While it doesn’t have the recognition of DEF CON or even HOPE, the Trenton Computer Festival (TCF) holds the record for the longest continually running computer convention, dating all the way back to 1976. TCF has offered vendor spaces, a swap meet, workshops, and keynote talks for almost as long as the personal computer has existed. But until now, all that knowledge was only available to those in the Northeast US that were willing to follow the itinerant event as its bounced between venues over the decades.
Two years might not sound like much, especially given the fact that there’s still 40+ years unaccounted for. But thanks to the incredible amount of content that is squeezed into each year’s event, the TCF YouTube channel is currently playing host to more than 80 presentations that run the gamut from live musical performances to deep-dives on the Apollo Guidance Computer and quantum computing. Whatever you’re interests happen to be, there’s a good chance you’ll find a presentation or two that talks about it in this impressive collection.
When we made our last visit to this legendary convention, our only real complaint was the fact that none of the presentations were being recorded. With over 40 talks crammed into a six hour event, attendees couldn’t hope but to see more than a fraction of what was on the schedule. The nature of going virtual obviously made it much easier to preserve all this incredible content for later viewing, but it’s unclear if the organizers will be able to maintain that momentum in 2023 when it’s expected TCF will once again be in-person.
Here’s a little eye-opener for you: next time you’re taking a walk, cast your eyes to the ground for a bit and see how far you can go without spotting a carelessly discarded face mask. In our experience, it’s no more than a block or two, especially if you live near a school. Masks and other disposal artifacts of the COVID-19 pandemic have turned into a menace, and uncounted billions of the things will be clogging up landfills, waterways, and byways for decades to come.
Unless they can be recycled into something useful, of course, like the plastic cases used for rapid antigen tests. This comes to us by way of [Ric Real] from the Design and Manufacturing Futures lab at the University of Bristol in the UK. If any of this sounds or looks familiar, refer back to October when the same team presented a method for turning old masks into 3D printer filament. The current work is an extension of that, but feeds the polypropylene pellets recovered from the old masks into a desktop injection molding machine.
The injection molding machine is fitted with 3D-printed molds for the shells of lateral flow devices (LFD) used for COVID-19 rapid antigen testing. The mold tooling was designed in Fusion 360 and printed on an Elegoo Mars MSLA printer using a high-strength, temperature-resistant resin. The molds stood up to the manual injection molding process pretty well, making good-quality parts in the familiar blue and white colors of the starting material. It’s obviously a proof of concept, but it’s good to see someone putting some thought into what we can do with the megatonnes of plastic waste generated by the pandemic response.
[Vaibhav Chhabra], the co-founder of Maker’s Asylum hackerspace in Mumbai, India, starts his Remoticon talk by telling a short story about how the hackerspace rose to its current status. Born out of frustration with a collapsed office ceiling, having gone through eight years of moving and reorganizations, it accumulated a loyal participant base – not unusual with hackerspaces that are managed well. This setting provided a perfect breeding ground for the M19 effort when COVID-19 reached India, mixing “what can we do” and “what should we do” inquiries into a perfect storm and starting the 49 day work session that swiftly outgrew the hackerspace, both physically and organizationally.
When the very first two weeks of the Infinite Two Week Quarantine Of 2020 were announced in India, a group of people decided to wait it out at the hackerspace instead of confining themselves to their homes. As various aspects of our society started crashing after the direct impact of COVID-19, news came through – that of a personal protective equipment shortage, especially important for frontline workers. Countries generally were not prepared when it came to PPE, and India was no different. Thus, folks in Maker’s Asylum stepped up, finding themselves in a perfect position to manufacture protective equipment when nobody else was prepared to help.
We’ve seen a wide variety of mask sanitization solutions, and now, [spiritplumber] from [Robots Everywhere] brings us a frugal and ingenious design – one that you barely even need tools for. This project might look rough around the edges but looks were never a prerequisite, and as a hacker worth their salt will recognize – this is an answer to “how to design a mask disinfector that anyone can build”.
Local shortages of masks have been threatening communities here and there, doubly so if you need a specific kind of mask that might be out of stock. This design could apply to a whole lot of other things where sterilization is desired, too – improving upon concepts, after all, is our favourite pastime.
The design is simple – a battery-powered motor rotating a mask inside a vat of concentrated H2O2, turned into mist by a cheap ultrasonic misting gadget. As the “turntable” rotates a your PPE of choice, making sure that every crevice is graced with cleaning touch of peroxide, it also causes the H2O2 mist to circulate. Fulfilling most important requirements for a proper sanitization system that more complex devices have been struggling with, this approach has certainly earned its place under the sun.
Throughout this two-year global COVID-19 nightmare, one thing that has been sorely lacking is access to testing. “Flu-like symptoms” covers a lot of ground, and knowing if a sore throat is just a sore throat or something more is important enough that we’ve collectively plowed billions into testing. Unfortunately, the testing infrastructure remains unevenly distributed, which is a problem this backpack SARS-CoV-2 testing lab aims to address.
The portable lab, developed by [E. Emily Lin] and colleagues at the Queen Mary University of London, uses a technique called LAMP, for loop-mediated isothermal amplification. LAMP probably deserves an article of its own to explain the process, but suffice it to say that like PCR, LAMP amplifies nucleic acid sequences, but does so without the need for expensive thermal cycling equipment. The kit contains a microcentrifuge that’s fashioned from an e-waste hard drive, a 3D printed rotor, and an Arduino to drive the motor and control the speed. The centrifuge is designed to run on any 12 VDC source, meaning the lab can be powered by a car battery or solar panel if necessary. Readout relies on the trusty Mark I eyeball and a pH-indicating buffer that changes color depending on how much SARS-CoV-2 virus was in the sample.
Well, that didn’t go quite as we expected, did it? Wind the clock back 365 days, and the world seemed to be breathing a collective sigh of relief after making it through 2020 in one piece. Folks started getting their COVID-19 vaccines, and in-person events started tentatively putting new dates on the calendar. After a rough year, it seemed like there was finally some light at the end of the tunnel.
Turns out, it was just a another train. New variants of everyone’s favorite acute respiratory syndrome have kept the pandemic rolling, and in many parts of the world, the last month or so has seen more new cases of the virus than at any point during 2020. This is the part of the Twilight Zone episode were we realize that not only have we not escaped the danger, we didn’t even understand the scope of it to begin with.
Case in point, the chip shortages. We can’t blame it entirely on the pandemic, but it certainly hasn’t helped matters. From video game systems to cars, production has crawled to a standstill as manufacturers fight to get their hands on integrated circuits that were once plentiful. It’s not just a problem for industry either, things have gotten so bad that there’s a good chance most of the people reading this have found themselves unable to get their hands on a part or two these last few months. If you were working on a hobby project, it’s a temporary annoyance. But for those who planned on finally bringing their latest big idea to market, we’ve heard tales of heartbreaking delays and costly redesigns.
It would be easy to look at the last twelve months and see nothing but disappointment, but that’s hardly the attitude you want to have at the beginning of the year. So let’s take the high road, and look back on some of the highlights from 2021 as we turn a hopeful eye towards the future.
Surprisingly there are no pre-symptomatic screening methods for the common cold or the flu, allowing these viruses to spread unbeknownst to the infected. However, if we could detect when infected people will get sick even before they were showing symptoms, we could do a lot more to contain the flu or common cold and possibly save lives. Well, that’s what this group of researchers in this highly collaborative study set out to accomplish using data from wearable devices.
Participants of the study were given an E4 wristband, a research-grade wearable that measures heart rate, skin temperature, electrodermal activity, and movement. They then wore the E4 before and after inoculation of either influenza or rhinovirus. The researchers used 25 binary, random forest classification models to predict whether or not participants were infected based on the physiological data reported by the E4 sensor. Their results are pretty lengthy, so I’ll only highlight a few major discussion points. In one particular analysis, they found that at 36 hours after inoculation their model had an accuracy of 89% with a 100% sensitivity and a 67% specificity. Those aren’t exactly world-shaking numbers, but something the researchers thought was pretty promising nonetheless.
One major consideration for the accuracy of their model is the quality of the data reported by the wearable. Namely, if the data reported by the wearable isn’t reliable itself, no model derived from such data can be trustworthy either. We’ve discussed those points here at Hackaday before. Another major consideration is the lack of a control group. You definitely need to know if the model is simply tagging everyone as “infected” (which specificity does give us an idea of, to be fair) and a control group of participants who have not been inoculated with either virus would be one possible way to answer that question. Fortunately, the researchers admit this limitation of their work and we hope they will remedy this in future studies.