Efficient and current roadway geometry data collection is a critical task for transportation agencies to undertake effective road planning, maintenance, design, and rehabilitation efforts. The methods for gathering such data can be broadly classified into two categories: a) land-based methods, which encompass field inventory, mobile mapping, and image logging, and b) aerial-based methods, which involve satellite imagery, drones, and laser scanning. However, employing land-based techniques for extensive highway networks covering thousands of miles proves arduous and costly, and poses safety risks for crew members. Consequently, there exists a pressing need to develop more efficient methodologies for acquiring this data promptly, safely, and economically. Fortunately, with the increasing availability of high-resolution images and recent strides in computer vision and object detection technologies, automated extraction of roadway geometry features has become feasible.

This study presents the application of generative deep learning techniques to evaluate marine fog visibility nowcasting using the FATIMA (Fog and turbulence interactions in the marine atmosphere) campaign observations collected during July 2022 in the North Atlantic in the Grand Banks area and vicinity of Sable Island (SI), northeast of Canada. The measurements were collected using the Vaisala Forward Scatter Sensor model FD70 and Weather Transmitter model WXT50, and Gill R3A ultrasonic anemometer mounted on the Research Vessel Atlantic Condor. To perform nowcasting, the time series of fog visibility (Vis), wind speed, dew point depression, and relative humidity with respect to water were preprocessed to have lagged time step features. Generative nowcasting of Vis time series for lead times of 30 and 60 minutes were performed using conditional generative adversarial networks (cGAN) regression at visibility thresholds of Vis < 1 km and < 10 km. Extreme gradient boosting (XGBoost) was used as a baseline method for comparison against cGAN. At the 30 min lead time, Vis was best predicted with cGAN at Vis < 1 km (RMSE = 0.151 km) and with XGBoost at Vis < 10 km (RMSE = 2.821 km). At the 60 min lead time, Vis was best predicted with XGBoost at Vis < 1 km (RMSE = 0.167 km) and Vis < 10 km (RMSE = 3.508 km), but the cGAN RMSE was similar to XGBoost. Despite nowcasting Vis at 30 min being quite difficult, the ability of the cGAN model to track the variation in Vis at 1 km suggests that there is potential for generative analysis of marine fog visibility using observational meteorological parameters.

Dr. Dan Spratt, chair of the Department of Radiation Oncology at University Hospitals Cleveland Medical Center, talks about how ArteraAI's Prostate Test is helping him to identify optimal therapies for his patients. Prostate cancer is the second leading cause of cancer death in men in the U.S., with an expected 288,000 cases and 34,700 deaths expected in 2023, per the American Cancer Society. As artificial intelligence-based health technologies continue to advance, a growing number of medical tech firms are looking to use AI to improve patient outcomes. One of these is ArteraAI, a firm in Jacksonville, Florida, that develops medical AI tests that help personalize therapy for cancer patients. Among the company's solutions is the ArteraAI Prostate Test, described as the first of its kind for patients with localized prostate cancer.

ShipHero, a shipping and logistics platform for more than 5,000 eCommerce brands and third-party logistics (3PL) providers, announced that it would implement inVia Robotics' robotic system at two more fulfillment centers. The company has been using inVia's automated picking and replenishment robots at its Jacksonville, Florida location, and its now adding that technology to its Allentown, Pennsylvania and Las Vegas warehouses. ShipHero and inVia have already built a native integration between inVia's warehouse execution system (WES) and ShipHero's warehouse management system (WMS) software, ensuring rapid and seamless deployments in the new facilities. "Over the last two years we've seen demand for 3PL services grow dramatically, which has led to a greater need for technology that can help keep products moving quickly through the order process," Lior Elazary, CEO and co-founder of inVia Robotics, said. "The native integration between our WES and ShipHero's WMS will allow us to very rapidly expand both of our technologies into additional warehouses, bypassing the need for time-consuming custom systems integration. We're excited to expand our AI and automation services across ShipHero's strategic distribution network."

While CUE is experiencing a moment in the spotlight, the robot isn't the best three-point shooter the world has ever known. American podiatrist Tom Amberry set the world record for humans, 2,750 consecutive shots, in 1993 at age 71. Ted St. Martin of Jacksonville, Fla., pushed the consecutive mark to 5,221 in 1996 and still holds the record today. Others have achieved a number of basketball shooting feats, some while blindfolded.

A private rocket-launch startup unveiled its fully autonomous drone designed to drop a rocket in midair that shoots small satellites into orbit without a launchpad. Alabama-based company Aevum rolled out its Ravn X Autonomous Launch Vehicle at the Cecil SpacePort launch facility in Jacksonville, Fla., on Thursday. America is changing faster than ever! Add Changing America to your Facebook or Twitter feed to stay on top of the news. The 80-foot aircraft has a wingspan of 60 feet, stands 18 feet tall and is the world's largest Unmanned Aircraft System (UAS) by mass, weighing 55,000 pounds.

The article, "AI-Enabled ECG Improves Ability to Identify Heart Failure in Emergency Departments," was originally published on Practical Cardiology. An artificial intelligence (AI)-enabled electrocardiogram (ECG) could aid clinicians in emergency departments more accurately identify heart failure. Findings from the study indicate the AI-enhanced ECG could improve identification of left ventricular systolic dysfunction in patients presenting the emergency departments with acute dyspnea. "AI-enhanced ECGs are quicker and outperform current standard-of-care tests. Our results suggest that high-risk cardiac patients can be identified quicker in the emergency department and provides an opportunity to link them early to appropriate cardiovascular care," said lead investigator Demilade Adedinsewo, MD, MPH, chief fellow in the division of cardiovascular medicine at Mayo Clinic in Jacksonville, Florida, in a statement.

When people seek emergency care for shortness of breath, a routine electrocardiogram (ECG or EKG) enhanced by artificial intelligence (AI) is better than standard blood tests at determining if the cause is heart failure, according to new research published today in Circulation: Arrhythmia and Electrophysiology, an American Heart Association journal. "Determining why someone has shortness of breath is challenging for emergency department physicians, and this AI-enabled ECG provides a rapid and effective method to screen these patients for left ventricular systolic dysfunction," said Demilade Adedinsewo, M.D., M.P.H., lead author of the study and chief fellow in the division of cardiovascular medicine at Mayo Clinic in Jacksonville, Florida. The left ventricle supplies most of the heart's pumping power, so it is larger than the other chambers and essential for normal function. In left ventricular systolic dysfunction (LVSD), the left ventricle is weakened and must work harder to maintain adequate blood flow to the body. In a typical year, about 1.2 million people go to emergency departments because they are short of breath.

When people seek emergency care for shortness of breath, a routine electrocardiogram (ECG or EKG) enhanced by artificial intelligence (AI) is better than standard blood tests at determining if the cause is heart failure, according to new research published today in Circulation: Arrhythmia and Electrophysiology, an American Heart Association journal. "Determining why someone has shortness of breath is challenging for emergency department physicians, and this AI-enabled ECG provides a rapid and effective method to screen these patients for left ventricular systolic dysfunction," said Demilade Adedinsewo, M.D., M.P.H., lead author of the study and chief fellow in the division of cardiovascular medicine at Mayo Clinic in Jacksonville, Florida. The left ventricle supplies most of the heart's pumping power, so it is larger than the other chambers and essential for normal function. In left ventricular systolic dysfunction (LVSD), the left ventricle is weakened and must work harder to maintain adequate blood flow to the body. In a typical year, about 1.2 million people go to emergency departments because they are short of breath.

That plan will include highway lanes enabled for self-driving trucks and terminals stretching from Los Angeles to Jacksonville, Fla., over the next two to three years, and eventually across the Lower 48 states, said Cheng Lu, TuSimple's president. Top news and in-depth analysis on the world of logistics, from supply chain to transport and technology. The company's fleet of 40 trucks now operates autonomously on seven routes between Phoenix, Tucson, Ariz., El Paso, Tex. and Dallas, with a human operator on board each vehicle to take over if needed. TuSimple plans to pilot fully autonomous driverless service next year, the company said, and aims to expand those operations nationwide in 2023 and 2024 with the help of commercialized technology it is developing with German car-parts maker ZF Friedrichshafen AG. To get there, TuSimple is building out lanes and terminals connected by high-definition routing maps that function "like virtual railroad tracks" for its retrofitted big rigs, Mr. Lu said.