Welcome to Fox News' Politics newsletter with the latest political news from Washington D.C. and updates from the 2024 campaign trail. Both Former President Trump and Hunter Biden have accused the Justice Department of bringing politically biased charges. Trump, ahead of campaign stops in the battleground states of Michigan and Wisconsin, claimed Biden has "orchestrated" every lawsuit and indictment against him with the help of the Justice Department. "Please remember, ALL of these Lawsuits, Charges, and Indictments that have been brought against me have been orchestrated and coordinated by Crooked Joe Biden, the White House, and the DOJ, as an ATTACK ON CROOKED'S POLITICAL OPPONENT, ME," Trump posted on his Truth Social account Tuesday morning. Similarly, Hunter Biden's attorney blasted the decision by a federal judge who refused to dismiss tax charges against the first son, saying they will continue to fight the "abnormal way" Special Counsel David Weiss has handled the case.

Current and former U.S. officials expressed fears on Tuesday that Israel's airstrikes on an Iranian embassy compound in Syria could escalate hostilities in the region, and prompt retaliatory strikes against Israel and its American ally. The officials said the attack on Monday, which killed three generals in Iran's Quds Force and four other officers, had dealt a serious blow to the force, the external military and intelligence service of the Islamic Revolutionary Guards Corps. Ralph Goff, a former senior C.I.A. official who served in the Middle East, called Israel's strike "incredibly reckless." "It will only result in escalation by Iran and its proxies, which is very dangerous" to American troops in the region who could be targeted in retaliatory strikes by Tehran's proxies, Mr. Goff said. Indeed, after the Israeli strike in Damascus, Syria's capital, on Monday, American troops based in southeastern Syria knocked down an attack drone, a Defense Department official said.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. What do Lady Gaga, Barack Obama, Bill Gates, Paul McCartney and Justin Bieber have in common with Ronald Reagan, Jimi Hendrix, Judy Garland, Fidel Castro and David Bowie? They are all left-handed, a trait shared by roughly 10% of people. But why are some people left-handed while most are righties?

Video captures the moment and aftermath of what appears to be a drone, allegedly of Ukrainian origin, striking Russian drone production facility. Russian officials claimed that only a worker's dormitory was hit. A Ukrainian "plane-type UAV" on Tuesday struck a Russian weapons plant that allegedly assembled drones, causing an incredible fireball after impact. "This morning, the republic's industrial enterprises in Yelabuga and Nizhnekamsk were attacked by drones," Rustam Minnikhanov, the leader of Russia's autonomous Republic of Tatarstan, said in a post on his Telegram channel. "There is no serious damage, the technological process of the enterprises was not disrupted," Minnikhanov added.

The United States and Britain on Monday announced a new partnership on the science of artificial intelligence safety, amid growing concerns about upcoming next-generation versions. The US commerce secretary, Gina Raimondo, and British technology secretary, Michelle Donelan, signed a memorandum of understanding in Washington to work jointly to develop advanced AI model testing, following commitments announced at an AI safety summit in Bletchley Park in November. "We all know AI is the defining technology of our generation," Raimondo said. "This partnership will accelerate both of our institutes' work across the full spectrum to address the risks of our national security concerns and the concerns of our broader society." Under the formal partnership, Britain and the United States plan to perform at least one joint testing exercise on a publicly accessible model and are considering exploring personnel exchanges between the institutes.

A suspected Ukrainian drone struck a dormitory in Russia's Tatarstan region – sending fireballs into the air and people scattering. At least 7 people were injured in the attack that struck an industrial part of town, where a factory making Iranian-designed drones is reportedly located.

Russia's top security agency says it has seized dozens of kilos of explosives sent from Ukraine concealed in Orthodox Christian religious icons that had transited through the European Union. The seizure took place on Tuesday, following an inspection of cargo in the northwestern Pskov region near the Latvian border, the Federal Security Service (FSB) said in a statement. There was no immediate comment by Ukraine, which has been fighting off a Russian invasion since February 2022. The FSB said the cargo had passed through Romania, Hungary, Slovakia, Poland, Lithuania and Latvia, and comprised 70 kilos (154 pounds) of home-made explosives and explosive devices "hidden in icons and ready for use". One person was arrested, it continued, adding that it would seek to track down all those involved, including foreigners, who would then face legal proceedings in Russia.

OpenAI, Google, Anthropic and other companies developing generative AI are continuing to improve their technologies and releasing better and better large language models. In order to create a common approach for independent evaluation on the safety of those models as they come out, the UK and the US governments have signed a Memorandum of Understanding. Together, the UK's AI Safety Institute and its counterpart in the US, which was announced by Vice President Kamala Harris but has yet to begin operations, will develop suites of tests to assess the risks and ensure the safety of "the most advanced AI models." They're planning to share technical knowledge, information and even personnel as part of the partnership, and one of their initial goals seems to be performing a joint testing exercise on a publicly accessible model. UK's science minister Michelle Donelan, who signed the agreement, told The Financial Times that they've "really got to act quickly" because they're expecting a new generation of AI models to come out over the next year.

Friction is one of the cruxes of hydrodynamic modeling; flood conditions are highly sensitive to the Friction Factors (FFs) used to calculate momentum losses. However, empirical FFs are challenging to measure because they require laboratory experiments. Flood models often rely on surrogate observations (such as land use) to estimate FFs, introducing uncertainty. This research presents a laboratory-trained Deep Neural Network (DNN), trained using flume experiments with data augmentation techniques, to measure Manning's n based on Point Cloud data. The DNN was deployed on real-world lidar Point Clouds to directly measure Manning's n under regulatory and extreme storm events, showing improved prediction capabilities in both 1D and 2D hydrodynamic models. For 1D models, the lidar values decreased differences with regulatory models for in-channel water depth when compared to land cover values. For 1D/2D coupled models, the lidar values produced better agreement with flood extents measured from airborne imagery, while better matching flood insurance claim data for Hurricane Harvey. In both 1D and 1D/2D coupled models, lidar resulted in better agreement with validation gauges. For these reasons, the lidar measurements of Manning's n were found to improve both regulatory models and forecasts for extreme storm events, while simultaneously providing a pathway to standardize the measurement of FFs. Changing FFs significantly affected fluvial and pluvial flood models, while surge flooding was generally unaffected. Downstream flow conditions were found to change the importance of FFs to fluvial models, advancing the literature of friction in flood models. This research introduces a reliable, repeatable, and readily-accessible avenue to measure high-resolution FFs based on 3D point clouds, improving flood prediction, and removing uncertainty from hydrodynamic modeling.

This paper investigates the enhancement of financial time series forecasting with the use of neural networks through supervised autoencoders, aiming to improve investment strategy performance. It specifically examines the impact of noise augmentation and triple barrier labeling on risk-adjusted returns, using the Sharpe and Information Ratios. The study focuses on the S&P 500 index, EUR/USD, and BTC/USD as the traded assets from January 1, 2010, to April 30, 2022. Findings indicate that supervised autoencoders, with balanced noise augmentation and bottleneck size, significantly boost strategy effectiveness. However, excessive noise and large bottleneck sizes can impair performance, highlighting the importance of precise parameter tuning. This paper also presents a derivation of a novel optimization metric that can be used with triple barrier labeling. The results of this study have substantial policy implications, suggesting that financial institutions and regulators could leverage techniques presented to enhance market stability and investor protection, while also encouraging more informed and strategic investment approaches in various financial sectors.