The story of how it took one 23-year-old engineer a day to remake swimming masks into medical
At the beginning of the epidemic, when medical institutions faced a shortage of personal protective equipment in the “red zone”, in Italy they came up with a technology how to make a medical mask for doctors from a swimming mask. Decathlon company was ready to give diving masks to hospitals. However, to use these masks, it was necessary to attach a special filter requiring an adapter. At the same time, the masks were of different models each needing specially designed additional parts.
Regular manufacturing would have been long and expensive, because first it would have taken producing molds for thermoplastic machines for each part and each machine separately. RUDN University Institute of Innovative Engineering Technologies (IIIT) proposed using additive, SLS (selective laser sintering) technologies and printing parts on Farsoon SS403P industrial 3D printers (Prodways x 4500).
It took RUDN Additive and Edge Technologies Center just one day to launch the production of adapters of the required parameters from certified medical plastic. Work included setting the task for the 3D printer, printing and cooling of the parts themselves, extracting and cleaning. In a day, 400 adapters of the required parameters were printed, and after two days, the Blokhin Cancer Center and the Mukhin City Clinical Hospital received the first batches of adapters and got effective and comfortable masks. Since most employees are in lockdown, part of the industrial design and logistics work was done remotely. The entire production was performed by only one engineer-technologist of the Center —a 23-year-old Mark Dyachenko!
"We began to print adapters for diving masks when it became clear that doctors lacked personal respiratory tract protective equipment. The adapter is installed on the top of the mask, to which 1 or 2 filters are attached. Each printing round makes 400 adapters, as soon as I took out the printed parts, I immediately prepared and started a new print. While the machine was printing parts, I cleaned the finished product. To print adapters, we used special medical plastic, absolutely harmless to the human body. Due to lockdown the work became more complicated, but we were always in touch with colleagues using messengers. I know that the doctors were grateful to us, and the page of one of the charitable organizations had a post with photos of our adapters and a mention of my name" - Mark Dyachenko, engineer-technologist at RUDN Additive and Edge Technologies Center.
Now RUDN has already manufactured 1,149 filter adapters for 3 mask models. Every seventh swimming mask in Russia, has become a mask for the doctors’ protection thanks to the 3D production of the Peoples’ Friendship University of Russia. They are used in 15 medical institutions in Moscow and the Moscow region.
Engineers at the Institute of Innovative Engineering Technologies at RUDN University have begun manufacturing face shields fasteners and hose holders for lung ventilators — 290 holders are already made. University experts continue experiments to improve enhanced protection medical masks.
Reference:
During one month more than 15 medical institutions in Moscow and the Moscow Region received masks with filters adapters manufactured by RUDN University:
- A. Vishnevsky hospital
- Meditsina JSC (Academician Roytberg’s Clinic)
- O.Mukhin Clinical Hospital
- M.Vladimirsky hospital
- I.Davydovsky State Clinical Hospital No. 23
- State Clinical Hospital No. 52
- N.Bauman State Clinical Hospital № 29
- V.Veresaev State Clinical Hospital No. 81
- Hospital for War Veterans No. 2
- Hospital for War Veterans No. 3
- Mozhaisk Central District Hospital
- N. Blokhin Cancer Center
- A.Vishnevsky Surgery Hospital
- Center for Family Planning and Reproduction
- Russian Railways Central Clinical Hospital
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Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
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Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.