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BiologIC Technologies Helps Implement High-throughput Heat Inactivation of Patient Samples at Cambridge Lighthouse Laboratory BiologIC Technologies, a pioneer in Industry 4.0 technologies for the bio-revolution, has collaborated with AstraZeneca and Electrolux Professional to implement a high-throughput solution for heat inactivation of patient samples at the Cambridge Lighthouse Laboratory. This solution renders the virus non-infectious, enhancing the safety, sustainability and scalability of the testing process. This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20210428005091/en/ BiologIC Technologies helps implement high-throughput heat inactivation of patient samples at Cambridge UK COVID-19 Test Centre. (Photo: Business Wire) The Cambridge Lighthouse Laboratory, established by AstraZeneca, the University of Cambridge and GlaxoSmithKline, and subsequently partnering with Charles River Laboratories, ....
Future WiFi networks will be powered by renewable sources. They will also have radio frequency (RF)-energy harvesting devices. In these networks, a solar-powered access point (AP) will be tasked with supporting both nonenergy harvesting or legacy data users such as laptops, and RF-energy harvesting sensor devices. A key issue is ensuring the AP uses its harvested energy efficiently. To this end, this article contributes two novel solutions that allow the AP to control its transmit power to meet the data rate requirement of legacy users and also to ensure RF-energy devices harvest sufficient energy to transmit their sensed data. Advantageously, these solutions can be deployed in current wireless networks, and they do not require perfect channel gain information to sensor devices or noncausal energy arrivals at an AP. The first solution uses a deep Q-network (DQN) whilst the second solution uses model predictive control (MPC) to manage the AP’s transmit power subject to its available e ....
Abstract This paper addresses the congestion problem in cellular networks through the assistance of parcel delivery drones. Drones have the primary task of parcel delivery and a secondary task of acting as relay nodes (hop) to add extra capacity in a cellular network. Base transceiver stations in the cells can admit ground user equipment to communicate directly with the drone (device-to-device communications) through in-band signalling between them. This paper proposes a novel algorithm, called CARLO, which optimizes trajectory and altitude of the drones in order to deliver physical parcels, maximize network capacity and reduce network interference. Our simulation studies show that our solution improves the network throughput while the energy inefficiency of taking detour path to assist congested cells is kept to a minimum. Moreover, it is guaranteed that parcels are delivered before deadline. ....
In this paper, we propose a wireless localization system based on energy-harvesting aided unmanned aerial vehicles (UAV). Our proposed system consists of a ground station (GS), a UAV, and multiple users located on the ground, in which both the ground station and all the ground users (GUs) want to know the locations of the ground users. To this end, the UAV first harvests energy from the GS, and then broadcasts signals to the GUs for localization. Each GU will estimate its location, and then transmits data, including its location information, to the GS with the help of the UAV. The links between nodes experience both large-scale lognormal shadowing and small-scale Nakagami-m fading. We first derive the Cramer-Rao lower bound (CRLB) under spatially correlated shadowing for localization performance evaluation. Next, we analyze the system throughput under delay-limited and delay-tolerant transmission modes. To derive exact closed-form expressions as well as high signal-to-noise ratio (SNR) ....