Tootfinder

Dynamic allocation: extremes, tail dependence, and regime Shifts
Yin Luo, Sheng Wang, Javed Jussa
https://arxiv.org/abs/2506.12587 https://

Dynamic allocation: extremes, tail dependence, and regime Shifts
By capturing outliers, volatility clustering, and tail dependence in the asset return distribution, we build a sophisticated model to predict the downside risk of the global financial market. We further develop a dynamic regime switching model that can forecast real-time risk regime of the market. Our GARCH-DCC-Copula risk model can significantly improve both risk- and alpha-based global tactical asset allocation strategies. Our risk regime has strong predictive power of quantitative equity fac…

Military AI Cyber Agents (MAICAs) Constitute a Global Threat to Critical Infrastructure
Timothy Dubber, Seth Lazar
https://arxiv.org/abs/2506.12094 https:/…

Military AI Cyber Agents (MAICAs) Constitute a Global Threat to Critical Infrastructure
This paper argues that autonomous AI cyber-weapons - Military-AI Cyber Agents (MAICAs) - create a credible pathway to catastrophic risk. It sets out the technical feasibility of MAICAs, explains why geopolitics and the nature of cyberspace make MAICAs a catastrophic risk, and proposes political, defensive-AI and analogue-resilience measures to blunt the threat.

UN Global Risk Report
"The UN Global Risk Report identifies which risks are most important and for which risks we are least prepared."
site: https://unglobalriskreport.org/
or

VaxPulse: Active Global Vaccine Infodemic Risk Assessment
Gerardo Luis Dimaguila (Epidemiology Informatics, Centre for Health Analytics, Melbourne Children's Campus, Australia, Department of Paediatrics, The University of Melbourne, Australia), Muhammad Javed (Epidemiology Informatics, Centre for Health Analytics, Melbourne Children's Campus, Australia, Global Vaccine Data Network, University of Auckland, New Zealand), Jeremiah Munakabayo (Epidemiology Informatics, Centre for H…

VaxPulse: Active Global Vaccine Infodemic Risk Assessment
Vaccine infodemics, driven by misinformation, disinformation, and inauthentic online behaviours, pose significant threats to global public health. This paper presents our response to this challenge, demonstrating how we developed VaxPulse Vaccine Infodemic Risk Assessment Lifecycle (VIRAL), an AI-powered social listening platform designed to monitor and assess vaccine-related infodemic risks. Leveraging interdisciplinary expertise and international collaborations, VaxPulse VIRAL integrates mach…

Science at Risk: The Urgent Need for Institutional Support of Long-Term Ecological and Evolutionary Research in an Era of Data Manipulation and Disinformation
Vincent A. Viblanc (UMR ISEM), Elise Huchard (UMR ISEM), Gilles Pinay (CEFE), Elena Orme\~no (CEFE), C\'eline Teplitsky (CEFE), Fran\c{c}ois Criscuolo (IGE), Dominique Joly (IGE), David Renault (IGE), C\'ecile Callou (IGE), Fran\c{c}oise Gourmelon (IGE), Sandrine Anquetin (IGE), B\'en\'edicte Augeard (OFB), Fabien…

Science at Risk: The Urgent Need for Institutional Support of Long-Term Ecological and Evolutionary Research in an Era of Data Manipulation and Disinformation
Planet Earth and the biodiversity it supports are in crisis. Human impact on terrestrial, marine and freshwater ecosystems and the hundreds of thousands of organisms that inhabit them is global. To what extent can we push ecosystems before they collapse? Will species adapt to these changes and at what rate? What are the consequences, for the environment and humankind? These are some of the most pressing issues to date. Clear answers can only be addressed through long-term research programs that…

Machine Learning based Enterprise Financial Audit Framework and High Risk Identification
Tingyu Yuan, Xi Zhang, Xuanjing Chen
https://arxiv.org/abs/2507.06266

Machine Learning based Enterprise Financial Audit Framework and High Risk Identification
In the face of global economic uncertainty, financial auditing has become essential for regulatory compliance and risk mitigation. Traditional manual auditing methods are increasingly limited by large data volumes, complex business structures, and evolving fraud tactics. This study proposes an AI-driven framework for enterprise financial audits and high-risk identification, leveraging machine learning to improve efficiency and accuracy. Using a dataset from the Big Four accounting firms (EY, Pw…

Balancing Profit and Fairness in Risk-Based Pricing Markets
Jesse Thibodeau, Hadi Nekoei, Afaf Ta\"ik, Janarthanan Rajendran, Golnoosh Farnadi
https://arxiv.org/abs/2506.00140

Balancing Profit and Fairness in Risk-Based Pricing Markets
Dynamic, risk-based pricing can systematically exclude vulnerable consumer groups from essential resources such as health insurance and consumer credit. We show that a regulator can realign private incentives with social objectives through a learned, interpretable tax schedule. First, we provide a formal proposition that bounding each firm's \emph{local} demographic gap implicitly bounds the \emph{global} opt-out disparity, motivating firm-level penalties. Building on this insight we introduce …

Investment Risk for Energy Infrastructure Construction Is Highest for #NuclearPower Plants, Lowest for #Solar

Investment Risk for Energy Infrastructure Construction Is Highest for Nuclear Power Plants, Lowest for Solar - CleanTechnica
A new study from the Boston University Institute for Global Sustainability finds that construction costs run over budget for more than 60% of energy infrastructure projects worldwide. By Laura Hurley Between now and 2050, the International Energy Agency projects that more than $100 trillion will be spent on building net-zero energy infrastructure globally. ... [continued]

This https://arxiv.org/abs/2506.00140 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csAI_…

Balancing Profit and Fairness in Risk-Based Pricing Markets
Dynamic, risk-based pricing can systematically exclude vulnerable consumer groups from essential resources such as health insurance and consumer credit. We show that a regulator can realign private incentives with social objectives through a learned, interpretable tax schedule. First, we provide a formal proposition that bounding each firm's \emph{local} demographic gap implicitly bounds the \emph{global} opt-out disparity, motivating firm-level penalties. Building on this insight we introduce …

Watermarking Without Standards Is Not AI Governance
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
https://arxiv.org/abs/2505.23814 https://

Watermarking Without Standards Is Not AI Governance
Watermarking has emerged as a leading technical proposal for attributing generative AI content and is increasingly cited in global governance frameworks. This paper argues that current implementations risk serving as symbolic compliance rather than delivering effective oversight. We identify a growing gap between regulatory expectations and the technical limitations of existing watermarking schemes. Through analysis of policy proposals and industry practices, we show how incentive structures di…

This https://arxiv.org/abs/2407.14272 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_qfi…

Global Balance and Systemic Risk in Financial Correlation Networks
The global balance index is used in the network literature to quantify how balanced a signed network is. In this paper we show that the global balance index of financial correlation networks can be used as a systemic risk measure. We define the global balance index of a network starting from a diffusive process that describes how the information spreads across nodes in a network, providing an alternative derivation to the usual combinatorial one. The steady state of this process is the solution…

DuAL-Net: A Hybrid Framework for Alzheimer's Disease Prediction from Whole-Genome Sequencing via Local SNP Windows and Global Annotations
Eun Hye Lee, Taeho Jo
https://arxiv.org/abs/2506.00673

DuAL-Net: A Hybrid Framework for Alzheimer's Disease Prediction from Whole-Genome Sequencing via Local SNP Windows and Global Annotations
Alzheimer's disease (AD) dementia is the most common form of dementia. With the emergence of disease-modifying therapies, predicting disease risk before symptom onset has become critical. We introduce DuAL-Net, a hybrid deep learning framework for AD dementia prediction using whole genome sequencing (WGS) data. DuAL-Net integrates two components: local probability modeling, which segments the genome into non-overlapping windows, and global annotation-based modeling, which annotates SNPs and reo…

Toward a Global Regime for Compute Governance: Building the Pause Button
Ananthi Al Ramiah, Raymond Koopmanschap, Josh Thorsteinson, Sadruddin Khan, Jim Zhou, Shafira Noh, Joep Meindertsma, Farhan Shafiq
https://arxiv.org/abs/2506.20530

Toward a Global Regime for Compute Governance: Building the Pause Button
As AI capabilities rapidly advance, the risk of catastrophic harm from large-scale training runs is growing. Yet the compute infrastructure that enables such development remains largely unregulated. This paper proposes a concrete framework for a global "Compute Pause Button": a governance system designed to prevent dangerously powerful AI systems from being trained by restricting access to computational resources. We identify three key intervention points -- technical, traceability, and regulat…

VisText-Mosquito: A Multimodal Dataset and Benchmark for AI-Based Mosquito Breeding Site Detection and Reasoning
Md. Adnanul Islam, Md. Faiyaz Abdullah Sayeedi, Md. Asaduzzaman Shuvo, Muhammad Ziaur Rahman, Shahanur Rahman Bappy, Raiyan Rahman, Swakkhar Shatabda
https://arxiv.org/abs/2506.14629

VisText-Mosquito: A Multimodal Dataset and Benchmark for AI-Based Mosquito Breeding Site Detection and Reasoning
Mosquito-borne diseases pose a major global health risk, requiring early detection and proactive control of breeding sites to prevent outbreaks. In this paper, we present VisText-Mosquito, a multimodal dataset that integrates visual and textual data to support automated detection, segmentation, and reasoning for mosquito breeding site analysis. The dataset includes 1,828 annotated images for object detection, 142 images for water surface segmentation, and natural language reasoning texts linked…

Detection, attribution, and modeling of climate change: key open issues
Nicola Scafetta
https://arxiv.org/abs/2506.13994 https://arxi…

Detection, attribution, and modeling of climate change: key open issues
The CMIP global climate models (GCMs) assess that nearly 100% of global surface warming observed between 1850-1900 and 2011-2020 is attributable to anthropogenic drivers like greenhouse gas emissions. These models also generate future climate projections based on shared socioeconomic pathways (SSPs), aiding in risk assessment and the development of costly Net-Zero climate mitigation strategies. Yet, the CMIP GCMs face significant scientific challenges in attributing and modeling climate change,…

How Viable are Energy Savings in Smart Homes? A Call to Embrace Rebound Effects in Sustainable HCI
Christina Bremer, Harshit Gujral, Michelle Lin, Lily Hinkers, Christoph Becker, Vlad C. Coroam\u{a}
https://arxiv.org/abs/2506.14653

How Viable are Energy Savings in Smart Homes? A Call to Embrace Rebound Effects in Sustainable HCI
As part of global climate action, digital technologies are seen as a key enabler of energy efficiency savings. A popular application domain for this work is smart homes. There is a risk, however, that these efficiency gains result in rebound effects, which reduce or even overcompensate the savings. Rebound effects are well-established in economics, but it is less clear whether they also inform smart energy research in other disciplines. In this paper, we ask: to what extent have rebound effects…

Identifying High-Risk Areas for Traffic Collisions in Montgomery, Maryland Using KDE and Spatial Autocorrelation Analysis
Stanislav Liashkov
https://arxiv.org/abs/2506.21930

Identifying High-Risk Areas for Traffic Collisions in Montgomery, Maryland Using KDE and Spatial Autocorrelation Analysis
Despite a global decline in motor vehicle crash fatalities due to improved research and road safety policies, road traffic injuries remain a significant public health concern. The World Health Organization 2023 report highlights that road traffic injuries are the leading cause of death among individuals aged 5-29, with over half of fatalities involving pedestrians, cyclists, and motorcyclists. This study addresses this critical issue by identifying high-risk areas in Montgomery County, Maryland…

Testing Paradox May Explain Increased Observed Prevalence of Bacterial STIs among MSM on HIV PrEP: A Modeling Study
Laura M\"uller, Piklu Mallick, Antonio B. Mar\'in-Carballo, Philipp D\"onges, Robyn J. N. Kettlitz, Carolina J. Klett-Tammen, Mirjam Kretzschmar, Viola Priesemann, Seba Contreras
https://arxiv.org/abs…

Testing Paradox May Explain Increased Observed Prevalence of Bacterial STIs among MSM on HIV PrEP: A Modeling Study
HIV pre-exposure Prophylaxis (PrEP) has become essential for global HIV control, but its implementation coincides with rising bacterial STI rates among men who have sex with men (MSM). While risk-compensation behavioral changes like reduced condom use are frequently reported, we examine whether intensified asymptomatic screening in PrEP programs creates surveillance artifacts that could be misinterpreted. We developed a compartmental model to represent the simultaneous spread of HIV and chlamyd…

Bayesian Hybrid Machine Learning of Gallstone Risk
Chitradipa Chakraborty, Nayana Mukherjee
https://arxiv.org/abs/2506.14561 https://…

Bayesian Hybrid Machine Learning of Gallstone Risk
Gallstone disease is a complex, multifactorial condition with significant global health burdens. Identifying underlying risk factors and their interactions is crucial for early diagnosis, targeted prevention, and effective clinical management. Although logistic regression remains a standard tool for assessing associations between predictors and gallstone status, it often underperforms in high-dimensional settings and may fail to capture intricate relationships among variables. To address these …

Today in “silly billboards in my community”. The first is by the very “truthful” (/s) people at LNGfacts.ca. Of course, the word "LNGfacts" does not appear anywhere in the dictionary because it's made up nonsense. Just like the "fact" that LNG “makes Canada stronger”... like we're going to win the war in Ukraine with our LNG or fend off #TheAmericanFascist. (Note: LNG is a tool of fascists not the other way around)
This billboard used to say “BC LNG WILL REDUCE GLOBAL EMISSIONS”... with a link to ‘bclnghelps.ca' but that was so clearly a lie that they were forced by the courts to remove it and delete their website, but I made a website instead in their honour called: bclngburns.ca
Back to today's billbboard though... Here's a fact from February 2025: “European LNG imports fell by 19% in 2024 as gas consumption reached an 11-year low, thanks, in part, to renewable energy additions.” (#BCPoli #BCLNG #ClimateAction #ClimateEmergency #ExtinctionRebellion #LNG #NaturalGas #Europe #EU #Ukraine #Russia