To play this video you need to enable JavaScript in your browser. The Nepali army has been working to rescue survivors who had been trapped inside a tunnel at a hydropower project in Rasuwa. Footage shared by the country's prime minister office shows soliders carrying survivors and crawling across thick slates of mud to reach others. An update issued by officials on Thursday indicated more than 100 people were estimated to have been trapped in the same tunnel. It forms part of rescue efforts being carried out across the country in the wake of the deadly flood as local police said the Nepal death toll reached 475 on Friday.

You're viewing the US edition You can switch to the UK or AU homepage at any time using this menu. Trump's CIA chief John Ratcliffe makes surprise trip to Moscow for secret meeting amid grim fears for Poland Hoover Dam's horror threat to 40 million Americans: As'tipping point' is reached... expert warns residents in THREE states to brace There's only one way Harry and Meghan's new royal life in Britain can work... and she's going to hate it: ROBERT JOBSON The photos that sparked wild internet rumours: James Blunt mingles with Hayden Panettiere on a yacht in 2009 after he broke his silence on claims he was the'British singer' who the late actress was put into bed with aged 18 Lindsay Clancy's lawyer clashes with witness as tensions reach fever pitch after exploding at reporter outside: Live updates Vanity Fair journalist covering Lindsay Clancy trial sparks outrage for SMILING on camera as she says'I'm proud of myself' in face of backlash ALEXANDRA SHULMAN: Emotionally battered, physically scarred... and I've put on weight. But I'm still in my bikini at 68, and this is why you should follow my lead Hollywood's nepo babies take over Vanity Fair's best dressed list: North West, Beyoncé's eldest Blue Ivy and Meryl Streep's daughter land top spots Your next new car could cost up to $6,000 more if President Trump's 50% tariff on Canada goes into effect Brand-new penis enlargement technique increased this man's size by a THIRD in just 45 minutes... he bares all and reveals results that've left him thrilled The 10-cent supplement that turbocharges your Mounjaro AND reduces your cholesterol: Most patients won't have heard of it, but now experts reveal why anyone on jabs must take it - and how it can stop you putting weight back on Renters rejoice as feds put an end to Zillow's $100M plot to neuter rival Redfin and eliminate rental market competition Brian Hickerson's dark family secrets outed by his own sister... who reveals moment his'demons' took over... and real reason Hayden Panettiere kept going back Woke Boston mayor goes on fever-pitched hunt to track down and threaten business owners renting parking spots to ICE agents in her city: 'This is unhinged' Lawyers for Anna Kepner's stepbrother make desperate bid to delay murder trial as they grapple with'unique and very unfortunate' evidence into Carnival cruise death Prince Harry and Meghan are'not the same people who left' and'relate to Britain differently', says Omid Scobie I left a sexless marriage at 54. Now, I'm having the time of my life with men in their 20s and 30s. This is what they all love about me...and why I'll still keep having our sleepovers in hotel rooms The Bible describes Jesus' burial place as a tomb carved into rock, set inside a garden near where he was crucified. For nearly 1,700 years, Christians have believed that tomb lies within Jerusalem's Church of the Holy Sepulchre.

You're viewing the US edition You can switch to the UK or AU homepage at any time using this menu. Enes Kanter Freedom hits back at'terrified' WNBA as he learns draft fate after ex-NBA star was ejected from game over explosive courtside clash Brian Hickerson's dark family secrets outed by his own sister... who reveals moment his'demons' took over... and real reason Hayden Panettiere kept going back His penis grew by a THIRD in minutes after game-changing new enlargement method... now thrilled patient bares all and declares: 'My phone's already buzzing' The 10-cent supplement that turbocharges your Mounjaro AND reduces your cholesterol: Most patients won't have heard of it, but now experts reveal why anyone on jabs must take it - and how it can stop you putting weight back on Canada threatens to cut off US electricity as Trump's trade war with Mark Carney spirals into fresh crisis: 'You better have batteries' Distressing audio reveals moment doctor's husband who left daughter, 2, to ...

As the world looks to incorporate more renewables into energy grids, centuries-old systems that can balance supply and demand are being reappraised and innovated upon.

Hydro-Science and Engineering (Hydro-SE) is a critical and irreplaceable domain that secures human water supply, generates clean hydropower energy, and mitigates flood and drought disasters. Featuring multiple engineering objectives, Hydro-SE is an inherently interdisciplinary domain that integrates scientific knowledge with engineering expertise. This integration necessitates extensive expert collaboration in decision-making, which poses difficulties for intelligence. With the rapid advancement of large language models (LLMs), their potential application in the Hydro-SE domain is being increasingly explored. However, the knowledge and application abilities of LLMs in Hydro-SE have not been sufficiently evaluated. To address this issue, we propose the Hydro-SE LLM evaluation benchmark (Hydro-SE Bench), which contains 4,000 multiple-choice questions. Hydro-SE Bench covers nine subfields and enables evaluation of LLMs in aspects of basic conceptual knowledge, engineering application ability, and reasoning and calculation ability. The evaluation results on Hydro-SE Bench show that the accuracy values vary among 0.74 to 0.80 for commercial LLMs, and among 0.41 to 0.68 for small-parameter LLMs. While LLMs perform well in subfields closely related to natural and physical sciences, they struggle with domain-specific knowledge such as industry standards and hydraulic structures. Model scaling mainly improves reasoning and calculation abilities, but there is still great potential for LLMs to better handle problems in practical engineering application. This study highlights the strengths and weaknesses of LLMs for Hydro-SE tasks, providing model developers with clear training targets and Hydro-SE researchers with practical guidance for applying LLMs.

Many real-world problems (e.g., resource management, autonomous driving, drug discovery) require optimizing multiple, conflicting objectives. Multi-objective reinforcement learning (MORL) extends classic reinforcement learning to handle multiple objectives simultaneously, yielding a set of policies that capture various trade-offs. However, the MORL field lacks complex, realistic environments and benchmarks. We introduce a water resource (Nile river basin) management case study and model it as a MORL environment. We then benchmark existing MORL algorithms on this task. Our results show that specialized water management methods outperform state-of-the-art MORL approaches, underscoring the scalability challenges MORL algorithms face in real-world scenarios.

Information extraction from regulatory documents using large language models presents critical trade-offs between performance and computational resources. We evaluated seven open-weight models (0.6B-70B parameters) on hydropower licensing documentation to provide empirical deployment guidance. Our analysis identified a pronounced 14B parameter threshold where validation methods transition from ineffective (F1 $<$ 0.15) to viable (F1 = 0.64). Consumer-deployable models achieve 64\% F1 through appropriate validation, while smaller models plateau at 51\%. Large-scale models approach 77\% F1 but require enterprise infrastructure. We identified systematic hallucination patterns where perfect recall indicates extraction failure rather than success in smaller models. Our findings establish the first comprehensive resource-performance mapping for open-weight information extraction in regulatory contexts, enabling evidence-based model selection. These results provide immediate value for hydropower compliance while contributing insights into parameter scaling effects that generalize across information extraction tasks.

Reinforcement learning (RL) can refine the reasoning abilities of large language models (LLMs), but critically depends on a key prerequisite: the LLM can already generate high-utility reasoning paths with non-negligible probability. For tasks beyond the LLM's current competence, such reasoning path can be hard to sample, and learning risks reinforcing familiar but suboptimal reasoning. We are motivated by the insight from cognitive science that Why is this the answer is often an easier question than What is the answer, as it avoids the heavy cognitive load of open-ended exploration, opting instead for explanatory reconstruction-systematically retracing the reasoning that links a question to its answer. We show that LLMs can similarly leverage answers to derive high-quality reasoning paths. We formalize this phenomenon and prove that conditioning on answer provably increases the expected utility of sampled reasoning paths, thereby transforming intractable problems into learnable ones. Building on this insight, we introduce RAVR (Reference-Answer-guided Variational Reasoning), an end-to-end framework that uses answer-conditioned reasoning as a variational surrogate for question-only reasoning. Experiments in both general and math domains demonstrate consistent improvements over strong baselines. We further analyze the reasoning behavior and find that RAVR reduces hesitation, strengthens conclusion consolidation, and promotes problem-specific strategies in reasoning.

Gabriela Cibils is on a mission - to help turn Paraguay into the Silicon Valley of South America. When she was growing up in the landlocked country, nestled between Brazil and Argentina, she says the nation wasn't super tech focused. But it was different for Ms Cibils, as her parents worked in the technology sector. And she was inspired to study in the US, where she got a degree in computing and neuroscience from the University of California, Berkeley. After graduating she spent eight years working in Silicon Valley, near San Francisco, with roles at various American start-ups.

First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper under review, Optimizing Energy Production Using Policy Search describes a policy search algorithm for optimizing the energy production in a hydroelectric power plant. First, the problem is specified with a model of the system, the goal and the constraints. Afterwards, a predictive state representation is introduced for the inflow process. Finally, a policy search algorithm based on a random local search is presented and evaluated on a dataset of a real power-plant.