There’s rough terrain – then there are the craters and near-vertical cliffs on the Moon, Mars, and beyond. The DuAxel is a robot built for situations just like those. By creating two single-axle rovers that can combine into one with a central payload we could maximize versatility during future missions. See more details: go.nasa.gov/34QNo5T.
SpaceX is targeting this weekend for its next Falcon 9 rocket launch from Kennedy Space Center, this time with another batch of Starlink internet satellites.
If schedules hold, teams will give the go-ahead for the 230-foot rocket to launch from pad 39A at 8:27 a.m. Sunday, the opening of an instantaneous window. It must launch at that time or delay to another day.
About eight minutes after liftoff, the rocket’s 162-foot first stage will target an autonomous landing on the Of Course I Still Love You drone ship in the Atlantic Ocean. SpaceX’s fleet of ships and the booster should return to Port Canaveral a few days later.
Summary: New artificial intelligence technology will analyze clinical data, brain images, and genetic information from Alzheimer’s patients to look for new biomarkers associated with the neurodegenerative disease.
Source: University of Pennsylvania
As the search for successful Alzheimer’s disease drugs remains elusive, experts believe that identifying biomarkers — early biological signs of the disease — could be key to solving the treatment conundrum. However, the rapid collection of data from tens of thousands of Alzheimer’s patients far exceeds the scientific community’s ability to make sense of it.
Summary: Researchers have identified a novel neural network in fruit flies that converts external stimuli of varying intensity into decisions about whether to act.
Source: University of Michigan
Fruit flies may be able to teach researchers a thing or two about artificial intelligence.
“Less than one”-shot learning can teach a model to identify more objects than the number of examples it is trained on.
China’s Chang’e 4 moon mission received a prestigious international award just as the two spacecraft that make up the project awoke for their 23rd lunar day.
:oooooo.
The Israeli Beewise hopes to replace the old hives and make them smarter so that bees can be monitored remotely and treated without human contact.
Re-Imagining Prisons — with AI, VR, and Digitalization.
Ira Pastor, ideaXme life sciences ambassador, interviews Ms Pia Puolakka, Project Manager of the Smart Prison Project, under the Criminal Sanctions Agency, within Finland’s Central Administration Unit.
Criminal Sanctions Agency: https://www.rikosseuraamus.fi/en/index/topical/pressreleasesandnews/Pressreleasesandnews2020/newkeravaopenprisonintroduces40additionalprisonerplacesandmodernpractices.html
Ira Pastor Comments
In 2018, according to the World Prison Population List, which gives details of the number of prisoners held in 223 prison systems in independent countries and dependent territories around the globe, there were close to 11 million people are held in penal institutions, either as pre-trial detainees/remand prisoners or having been convicted and sentenced. About 50% of them were represented by prison populations in the U.S., China, Brazil, Russia and India.
Interestingly, a few decades ago, going back to the 1960s, Finland had one of the highest rates of imprisonment in Europe, until researchers across the Nordic countries started investigating how much punishment helped in reducing crime, when they concluded it had minimal effect.
Over the following three decades, Finland remade its penal policy bit by bit, and by the end of this period of so called de-carceration,” Finland had one of the lowest rates of imprisonment on the continent, and they found that crime didn’t increase as a result.
What Finland found out that did work was a gradual reintroduction of prisoners into normal life.
Fabrics are key materials for a variety of applications that require flexibility, breathability, small storage footprint, and low weight. While fabrics are conventionally passive materials with static properties, emerging technologies have provided many flexible materials that can respond to external stimuli for actuation, structural control, and sensing. Here, we improve upon and process these responsive materials into functional fibers that we integrate into everyday fabrics and demonstrate as fabric-based robots that move, support loads, and allow closed-loop controls, all while retaining the desirable qualities of fabric. Robotic fabrics present a means to create smart adaptable clothing, self-deployable shelters, and lightweight shape-changing machinery.
Fabrics are ubiquitous materials that have conventionally been passive assemblies of interlacing, inactive fibers. However, the recent emergence of active fibers with actuation, sensing, and structural capabilities provides the opportunity to impart robotic function into fabric substrates. Here we present an implementation of robotic fabrics by integrating functional fibers into conventional fabrics using typical textile manufacturing techniques. We introduce a set of actuating and variable-stiffness fibers, as well as printable in-fabric sensors, which allows for robotic closed-loop control of everyday fabrics while remaining lightweight and maintaining breathability. Finally, we demonstrate the utility of robotic fabrics through their application to an active wearable tourniquet, a transforming and load-bearing deployable structure, and an untethered, self-stowing airfoil.
Posted in biological, holograms, robotics/AI | Leave a Comment on Holo-UNet: hologram-to-hologram neural network restoration for high fidelity low light quantitative phase imaging of live cells
Intensity shot noise in digital holograms distorts the quality of the phase images after phase retrieval, limiting the usefulness of quantitative phase microscopy (QPM) systems in long term live cell imaging. In this paper, we devise a hologram-to-hologram neural network, Holo-UNet, that restores high quality digital holograms under high shot noise conditions (sub-mW/cm2 intensities) at high acquisition rates (sub-milliseconds). In comparison to current phase recovery methods, Holo-UNet denoises the recorded hologram, and so prevents shot noise from propagating through the phase retrieval step that in turn adversely affects phase and intensity images. Holo-UNet was tested on 2 independent QPM systems without any adjustment to the hardware setting. In both cases, Holo-UNet outperformed existing phase recovery and block-matching techniques by ∼ 1.8 folds in phase fidelity as measured by SSIM. Holo-UNet is immediately applicable to a wide range of other high-speed interferometric phase imaging techniques. The network paves the way towards the expansion of high-speed low light QPM biological imaging with minimal dependence on hardware constraints.
