Tootfinder

Initial simulation of Samtec ARC6 connector launch. No ground plane cutout so the diffpair impedance drops to about 65Ω at the connector so far.
That will have to change, of course, but I wanted a baseline for comparison.

A new paper projecting Joshua tree habitat under future climate based on incredibly high-resolution distribution data, from Joshua Tree Genome Project collaborators at USGS. They estimate up to 80% loss of suitable habitat by 2100 under the worst-case climate scenario.
#JoshuaTree #science

Multiple Object Tracking in Video SAR: A Benchmark and Tracking Baseline
Haoxiang Chen, Wei Zhao, Rufei Zhang, Nannan Li, Dongjin Li
https://arxiv.org/abs/2506.12105

Multiple Object Tracking in Video SAR: A Benchmark and Tracking Baseline
In the context of multi-object tracking using video synthetic aperture radar (Video SAR), Doppler shifts induced by target motion result in artifacts that are easily mistaken for shadows caused by static occlusions. Moreover, appearance changes of the target caused by Doppler mismatch may lead to association failures and disrupt trajectory continuity. A major limitation in this field is the lack of public benchmark datasets for standardized algorithm evaluation. To address the above challenges,…

VLBA astrometry of PSRs B0329 54 and B1133 16: Improved pulsar distances and comparison of global ionospheric models
Ashish Kumar, Adam T. Deller, Pankaj Jain, Javier Mold\'on
https://arxiv.org/abs/2506.14368

VLBA astrometry of PSRs B0329+54 and B1133+16: Improved pulsar distances and comparison of global ionospheric models
Very long baseline interferometry (VLBI) astrometry is used to determine the three-dimensional position and proper motion of astronomical objects. A typical VLBI astrometric campaign generally includes around ten observations, making it challenging to characterise systematic uncertainties. Our study on two bright pulsars, B0329+54 and B1133+16, involves analysis of broadband Very Long Baseline Array (VLBA) data over $\sim30$ epochs (spanning approximately $3.5\, {\rm years}$). This extended dat…

FormGym: Doing Paperwork with Agents
Matthew Toles, Rattandeep Singh, Isaac Song Zhou Yu
https://arxiv.org/abs/2506.14079 https://arx…

FormGym: Doing Paperwork with Agents
Completing paperwork is a challenging and time-consuming problem. Form filling is especially challenging in the pure-image domain without access to OCR, typeset PDF text, or a DOM. For computer agents, it requires multiple abilities, including multi-modal understanding, information retrieval, and tool-use. We present a novel form-filling benchmark consisting of 432 fields spread across 55 documents and 3 tasks, requiring knowledge of 236 features per user. We find that baseline VLAs achieve les…

Factor-Graph-Based Passive Acoustic Navigation for Decentralized Cooperative Localization Using Bearing Elevation Depth Difference
Kalliyan Velasco, Timothy W. McLain, Joshua G. Mangelson
https://arxiv.org/abs/2506.14690

Factor-Graph-Based Passive Acoustic Navigation for Decentralized Cooperative Localization Using Bearing Elevation Depth Difference
Accurate and scalable underwater multi-agent localization remains a critical challenge due to the constraints of underwater communication. In this work, we propose a multi-agent localization framework using a factor-graph representation that incorporates bearing, elevation, and depth difference (BEDD). Our method leverages inverted ultra-short baseline (inverted-USBL) derived azimuth and elevation measurements from incoming acoustic signals and relative depth measurements to enable cooperative …

SplashNet: Split-and-Share Encoders for Accurate and Efficient Typing with Surface Electromyography
Nima Hadidi, Jason Chan, Ebrahim Feghhi, Jonathan Kao
https://arxiv.org/abs/2506.12356

SplashNet: Split-and-Share Encoders for Accurate and Efficient Typing with Surface Electromyography
Surface electromyography (sEMG) at the wrists could enable natural, keyboard-free text entry, yet the state-of-the-art emg2qwerty baseline still misrecognizes $51.8\%$ of characters in the zero-shot setting on unseen users and $7.0\%$ after user-specific fine-tuning. We trace many of these errors to mismatched cross-user signal statistics, fragile reliance on high-order feature dependencies, and the absence of architectural inductive biases aligned with the bilateral nature of typing. To addres…

What a baseline! #totp

Leveraging Transfer Learning and User-Specific Updates for Rapid Training of BCI Decoders
Ziheng Chen, Po T. Wang, Mina Ibrahim, Shivali Baveja, Rong Mu, An H. Do, Zoran Nenadic
https://arxiv.org/abs/2506.14120

Leveraging Transfer Learning and User-Specific Updates for Rapid Training of BCI Decoders
Lengthy subject- or session-specific data acquisition and calibration remain a key barrier to deploying electroencephalography (EEG)-based brain-computer interfaces (BCIs) outside the laboratory. Previous work has shown that cross subject, cross-session invariant features exist in EEG. We propose a transfer learning pipeline based on a two-layer convolutional neural network (CNN) that leverages these invariants to reduce the burden of data acquisition and calibration. A baseline model is traine…

Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks
M. Janssen, C. -k. Chan, J. Davelaar, M. Wielgus
https://arxiv.org/abs/2506.13875

Deep learning inference with the Event Horizon Telescope II. The Zingularity framework for Bayesian artificial neural networks
(abridged) In this second paper in our publication series, we present the open-source Zingularity framework for parameter inference with deep Bayesian artificial neural networks. We carried out out supervised learning with synthetic millimeter very long baseline interferometry observations of the EHT. Our ground-truth models are based on GRMHD simulations of Sgr A* and M87* on horizon scales. We investigated how well Zingularity neural networks are able to infer key model parameters from EHT ob…

Investigating the Potential of Large Language Model-Based Router Multi-Agent Architectures for Foundation Design Automation: A Task Classification and Expert Selection Study
Sompote Youwai, David Phim, Vianne Gayl Murcia, Rianne Clair Onas
https://arxiv.org/abs/2506.13811

Investigating the Potential of Large Language Model-Based Router Multi-Agent Architectures for Foundation Design Automation: A Task Classification and Expert Selection Study
This study investigates router-based multi-agent systems for automating foundation design calculations through intelligent task classification and expert selection. Three approaches were evaluated: single-agent processing, multi-agent designer-checker architecture, and router-based expert selection. Performance assessment utilized baseline models including DeepSeek R1, ChatGPT 4 Turbo, Grok 3, and Gemini 2.5 Pro across shallow foundation and pile design scenarios. The router-based configuration…

Efficient Implementation of a Semiparametric Joint Model for Multivariate Longitudinal Biomarkers and Competing Risks Time-to-Event Data
Shanpeng Li, Emily Ouyang, Jin Zhou, Xinping Cui, Gang Li
https://arxiv.org/abs/2506.12741

Efficient Implementation of a Semiparametric Joint Model for Multivariate Longitudinal Biomarkers and Competing Risks Time-to-Event Data
Joint modeling has become increasingly popular for characterizing the association between one or more longitudinal biomarkers and competing risks time-to-event outcomes. However, semiparametric multivariate joint modeling for large-scale data encounter substantial statistical and computational challenges, primarily due to the high dimensionality of random effects and the complexity of estimating nonparametric baseline hazards. These challenges often lead to prolonged computation time and excess…

This https://arxiv.org/abs/2505.23585 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

On-Policy RL with Optimal Reward Baseline
Reinforcement learning algorithms are fundamental to align large language models with human preferences and to enhance their reasoning capabilities. However, current reinforcement learning algorithms often suffer from training instability due to loose on-policy constraints and computational inefficiency due to auxiliary models. In this work, we propose On-Policy RL with Optimal reward baseline (OPO), a novel and simplified reinforcement learning algorithm designed to address these challenges. O…

Practical Improvements of A/B Testing with Off-Policy Estimation
Sakhi Otmane, Gilotte Alexandre, Rohde David
https://arxiv.org/abs/2506.10677 https://

Practical Improvements of A/B Testing with Off-Policy Estimation
We address the problem of A/B testing, a widely used protocol for evaluating the potential improvement achieved by a new decision system compared to a baseline. This protocol segments the population into two subgroups, each exposed to a version of the system and estimates the improvement as the difference between the measured effects. In this work, we demonstrate that the commonly used difference-in-means estimator, while unbiased, can be improved. We introduce a family of unbiased off-policy e…

Flying Co-Stereo: Enabling Long-Range Aerial Dense Mapping via Collaborative Stereo Vision of Dynamic-Baseline
Zhaoying Wang, Xingxing Zuo, Wei Dong
https://arxiv.org/abs/2506.00546

Flying Co-Stereo: Enabling Long-Range Aerial Dense Mapping via Collaborative Stereo Vision of Dynamic-Baseline
Lightweight long-range mapping is critical for safe navigation of UAV swarms in large-scale unknown environments. Traditional stereo vision systems with fixed short baselines face limited perception ranges. To address this, we propose Flying Co-Stereo, a cross-agent collaborative stereo vision system that leverages the wide-baseline spatial configuration of two UAVs for long-range dense mapping. Key innovations include: (1) a dual-spectrum visual-inertial-ranging estimator for robust baseline e…

Cowboys trade acquisition baseline for 8 young players whose development could alter NFL https://cowboyswire.usatoday.com/story/sports/nfl/cowboys/2025/06/01/cowboys-wr-george-pickens-development-nfl/83977098007…

Spatial and Pulse Efficiency Constraints in Atom Interferometric Gravitational Wave Detectors
Patrik Schach, Enno Giese
https://arxiv.org/abs/2506.09511 ht…

Spatial and Pulse Efficiency Constraints in Atom Interferometric Gravitational Wave Detectors
Currently planned and constructed terrestrial detectors for gravitational waves and dark matter based on differential light-pulse atom interferometry are designed around three primary strategies to enhance their sensitivity: (i) Resonant-mode enhancement using multiple diamonds, (ii) large-momentum-transfer techniques to increase arm separation within the interferometer, and (iii) very-long baseline schemes that increase the distance between the two interferometers. Both resonant-mode enhanceme…

BUT System for the MLC-SLM Challenge
Alexander Polok, Jiangyu Han, Dominik Klement, Samuele Cornell, Jan \v{C}ernock\'y, Luk\'a\v{s} Burget
https://arxiv.org/abs/2506.13414

BUT System for the MLC-SLM Challenge
We present a two-speaker automatic speech recognition (ASR) system that combines DiCoW -- a diarization-conditioned variant of Whisper -- with DiariZen, a diarization pipeline built on top of Pyannote. We first evaluate both systems in out-of-domain (OOD) multilingual scenarios without any fine-tuning. In this scenario, DiariZen consistently outperforms the baseline Pyannote diarization model, demonstrating strong generalization. Despite being fine-tuned on English-only data for target-speaker …

A Framework for Creating Non-Regressive Test Cases via Branch Consistency Analysis Driven by Descriptions
Yuxiang Zhang, Pengyu Xue, Zhen Yang, Xiaoxue Ren, Xiang Li, Linhao Wu, Jiancheng Zhao, Xingda Yu
https://arxiv.org/abs/2506.07486

A Framework for Creating Non-Regressive Test Cases via Branch Consistency Analysis Driven by Descriptions
Automated test-generation research overwhelmingly assumes the correctness of focal methods, yet practitioners routinely face non-regression scenarios where the focal method may be defective. A baseline evaluation of EvoSuite and two leading Large Language Model (LLM)-based generators, namely ChatTester and ChatUniTest, on defective focal methods reveals that despite achieving up to 83% of branch coverage, none of the generated tests expose defects. To resolve this problem, we first construct …

Origin of Radio Emission in Three Nearby Ultraluminous Infrared Galaxies with Signatures of Luminous Buried Active Galactic Nuclei
Takayuki J. Hayashi (National Astronomical Observatory of Japan), Yoshiaki Hagiwara (Toyo University), Masatoshi Imanishi (National Astronomical Observatory of Japan)
https://arxiv.org/abs/2506.10549…

Origin of Radio Emission in Three Nearby Ultraluminous Infrared Galaxies with Signatures of Luminous Buried Active Galactic Nuclei
We report multifrequency Very Long Baseline Array (VLBA) observations at 2.3 and 8.4GHz of three nearby ultraluminous infrared galaxies, identified via mid-infrared spectroscopic analyses as hosting deeply embedded active galactic nuclei (AGNs). Milliarcsecond-scale observations at both frequencies reveal compact continuum emission in IRAS F00188$-$0856 and IRAS F01298$-$0744, accounting for $\sim10$% of the flux density measured on arcsecond scales. The non-detection in IRAS F00091$-$0738 and …

"establish a baseline rhythm" I said. "It's easy I said."
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Peering into the heart of 3CR radio galaxies. A very long baseline interferometry perspective on optical-radio classifications at parsec scales
P. Grandi, G. Giovannini, E. Torresi, B. Boccardi
https://arxiv.org/abs/2506.07589

Peering into the heart of 3CR radio galaxies. A very long baseline interferometry perspective on optical-radio classifications at parsec scales
Historically, luminous edge-brightened Fanaroff-Riley type II (FRII) radio galaxies have been associated with radiatively efficient cold accretion disks. In contrast, faint edge-darkened Fanaroff-Riley Type Is (FRIs) are sustained by hot, inefficient accretion flows. However, several sources deviate from this paradigm, showing FRII morphologies and radiatively inefficient accretion. Three hypotheses have been proposed to explain the observations: (1) The evolutionary scenario: initially strong …

This https://arxiv.org/abs/2404.00306 has been replaced.
link: https://scholar.google.com/scholar?q=a

A blockchain-based intelligent recommender system framework for enhancing supply chain resilience
This research proposed a data-driven supply chain disruption response baseline framework based on intelligent recommender system technology as an initial SCRes reactive solution. To improve the data quality and reliability of the proposed IRS as a stable, secure, and resilient decision support system, blockchain technology is integrated into the baseline architecture. The smart contract is prototyped to demonstrate the information exchange mechanism under a BLC network environment. The BLC-IRS …

The TESS Ten Thousand Catalog: 10,001 uniformly-vetted and -validated Eclipsing Binary Stars detected in Full-Frame Image data by machine learning and analyzed by citizen scientists
Veselin B. Kostov, Brian P. Powell, Aline U. Fornear, Marco Z. Di Fraia, Robert Gagliano, Thomas L. Jacobs, Julien S. de Lambilly, Hugo A. Durantini Luca, Steven R. Majewski, Mark Omohundro, Jerome Orosz, Saul A. Rappaport, Ryan Salik, Donald Short, William Welsh, Svetoslav Alexandrov, Cledison Marcos da Si…

The TESS Ten Thousand Catalog: 10,001 uniformly-vetted and -validated Eclipsing Binary Stars detected in Full-Frame Image data by machine learning and analyzed by citizen scientists
The Transiting Exoplanet Survey Satellite (TESS) has surveyed nearly the entire sky in Full-Frame Image mode with a time resolution of 200 seconds to 30 minutes and a temporal baseline of at least 27 days. In addition to the primary goal of discovering new exoplanets, TESS is exceptionally capable at detecting variable stars, and in particular short-period eclipsing binaries which are relatively common, making up a few percent of all stars, and represent powerful astrophysical laboratories for …

A Chimera method for high-fidelity simulation of turbulent flows
Andrea Di Mascio, Sergio Pirozzoli
https://arxiv.org/abs/2506.05914 https://

A Chimera method for high-fidelity simulation of turbulent flows
We develop a block-structured solver for high-fidelity simulation of flows in complex geometries, based on overlapping (Chimera) meshes. The key components of the algorithm are a baseline dissipation-free central discretization and selective high-order filtering, which ensure uniform accuracy and minimal numerical diffusion. These favorable properties are preserved through efficient interpolation across overlapping blocks. Numerical tests demonstrate that the method guarantees a uniform order o…

This https://arxiv.org/abs/2506.00100 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCY_…

Children's Voice Privacy: First Steps And Emerging Challenges
Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children's voices. Such an evaluation is essential, as children's speech presents a distinct set of challenge…

On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
Undral Byambadalai, Tomu Hirata, Tatsushi Oka, Shota Yasui
https://arxiv.org/abs/2506.05945

On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
This paper focuses on the estimation of distributional treatment effects in randomized experiments that use covariate-adaptive randomization (CAR). These include designs such as Efron's biased-coin design and stratified block randomization, where participants are first grouped into strata based on baseline covariates and assigned treatments within each stratum to ensure balance across groups. In practice, datasets often contain additional covariates beyond the strata indicators. We propose a fl…

Scintillation Properties of PSR B1133 16 Measured with Very Long Baseline Interferometry
Ashley M. Stock, Fardin Syed, Marten H. van Kerkwijk, Rebecca Lin, Franz Kirsten, Ue-Li Pen
https://arxiv.org/abs/2506.02165

Scintillation Properties of PSR B1133+16 Measured with Very Long Baseline Interferometry
The scintillation of pulsars reveals small-scale structure of the interstellar medium. A powerful technique for characterizing the scintillating structures (screens) combines analysis of scintillation arcs and very long baseline interferometry (VLBI). We present the results of a VLBI analysis of the scintillation arcs of PSR B1133+16 from simultaneous observations with Arecibo, VLA, Jodrell Bank, Effelsberg, and Westerbork. Three arcs appear in the data set, all of which appear consistent…

All You Need Is Binary Search! A Practical View on Lightweight Database Indexing on GPUs
Justus Henneberg, Felix Schuhknecht
https://arxiv.org/abs/2506.01576

All You Need Is Binary Search! A Practical View on Lightweight Database Indexing on GPUs
Performing binary search on a sorted dense array is a widely used baseline when benchmarking sophisticated index structures: It is simple, fast to build, and indexes the dataset with minimal memory footprint. However, the popular opinion is that it cannot compete with sophisticated indexes in terms of lookup performance, and hence, should not actually be considered in practice. Interestingly, in our recent works on (even more sophisticated) GPU-resident index structures, we observed the surpr…

Conformer-based Ultrasound-to-Speech Conversion
Ibrahim Ibrahimov, Zaink\'o Csaba, G\'abor Gosztolya
https://arxiv.org/abs/2506.03831 https://

Conformer-based Ultrasound-to-Speech Conversion
Deep neural networks have shown promising potential for ultrasound-to-speech conversion task towards Silent Speech Interfaces. In this work, we applied two Conformer-based DNN architectures (Base and one with bi-LSTM) for this task. Speaker-specific models were trained on the data of four speakers from the Ultrasuite-Tal80 dataset, while the generated mel spectrograms were synthesized to audio waveform using a HiFi-GAN vocoder. Compared to a standard 2D-CNN baseline, objective measurements (MSE…

This https://arxiv.org/abs/2503.22088 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_ees…

Baseline Systems and Evaluation Metrics for Spatial Semantic Segmentation of Sound Scenes
Immersive communication has made significant advancements, especially with the release of the codec for Immersive Voice and Audio Services. Aiming at its further realization, the DCASE 2025 Challenge has recently introduced a task for spatial semantic segmentation of sound scenes (S5), which focuses on detecting and separating sound events in spatial sound scenes. In this paper, we explore methods for addressing the S5 task. Specifically, we present baseline S5 systems that combine audio taggin…

Longitudinal weighted and trimmed treatment effects with flip interventions
Alec McClean, Alexander W. Levis, Nicholas Williams, Ivan Diaz
https://arxiv.org/abs/2506.09188

Longitudinal weighted and trimmed treatment effects with flip interventions
Weighting and trimming are popular methods for addressing positivity violations in causal inference. While well-studied with single-timepoint data, standard methods do not easily generalize to address non-baseline positivity violations in longitudinal data, and remain vulnerable to such violations. In this paper, we extend weighting and trimming to longitudinal data via stochastic ``flip'' interventions, which maintain the treatment status of subjects who would have received the target treatmen…

Neural Network-based Information-Theoretic Transceivers for High-Order Modulation Schemes
Ngoc Long Pham, Tri Nhu Do
https://arxiv.org/abs/2506.00368 https…

Neural Network-based Information-Theoretic Transceivers for High-Order Modulation Schemes
Neural network (NN)-based end-to-end (E2E) communication systems, in which each system component may consist of a portion of a neural network, have been investigated as potential tools for developing artificial intelligence (Al)-native E2E systems. In this paper, we propose an NN-based bitwise receiver that improves computational efficiency while maintaining performance comparable to baseline demappers. Building on this foundation, we introduce a novel symbol-wise autoencoder (AE)-based E2E sys…

A non-local estimator for locally stationary Hawkes processes
Thomas Deschatre, Pierre Gruet, Antoine Lotz
https://arxiv.org/abs/2506.02631 https://…

A non-local estimator for locally stationary Hawkes processes
We consider the problem of estimating the parameters of a non-stationary Hawkes process with time-dependent reproduction rate and baseline intensity. Our approach relies on the standard maximum likelihood estimator (MLE), coinciding with the conventional approach for stationary point processes characterised by [Ogata, 1978]. In the fully parametric setting, we find that the MLE over a single observation of the process over $[0, T]$ remains consistent and asymptotically normal as $T \to \infty$.…

This https://arxiv.org/abs/2506.00691 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csLG_…

Optimizing Sensory Neurons: Nonlinear Attention Mechanisms for Accelerated Convergence in Permutation-Invariant Neural Networks for Reinforcement Learning
Training reinforcement learning (RL) agents often requires significant computational resources and extended training times. To address this, we build upon the foundation laid by Google Brain's Sensory Neuron, which introduced a novel neural architecture for reinforcement learning tasks that maintained permutation in-variance in the sensory neuron system. While the baseline model demonstrated significant performance improvements over traditional approaches, we identified opportunities to enhance…

Updated baseline design for HALHF: the hybrid, asymmetric, linear Higgs factory
C. A. Lindstr{\o}m, E. Adli, J. B. B. Chen, P. Drobniak, E. E. H{\o}rlyk, D. Kalvik, K. N. Sjobak, T. Barklow, S. Gessner, M. Hogan, M. Berggren, A. Laudrain, B. List, J. List, V. Maslov, K. P\~oder, M. Th\'evenet, N. Walker, J. Wood, S. Boogert, P. N. Burrows, V. Cilento, R. D'Arcy, B. Foster, S. Farrington, X. Lu, G. Moortgat-Pick, A. Seryi

Updated baseline design for HALHF: the hybrid, asymmetric, linear Higgs factory
Particle physicists aim to construct a electron-positron Higgs factory as the next major particle collider. However, the high associated costs motivate the development of more affordable collider designs. Plasma-wakefield acceleration is a promising technology to this end. HALHF is a proposal for a Higgs factory that utilizes beam-driven plasma-wakefield acceleration to accelerate electrons to high energy with high gradient, while using radio-frequency acceleration to accelerate positrons to a …

This https://arxiv.org/abs/2502.18284 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

Nested Expectations with Kernel Quadrature
This paper considers the challenging computational task of estimating nested expectations. Existing algorithms, such as nested Monte Carlo or multilevel Monte Carlo, are known to be consistent but require a large number of samples at both inner and outer levels to converge. Instead, we propose a novel estimator consisting of nested kernel quadrature estimators and we prove that it has a faster convergence rate than all baseline methods when the integrands have sufficient smoothness. We then dem…

This https://arxiv.org/abs/2505.03117 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csHC_…

Do ATCOs Need Explanations, and Why? Towards ATCO-Centered Explainable AI for Conflict Resolution Advisories
Interest in explainable artificial intelligence (XAI) is surging. Prior research has primarily focused on systems' ability to generate explanations, often guided by researchers' intuitions rather than end-users' needs. Unfortunately, such approaches have not yielded favorable outcomes when compared to a black-box baseline (i.e., no explanation). To address this gap, this paper advocates a human-centered approach that shifts focus to air traffic controllers (ATCOs) by asking a fundamental yet ov…

Dynamical mass of the Serpens intermediate-mass young stellar system EC\,95 with DYNAMO--VLBA
Jazm\'in Ord\'o\~nez-Toro (Instituto de Radioastronom\'ia y Astrof\'isica, Universidad Nacional Aut\'onoma de M\'exico, M\'exico), Sergio A. Dzib (Max Planck Institut f\"ur Radioastronomie, Germany), Laurent Loinard (Instituto de Radioastronom\'ia y Astrof\'isica, Universidad Nacional Aut\'onoma de M\'exico, M\'exico, Black Hole Initiative a…

Dynamical mass of the Serpens intermediate-mass young stellar system EC\,95 with DYNAMO--VLBA
We present dynamical mass measurements, obtained from multi-epoch Very Long Baseline Interferometry (VLBI) observations, for the young multiple stellar system EC\,95, located in the core of the Serpens star-forming region. Our dataset includes both archival data and more recent observations obtained as part of the \textit{Dynamical Masses of Young Stellar Multiple Systems with the VLBA project} (DYNAMO--VLBA), totalling 32 epochs over 12 years of observation. The observations span more than hal…

Children's Voice Privacy: First Steps And Emerging Challenges
Ajinkya Kulkarni, Francisco Teixeira, Enno Hermann, Thomas Rolland, Isabel Trancoso, Mathew Magimai Doss
https://arxiv.org/abs/2506.00100

Children's Voice Privacy: First Steps And Emerging Challenges
Children are one of the most under-represented groups in speech technologies, as well as one of the most vulnerable in terms of privacy. Despite this, anonymization techniques targeting this population have received little attention. In this study, we seek to bridge this gap, and establish a baseline for the use of voice anonymization techniques designed for adult speech when applied to children's voices. Such an evaluation is essential, as children's speech presents a distinct set of challenge…

Discovery and Localization of the Swift-Observed FRB 20241228A in a Star-forming Host Galaxy
Alice P. Curtin, Shion Andrew, Sunil Simha, Alice Cai, Kenzie Nimmo, Shami Chatterjee, Amanda M. Cook, Fengqiu Adam Dong, Yuxin Dong, Tarraneh Eftekhari, Wen-fai Fong, Emmanuel Fonseca, Jason W. T. Hessels, Ronniy C. Joseph, Victoria Kaspi, Calvin Leung, Robert Main, Kiyoshi W. Masui, Ryan Mckinven, Daniele Michilli, Mason Ng, Ayush Pandhi, Aaron B. Pearlman, Ziggy Pleunis, Mawson W. Sammons, K…

Discovery and Localization of the Swift-Observed FRB 20241228A in a Star-forming Host Galaxy
On 2024 December 28, CHIME/FRB detected the thus-far non-repeating FRB 20241228A with a real-time signal-to-noise ratio of $>50$. Approximately 112~s later, the X-ray Telescope onboard the Neil Gehrels Swift Observatory was on source, the fastest follow-up to-date of a non-repeating FRB (Tohuvavohu et al. in prep.). Using CHIME/FRB and two of the three CHIME/FRB Outriggers, we obtained a Very Long Baseline Interferometry localization for FRB 20241228A with a 1$σ$ confidence ellipse of 11$^{\pr…

A Relativistic Jet in the Radio Quiet AGN Mrk 110
Ailing Wang, Tao An, Kenneth I. Kellermann, Hua Feng, Emmanuel K. Bempong-Manful, Roland Timmerman, Shaoguang Guo
https://arxiv.org/abs/2506.03970

A Relativistic Jet in the Radio Quiet AGN Mrk 110
We report the discovery of a relativistic jet in Mrk~110, a narrow-line Seyfert 1 galaxy historically classified as a radio-quiet active galactic nucleus (AGN). Very Long Baseline Interferometry (VLBI) observations reveal intermittent jet activity during 2015--2016 and 2022--2024, with proper motion measurements yielding superluminal velocities of $\sim3.6\pm0.6\,c$ and $\sim2.1\pm0.2\,c$, respectively. The recent jet component decelerates to $\sim 1.5\pm0.2\,c$ at a projected distance of 1.1 p…

Rules, agents and order
Amalia Puente, Diego Radillo-Ochoa, C. A. Terrero-Escalante
https://arxiv.org/abs/2505.23985 https://arxiv.or…

Rules, agents and order
Complex systems often exhibit highly structured network topologies that reflect functional constraints. In this work, we investigate how, under varying combinations of system-wide selection rules and special agents, different classes of random processes give rise to global order, with a focus restricted to finite-size networks. Using the large-$N$ Erdos-Renyi model as a null baseline, we contrast purely random link-adding processes with goal-directed dynamics, including variants of the chip-fir…

Efficient Gibbs Sampling in Cox Regression Models Using Composite Partial Likelihood and P\'olya-Gamma Augmentation
Shu Tamano, Yui Tomo
https://arxiv.org/abs/2506.04675

Efficient Gibbs Sampling in Cox Regression Models Using Composite Partial Likelihood and Pólya-Gamma Augmentation
The Cox regression model and its Bayesian extensions are widely used in survival analysis. However, standard Bayesian approaches require modeling of the baseline hazard, and their full conditional distributions lack closed-form expressions. Therefore, the Metropolis-Hastings sampling algorithm is typically employed, whose efficiency is highly sensitive to the choice of proposal distribution. To address these issues, we propose the GS4Cox, an efficient Gibbs sampling algorithm for the Cox regres…

HR-VILAGE-3K3M: A Human Respiratory Viral Immunization Longitudinal Gene Expression Dataset for Systems Immunity
Xuejun Sun, Yiran Song, Xiaochen Zhou, Ruilie Cai, Yu Zhang, Xinyi Li, Rui Peng, Jialiu Xie, Yuanyuan Yan, Muyao Tang, Prem Lakshmanane, Baiming Zou, James S. Hagood, Raymond J. Pickles, Didong Li, Fei Zou, Xiaojing Zheng
https://

HR-VILAGE-3K3M: A Human Respiratory Viral Immunization Longitudinal Gene Expression Dataset for Systems Immunity
Respiratory viral infections pose a global health burden, yet the cellular immune responses driving protection or pathology remain unclear. Natural infection cohorts often lack pre-exposure baseline data and structured temporal sampling. In contrast, inoculation and vaccination trials generate insightful longitudinal transcriptomic data. However, the scattering of these datasets across platforms, along with inconsistent metadata and preprocessing procedure, hinders AI-driven discovery. To addre…

Variable Selection in Functional Linear Cox Model
Yuanzhen Yue, Stella Self, Yichao Wu, Jiajia Zhang, Rahul Ghosal
https://arxiv.org/abs/2506.02524 https:/…

Variable Selection in Functional Linear Cox Model
Modern biomedical studies frequently collect complex, high-dimensional physiological signals using wearables and sensors along with time-to-event outcomes, making efficient variable selection methods crucial for interpretation and improving the accuracy of survival models. We propose a novel variable selection method for a functional linear Cox model with multiple functional and scalar covariates measured at baseline. We utilize a spline-based semiparametric estimation approach for the function…

Long-Term Astrometric Monitoring of the Galactic Center Magnetar PSR J1745--2900
Geoffrey C. Bower, Adam T. Deller, Paul B. Demorest, Jason Dexter, Andreas Brunthaler, Gregory Desvignes, Ralph P. Eatough, Heino Falcke, Ciriaco Goddi, Michael Kramer, F. Yusef-Zadeh
https://arxiv.org/abs/2506.02348…

Long-Term Astrometric Monitoring of the Galactic Center Magnetar PSR J1745--2900
We present new astrometric observations of the Galactic Center magnetar, PSR J1745-2900, with the Very Long Baseline Array (VLBA). Combined with previously published measurements in 10 epochs that spanned 477 days, the complete data set consists of 25 epochs and 41 independent measurements that span 1984 days. These data constrain the proper motion to an accuracy of $\lesssim 2\%$ and set an upper limit on the absolute value of the magnetar's acceleration of $\lesssim (0.4, 0.2)\, {\rm mas\,y^{…

Transporting results from a trial to an external target population when trial participation impacts adherence
Rachael K. Ross, Ivan Diaz, Amy J. Pitts, Elizabeth A. Stuart, Kara E. Rudolph
https://arxiv.org/abs/2506.00157

Transporting results from a trial to an external target population when trial participation impacts adherence
Randomized clinical trials are considered the gold standard for informing treatment guidelines, but results may not generalize to real-world populations. Generalizability is hindered by distributional differences in baseline covariates and treatment-outcome mediators. Approaches to address differences in covariates are well established, but approaches to address differences in mediators are more limited. Here we consider the setting where trial activities that differ from usual care settings (e…

Unveiling the Complex Jet Dynamics in the Blazar 2021 317 through Multi-Epoch VLBI Observations
Haitian Shang, Wei Zhao, Xiaoyu Hong, Leonid I. Gurvits, Ailing Zeng, Tao An, Xiaopeng Cheng
https://arxiv.org/abs/2505.23082

Unveiling the Complex Jet Dynamics in the Blazar 2021+317 through Multi-Epoch VLBI Observations
We present an investigation of the compact structure of the AGN 2021+317 based on multi-epoch Very Long Baseline Interferometry (VLBI) observations at 15, 22, and 43 GHz in the period from 2013 through 2024. The VLBI images show a core-jet structure extended to the south, with two stationary components in the northern region, one of which likely to be the core of the source. We also detected two new moving jet components (S4 and S5) in the observations of 2021. Based on these observational find…