Tele-ultrasound has the potential greatly to improve health equity for countless remote communities. However, practical scenarios involve potentially large time delays which cause current implementations of telerobotic ultrasound (US) to fail. Using a local model of the remote environment to provide haptics to the expert operator can decrease teleoperation instability, but the delayed visual feedback remains problematic. This paper introduces a robotic tele-US system in which the local model is not only haptic, but also visual, by re-slicing and rendering a pre-acquired US sweep in real time to provide the operator a preview of what the delayed image will resemble. A prototype system is presented and tested with 15 volunteer operators. It is found that visual-haptic model-mediated teleoperation (MMT) compensates completely for time delays up to 1000 ms round trip in terms of operator effort and completion time while conventional MMT does not. Visual-haptic MMT also significantly outperforms MMT for longer time delays in terms of motion accuracy and force control. This proof-of-concept study suggests that visual-haptic MMT may facilitate remote robotic tele-US.

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}.

--Recent work introduced the concept of human teleoperation (HT), where the remote robot typically considered in conventional bilateral teleoperation is replaced by a novice person wearing a mixed reality head mounted display and tracking the motion of a virtual tool controlled by an expert. HT has advantages in cost, complexity, and patient acceptance for telemedicine in low-resource communities or remote locations. However, the stability, transparency, and performance of bilateral HT are unexplored. In this paper, we therefore develop a mathematical model and simulation of the HT system using test data. We then analyze various control architectures with this model and implement them with the HT system to find the achievable performance, investigate stability, and determine the most promising teleoperation scheme in the presence of time delays. We show that instability in HT, while not destructive or dangerous, makes the system impossible to use. However, stable and transparent teleoperation are possible with small time delays ( < 200 ms) through 3-channel teleoperation, or with large time delays through model-mediated teleoperation with local pose and force feedback for the novice. Many remote and underresourced communities experience severe challenges in accessing qualified medical care. For example, ultrasound imaging is important, widely used, and much lower cost than other modalities such as CT or MR. However, capturing and interpreting ultrasound images requires a high degree of expertise that is not commonly present in many small communities. As a result, a sonographer or radiologist must be transported to the town on a regular basis, or patients must be sent to a major medical center. Either case leads to long wait times and difficulty handling urgent cases. In communities across Canada, patients are flown hundreds of kilometers for standard ultrasound exams. This takes up to three days and exerts a high social and financial cost on the community. Therefore, tele-ultrasound is an important and growing field. However, current commercially available technologies are often impractical. Video teleguidance is simple, low-cost, and accessible to anyone but is highly inefficient and imprecise if the person being guided does not already have ultrasound experience [1]. On the other hand, robotic teleultrasound gives the physician complete and precise control but is expensive and complex to set up and maintain. We thus recently introduced a novel teleguidance method called human teleoperation to address the shortcomings of both existing approaches [1], [2]. This method is also applicable to many other remote guidance applications. In human teleoperation, a local novice, the "follower", performs an ultrasound exam on a patient while being guided by a remote operator, the sonographer or radiologist. The follower wears a mixed reality (MR) head-mounted display (HMD) which projects a virtual ultrasound probe into their field of view.

Ultrasound is a hand-held, low-cost, non-invasive medical imaging modality which plays a vital role in diagnosing various diseases. Despite this, many rural and remote communities do not have access to ultrasound scans due to the lack of local experts trained to perform them. To address this challenge, we built a mixed reality and haptics-based tele-ultrasound system to enable an expert to precisely guide a novice remotely in carrying out an ultrasound exam. The precision and flexibility of our solution makes it more practical than existing tele-ultrasound solutions. We tested the system in Skidegate on the islands of Haida Gwaii, BC, Canada, with the experts positioned 754 km away at the University of British Columbia, Vancouver, Canada. We performed 11 scans with 10 novices and 2 experts. The experts were tasked with acquiring 5 target images and measurements in the epigastric region. The novices of various backgrounds and ages were all inexperienced in mixed reality and were not required to have prior ultrasound experience. The captured images were evaluated by two radiologists who were not present for the tests. These results are discussed along with new insights into the human computer interaction in such a system. We show that human teleoperation is feasible and can achieve high performance for completing remote ultrasound procedures, even at a large distance and with completely novice followers.

Three of every four companies have reported talent or labor shortages and difficulty hiring–a 16-year high. Profound social, economic and demographic changes have created unmet demands for workers in industries ranging from hospitality to logistics to healthcare. Executives across sectors are struggling to attract and retain talent and it's likely that labor shortages will remain a critical issue for many organizations moving forward. However, the rapid advances in artificial intelligence (AI) have the potential to significantly disrupt labor markets. Leading organizations are using AI technologies to reduce the impact of labor shortages and improve their competitive position, while also saving on costs. Here's how they're putting AI and big data to use: Some say a non-supportive and unpleasant work environment is the reason their employees quit, creating labor shortages.

The Greater Summerville Chamber of Commerce along with Dorchester Economic Development held a virtual, Industry Appreciation event. The virtual gathering, presented by TD Bank, took on the challenging subject of Artificial Intelligence (A.I.). Cathy Hayes from the South Carolina Research Authority, began discussing the modern industrial revolution or Industry 4.0, by saying, when it comes to adopting A.I. companies need to start small and foster a modern culture with a fresh mindset. Traditional thinkers are not welcome and for good reason. Artificial Intelligence has already arrived in everyday life.