Proactive wireless caching and device to device (D2D) communication have emerged as promising techniques for enhancing users' quality of service and network performance. In this paper, we propose a new architecture for D2D caching with inter-cluster cooperation. We study a cellular network in which users cache popular files and share them with other users either in their proximity via D2D communication or with remote users using cellular transmission. We characterize the network average delay per request from a queuing perspective. Specifically, we formulate the delay minimization problem and show that it is NP-hard. Furthermore, we prove that the delay minimization problem is equivalent to the minimization of a non-increasing monotone supermodular function subject to a uniform partition matroid constraint. A computationally efficient greedy algorithm is proposed which is proven to be locally optimal within a factor (1 − e −1 ) ≈ 0.63 of the optimum. We analyze the average per request throughput for different caching schemes and conduct the scaling analysis for the average sum throughput. We show how throughput scaling depends on video content popularity when the number of files grows asymptotically large. Simulation results show a delay reduction of 45% to 80% compared to a D2D caching system without inter-cluster cooperation.

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Providing connectivity to aerial users, such as cellular-connected unmanned aerial vehicles (UAVs) or flying taxis, is a key challenge for tomorrow's cellular systems. In this paper, the use of coordinated multi-point (CoMP) transmission along with caching for providing seamless connectivity to aerial users is investigated. In particular, a network of clustered cache-enabled small base stations (SBSs) serving aerial users is considered in which a requested content by an aerial user is cooperatively transmitted from collaborative ground SBSs. For this network, a novel upper bound expression on the coverage probability is derived as a function of the system parameters. The effects of various system parameters such as collaboration distance and content availability on the achievable performance are then investigated. Results reveal that, when the antennas of the SBSs are tilted downwards, the coverage probability of a high-altitude aerial user is upper bounded by that of a ground user regardless of the transmission scheme. Moreover, it is shown that for a low signal-to-interference-ratio (SIR) threshold, CoMP transmission improves the coverage probability for aerial users from 10% to 70% under a collaboration distance of 200 m.

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Ependymomas are glial tumors derived from differentiated Background: ependymal cells. In contrast to other types of brain tumors, histological grading is not a good prognostic marker for these tumors. In order to determine genomic changes in an anaplastic ependymoma, we analyzed its mutation patterns by next generation sequencing (NGS).Tumor DNA was sequenced using an Ion PI v3 chip on Ion PubMed Abstract | Publisher Full Text | Free Full Text 3. Wesseling P, Capper D: WHO 2016 Classification of gliomas. Neuropathol Appl Neurobiol. 2018; 44(2): 139-150. PubMed Abstract | Publisher Full Text 4. Ostrom QT, Gittleman H, Fulop J, et al.: CBTRUS Statistical Report: Primary Brain and Central Nervous System Tumors Diagnosed in the United States in 2008-2012. Neuro Oncol. 2015; 17 Suppl 4: iv1-iv62. PubMed Abstract | Publisher Full Text | Free Full Text 5. Zamora C, Huisman TA, Izbudak I: Supratentorial Tumors in Pediatric Patients. Neuroimaging Clin N Am. 2017; 27(1): 39-67. PubMed Abstract | Publisher Full Text 6. Kilday JP, Rahman R, Dyer S, et al.: Pediatric ependymoma: biological perspectives. Mol Cancer Res. 2009; 7(6): 765-786. PubMed Abstract | Publisher Full Text 7. Hamilton RL, Pollack IF: The molecular biology of ependymomas. Brain Pathol. 1997; 7(2): 807-822. PubMed Abstract | Publisher Full Text 8. Horn B, Heideman R, Geyer R, et al.: A multi-institutional retrospective study of intracranial ependymoma in children: identification of risk factors. J Pediatr Hematol Oncol. 1999; 21(3): 203-211. PubMed Abstract | Publisher Full Text 9. Spoto GP, Press GA, Hesselink JR, et al.: Intracranial ependymoma and subependymoma: MR manifestations. AJR Am J Roentgenol. 1990; 154(4): 837-845. PubMed Abstract | Publisher Full Text 10. Andrade FG, de Aguiar PH, Matushita H, et al.: Intracranial and spinal ependymoma: series at Faculdade de Medicina, Universidade de São Paulo. Arq Neuropsiquiatr. 2009; 67(3A): 626-632. PubMed Abstract | Publisher Full Text 11. Vera-Bolanos E, Aldape K, Yuan Y, et al.: Clinical course and progression-free survival of adult intracranial and spinal ependymoma patients. Neuro Oncol. 2015; 17(3): 440-447. PubMed Abstract | Publisher Full Text | Free Full Text 12. Milano MT, Johnson MD, Sul J, et al.: Primary spinal cord glioma: a Surveillance, Epidemiology, and End Results database study. J Neurooncol. 2010; 98(1): 83-92. PubMed Abstract | Publisher Full Text 13. Louis DN, Perry A, Reifenberger G, et al.: The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathol. 2016; 131(6): 803-820. PubMed Abstract | Publisher Full Text 14. Leeper H, Felicella MM, Walbert T: Recent Advances in the Classification and Treatment of Ependymomas. Curr Treat Options Oncol. 2017; 18(9): 55. PubMed Abstract | Publisher Full Text 15. Hirose Y, Aldape K, Bollen A, et al.: Chromosomal abnormalities subdivide ependymal tumors into clinically relevant groups. Am J Pathol. 2001; 158(3): 1137-1143. PubMed Abstract | Publisher Full Text | Free Full Text 16. Ross GW, ...