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4,620 results on '"Nielsen, P."'

1. Quantum learning advantage on a scalable photonic platform

Author

Liu, Zheng-Hao, Brunel, Romain, Østergaard, Emil E. B., Cordero, Oscar, Chen, Senrui, Wong, Yat, Nielsen, Jens A. H., Bregnsbo, Axel B., Zhou, Sisi, Huang, Hsin-Yuan, Oh, Changhun, Jiang, Liang, Preskill, John, Neergaard-Nielsen, Jonas S., and Andersen, Ulrik L.

Subjects
Quantum Physics
Abstract

Recent advancements in quantum technologies have opened new horizons for exploring the physical world in ways once deemed impossible. Central to these breakthroughs is the concept of quantum advantage, where quantum systems outperform their classical counterparts in solving specific tasks. While much attention has been devoted to computational speedups, quantum advantage in learning physical systems remains a largely untapped frontier. Here, we present a photonic implementation of a quantum-enhanced protocol for learning the probability distribution of a multimode bosonic displacement process. By harnessing the unique properties of continuous-variable quantum entanglement, we obtain a massive advantage in sample complexity with respect to conventional methods without entangled resources. With approximately 5 dB of two-mode squeezing -- corresponding to imperfect Einstein--Podolsky--Rosen (EPR) entanglement -- we learn a 100-mode bosonic displacement process using 11.8 orders of magnitude fewer samples than a conventional scheme. Our results demonstrate that even with non-ideal, noisy entanglement, a significant quantum advantage can be realized in continuous-variable quantum systems. This marks an important step towards practical quantum-enhanced learning protocols with implications for quantum metrology, certification, and machine learning., Comment: 8 pages, 3 figures

Published
2025

2. Bridging DNP and MAS NMR dipolar recoupling -- from static single crystal to spinning powders

Author

Carvalho, Jose P., Nielsen, Anders Bodholt, Baligacs, Eniko, Wili, Nino, and Nielsen, Niels Chr.

Subjects
Physics - Chemical Physics
Abstract

Spin engineering of advanced pulse sequences has had a transformative impact on the development of nuclear magnetic resonance (NMR) spectroscopy, to an extending degree also electron paramagnetic resonance (EPR), and the hybrid between the two, dynamic nuclear polarization (DNP). Based on a simple formalism, we demonstrate that (i) single-crystal static-sample optimisations may tremendously ease design of experiments for rotating powders and (ii) pulse sequences may readily be exchanged between these distinct spectroscopies. Specifically, we design broadband heteronuclear solid-state NMR magic-angle-spinning (MAS) dipolar recoupling experiments based on the recently developed PLATO (PoLarizAtion Transfer via non-linear Optimization) microwave (MW) pulse sequence optimized on a single crystal for powder static-sample DNP. Using this concept, we demonstrate design of ultra-broadband 13C-15N and 2H-13C cross-polarization experiments, using PLATO on the 13C radio-frequency (RF) channel and square/ramped or RESPIRATION (Rotor Echo Short Pulse IRrAdiaTION) RF irradiation on the 15N and 2H RF channels, respectively.

Published
2025

3. On the use of an advanced Kirchhoff rod model to study mooring lines

Author

Roccia, Bruno A., Nguyen, Hoa T., Veseth, Petter, Nielsen, Finn G., and Gebhardt, Cristian G.

Subjects
Physics - Fluid Dynamics
Abstract

In this work, we investigate the application of an advanced nonlinear torsion- and shear-free Kirchhoff rod model, enhanced with a penalty-based barrier function (to simulate the seabed contact), intended for studying the static and dynamic behavior of mooring lines. The formulation incorporates conservative and non-conservative external loads, including those coming from the surrounding flow (added mass, tangential drag, and normal drag). To illustrate the favorable features of this model, we consider some key scenarios such as static configurations, pulsating force applications at the fairlead, and fluid-structure interaction between mooring lines and the surrounding flow. Verification against well-established solutions, including catenary configurations and OpenFAST simulations, shows excellent accuracy in predicting mooring line responses for a floating offshore wind turbine. Among the most important results, we can mention that under normal pulsating loads at the fairlead, the mooring line exhibits a transition from a drag-dominated regime at low frequencies to an added-mass-dominated regime at higher frequencies. Furthermore, tangential forcing at the fairlead reveals a strong coupling between axial and bending dynamics, contrasting with normal forcing scenarios where axial dynamics remain largely unaffected. These findings underscore the potential of the proposed approach for advanced mooring line simulations.

Published
2025

4. Prediction hubs are context-informed frequent tokens in LLMs

Author

Nielsen, Beatrix M. G., Macocco, Iuri, and Baroni, Marco

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Hubness, the tendency for few points to be among the nearest neighbours of a disproportionate number of other points, commonly arises when applying standard distance measures to high-dimensional data, often negatively impacting distance-based analysis. As autoregressive large language models (LLMs) operate on high-dimensional representations, we ask whether they are also affected by hubness. We first show, theoretically, that the only representation comparison operation performed by LLMs, namely that between context and unembedding vectors to determine continuation probabilities, is not characterized by the concentration of distances phenomenon that typically causes the appeareance of nuisance hubness. We then empirically show that this comparison still leads to a high degree of hubness, but the hubs in this case do not constitute a disturbance. They are rather the result of context-modulated frequent tokens often appearing in the pool of likely candidates for next token prediction. On the other hand, when other distance computations involving LLM representations are performed, we do not have the same theoretical guarantees, and, indeed, we see nuisance hubs appear. In summary, our work highlights, on the one hand, how hubness, while omnipresent in high-dimensional spaces, is not always a negative property that needs to be mitigated, and, on the other hand, it shows that various widely-used LLMs have developed a guessing strategy that consists in constantly assigning a high probability to frequent tokens.

Published
2025

5. A primordial radius valley as a consequence of planet formation

Author

Nielsen, Jesper, Johansen, Anders, Bali, Komal, and Dorn, Caroline

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

The radius distribution of close-in planets has been observed to have a bimodal distribution with a dearth of planets around ~1.5-2.0 $R_\oplus$ commonly referred to as the ''radius valley''. The origin of the valley is normally attributed to mass-loss process such as photoevaporation or core-powered mass loss. Recent work, however, has suggested that the radius valley may instead arise as a consequence of gas accretion by low-mass planets. In this work we therefore aim to investigate the formation of a primordial radius valley from the formation of planet cores through pebble accretion up until the dissipation of the protoplanetary disc and subsequent contraction of accreted atmospheres. The goal of this work is to explore the conditions for forming a primordial radius valley from first principles of planet formation theory, rather than attempting to explain the detailed structure of the observed valley. We use an analytical model with minimal assumptions to estimate the contraction rate of atmospheres and, indeed, find the formation of a primordial radius valley. The planets smaller than the valley did not reach the pebble isolation mass, which is required for the planets to cool down sufficiently to be able to accrete a significant amount of gas. We also estimate the slopes of the radius gap as a function of orbital period for the intrinsic population as well as for planets with orbital periods <100 days. For the intrinsic population, the radius gap follows the pebble isolation mass and increases with increasing orbital period, while for close-in planets the direction of the slope reverses and decreases with increasing orbital period. We find that planets smaller than the radius valley are predominantly rocky while the population of planets larger than the valley consists of a mixture of rocky and water-rich planets., Comment: 24 Pages, 23 Figures, accepted in A&A

Published
2025

6. On (in)consistency of M-estimators under contamination

Author

Klooster, Jens and Nielsen, Bent

Subjects
Mathematics - Statistics Theory, Economics - Econometrics, Statistics - Methodology
Abstract

We consider robust location-scale estimators under contamination. We show that commonly used robust estimators such as the median and the Huber estimator are inconsistent under asymmetric contamination, while the Tukey estimator is consistent. In order to make nuisance parameter free inference based on the Tukey estimator a consistent scale estimator is required. However, standard robust scale estimators such as the interquartile range and the median absolute deviation are inconsistent under contamination., Comment: 20 pages, 1 figure, 2 tables

Published
2025

7. FoQA: A Faroese Question-Answering Dataset

Author

Simonsen, Annika, Nielsen, Dan Saattrup, and Einarsson, Hafsteinn

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

We present FoQA, a Faroese extractive question-answering (QA) dataset with 2,000 samples, created using a semi-automated approach combining Large Language Models (LLMs) and human validation. The dataset was generated from Faroese Wikipedia articles using GPT-4-turbo for initial QA generation, followed by question rephrasing to increase complexity and native speaker validation to ensure quality. We provide baseline performance metrics for FoQA across multiple models, including LLMs and BERT, demonstrating its effectiveness in evaluating Faroese QA performance. The dataset is released in three versions: a validated set of 2,000 samples, a complete set of all 10,001 generated samples, and a set of 2,395 rejected samples for error analysis., Comment: Camera-ready version for RESOURCEFUL workshop, 2025

Published
2025

8. FlexDeMo: Decoupled Momentum Optimization for Fully and Hybrid Sharded Training

Author

From, Mogens Henrik, Nielsen, Jacob, Galke, Lukas, and Schneider-Kamp, Peter

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

Training large neural network models requires extensive computational resources, often distributed across several nodes and accelerators. Recent findings suggest that it may be sufficient to only exchange the fast moving components of the gradients, while accumulating momentum locally (Decoupled Momentum, or DeMo). However, when considering larger models that do not fit on a single accelerate, the exchange of gradient information and the integration of DeMo needs to be reconsidered. Here, we propose employing a hybrid strategy, FlexDeMo, whereby nodes fully synchronize locally between different GPUs and inter-node communication is improved through only using the fast-moving components. This effectively combines previous hybrid sharding strategies with the advantages of decoupled momentum. Our experimental results show that FlexDeMo is on par with AdamW in terms of validation loss, demonstrating its viability.

Published
2025

9. Neutrino Interaction Vertex Reconstruction in DUNE with Pandora Deep Learning

Author

DUNE Collaboration, Abud, A. Abed, Acciarri, R., Acero, M. A., Adames, M. R., Adamov, G., Adamowski, M., Adams, D., Adinolfi, M., Adriano, C., Aduszkiewicz, A., Aguilar, J., Akbar, F., Alemanno, F., Alex, N. S., Allison, K., Alrashed, M., Alton, A., Alvarez, R., Alves, T., Aman, A., Amar, H., Amedo, P., Anderson, J., Andreopoulos, C., Andreotti, M., Andrews, M. P., Andrianala, F., Andringa, S., Anjarazafy, F., Antic, D., Antoniassi, M., Antonova, M., Aranda-Fernandez, A., Arellano, L., Diaz, E. Arrieta, Arroyave, M. A., Asaadi, J., Ashkenazi, A., Asner, D., Asquith, L., Atkin, E., Auguste, D., Aurisano, A., Aushev, V., Autiero, D., Gómez, D. Ávila, Azam, M. B., Azfar, F., Back, A., Back, H., Back, J. J., Bagaturia, I., Bagby, L., Baigarashev, D., Balasubramanian, S., Balboni, A., Baldi, P., Baldini, W., Baldonedo, J., Baller, B., Bambah, B., Banerjee, R., Barao, F., Barbu, D., Barenboim, G., Alzás, P. Barham, Barker, G. J., Barkhouse, W., Barr, G., Monarca, J. Barranco, Barros, A., Barros, N., Barrow, D., Barrow, J. L., Basharina-Freshville, A., Bashyal, A., Basque, V., Basu, D., Batchelor, C., Bathe-Peters, L., Battat, J. B. R., Battisti, F., Bay, F., Bazetto, M. C. Q., Alba, J. L. L. Bazo, Beacom, J. F., Bechetoille, E., Behera, B., Belchior, E., Bell, B., Bell, G., Bellantoni, L., Bellettini, G., Bellini, V., Beltramello, O., Montiel, C. Benitez, Benjamin, D., Neves, F. Bento, Berger, J., Berkman, S., Bernal, J., Bernardini, P., Bersani, A., Bertolini, E., Bertolucci, S., Betancourt, M., Rodríguez, A. Betancur, Bezawada, Y., Bezerra, A. T., Bhat, A., Bhatnagar, V., Bhatt, J., Bhattacharjee, M., Bhattacharya, M., Bhuller, S., Bhuyan, B., Biagi, S., Bian, J., Biery, K., Bilki, B., Bishai, M., Blake, A., Blaszczyk, F. D., Blazey, G. C., Blucher, E., Bogart, B., Bogenschuetz, J., Boissevain, J., Bolognesi, S., Bolton, T., Bomben, L., Bonesini, M., Bonilla-Diaz, C., Booth, A., Boran, F., Merlo, R. Borges, Bostan, N., Botogoske, G., Bottino, B., Bouet, R., Boza, J., Bracinik, J., Brahma, B., Brailsford, D., Bramati, F., Branca, A., Brandt, A., Bremer, J., Brew, C., Brice, S. J., Brio, V., Brizzolari, C., Bromberg, C., Brooke, J., Bross, A., Brunetti, G., Brunetti, M. B., Buchanan, N., Budd, H., Buergi, J., Bundock, A., Burgardt, D., Butchart, S., V., G. Caceres, Cai, T., Calabrese, R., Calcutt, J., Calivers, L., Calvo, E., Caminata, A., Camino, A. F., Campanelli, W., Campani, A., Benitez, A. Campos, Canci, N., Capó, J., Caracas, I., Caratelli, D., Carber, D., Carceller, J. M., Carini, G., Carlus, B., Carneiro, M. F., Carniti, P., Terrazas, I. Caro, Carranza, H., Carrara, N., Carroll, L., Carroll, T., Carter, A., Casarejos, E., Casazza, D., Forero, J. F. Castaño, Castaño, F. A., Castillo, A., Castromonte, C., Catano-Mur, E., Cattadori, C., Cavalier, F., Cavanna, F., Centro, S., Cerati, G., Cerna, C., Cervelli, A., Villanueva, A. Cervera, Chalifour, M., Chappell, A., Chatterjee, A., Chauhan, B., Chen, H., Chen, M., Chen, W. C., Chen, Y., Chen, Z., Cherdack, D., Chhibra, S. S., Chi, C., Chiapponi, F., Chirco, R., Chitirasreemadam, N., Cho, K., Choate, S., Choi, G., Chokheli, D., Chong, P. S., Chowdhury, B., Christian, D., Chung, M., Church, E., Cicala, M. F., Cicerchia, M., Cicero, V., Ciolini, R., Clarke, P., Cline, G., Cocco, A. G., Coelho, J. A. B., Cohen, A., Collazo, J., Collot, J., Conrad, J. M., Convery, M., Conway, K., Copello, S., Cova, P., Cox, C., Cremonesi, L., Crespo-Anadón, J. I., Crisler, M., Cristaldo, E., Crnkovic, J., Crone, G., Cross, R., Cudd, A., Cuesta, C., Cui, Y., Curciarello, F., Cussans, D., Dai, J., Dalager, O., Dallaway, W., D'Amico, R., da Motta, H., Dar, Z. A., Darby, R., Peres, L. Da Silva, David, Q., Davies, G. S., Davini, S., Dawson, J., De Aguiar, R., De Almeida, P., Debbins, P., Decowski, M. P., de Gouvêa, A., De Holanda, P. C., De Jong, P., Sanchez, P. Del Amo, De Lauretis, G., Delbart, A., Delepine, D., Delgado, M., Dell'Acqua, A., Monache, G. Delle, Delmonte, N., De Lurgio, P., Demario, R., De Matteis, G., Neto, J. R. T. de Mello, DeMuth, D. M., Dennis, S., Densham, C., Denton, P., Deptuch, G. W., De Roeck, A., De Romeri, V., Detje, J. P., Devine, J., Dharmapalan, R., Dias, M., Diaz, A., Díaz, J. S., Díaz, F., Di Capua, F., Di Domenico, A., Di Domizio, S., Di Falco, S., Di Giulio, L., Ding, P., Di Noto, L., Diociaiuti, E., Di Silvestre, V., Distefano, C., Diurba, R., Diwan, M., Djurcic, Z., Dolan, S., Dolce, M., Dolek, F., Dolinski, M. J., Domenici, D., Donati, S., Donon, Y., Doran, S., Douglas, D., Doyle, T. A., Drielsma, F., Duarte, L., Duchesneau, D., Duffy, K., Dugas, K., Dunne, P., Dutta, B., Duyang, H., Dwyer, D. A., Dyshkant, A. S., Dytman, S., Eads, M., Earle, A., Edayath, S., Edmunds, D., Eisch, J., Emark, W., Englezos, P., Ereditato, A., Erjavec, T., Escobar, C. O., Evans, J. J., Ewart, E., Ezeribe, A. C., Fahey, K., Falcone, A., Fani', M., Farnese, C., Farrell, S., Farzan, Y., Felix, J., Feng, Y., Fernandez-Martinez, E., da Silva, M. Ferreira, Ferry, G., Fialova, E., Fields, L., Filip, P., Filkins, A., Filthaut, F., Fiorillo, G., Fiorini, M., Fogarty, S., Foreman, W., Fowler, J., Franc, J., Francis, K., Franco, D., Franklin, J., Freeman, J., Fried, J., Friedland, A., Fucci, M., Fuess, S., Furic, I. K., Furman, K., Furmanski, A. P., Gaba, R., Gabrielli, A., Gago, A. M, Galizzi, F., Gallagher, H., Galli, M., Gallice, N., Galymov, V., Gamberini, E., Gamble, T., Gandhi, R., Ganguly, S., Gao, F., Gao, S., Garcia-Gamez, D., García-Peris, M. Á., Gardim, F., Gardiner, S., Gastler, D., Gauch, A., Gauzzi, P., Gazzana, S., Ge, G., Geffroy, N., Gelli, B., Gent, S., Gerlach, L., Ghosh, A., Giammaria, T., Gibin, D., Gil-Botella, I., Gilligan, S., Gioiosa, A., Giovannella, S., Giri, A. K., Giugliano, C., Giusti, V., Gnani, D., Gogota, O., Gollapinni, S., Gollwitzer, K., Gomes, R. A., Bermeo, L. V. Gomez, Fajardo, L. S. Gomez, Gonzalez-Diaz, D., Goodman, M. C., Goswami, S., Gotti, C., Goudeau, J., Goudzovski, E., Grace, C., Gramellini, E., Gran, R., Granados, E., Granger, P., Grant, C., Gratieri, D. R., Grauso, G., Green, P., Greenberg, S., Greer, J., Griffith, W. C., Grzelak, K., Gu, L., Gu, W., Guarino, V., Guarise, M., Guenette, R., Guerzoni, M., Guffanti, D., Guglielmi, A., Guo, B., Guo, F. Y., Gupta, V., Gurung, G., Gutierrez, D., Guzowski, P., Guzzo, M. M., Gwon, S., Habig, A., Haegel, L., Hagaman, L., Hahn, A., Hakenmüller, J., Hamernik, T., Hamilton, P., Hancock, J., Handley, M., Happacher, F., Harris, D. A., Hart, A. L., Hartnell, J., Hartnett, T., Harton, J., Hasegawa, T., Hasnip, C. M., Hatcher, R., Hawkins, S., Hays, J., He, M., Heavey, A., Heeger, K. M., Heindel, A., Heise, J., Hellmuth, P., Henderson, L., Herner, K., Hewes, V., Higuera, A., Hilgenberg, C., Himmel, A., Hinkle, E., Hirsch, L. R., Ho, J., Zink, J. Hoefken, Hoff, J., Holin, A., Holvey, T., Hong, C., Hoppe, E., Horiuchi, S., Horton-Smith, G. A., Hosokawa, R., Houdy, T., Howard, B., Howell, R., Hristova, I., Hronek, M. S., Huang, J., Huang, R. G., Huang, X., Hulcher, Z., Iles, G., Ilic, N., Iliescu, A. M., Illingworth, R., Ingratta, G., Ioannisian, A., Irwin, B., Oliveira, M. Ismerio, Jackson, C. M., Jain, V., James, E., Jang, W., Jargowsky, B., Jena, D., Jentz, I., Ji, X., Jiang, C., Jiang, J., Jipa, A., Jo, J. H., Joaquim, F. R., Johnson, W., Jollet, C., Jones, R., Jovancevic, N., Judah, M., Jung, C. K., Jung, K. Y., Junk, T., Jwa, Y., Kabirnezhad, M., Kaboth, A. C., Kadenko, I., Kalikulov, O., Kalra, D., Kandemir, M., Kaplan, D. M., Karagiorgi, G., Karaman, G., Karcher, A., Karyotakis, Y., Kasetti, S. P., Kashur, L., Kauther, A., Kazaryan, N., Ke, L., Kearns, E., Keener, P. T., Kelly, K. J., Keloth, R., Kemp, E., Kemularia, O., Kermaidic, Y., Ketchum, W., Kettell, S. H., Khan, N., Khvedelidze, A., Kim, D., Kim, J., Kim, M. J., Kim, S., King, B., King, M., Kirby, M., Kish, A., Klein, J., Kleykamp, J., Klustova, A., Kobilarcik, T., Koch, L., Koehler, K., Koerner, L. W., Koh, D. H., Kordosky, M., Kosc, T., Kostelecký, V. A., Kothekar, K., Kotler, I., Kovalcuk, M., Krah, W., Kralik, R., Kramer, M., Kreczko, L., Krennrich, F., Kroupova, T., Kubota, S., Kubu, M., Kudryavtsev, V. A., Kufatty, G., Kuhlmann, S., Kumar, J., Kumar, P., Kumaran, S., Kunzmann, J., Kuravi, R., Kus, V., Kutter, T., Kvasnicka, J., Labree, T., Lackey, T., Lalău, I., Lambert, A., Land, B. J., Lane, C. E., Lane, N., Lang, K., Langford, T., Langstaff, M., Lanni, F., Larkin, J., Lasorak, P., Last, D., Laundrie, A., Laurenti, G., Lavaut, E., Laycock, P., Lazanu, I., LaZur, R., Lazzaroni, M., Le, T., Leardini, S., Learned, J., LeCompte, T., Miotto, G. Lehmann, Lehnert, R., Leitner, M., Lemoine, H., Silverio, D. Leon, Lepin, L. M., Li, J. -Y, Li, S. W., Li, Y., Liao, H., Lima, R., Lin, C. S., Lindebaum, D., Linden, S., Lineros, R. A., Lister, A., Littlejohn, B. R., Liu, H., Liu, J., Liu, Y., Lockwitz, S., Lomidze, I., Long, K., Lopes, T. V., Lopez, J., de Rego, I. López, López-March, N., LoSecco, J. M., Louis, W. C., Sanchez, A. Lozano, Lu, X. -G., Luk, K. B., Luo, X., Luppi, E., Machado, A. A., Machado, P., Macias, C. T., Macier, J. R., MacMahon, M., Magill, S., Magueur, C., Mahn, K., Maio, A., Major, A., Majumdar, K., Malige, A., Mameli, S., Man, M., Mandujano, R. C., Maneira, J., Manly, S., Mann, A., Manolopoulos, K., Plata, M. Manrique, Corchado, S. Manthey, Manyam, V. N., Manzanillas-Velez, L., Marchan, M., Marchionni, A., Marciano, W., Marfatia, D., Mariani, C., Maricic, J., Marinho, F., Marino, A. D., Markiewicz, T., Marques, F. Das Chagas, Marquet, C., Marshak, M., Marshall, C. M., Marshall, J., Martina, L., Martín-Albo, J., Martinez, N., Caicedo, D. A. Martinez, Martinez-Casales, M., López, F. Martínez, Miravé, P. Martínez, Martynenko, S., Mascagna, V., Mastbaum, A., Masud, M., Matichard, F., Matteucci, G., Matthews, J., Mauger, C., Mauri, N., Mavrokoridis, K., Mawby, I., Mayhew, F., Mazza, R., McAskill, T., McConkey, N., McFarland, K. S., McGrew, C., McNab, A., McNulty, C., Meazza, L., Meddage, V. C. N., Mehmood, M., Mehta, B., Mehta, P., Mei, F., Melas, P., Mellet, L., Mena, O., Mendez, H., Méndez, D. P., Mendonca, A. P., Menegolli, A., Meng, G., Mercuri, A. C. E. A., Meregaglia, A., Messier, M. D., Metallo, S., Metcalf, W., Mewes, M., Meyer, H., Miao, T., Micallef, J., Miccoli, A., Michna, G., Milincic, R., Miller, F., Miller, G., Miller, W., Minotti, A., Miralles, L., Mironov, C., Miryala, S., Miscetti, S., Mishra, C. S., Mishra, P., Mishra, S. R., Mislivec, A., Mladenov, D., Mocioiu, I., Mogan, A., Mohanta, R., Mohayai, T. A., Mokhov, N., Molina, J., Bueno, L. Molina, Montagna, E., Montanari, A., Montanari, C., Montanari, D., Montanino, D., Zetina, L. M. Montaño, Mooney, M., Moor, A. F., Moore, M., Moore, Z., Moreno, D., Moreno-Granados, G., Moreno-Palacios, O., Morescalchi, L., Moretti, R., Morris, C., Mossey, C., Moura, C. A., Mouster, G., Mu, W., Mualem, L., Mueller, J., Muether, M., Muheim, F., Muir, A., Mukhamejanov, Y., Mukhamejanova, A., Mulhearn, M., Munford, D., Munteanu, L. J., Muramatsu, H., Muraz, J., Murphy, M., Murphy, T., Muse, J., Mytilinaki, A., Nachtman, J., Nagai, Y., Nagu, S., Naples, D., Narita, S., Nava, J., Navrer-Agasson, A., Nayak, N., Nebot-Guinot, M., Nehm, A., Nelson, J. K., Neogi, O., Nesbit, J., Nessi, M., Newbold, D., Newcomer, M., Nichol, R., Nicolas-Arnaldos, F., Nielsen, A., Nikolica, A., Nikolov, J., Niner, E., Nishimura, K., Norman, A., Norrick, A., Novella, P., Nowak, A., Nowak, J. A., Oberling, M., Ochoa-Ricoux, J. P., Oh, S., Oh, S. B., Olivier, A., Olson, T., Onel, Y., Onishchuk, Y., Oranday, A., Osbiston, M., Vélez, J. A. Osorio, O'Sullivan, L., Ormachea, L. Otiniano, Pagani, L., Palacio, G., Palamara, O., Palestini, S., Paley, J. M., Pallavicini, M., Palomares, C., Pan, S., Panareo, M., Panda, P., Pandey, V., Vazquez, W. Panduro, Pantic, E., Paolone, V., Papadopoulou, A., Papaleo, R., Papoulias, D., Paramesvaran, S., Parke, S., Parsa, S., Parsa, Z., Parveen, S., Parvu, M., Pasciuto, D., Pascoli, S., Pasqualini, L., Pasternak, J., Camargo, G. Patiño, Paton, J. L., Patrick, C., Patrizii, L., Patterson, R. B., Patzak, T., Paudel, A., Paul, J., Paulucci, L., Pavlovic, Z., Pawloski, G., Payne, D., Peake, A., Pec, V., Pedreschi, E., Peeters, S. J. M., Pellico, W., Pennacchio, E., Penzo, A., Peres, O. L. G., Gonzalez, Y. F. Perez, Pérez-Molina, L., Pernas, C., Perry, J., Pershey, D., Pessina, G., Petrillo, G., Petta, C., Petti, R., Pfaff, M., Pia, V., Pickering, L., Pierini, L., Pietropaolo, F., Pimentel, V. L., Pinaroli, G., Pincha, S., Pinchault, J., Pitts, K., Pletcher, K., Plows, K., Pollack, C., Pollmann, T., Pompa, F., Pons, X., Poonthottathil, N., Popov, V., Poppi, F., Porter, J., Paixão, L. G. Porto, Potekhin, M., Pozzato, M., Pradhan, R., Prakash, T., Prest, M., Psihas, F., Pugnere, D., Pullia, D., Qian, X., Queen, J., Raaf, J. L., Rabelhofer, M., Radeka, V., Rademacker, J., Radics, B., Raffaelli, F., Rafique, A., Raguzin, E., Rahe, A., Rajagopalan, S., Rajaoalisoa, M., Rakhno, I., Rakotondravohitra, L., Ralaikoto, M. A., Ralte, L., Delgado, M. A. Ramirez, Ramson, B., Randriamanampisoa, S. S., Rappoldi, A., Raselli, G., Rath, T., Ratoff, P., Ray, R., Razafinime, H., Razakamiandra, R. F., Rea, E. M., Real, J. S., Rebel, B., Rechenmacher, R., Reichenbacher, J., Reitzner, S. D., Renner, E., Repetto, S., Rescia, S., Resnati, F., Restrepo, Diego, Reynolds, C., Ribas, M., Riboldi, S., Riccio, C., Riccobene, G., Ricol, J. S., Rigan, M., Rikalo, A., Rincón, E. V., Ritchie-Yates, A., Ritter, S., Rivera, D., Robert, A., Roberts, A., Robles, E., Rocha, J. L. Rocabado, Roda, M., Rodrigues, M. J. O., Rondon, J. Rodriguez, Rosauro-Alcaraz, S., Rosier, P., Ross, D., Rossella, M., Rossi, M., Roy, N., Roy, P., Rubbia, C., Rudik, D., Ruggeri, A., Ferreira, G. Ruiz, Rushiya, K., Russell, B., Sacerdoti, S., Saduyev, N., Sahoo, S. K., Sahu, N., Sakhiyev, S., Sala, P., Salmoria, G., Samanta, S., Samios, N., Sanchez, M. C., Bravo, A. Sánchez, Sánchez-Castillo, A., Sanchez-Lucas, P., Sanders, D. A., Sanfilippo, S., Santoro, D., Saoulidou, N., Sapienza, P., Sarcevic, I., Sarra, I., Savage, G., Savinov, V., Scanavini, G., Scaramelli, A., Scarff, A., Schefke, T., Schellman, H., Schifano, S., Schlabach, P., Schmitz, D., Schneider, A. W., Scholberg, K., Schukraft, A., Schuld, B., Schwartz, S., Segade, A., Segreto, E., Senise, C. R., Sensenig, J., Seppela, D., Shaevitz, M. H., Shanahan, P., Sharma, P., Kumar, R., Poudel, S. Sharma, Shaw, K., Shaw, T., Shchablo, K., Shen, J., Shepherd-Themistocleous, C., Shi, J., Shi, W., Shin, S., Shivakoti, S., Shmakov, A., Shoemaker, I., Shooltz, D., Shrock, R., Siden, M., Silber, J., Simard, L., Sinclair, J., Sinev, G., Singh, Jaydip, Singh, J., Singh, L., Singh, P., Singh, V., Chauhan, S. Singh, Sipos, R., Sironneau, C., Sirri, G., Siyeon, K., Skarpaas, K., Smedley, J., Smith, J., Smith, P., Smolik, J., Smy, M., Snape, M., Snider, E. L., Snopok, P., Nunes, M. Soares, Sobel, H., Soderberg, M., Salinas, C. J. Solano, Söldner-Rembold, S., Solomey, N., Solovov, V., Sondheim, W. E., Sorel, M., Soto-Oton, J., Sousa, A., Soustruznik, K., Correia, D. Souza, Spinella, F., Spitz, J., Spooner, N. J. C., Stalder, D., Stancari, M., Stanco, L., Steenis, J., Stein, R., Steiner, H. M., Lisbôa, A. F. Steklain, Stewart, J., Stillwell, B., Stock, J., Stokes, T., Strait, M., Strauss, T., Strigari, L., Stuart, A., Suarez, J. G., Subash, J., Surdo, A., Suter, L., Sutton, K., Suvorov, Y., Svoboda, R., Swain, S. K., Sweeney, C., Szczerbinska, B., Szelc, A. M., Sztuc, A., Taffara, A., Talukdar, N., Tamara, J., Tanaka, H. A., Tang, S., Taniuchi, N., Casanova, A. M. Tapia, Tapper, A., Tariq, S., Tarpara, E., Tatar, E., Tayloe, R., Tedeschi, D., Teklu, A. M., Vidal, J. Tena, Tennessen, P., Tenti, M., Terao, K., Terranova, F., Testera, G., Thakore, T., Thea, A., Thomas, S., Thompson, A., Thorn, C., Thorpe, C., Timm, S. C., Tiras, E., Tishchenko, V., Tiwari, S., Todorović, N., Tomassetti, L., Tonazzo, A., Torbunov, D., Muñoz, D. Torres, Torti, M., Tortola, M., Torun, Y., Tosi, N., Totani, D., Toups, M., Touramanis, C., Tran, D., Travaglini, R., Trevor, J., Triller, E., Trilov, S., Truchon, J., Truncali, D., Trzaska, W. H., Tsai, Y., Tsai, Y. -T., Tsamalaidze, Z., Tsang, K. V., Tsverava, N., Tu, S. Z., Tufanli, S., Tunnell, C., Turner, J., Tuzi, M., Tyler, J., Tyley, E., Tzanov, M., Uchida, M. A., González, J. Ureña, Urheim, J., Usher, T., Utaegbulam, H., Uzunyan, S., Vagins, M. R., Vahle, P., Valdiviesso, G. A., Vale, V., Valencia, E., Valentim, R., Vallari, Z., Vallazza, E., Valle, J. W. F., Van Berg, R., Forero, D. V., Vannozzi, A., Van Nuland-Troost, M., Varanini, F., Auccalla, T. Vargas, Oliva, D. Vargas, Vaughan, N., Vaziri, K., Vázquez-Ramos, A., Vega, J., Vences, J., Ventura, S., Verdugo, A., Vergani, S., Verzocchi, M., Vetter, K., Vicenzi, M., de Souza, H. Vieira, Vignoli, C., Vilela, C., Villa, E., Viola, S., Viren, B., Vizarreta, R., Hernandez, A. P. Vizcaya, Vlachos, S., Vorobyev, G., Vuong, Q., Waldron, A. V., Wallach, M., Walsh, J., Walton, T., Wan, L., Wang, B., Wang, H., Wang, J., Wang, L., Wang, M. H. L. S., Wang, X., Wang, Y., Warburton, K., Warner, D., Warsame, L., Wascko, M. O., Waters, D., Watson, A., Wawrowska, K., Weber, A., Weber, C. M., Weber, M., Wei, H., Weinstein, A., Westerdale, S., Wetstein, M., Whalen, K., White, A., Whitehead, L. H., Whittington, D., Wieler, F., Wilhlemi, J., Wilking, M. J., Wilkinson, A., Wilkinson, C., Wilson, F., Wilson, R. J., Winter, P., Wolcott, J., Wolfs, J., Wongjirad, T., Wood, A., Wood, K., Worcester, E., Worcester, M., Wresilo, K., Wrobel, M., Wu, S., Wu, W., Wurm, M., Wyenberg, J., Wynne, B. M., Xiao, Y., Xiotidis, I., Yaeggy, B., Yahlali, N., Yandel, E., Yang, J., Yang, T., Yankelevich, A., Yates, L., Yonehara, K., Young, T., Yu, B., Yu, H., Yu, J., Yu, Y., Yuan, W., Zaki, R., Zalesak, J., Zambelli, L., Zamorano, B., Zani, A., Zapata, O., Zazueta, L., Zeller, G. P., Zennamo, J., Zettlemoyer, J., Zeug, K., Zhang, C., Zhang, S., Zhao, M., Zhivun, E., Zimmerman, E. D., Zucchelli, S., Zuklin, J., Zutshi, V., and Zwaska, R.

Subjects
High Energy Physics - Experiment
Abstract

The Pandora Software Development Kit and algorithm libraries perform reconstruction of neutrino interactions in liquid argon time projection chamber detectors. Pandora is the primary event reconstruction software used at the Deep Underground Neutrino Experiment, which will operate four large-scale liquid argon time projection chambers at the far detector site in South Dakota, producing high-resolution images of charged particles emerging from neutrino interactions. While these high-resolution images provide excellent opportunities for physics, the complex topologies require sophisticated pattern recognition capabilities to interpret signals from the detectors as physically meaningful objects that form the inputs to physics analyses. A critical component is the identification of the neutrino interaction vertex. Subsequent reconstruction algorithms use this location to identify the individual primary particles and ensure they each result in a separate reconstructed particle. A new vertex-finding procedure described in this article integrates a U-ResNet neural network performing hit-level classification into the multi-algorithm approach used by Pandora to identify the neutrino interaction vertex. The machine learning solution is seamlessly integrated into a chain of pattern-recognition algorithms. The technique substantially outperforms the previous BDT-based solution, with a more than 20\% increase in the efficiency of sub-1\,cm vertex reconstruction across all neutrino flavours., Comment: 32 pages, 18 figures

Published
2025

10. On the Orbit of the Binary Brown Dwarf Companion GL229 Ba and Bb

Author

Thompson, William, Blakely, Dori, Xuan, Jerry W., Bouchard-Côté, Alexandre, Bourdarot, Guillaume, Biron-Lattes, Miguel, Campbell, Trevor, Eisenhauer, Frank, Henning, Thomas, Janson, Markus, Johnstone, Doug, Kammerer, Jens, Konopacky, Quinn, Lacour, Sylvestre, Marois, Christian, Mawet, Dimitri, Mérand, Antoine, Nguyen, Jayke Samson, Nielsen, Eric, Rickman, Emily, Ruffio, Jean-Baptiste, Surjanovic, Nikola, Wang, Jason J., and Winterhalder, Thomas

Subjects
Astrophysics - Solar and Stellar Astrophysics, Astrophysics - Earth and Planetary Astrophysics
Abstract

The companion GL229B was recently resolved by Xuan et al. (2024) as a tight binary of two brown dwarfs (Ba and Bb) through VLTI-GRAVITY interferometry and VLT-CRIRES+ RV measurements. Here, we present Bayesian models of the interferometric and RV data in additional detail, along with an updated outer orbit of the brown dwarf pair about the primary. To create a model of the inner orbit with robust uncertainties, we apply kernel phases to the GRAVITY data to address baseline redundancy in the raw closure phases. Using parallel tempering, we constrain the binary's orbit using only VLTI-GRAVITY data, despite each epoch having low visibility-plane coverage and/or SNR. We demonstrate very agreement the VLTI-GRAVITY and CRIRES+ datasets and find that the inner binary has a period of 12.1346$\pm$0.0011 days, eccentricity of 0.2317$\pm$0.0025, and total mass of 71.0$\pm$0.4 Mjup, with Ba and Bb having masses of 37.7$\pm$1.1Mjup and 33.4$\pm$1.0Mjup respectively. With new Keck/NIRC2 astrometry, we update the outer orbit GL229B around the primary. We find a semi-major axis of 42.9+3.0-2.4AU, eccentricity of 0.736$\pm$0.014, and a total mass for B of 71.7$\pm$0.6Mjup, consistent with that derived from the inner orbit. We find a mutual inclination of 31$\pm$2.5deg, below the threshold for Kozai-Lidov oscillations. The agreement on the mass of Ba+Bb between the inner and outer orbits is an important test of our ability to model RV, astrometry, and Hipparcos-Gaia proper motion anomaly. Our methodological advances in handling interferometric data with low SNR and sparse UV-coverage will benefit future observations of rapidly-orbiting companions with VLTI-GRAVITY., Comment: Resubmitted to AJ

Published
2025

11. Fourier-Tailored Light-Matter Coupling in van der Waals Heterostructures

Author

Danielsen, Dorte R., Lassaline, Nolan, Linde, Sander J., Nielsen, Magnus V., Zambrana-Puyalto, Xavier, Sarbajna, Avishek, Nguyen, Duc Hieu, Booth, Timothy J., Stenger, Nicolas, and Raza, Søren

Subjects
Physics - Optics, Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

Dielectric structures can support low-absorption optical modes, which are attractive for engineering light-matter interactions with excitonic resonances in two-dimensional (2D) materials. However, the coupling strength is often limited by the electromagnetic field being confined inside the dielectric, reducing spatial overlap with the active excitonic material. Here, we demonstrate a scheme for enhanced light-matter coupling by embedding excitonic tungsten disulfide (WS$_2$) within dielectric hexagonal boron nitride (hBN), forming a van der Waals (vdW) heterostructure that optimizes the field overlap and alignment between excitons and optical waveguide modes. To tailor diffractive coupling between free-space light and the waveguide modes in the vdW heterostructure, we fabricate Fourier surfaces in the top hBN layer using thermal scanning-probe lithography and etching, producing sinusoidal topographic landscapes with nanometer precision. We observe the formation of exciton-polaritons with a Rabi splitting indicating that the system is at the onset of strong coupling. These results demonstrate the potential of Fourier-tailored vdW heterostructures for exploring advanced optoelectronic and quantum devices.

Published
2025

12. MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

Author

Nielsen, Aleksandra Weronika, Manoochehri, Hafez Eslami, Zhong, Hua, Panwar, Vandana, Jarmale, Vipul, Jasti, Jay, Nourani, Mehrdad, Rakheja, Dinesh, Brugarolas, James, Kapur, Payal, and Rajaram, Satwik

Subjects
Quantitative Biology - Quantitative Methods
Abstract

The ability of tumors to evolve and adapt by developing subclones in different genetic and epigenetic states is a major challenge in oncology. Traditional tools like multi-regional sequencing used to study tumor evolution and the resultant intra-tumor heterogeneity (ITH) are often impractical because of their resource-intensiveness and limited scalability. Here, we present MorphoITH, a novel framework that leverages histopathology slides to deconvolve molecular ITH through tissue morphology. MorphoITH integrates a self-supervised deep learning similarity measure to capture phenotypic variation across multiple dimensions (cytology, architecture, and microenvironment) with rigorous methods to eliminate spurious sources of variation. Using a prototype of ITH, clear cell renal cell carcinoma (ccRCC), we show that MorphoITH captures clinically-significant biological features, such as vascular architecture and nuclear grades. Furthermore, we find that MorphoITH recognizes differential biological states corresponding to subclonal changes in key driver genes (BAP1/PBRM1/SETD2). Finally, by applying MorphoITH to a multi-regional sequencing experiment, we postulate evolutionary trajectories that largely recapitulate genetic evolution. In summary, MorphoITH provides a scalable phenotypic lens that bridges the gap between histopathology and genomics, advancing precision oncology.

Published
2025

13. Generator Sets for the Minkowski Sum Problem -- Theory and Insights

Author

Lyngesen, Mark, Gadegaard, Sune Lauth, and Nielsen, Lars Relund

Subjects
Mathematics - Optimization and Control, 90C29
Abstract

This paper considers a class of multi-objective optimization problems known as Minkowski sum problems. Minkowski sum problems have a decomposable structure, where the global nondominated (Pareto) set corresponds to the Minkowski sum of several local nondominated sets. In some cases, the vectors of local sets does not contribute to the generation of the global nondominated set, and may therefore lead to wasted computational efforts. Therefore, we investigate theoretical properties of both necessary and redundant vectors, and propose an algorithm based on bounding sets for identifying unnecessary local vectors. We conduct extensive numerical experiments to test the the impact of varying characteristics of the instances on the resulting global nondominated set and the number of redundant vectors.

Published
2025

14. Detecting Zero-Day Attacks in Digital Substations via In-Context Learning

Author

Manzoor, Faizan, Khattar, Vanshaj, Herath, Akila, Black, Clifton, Nielsen, Matthew C, Hong, Junho, Liu, Chen-Ching, and Jin, Ming

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

The occurrences of cyber attacks on the power grids have been increasing every year, with novel attack techniques emerging every year. In this paper, we address the critical challenge of detecting novel/zero-day attacks in digital substations that employ the IEC-61850 communication protocol. While many heuristic and machine learning (ML)-based methods have been proposed for attack detection in IEC-61850 digital substations, generalization to novel or zero-day attacks remains challenging. We propose an approach that leverages the in-context learning (ICL) capability of the transformer architecture, the fundamental building block of large language models. The ICL approach enables the model to detect zero-day attacks and learn from a few examples of that attack without explicit retraining. Our experiments on the IEC-61850 dataset demonstrate that the proposed method achieves more than $85\%$ detection accuracy on zero-day attacks while the existing state-of-the-art baselines fail. This work paves the way for building more secure and resilient digital substations of the future.

Published
2025

15. Signature of the $\alpha$-clustering structure of Light Nuclei in Relativistic Nuclear Collisions

Author

Lu, Zhiyong, Zhao, Mingrui, Nielsen, Emil Gorm Dahlbæk, Li, Xiaomei, and Zhou, You

Subjects
Nuclear Theory, Nuclear Experiment
Abstract

The "imaging-by-smashing" technique has been developed recently in relativistic nuclear collisions. By smashing heavy nuclei at RHIC and the LHC and analyzing the anisotropic expansion (flow) of the final state produced particles, unique information on the structure of the collided nuclei has been obtained. Existing efforts primarily focus on the colliding mode of heavy nuclei collisions. In contrast, nuclear structure studies with collisions of light nuclei and the fixed target mode, despite their significant impact and broad interest, have not been thoroughly explored. In this Letter, we investigate the $\alpha$-clustering signature of $^{20}$Ne and $^{16}$O in the fixed-target $^{208}$Pb--$^{20}$Ne and $^{208}$Pb--$^{16}$O collisions at $\sqrt{s_{_\mathrm{NN}}}$ = 68.5 GeV, using the parton transport model AMPT. The results of two- and four-particle cumulants of anisotropic flow demonstrate a robust $\alpha$-clustering signature that persists regardless of the complex dynamic evolution of the created systems. This study highlights the significant impact of the LHCb SMOG (SMOG2) project in discovering the $\alpha$-clustering signature of light nuclei at relativistic energies., Comment: 7 pages, 3 figures

Published
2025

16. Revisiting CLIP: Efficient Alignment of 3D MRI and Tabular Data using Domain-Specific Foundation Models

Author

Petersen, Jakob Krogh, Licht, Valdemar, Nielsen, Mads, and Munk, Asbjørn

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

Multi-modal models require aligned, shared embedding spaces. However, common CLIP-based approaches need large amounts of samples and do not natively support 3D or tabular data, both of which are crucial in the medical domain. To address these issues, we revisit CLIP-style alignment by training a domain-specific 3D foundation model as an image encoder and demonstrate that modality alignment is feasible with only 62 MRI scans. Our approach is enabled by a simple embedding accumulation strategy required for training in 3D, which scales the amount of negative pairs across batches in order to stabilize training. We perform a thorough evaluation of various design choices, including the choice of backbone and loss functions, and evaluate the proposed methodology on zero-shot classification and image-retrieval tasks. While zero-shot image-retrieval remains challenging, zero-shot classification results demonstrate that the proposed approach can meaningfully align the representations of 3D MRI with tabular data., Comment: 10 pages, 2 figures. To be published in ISBI 2025

Published
2025

17. Liquid Metal-Exfoliated SnO$_2$-Based Mixed-dimensional Heterostructures for Visible-to-Near-Infrared Photodetection

Author

Nath, Shimul Kanti, Syed, Nitu, Pan, Wenwu, Yu, Yang, Liu, Dawei, Nielsen, Michael P., Yuwono, Jodie, Kumar, Priyank, Zhu, Yan, Cortie, David L., Nguyen, Chung K., Fu, Lan, Roberts, Ann, Faraone, Lorenzo, Ekins-Daukes, Nicholas J., and Lei, Wen

Subjects
Condensed Matter - Materials Science, Physics - Optics
Abstract

Ultra-thin two-dimensional (2D) materials have gained significant attention for making next-generation optoelectronic devices. Here, we report a large-area heterojunction photodetector fabricated using a liquid metal-printed 2D $\text{SnO}_2$ layer transferred onto CdTe thin films. The resulting device demonstrates efficient broadband light sensing from visible to near-infrared wavelengths, with enhanced detectivity and faster photo response than bare CdTe photodetectors. Significantly, the device shows a nearly $10^5$-fold increase in current than the dark current level when illuminated with a 780 nm laser and achieves a specific detectivity of around $10^{12} \, \text{Jones}$, nearly two orders of magnitude higher than a device with pure CdTe thin film. Additionally, temperature-dependent optoelectronic testing shows that the device maintains a stable response up to $140^\circ \text{C}$ and generates distinctive photocurrent at temperatures up to $80^\circ \text{C}$, demonstrating its thermal stability. Using band structure analysis, density functional theory (DFT) calculations, and photocurrent mapping, the formation of a $p$-$n$ junction is indicated, contributing to the enhanced photo response attributed to the efficient carrier separation by the built-in potential in the hetero-junction and the superior electron mobility of 2D $\text{SnO}_2$. Our results highlight the effectiveness of integrating liquid metal-exfoliated 2D materials for enhanced photodetector performance.

Published
2025

18. Generative Data Augmentation Challenge: Synthesis of Room Acoustics for Speaker Distance Estimation

Author

Lin, Jackie, Götz, Georg, Llopis, Hermes Sampedro, Hafsteinsson, Haukur, Guðjónsson, Steinar, Nielsen, Daniel Gert, Pind, Finnur, Smaragdis, Paris, Manocha, Dinesh, Hershey, John, Kristjansson, Trausti, and Kim, Minje

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

This paper describes the synthesis of the room acoustics challenge as a part of the generative data augmentation workshop at ICASSP 2025. The challenge defines a unique generative task that is designed to improve the quantity and diversity of the room impulse responses dataset so that it can be used for spatially sensitive downstream tasks: speaker distance estimation. The challenge identifies the technical difficulty in measuring or simulating many rooms' acoustic characteristics precisely. As a solution, it proposes generative data augmentation as an alternative that can potentially be used to improve various downstream tasks. The challenge website, dataset, and evaluation code are available at https://sites.google.com/view/genda2025., Comment: Accepted to the Workshop on Generative Data Augmentation at ICASSP 2025. Challenge website: https://sites.google.com/view/genda2025

Published
2025

19. Intervening nuclear obscuration changing the X-ray look of the $z\approx6$ QSO CFHQS J164121+375520

Author

Vito, Fabio, Brandt, William Nielsen, Comastri, Andrea, Gilli, Roberto, Bauer, Franz, Belladitta, Silvia, Chartas, George, Iwasawa, Kazushi, Lanzuisi, Giorgio, Luo, Bin, Marchesi, Stefano, Mignoli, Marco, Ricci, Federica, Shemmer, Ohad, Spingola, Cristiana, Vignali, Cristian, Boschin, Walter, Cusano, Felice, and Paris, Diego

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - High Energy Astrophysical Phenomena
Abstract

X-ray observations of the optically selected $z=6.025$ QSO CFHQS J164121+375520 (hereafter J1641) revealed that its flux dropped by a factor $\gtrsim7$ from 2018, when it was a bright and soft X-ray source, to 2021. Such a strong variability amplitude has not been observed before among $z>6$ QSOs, and the underlying physical mechanism was unclear. We carried out a new X-ray and rest-frame UV monitoring campaign of J1641 over 2022-2024. We detected J1641 with Chandra in the 2-7 keV band, while no significant emission is detected at softer X-ray energies, making J1641 an X-ray changing look QSO at $z>6$. Comparing with the 2018 epoch, the 0.5-2 keV flux dropped dramatically by a factor $>20$. We ascribe this behaviour to intervening, and still ongoing, obscuration by Compton-thick gas intercepting our line of sight between 2018 and 2021. The screening material could be an inner disk or a failed nuclear wind that increased their thickness. Another possibility is that we have witnessed an occultation event due to dust-free clouds located at sub-pc/pc scales, similar to those recently invoked to explain the remarkable X-ray weakness of AGN discovered by JWST. These interpretations are also consistent with the lack of strong variations of the QSO rest-frame UV lightcurve over the same period. Future monitoring of J1641 and the possible discovery of other X-ray changing look QSOs at $z>6$ will provide us with precious information about the physics of rapid supermassive black-hole growth at high redshift., Comment: Accepted for publication on A&A Letters

Published
2025

20. Continuous variable measurement-device-independent quantum certification

Author

Larsen, B. L., Hajomer, A. A. E., Abiuso, P., Izumi, S., Gehring, T., Neergaard-Nielsen, J. S., Acin, A., and Andersen, U. L.

Subjects
Quantum Physics
Abstract

Secure and reliable certification of quantum resources is a fundamental challenge in the advancement of next-generation quantum technologies, particularly as devices become more complex and integrated into practical applications, where parts of the system may be untrusted or inaccessible by users. Addressing this challenge requires certification methods that rely on minimal assumptions and limited trust while still faithfully and reliably verifying the quantum resources in question. For infinite-dimensional bosonic systems, existing certification methods rely on fully trusted and well calibrated measurement systems, leaving significant security vulnerabilities open. In this work, we present the first experimental demonstration of measurement-device-independent (MDI) certification schemes for infinite-dimensional bosonic systems, where the certification process is conducted using entirely untrusted measurement devices and assuming only the trusted preparation of coherent states. Specifically, we implement schemes for the MDI certification of continuous-variable (CV) entanglement and the operation of an elementary optical CV quantum memory. We leverage techniques of Bayesian metrology and exploit the practicality and accessibility of Gaussian quantum optics to achieve secure and efficient certification. These results demonstrate the potential of the MDI framework to enhance trust in quantum technologies with applications in quantum communication and quantum computing., Comment: 22 pages, 12 figures

Published
2025

21. Farside helioseismology with Sun-as-a-star data: the solar cycle as seen with 7-day-long BiSON timeseries

Author

Howe, R., Chaplin, W. J., Elsworth, Y. P., Hale, S. J., Hatt, E., and Nielsen, M. B.

Subjects
Astrophysics - Solar and Stellar Astrophysics
Abstract

We present results from fitting $p$-mode spectra derived from 7-d segments of Sun-as-a-star helioseismic observations from the Birmingham Solar Oscillations Network covering 32 yr. The results show a clear dependence of the mode frequencies on solar activity, and the frequency dependence of the sensitivity to activity can also be seen. Because we use data segments that cover less than half of a solar rotation, we are able to test for the effect of activity on the solar far side. By fitting with a model that takes into account activity on the far side of the Sun, we show that the frequency shifts are sensitive to activity from the whole Sun, not just the side facing the observer. Our results suggest that there is potential to investigate activity-related asteroseismic frequency shifts in solar-like oscillators using short time series of observations., Comment: 6 pages, 7 figures. Accepted by MNRAS 14-Jan-25

Published
2025

22. Feedback Arc Sets and Feedback Arc Set Decompositions in Weighted and Unweighted Oriented Graphs

Author

Gutin, Gregory, Nielsen, Mads Anker, Yeo, Anders, and Zhou, Yacong

Subjects
Mathematics - Combinatorics, Computer Science - Discrete Mathematics
Abstract

For any arc-weighted oriented graph $D=(V(D), A(D),w)$, we write ${\rm fas}_w(D)$ to denote the minimum weight of a feedback arc set in $D$. In this paper, we consider upper bounds on ${\rm fas}_w(D)$ for arc-weight oriented graphs $D$ with bounded maximum degrees and directed girth. We obtain such bounds by introducing a new parameter ${\rm fasd}(D)$, which is the maximum integer such that $A(D)$ can be partitioned into ${\rm fasd}(D)$ feedback arc sets. This new parameter seems to be interesting in its own right. We obtain several bounds for both ${\rm fas}_w(D)$ and ${\rm fasd}(D)$ when $D$ has maximum degree $\Delta(D)\le \Delta$ and directed girth $g(D)\geq g$. In particular, we show that if $\Delta(D)\leq~4$ and $g(D)\geq 3$, then ${\rm fasd}(D) \geq 3$ and therefore ${\rm fas}_w(D)\leq \frac{w(D)}{3}$ which generalizes a tight bound for an unweighted oriented graph with maximum degree at most 4. We also show that ${\rm fasd}(D)\geq g$ and ${\rm fas}_w(D) \leq \frac{w(D)}{g}$ if $\Delta(D)\leq 3$ and $g(D)\geq g$ for $g\in \{3,4,5\}$ and these bounds are tight. However, for $g=10$ the bound ${\rm fasd}(D)\geq g$ does not always hold when $\Delta(D)\leq 3$. Finally we give some bounds for the cases when $\Delta$ or $g$ are large.

Published
2025

23. Euclidean domains with no multiplicative norms

Author

Dastrup, Caleb J. and Nielsen, Pace P.

Subjects
Mathematics - Commutative Algebra, Mathematics - Rings and Algebras
Abstract

We construct a Euclidean domain with no multiplicative Euclidean norm to a compatibly well-ordered monoid, and hence with no multiplicative Euclidean norm to $\mathbb{R}$ (under its usual order). A key step in the proof is showing that the UFD property is preserved when adjoining a free factorization.

Published
2025

24. TOI-5108 b and TOI 5786 b: Two transiting sub-Saturns detected and characterized with TESS, MaHPS and SOPHIE

Author

Thomas, Luis, Hébrard, Guillaume, Kellermann, Hanna, Korth, Judith, Heidari, Neda, Forveille, Thierry, Sousa, Sérgio G., Schöller, Laura, Riffeser, Arno, Gössl, Claus, Bell, Juan Serrano, Kiefer, Flavien, Hara, Nathan, Grupp, Frank, Ehrhardt, Juliana, Murgas, Felipe, Collins, Karen A., Bieryla, Allyson, Parviainen, Hannu, Belinski, Alexandr A., Esparza-Borges, Emma, Ciardi, David R., Clark, Catherine A., Fukui, Akihiko, Gilbert, Emily A., Hopp, Ulrich, Ikuta, Kai, Jenkins, Jon M., Latham, David W., Narita, Norio, Nielsen, Louise D., Quinn, Samuel N., Palle, Enric, Pippert, Jan-Niklas, Polanski, Alex S., Ries, Christoph, Schmidt, Michael, Schwarz, Richard P., Seager, Sara, Strakhov, Ivan A., Striegel, Stephanie, van Eyken, Julian C., Watanabe, Noriharu, Watkins, Cristilyn N., Winn, Joshua N., Ziegler, Carl, and Zöller, Raphael

Subjects
Astrophysics - Earth and Planetary Astrophysics
Abstract

We report the discovery and characterization of two sub-Saturns from the Transiting Exoplanet Survey Satellite (\textit{TESS}) using high-resolution spectroscopic observations from the MaHPS spectrograph at the Wendelstein Observatory and the SOPHIE spectrograph at the Haute-Provence Observatory. Combining photometry from TESS, KeplerCam, LCOGT, and MuSCAT2 with the radial velocity measurements from MaHPS and SOPHIE we measure precise radii and masses for both planets. TOI-5108 b is a sub-Saturn with a radius of $6.6 \pm 0.1$ $R_\oplus$ and a mass of $32 \pm 5$ $M_\oplus$. TOI-5786 b is similar to Saturn with a radius of $8.54 \pm 0.13$ $R_\oplus$ and a mass of $73 \pm 9$ $M_\oplus$. The host star for TOI-5108 b is a moderately bright (Vmag 9.75) G-type star. TOI-5786 is a slightly dimmer (Vmag 10.2) F-type star. Both planets are close to their host stars with periods of 6.75 days and 12.78 days respectively. This puts TOI-5108 b just inside the bounds of the Neptune desert while TOI-5786 b is right above the upper edge. We estimate hydrogen-helium envelope mass fractions of $38 \%$ for TOI-5108 b and $74 \% $ for TOI-5786 b. However, using a model for the interior structure that includes tidal effects the envelope fraction of TOI-5108 b could be much lower ($\sim 20\,\%$) depending on the obliquity. We estimate mass-loss rates between 1.0 * $10^9$ g/s and 9.8 * $10^9$ g/s for TOI-5108 b and between 3.6 * $10^8$ g/s and 3.5 * $10^9$ g/s for TOI-5786 b. Given their masses, this means that both planets are stable against photoevaporation. We also detect a transit signal for a second planet candidate in the TESS data of TOI-5786 with a period of 6.998 days and a radius of $3.83 \pm 0.16$ $R_\oplus$. Using our RV data and photodynamical modeling, we are able to provide a 3-$\sigma$ upper limit of 26.5 $M_\oplus$ for the mass of the potential inner companion to TOI-5786 b., Comment: 25 pages, 13 figures. Accepted for publication in A&A

Published
2025
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25. Search for continuous gravitational waves from known pulsars in the first part of the fourth LIGO-Virgo-KAGRA observing run

Author

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, Abac, A. G., Abbott, R., Abouelfettouh, I., Acernese, F., Ackley, K., Adhicary, S., Adhikari, N., Adhikari, R. X., Adkins, V. K., Agarwal, D., Agathos, M., Abchouyeh, M. Aghaei, Aguiar, O. D., Aguilar, I., Aiello, L., Ain, A., Ajith, P., Akutsu, T., Albanesi, S., Alfaidi, R. A., Al-Jodah, A., Alléné, C., Allocca, A., Al-Shammari, S., Altin, P. A., Alvarez-Lopez, S., Amato, A., Amez-Droz, L., Amorosi, A., Amra, C., Ananyeva, A., Anderson, S. B., Anderson, W. G., Andia, M., Ando, M., Andrade, T., Andres, N., Andrés-Carcasona, M., Andrić, T., Anglin, J., Ansoldi, S., Antelis, J. M., Antier, S., Aoumi, M., Appavuravther, E. Z., Appert, S., Apple, S. K., Arai, K., Araya, A., Araya, M. C., Areeda, J. S., Argianas, L., Aritomi, N., Armato, F., Arnaud, N., Arogeti, M., Aronson, S. M., Ashton, G., Aso, Y., Assiduo, M., Melo, S. Assis de Souza, Aston, S. M., Astone, P., Attadio, F., Aubin, F., AultONeal, K., Avallone, G., Babak, S., Badaracco, F., Badger, C., Bae, S., Bagnasco, S., Bagui, E., Baier, J. G., Baiotti, L., Bajpai, R., Baka, T., Ball, M., Ballardin, G., Ballmer, S. W., Banagiri, S., Banerjee, B., Bankar, D., Baral, P., Barayoga, J. C., Barish, B. C., Barker, D., Barneo, P., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barta, D., Bartoletti, A. M., Barton, M. A., Bartos, I., Basak, S., Basalaev, A., Bassiri, R., Basti, A., Bates, D. E., Bawaj, M., Baxi, P., Bayley, J. C., Baylor, A. C., Baynard II, P. A., Bazzan, M., Bedakihale, V. M., Beirnaert, F., Bejger, M., Belardinelli, D., Bell, A. S., Benedetto, V., Benoit, W., Bentley, J. D., Yaala, M. Ben, Bera, S., Berbel, M., Bergamin, F., Berger, B. K., Bernuzzi, S., Beroiz, M., Bersanetti, D., Bertolini, A., Betzwieser, J., Beveridge, D., Bevins, N., Bhandare, R., Bhardwaj, U., Bhatt, R., Bhattacharjee, D., Bhaumik, S., Bhowmick, S., Bianchi, A., Bilenko, I. A., Billingsley, G., Binetti, A., Bini, S., Birnholtz, O., Biscoveanu, S., Bisht, A., Bitossi, M., Bizouard, M. -A., Blackburn, J. K., Blagg, L. A., Blair, C. D., Blair, D. G., Bobba, F., Bode, N., Boileau, G., Boldrini, M., Bolingbroke, G. N., Bolliand, A., Bonavena, L. D., Bondarescu, R., Bondu, F., Bonilla, E., Bonilla, M. S., Bonino, A., Bonnand, R., Booker, P., Borchers, A., Boschi, V., Bose, S., Bossilkov, V., Boudart, V., Boudon, A., Bozzi, A., Bradaschia, C., Brady, P. R., Braglia, M., Branch, A., Branchesi, M., Brandt, J., Braun, I., Breschi, M., Briant, T., Brillet, A., Brinkmann, M., Brockill, P., Brockmueller, E., Brooks, A. F., Brown, B. C., Brown, D. D., Brozzetti, M. L., Brunett, S., Bruno, G., Bruntz, R., Bryant, J., Bucci, F., Buchanan, J., Bulashenko, O., Bulik, T., Bulten, H. J., Buonanno, A., Burtnyk, K., Buscicchio, R., Buskulic, D., Buy, C., Byer, R. L., Davies, G. S. Cabourn, Cabras, G., Cabrita, R., Cáceres-Barbosa, V., Cadonati, L., Cagnoli, G., Cahillane, C., Bustillo, J. Calderón, Callister, T. A., Calloni, E., Camp, J. B., Canepa, M., Santoro, G. Caneva, Cannon, K. C., Cao, H., Capistran, L. A., Capocasa, E., Capote, E., Carapella, G., Carbognani, F., Carlassara, M., Carlin, J. B., Carpinelli, M., Carrillo, G., Carter, J. J., Carullo, G., Diaz, J. Casanueva, Casentini, C., Castro-Lucas, S. Y., Caudill, S., Cavaglià, M., Cavalieri, R., Cella, G., Cerdá-Durán, P., Cesarini, E., Chaibi, W., Chakraborty, P., Subrahmanya, S. Chalathadka, Chan, J. C. L., Chan, M., Chandra, K., Chang, R. -J., Chao, S., Charlton, E. L., Charlton, P., Chassande-Mottin, E., Chatterjee, C., Chatterjee, Debarati, Chatterjee, Deep, Chaturvedi, M., Chaty, S., Chen, A., Chen, A. H. -Y., Chen, D., Chen, H., Chen, H. Y., Chen, J., Chen, K. H., Chen, Y., Chen, Yanbei, Chen, Yitian, Cheng, H. P., Chessa, P., Cheung, H. T., Cheung, S. Y., Chiadini, F., Chiarini, G., Chierici, R., Chincarini, A., Chiofalo, M. L., Chiummo, A., Chou, C., Choudhary, S., Christensen, N., Chua, S. S. Y., Chugh, P., Ciani, G., Ciecielag, P., Cieślar, M., Cifaldi, M., Ciolfi, R., Clara, F., Clark, J. A., Clarke, J., Clarke, T. A., Clearwater, P., Clesse, S., Coccia, E., Codazzo, E., Cohadon, P. -F., Colace, S., Colleoni, M., Collette, C. G., Collins, J., Colloms, S., Colombo, A., Colpi, M., Compton, C. M., Connolly, G., Conti, L., Corbitt, T. R., Cordero-Carrión, I., Corezzi, S., Cornish, N. J., Corsi, A., Cortese, S., Costa, C. A., Cottingham, R., Coughlin, M. W., Couineaux, A., Coulon, J. -P., Countryman, S. T., Coupechoux, J. -F., Couvares, P., Coward, D. M., Cowart, M. J., Coyne, R., Craig, K., Creed, R., Creighton, J. D. E., Creighton, T. D., Cremonese, P., Criswell, A. W., Crockett-Gray, J. C. G., Crook, S., Crouch, R., Csizmazia, J., Cudell, J. R., Cullen, T. J., Cumming, A., Cuoco, E., Cusinato, M., Dabadie, P., Canton, T. Dal, Dall'Osso, S., Pra, S. Dal, Dálya, G., D'Angelo, B., Danilishin, S., D'Antonio, S., Danzmann, K., Darroch, K. E., Dartez, L. P., Dasgupta, A., Datta, S., Dattilo, V., Daumas, A., Davari, N., Dave, I., Davenport, A., Davier, M., Davies, T. F., Davis, D., Davis, L., Davis, M. C., Davis, P. J., Dax, M., De Bolle, J., Deenadayalan, M., Degallaix, J., De Laurentis, M., Deléglise, S., De Lillo, F., Dell'Aquila, D., Del Pozzo, W., De Marco, F., De Matteis, F., D'Emilio, V., Demos, N., Dent, T., Depasse, A., DePergola, N., De Pietri, R., De Rosa, R., De Rossi, C., DeSalvo, R., De Simone, R., Dhani, A., Diab, R., Díaz, M. C., Di Cesare, M., Dideron, G., Didio, N. A., Dietrich, T., Di Fiore, L., Di Fronzo, C., Di Giovanni, M., Di Girolamo, T., Diksha, D., Di Michele, A., Ding, J., Di Pace, S., Di Palma, I., Di Renzo, F., Divyajyoti, Dmitriev, A., Doctor, Z., Dohmen, E., Doleva, P. P., Dominguez, D., D'Onofrio, L., Donovan, F., Dooley, K. L., Dooney, T., Doravari, S., Dorosh, O., Drago, M., Driggers, J. C., Ducoin, J. -G., Dunn, L., Dupletsa, U., D'Urso, D., Duval, H., Duverne, P. -A., Dwyer, S. E., Eassa, C., Ebersold, M., Eckhardt, T., Eddolls, G., Edelman, B., Edo, T. B., Edy, O., Effler, A., Eichholz, J., Einsle, H., Eisenmann, M., Eisenstein, R. A., Ejlli, A., Eleveld, R. M., Emma, M., Endo, K., Engl, A. J., Enloe, E., Errico, L., Essick, R. C., Estellés, H., Estevez, D., Etzel, T., Evans, M., Evstafyeva, T., Ewing, B. E., Ezquiaga, J. M., Fabrizi, F., Faedi, F., Fafone, V., Fairhurst, S., Farah, A. M., Farr, B., Farr, W. M., Favaro, G., Favata, M., Fays, M., Fazio, M., Feicht, J., Fejer, M. M., Felicetti, R., Fenyvesi, E., Ferguson, D. L., Ferraiuolo, S., Ferrante, I., Ferreira, T. A., Fidecaro, F., Figura, P., Fiori, A., Fiori, I., Fishbach, M., Fisher, R. P., Fittipaldi, R., Fiumara, V., Flaminio, R., Fleischer, S. M., Fleming, L. S., Floden, E., Foley, E. M., Fong, H., Font, J. A., Fornal, B., Forsyth, P. W. F., Franceschetti, K., Franchini, N., Frasca, S., Frasconi, F., Mascioli, A. Frattale, Frei, Z., Freise, A., Freitas, O., Frey, R., Frischhertz, W., Fritschel, P., Frolov, V. V., Fronzé, G. G., Fuentes-Garcia, M., Fujii, S., Fujimori, T., Fulda, P., Fyffe, M., Gadre, B., Gair, J. R., Galaudage, S., Galdi, V., Gallagher, H., Gallardo, S., Gallego, B., Gamba, R., Gamboa, A., Ganapathy, D., Ganguly, A., Garaventa, B., García-Bellido, J., Núñez, C. García, García-Quirós, C., Gardner, J. W., Gardner, K. A., Gargiulo, J., Garron, A., Garufi, F., Gasbarra, C., Gateley, B., Gayathri, V., Gemme, G., Gennai, A., Gennari, V., George, J., George, R., Gerberding, O., Gergely, L., Ghosh, Archisman, Ghosh, Sayantan, Ghosh, Shaon, Ghosh, Shrobana, Ghosh, Suprovo, Ghosh, Tathagata, Giacoppo, L., Giaime, J. A., Giardina, K. D., Gibson, D. R., Gibson, D. T., Gier, C., Giri, P., Gissi, F., Gkaitatzis, S., Glanzer, J., Glotin, F., Godfrey, J., Godwin, P., Goebbels, N. L., Goetz, E., Golomb, J., Lopez, S. Gomez, Goncharov, B., Gong, Y., González, G., Goodarzi, P., Goode, S., Goodwin-Jones, A. W., Gosselin, M., Göttel, A. S., Gouaty, R., Gould, D. W., Govorkova, K., Goyal, S., Grace, B., Grado, A., Graham, V., Granados, A. E., Granata, M., Granata, V., Gras, S., Grassia, P., Gray, A., Gray, C., Gray, R., Greco, G., Green, A. C., Green, S. M., Green, S. R., Gretarsson, A. M., Gretarsson, E. M., Griffith, D., Griffiths, W. L., Griggs, H. L., Grignani, G., Grimaldi, A., Grimaud, C., Grote, H., Guerra, D., Guetta, D., Guidi, G. M., Guimaraes, A. R., Gulati, H. K., Gulminelli, F., Gunny, A. M., Guo, H., Guo, W., Guo, Y., Gupta, Anchal, Gupta, Anuradha, Gupta, Ish, Gupta, N. C., Gupta, P., Gupta, S. K., Gupta, T., Gupte, N., Gurs, J., Gutierrez, N., Guzman, F., H, H. -Y., Haba, D., Haberland, M., Haino, S., Hall, E. D., Hamilton, E. Z., Hammond, G., Han, W. -B., Haney, M., Hanks, J., Hanna, C., Hannam, M. D., Hannuksela, O. A., Hanselman, A. G., Hansen, H., Hanson, J., Harada, R., Hardison, A. R., Haris, K., Harmark, T., Harms, J., Harry, G. M., Harry, I. W., Hart, J., Haskell, B., Haster, C. -J., Hathaway, J. S., Haughian, K., Hayakawa, H., Hayama, K., Hayes, R., Heffernan, A., Heidmann, A., Heintze, M. C., Heinze, J., Heinzel, J., Heitmann, H., Hellman, F., Hello, P., Helmling-Cornell, A. F., Hemming, G., Henderson-Sapir, O., Hendry, M., Heng, I. S., Hennes, E., Henshaw, C., Hertog, T., Heurs, M., Hewitt, A. L., Heyns, J., Higginbotham, S., Hild, S., Hill, S., Himemoto, Y., Hirata, N., Hirose, C., Ho, W. C. G., Hoang, S., Hochheim, S., Hofman, D., Holland, N. A., Holley-Bockelmann, K., Holmes, Z. J., Holz, D. E., Honet, L., Hong, C., Hornung, J., Hoshino, S., Hough, J., Hourihane, S., Howell, E. J., Hoy, C. G., Hrishikesh, C. A., Hsieh, H. -F., Hsiung, C., Hsu, H. C., Hsu, W. -F., Hu, P., Hu, Q., Huang, H. Y., Huang, Y. -J., Huddart, A. D., Hughey, B., Hui, D. C. Y., Hui, V., Husa, S., Huxford, R., Huynh-Dinh, T., Iampieri, L., Iandolo, G. A., Ianni, M., Iess, A., Imafuku, H., Inayoshi, K., Inoue, Y., Iorio, G., Iqbal, M. H., Irwin, J., Ishikawa, R., Isi, M., Ismail, M. A., Itoh, Y., Iwanaga, H., Iwaya, M., Iyer, B. R., JaberianHamedan, V., Jacquet, C., Jacquet, P. -E., Jadhav, S. J., Jadhav, S. P., Jain, T., James, A. L., James, P. A., Jamshidi, R., Janquart, J., Janssens, K., Janthalur, N. N., Jaraba, S., Jaranowski, P., Jaume, R., Javed, W., Jennings, A., Jia, W., Jiang, J., Jin, H., Kubisz, J., Johanson, C., Johns, G. R., Johnson, N. A., Johnston, M. C., Johnston, R., Johny, N., Jones, D. H., Jones, D. I., Jones, R., Jose, S., Joshi, P., Ju, L., Jung, K., Junker, J., Juste, V., Kajita, T., Kaku, I., Kalaghatgi, C., Kalogera, V., Kamiizumi, M., Kanda, N., Kandhasamy, S., Kang, G., Kanner, J. B., Kapadia, S. J., Kapasi, D. P., Karat, S., Karathanasis, C., Kashyap, R., Kasprzack, M., Kastaun, W., Kato, T., Katsavounidis, E., Katzman, W., Kaushik, R., Kawabe, K., Kawamoto, R., Kazemi, A., Keitel, D., Kelley-Derzon, J., Kennington, J., Kesharwani, R., Key, J. S., Khadela, R., Khadka, S., Khalili, F. Y., Khan, F., Khan, I., Khanam, T., Khursheed, M., Khusid, N. M., Kiendrebeogo, W., Kijbunchoo, N., Kim, C., Kim, J. C., Kim, K., Kim, M. H., Kim, S., Kim, Y. -M., Kimball, C., Kinley-Hanlon, M., Kinnear, M., Kissel, J. S., Klimenko, S., Knee, A. M., Knust, N., Kobayashi, K., Koch, P., Koehlenbeck, S. M., Koekoek, G., Kohri, K., Kokeyama, K., Koley, S., Kolitsidou, P., Kolstein, M., Komori, K., Kong, A. K. H., Kontos, A., Korobko, M., Kossak, R. V., Kou, X., Koushik, A., Kouvatsos, N., Kovalam, M., Kozak, D. B., Kranzhoff, S. L., Kringel, V., Krishnendu, N. V., Królak, A., Kruska, K., Kuehn, G., Kuijer, P., Kulkarni, S., Ramamohan, A. Kulur, Kumar, A., Kumar, Praveen, Kumar, Prayush, Kumar, Rahul, Kumar, Rakesh, Kume, J., Kuns, K., Kuntimaddi, N., Kuroyanagi, S., Kurth, N. J., Kuwahara, S., Kwak, K., Kwan, K., Kwok, J., Lacaille, G., Lagabbe, P., Laghi, D., Lai, S., Laity, A. H., Lakkis, M. H., Lalande, E., Lalleman, M., Lalremruati, P. C., Landry, M., Lane, B. B., Lang, R. N., Lange, J., Lantz, B., La Rana, A., La Rosa, I., Lartaux-Vollard, A., Lasky, P. D., Lawrence, J., Lawrence, M. N., Laxen, M., Lazzarini, A., Lazzaro, C., Leaci, P., Lecoeuche, Y. K., Lee, H. M., Lee, H. W., Lee, K., Lee, R. -K., Lee, R., Lee, S., Lee, Y., Legred, I. N., Lehmann, J., Lehner, L., Jean, M. Le, Lemaître, A., Lenti, M., Leonardi, M., Lequime, M., Leroy, N., Lesovsky, M., Letendre, N., Lethuillier, M., Levin, S. E., Levin, Y., Leyde, K., Li, A. K. Y., Li, K. L., Li, T. G. F., Li, X., Li, Z., Lihos, A., Lin, C-Y., Lin, C. -Y., Lin, E. T., Lin, F., Lin, H., Lin, L. C. -C., Lin, Y. -C., Linde, F., Linker, S. D., Littenberg, T. B., Liu, A., Liu, G. C., Liu, Jian, Villarreal, F. Llamas, Llobera-Querol, J., Lo, R. K. L., Locquet, J. -P., London, L. T., Longo, A., Lopez, D., Portilla, M. Lopez, Lorenzini, M., Lorenzo-Medina, A., Loriette, V., Lormand, M., Losurdo, G., Lott IV, T. P., Lough, J. D., Loughlin, H. A., Lousto, C. O., Lowry, M. J., Lu, N., Lück, H., Lumaca, D., Lundgren, A. P., Lussier, A. W., Ma, L. -T., Ma, S., Ma'arif, M., Macas, R., Macedo, A., MacInnis, M., Maciy, R. R., Macleod, D. M., MacMillan, I. A. O., Macquet, A., Macri, D., Maeda, K., Maenaut, S., Hernandez, I. Magaña, Magare, S. S., Magazzù, C., Magee, R. M., Maggio, E., Maggiore, R., Magnozzi, M., Mahesh, M., Mahesh, S., Maini, M., Majhi, S., Majorana, E., Makarem, C. N., Makelele, E., Malaquias-Reis, J. A., Mali, U., Maliakal, S., Malik, A., Man, N., Mandic, V., Mangano, V., Mannix, B., Mansell, G. L., Mansingh, G., Manske, M., Mantovani, M., Mapelli, M., Marchesoni, F., Pina, D. Marín, Marion, F., Márka, S., Márka, Z., Markosyan, A. S., Markowitz, A., Maros, E., Marsat, S., Martelli, F., Martin, I. W., Martin, R. M., Martinez, B. B., Martinez, M., Martinez, V., Martini, A., Martinovic, K., Martins, J. C., Martynov, D. V., Marx, E. J., Massaro, L., Masserot, A., Masso-Reid, M., Mastrodicasa, M., Mastrogiovanni, S., Matcovich, T., Matiushechkina, M., Matsuyama, M., Mavalvala, N., Maxwell, N., McCarrol, G., McCarthy, R., McClelland, D. E., McCormick, S., McCuller, L., McEachin, S., McElhenny, C., McGhee, G. I., McGinn, J., McGowan, K. B. M., McIver, J., McLeod, A., McRae, T., Meacher, D., Meijer, Q., Melatos, A., Mellaerts, S., Menendez-Vazquez, A., Menoni, C. S., Mera, F., Mercer, R. A., Mereni, L., Merfeld, K., Merilh, E. L., Mérou, J. R., Merritt, J. D., Merzougui, M., Messenger, C., Messick, C., Metzler, Z., Meyer-Conde, M., Meylahn, F., Mhaske, A., Miani, A., Miao, H., Michaloliakos, I., Michel, C., Michimura, Y., Middleton, H., Miller, A. L., Miller, S., Millhouse, M., Milotti, E., Milotti, V., Minenkov, Y., Mio, N., Mir, Ll. M., Mirasola, L., Miravet-Tenés, M., Miritescu, C. -A., Mishra, A. K., Mishra, A., Mishra, C., Mishra, T., Mitchell, A. L., Mitchell, J. G., Mitra, S., Mitrofanov, V. P., Mittleman, R., Miyakawa, O., Miyamoto, S., Miyoki, S., Mo, G., Mobilia, L., Mohapatra, S. R. P., Mohite, S. R., Molina-Ruiz, M., Mondal, C., Mondin, M., Montani, M., Moore, C. J., Moraru, D., More, A., More, S., Moreno, G., Morgan, C., Morisaki, S., Moriwaki, Y., Morras, G., Moscatello, A., Mourier, P., Mours, B., Mow-Lowry, C. M., Muciaccia, F., Mukherjee, Arunava, Mukherjee, D., Mukherjee, Samanwaya, Mukherjee, Soma, Mukherjee, Subroto, Mukherjee, Suvodip, Mukund, N., Mullavey, A., Munch, J., Mundi, J., Mungioli, C. L., Oberg, W. R. Munn, Murakami, Y., Murakoshi, M., Murray, P. G., Muusse, S., Nabari, D., Nadji, S. L., Nagar, A., Nagarajan, N., Nagler, K. N., Nakagaki, K., Nakamura, K., Nakano, H., Nakano, M., Nandi, D., Napolano, V., Narayan, P., Nardecchia, I., Narikawa, T., Narola, H., Naticchioni, L., Nayak, R. K., Neilson, J., Nelson, A., Nelson, T. J. N., Nery, M., Neunzert, A., Ng, S., Quynh, L. Nguyen, Nichols, S. A., Nielsen, A. B., Nieradka, G., Niko, A., Nishino, Y., Nishizawa, A., Nissanke, S., Nitoglia, E., Niu, W., Nocera, F., Norman, M., North, C., Novak, J., Siles, J. F. Nuño, Nuttall, L. K., Obayashi, K., Oberling, J., O'Dell, J., Oertel, M., Offermans, A., Oganesyan, G., Oh, J. J., Oh, K., O'Hanlon, T., Ohashi, M., Ohkawa, M., Ohme, F., Oliveira, A. S., Oliveri, R., O'Neal, B., Oohara, K., O'Reilly, B., Ormsby, N. D., Orselli, M., O'Shaughnessy, R., O'Shea, S., Oshima, Y., Oshino, S., Ossokine, S., Osthelder, C., Ota, I., Ottaway, D. J., Ouzriat, A., Overmier, H., Owen, B. J., Pace, A. E., Pagano, R., Page, M. A., Pai, A., Pal, A., Pal, S., Palaia, M. A., Pálfi, M., Palma, P. P., Palomba, C., Palud, P., Pan, H., Pan, J., Pan, K. C., Panai, R., Panda, P. K., Pandey, S., Panebianco, L., Pang, P. T. H., Pannarale, F., Pannone, K. A., Pant, B. C., Panther, F. H., Paoletti, F., Paolone, A., Papalexakis, E. E., Papalini, L., Papigkiotis, G., Paquis, A., Parisi, A., Park, B. -J., Park, J., Parker, W., Pascale, G., Pascucci, D., Pasqualetti, A., Passaquieti, R., Passenger, L., Passuello, D., Patane, O., Pathak, D., Pathak, M., Patra, A., Patricelli, B., Patron, A. S., Paul, K., Paul, S., Payne, E., Pearce, T., Pedraza, M., Pegna, R., Pele, A., Arellano, F. E. Peña, Penn, S., Penuliar, M. D., Perego, A., Pereira, Z., Perez, J. J., Périgois, C., Perna, G., Perreca, A., Perret, J., Perriès, S., Perry, J. W., Pesios, D., Petracca, S., Petrillo, C., Pfeiffer, H. P., Pham, H., Pham, K. A., Phukon, K. S., Phurailatpam, H., Piarulli, M., Piccari, L., Piccinni, O. J., Pichot, M., Piendibene, M., Piergiovanni, F., Pierini, L., Pierra, G., Pierro, V., Pietrzak, M., Pillas, M., Pilo, F., Pinard, L., Pinto, I. M., Pinto, M., Piotrzkowski, B. J., Pirello, M., Pitkin, M. D., Placidi, A., Placidi, E., Planas, M. L., Plastino, W., Poggiani, R., Polini, E., Pompili, L., Poon, J., Porcelli, E., Porter, E. K., Posnansky, C., Poulton, R., Powell, J., Pracchia, M., Pradhan, B. K., Pradier, T., Prajapati, A. K., Prasai, K., Prasanna, R., Prasia, P., Pratten, G., Principe, G., Principe, M., Prodi, G. A., Prokhorov, L., Prosposito, P., Puecher, A., Pullin, J., Punturo, M., Puppo, P., Pürrer, M., Qi, H., Qin, J., Quéméner, G., Quetschke, V., Quigley, C., Quinonez, P. J., Raab, F. J., Raabith, S. S., Raaijmakers, G., Raja, S., Rajan, C., Rajbhandari, B., Ramirez, K. E., Vidal, F. A. Ramis, Ramos-Buades, A., Rana, D., Ranjan, S., Ransom, K., Rapagnani, P., Ratto, B., Rawat, S., Ray, A., Raymond, V., Razzano, M., Read, J., Payo, M. Recaman, Regimbau, T., Rei, L., Reid, S., Reitze, D. H., Relton, P., Renzini, A. I., Rettegno, P., Revenu, B., Reyes, R., Rezaei, A. S., Ricci, F., Ricci, M., Ricciardone, A., Richardson, J. W., Richardson, M., Rijal, A., Riles, K., Riley, H. K., Rinaldi, S., Rittmeyer, J., Robertson, C., Robinet, F., Robinson, M., Rocchi, A., Rolland, L., Rollins, J. G., Romano, A. E., Romano, R., Romero, A., Romero-Shaw, I. M., Romie, J. H., Ronchini, S., Roocke, T. J., Rosa, L., Rosauer, T. J., Rose, C. A., Rosińska, D., Ross, M. P., Rossello, M., Rowan, S., Roy, S. K., Roy, S., Rozza, D., Ruggi, P., Ruhama, N., Morales, E. Ruiz, Ruiz-Rocha, K., Sachdev, S., Sadecki, T., Sadiq, J., Saffarieh, P., Sah, M. R., Saha, S. S., Saha, S., Sainrat, T., Menon, S. Sajith, Sakai, K., Sakellariadou, M., Sakon, S., Salafia, O. S., Salces-Carcoba, F., Salconi, L., Saleem, M., Salemi, F., Sallé, M., Salvador, S., Sanchez, A., Sanchez, E. J., Sanchez, J. H., Sanchez, L. E., Sanchis-Gual, N., Sanders, J. R., Sänger, E. M., Santoliquido, F., Saravanan, T. R., Sarin, N., Sasaoka, S., Sasli, A., Sassi, P., Sassolas, B., Satari, H., Sato, R., Sato, Y., Sauter, O., Savage, R. L., Sawada, T., Sawant, H. L., Sayah, S., Scacco, V., Schaetzl, D., Scheel, M., Schiebelbein, A., Schiworski, M. G., Schmidt, P., Schmidt, S., Schnabel, R., Schneewind, M., Schofield, R. M. S., Schouteden, K., Schulte, B. W., Schutz, B. F., Schwartz, E., Scialpi, M., Scott, J., Scott, S. M., Seetharamu, T. C., Seglar-Arroyo, M., Sekiguchi, Y., Sellers, D., Sengupta, A. S., Sentenac, D., Seo, E. G., Seo, J. W., Sequino, V., Serra, M., Servignat, G., Sevrin, A., Shaffer, T., Shah, U. S., Shaikh, M. A., Shao, L., Sharma, A. K., Sharma, P., Sharma-Chaudhary, S., Shaw, M. R., Shawhan, P., Shcheblanov, N. S., Sheridan, E., Shikano, Y., Shikauchi, M., Shimode, K., Shinkai, H., Shiota, J., Shoemaker, D. H., Shoemaker, D. M., Short, R. W., ShyamSundar, S., Sider, A., Siegel, H., Sieniawska, M., Sigg, D., Silenzi, L., Simmonds, M., Singer, L. P., Singh, A., Singh, D., Singh, M. K., Singh, S., Singha, A., Sintes, A. M., Sipala, V., Skliris, V., Slagmolen, B. J. J., Slaven-Blair, T. J., Smetana, J., Smith, J. R., Smith, L., Smith, R. J. E., Smith, W. J., Soldateschi, J., Somiya, K., Song, I., Soni, K., Soni, S., Sordini, V., Sorrentino, F., Sorrentino, N., Sotani, H., Soulard, R., Southgate, A., Spagnuolo, V., Spencer, A. P., Spera, M., Spinicelli, P., Spoon, J. B., Sprague, C. A., Srivastava, A. K., Stachurski, F., Steer, D. A., Steinlechner, J., Steinlechner, S., Stergioulas, N., Stevens, P., StPierre, M., Stratta, G., Strong, M. D., Strunk, A., Sturani, R., Stuver, A. L., Suchenek, M., Sudhagar, S., Sueltmann, N., Suleiman, L., Sullivan, K. D., Sun, L., Sunil, S., Suresh, J., Sutton, P. J., Suzuki, T., Suzuki, Y., Swinkels, B. L., Syx, A., Szczepańczyk, M. J., Szewczyk, P., Tacca, M., Tagoshi, H., Tait, S. C., Takahashi, H., Takahashi, R., Takamori, A., Takase, T., Takatani, K., Takeda, H., Takeshita, K., Talbot, C., Tamaki, M., Tamanini, N., Tanabe, D., Tanaka, K., Tanaka, S. J., Tanaka, T., Tang, D., Tanioka, S., Tanner, D. B., Tao, L., Tapia, R. D., Martín, E. N. Tapia San, Tarafder, R., Taranto, C., Taruya, A., Tasson, J. D., Teloi, M., Tenorio, R., Themann, H., Theodoropoulos, A., Thirugnanasambandam, M. P., Thomas, L. M., Thomas, M., Thomas, P., Thompson, J. E., Thondapu, S. R., Thorne, K. A., Thrane, E., Tissino, J., Tiwari, A., Tiwari, P., Tiwari, S., Tiwari, V., Todd, M. R., Toivonen, A. M., Toland, K., Tolley, A. E., Tomaru, T., Tomita, K., Tomura, T., Tong-Yu, C., Toriyama, A., Toropov, N., Torres-Forné, A., Torrie, C. I., Toscani, M., Melo, I. Tosta e, Tournefier, E., Trapananti, A., Travasso, F., Traylor, G., Trevor, M., Tringali, M. C., Tripathee, A., Troian, G., Troiano, L., Trovato, A., Trozzo, L., Trudeau, R. J., Tsang, T. T. L., Tso, R., Tsuchida, S., Tsukada, L., Tsutsui, T., Turbang, K., Turconi, M., Turski, C., Ubach, H., Uchiyama, T., Udall, R. P., Uehara, T., Uematsu, M., Ueno, K., Ueno, S., Undheim, V., Ushiba, T., Vacatello, M., Vahlbruch, H., Vaidya, N., Vajente, G., Vajpeyi, A., Valdes, G., Valencia, J., Valentini, M., Vallejo-Peña, S. A., Vallero, S., Valsan, V., van Bakel, N., van Beuzekom, M., van Dael, M., Brand, J. F. J. van den, Broeck, C. Van Den, Vander-Hyde, D. C., van der Sluys, M., Van de Walle, A., van Dongen, J., Vandra, K., van Haevermaet, H., van Heijningen, J. V., Van Hove, P., VanKeuren, M., Vanosky, J., van Putten, M. H. P. M., van Ranst, Z., van Remortel, N., Vardaro, M., Vargas, A. F., Varghese, J. J., Varma, V., Vasúth, M., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venikoudis, S., Venneberg, J., Verdier, P., Verkindt, D., Verma, B., Verma, P., Verma, Y., Vermeulen, S. M., Vetrano, F., Veutro, A., Vibhute, A. M., Viceré, A., Vidyant, S., Viets, A. D., Vijaykumar, A., Vilkha, A., Villa-Ortega, V., Vincent, E. T., Vinet, J. -Y., Viret, S., Virtuoso, A., Vitale, S., Vives, A., Vocca, H., Voigt, D., von Reis, E. R. G., von Wrangel, J. S. A., Vyatchanin, S. P., Wade, L. E., Wade, M., Wagner, K. J., Wajid, A., Walker, M., Wallace, G. S., Wallace, L., Wang, H., Wang, J. Z., Wang, W. H., Wang, Z., Waratkar, G., Warner, J., Was, M., Washimi, T., Washington, N. Y., Watarai, D., Wayt, K. E., Weaver, B. R., Weaver, B., Weaving, C. R., Webster, S. A., Weinert, M., Weinstein, A. J., Weiss, R., Wellmann, F., Wen, L., Weßels, P., Wette, K., Whelan, J. T., Whiting, B. F., Whittle, C., Wildberger, J. B., Wilk, O. S., Wilken, D., Wilkin, A. T., Willadsen, D. J., Willetts, K., Williams, D., Williams, M. J., Williams, N. S., Willis, J. L., Willke, B., Wils, M., Winterflood, J., Wipf, C. C., Woan, G., Woehler, J., Wofford, J. K., Wolfe, N. E., Wong, H. T., Wong, H. W. Y., Wong, I. C. F., Wright, J. L., Wright, M., Wu, C., Wu, D. S., Wu, H., Wuchner, E., Wysocki, D. M., Xu, V. A., Xu, Y., Yadav, N., Yamamoto, H., Yamamoto, K., Yamamoto, T. S., Yamamoto, T., Yamamura, S., Yamazaki, R., Yan, S., Yan, T., Yang, F. W., Yang, F., Yang, K. Z., Yang, Y., Yarbrough, Z., Yasui, H., Yeh, S. -W., Yelikar, A. B., Yin, X., Yokoyama, J., Yokozawa, T., Yoo, J., Yu, H., Yuan, S., Yuzurihara, H., Zadrożny, A., Zanolin, M., Zeeshan, M., Zelenova, T., Zendri, J. -P., Zeoli, M., Zerrad, M., Zevin, M., Zhang, A. C., Zhang, L., Zhang, R., Zhang, T., Zhang, Y., Zhao, C., Zhao, Yue, Zhao, Yuhang, Zheng, Y., Zhong, H., Zhou, R., Zhu, X. -J., Zhu, Z. -H., Zimmerman, A. B., Zucker, M. E., Zweizig, J., Furlan, S. B. Araujo, Arzoumanian, Z., Basu, A., Cassity, A., Cognard, I., Crowter, K., del Palacio, S., Espinoza, C. M., Fonseca, E., Flynn, C. M. L., Gancio, G., Garcia, F., Gendreau, K. C., Good, D. C., Guillemot, L., Guillot, S., Keith, M. J., Kuiper, L., Lower, M. E., Lyne, A. G., McKee, J. W., Meyers, B. W., Palfreyman, J. L., Pearlman, A. B., Romero, G. E., Shannon, R. M., Shaw, B., Stairs, I. H., Stappers, B. W., Tan, C. M., Theureau, G., Thompson, M., Weltevrede, P., and Zubieta, E.

Subjects
Astrophysics - High Energy Astrophysical Phenomena
Abstract

Continuous gravitational waves (CWs) emission from neutron stars carries information about their internal structure and equation of state, and it can provide tests of General Relativity. We present a search for CWs from a set of 45 known pulsars in the first part of the fourth LIGO--Virgo--KAGRA observing run, known as O4a. We conducted a targeted search for each pulsar using three independent analysis methods considering the single-harmonic and the dual-harmonic emission models. We find no evidence of a CW signal in O4a data for both models and set upper limits on the signal amplitude and on the ellipticity, which quantifies the asymmetry in the neutron star mass distribution. For the single-harmonic emission model, 29 targets have the upper limit on the amplitude below the theoretical spin-down limit. The lowest upper limit on the amplitude is $6.4\!\times\!10^{-27}$ for the young energetic pulsar J0537-6910, while the lowest constraint on the ellipticity is $8.8\!\times\!10^{-9}$ for the bright nearby millisecond pulsar J0437-4715. Additionally, for a subset of 16 targets we performed a narrowband search that is more robust regarding the emission model, with no evidence of a signal. We also found no evidence of non-standard polarizations as predicted by the Brans-Dicke theory., Comment: main paper: 12 pages, 6 figures, 4 tables

Published
2025

26. Fecal microbiota is associated with extraintestinal manifestations in inflammatory bowel disease.

Author

Hertz, Sandra, Anderson, Jacqueline, Nielsen, Hans, Schachtschneider, Claire, McCauley, Kathryn, Özçam, Mustafa, Larsen, Lone, Lynch, Susan, and Nielsen, Henrik

Subjects
16S rRNA sequencing, Crohn’s disease, Gut microbiota, extraintestinal manifestations, inflammatory bowel disease, ulcerative colitis, Humans, Feces, Male, Gastrointestinal Microbiome, Female, Inflammatory Bowel Diseases, Middle Aged, Adult, RNA, Ribosomal, 16S, Denmark, Leukocyte L1 Antigen Complex, Aged
Abstract

INTRODUCTION: A large proportion of patients with inflammatory bowel disease (IBD) experience IBD-related inflammatory conditions outside of the gastrointestinal tract, termed extraintestinal manifestations (EIMs) which further decreases quality of life and, in extreme cases, can be life threatening. The pathogenesis of EIMs remains unknown, and although gut microbiota alterations are a well-known characteristic of patients with IBD, its relationship with EIMs remains sparsely investigated. This study aimed to compare the gut microbiota of patients with IBD with and without EIMs. METHODS: A total of 131 Danish patients with IBD were included in the study, of whom 86 had a history of EIMs (IBD-EIM) and 45 did not (IBD-C). Stool samples underwent 16S rRNA sequencing. Amplicon sequence variants (ASVs) were mapped to the Silva database. Diversity indices and distance matrices were compared between IBD-EIM and IBD-C. Differentially abundant ASVs were identified using a custom multiple model statistical analysis approach, and modules of co-associated bacteria were identified using sparse correlations for compositional data (SparCC) and related to patient EIM status. RESULTS: Patients with IBD and EIMs exhibited increased disease activity, body mass index, increased fecal calprotectin levels and circulating monocytes and neutrophils. Microbiologically, IBD-EIM exhibited lower fecal microbial diversity than IBD-C (Mann-Whitneys test, p = .01) and distinct fecal microbiota composition (permutational multivariate analysis of variance; weighted UniFrac, R2 = 0.018, p = .01). A total of 26 ASVs exhibited differential relative abundances between IBD-EIM and IBD-C, including decreased Agathobacter and Blautia and increased Eggerthella lenta in the IBD-EIM group. SparCC analysis identified 27 bacterial co-association modules, three of which were negatively related to EIM (logistic regression, p

Published
2024

27. SeagrassFinder: Deep Learning for Eelgrass Detection and Coverage Estimation in the Wild

Author

Elsäßer, Jannik, Weihl, Laura, Cheplygina, Veronika, and Nielsen, Lisbeth Tangaa

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

Seagrass meadows play a crucial role in marine ecosystems, providing important services such as carbon sequestration, water quality improvement, and habitat provision. Monitoring the distribution and abundance of seagrass is essential for environmental impact assessments and conservation efforts. However, the current manual methods of analyzing underwater video transects to assess seagrass coverage are time-consuming and subjective. This work explores the use of deep learning models to automate the process of seagrass detection and coverage estimation from underwater video data. A dataset of over 8,300 annotated underwater images was created, and several deep learning architectures, including ResNet, InceptionNetV3, DenseNet, and Vision Transformer, were evaluated for the task of binary classification of ``Eelgrass Present'' and ``Eelgrass Absent'' images. The results demonstrate that deep learning models, particularly the Vision Transformer, can achieve high performance in predicting eelgrass presence, with AUROC scores exceeding 0.95 on the final test dataset. The use of transfer learning and the application of the Deep WaveNet underwater image enhancement model further improved the models' capabilities. The proposed methodology allows for the efficient processing of large volumes of video data, enabling the acquisition of much more detailed information on seagrass distributions compared to current manual methods. This information is crucial for environmental impact assessments and monitoring programs, as seagrasses are important indicators of coastal ecosystem health. Overall, this project demonstrates the value that deep learning can bring to the field of marine ecology and environmental monitoring.

Published
2024

28. A simple yet accurate stochastic approach to the quantum phase noise of nanolasers

Author

Bundgaard-Nielsen, Matias, Saldutti, Marco, Gøtzsche, Benjamin Falkenberg, Grovn, Emil, and Mørk, Jesper

Subjects
Quantum Physics
Abstract

Nanolasers operating at low power levels are strongly affected by intrinsic quantum noise, affecting both intensity fluctuations and laser coherence. Starting from semi-classical rate equations and making a simple hypothesis for the phase of the laser field, a simple stochastic model for the laser quantum noise is suggested. The model is shown to agree quantitatively with quantum master equations for microscopic lasers with a small number of emitters and with classical Langevin equations for macroscopic systems. In contrast, neither quantum master equations nor classical Langevin equations adequately address the mesoscopic regime. The stochastic approach is used to calculate the linewidth throughout the transition to lasing, where the linewidth changes from being dominated by the particle-like nature of photons below threshold to the wave-like nature above threshold, where it is strongly influenced by index fluctuations enhancing the linewidth., Comment: 6 pages, 4 figures. Submitted for PRL

Published
2024

29. WaveguideQED.jl: An Efficient Framework for Simulating Non-Markovian Waveguide Quantum Electrodynamics

Author

Bundgaard-Nielsen, Matias, Englund, Dirk, Heuck, Mikkel, and Krastanov, Stefan

Subjects
Quantum Physics
Abstract

In this paper, we introduce a numerical framework designed to solve problems within the emerging field of Waveguide Quantum Electrodynamics (WQED). The framework is based on collision quantum optics, where a localized quantum system interacts sequentially with individual time-bin modes. This approach provides a physically intuitive model that allows researchers familiar with tools such as QuTiP in Python, Quantum Optics Toolbox for Matlab, or QuantumOptics.jl in Julia to efficiently set up and execute WQED simulations. Despite its conceptual simplicity, we demonstrate the framework's robust ability to handle complex WQED scenarios. These applications include the scattering of single- or two-photon pulses by quantum emitters or cavities, as well as the exploration of non-Markovian dynamics, where emitted photons are reflected back, thereby introducing feedback mechanisms., Comment: 14 pages, 7 figures

Published
2024

30. Experimental Study of Low-Latency Video Streaming in an ORAN Setup with Generative AI

Author

Casparsen, Andreas, Bui, Van-Phuc, Pandey, Shashi Raj, Nielsen, Jimmy Jessen, and Popovski, Petar

Subjects
Computer Science - Networking and Internet Architecture, Electrical Engineering and Systems Science - Signal Processing
Abstract

Video streaming services depend on the underlying communication infrastructure and available network resources to offer ultra-low latency, high-quality content delivery. Open Radio Access Network (ORAN) provides a dynamic, programmable, and flexible RAN architecture that can be configured to support the requirements of time-critical applications. This work considers a setup in which the constrained network resources are supplemented by \gls{GAI} and \gls{MEC} {techniques} in order to reach a satisfactory video quality. Specifically, we implement a novel semantic control channel that enables \gls{MEC} to support low-latency applications by tight coupling among the ORAN xApp, \gls{MEC}, and the control channel. The proposed concepts are experimentally verified with an actual ORAN setup that supports video streaming. The performance evaluation includes the \gls{PSNR} metric and end-to-end latency. Our findings reveal that latency adjustments can yield gains in image \gls{PSNR}, underscoring the trade-off potential for optimized video quality in resource-limited environments.

Published
2024

31. The Global Carbon Budget as a cointegrated system

Author

Bennedsen, Mikkel, Hillebrand, Eric, and Nielsen, Morten Ørregaard

Subjects
Statistics - Applications, Economics - Econometrics
Abstract

The Global Carbon Budget, maintained by the Global Carbon Project, summarizes Earth's global carbon cycle through four annual time series beginning in 1959: atmospheric CO$_2$ concentrations, anthropogenic CO$_2$ emissions, and CO$_2$ uptake by land and ocean. We analyze these four time series as a multivariate (cointegrated) system. Statistical tests show that the four time series are cointegrated with rank three and identify anthropogenic CO$_2$ emissions as the single stochastic trend driving the nonstationary dynamics of the system. The three cointegrated relations correspond to the physical relations that the sinks are linearly related to atmospheric concentrations and that the change in concentrations equals emissions minus the combined uptake by land and ocean. Furthermore, likelihood ratio tests show that a parametrically restricted error-correction model that embodies these physical relations and accounts for the El Ni\~no/Southern Oscillation cannot be rejected on the data. The model can be used for both in-sample and out-of-sample analysis. In an application of the latter, we demonstrate that projections based on this model, using Shared Socioeconomic Pathways scenarios, yield results consistent with established climate science., Comment: Fixed broken reference

Published
2024

32. Bireflections of the commutator subgroup of an orthogonal group over the reals

Author

Nielsen, Klaus

Subjects
Mathematics - Group Theory, 20G20, 14L35, 15A23
Abstract

Let $O(p,q)$ be the orthogonal groups of signature $(p,q)$ over the reals. It is shown that an element of the commutator subgroup $O(p,q)'$ of $O(p,q)$ is bireflectional (product of 2 involutions in $O(p,q)'$) if and only if it is reversible (conjugate to its inverse). Moreover, the bireflectional elements of $O(p, q)'$ are classified., Comment: 7 pages. arXiv admin note: text overlap with arXiv:2411.01323

Published
2024

33. Searches for signatures of ultra-light axion dark matter in polarimetry data of the European Pulsar Timing Array

Author

Porayko, N. K., Usynina, P., Terol-Calvo, J., Camalich, J. Martin, Shaifullah, G. M., Castillo, A., Blas, D., Guillemot, L., Peel, M., Tiburzi, C., Postnov, K., Kramer, M., Antoniadis, J., Babak, S., Nielsen, A. -S. Bak, Barausse, E., Bassa, C. G., Blanchard, C., Bonetti, M., Bortolas, E., Brook, P. R., Burgay, M., Caballero, R. N., Chalumeau, A., Champion, D. J., Chanlaridis, S., Chen, S., Cognard, I., Desvignes, G., Falxa, M., Ferdman, R. D., Franchini, A., Gair, J. R., Goncharov, B., Graikou, E., Grießmeier, J. -M., Guo, Y. J., Hu, H., Iraci, F., Izquierdo-Villalba, D., Jang, J., Jawor, J., Janssen, G. H., Jessner, A., Karuppusamy, R., Keane, E. F., Keith, M. J., Krishnakumar, M. A., Lackeos, K., Lee, K. J., Liu, K., Liu, Y., Lyne, A. G., McKee, J. W., Main, R. A., Mickaliger, M. B., Niţu, I. C., Parthasarathy, A., Perera, B. B. P., Perrodin, D., Petiteau, A., Possenti, A., Leclere, H. Quelquejay, Samajdar, A., Sanidas, S. A., Sesana, A., Speri, L., Spiewak, R., Stappers, B. W., Susarla, S. C., Theureau, G., van der Wateren, E., Vecchio, A., Krishnan, V. Venkatraman, Wang, J., Wang, L., and Wu, Z.

Subjects
Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - High Energy Astrophysical Phenomena
Abstract

Ultra-light axion-like particles (ALPs) can be a viable solution to the dark matter problem. The scalar field associated with ALPs, coupled to the electromagnetic field, acts as an active birefringent medium, altering the polarisation properties of light through which it propagates. In particular, oscillations of the axionic field induce monochromatic variations of the plane of linearly polarised radiation of astrophysical signals. The radio emission of millisecond pulsars provides an excellent tool to search for such manifestations, given their high fractional linear polarisation and negligible fluctuations of their polarisation properties. We have searched for the evidence of ALPs in the polarimetry measurements of pulsars collected and preprocessed for the European Pulsar Timing Array (EPTA) campaign. Focusing on the twelve brightest sources in linear polarisation, we searched for an astrophysical signal from axions using both frequentist and Bayesian statistical frameworks. For the frequentist analysis, which uses Lomb-Scargle periodograms at its core, no statistically significant signal has been found. The model used for the Bayesian analysis has been adjusted to accommodate multiple deterministic systematics that may be present in the data. A statistically significant signal has been found in the dataset of multiple pulsars with common frequency between $10^{-8}$ Hz and $2\times10^{-8}$ Hz, which can most likely be explained by the residual Faraday rotation in the terrestrial ionosphere. Strong bounds on the coupling constant $g_{a\gamma}$, in the same ballpark as other searches, have been obtained in the mass range between $6\times10^{-24}$ eV and $5\times10^{-21}$ eV. We conclude by discussing problems that can limit the sensitivity of our search for ultra-light axions in the polarimetry data of pulsars, and possible ways to resolve them., Comment: 24 pages, 15 figures

Published
2024

34. Trading off performance and human oversight in algorithmic policy: evidence from Danish college admissions

Author

Nielsen, Magnus Lindgaard, Raaschou-Pedersen, Jonas Skjold, Chrisander, Emil, Lassen, David Dreyer, Grenet, Julien, Rogers, Anna, and Bjerre-Nielsen, Andreas

Subjects
Computer Science - Computers and Society
Abstract

Student dropout is a significant concern for educational institutions due to its social and economic impact, driving the need for risk prediction systems to identify at-risk students before enrollment. We explore the accuracy of such systems in the context of higher education by predicting degree completion before admission, with potential applications for prioritizing admissions decisions. Using a large-scale dataset from Danish higher education admissions, we demonstrate that advanced sequential AI models offer more precise and fair predictions compared to current practices that rely on either high school grade point averages or human judgment. These models not only improve accuracy but also outperform simpler models, even when the simpler models use protected sociodemographic attributes. Importantly, our predictions reveal how certain student profiles are better matched with specific programs and fields, suggesting potential efficiency and welfare gains in public policy. We estimate that even the use of simple AI models to guide admissions decisions, particularly in response to a newly implemented nationwide policy reducing admissions by 10 percent, could yield significant economic benefits. However, this improvement would come at the cost of reduced human oversight and lower transparency. Our findings underscore both the potential and challenges of incorporating advanced AI into educational policymaking.

Published
2024

35. Assessing the Efficacy of Classical and Deep Neuroimaging Biomarkers in Early Alzheimer's Disease Diagnosis

Author

Nielsen, Milla E., Nielsen, Mads, and Ghazi, Mostafa Mehdipour

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Alzheimer's disease (AD) is the leading cause of dementia, and its early detection is crucial for effective intervention, yet current diagnostic methods often fall short in sensitivity and specificity. This study aims to detect significant indicators of early AD by extracting and integrating various imaging biomarkers, including radiomics, hippocampal texture descriptors, cortical thickness measurements, and deep learning features. We analyze structural magnetic resonance imaging (MRI) scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohorts, utilizing comprehensive image analysis and machine learning techniques. Our results show that combining multiple biomarkers significantly improves detection accuracy. Radiomics and texture features emerged as the most effective predictors for early AD, achieving AUCs of 0.88 and 0.72 for AD and MCI detection, respectively. Although deep learning features proved to be less effective than traditional approaches, incorporating age with other biomarkers notably enhanced MCI detection performance. Additionally, our findings emphasize the continued importance of classical imaging biomarkers in the face of modern deep-learning approaches, providing a robust framework for early AD diagnosis., Comment: SPIE Medical Imaging (MI25)

Published
2024

36. Rate and Review

Author

Maria Nielsen Stewart, Noah Brown, Amber Candela, Samuel Otten, and Zandra de Araujo

Abstract

The authors developed an instructional nudges as part of a larger research project. These instructional nudges are designed to be small but powerful changes to teachers' existing practices. Some instructional nudges focus on modifying tasks used in classrooms. In this article, the authors share Rate and Review. The goal of Rate and Review is to support students in understanding that there are alternative solution strategies to what they might be used to using, provide students the opportunity to become more comfortable creating mathematical arguments, and develop a deeper understanding of a concept. Rate and Review provides formative assessment for teachers by supporting their reflections on students' understanding of current content and how students are making sense of common errors.

Published
2025
Full Text
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37. A Meta-Analytic Evaluation: Investigating Evidence for the Validity of the Cognitive Abilities Test

Author

Zafer Ozen, Nielsen Pereira, Tugce Karatas, Hernán Castillo-Hermosilla, and Yukiko Maeda

Abstract

Cognitive Abilities Test (CogAT) is one of the most frequently used gifted identification tools. In this meta-analytic study, we investigated empirical evidence of the validity of CogAT, in relation to different types of instruments. After reviewing 1,480 studies, a total of 24 with 33 effect sizes were included in the meta-analysis. According to our findings, the average effect size of r was found to be 0.63 with a 95% confidence interval [0.57, 0.69]. Based on the heterogeneity test, significant variation due to the systematic between-study differences exists among the included correlations. Egger's test for funnel plot asymmetry also indicates that no obvious publication bias exists in our study pool, which indicates there might not be a serious threat to alter the obtained results with publication bias. The moderator analysis revealed Lohman's authorship and publication type influenced the effect size differences among studies. CogAT's overall correlation with other identification tools (0.63) might suggest using at least one more identification tool besides CogAT.

Published
2025
Full Text
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38. A Rapid Review of Mental Health Training Programs for School Nurses.

Author

Thomas, Cassidie, Nielsen, Tiffany, and Best, Nakia

Subjects
reviews, school nurse, school nurse continuing education, student mental health, Humans, School Nursing, Mental Health, School Mental Health Services, School Health Services
Abstract

There is an urgent need for improved school-based mental health services to address students increasing mental health needs. School nurses are often at the frontlines of youth mental health, but report feeling unprepared to manage student needs due to limited training. We conducted a rapid review to identify evidence-based mental health educational interventions for school nurses and evaluate program characteristics. Eleven studies met the inclusion criteria. While the literature evaluating mental health training programs for school nurses is limited, it suggests that training may improve school nurse knowledge, confidence, and preparedness to address student mental health needs and improve the management of student mental health. Additionally, it highlighted the importance of support, resources, and policies that foster mental health promotion. Future research should focus on obtaining a current assessment of school nurse mental health education needs, evaluating existing interventions, and developing more evidence-based mental health training programs for school nurses.

Published
2025

39. Real-world clinical impact of plasma cell-free DNA metagenomic next-generation sequencing assay.

Author

Kaur, Ishminder, Shaw, Bennett, Multani, Ashrit, Pham, Christine, Malhotra, Sanchi, Smith, Ethan, Adachi, Kristina, Allyn, Paul, Bango, Zackary, Beaird, Omer Eugene, Caldera, JR, Chandrasekaran, Sukantha, Chan, Lynn, Cheema, Rabia, Daouk, Sarah, Deville, Jaime, Dong, Huan Vinh, Fan, Austin, Garner, Omai, Gaynor, Pryce, Gray, Hannah, Gorin, Aleksandr, Kalava, Sowmya, Kanatani, Meganne, Karnaze, Andrew, Saleh, Tawny, Sharma, Yamini, Stauber, Stacey, Vargas, Moises, Veral, Monette, Winston, Drew, Yanagimoto-Ogawa, Lauren, Aldrovandi, Grace, Nielsen-Saines, Karin, Fuller, Trevon, Jackson, Nicholas, Uslan, Daniel, Schaenman, Joanna, Vijayan, Tara, Sakona, Ashlyn, and Yang, Shangxin

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Women's Health, Clinical Research, Infection, Medical and Health Sciences, Epidemiology, Biomedical and clinical sciences, Health sciences
Abstract

To describe the real-world clinical impact of a commercially available plasma cell-free DNA metagenomic next-generation sequencing assay, the Karius test (KT). We retrospectively evaluated the clinical impact of KT by clinical panel adjudication. Descriptive statistics were used to study associations of diagnostic indications, host characteristics, and KT-generated microbiologic patterns with the clinical impact of KT. Multivariable logistic regression modeling was used to further characterize predictors of higher positive clinical impact. We evaluated 1000 unique clinical cases of KT from 941 patients between January 1, 2017-August 31, 2023. The cohort included adult (70%) and pediatric (30%) patients. The overall clinical impact of KT was positive in 16%, negative in 2%, and no clinical impact in 82% of the cases. Among adult patients, multivariable logistic regression modeling showed that culture-negative endocarditis (OR 2.3; 95% CI, 1.11-4.53; P .022) and concern for fastidious/zoonotic/vector-borne pathogens (OR 2.1; 95% CI, 1.11-3.76; P .019) were associated with positive clinical impact of KT. Host immunocompromised status was not reliably associated with a positive clinical impact of KT (OR 1.03; 95% CI, 0.83-1.29; P .7806). No significant predictors of KT clinical impact were found in pediatric patients. Microbiologic result pattern was also a significant predictor of impact. Our study highlights that despite the positive clinical impact of KT in select situations, most testing results had no clinical impact. We also confirm diagnostic indications where KT may have the highest yield, thereby generating tools for diagnostic stewardship.

Published
2025

40. Nr4a1 and Nr4a3 redundantly control clonal deletion and contribute to an anergy-like transcriptome in auto-reactive thymocytes to impose tolerance in mice.

Author

Nielsen, Hailyn, Yang, Letitia, Mueller, James, Ritter, Alexander, Hiwa, Ryosuke, Proekt, Irina, Rackaityte, Elze, Aylard, Dominik, Gupta, Mansi, Scharer, Christopher, Anderson, Mark, Au-Yeung, Byron, and Zikherman, Julie

Subjects
Animals, Nuclear Receptor Subfamily 4, Group A, Member 1, Thymocytes, Mice, Clonal Deletion, Transcriptome, Receptors, Thyroid Hormone, Clonal Anergy, Mice, Inbred C57BL, Mice, Knockout, Receptors, Steroid, Thymus Gland, DNA-Binding Proteins, T-Lymphocytes, Regulatory, Immune Tolerance, Receptors, Antigen, T-Cell, Bcl-2-Like Protein 11, Male, Female, Nerve Tissue Proteins
Abstract

The Nr4a nuclear hormone receptors are transcriptionally upregulated in response to antigen recognition by the T cell receptor (TCR) in the thymus and are implicated in clonal deletion, but the mechanisms by which they operate are not clear. Moreover, their role in central tolerance is obscured by redundancy among the Nr4a family members and by their reported functions in Treg generation and maintenance. Here we take advantage of competitive bone marrow chimeras and the OT-II/RIPmOVA model to show that Nr4a1 and Nr4a3 are essential for the upregulation of Bcl2l11/BIM and thymic clonal deletion by self-antigen. Importantly, thymocytes lacking Nr4a1/3 acquire an anergy-like signature after escaping clonal deletion and Treg lineage diversion. We further show that the Nr4a family helps mediate a broad transcriptional program in self-reactive thymocytes that resembles anergy and may operate at the margins of canonical thymic tolerance mechanisms to restrain self-reactive T cells after thymic egress.

Published
2025

41. A Dual‐Emissive DNA‐Templated Silver Nanocluster with Near‐Infrared I and II Emission

Author

Gonzàlez‐Rosell, Anna, Rück, Vanessa, Liisberg, Mikkel B, Cerretani, Cecilia, Nielsen, Villads RM, Vosch, Tom, and Copp, Stacy M

Subjects
Macromolecular and Materials Chemistry, Chemical Sciences, Bioengineering, Nanotechnology, DNA, Luminescence, Nanoclusters, Near-infrared, Optical Physics, Electrical and Electronic Engineering, Materials Engineering, Macromolecular and materials chemistry, Materials engineering, Condensed matter physics
Abstract

DNA-stabilized silver nanoclusters (DNA-AgN) are atomically precise and sequence-tuned nanomaterials with potential applications for deep tissue biomedical imaging. Here, a dual-emissive DNA-AgN is presented with fluorescence in the first near-infrared (NIR-I) spectral window and microsecond-lived photoluminescence in the second near-infrared (NIR-II) spectral window. High-resolution electrospray ionization mass spectrometry showed that the emitter has the molecular formula (DNA)2[Ag17]11+. The crystallization of (DNA)2[Ag17]11+ was unsuccessful, which prevented the use of X-ray diffraction to determine its structure. However, sequence variations of the templating DNA oligomer provided insights into nucleobases that are critical for stabilizing the Ag1711+. Moreover, addition of an adenosine or thymidine at the 5′-end of the stabilizing DNA strand maintained the composition and photophysical properties of the (DNA)2[Ag17]11+, suggesting a potential site for conjugation with biomolecules to enable targeted labeling in future bioimaging applications.

Published
2025

42. Discovery of robust and highly specific microbiome signatures of non-alcoholic fatty liver disease

Author

Nychas, Emmanouil, Marfil-Sánchez, Andrea, Chen, Xiuqiang, Mirhakkak, Mohammad, Li, Huating, Jia, Weiping, Xu, Aimin, Nielsen, Henrik Bjørn, Nieuwdorp, Max, Loomba, Rohit, Ni, Yueqiong, and Panagiotou, Gianni

Subjects
Microbiology, Biological Sciences, Machine Learning and Artificial Intelligence, Obesity, Digestive Diseases, Prevention, Hepatitis, Microbiome, Chronic Liver Disease and Cirrhosis, Nutrition, Genetics, Liver Disease, 2.1 Biological and endogenous factors, Metabolic and endocrine, Oral and gastrointestinal, Cardiovascular, Non-alcoholic Fatty Liver Disease, Humans, Gastrointestinal Microbiome, Female, Male, Middle Aged, Bacteria, Machine Learning, Metagenomics, Adult, Metagenome, NAFLD, Gut microbiota, Metabolic diseases, Machine learning, Network analysis, Metabolomics, Microbial consortia, Ecology, Medical Microbiology, Evolutionary biology
Abstract

BackgroundThe pathogenesis of non-alcoholic fatty liver disease (NAFLD) with a global prevalence of 30% is multifactorial and the involvement of gut bacteria has been recently proposed. However, finding robust bacterial signatures of NAFLD has been a great challenge, mainly due to its co-occurrence with other metabolic diseases.ResultsHere, we collected public metagenomic data and integrated the taxonomy profiles with in silico generated community metabolic outputs, and detailed clinical data, of 1206 Chinese subjects w/wo metabolic diseases, including NAFLD (obese and lean), obesity, T2D, hypertension, and atherosclerosis. We identified highly specific microbiome signatures through building accurate machine learning models (accuracy = 0.845-0.917) for NAFLD with high portability (generalizable) and low prediction rate (specific) when applied to other metabolic diseases, as well as through a community approach involving differential co-abundance ecological networks. Moreover, using these signatures coupled with further mediation analysis and metabolic dependency modeling, we propose synergistic defined microbial consortia associated with NAFLD phenotype in overweight and lean individuals, respectively.ConclusionOur study reveals robust and highly specific NAFLD signatures and offers a more realistic microbiome-therapeutics approach over individual species for this complex disease. Video Abstract.

Published
2025

43. Revisiting the Briggs Ancient DNA Damage Model: A Fast Maximum Likelihood Method to Estimate Post-Mortem Damage.

Author

Zhao, Lei, Henriksen, Rasmus, Ramsøe, Abigail, Nielsen, Rasmus, and Korneliussen, Thorfinn

Subjects
DNA deamination, ancient DNA, high‐throughput data, maximum likelihood estimation, posterior ancient probability, statistical inference, DNA, Ancient, DNA Damage, Sequence Analysis, DNA, Likelihood Functions, High-Throughput Nucleotide Sequencing, Computational Biology, Humans
Abstract

One essential initial step in the analysis of ancient DNA is to authenticate that the DNA sequencing reads are actually from ancient DNA. This is done by assessing if the reads exhibit typical characteristics of post-mortem damage (PMD), including cytosine deamination and nicks. We present a novel statistical method implemented in a fast multithreaded programme, ngsBriggs that enables rapid quantification of PMD by estimation of the Briggs ancient damage model parameters (Briggs parameters). Using a multinomial model with maximum likelihood fit, ngsBriggs accurately estimates the parameters of the Briggs model, quantifying the PMD signal from single and double-stranded DNA regions. We extend the original Briggs model to capture PMD signals for contemporary sequencing platforms and show that ngsBriggs accurately estimates the Briggs parameters across a variety of contamination levels. Classification of reads into ancient or modern reads, for the purpose of decontamination, is significantly more accurate using ngsBriggs than using other methods available. Furthermore, ngsBriggs is substantially faster than other state-of-the-art methods. ngsBriggs offers a practical and accurate method for researchers seeking to authenticate ancient DNA and improve the quality of their data.

Published
2025

44. The International Bathymetric Chart of the Arctic Ocean Version 5.0.

Author

Jakobsson, Martin, Mohammad, Rezwan, Karlsson, Marcus, Salas-Romero, Silvia, Vacek, Florian, Heinze, Florian, Bringensparr, Caroline, Castro, Carlos, Johnson, Paul, Kinney, Juliet, Cardigos, Sara, Bogonko, Michael, Accettella, Daniela, Amblas, David, An, Lu, Bohan, Aileen, Brandt, Angelika, Bünz, Stefan, Canals, Miquel, Casamor, José, Coakley, Bernard, Cornish, Natalie, Danielson, Seth, Demarte, Maurizio, Di Franco, Davide, Dickson, Mary-Lynn, Dorschel, Boris, Dowdeswell, Julian, Dreutter, Simon, Fremand, Alice, Hall, John, Hally, Bryan, Holland, David, Hong, Jon, Ivaldi, Roberta, Knutz, Paul, Krawczyk, Diana, Kristofferson, Yngve, Lastras, Galderic, Leck, Caroline, Lucchi, Renata, Masetti, Giuseppe, Morlighem, Mathieu, Muchowski, Julia, Nielsen, Tove, Noormets, Riko, Plaza-Faverola, Andreia, Prescott, Megan, Purser, Autun, Rasmussen, Tine, Rebesco, Michele, Rignot, Eric, Rysgaard, Søren, Silyakova, Anna, Snoeijs-Leijonmalm, Pauline, Sørensen, Aqqaluk, Straneo, Fiammetta, Sutherland, David, Tate, Alex, Travaglini, Paola, Trenholm, Nicole, van Wijk, Esmee, Wallace, Luke, Willis, Josh, Wood, Michael, Zimmermann, Mark, Zinglersen, Karl, and Mayer, Larry

Abstract

Knowledge about seafloor depth, or bathymetry, is crucial for various marine activities, including scientific research, offshore industry, safety of navigation, and ocean exploration. Mapping the central Arctic Ocean is challenging due to the presence of perennial sea ice, which limits data collection to icebreakers, submarines, and drifting ice stations. The International Bathymetric Chart of the Arctic Ocean (IBCAO) was initiated in 1997 with the goal of updating the Arctic Ocean bathymetric portrayal. The project team has since released four versions, each improving resolution and accuracy. Here, we present IBCAO Version 5.0, which offers a resolution four times as high as Version 4.0, with 100 × 100 m grid cells compared to 200 × 200 m. Over 25% of the Arctic Ocean is now mapped with individual depth soundings, based on a criterion that considers water depth. Version 5.0 also represents significant advancements in data compilation and computing techniques. Despite these improvements, challenges such as sea-ice cover and political dynamics still hinder comprehensive mapping.

Published
2024

45. Gaps in biomedical research in frontotemporal dementia: A call for diversity and disparities focused research

Author

Nuytemans, Karen, Franzen, Sanne, Broce, Iris J, Caramelli, Paulo, Ellajosyula, Ratnavalli, Finger, Elizabeth, Gupta, Veer, Gupta, Vivek, Illán‐Gala, Ignacio, Loi, Samantha M, Morhardt, Darby, Pijnenburg, Yolande, Rascovsky, Katya, Williams, Monique M, Yokoyama, Jennifer S, Acosta‐Uribe, Juliana, Akinyemi, Rufus, Alladi, Suvarna, Ayele, Biniyam A, Ayhan, Yavuz, Bourdage, Renelle, Castro‐Suarez, Sheila, de Souza, Leonardo Cruz, Dacks, Penny, de Boer, Sterre CM, de Leon, Jessica, Dodge, Shana, Grasso, Stephanie, Ghoshal, Nupur, Kamath, Vidyulata, Kumfor, Fiona, Matias‐Guiu, Jordi A, Narme, Pauline, Nielsen, T Rune, Okhuevbie, Daniel, Piña‐Escudero, Stefanie, Ruiz‐Garcia, Ramiro, Ryan, Brigid, Scarioni, Marta, Slachevsky, Andrea, Suarez‐Gonzalez, Aida, Tee, Boon Lead, Tsoy, Elena, Ulugut, Hulya, Onyike, Chiadi U, Babulal, Ganesh M, and PIA, ISTAART Diversity and Disparities PIA ISTAART Frontotemporal Dementia and Related Disorders

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical Sciences, Neurosciences, Psychology, Frontotemporal Dementia (FTD), Dementia, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurodegenerative, Brain Disorders, Alzheimer's Disease Related Dementias (ADRD), Rare Diseases, Acquired Cognitive Impairment, Alzheimer's Disease, Aphasia, Aging, Behavioral and Social Science, Neurological, Humans, Frontotemporal Dementia, Biomedical Research, Healthcare Disparities, Cultural Diversity, biomarkers, cultural diversity, epidemiology, ethnicity, frontotemporal dementia, genetics, infrastructure, ISTAART Frontotemporal Dementia and Related Disorders PIA, ISTAART Diversity and Disparities PIA, Geriatrics, Clinical sciences, Biological psychology
Abstract

Frontotemporal dementia (FTD) is one of the leading causes of young-onset dementia before age 65, typically manifesting as abnormal behavior (in behavioral variant FTD) or language impairment (in primary progressive aphasia). Although FTD affects all populations across the globe, knowledge regarding the pathophysiology and genetics derives primarily from studies conducted in North America and Western Europe. Globally, biomedical research for FTD is hindered by variable access to diagnosis, discussed in this group's earlier article, and by reduced access to expertise, funding, and infrastructure. This perspective paper was produced by two professional interest areas of the Alzheimer's Association International Society to Advance Alzheimer's Research and Treatment (ISTAART) and discusses the field's current status on the cross-cultural aspects of basic and translational research in FTD (including that focused on epidemiology, genetics, biomarkers, and treatment). It subsequently provides a summary of gaps and needs to address the disparities and advance global FTD biomedical research.

Published
2024

46. Acupuncture in the emergency department (ACUITY): Results from a BraveNet multi-center feasibility randomized controlled trial.

Author

Dusek, Jeffery, Kallenberg, Gene, Storrow, Alan, Hughes, Robert, Coyne, Christopher, Vago, David, Nielsen, Arya, Karasz, Alison, Kim, Ryung, Surdam, Jessica, Segall, Tracy, Faryar, Kiran, Dyer, Natalie, Barton, Bruce, and McKee, M

Subjects
Acute pain, Integrative medicine, Nonpharmacologic, Randomized controlled trial
Abstract

BACKGROUND: Pain plays a significant role in emergency department (ED) visits, however safe and effective nonpharmacologic options are needed. Prior studies of acupuncture in the ED reported pain reduction with minimal side effects, but most were small and single site. METHODS: We conducted ACUITY, a prospectively designed multi-center feasibility RCT. Our goal was to recruit 165 adults with acute non-emergent pain ≥4 on a 0-10-point scale at three EDs affiliated with BraveNet Practice Based Research Network. At baseline and 45-60 min later (post), participants self-assessed their pain and anxiety using a 0-10 rating scale. The primary feasibility outcome was recruitment of participants, whereas secondary outcomes were retention, and participant/provider acceptability. RESULTS: From May 3, 2021, to September 24, 2022, 632 eligible individuals were approached and 165 enrolled (165/632: 26.1 %), meeting our recruitment goal. Notably, 42.4 % of enrollees were Black/African American, 42.4 % were White/Caucasian, and 13.9 % were Hispanic/Latino. Participants were randomized to Acupuncture (n = 83) or Usual care (n = 82), of which 151 (91.5 %) and 128 (77.6 %) provided pain and anxiety scores at post-treatment and 1-week respectively. Acupuncture was rated acceptable to participants and providers. Mean pain ratings (pre-to-post) were 7.4 (2.2) to 4.8 (2.8) for acupuncture and 7.1 (2.3) to 6.4 (2.5) for usual care. Mean anxiety ratings (pre-to-post) were 4.5 (3.4) to 2.5 (2.6) for acupuncture and 4.1 (3.4) to 3.5 (3.2) for usual care. CONCLUSION: Successful completion of ACUITY indicates we have the expertise and preliminary data to conduct a future definitive, multi-center RCT. TRIAL REGISTRATION CLINICAL TRIALSGOV: NCT04880733.

Published
2024

47. Methodological Improvements to the Public Libraries Survey

Author

Institute of Museum and Library Services (IMLS), E. Nielsen, and M. Pelczar

Abstract

This research brief describes recent methodological initiatives with the Public Libraries Survey. It describes how starting with the 2022 data, Institute of Museum and Library Services (IMLS) updated geographic identifiers to better align Census Bureau geography types with the library's legal service area, with the goal of enabling data users to link PLS data with other geographical data more easily (e.g., the American Community Survey) and is assessing the feasibility of outlet-level data collection over the next year.

Published
2024

48. MIRI Deep Imaging Survey (MIDIS) of the Hubble Ultra Deep Field

Author

Östlin, Göran, Pérez-González, Pablo G., Melinder, Jens, Gillman, Steven, Iani, Edoardo, Costantin, Luca, Boogaard, Leindert A., Rinaldi, Pierluigi, Colina, Luis, Nørgaard-Nielsen, Hans Ulrik, Dicken, Daniel, Greve, Thomas R., Wright, Gillian, Alonso-Herrero, Almudena, Alvarez-Marquez, Javier, Annunziatella, Marianna, Bik, Arjan, Bosman, Sarah E. I., Caputi, Karina I., Gomez, Alejandro Crespo, Eckart, Andreas, Garcia-Marin, Macarena, Hjorth, Jens, Ilbert, Olivier, Jermann, Iris, Kendrew, Sarah, Labiano, Alvaro, Langeroodi, Danial, Fevre, Olivier Le, Libralato, Mattia, Meyer, Romain A., Moutard, Thibaud, Peissker, Florian, Pye, John P., Tikkanen, Tuomo V., Topinka, Martin, Walter, Fabian, Ward, Martin, van der Werf, Paul, van Dishoeck, Ewine F., Henning, Manuel Güdel Thomas, Lagage, Pierre-Olivier, Ray, Tom P., and Vandenbussche, Bart

Subjects
Astrophysics - Astrophysics of Galaxies, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The recently launched James Webb Space Telescope (JWST) is opening new observing windows on the distant universe. Among JWST's instruments, the Mid Infrared Instrument (MIRI) offers the unique capability of imaging observations at wavelengths $\lambda > 5\mu$m. This enables unique access to the rest frame near infra-red (NIR, $\lambda \ge 1$\mum) emission from galaxies at redshifts $z>4$ and the visual ($\lambda \gtrsim 5000$\AA) rest frame for $z>9$. We here report on the guaranteed time observations (GTO) from the MIRI European Consortium, of the Hubble Ultra Deep Field (HUDF), forming the MIRI Deep Imaging Survey (MIDIS), consisting of an on source integration time of $\sim41$ hours in the MIRI/F560W (5.6 $\mu$m) filter. To our knowledge, this constitutes the longest single filter exposure obtained with JWST of an extragalactic field as yet., Comment: submitted to A&A on July 30, 2024

Published
2024

49. A possible misaligned orbit for the young planet AU Mic c

Author

Yu, H., Garai, Z., Cretignier, M., Szabó, Gy. M., Aigrain, S., Gandolfi, D., Bryant, E. M., Correia, A. C. M., Klein, B., Brandeker, A., Owen, J. E., Günther, M. N., Winn, J. N., Heitzmann, A., Cegla, H. M., Wilson, T. G., Gill, S., Kriskovics, L., Barragán, O., Boldog, A., Nielsen, L. D., Billot, N., Lafarga, M., Meech, A., Alibert, Y., Alonso, R., Bárczy, T., Barrado, D., Barros, S. C. C., Baumjohann, W., Bayliss, D., Benz, W., Bergomi, M., Borsato, L., Broeg, C., Cameron, A. Collier, Csizmadia, Sz., Cubillos, P. E., Davies, M. B., Deleuil, M., Deline, A., Demangeon, O. D. S., Demory, B. O., Derekas, A., Doyle, L., Edwards, B., Egger, J. A., Ehrenreich, D., Erikson, A., Fortier, A., Fossati, L., Fridlund, M., Gazeas, K., Gillon, M., Güdel, M., Helling, Ch., Isaak, K. G., Kiss, L. L., Korth, J., Lam, K. W. F., Laskar, J., Etangs, A. Lecavelier des, Lendl, M., Magrin, D., Maxted, P. F. L., McCormac, J., Merín, B., Mordasini, C., Nascimbeni, V., O'Brien, S. M., Olofsson, G., Ottensamer, R., Pagano, I., Pallé, E., Peter, G., Piazza, D., Piotto, G., Pollacco, D., Queloz, D., Ragazzoni, R., Rando, N., Rauer, H., Ribas, I., Santos, N. C., Scandariato, G., Ségransan, D., Simon, A. E., Smith, A. M. S., Sousa, S. G., Southworth, R., Stalport, M., Steinberger, M., Sulis, S., Udry, S., Ulmer, B., Ulmer-Moll, S., Van Grootel, V., Venturini, J., Villaver, E., Walton, N. A., and Wheatley, P. J.

Subjects
Astrophysics - Earth and Planetary Astrophysics, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics
Abstract

The AU Microscopii planetary system is only 24 Myr old, and its geometry may provide clues about the early dynamical history of planetary systems. Here, we present the first measurement of the Rossiter-McLaughlin effect for the warm sub-Neptune AU Mic c, using two transits observed simultaneously with the European Southern Observatory's (ESO's) Very Large Telescope (VLT)/Echelle SPectrograph for Rocky Exoplanets and Stable Spectroscopic Observations (ESPRESSO), CHaracterising ExOPlanet Satellite (CHEOPS), and Next-Generation Transit Survey (NGTS). After correcting for flares and for the magnetic activity of the host star, and accounting for transit-timing variations, we find the sky-projected spin-orbit angle of planet c to be in the range $\lambda_c=67.8_{-49.0}^{+31.7}$\,degrees (1-$\sigma$). We examine the possibility that planet c is misaligned with respect to the orbit of the inner planet b ($\lambda_b=-2.96_{-10.30}^{+10.44}$\,degrees), and the equatorial plane of the host star, and discuss scenarios that could explain both this and the planet's high density, including secular interactions with other bodies in the system or a giant impact. We note that a significantly misaligned orbit for planet c is in some degree of tension with the dynamical stability of the system, and with the fact that we see both planets in transit, though these arguments alone do not preclude such an orbit. Further observations would be highly desirable to constrain the spin-orbit angle of planet c more precisely., Comment: Accepted for publication in MNRAS

Published
2024
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50. Contrastive Deep Learning Reveals Age Biomarkers in Histopathological Skin Biopsies

Author

Chakradeo, Kaustubh, Nielsen, Pernille, Gjerdrum, Lise Mette Rahbek, Hansen, Gry Sahl, Duchêne, David A, Mortensen, Laust H, Jensen, Majken K, and Bhatt, Samir

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Artificial Intelligence, Computer Science - Computer Vision and Pattern Recognition
Abstract

As global life expectancy increases, so does the burden of chronic diseases, yet individuals exhibit considerable variability in the rate at which they age. Identifying biomarkers that distinguish fast from slow ageing is crucial for understanding the biology of ageing, enabling early disease detection, and improving prevention strategies. Using contrastive deep learning, we show that skin biopsy images alone are sufficient to determine an individual's age. We then use visual features in histopathology slides of the skin biopsies to construct a novel biomarker of ageing. By linking with comprehensive health registers in Denmark, we demonstrate that visual features in histopathology slides of skin biopsies predict mortality and the prevalence of chronic age-related diseases. Our work highlights how routinely collected health data can provide additional value when used together with deep learning, by creating a new biomarker for ageing which can be actively used to determine mortality over time., Comment: 20 pages, 5 tables, 5 figures Under review: npj Digital Medicine

Published
2024

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