Oil prices have dropped following a report the US and Iran have reached a deal, subject to President Donald Trump's approval. Axios reported officials had made an agreement over an extended ceasefire on Thursday. It drove the price of a barrel of Brent crude down to a low of $93.36 from a earlier high of $98, before rebounding to about $94. Prices had jumped earlier after the US carried out new attacks on Iran, targeting a military site in Bandar Abbas, a strategic port city. The strikes occurred despite an ongoing ceasefire between Tehran and Washington to allow for talks to end the three-month-long war that has effectively closed the Strait of Hormuz waterway, pushing up global energy costs.

The US military has carried out new strikes on Iran, targeting a military site in Bandar Abbas, a strategic port city. US Central Command (Centcom) said its forces also shot down four Iranian one-way attack drones that posed a threat around the Strait of Hormuz. The site in Bandar Abbas was struck as it was about to launch a fifth drone, Centcom said. Iranian media reported that explosions were heard to the east of the city. The strikes come amid a fragile ceasefire between the US and Iran, and protracted negotiations to end the three-month war that has choked traffic in the Strait of Hormuz and shot up global energy prices.

Iran and U.S. trade airstrikes after Trump dismisses report of Hormuz deal DUBAI/WASHINGTON - Iran's Revolutionary Guard said on Thursday it targeted a U.S. airbase after the U.S. military carried out what a Washington official said were strikes targeting an Iranian drone operation near the Strait of Hormuz, hours after U.S. President Donald Trump rejected a report he was close to a compromise deal with Tehran. The escalation in hostilities highlighted threats to the tenuous ceasefire between the U.S. and Iran that took effect in early April, dampening hopes for a peace deal and sending oil prices surging again. A U.S. official, who requested anonymity to speak candidly about military operations, said the military shot down four Iranian attack drones and struck a ground control station in the port city of Bandar Abbas that was about to launch a fifth drone. In a time of both misinformation and too much information, quality journalism is more crucial than ever. By subscribing, you can help us get the story right. With your current subscription plan you can comment on stories.

Pope Leo XIV called Sunday for an immediate ceasefire in the war involving Iran, marking the pontiff's strongest remarks yet on conflict.

Iranian forces deploy explosive drone boats disguised as fishing vessels in Strait of Hormuz, defense expert Cameron Chell warns, marking new phase of hybrid warfare.

We devise an algorithm to generate sets of propositions that objectively instantiate graphs that support coherence-driven inference. We then benchmark the ability of large language models (LLMs) to reconstruct coherence graphs from (a straightforward transformation of) propositions expressed in natural language, with promising results from a single prompt to models optimized for reasoning. Combining coherence-driven inference with consistency evaluations by neural models may advance the state of the art in machine cognition.

Grading and quality control of Piarom dates, a premium and high-value variety cultivated predominantly in Iran, present significant challenges due to the complexity and variability of defects, as well as the absence of specialized automated systems tailored to this fruit. Traditional manual inspection methods are labor intensive, time consuming, and prone to human error, while existing AI-based sorting solutions are insufficient for addressing the nuanced characteristics of Piarom dates. In this study, we propose an innovative deep learning framework designed specifically for the real-time detection, classification, and grading of Piarom dates. Leveraging a custom dataset comprising over 9,900 high-resolution images annotated across 11 distinct defect categories, our framework integrates state-of-the-art object detection algorithms and Convolutional Neural Networks (CNNs) to achieve high precision in defect identification. Furthermore, we employ advanced segmentation techniques to estimate the area and weight of each date, thereby optimizing the grading process according to industry standards. Experimental results demonstrate that our system significantly outperforms existing methods in terms of accuracy and computational efficiency, making it highly suitable for industrial applications requiring real-time processing. This work not only provides a robust and scalable solution for automating quality control in the Piarom date industry but also contributes to the broader field of AI-driven food inspection technologies, with potential applications across various agricultural products.

Mussel farming is one of the most important aquaculture industries. The main risk to mussel farming is harmful algal blooms (HABs), which pose a risk to human consumption. In Galicia, the Spanish main producer of cultivated mussels, the opening and closing of the production areas is controlled by a monitoring program. In addition to the closures resulting from the presence of toxicity exceeding the legal threshold, in the absence of a confirmatory sampling and the existence of risk factors, precautionary closures may be applied. These decisions are made by experts without the support or formalisation of the experience on which they are based. Therefore, this work proposes a predictive model capable of supporting the application of precautionary closures. Achieving sensitivity, accuracy and kappa index values of 97.34%, 91.83% and 0.75 respectively, the kNN algorithm has provided the best results. This allows the creation of a system capable of helping in complex situations where forecast errors are more common.

You can become utterly dependent on a new glamorous technology, be it cyber-space, artificial intelligence. . . But does it create a potential achilles heel? Artificial intelligence (AI) has become the technical focal point for advancing naval and Department of Defense (DoD) capabilities. Secretary of the Navy Carlos Del Toro listed AI first among his priorities for innovating U.S. naval forces. Chief of Naval Operations Admiral Michael Gilday listed it as his top priority during his Senate confirmation hearing.2

TEHRAN - Iran's Revolutionary Guard shot down a U.S. surveillance drone Thursday in the Strait of Hormuz, marking the first time the Islamic Republic directly attacked the American military amid tensions over Tehran's unraveling nuclear deal with world powers. The two countries disputed the circumstances leading up to an Iranian surface-to-air missile bringing down the U.S. Navy RQ-4A Global Hawk, an unmanned aircraft with a wingspan larger than a Boeing 737 jetliner and costing over $100 million. Iran said the drone "violated" its territorial airspace, while the U.S. called the missile fire "an unprovoked attack" in international airspace over the narrow mouth of the Persian Gulf and President Donald Trump tweeted that "Iran made a very big mistake!" Trump later appeared to play down the incident, telling reporters in the Oval Office that he had a feeling that "a general or somebody" being "loose and stupid" made a mistake in shooting down the drone. The incident immediately heightened the crisis already gripping the wider region, which is rooted in Trump withdrawing the U.S. a year ago from Iran's 2015 nuclear deal and imposing crippling new sanctions on Tehran.