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17. Reduction of Subsidence and Large-Scale Rebound in the Beijing Plain after Anthropogenic Water Transfer and Ecological Recharge of Groundwater: Evidence from Long Time-Series Satellites InSAR.

Author

Zhou, Chaodong, Tang, Qiuhong, Zhao, Yanhui, Warner, Timothy A., Liu, Hongjiang, and Clague, John J.

Subjects
GROUNDWATER recharge, WATER transfer, LAND subsidence, RESTORATION ecology, WATER diversion, WATER table
Abstract

Beijing, China's capital city, has experienced decades of severe land subsidence due to the long-term overexploitation of groundwater. The implementation of the South-to-North Water Diversion Project (SNWDP) and artificial ecological restoration have significantly changed Beijing's hydro-ecological and geological environment in recent years, leading to a widespread rise in groundwater levels. However, whether the related land subsidence has slowed down or reversed under these measures has not yet been effectively monitored and quantitatively analyzed in terms of time and space. Accordingly, in this study, we proposed using an improved time-series deformation method, which combines persistent scatterers and distributed scatterers, to process Sentinel-1 images from 2015 to 2022 in the Beijing Plain region. We performed a geospatial analysis to gain a better understanding of how the new hydrological conditions changed the pattern of deformation on the Beijing Plain. The results indicated that our combined PS and DS method provided more measurements both in total quantity and spatial density than conventional PSI methods. The land subsidence in the Beijing Plain area has been effectively alleviated from a subsidence region of approximately 1377 km2 in 2015 to only approximately 78 km2 in 2022. Ecological restoration areas in the northeastern part of the Plain have even rebounded over this period, at a maximum of approximately 40 mm in 2022. The overall pattern of ground deformation (subsidence and uplift) is negatively correlated with changes in the groundwater table (decline and rise). Local deformation is controlled by the thickness of the compressible layer and an active fault. The year 2015, when anthropogenic water transfers were eliminated and ecological measures to recharge groundwater were implemented, was the crucial turning point of the change in the deformation trend in the subsidence history of Beijing. Our findings carry significance, not only for China, but also for other areas where large-scale groundwater extractions are causing severe ground subsidence or rebound. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Selecting and Interpreting Multiclass Loss and Accuracy Assessment Metrics for Classifications with Class Imbalance: Guidance and Best Practices.

Author

Farhadpour, Sarah, Warner, Timothy A., and Maxwell, Aaron E.

Subjects
*BEST practices, *THEMATIC maps, *CLASSIFICATION
Abstract

Evaluating classification accuracy is a key component of the training and validation stages of thematic map production, and the choice of metric has profound implications for both the success of the training process and the reliability of the final accuracy assessment. We explore key considerations in selecting and interpreting loss and assessment metrics in the context of data imbalance, which arises when the classes have unequal proportions within the dataset or landscape being mapped. The challenges involved in calculating single, integrated measures that summarize classification success, especially for datasets with considerable data imbalance, have led to much confusion in the literature. This confusion arises from a range of issues, including a lack of clarity over the redundancy of some accuracy measures, the importance of calculating final accuracy from population-based statistics, the effects of class imbalance on accuracy statistics, and the differing roles of accuracy measures when used for training and final evaluation. In order to characterize classification success at the class level, users typically generate averages from the class-based measures. These averages are sometimes generated at the macro-level, by taking averages of the individual-class statistics, or at the micro-level, by aggregating values within a confusion matrix, and then, calculating the statistic. We show that the micro-averaged producer's accuracy (recall), user's accuracy (precision), and F1-score, as well as weighted macro-averaged statistics where the class prevalences are used as weights, are all equivalent to each other and to the overall accuracy, and thus, are redundant and should be avoided. Our experiment, using a variety of loss metrics for training, suggests that the choice of loss metric is not as complex as it might appear to be, despite the range of choices available, which include cross-entropy (CE), weighted CE, and micro- and macro-Dice. The highest, or close to highest, accuracies in our experiments were obtained by using CE loss for models trained with balanced data, and for models trained with imbalanced data, the highest accuracies were obtained by using weighted CE loss. We recommend that, since weighted CE loss used with balanced training is equivalent to CE, weighted CE loss is a good all-round choice. Although Dice loss is commonly suggested as an alternative to CE loss when classes are imbalanced, micro-averaged Dice is similar to overall accuracy, and thus, is particularly poor for training with imbalanced data. Furthermore, although macro-Dice resulted in models with high accuracy when the training used balanced data, when the training used imbalanced data, the accuracies were lower than for weighted CE. In summary, the significance of this paper lies in its provision of readers with an overview of accuracy and loss metric terminology, insight regarding the redundancy of some measures, and guidance regarding best practices. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Neutrophil-Derived Protein S100A8/A9 Alters the Platelet Proteome in Acute Myocardial Infarction and Is Associated With Changes in Platelet Reactivity

Author

Joshi, Abhishek, Schmidt, Lukas E., Burnap, Sean A., Lu, Ruifang, Chan, Melissa V., Armstrong, Paul C., Baig, Ferheen, Gutmann, Clemens, Willeit, Peter, Santer, Peter, Barwari, Temo, Theofilatos, Konstantinos, Kiechl, Stefan, Willeit, Johann, Warner, Timothy D., Mathur, Anthony, and Mayr, Manuel

Published
2022
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26. Assessing Outside the Bubble: Performance Assessment for Common Core State Standards

Author

Bishop, Jesica M., Bristow, Lora J., Coriell, Bryn P., Jensen, Mark E., Johnson, Leif E., Luring, Sara R., Lyons-Tinsley, Mary Ann, Mefford, Megan M., Neu, Gwen L., Samulski, Emerson T., Warner, Timothy D., and White, Mathew F.

Abstract

The adoption of Common Core State Standards has increased the need for assessments capable of measuring more performance-based outcomes. This monograph brings together the current literature and resources for the development and implementation of performance assessment. The text was written as part of a project-based graduate course and has resulted in a clear, well researched and documented contribution that provides up to date information and references on Common Core State Standards and performance-based assessments. Three appendixes include: (1) Performance Task Examples; (2) Creating Rubrics; and (3) Glossary. (Contains 12 tables.) [This report was edited by: Eric V. Van Duzer and Gwen L. Neu.]

Published
2011

28. Cost-effective disaster-induced land cover analysis: a semi-automatic methodology Using machine learning and satellite imagery.

Author

I. Volke, Matias, Abarca-Del-Rio, Rodrigo, and A. Warner, Timothy

Subjects
LAND cover, REMOTE-sensing images, MACHINE learning, NATURAL disasters, TSUNAMIS, EARTHQUAKES, LANDSAT satellites
Abstract

This study introduces a cost-effective and automated methodology to swiftly and accurately gauge disaster-induced land cover changes, harnessing satellite imagery and machine learning. Using open-source platforms like Google Earth Engine, the approach streamlines training sample generation and assesses diverse machine learning algorithms on pre- and post-disaster Landsat images. The innovation lies in its semi-automatic training sample generation methodology, reducing time and manual effort for accurate land cover mapping and addressing the challenge of crafting training samples in disaster settings. The methodology was tested on the 2010 Chilean earthquake and tsunami, revealing a 45% increase in sediment cover and a 15% reduction in water cover, underlining vast landscape alterations. SVM stood out for its consistent accuracy. To validate the methodological robustness and broaden its applicability, we replicated the procedures using diverse land cover collection, including ESA WorldCover 10 m and Dynamic World. This comprehensive validation encompassed varied catastrophic events, extending the methodology's relevance beyond its original scope. The consistent findings across different scenarios underscored the method's robustness and underscored its potential for broader utilization. This streamlined, cost-effective approach suits multiple land cover products, setting the stage for constant Earth feature monitoring. In light of escalating natural disasters, the synergy of machine learning and geospatial technology spotlighted here offers promising avenues for improved disaster preparedness and response. [ABSTRACT FROM AUTHOR]

Published
2024
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29. What can we learn from senescent platelets, their transcriptomes and proteomes?

Author

Allan, Harriet E., Vadgama, Ami, Armstrong, Paul C., and Warner, Timothy D.

Subjects
BLOOD platelets, TRANSCRIPTOMES, PROTEOMICS, THROMBOSIS
Abstract

Research into the natural aging process of platelets has garnered much research interest in recent years, and there have long been associations drawn between the proportion of newly formed platelets in the circulation and the risk of thrombosis. However, these observations have largely been demonstrated in patient groups in which there may be underlying systemic changes that effect platelet function. Recent advances in technology have allowed in-depth analysis of differently aged platelets isolated from the peripheral blood of healthy individuals and have demonstrated that aged platelets, often referred to as senescent platelets, undergo extensive changes in the transcriptome and proteome. Ultimately, these changes result in platelets whose functions have deteriorated such that they cannot partake in hemostatic responses to the same extent as newly formed platelets. Here, we review transcriptomic and proteomic research in platelet aging in the context of health and how this research sheds light upon alterations in platelet structure and function. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Aspirin blocks formation of metastatic intravascular niches by inhibiting platelet-derived COX-1/thromboxane [A.sub.2]

Author

Lucotti, Serena, Cerutti, Camilla, Soyer, Magali, Gil-Bernabe, Ana M., Gomes, Ana L., Allen, Philip D., Smart, Sean, Markelc, Bostjan, Watson, Karla, Armstrong, Paul C., Mitchell, Jane A., Warner, Timothy D., Ridley, Anne J., and Muschel, Ruth J.

Subjects
Prostanoids -- Research, Aspirin -- Physiological aspects -- Research, Medical research, Cell adhesion -- Research, Cancer cells, Endothelium, Macrophages, Cancer, Clinical trials, COX-2 inhibitors, Cancer metastasis, Tumors, Lipids, Health care industry
Abstract

Because metastasis is associated with the majority of cancer-related deaths, its prevention is a clinical aspiration. Prostanoids are a large family of bioactive lipids derived from the activity of cyclooxygenase-1 (COX-1) and COX-2. Aspirin impairs the biosynthesis of all prostanoids through the irreversible inhibition of both COX isoforms. Long-term administration of aspirin leads to reduced distant metastases in murine models and clinical trials, but the COX isoform, downstream prostanoid, and cell compartment responsible for this effect are yet to be determined. Here, we have shown that aspirin dramatically reduced lung metastasis through inhibition of COX-1 while the cancer cells remained intravascular and that inhibition of platelet COX-1 alone was sufficient to impair metastasis. Thromboxane [A.sub.2] ([TXA.sub.2]) was the prostanoid product of COX- 1 responsible for this antimetastatic effect. Inhibition of the COX-1/[TXA.sub.2] pathway in platelets decreased aggregation of platelets on tumor cells, endothelial activation, tumor cell adhesion to the endothelium, and recruitment of metastasis-promoting monocytes/ macrophages, and diminished the formation of a premetastatic niche. Thus, platelet-derived [TXA.sub.2] orchestrates the generation of a favorable intravascular metastatic niche that promotes tumor cell seeding and identifies COX- 1/[TXA.sub.2] signaling as a target for the prevention of metastasis., Introduction Prostanoids are a family of bioactive lipids comprising prostaglandins (e.g., [PGD.sub.2], [PGE.sub.2], [PGF.sub.2a]), thromboxane [A.sub.2] ([TXA.sub.2]), and prostacyclin ([PGI.sub.2]). The rate-limiting step of prostanoid biosynthesis is catalyzed by cyclooxygenase [...]

Published
2019
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32. Crack arrest markings in stress corrosion cracking of 7xxx aluminium alloys: insights into active hydrogen embrittlement mechanisms

Author

Freixes, Martí López, Zhou, Xuyang, Aymerich-Armengol, Raquel, Vega-Paredes, Miquel, Peguet, Lionel, Warner, Timothy, and Gault, Baptiste

Subjects
Condensed Matter - Materials Science, Materials Science (cond-mat.mtrl-sci), FOS: Physical sciences
Abstract

Crack growth in stress corrosion cracking (SCC) in 7xxx Al alloys is an intermittent process, which generates successive crack arrest markings (CAMs) visible on the fracture surface. It is conjectured that H is generated at the crack tip during crack arrest, which then facilitates crack advancement through hydrogen embrittlement. Here, nanoscale imaging by 4D-scanning-transmission electron microscopy and atom probe tomography show that CAMs are produced by oxidation at the arrested crack tip, matrix precipitates dissolve and solute diffuse towards the growing CAM. Substantial homogenous residual strain remains underneath the fracture surface, indicative of non-localized plastic activity. Our study suggests that H induces crack propagation through decohesion.

Published
2023

37. PHD by Published Works

Author

Warner, Timothy John

Subjects
781.64, Audio technology, Record producers, Production technologies
Abstract

The thesis explores the complex relationship between modern audio technologies and the art of popular music through close scrutiny specific artefacts, a largely neglected area of musicological research. The detailed analyses presented here reveal the ways in which particular analogue and digital audio technologies are used, and how these have tended to shape and inform the musical and sonic characteristics of popular music recordings and related artefacts.

Published
2007

49. Incorporating Concept Mapping in Project-Based Learning: Lessons from Watershed Investigations

Author

Rye, James, Landenberger, Rick, and Warner, Timothy A.

Abstract

The concept map tool set forth by Novak and colleagues is underutilized in education. A meta-analysis has encouraged teachers to make extensive use of concept mapping, and researchers have advocated computer-based concept mapping applications that exploit hyperlink technology. Through an NSF sponsored geosciences education grant, middle and secondary science teachers participated in professional development to apply computer-based concept mapping in project-based learning (PBL) units that investigated local watersheds. Participants attended a summer institute, engaged in a summer through spring online learning academy, and presented PBL units at a subsequent fall science teachers' convention. The majority of 17 teachers who attended the summer institute had previously used the concept mapping strategy with students and rated it highly. Of the 12 teachers who continued beyond summer, applications of concept mapping ranged from collaborative planning of PBL projects to building students' vocabulary to students producing maps related to the PBL driving question. Barriers to the adoption and use of concept mapping included technology access at the schools, lack of time for teachers to advance their technology skills, lack of student motivation to choose to learn, and student difficulty with linking terms. In addition to mitigating the aforementioned barriers, projects targeting teachers' use of technology tools may enhance adoption by recruiting teachers as partners from schools as well as a small number that already are proficient in the targeted technology and emphasizing the utility of the concept map as a planning tool.

Published
2013
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50. Phenotypic Characterization of EIF2AK4 Mutation Carriers in a Large Cohort of Patients Diagnosed Clinically With Pulmonary Arterial Hypertension

Author

Hadinnapola, Charaka, Bleda, Marta, Haimel, Matthias, Screaton, Nicholas, Swift, Andrew, Dorfmüller, Peter, Preston, Stephen D., Southwood, Mark, Hernandez-Sanchez, Jules, Martin, Jennifer, Treacy, Carmen, Yates, Katherine, Bogaard, Harm, Church, Colin, Coghlan, Gerry, Condliffe, Robin, Corris, Paul A., Gibbs, Simon, Girerd, Barbara, Holden, Simon, Humbert, Marc, Kiely, David G., Lawrie, Allan, Machado, Rajiv, MacKenzie Ross, Robert, Moledina, Shahin, Montani, David, Newnham, Michael, Peacock, Andrew, Pepke-Zaba, Joanna, Rayner-Matthews, Paula, Shamardina, Olga, Soubrier, Florent, Southgate, Laura, Suntharalingam, Jay, Toshner, Mark, Trembath, Richard, Noordegraaf, Anton Vonk, Wilkins, Martin R., Wort, Stephen J., Wharton, John, Gräf, Stefan, Morrell, Nicholas W., Aitman, Timothy, Bennett, David, Caulfield, Mark, Chinnery, Patrick, Gale, Daniel, Koziell, Ania, Kuijpers, Taco W, Laffan, Michael A, Maher, Eamonn, Markus, Hugh S, Ouwehand, Willem H, Perry, David, Raymond, F Lucy, Roberts, Irene, Smith, Kenneth, Thrasher, Adrian, Watkins, Hugh, Williamson, Catherine, Woods, Geoffrey, Ashford, Sofie, Bradley, John R, Fletcher, Debra, Hammerton, Tracey, James, Roger, Kingston, Nathalie, Ouwehand, Willem H, Penkett, Christopher J, Raymond, F Lucy, Stirrups, Kathleen, Veltman, Marijke, Young, Tim, Ashford, Sofie, Brown, Matthew, Clements-Brod, Naomi, Davis, John, Dewhurst, Eleanor, Erwood, Marie, Frary, Amy, Linger, Rachel, Papadia, Sofia, Rehnstrom, Karola, Stark, Hannah, Allsup, David, Austin, Steve, Bakchoul, Tamam, Bariana, Tadbir K, Bolton-Maggs, Paula, Chalmers, Elizabeth, Collins, Peter, Erber, Wendy N, Everington, Tamara, Favier, Remi, Freson, Kathleen, Furie, Bruce, Gattens, Michael, Gomez, Keith, Greene, Daniel, Greinacher, Andreas, Hart, Daniel, Heemskerk, Johan WM, Henskens, Yvonne, Kazmi, Rashid, Keeling, David, Kelly, Anne M, Laffan, Michael A, Lambert, Michele P, Lentaigne, Claire, Liesner, Ri, Mangles, Sarah, Mathias, Mary, Millar, Carolyn M, Mumford, Andrew, Nurden, Paquita, Ouwehand, Willem H, Papadia, Sofia, Payne, Jeanette, Pasi, John, Perry, David J, Peerlinck, Kathelijne, Richards, Michael, Rondina, Matthew, Roughley, Catherine, Schulman, Sol, Schulze, Harald, Scully, Marie, Sivapalaratnam, Suthesh, Tait, R Campbell, Talks, Kate, Thachil, Jecko, Turro, Ernest, Toh, Cheng-Hock, Van Geet, Chris, De Vries, Minka, Warner, Timothy Q, Westbury, Sarah, Furnell, Abigail, Mapeta, Rutendo, Simeoni, Ilenia, Staines, Simon, Stephens, Jonathan, Stirrups, Kathleen, Whitehorn, Deborah, Watt, Christopher, Attwood, Antony, Daugherty, Louise, Deevi, Sri VV, Halmagyi, Csaba, Hu, Fengyuan, James, Roger, Matser, Vera, Meacham, Stuart, Megy, Karyn, Penkett, Christopher J, Stirrups, Kathleen, Titterton, Catherine, Tuna, Salih, Yu, Ping, von Ziegenweldt, Julie, Astle, William, Carss, Keren, Greene, Daniel, Lango-Allen, Hana, Turro, Ernest, Astle, William, Greene, Daniel, Richardson, Sylvia, Turro, Ernest, Calleja, Paul, Rankin, Stuart, Turek, Wojciech, Bryson, Christine, Anderson, Julie, Fletcher, Debra, McJannet, Coleen, Stock, Sophie, Young, Tim, Wassmer, Evangeline, Sohal, Aman, Santra, Saikat, Vogt, Julie, Chitre, Manali, Krishnakumar, Deepa, Ambegaonkar, Gautum, Maw, Anna, Armstrong, Ruth, Park, Soo-Mi, Mehta, Sarju, Paterson, Joan, Carmichael, Jenny, Allen, Louise, Hensiek, Anke, Firth, Helen, Stein, Penelope, Deegan, Patrick, Doffinger, Rainer, Parker, Alasdair, Bitner-Glindzicz, Maria, Scott, Richard, Hurst, Jane, Rosser, Elisabeth, Lees, Melissa, Clement, Emma, Henderson, Robert, Thompson, Dorothy, Gardham, Alice, Gissen, Paul, Josifova, Dragana, Thomas, Ellen, Patch, Chris, Deshpande, Charu, Flinter, Frances, Holder, Muriel, Canham, Natalie, Wakeling, Emma, Holder, Susan, Ghali, Neeti, Brady, Angie, Clowes, Virginia, MacLaren, Robert, Webster, Andrew, Moore, Anthony, Arno, Gavin, Michaelides, Michel, Rankin, Julia, Kurian, Manju, Murphy, Elaine, Carss, Keren, Sanchis-Juan, Alba, Erwood, Marie, Dewhurst, Eleanor, Grozeva, Detelina, Raymond, F Lucy, Reid, Evan, Woods, Geoff, Tischkowitz, Marc, Sandford, Richard, Ali, Sonia, Creaser-Myers, Amanda, Cookson, Victoria, DaCosta, Rosa, Dormand, Natalie, Ghataorhe, Pavandeep K, Greenhalgh, Alan, Huis in’t Veld, Anna, Kennedy, Fiona, Mackenzie Ross, Rob, Masati, Larahmie, Meehan, Sharon, Othman, Shokri, Pollock, Val, Polwarth, Gary, Rhodes, Christopher J, Rue-Albrecht, Kevin, Schotte, Gwen, Shipley, Debbie, Tan, Yvonne, Wanjiku, Ivy, Wort, John, Smith, Kenneth, Kuijpers, Taco, Thrasher, Adrian, Thaventhiran, James, Brown, Matthew, Lango Allen, Hana, Simeoni, Ilenia, Staples, Emily, Samarghitean, Crina, Alachkar, Hana, Antrobus, Richard, Arumugakani, Gururaj, Bacchelli, Chiara, Baxendale, Helen, Bethune, Claire, Bibi, Shahnaz, Booth, Claire, Browning, Michael, Burns, Siobhan, Chandra, Anita, Cooper, Nichola, Davies, Sophie, Devlin, Lisa, Doffinger, Rainer, Drewe, Elizabeth, Edgar, David, Egner, William, Ghurye, Rohit, Gilmour, Kimberley, Goddard, Sarah, Gordins, Pavel, Grigoriadou, Sofia, Hackett, Scott, Hague, Rosie, Hayman, Grant, Herwadkar, Archana, Huissoon, Aarnoud, Jolles, Stephen, Kelleher, Peter, Kumararatne, Dinakantha, Lear, Sara, Longhurst, Hilary, Lorenzo, Lorena, Maimaris, Jesmeen, Manson, Ania, McDermott, Elizabeth, Murng, Sai, Nejentsev, Sergey, Noorani, Sadia, Oksenhendler, Eric, Ponsford, Mark, Qasim, Waseem, Quinti, Isabella, Richter, Alex, Sargur, Ravishankar, Savic, Sinisa, Seneviratne, Suranjith, Sewell, Carrock, Stauss, Hans, Thomas, Moira, Welch, Steve, Willcocks, Lisa, Yeatman, Nigel, and Yong, Patrick

Published
2017
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