Stocks from the United States to Japan have risen sharply amid hopes that an end to the longest US government shutdown in history is imminent. US lawmakers on Sunday moved to end a five-week impasse over government funding, a boost for investors unnerved by signs of growing weakness in the US economy and the sky-high evaluations of firms involved in artificial intelligence. The funding package still needs to win final approval in the Senate and then pass the US House of Representatives, after which it would go to US President Donald Trump for his signature - a process expected to take days. Stock markets in the Asia Pacific made large gains on Monday, while futures in the US also rose in advance of stock exchanges reopening. South Korea's benchmark KOSPI led the gains, rising about 3 percent as of 4pm local time (07:00 GMT).

Doctors from Scotland and the US have completed what is thought to be a world-first stroke procedure using a robot. Prof Iris Grunwald, of the University of Dundee, performed the remote thrombectomy - the removal of blood clots after a stroke - on a human cadaver that had been donated to medical science. The professor was at Ninewells Hospital in Dundee, while the body she was operating on while using the machine was across the city at the university. Hours later, Ricardo Hanel - a neurosurgeon in Florida - used the technology to carry out the first transatlantic surgery from his Jacksonville base on a human body in Dundee over 4,000 miles (6,400km) away. The team has called it a potential game changer if it becomes approved for use on patients.

A woman who was plunged into sudden menopause after surgery to remove both ovaries is spearheading efforts to change NHS policy. Kate Dyson, 44, from Hastings, East Sussex, underwent the surgery six months ago after having a subtotal hysterectomy in 2021 to remove her uterus - a procedure which leaves the cervix in place. The mum-of-three says she was completely unprepared for the impact of surgical menopause, which is triggered by both ovaries being removed. Honestly, it was like falling off a hormonal cliff edge, she told BBC Radio Sussex. Within hours of the surgery I was home the same day.

You probably don't give much thought to the device that you're reading this article on, as long as it looks good and keeps working. But the elements that power and run it are the subject of an escalating struggle between the world's two biggest economies - the US and China - with African countries in the eye of the storm. The African continent is rich in critical minerals and metals - like lithium, rare earths, cobalt and tungsten - which are vital to making and running our personal tech. Such materials are also essential for everything from electric vehicles, to AI data centres, and weapon systems. China has long been the biggest player in the global market for critical minerals and metals.

Creating programs to represent board games can be a time-consuming task. Large Language Models (LLMs) arise as appealing tools to expedite this process, given their capacity to efficiently generate code from simple contextual information. In this work, we propose a method to test how capable three LLMs (Claude, DeepSeek and ChatGPT) are at creating code for board games, as well as new variants of existing games.

Whole Slide Image (WSI) representation is critical for cancer subtyping, cancer recognition and mutation prediction.Training an end-to-end WSI representation model poses significant challenges, as a standard gigapixel slide can contain tens of thousands of image tiles, making it difficult to compute gradients of all tiles in a single mini-batch due to current GPU limitations. To address this challenge, we propose a method of dynamic residual encoding with slide-level contrastive learning (DRE-SLCL) for end-to-end WSI representation. Our approach utilizes a memory bank to store the features of tiles across all WSIs in the dataset. During training, a mini-batch usually contains multiple WSIs. For each WSI in the batch, a subset of tiles is randomly sampled and their features are computed using a tile encoder. Then, additional tile features from the same WSI are selected from the memory bank. The representation of each individual WSI is generated using a residual encoding technique that incorporates both the sampled features and those retrieved from the memory bank. Finally, the slide-level contrastive loss is computed based on the representations and histopathology reports ofthe WSIs within the mini-batch. Experiments conducted over cancer subtyping, cancer recognition, and mutation prediction tasks proved the effectiveness of the proposed DRE-SLCL method.

Implementing board games in code can be a time-consuming task. However, Large Language Models (LLMs) have been proven effective at generating code for domain-specific tasks with simple contextual information. We aim to investigate whether LLMs can implement digital versions of board games from rules described in natural language. This would be a step towards an LLM-assisted framework for quick board game code generation. We expect to determine the main challenges for LLMs to implement the board games, and how different approaches and models compare to one another. We task three state-of-the-art LLMs (Claude, DeepSeek and ChatGPT) with coding a selection of 12 popular and obscure games in free-form and within Boardwalk, our proposed General Game Playing API. We anonymize the games and components to avoid evoking pre-trained LLM knowledge. The implementations are tested for playability and rule compliance. We evaluate success rate and common errors across LLMs and game popularity. Our approach proves viable, with the best performing model, Claude 3.7 Sonnet, yielding 55.6\% of games without any errors. While compliance with the API increases error frequency, the severity of errors is more significantly dependent on the LLM. We outline future steps for creating a framework to integrate this process, making the elaboration of board games more accessible.

Is Trump losing patience with Putin? Will sanctions against Russian oil giants hurt Putin? Ukraine has hit back at Russia's attempts to disable its energy infrastructure with air strikes that succeeded in disrupting power and heating in two cities across the border. Alexander Gusev, regional governor of Voronezh, said several drones were electronically jammed over the city - home to more than one million people - and sparked a fire at a local utility facility that was quickly extinguished. A Russian Defence Ministry statement made no mention of either the Voronezh or Belgorod areas, reporting 44 Ukrainian drones were destroyed or intercepted by Russian forces during the night.

Is Trump losing patience with Putin? Will sanctions against Russian oil giants hurt Putin? The United Kingdom is sending military equipment and personnel to Belgium after a spate of disruptive drone sightings forced the temporary closures of two major airports. Air Chief Marshal Richard Knighton told the BBC network on Sunday that the military had agreed to "deploy our people, our equipment to Belgium to help them" after a request from Belgian authorities. In the past week, both Belgium's main international airport at Brussels and one of Europe's biggest cargo airports at Liege were forced to close temporarily because of drone incursions.

UK military personnel and equipment are being sent to Belgium to help it bolster its defences after drone incursions on its airspace, suspected of being carried out by Russia. The new head of the UK military, Sir Richard Knighton, told the BBC's Sunday with Laura Kuenssberg that his Belgian counterpart asked for assistance earlier this week and that kit and personnel were on the way. Belgium's main airport Zavantem was forced to close temporarily on Thursday night after drones were spotted nearby . They were also spotted in other locations, including a military base. Sir Richard said it was not known if the incursions were by Russia, but added it was plausible they had been ordered by Moscow.