Tootfinder

Your data, their rules
https://blog.42futures.com/p/your-data-their-rules

The Tow Center releases a tracker that monitors lawsuits, deals, grants, and other developments between news publishers and AI companies (Klaudia Jaźwińska/Columbia Journalism Review)
https://www.cjr.org/analysis/lawsuit-license-openai-micros…

Lawsuit or license? A new tool to keep track of disputes and deals between publishers and AI companies.
Announcing a new tool to keep track of disputes and deals between news publishers and AI companies.

🚜 California farmland doused with 2.5 million pounds of PFAS pesticides each year, analysis finds
https://www.thenewlede.org/2025/11/california-farmland-doused-with-2-5-million-pounds-of-pfas-pesticides-each-y…

California farmland doused with 2.5 million pounds of PFAS pesticides each year, analysis finds - The New Lede
Farm fields in California, the largest US agricultural state, are sprayed each year with an average of 2.5 million pounds of pesticides containing toxic PFAS, potentially exposing millions of people to the chemicals through contaminated food, soil and drinking water, according to a new analysis of state regulatory data.

The government’s biggest coal sales in more than a decade, is coming in a few days,
offering 600 million tons from publicly owned reserves next to strip mines in Montana and Wyoming.
The sales are a signature piece of Trump’s ambitions for companies to dig more coal from federal lands and burn it for electricity.
Yet most power plants served by those mines plan to quit burning coal altogether within 10 years, an Associated Press data analysis shows.
Three other mines po…

Trump wants to mine more coal from public lands as appetite for it lags
U.S. officials in coming days are set to hold the government’s biggest coal sales in more than a decade. About 600 million tons of the fuel will be auctioned from publicly owned reserves next to strip mines in Montana and Wyoming. Data analyzed by The Associated Press shows most of the power plants served by those mines plan to quit burning coal altogether within 10 years. The sales are a signature piece of President Donald Trump’s ambitions to dig and burn more coal from federal lands. The…

An analysis of Waymo's data covering ~100M driverless miles across four US cities: Waymo cars have far lower crash rates per million miles than human drivers (Jonathan Slotkin/New York Times)
https://www.nytimes.com/2025/12/02/o…

Opinion | The Medical Case for Self-Driving Cars
Compared to human drivers, Waymo cars were involved in 91 percent fewer crashes that resulted in serious injuries.

Hi #Linux team - any recommendations for a work desktop computer with the following requirements:

• can do basic research stuff (reading, writing) and also a little bit of basic data analysis (with python or Matlab)
• would run a distribution like #ZorinOS or Mint
• with a Max…

Computing | Laptops, Tablets, Desktops, Servers and Computing Accessories
Shop our latest range of devices and accessories: Laptops, Tablets, Desktops, Servers and Computing Accessories. All from Insight UK.

End-of-Year Threat Intelligence Sightings Forecast
This report presents an analysis of Threat Intelligence (TI) Sightings aggregated from several key data sources, including social platforms, code repositories, and specialized TI feeds. The primary objective is to visually track historical trends per source and provide a short-term adaptive forecast for a defined period (in days).
#opensource

#ShamelesslyStolenFromBlueSky

An analysis of Crunchbase and PitchBook data: in 2025 so far, 80 tech startups reached $1B valuations, many of them focused on AI with exceptions like Kalshi (Dominic-Madori Davis/TechCrunch)
https://techcrunch.com/2025/12/01/at-least-36-new-tech-…

At least 80 new tech unicorns were minted in 2025 so far | TechCrunch
Using data from Crunchbase and PitchBook, TechCrunch tracked down the VC-backed startups that became unicorns so far this year.

Revealed: Europe’s water reserves drying up due to climate breakdown.
“When we compare the total terrestrial water storage data with climate datasets, the trends broadly correlate,” said Mohammad Shamsudduha, professor of water crisis and risk reduction at UCL.

Regional temperature records broken across the world in 2025 #environment

Regional temperature records broken across the world in 2025
Central Asia, the Sahel region and northern Europe experienced their hottest year on record in 2025, according to AFP analysis based on data from the European Copernicus program.

An analysis of 30 US data center proposals in 14 states: in most cases, local officials signed NDAs and worked with apparent shell companies to hide details (Natalie Kainz/NBC News)
https://www.nbcnews.com/tech/tech-news/dat

How NDAs keep AI data center details hidden from Americans
A review of over 30 data center proposals across 14 states found that in most cases, officials signed NDAs and worked with what appeared to be shell companies.

Analysis: New Data Suggests Russia Is Sustaining Mi-8 Output Despite Wartime Losses: https://benborges.xyz/2025/12/11/analysis-new-data-suggests-russia.html

ICE shift in tactics leads to soaring number of unjustifiable arrests
Government data shows that more than 60 percent of the people detained in at-large arrests since June did NOT have criminal convictions or pending charges.
-- even as authorities insist that immigration officers are focusing on violent criminals whom they describe as “the worst of the worst.”

ICE shift in tactics leads to soaring number of at-large arrests, data shows
The agency has moved away from focusing on arresting migrants at local jails to tracking them down in communities, a Washington Post analysis found.

🕶️ Community Analysis of Social Virtual Reality Based on Large-Scale Log Data of a Commercial Metaverse Platform
#vr

Community Analysis of Social Virtual Reality Based on Large-Scale Log Data of a Commercial Metaverse Platform
This study quantitatively analyzes the structural characteristics of user communities within Social Virtual Reality (Social VR) platforms supporting head-mounted displays (HMDs), based on large-scale log data. By detecting and evaluating community structures from data on substantial interactions (defined as prolonged co-presence in the same virtual space), we found that Social VR platforms tend to host numerous, relatively small communities characterized by strong internal cohesion and limited …

"This paper presents a comprehensive scientometric analysis of the long-term impact of [event] on the nation scientific development."
*oh, interesting!*
"Using Scopus-indexed data..."
*closes tab*

@… following up on our chat at #SDSL2025, I finally found some time to see how a #QGIS Processing Algorithm Provider plugin can be unit tested. Here's what I've …

trajectools/tests/test_run_algs.py at main
trajectools - Trajectools - trajectory data analysis tools for the QGIS Processing toolbox | Previous home: https://github.com/movingpandas/qgis-trajectools

Teaching students simple #WebScraping was always quite rewarding. It opens up numerous relevant, real-world data sources that are the foundation for any further analysis. Things already got more complicated with dynamic content loading, but now bot-exclusion-mechanisms make it almost impossible in many cases. Is web scraping for the

An analysis of AI training datasets, compiled by The Atlantic, shows AI models were trained on hundreds of thousands of YouTube videos from news publishers (Andrew Deck/Nieman Lab)
https://www.niemanlab.org/2025/10/hundred…

Hundreds of thousands of videos from news publishers like The New York Times and Vox were used to train AI models
YouTube channels from major news publishers and creators were in video data sets used by Microsoft, Meta, Snap, Runway AI, and Bytedance.

A template for data analysis projects structured as R packages (or not) https://github.com/Pakillo/template by @…

GitHub - Pakillo/template: A template for data analysis projects structured as R packages (or not)
A template for data analysis projects structured as R packages (or not) - Pakillo/template

RE: https://mastodon.social/@cheeaun/115415146417702654
After looking at this, got curious to know the limits in most servers.
So I did a little data analysis. Servers list from @…

Aixel: A Unified, Adaptive and Extensible System for AI-powered Data Analysis
Meihui Zhang, Liming Wang, Chi Zhang, Zhaojing Luo
https://arxiv.org/abs/2510.12642 https://…

Aixel: A Unified, Adaptive and Extensible System for AI-powered Data Analysis
A growing trend in modern data analysis is the integration of data management with learning, guided by accuracy, latency, and cost requirements. In practice, applications draw data of different formats from many sources. In the meanwhile, the objectives and budgets change over time. Existing systems handle these applications across databases, analysis libraries, and tuning services. Such fragmentation leads to complex user interaction, limited adaptability, suboptimal performance, and poor exte…

Synthetic Series-Symbol Data Generation for Time Series Foundation Models
Wenxuan Wang, Kai Wu, Yujian Betterest Li, Dan Wang, Xiaoyu Zhang
https://arxiv.org/abs/2510.08445 http…

Synthetic Series-Symbol Data Generation for Time Series Foundation Models
Foundation models for time series analysis (TSA) have attracted significant attention. However, challenges such as training data scarcity and imbalance continue to hinder their development. Inspired by complex dynamic system theories, we design a series-symbol data generation mechanism, enabling the unrestricted creation of high-quality time series data paired with corresponding symbolic expressions. To leverage series-symbol data pairs with strong correlations, we develop \texttt{SymTime}, a p…

Inside the deportation machine (giftlink)
https://www.nytimes.com/interactive/2025/12/22/us/trump-immigration-deportation-network-ice-arrests.html?unlocked_art…

The Complex Deportation Network Behind Trump’s Immigration Crackdown
An analysis of data on every ICE arrest, detention stay and deportation reveals the complexity and reach of President Trump’s immigration crackdown.

Mapping the Urban Mobility Intelligence Frontier: A Scientometric Analysis of Data-Driven Pedestrian Trajectory Prediction and Simulation
Junhao Xu, Hui Zeng
https://arxiv.org/abs/2510.10327

Mapping the Urban Mobility Intelligence Frontier: A Scientometric Analysis of Data-Driven Pedestrian Trajectory Prediction and Simulation
Understanding and predicting pedestrian dynamics has become essential for shaping safer, more responsive, and human-centered urban environments. This study conducts a comprehensive scientometric analysis of research on data-driven pedestrian trajectory prediction and crowd simulation, mapping its intellectual evolution and interdisciplinary structure. Using bibliometric data from the Web of Science Core Collection, we employ SciExplorer and Bibliometrix to identify major trends, influential con…

This is a good start but the subway should curve south down 19th Ave, meet up with Daly City BART and continue on the BART tracks down to Millbrae. That part is essential; a branch to Outer Richmond could be added later as a nice-to-have.
https://musubi3.github.io/sfmta-geary-subway…

44,000 Riders, Zero Trains: A Case for the Geary Subway
A data-driven analysis proving why the Geary corridor, with 44,000+ daily riders, is the most underserved transit route in San Francisco.

High-dimensional Analysis of Synthetic Data Selection
Parham Rezaei, Filip Kovacevic, Francesco Locatello, Marco Mondelli
https://arxiv.org/abs/2510.08123 https://

High-dimensional Analysis of Synthetic Data Selection
Despite the progress in the development of generative models, their usefulness in creating synthetic data that improve prediction performance of classifiers has been put into question. Besides heuristic principles such as "synthetic data should be close to the real data distribution", it is actually not clear which specific properties affect the generalization error. Our paper addresses this question through the lens of high-dimensional regression. Theoretically, we show that, for linear models…

The Data Enclave Advantage: A New Paradigm for Least-Privileged Data Access in a Zero-Trust World
Nico Bistolfi, Andreea Georgescu, Dave Hodson
https://arxiv.org/abs/2510.09494 …

The Data Enclave Advantage: A New Paradigm for Least-Privileged Data Access in a Zero-Trust World
As cloud infrastructure evolves to support dynamic and distributed workflows, accelerated now by AI-driven processes, the outdated model of standing permissions has become a critical vulnerability. Based on the Cloud Security Alliance (CSA) Top Threats to Cloud Computing Deep Dive 2025 Report, our analysis details how standing permissions cause catastrophic cloud breaches. While current security tools are addressing network and API security, the challenge of securing granular data access remain…

MS-Mix: Unveiling the Power of Mixup for Multimodal Sentiment Analysis
Hongyu Zhu, Lin Chen, Mounim A. El-Yacoubi, Mingsheng Shang
https://arxiv.org/abs/2510.11579 https://

MS-Mix: Unveiling the Power of Mixup for Multimodal Sentiment Analysis
Multimodal Sentiment Analysis (MSA) aims to identify and interpret human emotions by integrating information from heterogeneous data sources such as text, video, and audio. While deep learning models have advanced in network architecture design, they remain heavily limited by scarce multimodal annotated data. Although Mixup-based augmentation improves generalization in unimodal tasks, its direct application to MSA introduces critical challenges: random mixing often amplifies label ambiguity and…

Geospatial Reasoning fuses weather, satellite and population
data with Gemini AI for risk analysis
It runs in Google's Trusted Tester program for early access
(That ain't you)
https://www.testingcatalog.com/google-laun…

Google launches geospatial reasoning system for disaster aid
What's new? Geospatial Reasoning fuses weather, satellite and population data with Gemini AI for risk analysis; it runs in Google's Trusted Tester program for early access;

PowerPlots: An Open Source Power Grid Visualization and Data Analysis Framework for Academic Research
Noah Rhodes
https://arxiv.org/abs/2510.05063 https://…

PowerPlots: An Open Source Power Grid Visualization and Data Analysis Framework for Academic Research
Data visualization is important for developing an understanding of a complex system. PowerPlots.jl is a data visualization tool for power grids, one of the most complex systems in the world. The design of PowerPlots.jl is intended to facilitate exploration of power grid data while performing research and to facilitate communication of research findings to an audience. Several tools created to support this software also facilitate analysis of power grid data by transforming the data into graph t…

If there is any truth in these allegations, we really have to worry about that is going on in both AGS and GSOC.
The initial story was bad enough: the Irish police service being so incompetent that their statistics on homicides were wildly incorrect, and the whistleblower getting penalised; but this is batshit.

Garda whistleblower says she took work leave as she was ‘terrified’ of new analysis chief
Civilian was installed as Garda analysis bureau head after Lois West testified to Oireachtas about errors in homicide data

Most Cambodia & Laos tree cover loss in 2024 happened inside protected areas https://news.mongabay.com/short-article/2025/10/most-cambodia-laos-tree-cover-loss-in-2024-happened-inside-protected-areas/
…

Most Cambodia & Laos tree cover loss in 2024 happened inside protected areas
More than half of Cambodia and Laos’ tree cover loss in 2024 was recorded inside protected areas, Mongabay’s Gerald Flynn reports. The findings were a result of Mongabay’s analysis of satellite data published by the Global Land Analysis and Discovery laboratory at the University of Maryland, in partnership with Global Forest Watch. In Cambodia, 56% of the nation’s […]

Updated constraints on interacting dark energy: A comprehensive analysis using multiple CMB probes, DESI DR2, and supernovae observations
Tian-Nuo Li, Guo-Hong Du, Yun-He Li, Yichao Li, Jia-Le Ling, Jing-Fei Zhang, Xin Zhang
https://arxiv.org/abs/2510.11363

Updated constraints on interacting dark energy: A comprehensive analysis using multiple CMB probes, DESI DR2, and supernovae observations
Recent DESI baryon acoustic oscillation (BAO) measurements, combined with Planck cosmic microwave background (CMB) data and DESY5 type Ia supernova (SN) data, indicate a significant deviation from $Λ$CDM, which seems to suggest that this deviation can be explained by an interaction between dark energy and dark matter. In this work, we perform a comprehensive analysis by utilizing the latest DESI DR2 BAO data in conjunction with CMB data from ACT, SPT, Planck, and WMAP, along with SN data from …

Multi-Physics-Enhanced Bayesian Inverse Analysis: Information Gain from Additional Fields
Lea J. Haeusel, Jonas Nitzler, Lea J. K\"oglmeier, Wolfgang A. Wall
https://arxiv.org/abs/2510.11095

Multi-Physics-Enhanced Bayesian Inverse Analysis: Information Gain from Additional Fields
Many real-world inverse problems suffer from limited data, often because they rely on measurements of a single physical field. Such data frequently fail to sufficiently reduce parameter uncertainty in Bayesian inverse analysis. Incorporating easily available data from additional physical fields can substantially decrease this uncertainty. We focus on Bayesian inverse analyses based on computational models, e.g., those using the finite element method. To incorporate data from additional physical…

Dataminr to acquire cybersecurity firm ThreatConnect for $290 million
https://cyberscoop.com/dataminr-threatconnect-acquisition/

Dataminr to acquire cybersecurity firm ThreatConnect for $290 million
Dataminr, a New York-based company specializing in real-time threat intelligence, announced plans Tuesday to acquire ThreatConnect, a cybersecurity threat intelligence provider, for $290 million. The acquisition will combine Dataminr’s AI-powered analysis of public data with ThreatConnect’s internal threat management capabilities, creating what the companies describe as “Client-Tailored intelligence” that adapts to individual customer needs. The […]

CoDA: Agentic Systems for Collaborative Data Visualization
Zichen Chen, Jiefeng Chen, Sercan \"O. Arik, Misha Sra, Tomas Pfister, Jinsung Yoon
https://arxiv.org/abs/2510.03194

CoDA: Agentic Systems for Collaborative Data Visualization
Deep research has revolutionized data analysis, yet data scientists still devote substantial time to manually crafting visualizations, highlighting the need for robust automation from natural language queries. However, current systems struggle with complex datasets containing multiple files and iterative refinement. Existing approaches, including simple single- or multi-agent systems, often oversimplify the task, focusing on initial query parsing while failing to robustly manage data complexity…

Monitoring 3D Lattice Structures in Additive Manufacturing Using Topological Data Analysis
Yulin An, Xueqi Zhao, Enrique del Castillo
https://arxiv.org/abs/2510.11740 https://…

Monitoring 3D Lattice Structures in Additive Manufacturing Using Topological Data Analysis
We present a new method for the statistical process control of lattice structures using tools from Topological Data Analysis. Motivated by applications in additive manufacturing, such as aerospace components and biomedical implants, where hollow lattice geometries are critical, the proposed framework is based on monitoring the persistent homology properties of parts. Specifically, we focus on homological features of dimensions zero and one, corresponding to connected components and one-dimensio…

Exploring Quantum Spacetime with Topological Data Analysis
J. van der Duin, R. Loll, M. Schiffer, A. Silva
https://arxiv.org/abs/2510.05693 https://arxiv.o…

Exploring Quantum Spacetime with Topological Data Analysis
In a novel application of the tools of topological data analysis (TDA) to nonperturbative quantum gravity, we introduce a new class of observables that allows us to assess whether quantum spacetime really resembles a ``quantum foam" near the Planck scale. The key idea is to investigate the Betti numbers of coarse-grained path integral histories, regularized in terms of dynamical triangulations, as a function of the coarse-graining scale. In two dimensions our analysis exhibits the well-known fr…

First simultaneous global QCD analysis of kaon and pion parton distributions with lattice QCD constraints
P. C. Barry, Chueng-Ryong Ji, W. Melnitchouk, N. Sato, Fernanda Steffens
https://arxiv.org/abs/2510.11979

First simultaneous global QCD analysis of kaon and pion parton distributions with lattice QCD constraints
We perform the first simultaneous global QCD analysis of pion and kaon parton distribution functions (PDFs), constrained by pion- and kaon-induced Drell-Yan (DY) and leading neutron electroproduction data, together with lattice QCD data on pion and kaon PDF moments. The analysis indicates a softer valence $\bar u$ distribution in the $K^-$ than in the $π^-$, and a significantly more peaked valence $s$-quark density in $K^-$ compared with the $\bar u$. The effective exponent governing the high-…

The impact of missing data on the construction of LISA Time Delay Interferometry Michelson variables
Ollie Burke, Martina Muratore, Graham Woan
https://arxiv.org/abs/2510.06406 …

The impact of missing data on the construction of LISA Time Delay Interferometry Michelson variables
We investigate the impact of missing input data on the construction of second-generation Time Delay Interferometry (TDI) variables, which enable data analysis for the Laser Interferometer Space Antenna (LISA). TDI relies on the introduction of precise time delays into the raw interferometric data streams before they are combined to suppress otherwise dominant laser phase noise. We show that a single missing sample, corresponding to 0.25 s of data, will result in an effective data gap of approxi…

SenWave: A Fine-Grained Multi-Language Sentiment Analysis Dataset Sourced from COVID-19 Tweets
Qiang Yang, Xiuying Chen, Changsheng Ma, Rui Yin, Xin Gao, Xiangliang Zhang
https://arxiv.org/abs/2510.08214

SenWave: A Fine-Grained Multi-Language Sentiment Analysis Dataset Sourced from COVID-19 Tweets
The global impact of the COVID-19 pandemic has highlighted the need for a comprehensive understanding of public sentiment and reactions. Despite the availability of numerous public datasets on COVID-19, some reaching volumes of up to 100 billion data points, challenges persist regarding the availability of labeled data and the presence of coarse-grained or inappropriate sentiment labels. In this paper, we introduce SenWave, a novel fine-grained multi-language sentiment analysis dataset specific…

Analysis: of the 8,808 global data centers in October 2025, ~7,000 are in areas outside the optimal 18C to 27C temperature range; 600 are in areas above 27C (Rest of World)
https://restofworld.org/2025/data-center-heat-map/

We mapped the world’s hottest data centers
In 21 countries, all data centers are located in climates that are too hot.

98 % des arbres fruitiers et oliviers de Gaza ont été détruits. 90 % des serres sont endommagées et 75 % détruites, selon une analyse des images satellitaires.
https://www.zmescience.com/science/news-sc

#nytimes #report #usapol
"Inside the Deportation Machine"
-
"At least 32 people have died in ICE custody since Mr. Trump took office, more than the number in Mr. Biden’s entire…

The Complex Deportation Network Behind Trump’s Immigration Crackdown
An analysis of data on every ICE arrest, detention stay and deportation reveals the complexity and reach of President Trump’s immigration crackdown.

Energy Efficiency in Cloud-Based Big Data Processing for Earth Observation: Gap Analysis and Future Directions
Adhitya Bhawiyuga, Serkan Girgin, Rolf A. de By, Raul Zurita-Milla
https://arxiv.org/abs/2510.02882

Energy Efficiency in Cloud-Based Big Data Processing for Earth Observation: Gap Analysis and Future Directions
Earth observation (EO) data volumes are rapidly increasing. While cloud computing are now used for processing large EO datasets, the energy efficiency aspects of such a processing have received much less attention. This issue is notable given the increasing awareness of energy costs and carbon footprint in big data processing, particularly with increased attention on compute-intensive foundation models. In this paper we identify gaps in energy efficiency practices within cloud-based EO big data…

Claude skills are a big deal™️
Thanks to skills, you can reduce your multi-agent setup to a single agent with skills, greatly reducing complexity and increasing speed of execution.
In fact, if in the past you could have a number of agents each specialized in, for example, data analysis, getting data from a particular set of websites, making that data available in a dashboard, etc., with skills you can substitute all these agents with skills. (1/2)

I rewrote a data analysis pipeline, moving it from #python to #julialang . I am now in love with the threading support in Julia.
The task is very parallelizable but each thread needs random read access to a tens-of-GB dataset. In Python (with multiprocessing, shared stores, etc) data bookkeeping was a nightmar…

Sensitivity Analysis for Causal ML: A Use Case at Booking.com
Philipp Bach, Victor Chernozhukov, Carlos Cinelli, Lin Jia, Sven Klaassen, Nils Skotara, Martin Spindler
https://arxiv.org/abs/2510.09109

Sensitivity Analysis for Causal ML: A Use Case at Booking.com
Causal Machine Learning has emerged as a powerful tool for flexibly estimating causal effects from observational data in both industry and academia. However, causal inference from observational data relies on untestable assumptions about the data-generating process, such as the absence of unobserved confounders. When these assumptions are violated, causal effect estimates may become biased, undermining the validity of research findings. In these contexts, sensitivity analysis plays a crucial ro…

There is enough data to start publishing reports of my statistical analysis of the Italian Volleyball Serie A1 championship.
https://davideaversa.it/experiment/volley/seriea1w2025.html

Crosslisted article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- Ensemble-Based Data Assimilation for Material Model Characterization in High-Velocity Impact
Rong Jin, Guangyao Wang, Xingsheng Sun

Kayak: in principle, an application that may be well-served by "old" rules-based AI. Its function is supposed to be deterministic, needing more data ingestion & analysis than humans can tolerate.
But if they're calling it "AI" today, I'm sure it's a LLM/neural net gadget which will hallucinate flights & fares. Because we're playing out the theory that the #XRisk

Photometric Redshift Estimation for Rubin Observatory Data Preview 1 with Redshift Assessment Infrastructure Layers (RAIL)
T. Zhang, E. Charles, J. F. Crenshaw, S. J. Schmidt, P. Adari, J. Gschwend, S. Mau, B. Andrews, E. Aubourg, Y. Bains, K. Bechtol, A. Boucaud, D. Boutigny, P. Burchat, J. Chevalier, J. Chiang, H. -F. Chiang, D. Clowe, J. Cohen-Tanugi, C. Combet, A. Connolly, S. Dagoret-Campagne, P. N. Daly, F. Daruich, G. Daubard, J. De Vicente, H. Drass, K. Fanning, E. Gawiser, M. …

Photometric Redshift Estimation for Rubin Observatory Data Preview 1 with Redshift Assessment Infrastructure Layers (RAIL)
We present the first systematic analysis of photometric redshifts (photo-z) estimated from the Rubin Observatory Data Preview 1 (DP1) data taken with the Legacy Survey of Space and Time (LSST) Commissioning Camera. Employing the Redshift Assessment Infrastructure Layers (RAIL) framework, we apply eight photo-z algorithms to the DP1 photometry, using deep ugrizy coverage in the Extended Chandra Deep Field South (ECDFS) field and griz data in the Rubin_SV_38_7 field. In the ECDFS field, we constr…

Sentiment Matters: An Analysis of 200 Human-SAV Interactions
Lirui Guo, Michael G. Burke, Wynita M. Griggs
https://arxiv.org/abs/2510.08202 https://arxiv.o…

Sentiment Matters: An Analysis of 200 Human-SAV Interactions
Shared Autonomous Vehicles (SAVs) are likely to become an important part of the transportation system, making effective human-SAV interactions an important area of research. This paper introduces a dataset of 200 human-SAV interactions to further this area of study. We present an open-source human-SAV conversational dataset, comprising both textual data (e.g., 2,136 human-SAV exchanges) and empirical data (e.g., post-interaction survey results on a range of psychological factors). The dataset's…

Missing Data Imputation in the Context of Propensity Score Analysis: A Systematic Review
Saghar Garayemi, Reza Ali Akbari Khoei, Sarah Friedrich
https://arxiv.org/abs/2510.05857

Missing Data Imputation in the Context of Propensity Score Analysis: A Systematic Review
Missing data is a common challenge in observational studies. Another challenge stems from the observational nature of the study itself. Here, propensity score analysis can be used as a technique to replicate conditions similar to those found in clinical trials. With regard to the missing data, a majority of studies only analyze the complete cases, but this has several pitfalls. In this review, we investigate which methods are used for the handling of missing data in the context of propensity sc…

Evaluation of Real-Time Preprocessing Methods in AI-Based ECG Signal Analysis
Jasmin Freudenberg, Kai Hahn, Christian Weber, Madjid Fathi
https://arxiv.org/abs/2510.12541 https:…

Evaluation of Real-Time Preprocessing Methods in AI-Based ECG Signal Analysis
The increasing popularity of portable ECG systems and the growing demand for privacy-compliant, energy-efficient real-time analysis require new approaches to signal processing at the point of data acquisition. In this context, the edge domain is acquiring increasing importance, as it not only reduces latency times, but also enables an increased level of data security. The FACE project aims to develop an innovative machine learning solution for analysing long-term electrocardiograms that synergi…

Joint neutrino oscillation analysis from the T2K and NOvA experiments: #neutrinos may hold the keys to why we exist: https://www.eurekalert.org/news-releases/1103650 - MSU scientists help merge data from two neutrino experiments to offer most precise look yet at elusive particles.

The Pitfalls of Continuous Heavy-Tailed Distributions in High-Frequency Data Analysis
Vladim\'ir Hol\'y
https://arxiv.org/abs/2510.09785 https://ar…

The Pitfalls of Continuous Heavy-Tailed Distributions in High-Frequency Data Analysis
We address the challenges of modeling high-frequency integer price changes in financial markets using continuous distributions, particularly the Student's t-distribution. We demonstrate that traditional GARCH models, which rely on continuous distributions, are ill-suited for high-frequency data due to the discreteness of price changes. We propose a modification to the maximum likelihood estimation procedure that accounts for the discrete nature of observations while still using continuous distr…

RevMine: An LLM-Assisted Tool for Code Review Mining and Analysis Across Git Platforms
Samah Kansab, Francis Bordeleau, Ali Tizghadam
https://arxiv.org/abs/2510.04796 https://…

RevMine: An LLM-Assisted Tool for Code Review Mining and Analysis Across Git Platforms
Empirical research on code review processes is increasingly central to understanding software quality and collaboration. However, collecting and analyzing review data remains a time-consuming and technically intensive task. Most researchers follow similar workflows - writing ad hoc scripts to extract, filter, and analyze review data from platforms like GitHub and GitLab. This paper introduces RevMine, a conceptual tool that streamlines the entire code review mining pipeline using large language…

Analysis: since 2023, data center power demands have delayed 15 coal plants' retirements; the Trump administration has ordered two power plants to remain open (Ariel Wittenberg/Politico)
https://www.politico.com/news/2025/11/27/a

Analysis of the Supernova Remnant IC 443 using H.E.S.S. Data
Alison M. W. Mitchell (for the H.E.S.S. Collaboration), Lukas Grosspietsch (for the H.E.S.S. Collaboration), Tina Wach (for the H.E.S.S. Collaboration)
https://arxiv.org/abs/2510.02843

Analysis of the Supernova Remnant IC 443 using H.E.S.S. Data
IC 443 is a well-known supernova remnant that stands out due to its interaction with a dense molecular cloud, creating a complex environment where shocks can efficiently accelerate particles to high energies. This makes it a key target for investigating the mechanisms of cosmic-ray acceleration and gamma-ray production, particularly in the context of supernova remnants as potential sources of PeV cosmic rays. This work presents a first analysis of the region as observed by H.E.S.S.. We detect e…

Adapting HFMCA to Graph Data: Self-Supervised Learning for Generalizable fMRI Representations
Jakub Frac, Alexander Schmatz, Qiang Li, Guido Van Wingen, Shujian Yu
https://arxiv.org/abs/2510.05177

Adapting HFMCA to Graph Data: Self-Supervised Learning for Generalizable fMRI Representations
Functional magnetic resonance imaging (fMRI) analysis faces significant challenges due to limited dataset sizes and domain variability between studies. Traditional self-supervised learning methods inspired by computer vision often rely on positive and negative sample pairs, which can be problematic for neuroimaging data where defining appropriate contrasts is non-trivial. We propose adapting a recently developed Hierarchical Functional Maximal Correlation Algorithm (HFMCA) to graph-structured f…

“This seems the best bang for your buck; it’s less per year than private school.”, said the future mother.
UK IVF couples use legal loophole to rank embryos based on potential IQ, height and health
https://www.theguar…

Data or Language Supervision: What Makes CLIP Better than DINO?
Yiming Liu, Yuhui Zhang, Dhruba Ghosh, Ludwig Schmidt, Serena Yeung-Levy
https://arxiv.org/abs/2510.11835 https:/…

Data or Language Supervision: What Makes CLIP Better than DINO?
CLIP outperforms self-supervised models like DINO as vision encoders for vision-language models (VLMs), but it remains unclear whether this advantage stems from CLIP's language supervision or its much larger training data. To disentangle these factors, we pre-train CLIP and DINO under controlled settings -- using the same architecture, dataset, and training configuration -- achieving similar ImageNet accuracy. Embedding analysis shows that CLIP captures high-level semantics (e.g., object catego…

PromptLocate: Localizing Prompt Injection Attacks
Yuqi Jia, Yupei Liu, Zedian Shao, Jinyuan Jia, Neil Gong
https://arxiv.org/abs/2510.12252 https://arxiv.o…

PromptLocate: Localizing Prompt Injection Attacks
Prompt injection attacks deceive a large language model into completing an attacker-specified task instead of its intended task by contaminating its input data with an injected prompt, which consists of injected instruction(s) and data. Localizing the injected prompt within contaminated data is crucial for post-attack forensic analysis and data recovery. Despite its growing importance, prompt injection localization remains largely unexplored. In this work, we bridge this gap by proposing Prompt…

Developing an information criterion for spatial data analysis through Bayesian generalized fused lasso
Yuko Kakikawa, Yoshiyuki Ninomiya
https://arxiv.org/abs/2510.11172 https:/…

Developing an information criterion for spatial data analysis through Bayesian generalized fused lasso
In the field of spatial data analysis, spatially varying coefficients (SVC) models, which allow regression coefficients to vary by region and flexibly capture spatial heterogeneity, have continued to be developed in various directions. Moreover, the Bayesian generalized fused lasso is often used as a method that efficiently provides estimation under the natural assumption that regression coefficients of adjacent regions tend to take the same value. In most Bayesian methods, the selection of pri…

👨🏿‍🌾 Traces of old farm chemicals contaminate water across the US
#chemicals

Traces of old farm chemicals contaminate water across the US
Even though it delivers airtight data and analysis essential for understanding and managing the risks industrial societies pose to water, land, and health, the US Geological Survey is a federal science agency that rarely attracts public notice.

Claude skills are a big deal™️
Thanks to skills, you can reduce your multi-agent setup to a single agent with skills, greatly reducing complexity and increasing speed of execution.
In fact, if in the past you could have a number of agents each specialized in, for example, data analysis, getting data from a particular set of websites, making that data available in a dashboard, etc., with skills you can substitute all these agents with skills. (1/2)

BeSTAD: Behavior-Aware Spatio-Temporal Anomaly Detection for Human Mobility Data
Junyi Xie, Jina Kim, Yao-Yi Chiang, Lingyi Zhao, Khurram Shafique
https://arxiv.org/abs/2510.12076

BeSTAD: Behavior-Aware Spatio-Temporal Anomaly Detection for Human Mobility Data
Traditional anomaly detection in human mobility has primarily focused on trajectory-level analysis, identifying statistical outliers or spatiotemporal inconsistencies across aggregated movement traces. However, detecting individual-level anomalies, i.e., unusual deviations in a person's mobility behavior relative to their own historical patterns, within datasets encompassing large populations remains a significant challenge. In this paper, we present BeSTAD (Behavior-aware Spatio-Temporal Anoma…

Bridging Imperative Process Models and Process Data Queries-Translation and Relaxation
Abdur Rehman Anwar Qureshi, Adrian Rebmann, Timotheus Kampik, Matthias Weidlich, Mathias Weske
https://arxiv.org/abs/2510.06414

Bridging Imperative Process Models and Process Data Queries-Translation and Relaxation
Business process management is increasingly practiced using data-driven approaches. Still, classical imperative process models, which are typically formalized using Petri nets, are not straightforwardly applicable to the relational databases that contain much of the available structured process execution data. This creates a gap between the traditional world of process modeling and recent developments around data-driven process analysis, ultimately leading to the under-utilization of often read…

Cost Analysis of Human-corrected Transcription for Predominately Oral Languages
Yacouba Diarra, Nouhoum Souleymane Coulibaly, Michael Leventhal
https://arxiv.org/abs/2510.12781 …

Cost Analysis of Human-corrected Transcription for Predominately Oral Languages
Creating speech datasets for low-resource languages is a critical yet poorly understood challenge, particularly regarding the actual cost in human labor. This paper investigates the time and complexity required to produce high-quality annotated speech data for a subset of low-resource languages, low literacy Predominately Oral Languages, focusing on Bambara, a Manding language of Mali. Through a one-month field study involving ten transcribers with native proficiency, we analyze the correction …

Replaced article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- Maximum entropy temporal networks
Paolo Barucca

A look at Meta's 2GW Hyperion data center in Louisiana, with the first phase opening in 2028; an analysis shows sales tax breaks on GPUs could total $3.3B (Jon Keegan/Sherwood News)
https://sherwood.news/tech/hyperion/

The power play behind Hyperion, Mark Zuckerberg’s colossal data center being built in rural Louisiana
$10 billion of investment. Code names to disguise projects and companies. Mixed opinions. Skyrocketing property values. And enough tax breaks to pay every state cop in Louisiana for seven years.

nCTEQ global analysis of nuclear PDFs
M. Klasen
https://arxiv.org/abs/2510.05880 https://arxiv.org/pdf/2510.05880…

nCTEQ global analysis of nuclear PDFs
We review the series of specific nCTEQ analyses of nuclear parton distribution functions (PDFs) published since 2020 and present preliminary results of a new global analysis. Building on a modern proton baseline without nuclear data and extending the kinematic range, it combines and updates the previous separate analyses that focused on Jefferson Lab neutral-current deep-inelastic scattering (DIS), neutrino DIS and dimuon production, and the currently available CERN LHC data, in particular on W…

Transformed $\ell_1$ Regularizations for Robust Principal Component Analysis: Toward a Fine-Grained Understanding
Kun Zhao, Haoke Zhang, Jiayi Wang, Yifei Lou
https://arxiv.org/abs/2510.03624

Transformed $\ell_1$ Regularizations for Robust Principal Component Analysis: Toward a Fine-Grained Understanding
Robust Principal Component Analysis (RPCA) aims to recover a low-rank structure from noisy, partially observed data that is also corrupted by sparse, potentially large-magnitude outliers. Traditional RPCA models rely on convex relaxations, such as nuclear norm and $\ell_1$ norm, to approximate the rank of a matrix and the $\ell_0$ functional (the number of non-zero elements) of another. In this work, we advocate a nonconvex regularization method, referred to as transformed $\ell_1$ (TL1), to im…

The Adoption Paradox: A Comparative Analysis of Veterinary AI Adoption in China and the North America
Shumin Li, Xiaoyun Lai
https://arxiv.org/abs/2510.11758 https://

The Adoption Paradox: A Comparative Analysis of Veterinary AI Adoption in China and the North America
This study compares the perception, adoption, and application of artificial intelligence (AI) among veterinary professionals in China and North America (NA), testing the hypothesis that adoption patterns are shaped by regional market and demographic factors. A descriptive, cross-sectional survey was conducted with 455 veterinary professionals in China between May and July 2025. The results were compared with published data from a 2024 survey of 3,968 veterinary professionals in the United State…

Between #Matlab and #Python, which one would you recommend to learn, for a student who wants to learn programming (from scratch) to do data analysis? And why?
I am conflicted because I think Matlab is maybe slightly more straightforward to learn, but Python should be more useful in the long …

Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
Roy Siegelmann, Enrique Mallada
https://arxiv.org/abs/2510.03982

Data-driven Practical Stabilization of Nonlinear Systems via Chain Policies: Sample Complexity and Incremental Learning
We propose a method for data-driven practical stabilization of nonlinear systems with provable guarantees, based on the concept of Nonparametric Chain Policies (NCPs). The approach employs a normalized nearest-neighbor rule to assign, at each state, a finite-duration control signal derived from stored data, after which the process repeats. Unlike recent works that model the system as linear, polynomial, or polynomial fraction, we only assume the system to be locally Lipschitz. Our analysis buil…

"Your Doctor is Spying on You": An Analysis of Data Practices in Mobile Healthcare Applications
Luke Stevenson, Sanchari Das
https://arxiv.org/abs/2510.06015 https://

"Your Doctor is Spying on You": An Analysis of Data Practices in Mobile Healthcare Applications
Mobile healthcare (mHealth) applications promise convenient, continuous patient-provider interaction but also introduce severe and often underexamined security and privacy risks. We present an end-to-end audit of 272 Android mHealth apps from Google Play, combining permission forensics, static vulnerability analysis, and user review mining. Our multi-tool assessment with MobSF, RiskInDroid, and OWASP Mobile Audit revealed systemic weaknesses: 26.1% request fine-grained location without disclosu…

The $\alpha$--regression for compositional data: a unified framework for standard, spatially-lagged, and geographically-weighted regression models
Michail Tsagris
https://arxiv.org/abs/2510.12663

The $α$--regression for compositional data: a unified framework for standard, spatially-lagged, and geographically-weighted regression models
Compositional data-vectors of non--negative components summing to unity--frequently arise in scientific applications where covariates influence the relative proportions of components, yet traditional regression approaches struggle with the unit-sum constraint and zero values. This paper revisits the $α$--regression framework, which uses a flexible power transformation parameterized by $α$ to interpolate between raw data analysis and log-ratio methods, naturally handling zeros without imputati…

Analysis: Oracle has moved $66B of debt for building AI data centers off its balance sheet using SPVs; Meta has moved $30B, xAI moved $20B, and CoreWeave $2.6B (Tabby Kinder/Financial Times)
https://www.ft.com/content/0ae9d6cd-6b94-4e22-a559-f047734bef83

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis
Austin Feng, Andreas Varvarigos, Ioannis Panitsas, Daniela Fernandez, Jinbiao Wei, Yuwei Guo, Jialin Chen, Ali Maatouk, Leandros Tassiulas, Rex Ying
https://arxiv.org/abs/2510.06063

TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis
Modern enterprises generate vast streams of time series metrics when monitoring complex systems, known as observability data. Unlike conventional time series from domains such as weather, observability data are zero-inflated, highly stochastic, and exhibit minimal temporal structure. Despite their importance, observability datasets are underrepresented in public benchmarks due to proprietary restrictions. Existing datasets are often anonymized and normalized, removing scale information and limi…

Crosslisted article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- A mathematical theory for understanding when abstract representations emerge in neural networks
Bin Wang, W. Jeffrey Johnston, Stefano Fusi

Comparative Performance Analysis of Modern NoSQL Data Technologies: Redis, Aerospike, and Dragonfly
Deep Bodra, Sushil Khairnar
https://arxiv.org/abs/2510.08863 https://

Comparative Performance Analysis of Modern NoSQL Data Technologies: Redis, Aerospike, and Dragonfly
The rise of distributed applications and cloud computing has created a demand for scalable, high-performance key-value storage systems. This paper presents a performance evaluation of three prominent NoSQL key-value stores: Redis, Aerospike, and Dragonfly, using the Yahoo! Cloud Serving Benchmark (YCSB) framework. We conducted extensive experiments across three distinct workload patterns (read-heavy, write-heavy), and balanced while systematically varying client concurrency from 1 to 32 clients…

Protected areas hit hard as Mekong countries’ forest cover shrank in 2024 https://news.mongabay.com/2025/10/protected-areas-hit-hard-as-mekong-countries-forest-cover-shrank-in-2024/

Protected areas hit hard as Mekong countries’ forest cover shrank in 2024
BANGKOK — The Mekong countries of Cambodia, Laos, Myanmar, Thailand and Vietnam lost a combined area of tree cover of nearly a million hectares in 2024, or an area almost the size of Lebanon. That’s according to Mongabay’s analysis* of satellite data published by the Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland, […]

Parrot Analytics: movies made up ~50% of streaming revenue across Netflix, Prime Video, Disney , and WBD in 2024, up from ~27% in 2022, based on engagement data (Alejandro Rojas/The Hollywood Reporter)
https://www.hollywoodreporter.com/business/b…

How Movies Increasingly Drive Streaming Revenue
A Parrot Analytics analysis of thousands of titles across Amazon Prime Video, Disney+, Netflix, and Max finds that movies deliver disproportionately high engagement relative to the volume of content hours they represent.

You Only Train Once: Differentiable Subset Selection for Omics Data
Daphn\'e Chopard, Jorge da Silva Gon\c{c}alves, Irene Cannistraci, Thomas M. Sutter, Julia E. Vogt
https://arxiv.org/abs/2512.17678 https://arxiv.org/pdf/2512.17678 https://arxiv.org/html/2512.17678
arXiv:2512.17678v1 Announce Type: new
Abstract: Selecting compact and informative gene subsets from single-cell transcriptomic data is essential for biomarker discovery, improving interpretability, and cost-effective profiling. However, most existing feature selection approaches either operate as multi-stage pipelines or rely on post hoc feature attribution, making selection and prediction weakly coupled. In this work, we present YOTO (you only train once), an end-to-end framework that jointly identifies discrete gene subsets and performs prediction within a single differentiable architecture. In our model, the prediction task directly guides which genes are selected, while the learned subsets, in turn, shape the predictive representation. This closed feedback loop enables the model to iteratively refine both what it selects and how it predicts during training. Unlike existing approaches, YOTO enforces sparsity so that only the selected genes contribute to inference, eliminating the need to train additional downstream classifiers. Through a multi-task learning design, the model learns shared representations across related objectives, allowing partially labeled datasets to inform one another, and discovering gene subsets that generalize across tasks without additional training steps. We evaluate YOTO on two representative single-cell RNA-seq datasets, showing that it consistently outperforms state-of-the-art baselines. These results demonstrate that sparse, end-to-end, multi-task gene subset selection improves predictive performance and yields compact and meaningful gene subsets, advancing biomarker discovery and single-cell analysis.
toXiv_bot_toot

As Cyber Threats Escalate, the National Vulnerability Database Is Falling Behind
The National Institute of Standards and Technology (NIST) is struggling.
It faces a growing backlog to process data in its vulnerability repository, which publicly shares information assessing and detailing mitigation solutions against new cyber exploits.
With nearly 1,800 new reported vulnerabilities sitting in a queue for analysis this year, delays in processing leave the United States increa…

Two new approaches to multiple canonical correlation analysis for repeated measures data
Tomasz G\'orecki, Miros{\l}aw Krzy\'sko, Felix Gnettner, Piotr Kokoszka
https://arxiv.org/abs/2510.04457

Two new approaches to multiple canonical correlation analysis for repeated measures data
In classical canonical correlation analysis (CCA), the goal is to determine the linear transformations of two random vectors into two new random variables that are most strongly correlated. Canonical variables are pairs of these new random variables, while canonical correlations are correlations between these pairs. In this paper, we propose and study two generalizations of this classical method: (1) Instead of two random vectors we study more complex data structures that appear in important …

Early Multimodal Prediction of Cross-Lingual Meme Virality on Reddit: A Time-Window Analysis
Sedat Dogan, Nina Dethlefs, Debarati Chakraborty
https://arxiv.org/abs/2510.05761 ht…

Early Multimodal Prediction of Cross-Lingual Meme Virality on Reddit: A Time-Window Analysis
Predicting the virality of online content remains challenging, especially for culturally complex, fast-evolving memes. This study investigates the feasibility of early prediction of meme virality using a large-scale, cross-lingual dataset from 25 diverse Reddit communities. We propose a robust, data-driven method to define virality based on a hybrid engagement score, learning a percentile-based threshold from a chronologically held-out training set to prevent data leakage. We evaluated a suite …

An analysis of 47,000 publicly shared ChatGPT conversations: ~10% related to emotional or mental health, ChatGPT exhibits a "default to yes" behavior, and more (Washington Post)
https://www.washingtonpost.com/technology/2025/11/12/how-people-use-ch…

We analyzed 47,000 ChatGPT conversations. Here’s what people really use it for.
What do people ask the popular chatbot? We analyzed thousands of chats to identify common topics discussed by users and patterns in ChatGPT’s responses.

Replaced article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- Universal emergence of local Zipf-Mandelbrot law
Davide Cugini, Andr\'e Timpanaro, Giacomo Livan, Giacomo Guarnieri

Efficient Mining of Low-Utility Sequential Patterns
Jian Zhu, Zhidong Lin, Wensheng Gan, Ruichu Cai, Zhifeng Hao, Philip S. Yu
https://arxiv.org/abs/2510.10243 https://

Efficient Mining of Low-Utility Sequential Patterns
Discovering valuable insights from rich data is a crucial task for exploratory data analysis. Sequential pattern mining (SPM) has found widespread applications across various domains. In recent years, low-utility sequential pattern mining (LUSPM) has shown strong potential in applications such as intrusion detection and genomic sequence analysis. However, existing research in utility-based SPM focuses on high-utility sequential patterns, and the definitions and strategies used in high-utility S…

Threat intel company Dataminr plans to acquire cybersecurity threat intel provider ThreatConnect for $290M; Dataminr raised $85M in convertible funding in March (Greg Otto/CyberScoop)
https://cyberscoop.com/dataminr-threatconnect-acquisition/

Dataminr to acquire cybersecurity firm ThreatConnect for $290 million
Dataminr, a New York-based company specializing in real-time threat intelligence, announced plans Tuesday to acquire ThreatConnect, a cybersecurity threat intelligence provider, for $290 million. The acquisition will combine Dataminr’s AI-powered analysis of public data with ThreatConnect’s internal threat management capabilities, creating what the companies describe as “Client-Tailored intelligence” that adapts to individual customer needs. The […]

Replaced article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- DeepOHeat-v1: Efficient Operator Learning for Fast and Trustworthy Thermal Simulation and Optimiz...
Xinling Yu, Ziyue Liu, Hai Li, Yixing Li, Xin Ai, Zhiyu Zeng, Ian Young, …

Crosslisted article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- Deep Learning of the Biswas-Chatterjee-Sen Model
Neto, Alencar, Brito, Alves, Lima, Macedo-Filho, Ferreira, Alves

Google adds Gemini's Deep Search to Google Finance, which will also have prediction market data from Kalshi and Polymarket for event analysis, first in the US (Aamir Siddiqui/Android Authority)
https://www.androidauthority.com/google-finance…

Google Finance wants to become your smartest investing assistant with these new features
Google Finance is getting Deep Search as well as prediction markets data from Kalshi and Polymarket, alongside an international expansion.

Replaced article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- Comparative Analysis of Richardson-Lucy Deconvolution and Data Unfolding with Mean Integrated Squ...
Nikolay D. Gagunashvili

Crosslisted article(s) found for physics.data-an. https://arxiv.org/list/physics.data-an/new
[1/1]:
- Functional Connectivity Networks for Transportation Delay Analysis: from Theory to Software
Carlson Moses B\"uth, Massimiliano Zanin

An analysis of 1,100 TikTok users' watch histories across six months in 2024 shows how effective TikTok is at getting even its heaviest users to watch more (Washington Post)

Spending hours on TikTok? Here’s how the app keeps you swiping.
Washington Post reporters analyzed data from over 800 TikTok users to learn how the app turns people into power users, some of whom spend hours per day scrolling.