Joint Transmission Scheme and Coded Content Placement in Cluster-Centric UAV-Aided Cellular Networks

Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote learning/working and telemedicine has significantly increased. In this context, preserving high Quality of Service (QoS) and maintaining low-latency communication are of paramount importance. In cellular networks, the incorporation of unmanned aerial vehicles (UAVs) can result in enhanced connectivity for outdoor users due to the high probability of establishing Line of Sight (LoS) links. The UAV's limited battery life and its signal attenuation in indoor areas, however, make it inefficient to manage users' requests in indoor environments. Referred to as the cluster-centric and coded UAV-aided femtocaching (CCUF) framework, the network's coverage in both indoor and outdoor environments increases by considering a two-phase clustering framework for Femto access points (FAPs)' formation and UAVs' deployment. Our first objective is to increase the content diversity. In this context, we propose a coded content placement in a cluster-centric cellular network, which is integrated with the coordinated multipoint (CoMP) approach to mitigate the intercell interference in edge areas. Then, we compute, experimentally, the number of coded contents to be stored in each caching node to increase the cache-hit-ratio, signal-to-interference-plus-noise ratio (SINR), and cache diversity and decrease the users' access delay and cache redundancy for different content popularity profiles. Capitalizing on clustering, our second objective is to assign the best caching node to indoor/outdoor users for managing their requests. In this regard, we define the movement speed of ground users as the decision metric of the transmission scheme for serving outdoor users' requests to avoid frequent handovers between FAPs and increase the battery life of UAVs. Simulation results illustrate that the proposed CCUF implementation increases the cache-hit-ratio, SINR, and cache diversity and decrease the users' access delay, cache redundancy, and UAVs' energy consumption.

Real-Time Temperature Distribution Monitoring in Chinese Solar Greenhouse Using Virtual LAN

The internal air temperature of Chinese solar greenhouse (CSG) has the problem of uneven spatial and temporal distribution. To determine temperature distribution at different locations, we designed a greenhouse temperature real-time monitoring system based on virtual local area network (VLAN) and estimate, including interpolation estimation module, data acquisition, and transmission module. The temperature data were obtained from 24 sensors, and the Ordinary Kriging algorithm estimated the temperature distribution of the whole plane according to the data. The results showed that the real-time temperature distribution monitoring method established was fast and robust. In addition, data validity rate for VLAN technology deployed for data transmission was 2.64% higher than that of cellular network technology. The following results are obtained by interpolation estimation of temperature data using gaussian model. The average relative error (ARE) of estimate, mean absolute error (MAE), root mean square error (RMSE), and determination coefficient (R2) were −0.12 °C, 0.42 °C, 0.56 °C, and 0.9964, respectively. After simple optimization of the number of sensors, the following conclusions are drawn. When the number of sensors were decreased to 12~16, MAE, RMSE, and R2 were 0.40~0.60 °C, 0.60~0.80 °C, and >0.99, respectively. Furthermore, temperature distribution in the greenhouse varied in the east–west and north–south directions and had strong regularity. The calculation speed of estimate interpolation algorithm was 50~150 ms, and greenhouse Temperature Distribution Real-time Monitoring System (TDRMS) realized simultaneous acquisition, processing, and fast estimate.

Wireless sensor network enabled real-time remote intelligent health monitoring and management system using Internet of Things (IoT) sensing with cloud-based processing during covid-19 situation

Mankind was living quite an ordinary life when Covid 19 pandemic struck. The whole world was in turmoil and was busy trying to make the situation normal again. But it was impossible to regain the old scenario and people had to accept the new normal. The new normal demands people to follow different guidelines out of which maintaining a social distance of 6 feet was a prominent one. Even in this situation occurrence of any disease does not stop and there are always some patients visiting a doctor. Also, a doctor doesn't always have the luxury to visit every place to see patients, especially in rural areas where there is a transportation problem. So we have come up with a cloud-based system that will use the internet of things to diagnose a patient. This device will contain different sensors like temperature sensor, body oxygen level sensor, blood pressure sensor, heart rate sensor, and height and weight measuring gadgets to measure the body parameters of the patient and then store this information in the secured cloud which can then be accessed by the doctor to diagnose the patient. The sensors will be embedded in an Arduino and it will be connected to the cloud wirelessly with the help of a GSM module and node MCU. Also, a laptop will be present to connect the patient and the doctor in video mode for conversations. This system will also generate a prescription provided by the doctor which can be used anywhere. Thus, this device will not only promote social distancing but also it will prohibit the spread of diseases that are communicable. The doctors can work from the comfort of their home without touching a patient and also without traveling long distances to remote locations.

Investigating the effect of High-altitude Platform Positioning on Latency and Coverage of 4G Cellular Systems

Wireless communication technologies are rapidly being adopted and developed by countries all over the world as a strategy for sustaining a digital economy. This has proven very useful for economic recovery from the crises brought about by the COVID-19 pandemic of the year 2020. The latency and coverage area of a wireless network are two major areas that are always seeking improvement. The High-Altitude Platform communication technology can provide improvement in speed and coverage area for 4G cellular systems. This work investigated the effect of positioning High Altitude Platforms on the latency and coverage of 4G cellular Systems. A quantitative approach was used in the methodology of this paper. A HAP model showing a single platform flying in a circular trajectory over Base Transceiver Stations BTSs and serving as a relay mobile station was presented. A detailed simulation algorithm for the HAP and results for the simulation were given. Results showed that using the HAP as a relay mobile station in a network can give a latency reduction of up to 58.9%. Also, the altitude of the HAP directly affects the angle of reception which was found to improve the coverage.

Mechanisms of SARS-CoV-2 and Male Infertility: Could Connexin and Pannexin Play a Role?

The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on male infertility has lately received significant attention. SARS-CoV-2, the virus that causes coronavirus disease (COVID-19) in humans, has been shown to impose adverse effects on both the structural components and function of the testis, which potentially impact spermatogenesis. These adverse effects are partially explained by fever, systemic inflammation, oxidative stress, and an increased immune response leading to impaired blood-testis barrier. It has been well established that efficient cellular communication via gap junctions or functional channels is required for tissue homeostasis. Connexins and pannexins are two protein families that mediate autocrine and paracrine signaling between the cells and the extracellular environment. These channel-forming proteins have been shown to play a role in coordinating cellular communication in the testis and epididymis. Despite their role in maintaining a proper male reproductive milieu, their function is disrupted under pathological conditions. The involvement of these channels has been well documented in several physiological and pathological conditions and their designated function in infectious diseases. However, their role in COVID-19 and their meaningful contribution to male infertility remains to be elucidated. Therefore, this review highlights the multivariate pathophysiological mechanisms of SARS-CoV-2 involvement in male reproduction. It also aims to shed light on the role of connexin and pannexin channels in disease progression, emphasizing their unexplored role and regulation of SARS-CoV-2 pathophysiology. Finally, we hypothesize the possible involvement of connexins and pannexins in SARS-CoV-2 inducing male infertility to assist future research ideas targeting therapeutic approaches.

Microwave Emissions and the Problem of Modern Viral Diseases.

The results of a study on the mechanisms of the influence of an increased level of microwave radiation on the growth of infectious, primarily viral, diseases in the environment are presented. This is the radiation of the earth's ionosphere, which reached its maximum in the late 1980s-early 2000s, following an increase in the level of solar activity since the 17th century. Over the past 30 years, the anthropogenic electromagnetic background has increased 100 times due to the development of cellular mobile communications and computerization. The predicted interaction of natural and anthropogenic sources of microwaves sharply increases their negative impact on the ecological situation. Of particular concern is the active spread in recent years of the new 5G communication standard; in the future, it is the development of the most dangerous millimeter range in our country. Energy from the environment in the microwave range can cause "unexpected behavior" in the DNA of viruses. Clarifications to the recommendations of experts on the protection of the population with the help of electromagnetic shielding, obtained in the framework of supramolecular physics of the environment, are proposed.

Effects of Drugs Formerly Proposed for COVID-19 Treatment on Connexin43 Hemichannels.

Connexin43 (Cx43) hemichannels form a pathway for cellular communication between the cell and its extracellular environment. Under pathological conditions, Cx43 hemichannels release adenosine triphosphate (ATP), which triggers inflammation. Over the past two years, azithromycin, chloroquine, dexamethasone, favipiravir, hydroxychloroquine, lopinavir, remdesivir, ribavirin, and ritonavir have been proposed as drugs for the treatment of the coronavirus disease 2019 (COVID-19), which is associated with prominent systemic inflammation. The current study aimed to investigate if Cx43 hemichannels, being key players in inflammation, could be affected by these drugs which were formerly designated as COVID-19 drugs. For this purpose, Cx43-transduced cells were exposed to these drugs. The effects on Cx43 hemichannel activity were assessed by measuring extracellular ATP release, while the effects at the transcriptional and translational levels were monitored by means of real-time quantitative reverse transcriptase polymerase chain reaction analysis and immunoblot analysis, respectively. Exposure to lopinavir and ritonavir combined (4:1 ratio), as well as to remdesivir, reduced Cx43 mRNA levels. None of the tested drugs affected Cx43 protein expression.

Machine-Learning-Based Uplink Throughput Prediction from Physical Layer Measurements

The uplink (UL) throughput prediction is indispensable for a sustainable and reliable cellular network due to the enormous amounts of mobile data used by interconnecting devices, cloud services, and social media. Therefore, network service providers implement highly complex mobile network systems with a large number of parameters and feature add-ons. In addition to the increased complexity, old-fashioned methods have become insufficient for network management, requiring an autonomous calibration to minimize utilization of the system parameter and the processing time. Many machine learning algorithms utilize the Long-Term Evolution (LTE) parameters for channel throughput prediction, mainly in favor of downlink (DL). However, these algorithms have not achieved the desired results because UL traffic prediction has become more critical due to the channel asymmetry in favor of DL throughput closing rapidly. The environment (urban, suburban, rural areas) affect should also be taken into account to improve the accuracy of the machine learning algorithm. Thus, in this research, we propose a machine learning-based UL data rate prediction solution by comparing several machine learning algorithms for three locations (Houston, Texas, Melbourne, Florida, and Batman, Turkey) and determine the best accuracy among all. We first performed an extensive LTE data collection in proposed locations and determined the LTE lower layer parameters correlated with UL throughput. The selected LTE parameters, which are highly correlated with UL throughput (RSRP, RSRQ, and SNR), are trained in five different learning algorithms for estimating UL data rates. The results show that decision tree and k-nearest neighbor algorithms outperform the other algorithms at throughput estimation. The prediction accuracy with the R2 determination coefficient of 92%, 85%, and 69% is obtained from Melbourne, Florida, Batman, Turkey, and Houston, Texas, respectively.

Extracellular Vesicles and Acute Kidney Injury: Potential Therapeutic Avenue for Renal Repair and Regeneration.

Acute kidney injury (AKI) is a sudden decline of renal function and represents a global clinical problem due to an elevated morbidity and mortality. Despite many efforts, currently there are no treatments to halt this devastating condition. Extracellular vesicles (EVs) are nanoparticles secreted by various cell types in both physiological and pathological conditions. EVs can arise from distinct parts of the kidney and can mediate intercellular communication between various cell types along the nephron. Besides their potential as diagnostic tools, EVs have been proposed as powerful new tools for regenerative medicine and have been broadly studied as therapeutic mediators in different models of experimental AKI. In this review, we present an overview of the basic features and biological relevance of EVs, with an emphasis on their functional role in cell-to-cell communication in the kidney. We explore versatile roles of EVs in crucial pathophysiological mechanisms contributing to AKI and give a detailed description of the renoprotective effects of EVs from different origins in AKI. Finally, we explain known mechanisms of action of EVs in AKI and provide an outlook on the potential clinical translation of EVs in the setting of AKI.

Design of low cost IoT enabled embedded control system for covid free smart home

In the era of automation, the Internet of Things (IoT) has come up as a solution and innovation for many applications to improve the basic facilities required in the day-to-day routine. IoT, itself is the interconnectivity of different physical devices with the help of wireless networks e.g., Bluetooth, Wi-Fi without human intervention. The low-cost embedded control unit for Covid free Smart Home is based on the idea of home automation by keeping the current situation of the Covid pandemic in mind. Irradiation of Ultraviolet C (UVC) spectrum is used to sanitize household goods, where convectional sanitization process is not suitable. Simple home automation means controlling or monitoring different electronic/electrical home appliances, devices, and other such things with smartphones or by doing sensor-based operations. All the required devices are connected with one embedded control unit which is managed through a mobile app. This functionality can be accessed either by manually operating a mobile app or with voice assistants e.g., Alexa or Google Assistant, etc. The basic point of communication among devices is based on real-time sensor inputs, which trigger the devices for action and react as per requirements. Ambient light sensors are used to control the on/off the functionality of lights based on the intensity of light present naturally. In this scenario, lights will be switched off in day mode and switched on in night mode. Advancement in wireless technologies enables the researchers to apply various modes of communications among the sensors, gateway, and applications. Bluetooth, Wireless sensor network (WSN), Wi-Fi, Global system for mobile communication (GSM) are a few of them, which are being used either in sensing nodes or in communication gateway to make home automation free of the wired network.

Applying Infinite Petri Nets to the Cybersecurity of Intelligent Networks, Grids and Clouds

Correctness of networking protocols represents the principal requirement of cybersecurity. Correctness of protocols is established via the procedures of their verification. A classical communication system includes a pair of interacting systems. Recent developments of computing and communication grids for radio broadcasting, cellular networks, communication subsystems of supercomputers, specialized grids for numerical methods and networks on chips require verification of protocols for any number of devices. For analysis of computing and communication grid structures, a new class of infinite Petri nets has been introduced and studied for more than 10 years. Infinite Petri nets were also applied for simulating cellular automata. Rectangular, triangular and hexagonal grids on plane, hyper cube and hyper torus in multidimensional space have been considered. Composing and solving in parametric form infinite Diophantine systems of linear equations allowed us to prove the protocol properties for any grid size and any number of dimensions. Software generators of infinite Petri net models have been developed. Special classes of graphs, such as a graph of packet transmission directions and a graph of blockings, have been introduced and studied. Complex deadlocks have been revealed and classified. In the present paper, infinite Petri nets are divided into two following kinds: a single infinite construct and an infinite set of constructs of specified size (and number of dimensions). Finally, the paper discusses possible future work directions.