Lifeboat Foundation

Circa 2018

Many electric bicycle manufacturers claim that their e-bikes can go far, but only one can claim that their bikes go the farthest. With a Guinness world record breaking 367 km (228 mi) distance on a single charge, Delfast’s Prime electric bicycle takes the cake when it comes to long range electric bicycles.

Delfast Bikes, a Ukranian-based electric bicycle company, began their e-bike aspirations as a Kickstarter campaign just over a year ago, raising the initial funding necessary for the manufacturing of a first run of e-bikes in a single day.

Continue reading “Delfast electric bikes set world record for range and enter full production” »

When Dr. Shiran Barber-Zucker joined the lab of Prof. Sarel Fleishman as a postdoctoral fellow, she chose to pursue an environmental dream: breaking down plastic waste into useful chemicals. Nature has clever ways of decomposing tough materials: Dead trees, for example, are recycled by white-rot fungi, whose enzymes degrade wood into nutrients that return to the soil. So why not coax the same enzymes into degrading man-made waste?

Barber-Zucker’s problem was that these enzymes, called versatile peroxidases, are notoriously unstable. “These natural enzymes are real prima donnas; they are extremely difficult to work with,” says Fleishman, of the Biomolecular Sciences Department at the Weizmann Institute of Science. Over the past few years, his lab has developed computational methods that are being used by thousands of research teams around the world to design enzymes and other proteins with enhanced stability and additional desired properties. For such methods to be applied, however, a protein’s precise molecular structure must be known. This typically means that the protein must be sufficiently stable to form crystals, which can be bombarded with X-rays to reveal their structure in 3D. This structure is then tweaked using the lab’s algorithms to design an improved protein that doesn’t exist in nature.

A new measurement of a fundamental particle called the W boson appears to defy the standard model of particle physics, our current understanding of how the basic building blocks of the universe interact. The result, which was a decade in the making, will be heavily scrutinised, but if it holds true, it could lead to entirely new theories of physics.

“It would be the biggest discovery since, well, since the start of the standard model 60 years ago,” says Martijn Mulders at the CERN particle physics laboratory near Geneva, Switzerland, who has written a commentary on the result for the journal Science.

The standard model describes three distinct forces: electromagnetism, the strong force and the weak force. Particles called bosons serve as mediators for these forces between particles of matter. The weak force, which is responsible for radioactive decay, uses the W boson as one of its messengers.

Circa 2015

Engineers from the University of California, San Diego have developed an ultra-thin temporary tattoo that can painlessly and accurately monitor the glucose levels of diabetics.

The flexible device costs just a few cents and lasts for a day at a time, and early tests have shown that it’s just as sensitive as a finger-prick test.

Continue reading “This Temporary Tattoo Can Monitor Diabetics’ Glucose Levels as Accurately as a Finger Prick” »

Circa 2015

Researchers have taken a regular gel pen and turned it into a DIY chemical sensor.

A new type of battery made from electrically conductive polymers—basically plastic—could help make energy storage on the grid cheaper and more durable, enabling a greater use of renewable power.

The batteries, made by Boston-based startup PolyJoule, could offer a less expensive and longer-lasting alternative to lithium-ion batteries for storing electricity from intermittent sources like wind and solar.

… along with new, unfamiliar — and often poorly understood — risks.

Technology and business risks morph with changes in technology and how it is delivered. While cloud services are often considered more dependable, businesses face new risks with SaaS and public cloud — risks that are unfamiliar or not completely understood. People’s eyes pop open and ears perk up when they witness prolonged outage events such as the current issue with Atlassian. Suddenly, SaaS dependencies and resilience issues become relevant, as a business can’t access its favorite SaaS tool. The unique risk of using SaaS is that you don’t have control over the application or the tool and cannot reimplement yourself. It is also important to understand the cascading risks, as some of the well-known SaaS services are hosted on a leading hyperscaler’s infrastructure. You need to analyze the business impact of SaaS and cloud services outages just like for any other technology in your portfolio.

Trust but verify vendor claims about service-level agreements supporting operations and resilience plans. To ensure that your SaaS providers deliver on their own promises:

Despite millions of dollars in losses by the likes of Zillow, iBuying’s failure doesn’t signal the end of tech-led disruption, just a fumbled beginning.

Perovskites are a family of materials that are currently the leading contender to potentially replace today’s silicon-based solar photovoltaics. They hold the promise of panels that are far thinner and lighter, that could be made with ultra-high throughput at room temperature instead of at hundreds of degrees, and that are cheaper and easier to transport and install. But bringing these materials from controlled laboratory experiments into a product that can be manufactured competitively has been a long struggle.

Manufacturing perovskite-based solar cells involves optimizing at least a dozen or so variables at once, even within one particular manufacturing approach among many possibilities. But a new system based on a novel approach to machine learning could speed up the development of optimized production methods and help make the next generation of solar power a reality.

The system, developed by researchers at MIT and Stanford University over the last few years, makes it possible to integrate data from prior experiments, and information based on personal observations by experienced workers, into the machine learning process. This makes the outcomes more accurate and has already led to the manufacturing of perovskite cells with an energy conversion efficiency of 18.5 percent, a competitive level for today’s market.