This paper studies a mobile edge computing (MEC) system in which two mobile devices are energized by the wireless power transfer (WPT) from an access point (AP) and they can offload part or all of their computation-intensive latency-critical tasks to the AP connected with an MEC server or an edge cloud. This harvest-then-offload protocol operates in an optimized timedivision manner. To overcome the doubly near-far effect for the farther mobile device, cooperative communications in the form of relaying via the nearer mobile device is considered for offloading. Our aim is to minimize the AP's total transmit energy subject to the constraints of the computational tasks. We illustrate that the optimization is equivalent to a min-max problem, which can be optimally solved by a two-phase method. The first phase obtains the optimal offloading decisions by solving a sum-energysaving maximization problem for given an energy transmit power. In the second phase, the optimal minimum energy transmit power is obtained by a bisection search method. Numerical results demonstrate that the optimized MEC system utilizing cooperation has significant performance improvement over systems without cooperation.

In this paper, we study an unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) architecture, in which a UAV roaming around the area may serve as a computing server to help user equipment (UEs) compute their tasks or act as a relay for further offloading their computation tasks to the access point (AP). We aim to minimize the weighted sum energy consumption of the UAV and UEs subject to the task constraints, the information-causality constraints, the bandwidth allocation constraints and the UAV's trajectory constraints. The required optimization is nonconvex, and an alternating optimization algorithm is proposed to jointly optimize the computation resource scheduling, bandwidth allocation, and the UAV's trajectory in an iterative fashion. Numerical results demonstrate that significant performance gain is obtained over conventional methods. Also, the advantages of the proposed algorithm are more prominent when handling computation-intensive latency-critical tasks.

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The sporadic emergence of New Delhi metallo-β-lactamase-1 (NDM-1)-producing Acinetobacter spp. has been reported in China; however, NDM-1-positive bacteria epidemics are rarely reported in intensive care units (ICUs) in China, or even in the world. During 15 months' surveillance Acinetobacter spp. isolated from patients, heathcare workers and surfaces of a Chinese ICU were screened for the bla(NDM-1) gene. A total of 27 of 3114 Acinetobacter spp. strains were NDM-1 positive and identified as A. pittii with sequence type 63 (ST63) by multilocus sequence typing. Of the 27 NDM-1-positive A. pittii strains, 22 were isolated from the ICU surfaces and grouped into a major clone A using pulsed-field gel electrophoresis typing, while the other five strains isolated from the patients were classified into three clones (A, B and C). The bla(NDM-1) gene was located on a 45-kb plasmid for all three A. pittii clones. The plasmid could be transferred to A. pittii and A. baumannii recipients at both 30 and 37°C but not to Escherichia coli J53. The plasmid could not be classified into any of the known plasmid incompatibility groups. The bla(NDM-1) region in the plasmid was flanked by two insertion sequence elements, ISAba125 and ISAba11, and no other carbapenemase gene was present in this NDM-1-positive A. pittii isolate. Thus, we present the first report on the transmission and characterization of NDM-1-producing A. pittii in an ICU in China as well as a novel bla(NDM-1) gene-bearing plasmid.

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