UAV Swarm-Enabled Aerial CoMP: A Physical Layer Security Perspective

Unlike aerial base station enabled by a single unmanned aerial vehicle (UAV), aerial coordinated multiple points (CoMP) can be enabled by a UAV swarm. In this case, the management of multiple UAVs is important. This paper considers the power allocation strategy for a UAV swarm-enabled aerial network to enhance the physical layer security of the downlink transmission, where an eavesdropper moves following the trajectory of the swarm for better eavesdropping. Unlike existing works, we use only the large-scale channel state information (CSI) and maximize the secrecy throughput in a whole-trajectory-oriented manner. The overall transmission energy constraint on each UAV and the total transmission duration for all the legitimate users are considered. The non-convexity of the formulated problem is solved by using max-min optimization with iteration. Both the transmission power of desired signals and artificial noise (AN) are derived iteratively. Simulation results are presented to validate the effectiveness of our proposed power allocation algorithm and to show the advantage of aerial CoMP by using only the large-scale CSI

UAV-Aided MIMO communications for 5G Internet of Things

The unmanned aerial vehicle (UAV) is a promising enabler of the Internet of Things (IoT) vision, due to its agile maneuverability. In this paper, we explore the potential gain of UAV-aided data collection in a generalized IoT scenario. Particularly, a composite channel model including both large-scale and small-scale fading is used to depict typical propagation environments. Moreover, rigorous energy constraints are considered to characterize IoT devices as practically as possible. A multi-antenna UAV is employed, which can communicate with a cluster of single-antenna IoT devices to form a virtual MIMO link. We formulate a whole-trajectory-oriented optimization problem, where the transmission duration and the transmit power of all devices are jointly designed to maximize the data collection efficiency for the whole flight. Different from previous studies, only the slowly-varying large-scale channel state information (CSI) is assumed available, to coincide with the fact that practically it is quite difficult to predictively acquire the random small-scale channel fading prior to the UAV flight. We propose an iterative scheme to overcome the non-convexity of the formulated problem. The presented scheme can provide a significant performance gain over traditional schemes and converges quickly

Stabilization mechanism of water-in-oil emulsions by medium- and long-chain diacylglycerol: post-crystallization vs. pre-crystallization

The restriction of using trans-fatty acid is driving the food industries to develop natural, healthy and efficient emulsifiers for the fabrication of water-in-oil (W/O) emulsions. In this work, medium- and long-chain diacylglycerol (MLCD) with high nutritional features and surface activities was used for the preparation of emulsion. The influence of crystallization procedures (pre- or post-crystallization) on the emulsions’ stability was examined in terms of the change in droplet size distribution (DSD), sedimentation, microstructure and thermal properties. The sedimentation and coalescence of emulsions were reduced when higher amount (8%, w/w) of MLCD was used. The post-crystallized emulsions showed narrower DSD and less sedimentation compared to the pre-crystallized emulsions. Pre-crystallized emulsion prepared using shear speed of 10,000 rpm showed improved stability due to the reduction of crystal size. MLCD was able to form typical interfacial crystal shells in post-crystallized emulsions whereas only large crystals were formed in the continuous phase in the pre-crystallizations. Therefore, the post-crystallized emulsions had higher thickness and sedimentation was effectively reduced. The findings in this work could be the basis for the future application of MLCD and provide insights on how the physical stabilities of emulsions can be affected when different crystallization processes are employed

Coverage optimization for UAV-aided Internet of Things with partial channel knowledge

Due to the high maneuverability of unmanned aerial vehicles (UAVs), they have been widely deployed to boost the performance of Internet of Things (IoT). In this paper, to promote the coverage performance of UAV-aided IoT communications, we maximize the minimum average rate of the IoT devices by jointly optimizing the resource allocation strategy and the UAV altitude. Particularly, to depict the practical propagation environment, we take the composite channel model including both the small-scale and the large-scale channel fading into account. Due to the difficulty in acquiring the random small-scale channel fading, we assume that only the large-scale channel sate information (CSI) is available. On this basis, we formulate an optimization problem, which is not convex and challenging to solve. Then, an efficient iterative algorithm is proposed using block coordinate descent and successive convex optimization tools. Finally, simulation results are presented to demonstrate the significant performance gain of the proposed scheme over existing ones

Polymerase Epsilon-Associated Ultramutagenesis in Cancer

With advances in next generation sequencing (NGS) technologies, efforts have been made to develop personalized medicine, targeting the specific genetic makeup of an individual. Somatic or germline DNA Polymerase epsilon (PolE) mutations cause ultramutated (>100 mutations/Mb) cancer. In contrast to mismatch repair-deficient hypermutated (>10 mutations/Mb) cancer, PolE-associated cancer is primarily microsatellite stable (MSS) In this article, we provide a comprehensive review of this PolE-associated ultramutated tumor. We describe its molecular characteristics, including the mutation sites and mutation signature of this type of tumor and the mechanism of its ultramutagenesis. We discuss its good clinical prognosis and elucidate the mechanism for enhanced immunogenicity with a high tumor mutation burden, increased neoantigen load, and enriched tumor-infiltrating lymphocytes. We also provide the rationale for immune checkpoint inhibitors in PolE-mutated tumors

Inertial Aided Cycle-slip Detection and Repair for BDS Triple-frequency Signal in Severe Multipath Environment

Inertial information has been proposed to improve the success rate and repair rate for BDS triple-frequency cycle-slip detection in severe environment with multipath effects.At the same time, a BDS/INS loose coupled model has been developed. An innovative INS aided BDS triple-frequency combination method was developed which based on the traditional method of code-phase combination and geometry-free linear combination. The INS aided cycle-slip detection monitoring value was established and the effect of INS positioning error on cycle-slip capacity was analyzed. The proposed method overcomes the shortcoming of cycle-slip detection capacity influenced by the pseudorange observation precision. It also realizes small cycle-slips detection for BDS in severe multipath effects environment. At last, a field test was analysised with INS/BDS triple-frequency integrated positioning system onboard. The results indicate that the method proposed in this paper shows a high cycle-slip detection success rate and repair rate, when traditional triple-frequency detection model losed efficacy above water surface with multipath effects, and it also can be effective in low frequency sampling data