If a major disaster like Fukushima or Chernobyl ever happens again, the world would know almost straight away, thanks to an array of government and DIY radiation-monitoring programs running globally.

Russia has accused Ukraine of carrying out a drone attack on a nuclear plant that has caused a fire and damage to an auxiliary transformer as Ukraine celebrates its Independence Day for the 34th time. Sunday's attack forced a 50 percent reduction in the operating capacity at reactor number three at the Kursk Nuclear Power Plant (NPP), close to the border with Ukraine, according to Russian officials, who added that several power and energy facilities were targeted in the overnight strikes. The fire at the nuclear facility was quickly extinguished with no injuries reported, the plant's news service said on Telegram. Two other reactors are operating without power generation, and one is undergoing scheduled repairs, it said, adding that radiation levels were normal. Alexander Khinshtein, the Kursk region's acting governor, said Ukrainian attacks on the plant, 60km (38 miles) from the Russia-Ukraine border, "are a threat to nuclear safety and a violation of all international conventions".

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. An alleged drone struck the protective shell covering the Chernobyl Nuclear Power Plant in Ukraine early Friday, and Ukrainian President Volodymyr Zelenskyy is pointing the finger at Russia. The International Atomic Energy Agency reported on X that overnight Thursday, the IAEA team at the Chornobyl site heard an explosion coming from the New Safe Confinement. The site protects the remains of the nuclear reactor that exploded in Chernobyl in 1986 and was reportedly set ablaze after an unmanned aerial vehicle (UAV) struck the NSC roof.

Ukrainian President Volodymyr Zelenskyy said Friday that a Russian drone had struck a cover built to contain radiation at the Chernobyl nuclear power plant, adding that "radiation levels have not increased." The Ukrainian air force said that Russia had launched more than 100 drones across the country overnight -- including attack drones -- targeting northern regions of the country where the Chernobyl power plant lies. "Last night, a Russian attack drone with a high-explosive warhead struck the cover protecting the world from radiation at the destroyed 4th power unit of the Chernobyl Nuclear Power Plant," Zelenskyy said in a social media post. The International Atomic Energy Agency also reported an "explosion" at the site, and said "radiation levels inside and outside remain normal and stable." The agency, which has had a team deployed on the site since the early stages of Russia's invasion of Ukraine, published images apparently showing the drone on fire after crashing into the covering.

Extended human presence beyond low-Earth orbit (BLEO) during missions to the Moon and Mars will pose significant challenges in the near future. A primary health risk associated with these missions is radiation exposure, primarily from galatic cosmic rays (GCRs) and solar proton events (SPEs). While GCRs present a more consistent, albeit modulated threat, SPEs are harder to predict and can deliver acute doses over short periods. Currently NASA utilizes analytical tools for monitoring the space radiation environment in order to make decisions of immediate action to shelter astronauts. However this reactive approach could be significantly enhanced by predictive models that can forecast radiation exposure in advance, ideally hours ahead of major events, while providing estimates of prediction uncertainty to improve decision-making. In this work we present a machine learning approach for forecasting radiation exposure in BLEO using multimodal time-series data including direct solar imagery from Solar Dynamics Observatory, X-ray flux measurements from GOES missions, and radiation dose measurements from the BioSentinel satellite that was launched as part of Artemis 1 mission. To our knowledge, this is the first time full-disk solar imagery has been used to forecast radiation exposure. We demonstrate that our model can predict the onset of increased radiation due to an SPE event, as well as the radiation decay profile after an event has occurred.

However, since the energy upgrade, CEBAF has suffered from significant FE induced radiation. With RF on, dose Jefferson Lab's Continuous Electron Beam Accelerator rates observed at 30 cm from the beamline are as high Facility (CEBAF) [1] relies on two superconducting as 10 rem/h and 100 rem/h for neutron and gamma radiation, radio-frequency linear accelerators (SRF linacs) to deliver respectively. This level of radiation causes significant high-energy electron beams to nuclear physics experiments damage to beamline components, including vacuum in the four experimental halls [2]. An integral valves, magnets, and cables of beam position monitors part of these linacs are cryomodules which contain and ion pumps. Replacing these components can use multiple SRF cavities. These SRF cavities provide the significant resources. Worse, portions of both linacs are main accelerating gradients to the electron beam, and considered "Radiation Areas" for days or even weeks into currently produce the 12 GeV beam necessary for scientific scheduled downtime, limiting maintenance activities to discovery.

Nuclear radiation (NR), which refers to the energy emitted from atomic nuclei during decay, poses substantial risks to human health and environmental safety. Accurate forecasting of nuclear radiation levels is crucial for informed decision-making by both individuals and governments. However, this task is challenging due to the imbalanced distribution of monitoring stations over a wide spatial range and the non-stationary radiation variation patterns. In this study, we introduce NRFormer, an innovative framework tailored for national-wide prediction of nuclear radiation variations. By integrating a non-stationary temporal attention module, an imbalance-aware spatial attention module, and a radiation propagation prompting module, NRFormer collectively captures complex spatio-temporal dynamics of nuclear radiation. Extensive experiments on two real-world datasets demonstrate the superiority of our proposed framework against seven baselines. This research not only enhances the accuracy and reliability in nuclear radiation forecasting but also contributes to advancing emergency response strategies and monitoring systems, thereby safeguarding environmental and public health.

NASA's Orion spacecraft arrived at the moon yesterday after travelling some 230,000 miles (370,000km) in five days. The capsule zoomed over the landing sites of Apollo 11, 12 and 14 as it came within 80 miles (130km) of the lunar surface. But now it is circling the moon, what exactly will it be doing for the next 10 days before it heads home? As you'd expect there are a multitude of science experiments NASA is carrying out, including checking radiation levels, seeing how'space seeds' behave and monitoring a dummy called Commander Moonikin to see how he is coping with the journey. Artemis I will not only fly farther than any spacecraft built for humans - around 40,000 miles (64,000km) beyond the far side of the moon - it will also stay in space the longest without docking to a space station, and return home faster and hotter than ever before.

Japan's catastrophic Fukushima disaster in 2011 has resulted in a unique species of boar-pig, a new study reveals. Researchers investigating the effects of the nuclear disaster on animals in the area report that radiation has had no adverse effects on their genetics. However, wild boars (Sus scrofa leucomystax) have proliferated in the area, after being left to roam freely from the lack of humans. The boars have bred with domestic pigs (Sus scrofa domesticus) that escaped from nearby properties after farmers had to flee, creating a new hybrid species. Rare spotted wild boar observed inside the evacuated area of Fukushima, Japan, indicative of the'introgression' - the transfer of genetic information from one species to another - with domestic pigs Images from remotely-operated cameras indicate wildlife is flourishing in Fukushima's exclusion zone. Wildlife ecologist James Beasley of the University of Georgia and colleagues used a network of 106 remote cameras to capture images of the wildlife in the area over a four-month period.

If there's one thing a hospital patient doesn't want to think about as they prepare for a medical scan it's the possibility a cyberattacker might have found a way to remotely tamper with the diagnostic images, or even quietly upped the radiation levels used to generate them. The good news is that nobody has ever been confirmed to have done such a thing to a computed tomography (CT) X-ray scanner, which along with MRI (magnetic resonance imaging) and ultrasound systems form the backbone of modern hospital diagnosis. There is a caveat of course – the moment when somebody tries must be growing closer, leaving researchers searching for a reliable way to head off the troubling possibilities. Now a team at Israel's famous Ben-Gurion University of the Negev thinks it has come up with a solution to the problem of defending medical imaging devices (MIDs) using an AI system trained with families of open source algorithms to monitor commands sent to CT scanners for something that doesn't look right. In a proof of concept study due to be published this month, this splits the AI defense into a context-free (CF) layer that filters for obviously suspect commands (an excessive radiation level, say), and a more sophisticated context-sensitive (CS) layer that compares an apparently legitimate command to the medical context in which it is being used (giving a child an adult radiation dose).