Ominous warning for humanity as birds suddenly adopt'unsettling' behavior Meghan is accused of'giggling as model stumbles on the catwalk': More Paris Fashion Week disasters emerge, including awkward moment with Kristin Scott Thomas More girls are starting their periods younger than ever before - scientists think they've finally found what's causing it The TRUTH to the doting mother who slaughtered her children and husband told by those she'd been quietly tormenting for years Insiders confirm what everyone suspects about Taylor Swift and Blake Lively... the private apology... and how any future friendship hangs on one humiliating condition Outrage as Baltimore's Dem mayor spends $164k of taxpayer cash on ultra-luxurious new SUV I have no sympathy for them - but this disturbing new trend isn't the answer: JANA HOCKING Taylor Swift reveals truth behind raunchy song about Travis Kelce's manhood Trump stuns CNN reporter as he muses about Ghislaine Maxwell pardon: 'I haven't heard that name in so long' Revealed: Which slimming jab REALLY works best. The doctors' ultimate expert guide on which to pick, how to save money, beat every side effect... and what you need to know about the'golden dose' Functioning alcoholics hide in plain sight... so are YOU one? Trump brands NFL's Bad Bunny Super Bowl halftime show selection'absolutely ridiculous' The troubled background of delivery man stabbed by Mark Sanchez... as he launches million-dollar lawsuit and sparks civil war at Fox A huge asteroid came within 300 miles of hitting Earth, and scientists only noticed after it had already skimmed past the planet. The 9.8-foot (three metre) space rock, dubbed 2025 TF, flew over Antarctica in the early hours of October 1. Passing at an altitude of just 265 miles (428 kilometres), the rock came closer to the Earth's surface than the orbit of the International Space Station . However, space agencies only realised the near-miss had occurred when the asteroid was detected by the Catalina Sky Survey a few hours later.

With the remarkable development and widespread applications of large language models (LLMs), the use of machine-generated text (MGT) is becoming increasingly common. This trend brings potential risks, particularly to the quality and completeness of information in fields such as news and education. Current research predominantly addresses the detection of pure MGT without adequately addressing mixed scenarios including AI-revised Human-Written Text (HWT) or human-revised MGT. To confront this challenge, we introduce mixcase, a novel concept representing a hybrid text form involving both machine-generated and human-generated content. We collected mixcase instances generated from multiple daily text-editing scenarios and composed MixSet, the first dataset dedicated to studying these mixed modification scenarios. We conduct experiments to evaluate the efficacy of popular MGT detectors, assessing their effectiveness, robustness, and generalization performance. Our findings reveal that existing detectors struggle to identify mixcase as a separate class or MGT, particularly in dealing with subtle modifications and style adaptability. This research underscores the urgent need for more fine-grain detectors tailored for mixcase, offering valuable insights for future research. Code and Models are available at https://github.com/Dongping-Chen/MixSet.

The risk of collision between resident space objects has significantly increased in recent years. As a result, spacecraft collision avoidance procedures have become an essential part of satellite operations. To ensure safe and effective space activities, satellite owners and operators rely on constantly updated estimates of encounters. These estimates include the uncertainty associated with the position of each object at the expected TCA. These estimates are crucial in planning risk mitigation measures, such as collision avoidance manoeuvres. As the TCA approaches, the accuracy of these estimates improves, as both objects' orbit determination and propagation procedures are made for increasingly shorter time intervals. However, this improvement comes at the cost of taking place close to the critical decision moment. This means that safe avoidance manoeuvres might not be possible or could incur significant costs. Therefore, knowing the evolution of this variable in advance can be crucial for operators. This work proposes a machine learning model based on diffusion models to forecast the position uncertainty of objects involved in a close encounter, particularly for the secondary object (usually debris), which tends to be more unpredictable. We compare the performance of our model with other state-of-the-art solutions and a na\"ive baseline approach, showing that the proposed solution has the potential to significantly improve the safety and effectiveness of spacecraft operations.

Formal methods refer to rigorous, mathematical approaches to system development and have played a key role in establishing the correctness of safety-critical systems. The main building blocks of formal methods are models and specifications, which are analogous to behaviors and requirements in system design and give us the means to verify and synthesize system behaviors with formal guarantees. This monograph provides a survey of the current state of the art on applications of formal methods in the autonomous systems domain. We consider correct-by-construction synthesis under various formulations, including closed systems, reactive, and probabilistic settings. Beyond synthesizing systems in known environments, we address the concept of uncertainty and bound the behavior of systems that employ learning using formal methods. Further, we examine the synthesis of systems with monitoring, a mitigation technique for ensuring that once a system deviates from expected behavior, it knows a way of returning to normalcy. We also show how to overcome some limitations of formal methods themselves with learning. We conclude with future directions for formal methods in reinforcement learning, uncertainty, privacy, explainability of formal methods, and regulation and certification.

If you've watched a classic, landmark sci-fi movie and you were blown away by the quality and realism of its effects, then there's a good chance Douglas Trumbull's name is in the credits. The VFX pioneer, who passed away on February 8th, 2022, has worked on key films in the sci-fi canon. Even a short version of his resume would have to include 2001: A Space Odyssey, Close Encounters of the Third Kind, Star Trek: The Motion Picture, Blade Runner and Silent Running. To have worked on one of those in your lifetime would have been a big deal, but to have contributed to all of them speaks to just how much work Trumbull did to push the artform forward. Trumbull was the son of an artist and engineer, Donald Trumbull, who worked on VFX for The Wizard of Oz.

Uncertain partially observable Markov decision processes (uPOMDPs) allow the probabilistic transition and observation functions of standard POMDPs to belong to a so-called uncertainty set. Such uncertainty sets capture uncountable sets of probability distributions. We develop an algorithm to compute finite-memory policies for uPOMDPs that robustly satisfy given specifications against any admissible distribution. In general, computing such policies is both theoretically and practically intractable. We provide an efficient solution to this problem in four steps. (1) We state the underlying problem as a nonconvex optimization problem with infinitely many constraints. (2) A dedicated dualization scheme yields a dual problem that is still nonconvex but has finitely many constraints. (3) We linearize this dual problem and (4) solve the resulting finite linear program to obtain locally optimal solutions to the original problem. The resulting problem formulation is exponentially smaller than those resulting from existing methods. We demonstrate the applicability of our algorithm using large instances of an aircraft collision-avoidance scenario and a novel spacecraft motion planning case study.

Pilots can't spot drones as they approach a runway, warns a shock new study. They fail to catch sight of the flying gadgets 70 per cent of the time - even when they are in their airspace, according to the findings. And they almost never identify the machines if they are hovering motionless above the ground. The disturbing findings uncover a'real and present danger' to safety, warn US aviation experts. Study co author Dr Ryan Wallace, of Embry-Riddle Aeronautical University in the United States, said: 'Dangerous close encounters between aircraft and drones are becoming an increasingly common problem.

Last month, I had a kind of close encounter at the bank branch office . I didn't face an alien from another planet saying, "I come in peace". But I had a very strange situation confronting an artificial intelligent teller sucking my pay check in a blink of an eye, not letting me say one word. Maybe you think that I'm exaggerating a little or I just watched the movie 2001 A Space Odyssey for the first time. Maybe you're right, but let me tell you that it wasn't a pleasurable experience seeing a cold machine swallow my earnings for the whole month and then make a "beep" as an electronic digestion burp.

Last night I had a daily challenge pop up on my Fortnite: Battle Royale account asking me to eliminate four players with shotguns, and I haven't gotten to it yet. I think I may just wait for tomorrow, because shotguns will be readily available in the upcoming "Close Encounters" Limited Time Mode, which starts tomorrow, likely at 4:00 a.m. Close Encounters sounds a little bit like Tequila Sunrise, a limited time mode that ran in PlayerUnkown's Battlegrounds recently but with one major addition: Jetpacks. Weapon drops will be limited to shotguns, which were already one of the most popular weapon types in the game. Tactical and Pump Action shotguns will spawn as floor loot, with Heavy Shotguns and Jetpacks reserved for chests and supply drops. We assume that shells won't exactly be hard to come by.

Yesterday, Fortnite: Battle Royale finally got its jetpacks. For a little bit I thought Epic had abandoned the idea and folded the jetpack mechanic into the hop rocks it introduced alongside Season 4, but apparently they were still alive and waiting for the moment to hit the game. Jetpacks are part of a new loot category called backpacks: items that take up an inventory space but have some sort of persistent ability that's different from a regular weapon or consumable. They're chaotic fun, like the best Fortnite items: they have limited fuel and don't negate fall damage, so I managed to kill myself as soon as I grabbed one. Though in my defense I was already in the storm.