We present AgentZero++, an agent-based model that integrates cognitive, emotional, and social mechanisms to simulate decentralized collective violence in spatially distributed systems. Building on Epstein's Agent\_Zero framework, we extend the original model with eight behavioral enhancements: age-based impulse control; memory-based risk estimation; affect-cognition coupling; endogenous destructive radius; fight-or-flight dynamics; affective homophily; retaliatory damage; and multi-agent coordination. These additions allow agents to adapt based on internal states, previous experiences, and social feedback, producing emergent dynamics such as protest asymmetries, escalation cycles, and localized retaliation. Implemented in Python using the Mesa ABM framework, AgentZero++ enables modular experimentation and visualization of how micro-level cognitive heterogeneity shapes macro-level conflict patterns. Our results highlight how small variations in memory, reactivity, and affective alignment can amplify or dampen unrest through feedback loops. By explicitly modeling emotional thresholds, identity-driven behavior, and adaptive networks, this work contributes a flexible and extensible platform for analyzing affective contagion and psychologically grounded collective action.

NVIDIA CEO and co-founder Jensen Huang commends President Donald Trump's A.I. agenda and outlines what the country's job future will look like on'Special Report.' Classical and character-based education may seem to some antiquated concepts in the new AI-driven world. However, two recent and prominent AI developments definitively prove the opposite to be true. Going back to our nation's founding, great minds were universal in the belief that the survival of the Republic depended on an educated and virtuous public. Now, if AI experts are to be believed, classical and character education is fundamental to the very survival of humanity.

When you think of Nintendo, it's almost impossible not to picture Donkey Kong. Yet despite Donkers' undeniable place in gaming history – and obligatory appearances in Smash Bros and Mario Kart – for the last few console generations, Donkey Kong platformers have been MIA. Enter DK's first standalone adventure in 11 years, Donkey Kong Bananza. While Mario's recent adventures saw him exploring the reaches of outer space or deftly possessing enemies with an anthropomorphic hat, DK's grand return is all about primal rage. As you smash and punch your way through walls, floors and ceilings, you can burrow all the way to the ground below, forging new paths and unearthing hidden treasures.

A fragile ceasefire remains in place between Israel and Iran, one day after US President Donald Trump announced a truce, ending 12 days of fighting that erupted following Israeli strikes on Tehran's nuclear and military sites. An analysis of data from the Armed Conflict Location and Event Data Project (ACLED) shows that between October 7, 2023, and just before Israel attacked Iran on June 13, 2025, Israel carried out nearly 35,000 recorded attacks across five countries: the occupied Palestinian territory, Lebanon, Syria, Yemen, and Iran. These attacks include air and drone strikes, shelling and missile attacks, remote explosives, and property destruction. The majority of attacks have been on Palestinian territory with at least 18,235 recorded incidents, followed by Lebanon (15,520), Syria (616), Iran (58) and Yemen (39). While the bulk of Israel's attacks have concentrated on nearby Gaza, the occupied West Bank, and Lebanon, its military operations have also reached far beyond its immediate borders.

The most accurate clock in space launches within days and will begin building a highly synchronised network out of the best clocks on Earth. But the project, decades in preparation, will only operate for a few years before it burns up as the International Space Station deorbits at the end of the decade. NASA's most accurate atomic clock will be tested on a mission to Venus The Atomic Clock Ensemble in Space (ACES) is a European Space Agency (ESA) mission that will generate a time signal with unprecedented accuracy and then transmit it via laser to nine ground stations as it passes overhead at 27,000 kilometres per hour. This network of clocks will be in extremely close synchronisation and provide highly accurate timekeeping around the world. The result is that ACES will be able to test Einstein's theory of general relativity, which says that the passing of time is affected by the strength of gravity, with great accuracy.

Recent advancements in Neural Combinatorial Optimization (NCO) have shown promise in solving routing problems like the Traveling Salesman Problem (TSP) and Capacitated Vehicle Routing Problem (CVRP) without handcrafted designs. Research in this domain has explored two primary categories of methods: iterative and non-iterative. While non-iterative methods struggle to generate near-optimal solutions directly, iterative methods simplify the task by learning local search steps. However, existing iterative methods are often limited by restricted neighborhood searches, leading to suboptimal results. To address this limitation, we propose a novel approach that extends the search to larger neighborhoods by learning a destroy-and-repair strategy. Specifically, we introduce a Destroy-and-Repair framework based on Hyper-Graphs (DRHG). This framework reduces consecutive intact edges to hyper-edges, allowing the model to pay more attention to the destroyed part and decrease the complexity of encoding all nodes. Experiments demonstrate that DRHG achieves stateof-the-art performance on TSP with up to 10,000 nodes and shows strong generalization to real-world TSPLib and CVRPLib problems.

This month, humanity will learn just how close we are to annihilation. Every January, the Bulletin of the Atomic Scientists (BAS) sets a new time for the Doomsday Clock - the symbolic scale for humanity's proximity to the apocalypse. Last year, scientists left the clock sitting at 90 seconds to midnight - the closest humanity had come to destruction since the creation of the atomic bomb. But with war still raging in Ukraine and chaos across the Middle East, experts say that the risk of nuclear war is now'far too high'. Dr Haydn Belfield, research associate at the Centre for the Study of Existential Risk, told MailOnline: 'We are probably closer to nuclear war than at any point in the last forty years.'

In this paper, we propose TextDestroyer, the first training- and annotation-free method for scene text destruction using a pre-trained diffusion model. Existing scene text removal models require complex annotation and retraining, and may leave faint yet recognizable text information, compromising privacy protection and content concealment. TextDestroyer addresses these issues by employing a three-stage hierarchical process to obtain accurate text masks. Our method scrambles text areas in the latent start code using a Gaussian distribution before reconstruction. During the diffusion denoising process, self-attention key and value are referenced from the original latent to restore the compromised background. Latent codes saved at each inversion step are used for replacement during reconstruction, ensuring perfect background restoration. The advantages of TextDestroyer include: (1) it eliminates labor-intensive data annotation and resource-intensive training; (2) it achieves more thorough text destruction, preventing recognizable traces; and (3) it demonstrates better generalization capabilities, performing well on both real-world scenes and generated images.

Teams of mobile [aerial, ground, or aquatic] robots have applications in resource delivery, patrolling, information-gathering, agriculture, forest fire fighting, chemical plume source localization and mapping, and search-and-rescue. Robot teams traversing hazardous environments -- with e.g. rough terrain or seas, strong winds, or adversaries capable of attacking or capturing robots -- should plan and coordinate their trails in consideration of risks of disablement, destruction, or capture. Specifically, the robots should take the safest trails, coordinate their trails to cooperatively achieve the team-level objective with robustness to robot failures, and balance the reward from visiting locations against risks of robot losses. Herein, we consider bi-objective trail-planning for a mobile team of robots orienteering in a hazardous environment. The hazardous environment is abstracted as a directed graph whose arcs, when traversed by a robot, present known probabilities of survival. Each node of the graph offers a reward to the team if visited by a robot (which e.g. delivers a good to or images the node). We wish to search for the Pareto-optimal robot-team trail plans that maximize two [conflicting] team objectives: the expected (i) team reward and (ii) number of robots that survive the mission. A human decision-maker can then select trail plans that balance, according to their values, reward and robot survival. We implement ant colony optimization, guided by heuristics, to search for the Pareto-optimal set of robot team trail plans. As a case study, we illustrate with an information-gathering mission in an art museum.

This paper explores the potential of generative AI within interactive art, employing a practice-based research approach. It presents the interactive artwork "Visions of Destruction" as a detailed case study, highlighting its innovative use of generative AI to create a dynamic, audience-responsive experience. This artwork applies gaze-based interaction to dynamically alter digital landscapes, symbolizing the impact of human activities on the environment by generating contemporary collages created with AI, trained on data about human damage to nature, and guided by audience interaction. The transformation of pristine natural scenes into human-made and industrialized landscapes through viewer interaction serves as a stark reminder of environmental degradation. The paper thoroughly explores the technical challenges and artistic innovations involved in creating such an interactive art installation, emphasizing the potential of generative AI to revolutionize artistic expression, audience engagement, and especially the opportunities for the interactive art field. It offers insights into the conceptual framework behind the artwork, aiming to evoke a deeper understanding and reflection on the Anthropocene era and human-induced climate change. This study contributes significantly to the field of creative AI and interactive art, blending technology and environmental consciousness in a compelling, thought-provoking manner.