Lifeboat Foundation

New types of antibiotics are being developed using an AI machine-learning approach that scans a pool of more than 100 million molecules, including one that works against strains of bacteria previously considered untreatable, according to a recent account in Nature.

If Dr. Mainprize felt proud of his role in the breakthrough, he didn’t show it.

He was well aware of the significance of this achievement; it was potentially the key to tackling a wide range of illnesses, from brain cancer to Parkinson’s disease and Alzheimer’s disease – illnesses that are currently impossible or hard to cure. But he also knew he and his team at Sunnybrook Health Sciences Centre still had a long way to go before their work translated into actual treatment for patients, said his close friend and colleague Nir Lipsman.

The kickoff of Lyft’s second challenge comes months after Waymo expanded its public driving data set and launched the $110,000 Waymo Open Dataset competition. Winners were announced mid-June during a workshop at the 2020 Conference on Computer Vision and Pattern Recognition (CVPR), which was held online this year due to the coronavirus pandemic.

Following the release of the Perception Dataset and the conclusion of its 2019 object detection competition, Lyft today shared a new corpus — the Prediction Dataset — containing the logs of movements of cars, pedestrians, and other obstacles encountered by its fleet of 23 autonomous vehicles in Palo Alto. Coinciding with this, the company plans to launch a challenge that will task entrants with predicting the motion of traffic agents.

A longstanding research problem within the self-driving domain is creating models robust and reliable enough to predict traffic motion. Lyft’s data set focuses on motion prediction by including the movement of traffic types its fleet crossed paths with, like cars, cyclists, and pedestrians. This movement is derived from data collected by the sensor suite mounted to the roof of Lyft’s vehicles, which captures things like lidar and radar readings as the vehicles drive tens of thousands of miles:

Continue reading “Lyft releases new self-driving vehicle data set and launches $30,000 challenge” »

Alphabet’s Sidewalk Labs plans to spin out some of its smart city ideas into separate companies, CEO Daniel Doctoroff said today at Collision from Home conference. Doctoroff listed three potential companies: mass timber construction, affordable electrification sans fossil fuels, and planning tools optimized with machine learning and computation design.

Last month, Sidewalk Labs killed its Toronto smart city project, which envisioned raincoats designed for buildings, heated pavement, and object-classifying cameras. Privacy advocates celebrated that the Google sister company would not be getting invasive power to surveil residents. But as I argued in my column that week, the story was far from over. Sidewalk Labs was using the COVID-19 pandemic as a scapegoat for the Toronto project, but the company wouldn’t stay idle.

Now that the world is in the thick of the coronavirus pandemic, governments are quickly deploying their own cocktails of tracking methods. These include device-based contact tracing, wearables, thermal scanning, drones, and facial recognition technology. It’s important to understand how those tools and technologies work and how governments are using them to track not just the spread of the coronavirus, but the movements of their citizens.

Contact tracing is one of the fastest-growing means of viral tracking. Although the term entered the common lexicon with the novel coronavirus, it’s not a new practice. The Centers for Disease Control and Prevention (CDC) says contact tracing is “a core disease control measure employed by local and state health department personnel for decades.”

Traditionally, contact tracing involves a trained public health professional interviewing an ill patient about everyone they’ve been in contact with and then contacting those people to provide education and support, all without revealing the identity of the original patient. But in a global pandemic, that careful manual method cannot keep pace, so a more automated system is needed.

But as millions of animals continue to be used in biomedical research each year, and new legislation calls on federal agencies to reduce and justify their animal use, some have begun to argue that it’s time to replace the three Rs themselves. “It was an important advance in animal research ethics, but it’s no longer enough,” Tom Beauchamp told attendees last week at a lab animal conference.

Science talks with two experts in animal ethics who want to go beyond the three Rs.

Summary: Study identifies a different set of individual neurons in the medial frontal cortex that is responsible for memory-based decision making. The findings have implications for the treatment of Alzheimer’s disease, schizophrenia, and other disorders associated with problems in cognitive flexibility.

Source: CalTech

Continue reading “‘Where are my keys?’ and other memory-based choices probed in the brain” »

AstraZeneca’s experimental COVID-19 vaccine is probably the world’s leading candidate and most advanced in terms of development, the World Health Organization’s (WHO) chief scientist said on Friday.

DNA replication is a process of critical importance to the cell, and must be coordinated precisely to ensure that genomic information is duplicated once and only once during each cell cycle. Using super-resolution technology a University of Technology Sydney led team has directly visualized the process of DNA replication in single human cells.

This is the first quantitative characterization to date of the spatio-temporal organization, morphology, and in situ epigenetic signatures of individual replication foci (RFi) in single human cells at the nanoscale.

The results of the study, published in PNAS (Proceedings of the National Academy of Sciences) give new insight into a poorly understood area of DNA replication namely how replication origin sites are chosen from thousands of possible sites.