Tootfinder

"""
Writing has been an instrument for some of the highest expressions of the human spirit: poetry, philosophy, science. But to understand it — why it came into being, how it changed the human experience — we have to first appreciate its crass practicality. It evolved mainly as an instrument of the mundane: the economic, the administrative, the political.
Confusion over this point is understandable. Some scholars have equated the origin of “civilization” with the origin of writing. Laypeople sometimes take this equation to mean that with writing humanity put aside its barbarous past and started behaving in gentlemanly fashion, sipping tea and remembering to say “please.” And indeed, this may be only a mild caricature of what some nineteenth-century scholars actually meant by the equation: writing equals Greece equals Plato; illiteracy equals barbarism equals Attila the Hun.
But, in truth, if you add literacy to Attila the Hun, you don’t get Plato. You get Genghis Khan. During the thirteenth century, he administered what even today is the largest continuous land empire in the history of the world. And he could do so only because he had the requisite means of control: a script that, when carried by his pony express, amounted to the fastest large-scale information-processing technology of his era. One consequence was to give pillaging a scope beyond Attila’s wildest dreams. Information technology, like energy technology or any other technology, can be a tool for good or bad. By itself, it is no guarantor of moral progress or civility.
"""
(Robert Wright, Nonzero: The Logic of Human Destiny)

Iran reportedly preparing to mine Strait of Hormuz, a possible boon for Russia's Ukraine war coffers: https://benborges.xyz/2025/07/02/iran-reportedly-preparing-to-mine.html

This https://arxiv.org/abs/2410.00059 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

IDEA: An Inverse Domain Expert Adaptation Based Active DNN IP Protection Method
Illegitimate reproduction, distribution and derivation of Deep Neural Network (DNN) models can inflict economic loss, reputation damage and even privacy infringement. Passive DNN intellectual property (IP) protection methods such as watermarking and fingerprinting attempt to prove the ownership upon IP violation, but they are often too late to stop catastrophic damage of IP abuse and too feeble against strong adversaries. In this paper, we propose IDEA, an Inverse Domain Expert Adaptation based…

Gold after Randomized Sand: Model-X Split Knockoffs for Controlled Transformation Selection
Yang Cao, Hangyu Lin, Xinwei Sun, Yuan Yao
https://arxiv.org/abs/2507.01732

Gold after Randomized Sand: Model-X Split Knockoffs for Controlled Transformation Selection
Controlling the False Discovery Rate (FDR) in variable selection is crucial for reproducibility and preventing over-selection, particularly with the increasing prevalence of predictive modeling. The Split Knockoff method, a recent extension of the canonical Knockoffs framework, offers finite-sample FDR control for selecting sparse transformations, finding applications across signal processing, economics, information technology, and the life sciences. However, its current formulation is limited …

An Improved Inference for IV Regressions
Liyu Dou, Pengjin Min, Wenjie Wang, Yichong Zhang
https://arxiv.org/abs/2506.23816 https://a…

An Improved Inference for IV Regressions
Researchers often report empirical results that are based on low-dimensional IVs, such as the shift-share IV, together with many IVs. Could we combine these results in an efficient way and take advantage of the information from both sides? In this paper, we propose a combination inference procedure to solve the problem. Specifically, we consider a linear combination of three test statistics: a standard cluster-robust Wald statistic based on the low-dimensional IVs, a leave-one-cluster-out Lagra…

Deep Research Agents: A Systematic Examination And Roadmap
Yuxuan Huang, Yihang Chen, Haozheng Zhang, Kang Li, Meng Fang, Linyi Yang, Xiaoguang Li, Lifeng Shang, Songcen Xu, Jianye Hao, Kun Shao, Jun Wang
https://arxiv.org/abs/2506.18096

Deep Research Agents: A Systematic Examination And Roadmap
The rapid progress of Large Language Models (LLMs) has given rise to a new category of autonomous AI systems, referred to as Deep Research (DR) agents. These agents are designed to tackle complex, multi-turn informational research tasks by leveraging a combination of dynamic reasoning, adaptive long-horizon planning, multi-hop information retrieval, iterative tool use, and the generation of structured analytical reports. In this paper, we conduct a detailed analysis of the foundational technolo…

What might the future of research and education networking look like?
“Foresight 2030: Navigating Change” report explores 9 key challenges, 3 possible futures, and one key takeaway: change is coming, and collaboration is our strength.
📖 Read the article by Charles Hutchings, Raimundas Tuminauskas & Beatrix Weber −

Foresight 2030 – Navigating Change | GÉANT CONNECT Online
“Foresight 2030 is a great example of what NRENs do best: collaborate for the benefit of the unique and crucial digital infrastructure which supports research and education and the benefit they bring to science and learning, communities and economies internationally. The report demonstrates the reach and significance of the technical expertise NRENs convene within and

Demand for LNG in Europe dropped by 18 per cent between 2022 and 2024, and Canadian exports would have a hard time competing in Asian markets, says advocacy group Investors for Paris Compliance. “Investing in infrastructure that will be very expensive and likely won’t be profitable will weaken our economy rather than strengthen it,” Renaud Gignac, an economist and senior adviser for the group, said in an interview.

New report casts doubt on potential revival of Quebec LNG project
Reviving a liquefied natural gas export project in Quebec's Saguenay region would be costly and likely unprofitable, a shareholder advocacy group says.

Causal Inference for Aggregated Treatment
Carolina Caetano, Gregorio Caetano, Brantly Callaway, Derek Dyal
https://arxiv.org/abs/2506.22885 https://…

Causal Inference for Aggregated Treatment
In this paper, we study causal inference when the treatment variable is an aggregation of multiple sub-treatment variables. Researchers often report marginal causal effects for the aggregated treatment, implicitly assuming that the target parameter corresponds to a well-defined average of sub-treatment effects. We show that, even in an ideal scenario for causal inference such as random assignment, the weights underlying this average have some key undesirable properties: they are not unique, the…

What Causes Errors in Wang-Sheeley-Arge Solar Wind Modeling at L1 ?
Satabdwa Majumdar, Martin Reiss, Karin Muglach, Charles N. Arge
https://arxiv.org/abs/2506.09676

What Causes Errors in Wang-Sheeley-Arge Solar Wind Modeling at L1 ?
Previous ambient solar wind (SW) validation studies have reported on discrepancies between modeled and observed SW conditions at L1. They indicated that a major source of discrepancies stems from how we model the solar corona. Thus, enhancing predictive capabilities demands a thorough examination of coronal modeling. The Wang-Sheeley-Arge (WSA) model has been a workhorse model that provides the near-Sun SW conditions. An important component of it is the Potential Field Source Surface (PFSS) mod…