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Virus detection using nanoparticles and deep neural network–enabled smartphone system

Emerging and reemerging infections present an ever-increasing challenge to global health. Here, we report a nanoparticle-enabled smartphone (NES) system for rapid and sensitive virus detection. The virus is captured on a microchip and labeled with specifically designed platinum nanoprobes to induce gas bubble formation in the presence of hydrogen peroxide. The formed bubbles are controlled to make distinct visual patterns, allowing simple and sensitive virus detection using a convolutional neural network (CNN)-enabled smartphone system and without using any optical hardware smartphone attachment. We evaluated the developed CNN-NES for testing viruses such as hepatitis B virus (HBV), HCV, and Zika virus (ZIKV). The CNN-NES was tested with 134 ZIKV-and HBV-spiked and ZIKV-and HCV-infected patient plasma/serum samples. The sensitivity of the system in qualitatively detecting viral-infected samples with a clinically relevant virus concentration threshold of 250 copies/ml was 98.97% with a confidence interval of 94.39 to 99.97%.


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Smartphone systems can also benefit from the recent unprecedented advancements in nanotechnology to develop diagnostic approaches. Catalysis can be considered as one of the popular applications of nanoparticles because of their large surface-to-volume ratio and high surface energy (11–16). So far, numerous diagnostic platforms for cancer and infectious diseases have been developed by substituting enzymes, such as catalase, oxidase, and peroxidase with nanoparticle structures (17–20). Here, we adopted the intrinsic catalytic properties of platinum nanoparticles (PtNPs) for gas bubble formation to detect viruses on-chip using a convolutional neural network (CNN)–enabled smartphone system.

Iron Ox launches world’s first fully-autonomous farm

Circa 2018


Californian robotics company Iron Ox claims to be ‘reinventing farming from the ground up’, as it unveils an autonomous indoor farm that leverages the latest advancements in arable science, machine learning, and robotics.

Indoor farms see harvesting, seeding and plant inspections occur thousands of times a day – tasks perfectly suited to robots. Iron Ox is using the latest in machine learning and computer vision to enable its robots to respond to the needs of individual plants.

The farm is now in full production, thanks to its two key proprietary robotics systems – a robotic arm and a mobile transport. They work cohesively, with the latter using sensors and computer vision technology more typically seen in a self-driving car. The robotic arm, meanwhile, can analyse each plant at sub-millimetre scale.

Artificial intelligence co-pilots US military aircraft for the first time

Artificial intelligence helped co-pilot a U-2 “Dragon Lady” spy plane during a test flight Tuesday, the first time artificial intelligence has been used in such a way aboard a US military aircraft.

Mastering artificial intelligence or “AI” is increasingly seen as critical to the future of warfare and Air Force officials said Tuesday’s training flight represented a major milestone.

“The Air Force flew artificial intelligence as a working aircrew member onboard a military aircraft for the first time, December 15,” the Air Force said in a statement, saying the flight signaled “a major leap forward for national defense in the digital age.”

Do Neural Networks Dream Visual Illusions?

Summary: When convolutional neural networks are trained under experimental conditions, they are deceived by the brightness and color of a visual image in similar ways to the human visual system.

Source: UPF Barcelona.

A convolutional neural network is a type of artificial neural network in which the neurons are organized into receptive fields in a very similar way to neurons in the visual cortex of a biological brain.

Teaching Artificial Intelligence to Adapt

Summary: A new AI model mimics how the prefrontal cortex uses gating to control information flow between different areas of neurons. The system could help in the development of new artificial intelligence technologies that better mimic the human brain.

Source: Salk Institute.

Getting computers to “think” like humans is the holy grail of artificial intelligence, but human brains turn out to be tough acts to follow. The human brain is a master of applying previously learned knowledge to new situations and constantly refining what’s been learned. This ability to be adaptive has been hard to replicate in machines.

IEEE BAU Robotics and Automation Chapter

✨ ′′ Using a high speed 5 G network, a London surgeon has performed remote experimental surgery for a banana based in the U.S. state of California.

This evolution opens up prospects for complicated remote surgeries without going through the trouble of future travel.
#IEEE_BAU_RAS


✨‏باستخدام شبكة 5G فائقة السرعة قام جرّاح في لندن بإجراء عملية جراحية تجريبية عن بُعد لموزة موجودة في ولاية كاليفورنيا الأمريكية.

‏هذا التطور يفتح الآفاق لإجراء عمليات جراحية معقدة عن بعد دون تكبد عناء السفر مستقبلاً.” #IEEE_BAU_RAS