Radio remains a pervasive medium for mass information dissemination, with AM/FM stations reaching more Americans than either smartphone-based social networking or live television. Increasingly, radio broadcasts are also streamed online and accessed over the Internet. We present WavePulse, a framework that records, documents, and analyzes radio content in real-time. While our framework is generally applicable, we showcase the efficacy of WavePulse in a collaborative project with a team of political scientists focusing on the 2024 Presidential Elections. We use WavePulse to monitor livestreams of 396 news radio stations over a period of three months, processing close to 500,000 hours of audio streams. These streams were converted into time-stamped, diarized transcripts and analyzed to track answer key political science questions at both the national and state levels. Our analysis revealed how local issues interacted with national trends, providing insights into information flow. Our results demonstrate WavePulse's efficacy in capturing and analyzing content from radio livestreams sourced from the Web. Code and dataset can be accessed at \url{https://wave-pulse.io}.

Last year, Kaylin Hayman walked into a Pittsburgh court to testify against a man she'd never met who had used her face to make pornographic pictures with artificial intelligence technology. Kaylin, 16, is a child actress who starred in the Disney show Just Roll With It from 2019 to 2021. The perpetrator, a 57-year-old man named James Smelko, had targeted her because of her public profile. She is one of about 40 of his victims, all of them child actors. In one of the images of Kaylin submitted into evidence at the trial, Smelko used her face from a photo posted on Instagram when she was 12, working on set, and superimposed it onto the naked body of someone else.

After several reports of artificial intelligence-generated child pornography surfaced in California, Ventura County Dist. Erik Nasarenko advocated for a change to state law to protect children who are increasingly vulnerable to this misuse of technology. Last December, Nasarenko received his first tip regarding a person who had artificially created photos depicting an underaged girl performing sex acts with an adult man. "When it came to my attention, I said let's file [charges]," Nasarenko told The Times. But, because of current loopholes in California law, he learned that he couldn't press charges in cases where the photos of children are AI-generated.

Modeling stochastic traffic behaviors at the microscopic level, such as car-following and lane-changing, is a crucial task to understand the interactions between individual vehicles in traffic streams. Leveraging a recently developed theory named physics regularized Gaussian process (PRGP), this study presents a stochastic microscopic traffic model that can capture the randomness and measure errors in the real world. Physical knowledge from classical car-following models is converted as physics regularizers, in the form of shadow Gaussian process (GP), of a multivariate PRGP for improving the modeling accuracy. More specifically, a Bayesian inference algorithm is developed to estimate the mean and kernel of GPs, and an enhanced latent force model is formulated to encode physical knowledge into stochastic processes. Also, based on the posterior regularization inference framework, an efficient stochastic optimization algorithm is developed to maximize the evidence lower-bound of the system likelihood. To evaluate the performance of the proposed models, this study conducts empirical studies on real-world vehicle trajectories from the NGSIM dataset. Since one unique feature of the proposed framework is the capability of capturing both car-following and lane-changing behaviors with one single model, numerical tests are carried out with two separated datasets, one contains lane-changing maneuvers and the other doesn't. The results show the proposed method outperforms the previous influential methods in estimation precision.

Seaborne robots have made a startling discovery beneath a 20-mile glacier in Alaska. The technology found the massive rivers of ice may be melting under the LeConte Glacier much faster than previously thought. Scientists programmed autonomous kayaks to swim near the icy cliffs of the glacier to measure the'ambient meltwater intrusions', which shows how much fresh water is flowing into the ocean from underneath the glacier. The study found ambient melting was 100 times higher than models had estimated. This is the first time experts have been able to analyze plumes of meltwater - the water released when snow or ice melts, where glaciers meet the ocean- because the feat is far too dangerous for ships due to falling ice of slabs from the glacier.

Earthquake Alert! 6.7 temblor, epicenter 3.8 miles west of Ventura, California--impact will be in eleven minutes--evacuate, evacuate!" While you run to the hall closet to grab your earthquake kit, you shout out: "Alexa, where is my emergency evac location?" Walk north to Wilshire, then take a left on Warner," she responds. As you and your neighbors pour into the building stairwell, you hear audio from a phone: "Google Earth Q estimates substantial potential for structural damage in the West San Fernando Valley and Coastal West Los Angeles to pre-2006 code dwellings and buildings. Most of West LA will experience total loss of power for anywhere from six to twenty-four hours in duration."

Janae builds inbound social media sales and marketing plans for healthcare IT companies. Artificial Intelligence, or AI for short, does not always equate to high intelligence and this can have a high cost for healthcare systems. Navigating the intersection of AI and healthcare requires more than clinical operations expertise; it requires advanced knowledge in business motivation, partnerships, legal considerations, and ethics. This year I had the pleasure of attending a meetup for people interested in and working with AI for healthcare at the Healthcare Information and Management Systems Society (HIMSS) annual meeting in Orlando, Florida. At the beginning of the meetup Wen Dombrowski, MD, asked everyone to stand up and participate in a partner led movement activity.

An engineer has created a machine that holds a hot dog in front of a dog to direct it. The device sits on the dog's back and rotates the hot dog in different directions with the aid of a remote control. The engineer had all the construction and tests filmed, which yielded mixed but funny results. The device sits on the dog's back and rotates the hot dog in different directions with the aid of a remote control. Engineer William Osman, based in Ventura, California, has worked on other projects including a remote controlled pumpkin combat robot and a gingerbread house made with a laser cutter.