Mobility Increases the Data Offloading Ratio in D2D Caching Networks

Caching at mobile devices, accompanied by device-to-device (D2D) communications, is one promising technique to accommodate the exponentially increasing mobile data traffic. While most previous works ignored user mobility, there are some recent works taking it into account. However, the duration of user contact times has been ignored, making it difficult to explicitly characterize the effect of mobility. In this paper, we adopt the alternating renewal process to model the duration of both the contact and inter-contact times, and investigate how the caching performance is affected by mobility. The data offloading ratio, i.e., the proportion of requested data that can be delivered via D2D links, is taken as the performance metric. We first approximate the distribution of the communication time for a given user by beta distribution through moment matching. With this approximation, an accurate expression of the data offloading ratio is derived. For the homogeneous case where the average contact and inter-contact times of different user pairs are identical, we prove that the data offloading ratio increases with the user moving speed, assuming that the transmission rate remains the same. Simulation results are provided to show the accuracy of the approximate result, and also validate the effect of user mobility.Comment: 6 pages, 5 figures, accepted to IEEE Int. Conf. Commun. (ICC), Paris, France, May 201

2nd IEEE International Mediterranean Conference on Communications and Networking (IEEE MeditCom 2022) 5-8 September 2022, Athens, Greece

International audienc

Metastatic Clear Cell Hidradenocarcinoma: Response to Chemotherapy and Long Disease Control

Introduction: Hidradenocarcinoma is a rare aggressive tumor arising from sweat glands that may occur from preexisting hidradenoma or most frequently appears de novo. It is often located in the head and neck. It is also characterized by a high potential of local recurrence, metastasis and poor outcome. This tumor is often radiotherapy and chemotherapy resistant.Presentation of case: We report a case of a 77-year-old man with a metastatic hidradenocarcinoma to the bone and lymph nodes who was operated 7 years ago for an hidradenoma of the right foot. He was treated with capecitabine-based chemotherapy with good tolerance and obtention of partial response during 10 months. After that, his disease progressed and he died 1 year after diagnosis.Conclusion: Hidradenocarcinoma is a cancer with a poor prognosis . Because of its low prevalence and high rate of recurrence, its treatment is still controversial. Our good result demonstrates that adjunction of chemotherapy in metastatic forms is effective for a better control and long overall survival

A Tutorial on Extremely Large-Scale MIMO for 6G: Fundamentals, Signal Processing, and Applications

Extremely large-scale multiple-input-multiple-output (XL-MIMO), which offers vast spatial degrees of freedom, has emerged as a potentially pivotal enabling technology for the sixth generation (6G) of wireless mobile networks. With its growing significance, both opportunities and challenges are concurrently manifesting. This paper presents a comprehensive survey of research on XL-MIMO wireless systems. In particular, we introduce four XL-MIMO hardware architectures: uniform linear array (ULA)-based XL-MIMO, uniform planar array (UPA)-based XL-MIMO utilizing either patch antennas or point antennas, and continuous aperture (CAP)-based XL-MIMO. We comprehensively analyze and discuss their characteristics and interrelationships. Following this, we examine exact and approximate near-field channel models for XL-MIMO. Given the distinct electromagnetic properties of near-field communications, we present a range of channel models to demonstrate the benefits of XL-MIMO. We further motivate and discuss low-complexity signal processing schemes to promote the practical implementation of XL-MIMO. Furthermore, we explore the interplay between XL-MIMO and other emergent 6G technologies. Finally, we outline several compelling research directions for future XL-MIMO wireless communication systems.Comment: 38 pages, 10 figure

AoI-Minimal Trajectory Planning and Data Collection in UAV-Assisted Wireless Powered IoT Networks

This article investigates the unmanned aerial vehicle (UAV)-assisted wireless powered Internet-of-Things system, where a UAV takes off from a data center, flies to each of the ground sensor nodes (SNs) in order to transfer energy and collect data from the SNs, and then returns to the data center. For such a system, an optimization problem is formulated to minimize the average Age of Information (AoI) of the data collected from all ground SNs. Since the average AoI depends on the UAV's trajectory, the time required for energy harvesting (EH) and data collection for each SN, these factors need to be optimized jointly. Moreover, instead of the traditional linear EH model, we employ a nonlinear model because the behavior of the EH circuits is nonlinear by nature. To solve this nonconvex problem, we propose to decompose it into two subproblems, i.e., a joint energy transfer and data collection time allocation problem and a UAV's trajectory planning problem. For the first subproblem, we prove that it is convex and give an optimal solution by using Karush-Kuhn-Tucker (KKT) conditions. This solution is used as the input for the second subproblem, and we solve optimally it by designing dynamic programming (DP) and ant colony (AC) heuristic algorithms. The simulation results show that the DP-based algorithm obtains the minimal average AoI of the system, and the AC-based heuristic finds solutions with near-optimal average AoI. The results also reveal that the average AoI increases as the flying altitude of the UAV increases and linearly with the size of the collected data at each ground SN

Epidemiology of Coxiella burnetii infection in Africa: a OneHealth systematic review

Background: Q fever is a common cause of febrile illness and community-acquired pneumonia in resource-limited settings. Coxiella burnetii, the causative pathogen, is transmitted among varied host species, but the epidemiology of the organism in Africa is poorly understood. We conducted a systematic review of C. burnetii epidemiology in Africa from a “One Health” perspective to synthesize the published data and identify knowledge gaps.<p></p> Methods/Principal Findings: We searched nine databases to identify articles relevant to four key aspects of C. burnetii epidemiology in human and animal populations in Africa: infection prevalence; disease incidence; transmission risk factors; and infection control efforts. We identified 929 unique articles, 100 of which remained after full-text review. Of these, 41 articles describing 51 studies qualified for data extraction. Animal seroprevalence studies revealed infection by C. burnetii (≤13%) among cattle except for studies in Western and Middle Africa (18–55%). Small ruminant seroprevalence ranged from 11–33%. Human seroprevalence was <8% with the exception of studies among children and in Egypt (10–32%). Close contact with camels and rural residence were associated with increased seropositivity among humans. C. burnetii infection has been associated with livestock abortion. In human cohort studies, Q fever accounted for 2–9% of febrile illness hospitalizations and 1–3% of infective endocarditis cases. We found no studies of disease incidence estimates or disease control efforts.<p></p> Conclusions/Significance: C. burnetii infection is detected in humans and in a wide range of animal species across Africa, but seroprevalence varies widely by species and location. Risk factors underlying this variability are poorly understood as is the role of C. burnetii in livestock abortion. Q fever consistently accounts for a notable proportion of undifferentiated human febrile illness and infective endocarditis in cohort studies, but incidence estimates are lacking. C. burnetii presents a real yet underappreciated threat to human and animal health throughout Africa.<p></p&gt