Angel Reese thanks WNBA for suspending Sandy Brondello, frames'protected species' comment as discrimination Rory McIlroy should be the last golfer to criticize others for'performative' behavior Brexton Busch wins first race since father Kyle Busch's death in emotional return to Victory Lane Caitlin Clark'cheering hard' for Argentina over Spain in World Cup final: 'I want Messi' Ella Langley turns 63-year-old former NFL head coach into'Ella Fella' I am once again begging the folks in USC's athletic department to study some Greek literature Jaxson Dart's swimsuit model girlfriend gets patriotic, golfer Hailey Ostrom takes on Lake Powell & Bigfoot Caitlin Clark's former teammate calls out WNBA for suspending Tempo head coach over'protected species' remark Christopher Nolan brings'The Odyssey' to life with groundbreaking IMAX technology WATCH: Anchor STUNNED by socialist's answer More than 200 military musicians bring America's story to life The All-Star forward finished with eight points and five rebounds in Atlanta's 93-91 victory over the Chicago Sky. Dan Dakich reacts to and fixes Angel Reese's shooting form. Angel Reese's eventful weekend ended with an injury and one of her worst performances of the season. The Atlanta Dream star left Sunday afternoon's game against her former team, the Chicago Sky, after her left leg appeared to give out as she attempted a layup early in the fourth quarter. Reese fell to the floor after missing the shot, briefly got back to her feet and then went down again.

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The games start June 11 and end with a grand finale in New Jersey on July 19. There are 104 of them. Here's how to watch'em all. The FIFA Men's World Cup is almost here, and this one will be the biggest ever. The tournament is hosted by three countries: Mexico, Canada, and the US.

The company has suspended operations in a second city. Autonomous cars are getting more capable all the time, but they remain a bit too willing to fight mother nature and lose. Case in point: Waymo has halted its robotaxi service in a second US city in the past fortnight due to issues with heavy rain and flooding. First reported by, the company has paused its operations in Atlanta after one of its self-driving vehicles was seen driving through a heavily flooded street, where it eventually got stuck for around an hour. This comes after Waymo also temporarily suspended its San Antonio service last week and issued a voluntary recall for nearly 4,000 robotaxis.

We present UNIPHY+, a unified physiological foundation model (physioFM) framework designed to enable continuous human health and diseases monitoring across care settings using ubiquitously obtainable physiological data. We propose novel strategies for incorporating contextual information during pretraining, fine-tuning, and lightweight model personalization via multi-modal learning, feature fusion-tuning, and knowledge distillation. We advocate testing UNIPHY+ with a broad set of use cases from intensive care to ambulatory monitoring in order to demonstrate that UNIPHY+ can empower generalizable, scalable, and personalized physiological AI to support both clinical decision-making and long-term health monitoring.

Two new self-driving car services--one in Atlanta from Lyft and May Mobility, another in Las Vegas from Amazon subsidiary Zoox--prove that the robotaxi race is still on. Now comes the hard part. Today, two robotaxi firms operating on opposite sides of the US say they're opening their services to the public. The Ann Arbor tech developer May Mobility has launched its self-driving car service on the Lyft app in a section of Atlanta, Georgia. Starting today, anyone who orders a Lyft in the area might be paired with an autonomous vehicle.

The 2025 IEEE International Conference on Robotics & Automation (ICRA) took place from 19–23 May, in Atlanta, USA. The event featured plenary and keynote sessions, tutorial and workshops, forums, and a community day. Find out what the participants got up during the conference. Check out what's happening at the #ICRA2025 Welcome Reception! The excitement is real -- #ICRA2025 is already buzzing!

The 2025 IEEE International Conference on Robotics & Automation (ICRA) took place from 19–23 May, in Atlanta, USA. The event featured plenary and keynote sessions, tutorial and workshops, forums, and a community day. Find out what the participants got up during the conference. Check out what's happening at the #ICRA2025 Welcome Reception! The excitement is real -- #ICRA2025 is already buzzing!

Micro-video recommendation is attracting global attention and becoming a popular daily service for people of all ages. Recently, Graph Neural Networks-based micro-video recommendation has displayed performance improvement for many kinds of recommendation tasks. However, the existing works fail to fully consider the characteristics of micro-videos, such as the high timeliness of news nature micro-video recommendation and sequential interactions of frequently changed interests. In this paper, a novel Multi-aggregator Time-warping Heterogeneous Graph Neural Network (MTHGNN) is proposed for personalized news nature micro-video recommendation based on sequential sessions, where characteristics of micro-videos are comprehensively studied, users' preference is mined via multi-aggregator, the temporal and dynamic changes of users' preference are captured, and timeliness is considered. Through the comparison with the state-of-the-arts, the experimental results validate the superiority of our MTHGNN model.

Software development support tools have been studied for a long time, with recent approaches using Large Language Models (LLMs) for code generation. These models can generate Python code for data science and machine learning applications. LLMs are helpful for software engineers because they increase productivity in daily work. An LLM can also serve as a "mentor" for inexperienced software developers, and be a viable learning support. High-quality code generation with LLMs can also be beneficial in geospatial data science. However, this domain poses different challenges, and code generation LLMs are typically not evaluated on geospatial tasks. Here, we show how we constructed an evaluation benchmark for code generation models, based on a selection of geospatial tasks. We categorised geospatial tasks based on their complexity and required tools. Then, we created a dataset with tasks that test model capabilities in spatial reasoning, spatial data processing, and geospatial tools usage. The dataset consists of specific coding problems that were manually created for high quality. For every problem, we proposed a set of test scenarios that make it possible to automatically check the generated code for correctness. In addition, we tested a selection of existing code generation LLMs for code generation in the geospatial domain. We share our dataset and reproducible evaluation code on a public GitHub repository, arguing that this can serve as an evaluation benchmark for new LLMs in the future. Our dataset will hopefully contribute to the development new models capable of solving geospatial coding tasks with high accuracy. These models will enable the creation of coding assistants tailored for geospatial applications.