LEAF Mission Seeks To Grow Plants On The Moon

November 6, 2024 by Maya Posch 12 Comments

Space Lab's LEAF model crops & growth chamber. — Credit: Space Lab

We have seen a recent surge of interest in whether it’s possible to grow potatoes and other plants in Martian soil, but what is the likelihood that a future (manned) lunar base could do something similar? To that end [Space Lab] is developing the LEAF project that will be part of NASA’s upcoming Artemis III lunar mission. This mission would be the first to have Americans return to the Moon by about 2028, using the somewhat convoluted multi-system SLS-Starship-Lunar Gateway trifecta. The LEAF (Lunar Effects on Agricultural Flora) science module will feature three types of plants (rape (Brassica Rapa), duckweed and cress (Arabidopsis thaliana) ) in an isolated atmosphere.

The main goal of this project is to find out how the plants are affected by the lunar gravity, radiation and light levels at the landing site at the south pole. This would be the equivalent of a hydroponics setup in a lunar base. After about a week of lunar surface time the growth chamber will be split up into two: one returning back to Earth for examination and the other remains on the surface to observe their long-term health until they perish from cold or other causes.

This is not the first time that growing plants on the lunar surface has been attempted, with China’s Chang’e 4 mission from 2019. The lander’s Lunar Micro Ecosystem featured a range of seeds as well, which reportedly successfully sprouted, but the project was terminated after 9 days instead of the planned 100 due to issues with heating the biosphere during the brutal -52°C lunar night. Hopefully LEAF can avoid this kind of scenario when it eventually is deployed on the Moon.

Amazon Receives FAA Approval For MK30 Delivery Drone

November 6, 2024 by Maya Posch 23 Comments

It’s been about a decade since Amazon began to fly its delivery drones, aiming to revolutionize the online shopping experience with rapid delivery of certain items. Most recently Amazon got permission from the FAA to not only start flying from its new Arizona-based location, but also to fly beyond-visual-line-of-sight (BVLOS) missions with the new MK30 drone. We reported on this new MK30 drone which was introduced earlier this year along with the news of the Amazon Prime Air delivery service ceasing operations in California and moving them to Arizona instead.

This new drone has got twice the range as the old MK27 drone that it replaces and is said to be significantly quieter as well. The BLOS permission means that the delivery drones can service areas which are not directly visible from the warehouse with its attached drone delivery facility. With some people within the service range of the MK27 drones having previously complained about the noise levels, we will see quickly enough whether the MK30 can appease most.

As for the type of parcels you can have delivered with this service, it is limited to 2.27 kg (~5 lbs), which is plenty for medication and a range of other items where rapid delivery would be desirable.

The Hardware pipeline consists of three parts: antenna, signal conditioners, and computer. The solid lines indicate LMR-400 cable (low loss microwave coax), whereas the dotted line represents USB 3.0. (Credit: Jack Phelps)

Tracking Hydrogen In Space With A Home Radio Telescope For 21 Cm Emissions

November 5, 2024 by Maya Posch 7 Comments

What do you get when you put a one-meter parabolic dish, an SDR, a Raspberry Pi, and an H1-LNA for 21 cm emissions together? The answer is: a radio telescope that can track hydrogen in the Milky Way as well as the velocities of hydrogen clouds via their Doppler shifts, according to a paper by [Jack Phelps] titled “Galactic Neutral Hydrogen Structures Spectroscopy and Kinematics: Designing a Home Radio Telescope for 21 cm Emission“.

The hardware pipeline consists of three parts: antenna, signal conditioners, and computer, as per the above graphic by [Jack Phelps]. The solid lines are low-loss microwave coax LMR-400 cable, and the dotted line represents USB 3.0 between the RTL-SDR and Raspberry Pi 4 system. This Raspberry Pi 4 runs a pre-made OS image (NsfSdr) by [Dr. Glenn Langston] at the National Science Foundation, which contains scripts for hydrogen line observation, calibration and data processing.

After calibration, the findings were verified using publicly available data, and the setup could be used to detect hydrogen by pointing the antenna at the intended target in space. Although a one-meter parabolic dish isn’t going to give you the most sensitivity, it’s still pretty rad that using effectively all off-the-shelf components and freely available software, you too can have your own radio telescope.

Flirting With Kessler: Why Space Debris Physics Make It Such An Orbital Pain

November 5, 2024 by Maya Posch 37 Comments

Picture in your mind a big parking lot with 131 million cars on it. Now imagine that they are spread out over the entire Earth’s inhabited areas. Although still a large number, it is absolutely dwarfed by the approximately 1.47 billion cars registered and in use today, with room to spare for houses, parks and much more. The 131 million represents the total number of known and estimated space debris objects in Earth orbit sized 1 mm and up, as per the European Space Agency. This comes on top of the approximately 13,200 satellites still in Earth orbit of which 10,200 are still functional.

Now imagine that most of these 131 million cars of earlier are sized 10 cm or smaller. Spaced out across the Earth’s entire surface you’d not be able to see more than at most one. Above the Earth’s surface there are many orbital planes and no pesky oceans to prevent millimeter and centimeter-sized cars from being spaced out there. This gives a rough idea of just how incredibly empty Earth’s orbital planes are and why from the International Space Station you rarely notice any such space debris until a small bit slams into a solar panel or something equally not amusing.

Cleaning up space debris seems rather unnecessary in this perspective, except that even the tiniest chunk travels at orbital velocities of multiple kilometers per second with kinetic energy to spare. Hence your task: to chase down sub-10 cm debris in hundreds of kilometers of mostly empty orbital planes as it zips along with destructive intent. Surely this cannot be so difficult with lasers on the ISS or something?

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Reusing An Old Android Phone For GPIO With External USB Devices

November 4, 2024 by Maya Posch 44 Comments

Each year millions of old smartphones are either tossed as e-waste or are condemned to lie unloved in dusty drawers, despite the hardware in them usually being still perfectly fine. Reusing these little computers for another purpose once the phone’s manufacturer drops support is made hard by a range of hardware and software (driver) issues. One possible way to do so is suggested by [Doctor Volt] in a video where a Samsung Galaxy S4 is combined with a USB-connected FT232R board to add external GPIO.

The idea is pretty simple: the serial adapter is recognized by the existing Android OS and within the standard Android development environment this module can be used. Within this demonstrator it’s merely used to blink some LEDs and react to inputs, but it shows how to reuse one of these phones in a non-destructive manner. Even better is that the phone’s existing sensors and cameras can still be used as normal in this way, too, which opens a whole range of (cheap) DIY projects that can be programmed either in Java/Kotlin or in C or C++ via the Native Development Kit.

The only wrinkle is that while the phone is connected like this, charging is not possible. For the S4 it’s easy to solve as it has a removable battery, so an external power input was wired in with a dummy battery-sized bit of perfboard. With modern phones without removable batteries simultaneous USB/audio dongle and charging usage via the USB-C connector is claimed to be possible, but this is something to check beforehand.

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Building A Discrete 14-Bit String DAC

November 3, 2024 by Maya Posch 4 Comments

The discrete 14-bit DAC under test. (Credit: Sine Lab, YouTube)

How easy is it to build your own Digital to Analog Converter (DAC)? Although you can readily purchase a wide variety of DACs these days, building your own can be very instructive, as the [Sine Lab] on YouTube explores in a recent video with the construction of a discrete 14-bit DAC. First there are the different architectures you can pick for a DAC, which range from R-2R (resistor ladder) to delta-sigma versions, each having its own level of complexity and providing different response times, accuracy and other characteristics.

The architecture that the [Sine Lab] picked was a String DAC with interpolator. The String type DAC has the advantage of having inherently monotonic output voltage and better switching-induced glitch performance than the R-2R DAC. At its core it still uses resistors and switches (transistors), with the latter summing up the input digital value. This makes adding more bits to the DAC as easy as adding more of these same resistors and switches, the only question is how many. In the case of a String DAC that’d be 2^N, which implies that you want to use multiple strings, as in the above graphic.

Scaling this up to 16-bit would thus entail 65,536 resistors/switches in the naive approach, or with 2 8-bit strings 513 switches, 512 resistors and 2 buffers. In the actual design in the video both MOSFETs and 74HCT4051 multiplexers were used, which also necessitated creating two buses per string to help with the input decoding. This is the part where things get serious in the video, but the reasoning for each change and addition is explained clearly as the full 6-bit DAC with interpolator is being designed and built.

One big issue with discrete DACs comes when you have to find matching MOSFETs and similar, which is where LSI DACs are generally significantly more precise. Even so, this discrete design came pretty close to a commercial offering, which is pretty impressive.

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All You Need For Artificial Intelligence Is A Commodore 64

November 3, 2024 by Maya Posch 49 Comments

Artificial intelligence has always been around us, with [Timothy J. O’Malley]’s 1985 book on AI projects for the Commodore 64 being one example of this. With AI defined as being the theory and development of systems that can perform tasks that normally requiring human intelligence (e.g. visual perception, speech recognition, decision-making), this book is a good introduction to the many ways that computer systems for decades now have been able to learn, make decisions and in general become more human-like. Even if there’s no electronic personality behind the actions.

In the book’s first chapter, [Timothy] isn’t afraid to toss in some opinions about the true nature of intelligence and thinking. Starting with the concept that intelligence is based around storing information and being able to derive meaning from connections between stored pieces of information, the idea of a basic AI as one would use in a game for the computer opponent arises. A number of ways of implementing such an AI is explored in the first and subsequent chapters, using Towers of Hanoi, chess, Nim and other games.

After this we look at natural language processing – referencing ELIZA as an example – followed by heuristics, pattern recognition and AI for robotics. Although much of this may seem outdated in this modern age of LLMs and neural networks, it’s important to realize that much of what we consider ‘bleeding edge’ today has its roots in AI research performed in the 1950s and 1960s. As [Timothy] rightfully states in the final chapter, there is no real limit to how far you can push this type of AI as long as you have more hardware and storage to throw at the problem. This is where we now got datacenters full of GPU-equipped systems churning through vector space calculations for the sake of today’s LLM & diffusion model take on ‘AI’.

Using a Commodore 64 to demonstrate the (lack of) validity of claims is not a new one, with recently a group of researchers using one of these breadbin marvels to run an Ising model with a tensor network and outperforming IBM’s quantum processor. As they say, just because it’s new and shiny doesn’t necessarily mean that it is actually better.