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1. The Effects of Signal-to-Noise Ratio on Generative Adversarial Networks Applied to Marine Bioacoustic Data

Author

Atkinson, Georgia, Wright, Nick, McGough, A. Stephen, and Berggren, Per

Subjects
Computer Science - Sound, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

In recent years generative adversarial networks (GANs) have been used to supplement datasets within the field of marine bioacoustics. This is driven by factors such as the cost to collect data, data sparsity and aid preprocessing. One notable challenge with marine bioacoustic data is the low signal-to-noise ratio (SNR) posing difficulty when applying deep learning techniques such as GANs. This work investigates the effect SNR has on the audio-based GAN performance and examines three different evaluation methodologies for GAN performance, yielding interesting results on the effects of SNR on GANs, specifically WaveGAN., Comment: 6 pages, 6 figures

Published
2023

2. Towards Automatic Cetacean Photo-Identification: A Framework for Fine-Grain, Few-Shot Learning in Marine Ecology

Author

Trotter, Cameron, Wright, Nick, McGough, A. Stephen, Sharpe, Matt, Cheney, Barbara, Civil, Mònica Arso, Moore, Reny Tyson, Allen, Jason, and Berggren, Per

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning
Abstract

Photo-identification (photo-id) is one of the main non-invasive capture-recapture methods utilised by marine researchers for monitoring cetacean (dolphin, whale, and porpoise) populations. This method has historically been performed manually resulting in high workload and cost due to the vast number of images collected. Recently automated aids have been developed to help speed-up photo-id, although they are often disjoint in their processing and do not utilise all available identifying information. Work presented in this paper aims to create a fully automatic photo-id aid capable of providing most likely matches based on all available information without the need for data pre-processing such as cropping. This is achieved through a pipeline of computer vision models and post-processing techniques aimed at detecting cetaceans in unedited field imagery before passing them downstream for individual level catalogue matching. The system is capable of handling previously uncatalogued individuals and flagging these for investigation thanks to catalogue similarity comparison. We evaluate the system against multiple real-life photo-id catalogues, achieving mAP@IOU[0.5] = 0.91, 0.96 for the task of dorsal fin detection on catalogues from Tanzania and the UK respectively and 83.1, 97.5% top-10 accuracy for the task of individual classification on catalogues from the UK and USA., Comment: 8 pages, 8 figures, 3 tables. Submitted and accepted to IEEE Big Data 2022 Conference

Published
2022

3. NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation

Author

Trotter, Cameron, Atkinson, Georgia, Sharpe, Matt, Richardson, Kirsten, McGough, A. Stephen, Wright, Nick, Burville, Ben, and Berggren, Per

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

We introduce the Northumberland Dolphin Dataset 2020 (NDD20), a challenging image dataset annotated for both coarse and fine-grained instance segmentation and categorisation. This dataset, the first release of the NDD, was created in response to the rapid expansion of computer vision into conservation research and the production of field-deployable systems suited to extreme environmental conditions -- an area with few open source datasets. NDD20 contains a large collection of above and below water images of two different dolphin species for traditional coarse and fine-grained segmentation. All data contained in NDD20 was obtained via manual collection in the North Sea around the Northumberland coastline, UK. We present experimentation using standard deep learning network architecture trained using NDD20 and report baselines results., Comment: 5 pages, 6 figures, download link, submitted to FGVC7 Workshop @ CVPR20

Published
2020

4. The Northumberland Dolphin Dataset: A Multimedia Individual Cetacean Dataset for Fine-Grained Categorisation

Author

Trotter, Cameron, Atkinson, Georgia, Sharpe, Matthew, McGough, A. Stephen, Wright, Nick, and Berggren, Per

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

Methods for cetacean research include photo-identification (photo-id) and passive acoustic monitoring (PAM) which generate thousands of images per expedition that are currently hand categorised by researchers into the individual dolphins sighted. With the vast amount of data obtained it is crucially important to develop a system that is able to categorise this quickly. The Northumberland Dolphin Dataset (NDD) is an on-going novel dataset project made up of above and below water images of, and spectrograms of whistles from, white-beaked dolphins. These are produced by photo-id and PAM data collection methods applied off the coast of Northumberland, UK. This dataset will aid in building cetacean identification models, reducing the number of human-hours required to categorise images. Example use cases and areas identified for speed up are examined., Comment: 4 pages, 4 figures, submitted to FGVC6 Workshop at CVPR2019

Published
2019

6. Mechanism and effects of pulsatile GABA secretion from cytosolic pools in the human beta cell.

Author

Menegaz, Danusa, Hagan, D Walker, Almaça, Joana, Cianciaruso, Chiara, Rodriguez-Diaz, Rayner, Molina, Judith, Dolan, Robert M, Becker, Matthew W, Schwalie, Petra C, Nano, Rita, Lebreton, Fanny, Kang, Chen, Sah, Rajan, Gaisano, Herbert Y, Berggren, Per-Olof, Baekkeskov, Steinunn, Caicedo, Alejandro, and Phelps, Edward A

Abstract

Pancreatic beta cells synthesize and secrete the neurotransmitter γ-aminobutyric acid (GABA) as a paracrine and autocrine signal to help regulate hormone secretion and islet homeostasis. Islet GABA release has classically been described as a secretory vesicle-mediated event. Yet, a limitation of the hypothesized vesicular GABA release from islets is the lack of expression of a vesicular GABA transporter in beta cells. Consequentially, GABA accumulates in the cytosol. Here we provide evidence that the human beta cell effluxes GABA from a cytosolic pool in a pulsatile manner, imposing a synchronizing rhythm on pulsatile insulin secretion. The volume regulatory anion channel (VRAC), functionally encoded by LRRC8A or Swell1, is critical for pulsatile GABA secretion. GABA content in beta cells is depleted and secretion is disrupted in islets from type 1 and type 2 diabetic patients, suggesting that loss of GABA as a synchronizing signal for hormone output may correlate with diabetes pathogenesis.

Published
2019

7. An MR-based brain template and atlas for optical projection tomography and light sheet fluorescence microscopy in neuroscience

Author

Willekens, Stefanie M. A., primary, Morini, Federico, additional, Mediavilla, Tomas, additional, Nilsson, Emma, additional, Orädd, Greger, additional, Hahn, Max, additional, Chotiwan, Nunya, additional, Visa, Montse, additional, Berggren, Per-Olof, additional, Ilegems, Erwin, additional, Överby, Anna K., additional, Ahlgren, Ulf, additional, and Marcellino, Daniel, additional

Published
2024
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10. Linking extinction risk to the economic and nutritional value of sharks in small‐scale fisheries.

Author

Temple, Andrew J., Berggren, Per, Jiddawi, Narriman, Wambiji, Nina, Poonian, Chris N. S., Salmin, Yussuf N., Berumen, Michael L., and Stead, Selina M.

Abstract

To achieve sustainable shark fisheries, it is key to understand not only the biological drivers and environmental consequences of overfishing, but also the social and economic drivers of fisher behavior. The extinction risk of sharks is highest in coastal tropical waters, where small‐scale fisheries are most prevalent. Small‐scale fisheries provide a critical source of economic and nutritional security to coastal communities, and these fishers are among the most vulnerable social and economic groups. We used Kenya's and Zanzibar's small‐scale shark fisheries, which are illustrative of the many data‐poor, small‐scale shark fisheries worldwide, as case studies to explore the relationship between extinction risk and the economic and nutritional value of sharks. To achieve this, we combined existing data on shark landings, extinction risk, and nutritional value with sales data at 16 key landing sites and information from interviews with 476 fishers. Shark fisheries were an important source of economic and nutritional security, valued at >US$4 million annually and providing enough nutrition for tens of thousands of people. Economically and nutritionally, catches were dominated by threatened species (72.7% and 64.6–89.7%, respectively). The most economically valuable species were large and slow to reproduce (e.g. mobulid rays, wedgefish, and bull, silky, and mako sharks) and therefore more likely to be threatened with extinction. Given the financial incentive and intensive fishing pressure, small‐scale fisheries are undoubtedly major contributors to the decline of threatened coastal shark species. In the absence of effective fisheries management and enforcement, we argue that within small‐scale fisheries the conditions exist for an economically incentivized feedback loop in which vulnerable fishers are driven to persistently overfish vulnerable and declining shark species. To protect these species from extinction, this feedback loop must be broken. [ABSTRACT FROM AUTHOR]

Published
2024
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17. An integrative proteomics method identifies a regulator of translation during stem cell maintenance and differentiation

Author

Sabatier, Pierre, Beusch, Christian M., Saei, Amir A., Aoun, Mike, Moruzzi, Noah, Coelho, Ana, Leijten, Niels, Nordenskjöld, Magnus, Micke, Patrick, Maltseva, Diana, Tonevitsky, Alexander G., Millischer, Vincent, Carlos Villaescusa, J., Kadekar, Sandeep, Gaetani, Massimiliano, Altynbekova, Kamilya, Kel, Alexander, Berggren, Per-Olof, Simonson, Oscar, Grinnemo, Karl-Henrik, Holmdahl, Rikard, Rodin, Sergey, and Zubarev, Roman A.

Published
2021
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22. Kynurenic Acid and Gpr35 Regulate Adipose Tissue Energy Homeostasis and Inflammation

Author

Agudelo, Leandro Z., Ferreira, Duarte M.S., Cervenka, Igor, Bryzgalova, Galyna, Dadvar, Shamim, Jannig, Paulo R., Pettersson-Klein, Amanda T., Lakshmikanth, Tadepally, Sustarsic, Elahu G., Porsmyr-Palmertz, Margareta, Correia, Jorge C., Izadi, Manizheh, Martínez-Redondo, Vicente, Ueland, Per M., Midttun, Øivind, Gerhart-Hines, Zachary, Brodin, Petter, Pereira, Teresa, Berggren, Per-Olof, and Ruas, Jorge L.

Published
2018
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30. Apolipoprotein CIII Promotes Ca2+-Dependent β Cell Death in Type 1 Diabetes

Author

Juntti-Berggren, Lisa, Refai, Essam, Appelskog, Ioulia, Andersson, Mats, Imreh, Gabriela, Dekki, Nancy, Uhles, Sabine, Yu, Lina, Griffiths, William J., Zaitsev, Sergei, Leibiger, Ingo, Yang, Shao-Nian, Olivecronal, Gunilla, Jörnvall, Hans, Berggren, Per-Olof, and Spiegelman, Bruce M.

Published
2004

36. Structural basis for delta cell paracrine regulation in pancreatic islets

Author

Arrojo e Drigo, Rafael, Jacob, Stefan, García-Prieto, Concha F., Zheng, Xiaofeng, Fukuda, Masahiro, Nhu, Hoa Tran Thi, Stelmashenko, Olga, Peçanha, Flavia Letícia Martins, Rodriguez-Diaz, Rayner, Bushong, Eric, Deerinck, Thomas, Phan, Sebastien, Ali, Yusuf, Leibiger, Ingo, Chua, Minni, Boudier, Thomas, Song, Sang-Ho, Graf, Martin, Augustine, George J., Ellisman, Mark H., and Berggren, Per-Olof

Published
2019
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38. Author Correction: Structural basis for delta cell paracrine regulation in pancreatic islets

Author

e Drigo, Rafael Arrojo, Jacob, Stefan, García-Prieto, Concha F., Zheng, Xiaofeng, Fukuda, Masahiro, Nhu, Hoa Tran Thi, Stelmashenko, Olga, Peçanha, Flavia Letícia Martins, Rodriguez-Diaz, Rayner, Bushong, Eric, Deerinck, Thomas, Phan, Sebastien, Ali, Yusuf, Leibiger, Ingo, Chua, Minni, Boudier, Thomas, Song, Sang-Ho, Graf, Martin, Augustine, George J., Ellisman, Mark H., and Berggren, Per-Olof

Published
2019
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