"Ultraseven" is a Japanese tokusatsu television series that first aired in 1967. It is part of the Ultra Series created by Eiji Tsuburaya and produced by Tsuburaya Productions. The show follows the story of an alien superhero, Ultraseven, who takes on human form to defend Earth from various monsters and extraterrestrial threats.

The Journal of Applied Remote Sensing is a peer-reviewed scientific journal that focuses on the application of remote sensing technologies and techniques to address various environmental, societal, and scientific challenges. It publishes research articles, reviews, and case studies that cover a wide range of topics, such as the analysis of satellite and aerial imagery, data processing, and the use of remote sensing in fields like agriculture, forestry, urban planning, climate science, and disaster management.

Life Sciences in Space Research encompasses the study of living organisms and biological systems in the context of space environments. This field investigates how various factors related to space, such as microgravity, radiation, and isolation, affect biological processes, health, and behavior of living organisms, including humans.

Planetary and Space Science is an interdisciplinary field that focuses on the study of planets, moons, asteroids, comets, and other celestial bodies, as well as various phenomena occurring in space. This field encompasses a range of subjects including: 1. **Planetary Geology**: The study of the composition, structure, and processes of planets and their moons, including surface features, atmospheres, and geological histories.

One important quantum mechanics experiment, which using quantum effects explain the dependency of specific heat capacity on temperature, an effect which is not present in the Dulong-Petit law.

This is the solid-state analogue to the black-body radiation problem. It is also therefore a quantum mechanics-specific phenomenon.

What makes lasers so special: Lasers vs other light sources.

Bibliography:

Ciro Santilli is a fan of this late 2010's buzzword.

It basically came about because of the endless stream of useless software startups made since the 2000's by one or two people with no investments with the continued increase in computers and Internet speeds until the great wall was reached.

Deep tech means not one of those. More specifically, it means technologies that require significant investment in expensive materials and laboratory equipment to progress, such as molecular biology technologies and quantum computing.

And it basically comes down to technologies that wrestle with the fundamental laws of physics rather than software data wrangling.

Computers are of course limited by the laws of physics, but those are much hidden by several layers of indirection.

Full visibility, and full control, make computer tasks be tasks that eventually always work out more or less as expected.

The same does not hold true when real Physics is involved.

Physics is brutal.

To start with, you can't even see your system very clearly, and often doing so requires altering its behaviour.

For example, in molecular biology, most great discoveries are made after some new technique is made to be able to observe smaller things.

But you often have to kill your cells to make those observations, which makes it very hard to understand how they work dynamically.

What we would really want would be to track every single protein as it goes about inside the cell. But that is likely an impossible dream.

The same for the brain. If we had observations of every neuron, how long would it take to understand it? Not long, people are really good at reverse engineering things when there is enough information available to do so, see also science is the reverse engineering of nature.

Then, even when you start to see the system, you might have a very hard time controlling it, because it is so fragile. This is basically the case of quantum computing in 2020.

It is for those reasons that deep tech is so exciting.

The next big things will come from deep tech. Failure is always a possibility, and you can't know before you try.

But that's also why its so fun to dare.

Stuff that Ciro Santilli considers "deep tech" as of 2020:

Basic class example.

Applications of power, we have to remember it is there to notice how awesome it is!

"Many Antennas" typically refers to a concept in wireless communication and networking that involves using multiple antennas at the transmitter and/or receiver to improve performance. This technique is often associated with a broader set of technologies commonly known as Multiple Input Multiple Output (MIMO).

Maximal entropy random walk (MERW) is a probabilistic model used in the field of statistical mechanics, random processes, and complex networks. It is based on principles of entropy, particularly the notion of maximizing entropy under certain constraints. The fundamental idea is to model a random walker’s movement across a network or graph in such a way that the walker explores the space as evenly as possible, while still respecting the underlying structure of the graph.

Multi-user MIMO (MU-MIMO) is a wireless communication technology that enhances the capacity and efficiency of a network by allowing multiple users to simultaneously share the same frequency channel. It is a key feature in modern wireless systems, particularly in LTE (Long Term Evolution) and 5G networks. Here's how it works: 1. **Multiple Antennas**: In MU-MIMO, the base station (e.g., a cell tower) is equipped with multiple antennas.

Outage probability is a term commonly used in telecommunications and networking to quantify the likelihood that a system or communication link will fail to meet certain performance criteria, such as data transmission rates or signal quality. It refers to the probability that the quality of service (QoS) falls below a predefined threshold, leading to the inability to effectively transmit information.

Sanov's theorem is a result in statistical mechanics and large deviations theory that describes the asymptotic behavior of the empirical measures of independent random variables. It provides a way to understand how the probabilities of large deviations from the typical behavior of a stochastic system decay as the number of observations increases. Specifically, Sanov’s theorem states that for a sequence of independent and identically distributed (i.i.d.