System Bits: Aug. 2

Helping drones navigate urban environments
While it has been widely discussed, Amazon wants to start using drones to deliver packages by 2017, but if you live in a high-rise apartment, you might be waiting a bit longer because because UAVs (Unmanned Aerial Vehicles) use GPS for localization and navigation but in urban areas, high-rise buildings may block the line of sight to GPS satellites, causing drop-outs or making the signal completely unavailable. Now, University of Illinois assistant professor of aerospace engineering Grace Xingxin Gao and her team are working to overcome those limitations by using vision-based positioning to fill in the gaps when GPS is unavailable.

Gao and her students conducted flight tests in a GPS-challenged environment using the UAV built by her research group. Although Gao’s group has received the FAA Certificate of Authorization (COA) for flying UAVs, their goal is to fly UAVs over busy streets safely. Their solution is to fly UAVs in a moving cage. She said civilian drones are expected to be used in any number of applications, from construction monitoring to emergency response, and for these applications, it is imperative to have accurate, always-available, and safe positioning and navigation to help prevent drones from colliding with tall buildings.

Source: University of Illinois

Given that current vision-based positioning systems lack the ability to aggregate data from multiple sources, have limited computational capabilities, and are incapable of handling large data sets. Gao’s team seeks to integrate on-board GPS with camera vision. They will develop a universal platform and interface to make all image and visual video data accessible to UAVs in real-time. To accomplish that goal, the team will develop algorithms that leverage GPS Direct Positioning (DP), which estimates navigation from the raw signal, instead of GPS scalar tracking, the traditional method.

The team is leveraging GPS Direct Positioning (DP) to provide increased robustness when it comes to overcoming GPS signal noise, attenuation, multipath issues, and obstruction. However, it is also computationally intensive, requiring the team to develop algorithms that reduce computation load and increase robustness by tight-coupling of DP and vision data. The algorithms will partition the tasks into on-board and off-board components, sending some computational work to the cloud or a data center via a wireless network.

Record achieved for bulk superconductor magnetic field
With important implications for practical applications of bulk superconductors, Dr. Mark Ainslie of the Bulk Superconductivity Group at the University of Cambridge, in conjunction with a Japanese research team, has achieved a bulk superconductor magnetic field record. 

The record-high trapped magnetic field of 1.1 T at 13 K in a magnesium diboride (MgB2) bulk superconductor using a practical, pulsed-field magnetisation technique comes on the heels of the Bulk Superconductivity Group’s previous 2014 world record result, where 17.6 T was achieved in a stack of two Gd-Ba-Cu-O high-temperature superconductors at 26 K using a slower and more expensive, field-cooling magnetization technique. Field-cooling is commonly used for fundamental, high-field measurements and gives the best indication of the maximum trapped field capability of a sample.

Sample holder for split-coil PFM experiments with two of the Bulk Superconductivity Group’s Gd-Ba-Cu-O bulk high-temperature superconductors. (Source: University of Cambridge)

The research was carried out in collaboration with Professor Hiroyuki Fujishiro of Iwate University, Japan, in parallel with Ainslie’s recently published work on enhancing the practical trapped magnetic field achievable in bulk high-temperature superconductors using a novel magnetising technique based on a split-coil arrangement with a soft iron yoke to improve the effectiveness of the system.

Placenta-on-a-chip
University of Pennsylvania have developed the first placenta-on-a-chip that can fully model the transport of nutrients across the placental barrier.

The flash-drive-sized device contains two layers of human cells that model the interface between mother and fetus. Microfluidic channels on either side of those layers allow researchers to study how molecules are transported through, or are blocked by, that interface.
Like other organs-on-chips, such as ones developed to simulate lungs, intestines and eyes, the placenta-on-a-chip can mimic and study the function of that human organ in ways that have not been possible using traditional tools.

Research on the team’s placenta-on-a-chip is part of a nationwide effort sponsored by the March of Dimes to identify causes of preterm birth and ways to prevent it. Prematurely born babies may experience lifelong, debilitating consequences, but the underlying mechanisms of this condition are not well understood due in part to the difficulties of experimenting with intact, living human placentae.    

The researchers’ placenta-on-a-chip is a clear silicone device with two parallel microfluidic channels separated by a porous membrane. On one side of those pores, trophoblast cells, which are found at the placental interface with maternal blood, are grown. On the other side are endothelial cells, found on the interior of fetal blood vessels. The layers of those two cell types mimic the placental barrier, the gatekeeper between the maternal and fetal circulatory systems.    
That barrier mediates all transport between mother and fetus during pregnancy. Nutrients, but also foreign agents like viruses, need to be either transported by that barrier or stopped.

The flash-drive-sized device contains two layers of human cells that model the interface between mother and fetus.
(Source : University of Pennsylvania)

While the placenta-on-a-chip is still in the early stages of testing, researchers at Penn and beyond are already planning to use it in studies on preterm birth.