The field of robotics has taken a significant leap forward with the development of an amphibious robotic dog, capable of efficiently navigating both land and water. This innovative creation was inspired by the remarkable mobility of mammals in aquatic environments.

Unlike existing amphibious robots that often draw inspiration from reptiles or insects, this robotic canine is based on the swimming style of dogs. This design choice has allowed it to overcome several limitations faced by insect-inspired designs, such as reduced agility and load capacity.

The key to the amphibious robot’s water mobility lies in its unique paddling mechanism, modeled after the natural swimming motion of dogs. By carefully balancing weight and buoyancy, the engineers have ensured stable and effective aquatic performance.

To test its capabilities, the researchers developed and experimented with three distinct paddling gaits:

* A doggy paddle method that prioritizes speed
* A trot-like style that focuses on stability
* A third gait that combines elements of both

Through extensive experimentation, it was found that the doggy paddle method proved superior for speed, achieving a maximum water speed of 0.576 kilometers per hour (kph). On land, the amphibious robotic dog reaches speeds of 1.26 kph, offering versatile mobility in amphibious environments.

“This innovation marks a big step forward in designing nature-inspired robots,” says Yunquan Li, corresponding author of the study. “Our robot dog’s ability to efficiently move through water and on land is due to its bioinspired trajectory planning, which mimics the natural paddling gait of real dogs.”

The implications of this technology are vast and exciting, with potential applications in environmental research, military vehicles, rescue missions, and more. As we continue to push the boundaries of what’s possible with robotics, it’s clear that the future holds much promise for innovation and discovery.

The study, conducted by University of Bristol academics, has shed light on the importance of tailoring social media to suit individual needs. By categorizing users into distinct groups based on their motivations and behaviors, researchers have found that finding the right level of personal investment is key to a positive experience online.

The research revealed three main user types:

1. Those who browse without strong intentionality, often mindlessly scrolling through feeds.
2. Those deeply invested in their online lives, potentially leading to compulsive use and negative consequences for well-being.
3. Those who see value in using social media but retain personal distance, arguably having the best outcomes overall.

The findings suggest that social media platforms could be redesigned to support more intentional use by introducing customized features tailored to different user needs. This approach has the potential to help users regain control over their time online and make it more purposeful and valued.

By adapting interfaces to align with individual well-being, social media platforms can promote sustainable engagement connected to things that matter to the user, rather than just maximizing screen time. The implications of this work extend beyond social media design into technology use more broadly, offering a data-driven approach to promoting digital self-regulation and overall well-being.

The next phase of this research will explore how social media platforms can identify different user groups and adapt interfaces to support intentional online engagement that prioritizes personal well-being.

The article highlights a groundbreaking technology developed by engineers at the University of Mississippi that can detect heart attacks faster and more accurately than traditional methods. Electrical and computer engineering assistant professor Kasem Khalil led the research, which was published in Intelligent Systems, Blockchain and Communication Technologies.

The technology uses artificial intelligence and advanced mathematics to design a chip that analyzes electrocardiograms (ECGs) – graphs of the heart’s electrical signals – and detects a heart attack in real-time. This chip is lightweight and energy efficient enough to be embedded in wearable devices while still being 92.4% accurate, higher than many current methods.

In the United States, someone dies from a heart attack every 40 seconds. Heart disease is the leading cause of death in the country. Khalil’s technology aims to improve heart attack detection methods without sacrificing accuracy. The researchers believe that their wearable device can cut down on diagnosis time, allowing patients to receive faster treatment and reducing the likelihood of permanent damage.

The team used a chip design approach that focuses on all aspects of the technology they hope to create, from software development to hardware implementation. This holistic approach allowed them to optimize the system and make it more efficient.

Current methods of heart attack detection often require a patient to go through an electrocardiogram or blood tests in a medical facility, which can take time that a patient might not have. The researchers see their technology as a potential game-changer in real-time diagnosis, allowing patients to receive faster treatment and reducing the risk of permanent damage.

While Khalil’s team continues developing the technology, they envision other health care applications for these devices, such as predicting or identifying seizures, dementia, and other conditions. The detection of diseases depends on the disease itself, but the researchers are working to find faster, more efficient ways of doing that.

This wearable heart attack detection tech has the potential to save lives by enabling real-time diagnosis and reducing the time-sensitive element of heart attacks. Its impact could be significant in improving patient outcomes and reducing mortality rates associated with heart disease.