsUsability assessments vary markedly by professional group and role. In its current stage of development, the FA+ system does not fully meet the requirements for a suitable ITI. Improvements in the user interface, performance, interoperability, security, and advanced features are necessary to make it more effective and user-friendly. Collaborating with end users and incorporating their feedback are crucial for the successful development of any practice network research ITI.

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

Author

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

Published
2024
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17. Long-term efficacy and safety of nusinersen in adults with 5q spinal muscular atrophy: a prospective European multinational observational study

Author

Günther, René, Wurster, Claudia Diana, Brakemeier, Svenja, Osmanovic, Alma, Schreiber-Katz, Olivia, Petri, Susanne, Uzelac, Zeljko, Hiebeler, Miriam, Thiele, Simone, Walter, Maggie C., Weiler, Markus, Kessler, Tobias, Freigang, Maren, Lapp, Hanna Sophie, Cordts, Isabell, Lingor, Paul, Deschauer, Marcus, Hahn, Andreas, Martakis, Kyriakos, Steinbach, Robert, Ilse, Benjamin, Rödiger, Annekathrin, Bellut, Julia, Nentwich, Julia, Zeller, Daniel, Muhandes, Mohamad Tareq, Baum, Tobias, Christoph Koch, Jan, Schrank, Bertold, Fischer, Sophie, Hermann, Andreas, Kamm, Christoph, Naegel, Steffen, Mensch, Alexander, Weber, Markus, Neuwirth, Christoph, Lehmann, Helmar C., Wunderlich, Gilbert, Stadler, Christian, Tomforde, Maike, George, Annette, Groß, Martin, Pechmann, Astrid, Kirschner, Janbernd, Türk, Matthias, Schimmel, Mareike, Bernert, Günther, Martin, Pascal, Rauscher, Christian, Meyer zu Hörste, Gerd, Baum, Petra, Löscher, Wolfgang, Flotats-Bastardas, Marina, Köhler, Cornelia, Probst-Schendzielorz, Kristina, Goldbach, Susanne, Schara-Schmidt, Ulrike, Müller-Felber, Wolfgang, Lochmüller, Hanns, von Velsen, Otgonzul, Kleinschnitz, Christoph, Ludolph, Albert C., and Hagenacker, Tim

Published
2024
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18. NEXT GENERATION LEADERS.

Author

BAJEKAL, NAINA, Zorthian, Julia, WORLAND, JUSTIN, SERHAN, YASMEEN, DE GUZMAN, CHAD, Loescher, Lillian, KLUGER, JEFFREY, HENSHALL, WILL, MENDEZ II, MOISES, PARK, ALICE, WAXMAN, OLIVIA B., and KOH EWE

Subjects
ISRAELIS, FASHION, BUSINESSPEOPLE, PATIENTS' families, ADULTS
Abstract

This article highlights the achievements of three individuals and a food-tech company. Ncuti Gatwa, a Scottish actor of Rwandan descent, has made history by becoming the first queer Black person to play the lead role in Doctor Who. Beth Koigi, a Kenyan entrepreneur, co-founded Majik Water to provide clean drinking water in arid regions. NotCo, a Chilean food-tech company, uses artificial intelligence to create plant-based food products that mimic the taste of animal-based foods. The company has experienced rapid growth and aims to focus on customer experience to make plant-based food mainstream. [Extracted from the article]

Published
2024

19. Predicting the next pandemic: VACCELERATE ranking of the WorldHealth Organization's Blueprint forAction toPreventEpidemics

Author

Busch, Martin, Seifert, Ulrike, Widmer, Andreas, Nagao, Miki, Rello, Jordi, Todorova, Tatina, Cviljević, Sabina, Heath, Christopher H., Jančorienė, Ligita, Fischer, Thea Koelsen, Orth, Hans Martin, Johansen, Isik Somuncu, Doymaz, Mehmet, Tragiannidis, Athanasios, Löscher, Thomas, Xu, Jin-Fu, Husa, Petr, Oteo, José Antonio, Issack, Mohammad I., Zeitlinger, Markus, Le Grand, Roger, Zdziarski, Przemysław, Demirkan, Fatih, Amador, Paloma Merino, García-Lozano, Tomás, Cao, Qing, Vázquez, Lourdes, Caeiro, Juan Pablo, Hermans, Peter, Nahrwar, Shahroch, Avsar, Korkut, Kumar, Deepak, Fernández, Norma, Mardani, Masoud, Segal, Esther, Pan, Angelo, Gkentzi, Despoina, Gioula, Georgia, Cortés, Jorge Alberto, Oliveira, Joaquim, van Damme, Pierre, Bin Mohd Zaili, Mohd Zaki, Antinori, Spinello, Zablockienė, Birutė, Papazisis, Georgios, Aneke, Chioma Inyang, Valerio, Maricela, McConkey, Samuel, Aujayeb, Avinash, Azzini, Anna Maria, Roganović, Jelena, Greve-Isdahl Mohn, Kristin, Kremsner, Peter, Gkrania-Klotsas, Effrossyni, Corzo, Dora, Khanna, Nina, Smiatacz, Tomasz, Scheithauer, Simone, Merelli, Maria, Klempa, Boris, Vrḫovac, Radovan, Ruggiero, Antonio, Chaudhary, Pankaj, Maquera-Afaray, Julio, Ekkelenkamp, Miquel, Jindra, Pavel, Pantić, Nikola, Guerra, Gemma Jiménez, Weiss, Guenter, Roohi, Behrad, Argyropoulos, Christos D., Silfverdal, Sven Aprne, van Praet, Jens, Bal, Zumrut Sahbudak, Kanj, Souha, Young, Barnaby, Pana, Zoi Dorothea, Roilides, Emmanuel, Stearns, Stephen C., Wauters, Joost, Baño, Jesús Rodríguez, Pletz, Mathias W., Travar, Maja, Kühn, Steven, Riera, Fernando, Cornely, Daniel, Laura, Vlad Jeni, Koehler, Philipp, Eley, Brian, Nair, Pravin K., Ciesek, Sandra, Olaru, Ioana Diana, Marques, Laura, Pontali, Emanuele, Naunheim, Alexandra, Lieb, Adrian, Gerhard, Markus, Farooqi, Joveria Qais, Turtle, Lance, Méndez, Gustavo Adolfo, Cox, Rebecca Jane, Goodman, Nigel, Caceca, Billie, Pemán, Javier, Dawood, Halima, Askling, Helena Hervius, Fomsgaard, Anders, Hernández, Alejandra Calderón, Staehelin, Cornelia, Liu, Chia-Ying, Icardi, Giancarlo, Castagnola, Elio, Salzer, Helmut J.F., Lundgren, Jens, Javadli, Samir, Forghieri, Fabio, Salmanton-García, Jon, Wipfler, Pauline, Leckler, Janina, Nauclér, Pontus, Mallon, Patrick W., Bruijning-Verhagen, Patricia C.J.L., Schmitt, Heinz-Joseph, Bethe, Ullrich, Olesen, Ole F., Stewart, Fiona A., Albus, Kerstin, and Cornely, Oliver A.

Published
2024
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23. Corrigendum to 'Greenhouse gas measurements over a 144 km open path in the Canary Islands' published in Atmos. Meas. Tech., 5, 2309–2319, 2012

Author

V. L. Kasyutich, P. A. Martin, V. Proschek, S. Schweitzer, J. J. Harrison, C. A. Beale, R. J. Hargreaves, G. González Abad, K. A. Tereszchuk, C. B. Thomas, J.-G. Wang, G. Kirchengast, P. F. Bernath, J. S. A. Brooke, C. Gerbig, O. Kolle, and A. Loescher

Subjects
Environmental engineering, TA170-171, Earthwork. Foundations, TA715-787
Abstract

No abstract available.

Published
2012
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31. Large-scale sequencing identifies multiple genes and rare variants associated with Crohn’s disease susceptibility

Author

Sazonovs, Aleksejs, Stevens, Christine R., Venkataraman, Guhan R., Yuan, Kai, Avila, Brandon, Abreu, Maria T., Ahmad, Tariq, Allez, Matthieu, Ananthakrishnan, Ashwin N., Atzmon, Gil, Baras, Aris, Barrett, Jeffrey C., Barzilai, Nir, Beaugerie, Laurent, Beecham, Ashley, Bernstein, Charles N., Bitton, Alain, Bokemeyer, Bernd, Chan, Andrew, Chung, Daniel, Cleynen, Isabelle, Cosnes, Jacques, Cutler, David J., Daly, Allan, Damas, Oriana M., Datta, Lisa W., Dawany, Noor, Devoto, Marcella, Dodge, Sheila, Ellinghaus, Eva, Fachal, Laura, Farkkila, Martti, Faubion, William, Ferreira, Manuel, Franchimont, Denis, Gabriel, Stacey B., Ge, Tian, Georges, Michel, Gettler, Kyle, Giri, Mamta, Glaser, Benjamin, Goerg, Siegfried, Goyette, Philippe, Graham, Daniel, Hämäläinen, Eija, Haritunians, Talin, Heap, Graham A., Hiltunen, Mikko, Hoeppner, Marc, Horowitz, Julie E., Irving, Peter, Iyer, Vivek, Jalas, Chaim, Kelsen, Judith, Khalili, Hamed, Kirschner, Barbara S., Kontula, Kimmo, Koskela, Jukka T., Kugathasan, Subra, Kupcinskas, Juozas, Lamb, Christopher A., Laudes, Matthias, Lévesque, Chloé, Levine, Adam P., Lewis, James D., Liefferinckx, Claire, Loescher, Britt-Sabina, Louis, Edouard, Mansfield, John, May, Sandra, McCauley, Jacob L., Mengesha, Emebet, Mni, Myriam, Moayyedi, Paul, Moran, Christopher J., Newberry, Rodney D., O’Charoen, Sirimon, Okou, David T., Oldenburg, Bas, Ostrer, Harry, Palotie, Aarno, Paquette, Jean, Pekow, Joel, Peter, Inga, Pierik, Marieke J., Ponsioen, Cyriel Y., Pontikos, Nikolas, Prescott, Natalie, Pulver, Ann E., Rahmouni, Souad, Rice, Daniel L., Saavalainen, Päivi, Sands, Bruce, Sartor, R. Balfour, Schiff, Elena R., Schreiber, Stefan, Schumm, L. Philip, Segal, Anthony W., Seksik, Philippe, Shawky, Rasha, Sheikh, Shehzad Z., Silverberg, Mark S., Simmons, Alison, Skeiceviciene, Jurgita, Sokol, Harry, Solomonson, Matthew, Somineni, Hari, Sun, Dylan, Targan, Stephan, Turner, Dan, Uhlig, Holm H., van der Meulen, Andrea E., Vermeire, Séverine, Verstockt, Sare, Voskuil, Michiel D., Winter, Harland S., Young, Justine, Duerr, Richard H., Franke, Andre, Brant, Steven R., Cho, Judy, Weersma, Rinse K., Parkes, Miles, Xavier, Ramnik J., Rivas, Manuel A., Rioux, John D., McGovern, Dermot P. B., Huang, Hailiang, Anderson, Carl A., and Daly, Mark J.

Published
2022
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36. Use of waveform engineering to stress test, characterise and design a highly efficient MMIC power amplifier

Author

Loescher, David

Subjects
621.381
Abstract

This thesis brings together different areas of waveform engineering in power amplifier research, from load pull and reliability testing through to measuring finished designs. It shows how using all this knowledge together can enable an engineer to start with just a transistor, and progress to a functional design much faster with the use of waveform engineering at every stage. Initially this project looked at expanding the conventional voltage standing wave ratio sweep to address more than the fundamental impedance with static harmonic impedances by including full harmonic impedance sweeps. This showed there were voltage peaking interactions that could potentially cause device failure, these were caused by interactions between the fundamental and harmonic impedances. The next step was to identify the cause of failures that had occurred during voltage standing wave ratio sweeps. This demonstrated the need for waveforms to identify failures caused by peak voltage and/or current. Waveform data can also be used to analyse and compare the different device technologies and analyse their performance, allowing deep insight into the `knee' region of the RF-IV plot, and how it affects performance of a technology using a novel data processing approach. The final use of waveforms in this thesis is at the design stage, where a Continuous Class B design was done on a quasi-MMIC. This design was then fabricated and tested, showing that Continuous Class B and other continuous modes can be used for quasi-MMIC designs at S-band as well as the previously used laminate designs. Another topology that was used in this thesis was Doherty, which has traditionally struggled with bandwidth, but using a novel 50 V GaN FET supplied by Qorvo allowed a more broadband Doherty design to be fabricated.

Published
2018

37. From Bottom-Up to Top-Down : Europe’s CO 2 Emissions Monitoring Capacity

Author

Janssens-Maenhout, G., Pinty, B., Dowell, M., Zunker, H., Andersson, E., Balsamo, G., Bézy, J.-L., Brunhes, T., Bösch, H., Bojkov, B., Brunner, D., Buchwitz, M., Crisp, D., Ciais, P., Counet, P., Dee, D., van der Gon, H. Denier, Dolman, H., Drinkwater, M. R., Dubovik, O., Engelen, R., Fehr, T., Fernandez, V., Heimann, M., Holmlund, K., Houweling, S., Husband, R., Juvyns, O., Kentarchos, A., Landgraf, J., Lang, R., Löscher, A., Marshall, J., Meijer, Y., Nakajima, M., Palmer, P. I., Peylin, P., Rayner, P., Scholze, M., Sierk, B., Tamminen, J., and Veefkind, P.

Published
2021

39. Safety and efficacy of cipaglucosidase alfa plus miglustat versus alglucosidase alfa plus placebo in late-onset Pompe disease (PROPEL): an international, randomised, double-blind, parallel-group, phase 3 trial

Author

Sebok, Agnes, Pestronk, Alan, Dominovic-Kovacevic, Aleksandra, Khan, Aneal, Koritnik, Blaž, Tard, Celine, Lindberg, Christopher, Quinn, Colin, Kornblum, Cornelia, Eldridge, Crystal, Bodkin, Cynthia, Reyes-Leiva, David, Hughes, Derralynn, Stefanescu, Ela, SALORT-CAMPANA, Emmanuelle, Butler, Ernest, Bouhour, Francoise, Kim, Gee, Konstantinos Papadimas, George, Parenti, Giancarlo, Bartosik-Psujek, Halina, Kushlaf, Hani, Akihiro, Hashiguchi, Lau, Heather, Pedro, Helio, Andersen, Henning, Amartino, Hernan, Shiraishi, Hideaki, Kobayashi, Hiroshi, Tarnev, Ivaylo, Vengoechea, Jaime, Avelar, Jennifer, Shin, Jin-Hong, Cauci, Jonathan, Alonso-Pérez, Jorge, Janszky, Jozsef, Berthy, Julie, Gutschmidt, Kristina, Claeys, Kristl, Judit Molnar, Maria, Wencel, Marie, Tarnopolsky, Mark, Dimachkie, Mazen, Tchan, Michel, Freimer, Miriam, Longo, Nicola, Vidal-Fernandez, Nuria, Musumeci, Olimpia, Goker-Alpan, Ozlem, Deegan, Patrick, Clemens, Paula R., Roxburgh, Richard, Henderson, Robert, Hopkin, Robert, Sacconi, Sabrina, Fecarotta, Simona, Attarian, Shahram, Wenninger, Stephan, Dearmey, Stephanie, Hiwot, Tarekegn, Burrow, Thomas, Ruck, Tobias, Sawada, Tomo, Laszlo, Vescei, Löscher, Wolfgang, Chien, Yin-Hsiu, Schoser, Benedikt, Roberts, Mark, Byrne, Barry J, Sitaraman, Sheela, Jiang, Hai, Laforêt, Pascal, Toscano, Antonio, Castelli, Jeff, Díaz-Manera, Jordi, Goldman, Mitchell, van der Ploeg, Ans T, Bratkovic, Drago, Kuchipudi, Srilakshmi, Mozaffar, Tahseen, and Kishnani, Priya S

Published
2021
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40. Regulation of titin-based cardiac stiffness by unfolded domain oxidation (UnDOx)

Author

Loescher, Christine M., Breitkreuz, Martin, Li, Yong, Nickel, Alexander, Unger, Andreas, Dietl, Alexander, Schmidt, Andreas, Mohamed, Belal A., Kötter, Sebastian, Schmitt, Joachim P., Krüger, Marcus, Krüger, Martina, Toischer, Karl, Maack, Christoph, Leichert, Lars I., Hamdani, Nazha, and Linke, Wolfgang A.

Published
2020

41. Toward an Operational Anthropogenic CO₂ Emissions Monitoring and Verification Support Capacity

Author

Janssens-Maenhout, G., Pinty, B., Dowell, M., Zunker, H., Andersson, E., Balsamo, G., Bézy, J.-L., Brunhes, T., Bösch, H., Bojkov, B., Brunner, D., Buchwitz, M., Crisp, D., Ciais, P., Counet, P., Dee, D., van der Gon, H. Denier, Dolman, H., Drinkwater, M. R., Dubovik, O., Engelen, R., Fehr, T., Fernandez, V., Heimann, M., Holmlund, K., Houweling, S., Husband, R., Juvyns, O., Kentarchos, A., Landgraf, J., Lang, R., Löscher, A., Marshall, J., Meijer, Y., Nakajima, M., Palmer, P. I., Peylin, P., Rayner, P., Scholze, M., Sierk, B., Tamminen, J., and Veefkind, P.

Published
2020

42. Safety and efficacy of oral levosimendan in people with amyotrophic lateral sclerosis (the REFALS study): a randomised, double-blind, placebo-controlled phase 3 trial

Author

Kiernan, Matthew, Mathers, Susan, Henderson, Robert, Needham, Merrilee, Schultz, David, Löscher, Wolfgang, Mitrovic, Nenad, Rath, Jakob, Damme, Philip Van, De Bleecker, Jan L., Delstanche, Stéphanie, Johnston, Wendy, Zinman, Lorne, O'Connell, Colleen, Matte, Genevieve, Dionne, Annie, Korngut, Lawrence, Turnbull, John, Laaksovirta, Hannu, Jokela, Manu, Tapiola, Tero, Soriani, Marie-Hélène, Couratier, Philippe, Camu, William, Corcia, Philippe, Ludolph, Albert, Großkreutz, Julian, Meyer, Thomas, Boentert, Matthias, Schrank, Berthold, Prudlo, Johannes, Untucht, Robert, Hardiman, Orla, Siciliano, Gabriele, Chio', Adriano, Mazzini, Letizia, Inghilleri, Maurizio, Caponnetto, Claudia, Mora, Gabriele, Mora Pardina, Jesús S, Farrero Munoz, Eva, Vázquez Costa, Juan F, Aguera Morales, Eduardo, Varona, Luis, Andersen, Peter, Ingre, Caroline, Johansson, Rune, Radunovic, Aleksandar, Young, Carolyn, Babu, Suma, Shaibani, Aziz, Staff, Nathan, Vu, Tuan, Rivner, Michael, Scelsa, Stephen, Sivakumar, Kumaraswamy, Waheed, Waqar, Heitzman, Daragh, Rana, Sandeep, Pattee, Gary, Ajroud-Driss, Senda, Bayat, Elham, Kasarskis, Edward, Lange, Dale J, Elliott, Michael, Harris, Brent, Felice, Kevin, Pulley, Michael T, Kwan, Justin, Brown, Martin, Ravits, John, Burford, Matthew, Karam, Chafic, Miller, Timothy, Andrews, Jinsy, Levine, Todd, Locatelli, Eduardo, Wymer, James, Bedlack, Richard, Fee, Dominic, Goyal, Namita, Oskarsson, Bjorn, McCluskey, Leo, Caress, James, Weiss, Michael, Quick, Adam, Bromberg, Mark, Lacomis, David, Goutman, Stephen, Rezania, Kourosh, Guliani, Gaurav, Goslin, Kimberly, Katz, Jonathan S, Cudkowicz, Merit, Genge, Angela, Maragakis, Nicholas, Petri, Susanne, van den Berg, Leonard, Aho, Valtteri V, Sarapohja, Toni, Kuoppamäki, Mikko, Garratt, Chris, and Al-Chalabi, Ammar

Published
2021
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45. The literary shape and missional significance of Acts : an invitation to be an instrument for the kingdom of God

Author

Loescher, Will

Subjects
226
Abstract

A fresh reading of Acts shows how its structure and story reveal missional significance, inviting God’s people to be an instrument for the kingdom of God. This study investigates three related areas in: (1) constructing an appropriate literary method from within the vast field of literary criticism; (2) focusing on Acts as a whole literary work instead of narrower pericopes or the broader corpus of Luke-Acts; and (3) revealing theological significance from literary shape instead of imposing it on the narrative. The method is a focused narrative criticism joining structure elements (sections, sequence, and size) and story components (literary-spatial, literary-temporal, character, speech, and intertextual) to inform a narrative theology arising from the text. Three Graeco-Roman literary principles (from Horace and Aristotle) organise ancient and modern literary concepts. The study’s core central chapters investigate the literary shape of Acts’ Ending (21:15–28:31) as a finish and closure, Acts’ Beginning (1:1–8:3) as a start and opening, and Acts’ Middle (8:4–21:14) as a centre and climax. The resulting theological significance focuses on the culmination, foundation, and pivot of mission and the kingdom of God. The literary and theological findings include the structural proportionalism of Acts 1:1–8:3 (initial success) and Acts 21:15–28:31 (Paul’s restoration), a central scene at Lystra (14:8–20a), story advances and declines in the Gentile mission, a decline with Paul from 19:21, and the missional significance of a mission instrument (Jesus, Israel, twelve apostles, Peter, Philip, Stephen, Saul/Paul, church) target (Jews, Gentiles), message (God, Jesus, resurrection, salvation), source (Holy Spirit, “the Word of God/Lord”, “the name of Jesus”), method (verbal communication, supernatural activity), success, suffering, and expansion. This research contributes a focused method of narrative criticism and theology, integrates structure and story, gives an exploration of the whole Acts’ narrative, and demonstrates how Acts’ literary shape reveals the important missional significance of the church being an instrument for the expanding kingdom of God.

Published
2017

48. A simple, accurate, and explicit form of the Green–Ampt model to estimate infiltration, sorptivity, and hydraulic conductivity.

Author

Sadeghi, S. H., Loescher, H. W., Jacoby, P. W., and Sullivan, P. L.

Subjects
HYDRAULIC conductivity, WATER supply, NATURAL resources, HYDROLOGISTS, SEEPAGE, SOILS, SIMPLICITY
Abstract

Finding an explicit solution to the widely used Green–Ampt (G–A) one‐dimensional infiltration model has been subject of efforts for more than half a century. We derived an explicit semiempirical approach that combines accuracy with simplicity, a concept that has been generally neglected in previous studies. The equation is F=Kst(0.70635+0.324151+9.43456(S2Ks2t))$F\; = {K_s}\;t\;({0.70635 + 0.32415\sqrt {1 + 9.43456({\frac{{{S^2}}}{{{K_s}^2t}}})} })$, with F (L), Ks (L/T), S (L/T0.5) and t (T) being cumulative infiltration, saturated hydraulic conductivity, sorptivity, and time, respectively. Relative errors (ɛ) by the application of this equation generally do not exceed ±0.3% in most applied infiltration problems faced by water resources engineering today. We show both numerically and mathematically that │ɛ│> 0.3% could only occur if Kst/F > 0.904, a criterion that could apply to sand and loamy sand soils (i.e., coarse texture) and if they experience infiltration rates for over 6 h and 19 h, respectively. Hence, we also derived a simple linear adjustment in the model as Fadj ≅ 0.9796 F + 0.335 S2/Ks to address these longer infiltration rates, and to assure that ɛ remains within the expected ±0.3% range of uncertainty. A linearized regression technique was also developed to accurately estimate S and Ks when the G–A model is used. We numerically demonstrated that our fitting method could be used even when the G–A approach is less valid (diffusive soils), provided that the actual value of the capillary length (λ) is initially known. An added benefit of our approach is that by setting λ equal to 1/3 and 2/3, it can significantly limit the range of initializing, unknown, a priori values of S and Ks, as these two parameters are estimated through the inverse solution of implicit infiltration models. Due to the model's simplicity and accuracy, our solution should find application among hydrologists, natural resource scientists, and engineers who wish to easily derive accurate estimations from the G–A infiltration approach and/or estimate sorptivity and hydraulic conductivity without encountering divergence problems. Core Ideas: A new explicit form of the one‐dimensional Green–Ampt infiltration model was developed.This model combined simplicity, accuracy, and computational efficiency.A new linearized regression solution was derived to estimate sorptivity and hydraulic conductivity.This linearized fitting method can eliminate the risk of convergence associated with other numerical approaches. [ABSTRACT FROM AUTHOR]

Published
2024
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49. Fifteen Years of Integrated Terrestrial Environmental Observatories (TERENO) in Germany: Functions, Services, and Lessons Learned.

Author

Zacharias, Steffen, Loescher, Henry W., Bogena, Heye, Kiese, Ralf, Schrön, Martin, Attinger, Sabine, Blume, Theresa, Borchardt, Dietrich, Borg, Erik, Bumberger, Jan, Chwala, Christian, Dietrich, Peter, Fersch, Benjamin, Frenzel, Mark, Gaillardet, Jérôme, Groh, Jannis, Hajnsek, Irena, Itzerott, Sibylle, Kunkel, Ralf, and Kunstmann, Harald

Subjects
TECHNOLOGICAL progress, EARTH system science, GLOBAL environmental change, OBSERVATORIES, ECOLOGICAL forecasting, AGRICULTURAL innovations, ATMOSPHERIC boundary layer, WATER demand management
Abstract

The need to develop and provide integrated observation systems to better understand and manage global and regional environmental change is one of the major challenges facing Earth system science today. In 2008, the German Helmholtz Association took up this challenge and launched the German research infrastructure TERrestrial ENvironmental Observatories (TERENO). The aim of TERENO is the establishment and maintenance of a network of observatories as a basis for an interdisciplinary and long‐term research program to investigate the effects of global environmental change on terrestrial ecosystems and their socio‐economic consequences. State‐of‐the‐art methods from the field of environmental monitoring, geophysics, remote sensing, and modeling are used to record and analyze states and fluxes in different environmental disciplines from groundwater through the vadose zone, surface water, and biosphere, up to the lower atmosphere. Over the past 15 years we have collectively gained experience in operating a long‐term observing network, thereby overcoming unexpected operational and institutional challenges, exceeding expectations, and facilitating new research. Today, the TERENO network is a key pillar for environmental modeling and forecasting in Germany, an information hub for practitioners and policy stakeholders in agriculture, forestry, and water management at regional to national levels, a nucleus for international collaboration, academic training and scientific outreach, an important anchor for large‐scale experiments, and a trigger for methodological innovation and technological progress. This article describes TERENO's key services and functions, presents the main lessons learned from this 15‐year effort, and emphasizes the need to continue long‐term integrated environmental monitoring programmes in the future. Plain Language Summary: This paper discusses the importance of creating comprehensive environmental observation systems to better understand and address global and regional environmental changes. In 2008, a German research infrastructure named Terrestrial Environmental Observatories (TERENO) was established to build and maintain a network of observatories. The goal is to conduct interdisciplinary, long‐term research on the impacts of global environmental changes on terrestrial ecosystems and their socio‐economic effects. The TERENO network employs advanced methods from environmental monitoring, geophysics, remote sensing, and modeling to study various environmental aspects. Over the past 15 years, four observatories have been part of this network, contributing to valuable experience in overcoming challenges and exceeding expectations. Today, TERENO is a crucial component for environmental modeling and forecasting in Germany, serving as an information hub for practitioners and policymakers. It also fosters international collaboration, supports large‐scale experiments, and drives methodological and technological advancements. The article highlights key lessons learned from this 15‐year effort and emphasizes the importance of continuing such integrated environmental monitoring programs in the future. Key Points: Integrated observatories ensure a holistic Earth Systems perspective, offering data for current and future ecological challengesThe scientific and societal value of observatories is invaluable, but their design, construction and operation require considerable effortFor assured long‐term data collection, research infrastructure must have flexible design for adapting to changing research needs [ABSTRACT FROM AUTHOR]

Published
2024
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50. Pursuing Success in a Hybrid PhD Nursing Program.

Author

Littzen, Chloé, May, Jennifer, Rainbow, Jessica, Morrison, Helena, and Loescher, Lois

Subjects
CURRICULUM, SCALE analysis (Psychology), GRADUATE nursing education, QUALITATIVE research, DOCTORAL students, DOCTORAL programs, AFFINITY groups, INTERVIEWING, BENCHMARKING (Management), QUESTIONNAIRES, QUANTITATIVE research, DESCRIPTIVE statistics, MENTORING, EXPERIENCE, STUDENTS, MOTIVATION (Psychology), ONLINE education, ACADEMIC achievement, RESEARCH methodology, ALUMNAE & alumni, LEARNING strategies, STUDENT attitudes, SOCIAL support, COMPARATIVE studies, NURSING students
Abstract

Background: Little is known about hybrid PhD nursing students' experiences. Method: The purpose of this study was to describe and analyze the experiences of PhD nursing students in a hybrid program using a convergent mixed methods design. Recent nursing PhD alumni (n = 18), and current PhD students (n = 4) were recruited at a research-intensive university in the southwestern United States. Results: Four metainferences were identified: (1) the facilitator of faculty as both advisors and mentors; (2) the facilitator of peers as support, motivation, and a source of advice that preceded advisors; (3) the barrier of receiving conflicting feedback from advisory and dissertation committees; and (4) the barrier of not understanding the PhD student process. Conclusion: Peer support is fundamental for hybrid PhD nursing student success; conflicting feedback and not understanding the process are significant barriers. Strategies are recommended to mitigate barriers to facilitate hybrid PhD nursing students' success. [J Nurs Educ. 2024;63(5):328–331.] [ABSTRACT FROM AUTHOR]

Published
2024
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