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Category: biological – Page 80

What did scientists think about aging in 1931? That’s right. 1931. because that is the year the first biological textbook was published “The Science of Life”. I managed to get my hands on the first edition of this textbook. This was my face when i first received it. As you can see i was quite excited. And this textbook is made up of separate books. I bought book i last year and i read it. Having enjoyed it and discovered that it was part of this massive ensemble piece — well, i’ve read the first “book” — there are, if my roman numerals are correct, 9 books in total. And in this first book, penned “The Living Body”, the authors, most famously, H.G.Wells, Sir Julian Huxley and G.P.Wells, H.G’s son discusses the body as a machine and that.

“For the present it is enough to remember that all animals (including men) are combustion engines of an intricate and curious kind, which live by oxidising their food”

I bought first The Living Body and then discovered it was part of this massive ensemble piece and decided i needed to read it. Now, besides being surprised to find out that H.G.Wells wrote not just non-fiction, but biology non-fiction, i was also surprised to hear how both similar & dissimilar their views were back in 1931 compared to today and i wasnt sure if that was good or terrifying.

So, how did they think of human aging. Well, in the last chapter of this 1st book titled “The wearing out of the machine and its reproduction”, they discuss it.

Sheekey bookmarks — https://www.contrado.co.uk/stores/the-sheekey-science-show/c…rk-1999569

Find me on Twitter — https://twitter.com/EleanorSheekey.

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Many current computational models that aim to simulate cortical and hippocampal modules of the brain depend on artificial neural networks. However, such classical or even deep neural networks are very slow, sometimes taking thousands of trials to obtain the final response with a considerable amount of error. The need for a large number of trials at learning and the inaccurate output responses are due to the complexity of the input cue and the biological processes being simulated. This article proposes a computational model for an intact and a lesioned cortico-hippocampal system using quantum-inspired neural networks. This cortico-hippocampal computational quantum-inspired (CHCQI) model simulates cortical and hippocampal modules by using adaptively updated neural networks entangled with quantum circuits. The proposed model is used to simulate various classical conditioning tasks related to biological processes. The output of the simulated tasks yielded the desired responses quickly and efficiently compared with other computational models, including the recently published Green model.

Several researchers have proposed models that combine artificial neural networks (ANNs) or quantum neural networks (QNNs) with various other ingredients. For example, Haykin (1999) and Bishop (1995) developed multilevel activation function QNNs using the quantum linear superposition feature (Bonnell and Papini, 1997).

The prime factorization algorithm of Shor was used to illustrate the basic workings of QNNs (Shor, 1994). Shor’s algorithm uses quantum computations by quantum gates to provide the potential power for quantum computers (Bocharov et al., 2017; Dridi and Alghassi, 2017; Demirci et al., 2018; Jiang et al., 2018). Meanwhile, the work of Kak (1995) focused on the relationship between quantum mechanics principles and ANNs. Kak introduced the first quantum network based on the principles of neural networks, combining quantum computation with convolutional neural networks to produce quantum neural computation (Kak, 1995; Zhou, 2010). Since then, a myriad of QNN models have been proposed, such as those of Zhou (2010) and Schuld et al. (2014).

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The robot tasked with making bricks out of lunar soil will be launched during China’s Chang’e-8 mission around 2028.

With Artemis II set to launch on November 24, it is no surprise that science journals are buzzing with research on lunar regolith, building bases on the moon, and working with moon soil to grow plants… you get the drift.

A recent study in the journal Communications Biology described an experiment in which the moon soil samples collected during the Apollo missions were used to grow plants. And for the first time, an Earth plant, Arabidopsis thaliana, commonly called thale cress, grew and thrived in the lunar soil samples during the experiment.

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In the last decade, we have witnessed biology bring us some incredible products and technologies: from mushroom-based packaging to animal-free hotdogs and mRNA vaccines that helped curb a global pandemic. The power of synthetic biology to transform our world cannot be overstated: this industry is projected to contribute to as much as a third of the global economic output by 2030, or nearly $30 trillion, and could impact almost every area of our lives, from the food we eat to the medicine we put in our bodies.

The leaders of this unstoppable bio revolution – many of whom you can meet at the SynBioBeta conference in Oakland, CA, on May 23–25 – are bringing the future closer every day through their ambitious vision, long-range strategy, and proactive oversight. These ten powerful women are shaping our world as company leaders, biosecurity experts, policymakers, and philanthropists focused on charting a new course to a more sustainable, equitable, clean, and safe future.

As an early pioneer in the high-throughput synthesis and sequencing of DNA, Emily Leproust has dedicated her life to democratizing gene synthesis to catapult the growth of synthetic biology applications from medicine, food, agriculture, and industrial chemicals to DNA data storage. She was one of the co-founders of Twist Bioscience in 2013 and is still leading the expanding company as CEO. To say that Twist’s silicon platform was a game-changer for the industry is an understatement. And it is no surprise that Leproust was recently honored with the BIO Rosalind Franklin Award for her work in the biobased economy and biotech innovation.

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Humongous Fungus, a specimen of Armillaria ostoyae, has claimed the title of world’s largest single organism. Though it features honey mushrooms above ground, the bulk of this creature’s mass arises from its vast subterranean mycelial network of filamentous tendrils. It has spread across more than 2,000 acres of soil and weighs over 30,000 metric tons. Yet I would contend that Humongous Fungus represents a mere microcosm of the world’s true largest organism, a creature that I will call Cyborg Earth. What is Cyborg Earth? Eastern religions have suggested that all life is fundamentally interconnected. Cyborg Earth represents an extension of this concept.

All across the globe, biological life thrives. Quintillions upon quintillions of biomolecular computations happen every second, powering all life. Mycoplasma bacteria. Communities of leafcutter ants. The Humongous Fungus. Beloved beagles. Seasonal influenza viruses. Parasitic roundworms. Families of Canadian elk. Vast blooms of cyanobacteria. Humanity. Life works because of complexity that arises from simplicity that in turn arises from whatever inscrutable quantum mechanical rules lay beneath the molecular scale.

All creatures rearrange atoms in various ways. Termites and beavers rearrange larger bunches of atoms than most organisms. As humans progressed from paleolithic to metalwork to industrialization and then to the space age, information revolution, and era of artificial intelligence, they learned to converse with the atoms around them in an ever more complex fashion. We are actors in an operatic performance, we are subroutines of evolution, we are interwoven matryoshka patterns, an epic chemistry.

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Shortly after Max Planck shook the scientific world with ideas about the fundamental quantization of energy, researchers built and leveraged theories of quantum mechanics to resolve physical phenomena that had previously been unexplainable, including the behavior of heat in solids and light absorption on an atomic level. In the 120-plus years since, researchers have looked beyond physics and used quantum theory’s same perplexing — even “spooky,” according to Einstein — laws to solve inexplicable phenomena in a variety of other disciplines.

Today, researchers at the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, are applying quantum mechanics to biology to better understand of one of nature’s biggest mysteries — magnetosensitivity, an organism’s ability to sense Earth’s magnetic field and use it as a tool to adjust some biological processes. And they’ve found some surprising results.

In a recent study, APL research engineer and scientist Carlos Martino and his APL colleagues Nam Le, Michael Salerno, Janna Domenico, Christopher Stiles, Megan Hannegan, and Ryan McQuillen, along with Ilia Solov’yov from the Carl von Ossietzky University of Oldenburg in Germany, found that an enzyme that plays a central role in human metabolism has some of the same key features as a magnetically sensitive protein found in birds.

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A group of molecular and chemical biologists at the University of California, San Diego, has found possible evidence of interdomain horizontal gene transfer leading to the development of the eye in vertebrates. In their study, reported in Proceedings of the National Academy of Sciences, Chinmay Kalluraya, Alexander Weitzel, Brian Tsu and Matthew Daugherty used the IQ-TREE software program to trace the evolutionary history of genes associated with vision.

Ever since scientists proved that humans, along with other animals, developed due to , one problem has stood out—how could evolution possibly account for the development of something as complicated as the eyeball? Even Charles Darwin was said to be stumped by the question. In recent times, this seeming conundrum has been used by some groups as a means to discredit altogether. In this new effort, the team in California sought to answer the question once and for all.

Their work began with the idea that vision in vertebrates may have got its start by using light-sensitive genes transferred from microbes. To find out if that might be the case, the team submitted likely human gene candidates to the IQ-TREE program to look for similar genetic sequences in other creatures, most specifically, microbes.

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The Oxford Martin Programme on Bio-Inspired Technologies is investigating the possibility of making computers real.

We aim to develop a completely new methodology for overcoming the extreme fragility of memory. By learning how biological molecules shield fragile states from the environment, we hope to create the building blocks of future computers.

The unique power of computers comes from their ability to carry out all possible calculations in parallel.

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