Lifeboat Foundation

Biodiversity is on the verge of being devastated due to the inclination towards deforestation these days. The adverse climatic conditions that our Earth is facing nowadays are also the result of this pressing concern. However, to mitigate this climatic distress caused by deforestation, a team of researchers at the MIT Institute has come up with a novel technique to artificially grow wood in a controlled environment in the lab, which can then be used for making furniture and other wooden houses, which are now being made from cutting trees, thereby posing a threat to our natural habitat. Apart from the amazing growth, we can also print “3D custom-designed wooden structures” out of the replicas, which can considerably reduce wood waste as well.

Prior to discussing the mechanism of wood production, an interesting thing to note is that we can easily change the shape and structure of these artificially produced woods according to our requirements. The researchers have demonstrated the whole process through an experiment in which a flowering plant known as “Common zinnia (Zinnia Elegans)” would be taken and the cells are then extracted from its leaves which can then be conserved in a liquid mixture for several days. After it becomes nutritionally embellished, a gel-based material would be utilized to further refine the mixture.

However, these cells would then give birth to new plant cells which will then be treated accordingly as per the lab conditions. Moreover, we can also reform the physical and mechanical properties of the cells by increasing or decreasing the hormonal concentrations as per the needs.

Spike-based neuromorphic hardware holds the promise to provide more energy efficient implementations of Deep Neural Networks (DNNs) than standard hardware such as GPUs. But this requires to understand how DNNs can be emulated in an event-based sparse firing regime, since otherwise the energy-advantage gets lost. In particular, DNNs that solve sequence processing tasks typically employ Long Short-Term Memory (LSTM) units that are hard to emulate with few spikes. We show that a facet of many biological neurons, slow after-hyperpolarizing (AHP) currents after each spike, provides an efficient solution. AHP-currents can easily be implemented in neuromorphic hardware that supports multi-compartment neuron models, such as Intel’s Loihi chip. Filter approximation theory explains why AHP-neurons can emulate the function of LSTM units.

A small spacecraft will wade the gravitational tides between Earth and the Moon.

Ford Motor Company recently filed a patent for a combustion engine that will run on hydrogen, Motor1 reports. The patent isn’t like your normal hydrogen-powered vehicle which uses a propulsion system that converts energy stored as hydrogen to electricity via a fuel cell. The patent Ford filed is for a turbocharged combustion engine that runs on hydrogen.

Muscle Cars and Truck, which initially discovered and reported on the patent, noted that on paper, Ford’s engine should be capable of operating across a wide range of air/fuel lambda, which is the Greek letter used to represent a fuel’s stoichiometric value as 1.00, with values depending on torque demands. MCT also noted that internal exhaust gas recirculation and valve timing will be used to control combustion.

MCT quickly touched upon the importance of the stoichiometric value of a fuel, which is the ratio by which all of the fuel is mixed with all of the oxygen to produce a competitive burn. Notably, Ford’s new method of turbocharged hydrogen will explore lambda values in excess of 2.00. This means that the new engine would be able to operate in an extremely lean state and use more than double the amount of air required for the stoichiometric combustion of hydrogen. You can read more about this here.

😳!!!

New research suggests that Darwinian evolution could be happening up to four times faster than previously thought, based on an analysis of genetic variation.

Continue reading “I tried ordering pizza with my mind on the new Domino’s ‘Stranger Things’ app. Despite some glitches, it worked and was really fun” »

This just came out, a day or so ago.

Can the aging process be reversed — or even halted, altogether? If we manage to decode this final mystery of our human biology, we might soon be able to eradicate age-related illnesses like cancer, dementia and heart problems.

Continue reading “More life — Decoding the secret of aging | DW Documentary” »

Recently, scientists made groundbreaking detections that allowed them that gravity does not act instantaneously as Newton thought, instead it propagates at the speed of light.

Neil Cornish, a physicist at Montana State University said, “The speed of gravity, like the speed of light, is one of the fundamental constants in the Universe. Until the advent of gravitational wave astronomy, we had no way to directly measure the speed of gravity.”

In the course of recent months, physicists have gained exceptionally fast ground in bouncing the speed of gravity utilizing gravitational wave perceptions. Earlier, the first LIGO detections of gravitational waves constrained the speed of gravity suggests 50% of the speed of light.

A 100% renewable energy future cannot ignore geothermal as part of the mix.

Modelling only looked at solar and wind rather than considering the baseload capability of geothermal as a renewable energy solution.

Classifying celestial objects is a long-standing problem. With sources at near unimaginable distances, sometimes it’s difficult for researchers to distinguish between objects such as stars, galaxies, quasars or supernovae.

Instituto de Astrofísica e Ciências do Espaço’s (IA) researchers Pedro Cunha and Andrew Humphrey tried to solve this classical problem by creating SHEEP, a machine-learning algorithm that determines the nature of astronomical sources. Andrew Humphrey (IA & University of Porto, Portugal) comments: “The problem of classifying celestial objects is very challenging, in terms of the numbers and the complexity of the universe, and artificial intelligence is a very promising tool for this type of task.”

The first author of the article, now published in the journal Astronomy & Astrophysics, Pedro Cunha, a Ph.D. student at IA and in the Dept. of Physics and the University of Porto, says, “This work was born as a side project from my MSc thesis. It combined the lessons learned during that time into a unique project.”