148,490 results on '"Jacobsen, A"'
Search Results
2. 'I Am Not Complaining': Listening to International Students' Requests and Complaints as Expressions of Diverse Learning Needs
- Author
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Irene Torres-Arends and Michele Jacobsen
- Abstract
This study explores the learning needs of international students at a Canadian private university. Through a qualitative content analysis of 580 students' emails, we identified and examined 819 requests and complaints The analysis highlighted trends about due dates, assignment resubmissions, regrading, and plagiarism issues, leading to the identification of five primary needs: improved internet access and digital literacy support, acknowledgment of cultural differences, assignment design without assumptions, accessible learning management systems, and inclusive learning environments. These findings underline the necessity of empathetic listening to develop strategies that facilitate international students' transition to Canadian higher education, enhancing their learning experiences. The research suggests innovative approaches for incorporating international students' perspectives into course and program design, advocating for active engagement with these students to create educational environments that are inclusive and responsive to their unique needs.
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- 2024
3. Two Stage Segmentation of Cervical Tumors using PocketNet
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Twam, Awj, Jacobsen, Megan, Glenn, Rachel, Klopp, Ann, Venkatesan, Aradhana M., and Fuentes, David
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Cervical cancer remains the fourth most common malignancy amongst women worldwide.1 Concurrent chemoradiotherapy (CRT) serves as the mainstay definitive treatment regimen for locally advanced cervical cancers and includes external beam radiation followed by brachytherapy.2 Integral to radiotherapy treatment planning is the routine contouring of both the target tumor at the level of the cervix, associated gynecologic anatomy and the adjacent organs at risk (OARs). However, manual contouring of these structures is both time and labor intensive and associated with known interobserver variability that can impact treatment outcomes. While multiple tools have been developed to automatically segment OARs and the high-risk clinical tumor volume (HR-CTV) using computed tomography (CT) images,3,4,5,6 the development of deep learning-based tumor segmentation tools using routine T2-weighted (T2w) magnetic resonance imaging (MRI) addresses an unmet clinical need to improve the routine contouring of both anatomical structures and cervical cancers, thereby increasing quality and consistency of radiotherapy planning. This work applied a novel deep-learning model (PocketNet) to segment the cervix, vagina, uterus, and tumor(s) on T2w MRI. The performance of the PocketNet architecture was evaluated, when trained on data via 5-fold cross validation. PocketNet achieved a mean Dice-Sorensen similarity coefficient (DSC) exceeding 70% for tumor segmentation and 80% for organ segmentation. These results suggest that PocketNet is robust to variations in contrast protocols, providing reliable segmentation of the ROIs.
- Published
- 2024
4. Can Graph Reordering Speed Up Graph Neural Network Training? An Experimental Study
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Merkel, Nikolai, Toussing, Pierre, Mayer, Ruben, and Jacobsen, Hans-Arno
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Computer Science - Machine Learning ,Computer Science - Databases ,Computer Science - Performance - Abstract
Graph neural networks (GNNs) are a type of neural network capable of learning on graph-structured data. However, training GNNs on large-scale graphs is challenging due to iterative aggregations of high-dimensional features from neighboring vertices within sparse graph structures combined with neural network operations. The sparsity of graphs frequently results in suboptimal memory access patterns and longer training time. Graph reordering is an optimization strategy aiming to improve the graph data layout. It has shown to be effective to speed up graph analytics workloads, but its effect on the performance of GNN training has not been investigated yet. The generalization of reordering to GNN performance is nontrivial, as multiple aspects must be considered: GNN hyper-parameters such as the number of layers, the number of hidden dimensions, and the feature size used in the GNN model, neural network operations, large intermediate vertex states, and GPU acceleration. In our work, we close this gap by performing an empirical evaluation of 12 reordering strategies in two state-of-the-art GNN systems, PyTorch Geometric and Deep Graph Library. Our results show that graph reordering is effective in reducing training time for CPU- and GPU-based training, respectively. Further, we find that GNN hyper-parameters influence the effectiveness of reordering, that reordering metrics play an important role in selecting a reordering strategy, that lightweight reordering performs better for GPU-based than for CPU-based training, and that invested reordering time can in many cases be amortized., Comment: To be published in proceedings of the 51st International Conference on Very Large Data Bases (VLDB), September 1-5, 2025
- Published
- 2024
5. How Redundant Is the Transformer Stack in Speech Representation Models?
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Dorszewski, Teresa, Jacobsen, Albert Kjøller, Tětková, Lenka, and Hansen, Lars Kai
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Electrical Engineering and Systems Science - Audio and Speech Processing ,Computer Science - Computation and Language ,Computer Science - Machine Learning ,Computer Science - Sound - Abstract
Self-supervised speech representation models, particularly those leveraging transformer architectures, have demonstrated remarkable performance across various tasks such as speech recognition, speaker identification, and emotion detection. Recent studies on transformer models revealed a high redundancy between layers and the potential for significant pruning, which we will investigate here for transformer-based speech representation models. We perform a detailed analysis of layer similarity in speech representation models using three similarity metrics: cosine similarity, centered kernel alignment, and mutual nearest-neighbor alignment. Our findings reveal a block-like structure of high similarity, suggesting two main processing steps and significant redundancy of layers. We demonstrate the effectiveness of pruning transformer-based speech representation models without the need for post-training, achieving up to 40% reduction in transformer layers while maintaining over 95% of the model's predictive capacity. Furthermore, we employ a knowledge distillation method to substitute the entire transformer stack with mimicking layers, reducing the network size 95-98% and the inference time by up to 94%. This substantial decrease in computational load occurs without considerable performance loss, suggesting that the transformer stack is almost completely redundant for downstream applications of speech representation models.
- Published
- 2024
6. 1D Thermoembolization Model Using CT Imaging Data for Porcine Liver
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Amare, Rohan, Stolley, Danielle, Parrish, Steve, Jacobsen, Megan, Layman, Rick, Santos, Chimamanda, Riviere, Beatrice, Fowlkes, Natalie, Fuentes, David, and Cressman, Erik
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Physics - Medical Physics - Abstract
Objective: Innovative therapies such as thermoembolization are expected to play an important role in improvising care for patients with diseases such as hepatocellular carcinoma. Thermoembolization is a minimally invasive strategy that combines thermal ablation and embolization in a single procedure. This approach exploits an exothermic chemical reaction that occurs when an acid chloride is delivered via an endovascular route. However, comprehension of the complexities of the biophysics of thermoembolization is challenging. Mathematical models can aid in understanding such complex processes and assisting clinicians in making informed decisions. In this study, we used a Hagen Poiseuille 1D blood flow model to predict the mass transport and possible embolization locations in a porcine hepatic artery. Method: The 1D flow model was used on in vivo embolization imaging data of three pigs. The hydrolysis time constant of acid chloride chemical reaction was optimized for each pig, and LOOCV method was used to test the model's predictive ability. Conclusion: This basic model provided a balanced accuracy rate of 66.8% for identifying the possible locations of embolization in the hepatic artery. Use of the model provides an initial understanding of the vascular transport phenomena that are predicted to occur as a result of thermoembolization.
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- 2024
7. Bayesian optimization of atomic structures with prior probabilities from universal interatomic potentials
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Lyngby, Peder, Larsen, Casper, and Jacobsen, Karsten Wedel
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Condensed Matter - Materials Science ,Computer Science - Machine Learning - Abstract
The optimization of atomic structures plays a pivotal role in understanding and designing materials with desired properties. However, conventional methods often struggle with the formidable task of navigating the vast potential energy surface, especially in high-dimensional spaces with numerous local minima. Recent advancements in machine learning-driven surrogate models offer a promising avenue for alleviating this computational burden. In this study, we propose a novel approach that combines the strengths of universal machine learning potentials with a Bayesian approach of the GOFEE/BEACON framework. By leveraging the comprehensive chemical knowledge encoded in pretrained universal machine learning potentials as a prior estimate of energy and forces, we enable the Gaussian process to focus solely on capturing the intricate nuances of the potential energy surface. We demonstrate the efficacy of our approach through comparative analyses across diverse systems, including periodic bulk materials, surface structures, and a cluster.
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- 2024
8. Distributed Quantum Computing for Chemical Applications
- Author
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Jones, Grier M. and Jacobsen, Hans-Arno
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Quantum Physics ,Electrical Engineering and Systems Science - Systems and Control ,Physics - Chemical Physics - Abstract
In recent years, interest in quantum computing has increased due to technological advances in quantum hardware and algorithms. Despite the promises of quantum advantage, the applicability of quantum devices has been limited to few qubits on hardware that experiences decoherence due to noise. One proposed method to get around this challenge is distributed quantum computing (DQC). Like classical distributed computing, DQC aims at increasing compute power by spreading the compute processes across many devices, with the goal to minimize the noise and circuit depth required by quantum devices. In this paper, we cover the fundamental concepts of DQC and provide insight into where the field of DQC stands with respect to the field of chemistry -- a field which can potentially be used to demonstrate quantum advantage on noisy-intermediate scale quantum devices.
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- 2024
9. Cultural Transmission, Technology, and Treatment of the Elderly
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Baker, Matthew J. and Jacobsen, Joyce P.
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Economics - General Economics - Abstract
We discuss the interrelationship between the treatment of the elderly, the nature of production, and the transmission of culture. Respect for the elderly is endogenous. Parents cultivate an interest in consuming culture in their children; when they are older, children compensate their elders proportional to the degree to which their interests were previously cultivated. We show that this model is functionally equivalent to one in which cultural goods are transferred across generations. We focus on the relative well-being of the elderly and use the model to explain patterns in their relative well-being across societies. An important theme is that the cultivation of culture and norms for the respect and support of the elderly bear a nonlinear relationship with many economic variables, such as capital and or land intensity in production. We also discuss the interaction of property rights with production, assets such as productive resources, and relative treatment of the elderly. Insecurity of some types of property rights, such as rights over output, may benefit the elderly, while secure rights over productive resources may also benefit the elderly. We discuss how the elderly could be affected by demographic, technological and policy changes in both developing and developed economies.
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- 2024
10. The Solar eruptioN Integral Field Spectrograph
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Herde, Vicki L., Chamberlin, Phillip C., Schmit, Don, Daw, Adrian, Milligan, Ryan O., Polito, Vanessa, Bose, Souvik, Boyajian, Spencer, Buedel, Paris, Edgar, Will, Gebben, Alex, Gong, Qian, Jacobsen, Ross, Nell, Nicholas, Schwab, Bennet, Sims, Alan, Summers, David, Turner, Zachary, Valade, Trace, and Wallace, Joseph
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Astrophysics - Solar and Stellar Astrophysics ,Astrophysics - Instrumentation and Methods for Astrophysics ,Physics - Instrumentation and Detectors ,Physics - Space Physics - Abstract
The Solar eruptioN Integral Field Spectrograph (SNIFS) is a solar-gazing spectrograph scheduled to fly in the summer of 2025 on a NASA sounding rocket. Its goal is to view the solar chromosphere and transition region at a high cadence (1s) both spatially (0.5") and spectrally (33 m{\AA}) viewing wavelengths around Lyman Alpha (1216 {\AA}), Si iii (1206 {\AA}) and O v (1218 {\AA}) to observe spicules, nanoflares, and possibly a solar flare. This time cadence will provide yet-unobserved detail about fast-changing features of the Sun. The instrument is comprised of a Gregorian-style reflecting telescope combined with a spectrograph via a specialized mirrorlet array that focuses the light from each spatial location in the image so that it may be spectrally dispersed without overlap from neighboring locations. This paper discusses the driving science, detailed instrument and subsystem design, and pre-integration testing of the SNIFS instrument., Comment: 22 pages (not including references), 7 figures, submitting to Solar Physics
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- 2024
11. Federated Learning and AI Regulation in the European Union: Who is Responsible? -- An Interdisciplinary Analysis
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Woisetschläger, Herbert, Mertel, Simon, Krönke, Christoph, Mayer, Ruben, and Jacobsen, Hans-Arno
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Computer Science - Artificial Intelligence ,K.5 ,I.2.11 ,C.2.4 ,D.2.1 - Abstract
The European Union Artificial Intelligence Act mandates clear stakeholder responsibilities in developing and deploying machine learning applications to avoid substantial fines, prioritizing private and secure data processing with data remaining at its origin. Federated Learning (FL) enables the training of generative AI Models across data siloes, sharing only model parameters while improving data security. Since FL is a cooperative learning paradigm, clients and servers naturally share legal responsibility in the FL pipeline. Our work contributes to clarifying the roles of both parties, explains strategies for shifting responsibilities to the server operator, and points out open technical challenges that we must solve to improve FL's practical applicability under the EU AI Act., Comment: Accepted at the GenLaw'24 workshop in conjunction with ICML'24
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- 2024
12. Establishing a Panel Study of Refugees in Germany: First Wave Response and Panel Attrition from a Comparative Perspective
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Jannes Jacobsen and Manuel Siegert
- Abstract
This article analyzes whether response patterns in surveys differ between the general population, regular immigrants, and recent refugees. Analyses show that the address quality of refugees contacted in the first wave of a panel study is worse than that of the general population, but of a similar quality to that of other recent immigrants. Once contacted, people in refugee households are more willing than others to participate in the first wave. In subsequent waves, this pattern changes. Address quality remains relatively low, and the motivation to participate deteriorates and is worse in comparison with other populations. However, Cox regression models of individual response behaviour reveal that this is mostly a composition effect. When socio-demographic and interviewer characteristics are taken into account, refugees have a lower risk of attrition than other immigrants, but they have a similar risk as the general population. This article provides important insights for the implementation of research about recent immigrants and refugees into ongoing panel studies.
- Published
- 2024
- Full Text
- View/download PDF
13. Understanding and valuing human connections to deep-sea methane seeps off Costa Rica
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Pereira, Olívia S, Jacobsen, Mark, Carson, Richard, Cortés, Jorge, and Levin, Lisa A
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Economics ,Applied Economics ,Life on Land ,Choice modelling ,Deep sea ,Ecosystem services ,Existence value ,Methane seeps ,Environmental Science and Management ,Other Economics ,Agricultural Economics & Policy ,Ecology ,Applied economics ,Other economics - Published
- 2024
14. Airborne DNA reveals predictable spatial and seasonal dynamics of fungi.
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Abrego, Nerea, Furneaux, Brendan, Hardwick, Bess, Somervuo, Panu, Palorinne, Isabella, Aguilar-Trigueros, Carlos, Andrew, Nigel, Babiy, Ulyana, Bao, Tan, Bazzano, Gisela, Bondarchuk, Svetlana, Bonebrake, Timothy, Brennan, Georgina, Bret-Harte, Syndonia, Bässler, Claus, Cagnolo, Luciano, Cameron, Erin, Chapurlat, Elodie, Creer, Simon, DAcqui, Luigi, de Vere, Natasha, Desprez-Loustau, Marie-Laure, Dongmo, Michel, Jacobsen, Ida, Fisher, Brian, Flores de Jesus, Miguel, Gilbert, Gregory, Griffith, Gareth, Gritsuk, Anna, Gross, Andrin, Grudd, Håkan, Halme, Panu, Hanna, Rachid, Hansen, Jannik, Hansen, Lars, Hegbe, Apollon, Hill, Sarah, Hogg, Ian, Hultman, Jenni, Hyde, Kevin, Hynson, Nicole, Ivanova, Natalia, Karisto, Petteri, Kerdraon, Deirdre, Knorre, Anastasia, Krisai-Greilhuber, Irmgard, Kurhinen, Juri, Kuzmina, Masha, Lecomte, Nicolas, Lecomte, Erin, Loaiza, Viviana, Lundin, Erik, Meire, Alexander, Mešić, Armin, Miettinen, Otto, Monkhouse, Norman, Mortimer, Peter, Müller, Jörg, Nilsson, R, Nonti, Puani, Nordén, Jenni, Nordén, Björn, Norros, Veera, Paz, Claudia, Pellikka, Petri, Pereira, Danilo, Petch, Geoff, Pitkänen, Juha-Matti, Popa, Flavius, Potter, Caitlin, Purhonen, Jenna, Pätsi, Sanna, Rafiq, Abdullah, Raharinjanahary, Dimby, Rakos, Niklas, Rathnayaka, Achala, Raundrup, Katrine, Rebriev, Yury, Rikkinen, Jouko, Rogers, Hanna, Rogovsky, Andrey, Rozhkov, Yuri, Runnel, Kadri, Saarto, Annika, Savchenko, Anton, Schlegel, Markus, Schmidt, Niels, Seibold, Sebastian, Skjøth, Carsten, Stengel, Elisa, Sutyrina, Svetlana, Syvänperä, Ilkka, Tedersoo, Leho, Timm, Jebidiah, Tipton, Laura, Toju, Hirokazu, Uscka-Perzanowska, Maria, van der Bank, Michelle, van der Bank, F, and Vandenbrink, Bryan
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Air Microbiology ,Biodiversity ,DNA ,Fungal ,Fungi ,Mycorrhizae ,Phylogeny ,Seasons ,Spatio-Temporal Analysis ,Spores ,Fungal ,Temperature ,Tropical Climate ,Geographic Mapping - Abstract
Fungi are among the most diverse and ecologically important kingdoms in life. However, the distributional ranges of fungi remain largely unknown as do the ecological mechanisms that shape their distributions1,2. To provide an integrated view of the spatial and seasonal dynamics of fungi, we implemented a globally distributed standardized aerial sampling of fungal spores3. The vast majority of operational taxonomic units were detected within only one climatic zone, and the spatiotemporal patterns of species richness and community composition were mostly explained by annual mean air temperature. Tropical regions hosted the highest fungal diversity except for lichenized, ericoid mycorrhizal and ectomycorrhizal fungi, which reached their peak diversity in temperate regions. The sensitivity in climatic responses was associated with phylogenetic relatedness, suggesting that large-scale distributions of some fungal groups are partially constrained by their ancestral niche. There was a strong phylogenetic signal in seasonal sensitivity, suggesting that some groups of fungi have retained their ancestral trait of sporulating for only a short period. Overall, our results show that the hyperdiverse kingdom of fungi follows globally highly predictable spatial and temporal dynamics, with seasonality in both species richness and community composition increasing with latitude. Our study reports patterns resembling those described for other major groups of organisms, thus making a major contribution to the long-standing debate on whether organisms with a microbial lifestyle follow the global biodiversity paradigms known for macroorganisms4,5.
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- 2024
15. Ksurf: Attention Kalman Filter and Principal Component Analysis for Prediction under Highly Variable Cloud Workloads
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Dang'ana, Michael and Jacobsen, Arno
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Computer Science - Distributed, Parallel, and Cluster Computing - Abstract
Cloud platforms have become essential in rapidly deploying application systems online to serve large numbers of users. Resource estimation and workload forecasting are critical in cloud data centers. Complexity in the cloud provider environment due to varying numbers of virtual machines introduces high variability in workloads and resource usage, making resource predictions problematic using state-of-the-art models that fail to deal with nonlinear characteristics. Estimating and predicting the resource metrics of cloud systems across packet networks influenced by unknown external dynamics is a task affected by high measurement noise and variance. An ideal solution to these problems is the Kalman filter, a variance-minimizing estimator used for system state estimation and efficient low latency system state prediction. Kalman filters are optimal estimators for highly variable data with Gaussian state space characteristics such as internet workloads. This work provides a solution by making these contributions: i) it introduces and evaluates the Kalman filter-based model parameter prediction using principal component analysis and an attention mechanism for noisy cloud data, ii) evaluates the scheme on a Google Cloud benchmark comparing it to the state-of-the-art Bi-directional Grid Long Short-Term Memory network model on prediction tasks, iii) it applies these techniques to demonstrate the accuracy and stability improvements on a realtime messaging system auto-scaler in Apache Kafka. The new scheme improves prediction accuracy by $37\%$ over state-of-the-art Kalman filters in noisy signal prediction tasks. It reduces the prediction error of the neural network model by over $40\%$. It is shown to improve Apache Kafka workload-based scaling stability by $58\%$., Comment: 14 pages, 24 figures, to be submitted to EECSI conference
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- 2024
16. Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition
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Shao, Kai, Wang, Rui, Hao, Yixue, Hu, Long, Chen, Min, and Jacobsen, Hans Arno
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence - Abstract
Depression recognition based on physiological signals such as functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) has made considerable progress. However, most existing studies ignore the complementarity and semantic consistency of multimodal physiological signals under the same stimulation task in complex spatio-temporal patterns. In this paper, we introduce a multimodal physiological signals representation learning framework using Siamese architecture via multiscale contrasting for depression recognition (MRLMC). First, fNIRS and EEG are transformed into different but correlated data based on a time-domain data augmentation strategy. Then, we design a spatio-temporal contrasting module to learn the representation of fNIRS and EEG through weight-sharing multiscale spatio-temporal convolution. Furthermore, to enhance the learning of semantic representation associated with stimulation tasks, a semantic consistency contrast module is proposed, aiming to maximize the semantic similarity of fNIRS and EEG. Extensive experiments on publicly available and self-collected multimodal physiological signals datasets indicate that MRLMC outperforms the state-of-the-art models. Moreover, our proposed framework is capable of transferring to multimodal time series downstream tasks.
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- 2024
17. Should my Blockchain Learn to Drive? A Study of Hyperledger Fabric
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Chacko, Jeeta Ann, Mayer, Ruben, and Jacobsen, Hans-Arno
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Computer Science - Distributed, Parallel, and Cluster Computing ,Computer Science - Cryptography and Security - Abstract
Similar to other transaction processing frameworks, blockchain systems need to be dynamically reconfigured to adapt to varying workloads and changes in network conditions. However, achieving optimal reconfiguration is particularly challenging due to the complexity of the blockchain stack, which has diverse configurable parameters. This paper explores the concept of self-driving blockchains, which have the potential to predict workload changes and reconfigure themselves for optimal performance without human intervention. We compare and contrast our discussions with existing research on databases and highlight aspects unique to blockchains. We identify specific parameters and components in Hyperledger Fabric, a popular permissioned blockchain system, that are suitable for autonomous adaptation and offer potential solutions for the challenges involved. Further, we implement three demonstrative locally autonomous systems, each targeting a different layer of the blockchain stack, and conduct experiments to understand the feasibility of our findings. Our experiments indicate up to 11% improvement in success throughput and a 30% decrease in latency, making this a significant step towards implementing a fully autonomous blockchain system in the future.
- Published
- 2024
18. An Equivalence Between Static and Dynamic Regret Minimization
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Jacobsen, Andrew and Orabona, Francesco
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Computer Science - Machine Learning ,Mathematics - Optimization and Control ,Statistics - Machine Learning - Abstract
We study the problem of dynamic regret minimization in online convex optimization, in which the objective is to minimize the difference between the cumulative loss of an algorithm and that of an arbitrary sequence of comparators. While the literature on this topic is very rich, a unifying framework for the analysis and design of these algorithms is still missing. In this paper, \emph{we show that dynamic regret minimization is equivalent to static regret minimization in an extended decision space}. Using this simple observation, we show that there is a frontier of lower bounds trading off penalties due to the variance of the losses and penalties due to variability of the comparator sequence, and provide a framework for achieving any of the guarantees along this frontier. As a result, we prove for the first time that adapting to the squared path-length of an arbitrary sequence of comparators to achieve regret $R_{T}(u_{1},\dots,u_{T})\le O(\sqrt{T\sum_{t} \|u_{t}-u_{t+1}\|^{2}})$ is impossible. However, we prove that it is possible to adapt to a new notion of variability based on the locally-smoothed squared path-length of the comparator sequence, and provide an algorithm guaranteeing dynamic regret of the form $R_{T}(u_{1},\dots,u_{T})\le \tilde O(\sqrt{T\sum_{i}\|\bar u_{i}-\bar u_{i+1}\|^{2}})$. Up to polylogarithmic terms, the new notion of variability is never worse than the classic one involving the path-length., Comment: 26 pages
- Published
- 2024
19. Online Linear Regression in Dynamic Environments via Discounting
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Jacobsen, Andrew and Cutkosky, Ashok
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Computer Science - Machine Learning ,Statistics - Machine Learning - Abstract
We develop algorithms for online linear regression which achieve optimal static and dynamic regret guarantees \emph{even in the complete absence of prior knowledge}. We present a novel analysis showing that a discounted variant of the Vovk-Azoury-Warmuth forecaster achieves dynamic regret of the form $R_{T}(\vec{u})\le O\left(d\log(T)\vee \sqrt{dP_{T}^{\gamma}(\vec{u})T}\right)$, where $P_{T}^{\gamma}(\vec{u})$ is a measure of variability of the comparator sequence, and show that the discount factor achieving this result can be learned on-the-fly. We show that this result is optimal by providing a matching lower bound. We also extend our results to \emph{strongly-adaptive} guarantees which hold over every sub-interval $[a,b]\subseteq[1,T]$ simultaneously., Comment: ICML 2024, 38 pages
- Published
- 2024
20. Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
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Wehenkel, Antoine, Gamella, Juan L., Sener, Ozan, Behrmann, Jens, Sapiro, Guillermo, Cuturi, Marco, and Jacobsen, Jörn-Henrik
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Statistics - Machine Learning ,Computer Science - Machine Learning ,Statistics - Methodology - Abstract
Driven by steady progress in generative modeling, simulation-based inference (SBI) has enabled inference over stochastic simulators. However, recent work has demonstrated that model misspecification can harm SBI's reliability. This work introduces robust posterior estimation (ROPE), a framework that overcomes model misspecification with a small real-world calibration set of ground truth parameter measurements. We formalize the misspecification gap as the solution of an optimal transport problem between learned representations of real-world and simulated observations. Assuming the prior distribution over the parameters of interest is known and well-specified, our method offers a controllable balance between calibrated uncertainty and informative inference under all possible misspecifications of the simulator. Our empirical results on four synthetic tasks and two real-world problems demonstrate that ROPE outperforms baselines and consistently returns informative and calibrated credible intervals.
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- 2024
21. Approaching the conformal limit of quark matter with different chemical potentials
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Brown, Connor, Dexheimer, Veronica, Jacobsen, Rafael Bán, and Farias, Ricardo Luciano Sonego
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High Energy Physics - Phenomenology ,Astrophysics - High Energy Astrophysical Phenomena ,Astrophysics - Solar and Stellar Astrophysics ,High Energy Physics - Theory ,Nuclear Theory - Abstract
We study in detail the influence of different chemical potentials (baryon, charged, strange, and neutrino) on how and how fast a free gas of quarks in the zero-temperature limit reaches the conformal limit. We discuss the influence of non-zero masses, the inclusion of leptons, and different constraints, such as charge neutrality, zero-net strangeness, and fixed lepton fraction. We also investigate for the first time how the symmetry energy of the system under some of these conditions approaches the conformal limit. Finally, we briefly discuss what kind of corrections are expected from perturbative QCD as one goes away from the conformal limit., Comment: 14 pages, 5 figures
- Published
- 2024
- Full Text
- View/download PDF
22. Phonon dispersion of quantum paraelectric SrTiO3 in electric fields
- Author
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Jacobsen, Henrik, Barthkowiak, Marek, Weber, Tobias, Stuhr, Uwe, Roessli, Bertrand, Niedermayer, Christof, and Staub, Urs
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Condensed Matter - Materials Science - Abstract
Here we report on an elastic and inelastic neutron scattering study addressing the effect of electric fields on quantum paraelectric SrTiO3. Our elastic scattering results find small changes as a function of field in a superlattice reflection that sample the octahedral rotations, which is indicative of only weak coupling of octahedral rotation and electric polarization. By collecting not only the change in gap, but also of the dispersion, we can better quantify the changes in the lattice dynamics. The findings are put in context to recent field DFT calculations predicting the E-field effect on the atomic motions of the lowest lying transverse optical (soft) mode. We find hints of non-linear coupling to the acoustic mode and to the phonon with polarization perpendicular to the E-field, which shows the non-linearity in the chemical potential that is also relevant when strongly driving SrTiO3 with E-field (THz) pulses.
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- 2024
23. Variational Bayesian Optimal Experimental Design with Normalizing Flows
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Dong, Jiayuan, Jacobsen, Christian, Khalloufi, Mehdi, Akram, Maryam, Liu, Wanjiao, Duraisamy, Karthik, and Huan, Xun
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Computer Science - Machine Learning ,Computer Science - Computational Engineering, Finance, and Science ,Statistics - Computation ,Statistics - Methodology ,Statistics - Machine Learning ,62K05, 94A17, 62C10, 62F15 - Abstract
Bayesian optimal experimental design (OED) seeks experiments that maximize the expected information gain (EIG) in model parameters. Directly estimating the EIG using nested Monte Carlo is computationally expensive and requires an explicit likelihood. Variational OED (vOED), in contrast, estimates a lower bound of the EIG without likelihood evaluations by approximating the posterior distributions with variational forms, and then tightens the bound by optimizing its variational parameters. We introduce the use of normalizing flows (NFs) for representing variational distributions in vOED; we call this approach vOED-NFs. Specifically, we adopt NFs with a conditional invertible neural network architecture built from compositions of coupling layers, and enhanced with a summary network for data dimension reduction. We present Monte Carlo estimators to the lower bound along with gradient expressions to enable a gradient-based simultaneous optimization of the variational parameters and the design variables. The vOED-NFs algorithm is then validated in two benchmark problems, and demonstrated on a partial differential equation-governed application of cathodic electrophoretic deposition and an implicit likelihood case with stochastic modeling of aphid population. The findings suggest that a composition of 4--5 coupling layers is able to achieve lower EIG estimation bias, under a fixed budget of forward model runs, compared to previous approaches. The resulting NFs produce approximate posteriors that agree well with the true posteriors, able to capture non-Gaussian and multi-modal features effectively.
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- 2024
24. Electrical control of superconducting spin valves using ferromagnetic helices
- Author
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Salamone, Tancredi, Hugdal, Henning G., Amundsen, Morten, and Jacobsen, Sol H.
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Condensed Matter - Superconductivity - Abstract
The geometrical properties of a helical ferromagnet are shown theoretically to control the critical temperature of a proximity-coupled superconductor. Using the Usadel equation for diffusive spin transport, we provide self-consistent analysis of how curvature and torsion modulate the proximity effect. When the helix is attached to a piezoelectric actuator, the pitch of the helix -- and hence the superconducting transition -- can be controlled electrically.
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- 2024
25. Good Books are Complex Matters: Gauging Complexity Profiles Across Diverse Categories of Perceived Literary Quality
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Bizzoni, Yuri, Feldkamp, Pascale, Lassen, Ida Marie, Jacobsen, Mia, Thomsen, Mads Rosendahl, and Nielbo, Kristoffer
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Computer Science - Computation and Language - Abstract
In this study, we employ a classification approach to show that different categories of literary "quality" display unique linguistic profiles, leveraging a corpus that encompasses titles from the Norton Anthology, Penguin Classics series, and the Open Syllabus project, contrasted against contemporary bestsellers, Nobel prize winners and recipients of prestigious literary awards. Our analysis reveals that canonical and so called high-brow texts exhibit distinct textual features when compared to other quality categories such as bestsellers and popular titles as well as to control groups, likely responding to distinct (but not mutually exclusive) models of quality. We apply a classic machine learning approach, namely Random Forest, to distinguish quality novels from "control groups", achieving up to 77\% F1 scores in differentiating between the categories. We find that quality category tend to be easier to distinguish from control groups than from other quality categories, suggesting than literary quality features might be distinguishable but shared through quality proxies.
- Published
- 2024
26. Federated Computing -- Survey on Building Blocks, Extensions and Systems
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Schwermer, René, Mayer, Ruben, and Jacobsen, Hans-Arno
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Computer Science - Machine Learning - Abstract
In response to the increasing volume and sensitivity of data, traditional centralized computing models face challenges, such as data security breaches and regulatory hurdles. Federated Computing (FC) addresses these concerns by enabling collaborative processing without compromising individual data privacy. This is achieved through a decentralized network of devices, each retaining control over its data, while participating in collective computations. The motivation behind FC extends beyond technical considerations to encompass societal implications. As the need for responsible AI and ethical data practices intensifies, FC aligns with the principles of user empowerment and data sovereignty. FC comprises of Federated Learning (FL) and Federated Analytics (FA). FC systems became more complex over time and they currently lack a clear definition and taxonomy describing its moving pieces. Current surveys capture domain-specific FL use cases, describe individual components in an FC pipeline individually or decoupled from each other, or provide a quantitative overview of the number of published papers. This work surveys more than 150 papers to distill the underlying structure of FC systems with their basic building blocks, extensions, architecture, environment, and motivation. We capture FL and FA systems individually and point out unique difference between those two.
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- 2024
27. Critical spin chains and loop models with $U(n)$ symmetry
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Roux, Paul, Jacobsen, Jesper Lykke, Ribault, Sylvain, and Saleur, Hubert
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High Energy Physics - Theory ,Mathematical Physics - Abstract
Starting with the Ising model, statistical models with global symmetries provide fruitful approaches to interesting physical systems, for example percolation or polymers. These include the $O(n)$ model (symmetry group $O(n)$) and the Potts model (symmetry group $S_Q$). Both models make sense for $n,Q\in \mathbb{C}$ and not just $n,Q\in \mathbb{N}$, and both give rise to a conformal field theory in the critical limit. Here, we study similar models based on the unitary group $U(n)$. We focus on the two-dimensional case, where the models can be described either as gases of non-intersecting orientable loops, or as alternating spin chains. This allows us to determine their spectra either by computing a twisted torus partition function, or by studying representations of the walled Brauer algebra. In the critical limit, our models give rise to a CFT with global $U(n)$ symmetry, which exists for any $n\in\mathbb{C}$. Its spectrum is similar to those of the $O(n)$ and Potts CFTs, but a bit simpler. We conjecture that the $O(n)$ CFT is a $\mathbb{Z}_2$ orbifold of the $U(n)$ CFT, where $\mathbb{Z}_2$ acts as complex conjugation., Comment: 36 pages
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- 2024
28. Institutional Entrepreneurship in Loosely Coupled Systems: The Subject Position of MOOC Entrepreneurs and Their Interpretive Struggles in a Norwegian Context
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Inger Dagrun Langseth, Dan Yngve Jacobsen, and Halvdan Haugsbakken
- Abstract
While technological change in organizations is fast and eminent to most people, the adoption of Massive Open Online Courses, micro-credentials, and flexible and scalable online courses, appear to be comparatively slow in Higher Education in the Nordic countries. To explore this phenomenon, we completed 10 qualitative interviews at ten different higher education institutions across Norway in fall 2020. The informants were strategically selected among employees who had been involved in open platform technology, MOOC production and support for faculties. Adopting thematic analyses, we found entrepreneurs who positioned themselves in pockets of innovation with the intention to transform teaching and learning. Rather than seeing technological innovations as "more of the same", the entrepreneurs embraced the possibilities emerging in new educational practices. Inspired by "New Institutionalism," we focused on the organizational conditions for MOOC production. The entrepreneurs often entered interpretive struggles at higher organizational levels in competition with other stakeholders. Despite national initiatives and funding, many stakeholders questioned the value of MOOCs. Our study points to discrepancies in understanding the disruptive and transformative change that new technology can bring to study programs and lifelong learning. The informants also experienced insufficient support from leaders and lamented the lack of a national platform for open online access. We link these findings to embedded theories, belief systems and discourses in educational cultures and management in Higher Education.
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- 2024
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29. Visualizing ribonuclease digestion of RNA-like polymers produced by hot wet-dry cycles
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Da Silva, Laura, Eiby, Simon Holm Jacobsen, Bjerrum, Morten Jannik, Thulstrup, Peter Waaben, Deamer, David, and Hassenkam, Tue
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Biochemistry and Cell Biology ,Biological Sciences ,Genetics ,RNA ,Ribonuclease ,Pancreatic ,Uridine Monophosphate ,Microscopy ,Atomic Force ,Hot Temperature ,Polymers ,Adenosine Monophosphate ,Hydrolysis ,Polymerization ,RNA world hypothesis ,RNA synthesis ,Hydrothermal fields ,'-5 ' phosphodiester bonds ,3′-5′ phosphodiester bonds ,Medicinal and Biomolecular Chemistry ,Medical Biochemistry and Metabolomics ,Biochemistry & Molecular Biology ,Biochemistry and cell biology ,Medicinal and biomolecular chemistry - Abstract
Polymerization of nucleotides under prebiotic conditions simulating the early Earth has been extensively studied. Several independent methods have been used to verify that RNA-like polymers can be produced by hot wet-dry cycling of nucleotides. However, it has not been shown that these RNA-like polymers are similar to biological RNA with 3'-5' phosphodiester bonds. In the results described here, RNA-like polymers were generated from 5'-monophosphate nucleosides AMP and UMP. To confirm that the polymers resemble biological RNA, ribonuclease A should catalyze hydrolysis of the 3'-5' phosphodiester bonds between pyrimidine nucleotides to each other or to purine nucleotides, but not purine-purine nucleotide bonds. Here we show AFM images of specific polymers produced by hot wet-dry cycling of AMP, UMP and AMP/UMP (1:1) solutions on mica surfaces, before and after exposure to ribonuclease A. AMP polymers were unaffected by ribonuclease A but UMP polymers disappeared. This indicates that a major fraction of the bonds in the UMP polymers is indeed 3'-5' phosphodiester bonds. Some of the polymers generated from the AMP/UMP mixture also showed clear signs of cleavage. Because ribonuclease A recognizes the ester bonds in the polymers, we show for the first time that these prebiotically produced polymers are in fact similar to biological RNA but are likely to be linked by a mixture of 3'-5' and 2'-5' phosphodiester bonds.
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- 2024
30. [Not Available].
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Van Asbroeck, Stephanie, Köhler, Sebastian, van Boxtel, Martin, Lipnicki, Darren, Crawford, John, Castro-Costa, Erico, Lima-Costa, Maria, Blay, Sergio, Shifu, Xiao, Wang, Tao, Yue, Ling, Lipton, Richard, Katz, Mindy, Derby, Carol, Guerchet, Maëlenn, Preux, Pierre-Marie, Mbelesso, Pascal, Norton, Joanna, Ritchie, Karen, Skoog, Ingmar, Najar, Jenna, Sterner, Therese, Scarmeas, Nikolaos, Yannakoulia, Mary, Dardiotis, Themis, Rolandi, Elena, Davin, Annalisa, Rossi, Michele, Gureje, Oye, Ojagbemi, Akin, Bello, Toyin, Kim, Ki, Han, Ji, Oh, Dae, Trompet, Stella, Gussekloo, Jacobijn, Riedel-Heller, Steffi, Röhr, Susanne, Pabst, Alexander, Shahar, Suzana, Rivan, Nurul, Singh, Devinder, Jacobsen, Erin, Ganguli, Mary, Hughes, Tiffany, Haan, Mary, Aiello, Allison, Ding, Ding, Zhao, Qianhua, Xiao, Zhenxu, Narazaki, Kenji, Chen, Tao, Chen, Sanmei, Ng, Tze, Gwee, Xinyi, Gao, Qi, Brodaty, Henry, Trollor, Julian, Kochan, Nicole, Lobo, Antonio, Santabárbara, Javier, Gracia-Garcia, Patricia, Sachdev, Perminder, and Deckers, Kay
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age ,dementia ,dementia risk reduction ,education ,effect modification ,ethnicity ,individual participant data meta‐analysis ,interaction ,lifestyle ,primary prevention ,region ,risk factor ,risk personalization ,sex ,socioeconomic ,Humans ,Dementia ,Life Style ,Male ,Female ,Risk Factors ,Aged ,Prospective Studies ,Incidence - Abstract
INTRODUCTION: The LIfestyle for BRAin Health (LIBRA) index yields a dementia risk score based on modifiable lifestyle factors and is validated in Western samples. We investigated whether the association between LIBRA scores and incident dementia is moderated by geographical location or sociodemographic characteristics. METHODS: We combined data from 21 prospective cohorts across six continents (N = 31,680) and conducted cohort-specific Cox proportional hazard regression analyses in a two-step individual participant data meta-analysis. RESULTS: A one-standard-deviation increase in LIBRA score was associated with a 21% higher risk for dementia. The association was stronger for Asian cohorts compared to European cohorts, and for individuals aged ≤75 years (vs older), though only within the first 5 years of follow-up. No interactions with sex, education, or socioeconomic position were observed. DISCUSSION: Modifiable risk and protective factors appear relevant for dementia risk reduction across diverse geographical and sociodemographic groups. HIGHLIGHTS: A two-step individual participant data meta-analysis was conducted. This was done at a global scale using data from 21 ethno-regionally diverse cohorts. The association between a modifiable dementia risk score and dementia was examined. The association was modified by geographical region and age at baseline. Yet, modifiable dementia risk and protective factors appear relevant in all investigated groups and regions.
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- 2024
31. Global Spore Sampling Project: A global, standardized dataset of airborne fungal DNA.
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Ovaskainen, Otso, Abrego, Nerea, Furneaux, Brendan, Hardwick, Bess, Somervuo, Panu, Palorinne, Isabella, Andrew, Nigel, Babiy, Ulyana, Bao, Tan, Bazzano, Gisela, Bondarchuk, Svetlana, Bonebrake, Timothy, Brennan, Georgina, Bret-Harte, Syndonia, Bässler, Claus, Cagnolo, Luciano, Cameron, Erin, Chapurlat, Elodie, Creer, Simon, DAcqui, Luigi, de Vere, Natasha, Desprez-Loustau, Marie-Laure, Dongmo, Michel, Dyrholm Jacobsen, Ida, Fisher, Brian, Flores de Jesus, Miguel, Griffith, Gareth, Gritsuk, Anna, Gross, Andrin, Grudd, Håkan, Halme, Panu, Hanna, Rachid, Hansen, Jannik, Hansen, Lars, Hegbe, Apollon, Hill, Sarah, Hogg, Ian, Hultman, Jenni, Hyde, Kevin, Hynson, Nicole, Ivanova, Natalia, Karisto, Petteri, Kerdraon, Deirdre, Knorre, Anastasia, Krisai-Greilhuber, Irmgard, Kurhinen, Juri, Kuzmina, Masha, Lecomte, Nicolas, Lecomte, Erin, Loaiza, Viviana, Lundin, Erik, Meire, Alexander, Mešić, Armin, Miettinen, Otto, Monkhause, Norman, Mortimer, Peter, Müller, Jörg, Nilsson, R, Nonti, Puani, Nordén, Jenni, Nordén, Björn, Paz, Claudia, Pellikka, Petri, Pereira, Danilo, Petch, Geoff, Pitkänen, Juha-Matti, Popa, Flavius, Potter, Caitlin, Purhonen, Jenna, Pätsi, Sanna, Rafiq, Abdullah, Raharinjanahary, Dimby, Rakos, Niklas, Rathnayaka, Achala, Raundrup, Katrine, Rebriev, Yury, Rikkinen, Jouko, Rogers, Hanna, Rogovsky, Andrey, Rozhkov, Yuri, Runnel, Kadri, Saarto, Annika, Savchenko, Anton, Schlegel, Markus, Schmidt, Niels, Seibold, Sebastian, Skjøth, Carsten, Stengel, Elisa, Sutyrina, Svetlana, Syvänperä, Ilkka, Tedersoo, Leho, Timm, Jebidiah, Tipton, Laura, Toju, Hirokazu, Uscka-Perzanowska, Maria, van der Bank, Michelle, Herman van der Bank, F, Vandenbrink, Bryan, Ventura, Stefano, and Vignisson, Solvi
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Air Microbiology ,Spores ,Fungal ,DNA ,Fungal ,Fungi ,Biodiversity - Abstract
Novel methods for sampling and characterizing biodiversity hold great promise for re-evaluating patterns of life across the planet. The sampling of airborne spores with a cyclone sampler, and the sequencing of their DNA, have been suggested as an efficient and well-calibrated tool for surveying fungal diversity across various environments. Here we present data originating from the Global Spore Sampling Project, comprising 2,768 samples collected during two years at 47 outdoor locations across the world. Each sample represents fungal DNA extracted from 24 m3 of air. We applied a conservative bioinformatics pipeline that filtered out sequences that did not show strong evidence of representing a fungal species. The pipeline yielded 27,954 species-level operational taxonomic units (OTUs). Each OTU is accompanied by a probabilistic taxonomic classification, validated through comparison with expert evaluations. To examine the potential of the data for ecological analyses, we partitioned the variation in species distributions into spatial and seasonal components, showing a strong effect of the annual mean temperature on community composition.
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- 2024
32. Anti-KIF20B autoantibodies are associated with cranial neuropathy in systemic lupus erythematosus.
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Krustev, Eugene, Hanly, John, Chin, Ricky, Buhler, Katherine, Urowitz, Murray, Gordon, Caroline, Bae, Sang-Cheol, Romero-Diaz, Juanita, Sánchez-Guerrero, Jorge, Bernatsky, Sasha, Wallace, Daniel, Isenberg, David, Rahman, Anisur, Merrill, Joan, Fortin, Paul, Gladman, Dafna, Bruce, Ian, Petri, Michelle, Ginzler, Ellen, Dooley, Mary, Ramsey-Goldman, Rosalind, Manzi, Susan, Jönsen, Andreas, Alarcón, Graciela, van Vollenhoven, Ronald, Aranow, Cynthia, Mackay, Meggan, Ruiz-Irastorza, Guillermo, Lim, Sam, Inanc, Murat, Kalunian, Kenneth, Jacobsen, Søren, Peschken, Christine, Kamen, Diane, Askenase, Anca, Buyon, Jill, Fritzler, Marvin, Clarke, Ann, and Choi, May
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Antibodies ,Autoantibodies ,Autoimmune Diseases ,Systemic Lupus Erythematosus ,Female ,Humans ,Male ,Autoantibodies ,Biomarkers ,Kinesins ,Lupus Erythematosus ,Systemic - Abstract
BACKGROUND: Cranial neuropathies (CN) are a rare neuropsychiatric SLE (NPSLE) manifestation. Previous studies reported that antibodies to the kinesin family member 20B (KIF20B) (anti-KIF20B) protein were associated with idiopathic ataxia and CN. We assessed anti-KIF20B as a potential biomarker for NPSLE in an international SLE inception cohort. METHODS: Individuals fulfilling the revised 1997 American College of Rheumatology (ACR) SLE classification criteria were enrolled from 31 centres from 1999 to 2011 and followed annually in the Systemic Lupus Erythematosus International Collaborating Clinics inception cohort. Anti-KIF20B testing was performed on baseline (within 15 months of diagnosis or first annual visit) samples using an addressable laser bead immunoassay. Logistic regression (penalised maximum likelihood and adjusting for confounding variables) examined the association between anti-KIF20B and NPSLE manifestations (1999 ACR case definitions), including CN, occurring over the first 5 years of follow-up. RESULTS: Of the 1827 enrolled cohort members, baseline serum and 5 years of follow-up data were available on 795 patients who were included in this study: 29.8% were anti-KIF20B-positive, 88.7% female, and 52.1% White. The frequency of anti-KIF20B positivity differed only for those with CN (n=10) versus without CN (n=785) (70.0% vs 29.3%; OR 5.2, 95% CI 1.4, 18.5). Compared with patients without CN, patients with CN were more likely to fulfil the ACR haematological (90.0% vs 66.1%; difference 23.9%, 95% CI 5.0%, 42.8%) and ANA (100% vs 95.7%; difference 4.3%, 95% CI 2.9%, 5.8%) criteria. In the multivariate analysis adjusting for age at baseline, female, White race and ethnicity, and ACR haematological and ANA criteria, anti-KIF20B positivity remained associated with CN (OR 5.2, 95% CI 1.4, 19.1). CONCLUSION: Anti-KIF20B is a potential biomarker for SLE-related CN. Further studies are needed to examine how autoantibodies against KIF20B, which is variably expressed in a variety of neurological cells, contribute to disease pathogenesis.
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- 2024
33. Emerging Jordan blocks in the two-dimensional Potts and loop models at generic $Q$
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Liu, Lawrence, Jacobsen, Jesper Lykke, and Saleur, Hubert
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Mathematical Physics ,Condensed Matter - Statistical Mechanics ,High Energy Physics - Theory - Abstract
It was recently suggested -- based on general self-consistency arguments as well as results from the bootstrap (arXiv:2005.07708, arXiv:2007.11539, arXiv:2007.04190) -- that the CFT describing the $Q$-state Potts model is logarithmic for generic values of $Q$, with rank-two Jordan blocks for $L_0$ and ${\mkern 1.5mu\overline{\mkern-1.5mu L\mkern-1.5mu}\mkern 1.5mu}_0$ in many sectors of the theory. This is despite the well-known fact that the lattice transfer matrix (or Hamiltonian) is diagonalizable in (arbitrary) finite size. While the emergence of Jordan blocks only in the limit $L\to\infty$ is perfectly possible conceptually, diagonalizability in finite size makes the measurement of logarithmic couplings (whose values are analytically predicted in arXiv:2007.11539, arXiv:2007.04190) very challenging. This problem is solved in the present paper (which can be considered a companion to arXiv:2007.11539), and the conjectured logarithmic structure of the CFT confirmed in detail by the study of the lattice model and associated "emerging Jordan blocks.", Comment: arXiv admin note: substantial text overlap with arXiv:2403.09881
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- 2024
34. Generation of Spatially Coherent Light at Extreme Ultraviolet Wavelengths
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Bartels, Randy A., Paul, Ariel, Green, Hans, Kapteyn, Henry C., Murnane, Margaret M., Backus, Sterling, Christov, Ivan P., Liu, Yanwei, Attwood, David, and Jacobsen, Chris
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Physics - Optics ,Physics - Atomic Physics ,Quantum Physics - Abstract
We present spatial coherence measurements of extreme-ultraviolet light generated using the process of high-harmonic upconversion of a femtosecond laser. Using a phase-matched hollow-fiber geometry, the generated beam is found to exhibit essentially full spatial coherence. The coherence of this laser-like EUV source is demonstrated by recording Gabor holograms of small objects. This work demonstrates the capability to do EUV holography using a tabletop experimental setup. Such an EUV source, with low divergence and high spatial coherence, can be used for experiments such as high-precision metrology, inspection of optical components for EUV lithography (1), and for microscopy and holography (2) with nanometer resolution. Furthermore, the short time duration of the EUV radiation (a few femtoseconds) will enable EUV microscopy and holography to be performed with ultrahigh time resolution., Comment: 16 pages, 4 figures
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- 2024
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35. Spin-orbit proximity in MoS$_2$/bilayer graphene heterostructures
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Masseroni, M., Gull, M., Panigrahi, A., Jacobsen, N., Fischer, F., Tong, C., Gerber, J. D., Niese, M., Taniguchi, T., Watanabe, K., Levitov, L., Ihn, T., Ensslin, K., and Duprez, H.
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Condensed Matter - Mesoscale and Nanoscale Physics - Abstract
Van der Waals heterostructures provide a versatile platform for tailoring electronic properties through the integration of two-dimensional materials. Among these combinations, the interaction between bilayer graphene and transition metal dichalcogenides (TMDs) stands out due to its potential for inducing spin-orbit coupling (SOC) in graphene. Future devices concepts require the understanding the precise nature of SOC in TMD/bilayer graphene heterostructures and its influence on electronic transport phenomena. Here, we experimentally confirm the presence of two distinct types of SOC, Ising (1.55 meV) and Rashba (2.5 meV), in bilayer graphene when interfaced with molybdenum disulphide, recognized as one of the most stable TMDs. Furthermore, we reveal a non-monotonic trend in conductivity with respect to the electric displacement field at charge neutrality. This phenomenon is ascribed to the existence of single-particle gaps induced by the Ising SOC, which can be closed by a critical displacement field. Remarkably, our findings also unveil sharp peaks in the magnetoconductivity around the critical displacement field, challenging existing theoretical models.
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- 2024
36. Attacking with Something That Does Not Exist: 'Proof of Non-Existence' Can Exhaust DNS Resolver CPU
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Gruza, Olivia, Heftrig, Elias, Jacobsen, Oliver, Schulmann, Haya, Vogel, Niklas, and Waidner, Michael
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Computer Science - Cryptography and Security - Abstract
NSEC3 is a proof of non-existence in DNSSEC, which provides an authenticated assertion that a queried resource does not exist in the target domain. NSEC3 consists of alphabetically sorted hashed names before and after the queried hostname. To make dictionary attacks harder, the hash function can be applied in multiple iterations, which however also increases the load on the DNS resolver during the computation of the SHA-1 hashes in NSEC3 records. Concerns about the load created by the computation of NSEC3 records on the DNS resolvers were already considered in the NSEC3 specifications RFC5155 and RFC9276. In February 2024, the potential of NSEC3 to exhaust DNS resolvers' resources was assigned a CVE-2023-50868, confirming that extra iterations of NSEC3 created substantial load. However, there is no published evaluation of the attack and the impact of the attack on the resolvers was not clarified. In this work we perform the first evaluation of the NSEC3-encloser attack against DNS resolver implementations and find that the NSEC3-encloser attack can still create a 72x increase in CPU instruction count, despite the victim resolver following RFC5155 recommendations in limiting hash iteration counts. The impact of the attack varies across the different DNS resolvers, but we show that with a sufficient volume of DNS packets the attack can increase CPU load and cause packet loss. We find that at a rate of 150 malicious NSEC3 records per second, depending on the DNS implementation, the loss rate of benign DNS requests varies between 2.7% and 30%. We provide a detailed description and implementation of the NSEC3-encloser attack. We also develop the first analysis how each NSEC3 parameter impacts the load inflicted on the victim resolver during NSEC3-encloser attack., Comment: 13 pages, 7 figures for the associated zonefile generator implementation, see https://github.com/Goethe-Universitat-cybersecurity/NSEC3-Encloser-Attack submitted to USENIX WOOT '24
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- 2024
37. Comparative Analysis of Sub-band Allocation Algorithms in In-body Sub-networks Supporting XR Applications
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Bagherinejad, Saeed, Jacobsen, Thomas, Pratas, Nuno K., and Adeogun, Ramoni O.
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Computer Science - Information Theory ,Electrical Engineering and Systems Science - Signal Processing - Abstract
In-body subnetworks (IBS) are envisioned to support reliable wireless connectivity for emerging applications including extended reality (XR) in the human body. As the deployment of in-body sub-networks is uncontrollable by nature, the dynamic radio resource allocation scheme in place becomes of the uttermost importance for the performance of the in-body sub-networks. This paper provides a comparative study on the performance of the state-of-the-art interference-aware sub-band allocation algorithms in in-body sub-networks supporting the XR applications. The study identified suitable models for characterizing in-body sub-networks which are used in a snapshot-based simulation framework to perform a comprehensive evaluation of the performance of state-of-art sub-band allocation algorithms, including greedy selection, sequential greedy selection (SG), centralized graph coloring (CGC), and sequential iterative sub-band allocation (SISA). The study shows that for XR requirements, the SISA and SG algorithms can support IBS densities up to 75% higher than CGC., Comment: Accepted for IEEE WCNC 2024
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- 2024
38. Hydrodynamics of electron-hole fluid photogenerated in a mesoscopic two-dimensional channel
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Patricio, M. A. T., Jacobsen, G. M., Teodoro, M. D., Gusev, G. M., Bakarov, A. K., and Pusep, Yu. A.
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Condensed Matter - Mesoscale and Nanoscale Physics - Abstract
The dynamics of the diffusion flow of holes photoinjected into a mesoscopic GaAs channel of variable width, where they, together with background electrons, form a hydrodynamic electron-hole fluid, is studied using time-resolved microphotoluminescence. It is found that the rate of recombination of photoinjected holes, which is proportional to the rate of their flow, decreases when holes pass through the expanded sections of the channel. In fact, this is the Venturi effect, which consists in a decrease in the velocity of the fluid in the expanded sections of the pipe. Moreover, a non-uniform diffusion velocity profile is observed, similar to the parabolic Hagen-Poiseuille velocity profile, which indicates a viscous hydrodynamic flow. It is shown that in argeement with a theory, the magnetic field strongly suppresses the viscosity of the electron-hole fluid. Additional evidence of the viscous nature of the studied electron-hole fluid is the observed increase in the recombination rate with increasing temperature, which is similar to the decrease in the electrical resistance of viscous electrons with temperature., Comment: 7 pages, 4 figures
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- 2024
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- View/download PDF
39. Lattice realization of complex CFTs: Two-dimensional Potts model with $Q>4$ states
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Jacobsen, Jesper Lykke and Wiese, Kay Joerg
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High Energy Physics - Theory ,Condensed Matter - Statistical Mechanics ,Mathematical Physics - Abstract
The two-dimensional $Q$-state Potts model with real couplings has a first-order transition for $Q>4$. We study a loop-model realization in which $Q$ is a continuous parameter. This model allows for the collision of a critical and a tricritical fixed point at $Q=4$, which then emerge as complex conformally invariant theories at $Q>4$, or even complex $Q$, for suitable complex coupling constants. All critical exponents can be obtained as analytic continuation of known exact results for $Q \le 4$. We verify this scenario in detail for $Q=5$ using transfer-matrix computations., Comment: 5 pages, 6 figures
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- 2024
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40. A geometric model for semilinear locally gentle algebras
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Banaian, Esther, Bennett-Tennenhaus, Raphael, Jacobsen, Karin M., and Wright, Kayla
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Mathematics - Representation Theory ,Primary 16G20, Secondary 05E10, 05C10, 16D90 - Abstract
We consider certain generalizations of gentle algebras that we call semilinear locally gentle algebras. These rings are examples of semilinear clannish algebras as introduced by the second author and Crawley-Boevey. We generalise the notion of a nodal algebra from work of Burban and Drozd and prove that semilinear gentle algebras are nodal by adapting a theorem of Zembyk. We also provide a geometric realization of Zembyk's proof, which involves cutting the surface into simpler pieces in order to endow our locally gentle algebra with a semilinear structure. We then consider this surface glued back together, with the seams in place, and use it to give a geometric model for the finite-dimensional modules over the semilinear locally gentle algebra., Comment: 36 pages, comments welcome
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- 2024
41. Federated Learning Priorities Under the European Union Artificial Intelligence Act
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Woisetschläger, Herbert, Erben, Alexander, Marino, Bill, Wang, Shiqiang, Lane, Nicholas D., Mayer, Ruben, and Jacobsen, Hans-Arno
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computers and Society ,Computer Science - Distributed, Parallel, and Cluster Computing ,I.2 ,I.2.11 ,K.5 - Abstract
The age of AI regulation is upon us, with the European Union Artificial Intelligence Act (AI Act) leading the way. Our key inquiry is how this will affect Federated Learning (FL), whose starting point of prioritizing data privacy while performing ML fundamentally differs from that of centralized learning. We believe the AI Act and future regulations could be the missing catalyst that pushes FL toward mainstream adoption. However, this can only occur if the FL community reprioritizes its research focus. In our position paper, we perform a first-of-its-kind interdisciplinary analysis (legal and ML) of the impact the AI Act may have on FL and make a series of observations supporting our primary position through quantitative and qualitative analysis. We explore data governance issues and the concern for privacy. We establish new challenges regarding performance and energy efficiency within lifecycle monitoring. Taken together, our analysis suggests there is a sizable opportunity for FL to become a crucial component of AI Act-compliant ML systems and for the new regulation to drive the adoption of FL techniques in general. Most noteworthy are the opportunities to defend against data bias and enhance private and secure computation
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- 2024
42. Choosing a Classical Planner with Graph Neural Networks
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Vatter, Jana, Mayer, Ruben, Jacobsen, Hans-Arno, Samulowitz, Horst, and Katz, Michael
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Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
Online planner selection is the task of choosing a solver out of a predefined set for a given planning problem. As planning is computationally hard, the performance of solvers varies greatly on planning problems. Thus, the ability to predict their performance on a given problem is of great importance. While a variety of learning methods have been employed, for classical cost-optimal planning the prevailing approach uses Graph Neural Networks (GNNs). In this work, we continue the line of work on using GNNs for online planner selection. We perform a thorough investigation of the impact of the chosen GNN model, graph representation and node features, as well as prediction task. Going further, we propose using the graph representation obtained by a GNN as an input to the Extreme Gradient Boosting (XGBoost) model, resulting in a more resource-efficient yet accurate approach. We show the effectiveness of a variety of GNN-based online planner selection methods, opening up new exciting avenues for research on online planner selection.
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- 2024
43. Chemical Classification of Spherules Recovered From The Pacific Ocean Site of The CNEOS 2014-01-08 (IM1) Bolide
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Loeb, A., Jacobsen, S. B., Tagle, R., Adamson, T., Bergstrom, S., Cloete, R., Cohen, S., Domine, Laura, Fu, H., Hoskinson, C., Hyung, E., Kelly, M., Lard, E., Laukien, F., Lem, J., McCallum, R., Millsap, R., Parendo, C., Pataev, M. I., Peddeti, C., Pugh, J., Samuha, S., Sasselov, D. D., Schlereth, M., Siler, J., Siraj, A., Smith, P. M., Taylor, J., Weed, R., Wright, A., and Wynn, J.
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Astrophysics - Earth and Planetary Astrophysics - Abstract
We have conducted an extensive towed-magnetic-sled survey during the period of June 14-28, 2023, over the seafloor about 85 km north of Manus Island, Papua New Guinea, centered around the calculated path of the bolide CNEOS 2014-01-08 (IM1). We found about 850 spherules of diameter 0.1-1.3 millimeters in our samples. The samples were analyzed by micro-XRF, Electron Probe Microanalyzer and ICP Mass spectrometry. Here we report major and trace element compositions of the samples and classify spherules based on that analysis. Spherules comprising 22% of the collection, appear to all reflect planetary igneous differentiation and are all different from previously described spherules. A subset of the differentiated-spherules show an excess of Be, La and U, by up to three orders of magnitude relative to the solar system standard of CI chondrites. Detailed mass spectrometry of 12 of these "BeLaU"-type spherules, the population of which may constitute up to ~10% of our entire collected sample, suggests that they are derived from material formed by planetary igneous fractionation. Their chemical composition is unlike any known solar system material. The "BeLaU"-type spherules reflect a highly differentiated, extremely evolved composition of an unknown source., Comment: Accepted for publication in Chemical Geology
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- 2024
44. A Survey on Efficient Federated Learning Methods for Foundation Model Training
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Woisetschläger, Herbert, Isenko, Alexander, Wang, Shiqiang, Mayer, Ruben, and Jacobsen, Hans-Arno
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Distributed, Parallel, and Cluster Computing ,I.2.11 ,C.2 - Abstract
Federated Learning (FL) has become an established technique to facilitate privacy-preserving collaborative training across a multitude of clients. However, new approaches to FL often discuss their contributions involving small deep-learning models only and focus on training full models on clients. In the wake of Foundation Models (FM), the reality is different for many deep learning applications. Typically, FMs have already been pre-trained across a wide variety of tasks and can be fine-tuned to specific downstream tasks over significantly smaller datasets than required for full model training. However, access to such datasets is often challenging. By its design, FL can help to open data silos. With this survey, we introduce a novel taxonomy focused on computational and communication efficiency, the vital elements to make use of FMs in FL systems. We discuss the benefits and drawbacks of parameter-efficient fine-tuning (PEFT) for FL applications, elaborate on the readiness of FL frameworks to work with FMs, and provide future research opportunities on how to evaluate generative models in FL as well as the interplay of privacy and PEFT., Comment: Accepted for publication at IJCAI 2024. Please cite the published paper via https://doi.org/10.24963/ijcai.2024/919
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- 2024
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45. Dichroic cavity mode splitting and lifetimes from interactions with a ferromagnetic metal
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Hugdal, Henning G., Høydalsvik, Eirik Jaccheri, and Jacobsen, Sol H.
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Condensed Matter - Mesoscale and Nanoscale Physics ,Quantum Physics - Abstract
We study the effect of ferromagnetic metals (FM) on the circularly polarized modes of an electromagnetic cavity and show that broken time-reversal symmetry leads to a dichroic response of the cavity modes. With one spin-split band, the Zeeman coupling between the FM electrons and cavity modes leads to an anticrossing for mode frequencies comparable to the spin splitting. However, this is only the case for one of the circularly polarized modes, while the other is unaffected by the FM, allowing for the determination of the spin-splitting of the FM using polarization-dependent transmission experiments. Moreover, we show that for two spin-split bands, also the lifetimes of the cavity modes display a polarization-dependent response. The change in photon lifetimes can be understood as a suppression due to level attraction with a continuum of Stoner modes with the same wavevector. The reduced lifetime of modes of only one polarization could potentially be used to engineer and control circularly polarized cavities., Comment: 5 pages, 3 figures
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- 2024
46. The Appalachian Region: A Data Overview from the 2017-2021 American Community Survey. Chartbook
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Appalachian Regional Commission (ARC), Population Reference Bureau (PRB), Pollard, Kelvin, Srygley, Sara, and Jacobsen, Linda A.
- Abstract
"The Appalachian Region: A Data Overview from the 2017-2021 American Community Survey," also known as "The Chartbook," draws from the most recent American Community Survey and comparable Census Population Estimates. The report contains over 300,000 data points about Appalachia's economy, income, employment, education, and other important indicators--all presented at regional, subregional, state, and county levels. Though that data was collected before, and during the initial ten months of, the COVID-19 pandemic, they provide a critical benchmark for comparison when more pandemic and post-pandemic information becomes available. [For the 2016-2020 Chartbook, see ED625962.]
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- 2023
47. Disconnected Connections of Learning Beyond Formal Schooling Through Human–Computer–Human Interactions
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Prestridge, Sarah, Tan, Seng Chee, Jacobsen, Michele, Hoppe, H. Ulrich, Angeli, Charoula, Milrad, Marcelo, Pangeni, Shesha Kanta, Kovatcheva, Eugenia, Kafyulilo, Ayoub, Flanagan, Brendan, and Khaddage, Ferial
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- 2024
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48. Development of a novel oncolytic adenovirus controlled by CDX2 promoter for esophageal adenocarcinoma therapy
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Nakamura, Naohiko, Shinoda, Shuhei, Sato-Dahlman, Mizuho, Roach, Brett, Jacobsen, Kari, and Yamamoto, Masato
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- 2024
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49. Duvelisib plus romidepsin in relapsed/refractory T cell lymphomas: a phase 1b/2a trial
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Horwitz, Steven M., Nirmal, Ajit J., Rahman, Jahan, Xu, Ran, Drill, Esther, Galasso, Natasha, Ganesan, Nivetha, Davey, Theresa, Hancock, Helen, Perez, Leslie, Maccaro, Catherine, Bahgat, Alexandra, Marzouk, Evan, Cathcart, Elizabeth, Moskowitz, Alison, Noy, Ariela, Kumar, Anita, Jacobsen, Eric, Fisher, David C., Mehta-Shah, Neha, Kim, Youn H., Khodadoust, Michael, Kotlov, Nikita, Nikitina, Anastasia, Kudryashova, Olga, Zubareva, Valeria, Zornikova, Ksenia, Shin, Nara, Sorokina, Maria, Degryse, Sandrine, Postovalova, Ekaterina, Bagaev, Aleksander, Hosszu, Kinga, McAvoy, Devin, Boelens, Jaap J., Wu, Wenchao, Ciantra, Zoe, Appelt, Jackson W., Trevisani, Christopher, Amaka, Sam, Weinstock, David M., and Vardhana, Santosha A.
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- 2024
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50. PAX8 expression in cancerous and non-neoplastic tissue: a tissue microarray study on more than 17,000 tumors from 149 different tumor entities
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Gorbokon, Natalia, Baltruschat, Sarah, Lennartz, Maximilian, Luebke, Andreas M., Höflmayer, Doris, Kluth, Martina, Hube-Magg, Claudia, Hinsch, Andrea, Fraune, Christoph, Lebok, Patrick, Bernreuther, Christian, Sauter, Guido, Marx, Andreas H., Simon, Ronald, Krech, Till, Clauditz, Till S., Jacobsen, Frank, Burandt, Eike, Steurer, Stefan, and Minner, Sarah
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- 2024
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