Tootfinder

Inner disc and circumplanetary material in the PDS 70 system
Daniele Fasano, Myriam Benisty, Pietro Curone, Stefano Facchini, Francesco Zagaria, Tomohiro C. Yoshida, Kiyoaki Doi, Anibal Sierra, Sean Andrews, Jaehan Bae, Andrea Isella, Nicol\'as T. Kurtovic, Laura M. P\'erez, Paola Pinilla, Luna Rampinelli, Richard Teague
https://

Inner disc and circumplanetary material in the PDS 70 system
The two giant protoplanets directly imaged in the dust-depleted cavity of PDS 70 offer a unique opportunity to study ongoing planet formation. Both planets have been detected in infrared thermal emission and in H$α$, indicating active accretion. We calibrate and analyse archival ALMA Band 6 and 7 observations of PDS 70 from 2019, 2021, and 2023 to search for circumplanetary material and assess its motion. Using 2D visibility modelling of the high-resolution (~0.11"x0.08" in Band 6; ~0.05"x0.05…

Down But Not Out: The Case of Long-Period Comet C/2021 O3 (Panstarrs)
David Jewitt. Jing Li, Michael Jaeger, Yoonyoung Kim
https://arxiv.org/abs/2506.09263

Down But Not Out: The Case of Long-Period Comet C/2021 O3 (Panstarrs)
We combine ground- and space-based observations of long-period comet C/2021 O3 (Panstarrs) (perihelion distance 0.287 au) in order to investigate its reported near-perihelion destruction. Pre-perihelion photometric observations show a remarkably small heliocentric dependence of the scattered light, $\propto r_H^{-s}$ with $s = 2.59\pm0.21$, distinct from values reported in other long-period comets, for which $s$ = 4 is the canonical standard. The index is smaller than expected of coma productio…

Temporally Extending Existing Web Archive Collections for Longitudinal Analysis
Lesley Frew, Michael L. Nelson, Michele C. Weigle
https://arxiv.org/abs/2505.24091

Temporally Extending Existing Web Archive Collections for Longitudinal Analysis
The Environmental Governance and Data Initiative (EDGI) regularly crawled US federal environmental websites between 2016 and 2020 to capture changes between two presidential administrations. However, because it does not include the previous administration ending in 2008, the collection is unsuitable for answering our research question, Were the website terms deleted by the Trump administration (2017--2021) added by the Obama administration (2009--2017)? Thus, like many researchers using the Way…

I understand why sensible people say not to trust "answers" from AI/LLM but I don't understand why they then act like that invalidates the usefulness of LLMs.
abbv dividends 2021 through 2025?
Answer for some reason lists a chart for Agilent Technologies, Inc.
Then lists a chart showing dividends for ABBV by year (including quarterly payment amounts).
I can see those amounts are close (probably exactly right...) and for my quick estimate good enough.

Blue Lights, Insurmountable Debt, and the Affordances of its Erasure
https://ift.tt/pL6dIVC
By Justin Martin In The Dawn of Everything: A New History of Humanity (2021), anthropologist David…
via Input 4 RELCFP

Blue Lights, Insurmountable Debt, and the Affordances of its Erasure
By Justin Martin In The Dawn of Everything: A New History of Humanity (2021), anthropologist David Graeber and Archeologist David Wengrow set out to offer a new way of thinking about the human orig…

This https://arxiv.org/abs/2412.04265 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_eco…

On Extrapolation of Treatment Effects in Multiple-Cutoff Regression Discontinuity Designs
Regression discontinuity (RD) designs typically identify the treatment effect at a single cutoff point, which may not always be the primary interest. When and how, then, can we learn about treatment effects away from the cutoff? This paper addresses this question within a multiple-cutoff RD framework. We begin by examining the plausibility of the constant bias assumption proposed by Cattaneo, Keele, Titiunik, and Vazquez-Bare (2021) through the lens of rational decision-making behavior. We argu…

This https://arxiv.org/abs/2501.13881 has been replaced.
link: https://scholar.google.com/scholar?q=a

The machine learning platform for developers of large systems
The machine learning system in the form of Retrieval Augmented Generation (RAG) has developed steadily since about 2021. RAG could be observed as a version of the knowledge transfer. In the studied case, the large computing systems are observed as the application point of RAG, which includes large language model (LLM), as a partner for the developing team. Such an approach has advantages during the development process and further in exploitation time.