Terra Drone's Terra A1 interceptor drone has entered active combat use in Ukraine after being deployed to a military unit tasked with countering Russian uncrewed aerial systems. Japanese drone company Terra Drone said its Terra A1 interceptor -- developed with its Ukrainian partner Amazing Drones -- has moved from the lab to the front lines, entering active combat use in Ukraine against Russian-made Shahed drones. "Deployment for defense purposes has already begun with a military unit, and evaluation and feedback collection under actual operating conditions are currently under way," the Tokyo-based firm, which recently made a strategic investment in the Ukrainian startup, said in a recent statement. Terra Drone explained that this initial "real-world operational deployment" -- carried out via its local partner -- will follow a phased rollout, where new equipment is first issued to a single unit and then expanded to further deployments depending on evaluations from the field. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

Damped sinusoidal oscillations are widely observed in many physical systems, and their analysis provides access to underlying physical properties. However, parameter estimation becomes difficult when the signal decays rapidly, multiple components are superposed, and observational noise is present. In this study, we develop an autoencoder-based method that uses the latent space to estimate the frequency, phase, decay time, and amplitude of each component in noisy multi-component damped sinusoidal signals. We investigate multi-component cases under Gaussian-distribution training and further examine the effect of the training-data distribution through comparisons between Gaussian and uniform training. The performance is evaluated through waveform reconstruction and parameter-estimation accuracy. We find that the proposed method can estimate the parameters with high accuracy even in challenging setups, such as those involving a subdominant component or nearly opposite-phase components, while remaining reasonably robust when the training distribution is less informative. This demonstrates its potential as a tool for analyzing short-duration, noisy signals.

Patriot missile involved in Bahrain blast likely U.S.-operated, analysis finds Smoke rises following a strike on the Bapco Oil Refinery, amid the U.S.-Israeli conflict with Iran, on Sitra Island Bahrain, on March 9. | REUTERS An American-operated Patriot air defense battery likely fired the interceptor missile involved in a pre-dawn explosion that injured dozens of civilians and tore through homes in U.S.-ally Bahrain 10 days into the war on Iran, according to an analysis by academic researchers examined by Reuters. Both Bahrain and Washington have blamed an Iranian drone attack for the March 9 blast, which the Gulf kingdom said injured 32 people including children, some seriously. Commenting on the day of the attack, U.S. Central Command said on X that an Iranian drone struck a residential neighborhood in Bahrain. In response to questions, Bahrain on Saturday acknowledged for the first time that a Patriot missile was involved in the explosion over the Mahazza neighborhood on Sitra island, offshore from the capital Manama and also home to an oil refinery. In a statement, a Bahraini government spokesperson said the missile successfully intercepted an Iranian drone mid-air, saving lives. In a time of both misinformation and too much information, quality journalism is more crucial than ever.

This method allows API users to easily generate, discover, and mix and match image concepts without prior knowledge of how to prompt the model.

Given a query text, the similarity is determined bythemost similar prototype tofind correspondence inthevideo, which is termed text-adaptive matching.

Our regret bound generalizes that of GP-UCB [38] which always selects all variables, aswellasthatofDropout [21]whichselectsdvariables randomly ineachiteration.

However, because they are not identifiable without any assumptions, various assumptions have been utilized to evaluate the joint probabilities of potential outcomes, e.g., the assumption of monotonicity (Pearl, 2009; Tian and Pearl, 2000), the independence between potential outcomes (Robins and Richardson, 2011), the condition of gain equality (Li and Pearl, 2019), and the specific functional relationshipsbetween cause and effect (Pearl, 2009). Unlike existing identification conditions, in order to evaluate the joint probabilities of potential outcomeswithoutsuch assumptions,this paper proposestwo types of novel identification conditions using covariate information. In addition, when the joint probabilities of potential outcomes are identifiable through the proposed conditions, the estimation problem of the joint probabilities of potential outcomes reduces to that of singular models and thus they can not be evaluated by standard statistical estimation methods. To solve the problem,this paper proposes a new statisticalestimationmethod based on the augmented Lagrangianmethod and shows the asymptoticnormality of the proposed estimators. Given space constraints, the proofs, the details on the statistical estimationmethod, some numerical experiments, and the case study are provided in the supplementary material.