AEGIS – Mobile Device for Generating Electromagnetic Curtain for Special Applications and Countering the Threats of RCIED

In the article the concept, design and realization of the technological demonstrator of a mobile device for generating an electromagnetic curtain (with a name AEGIS) were presented, both in the hardware and software areas. The device is designed to block the radio communication which allow detonating the Radio Controlled Improvised Explosive Devices (RCIEDs). The preliminary laboratory tests of the demonstrator for generating the jamming signal, that were presented in the paper, aimed at assessing the correctness of the device operation and verification of generated signal parameters. On the basis of the obtained results, the ability to jam the cellular systems as well as other radio devices operating in the frequency band from 400 MHz to 2700 MHz was assessed

Human TRMT2A methylates tRNA and contributes to translation fidelity

5-Methyluridine (m5U) is one of the most abundant RNA modifications found in cytosolic tRNA. tRNA methyltransferase 2 homolog A (hTRMT2A) is the dedicated mammalian enzyme for m5U formation at tRNA position 54. However, its RNA binding specificity and functional role in the cell are not well understood. Here we dissected structural and sequence requirements for binding and methylation of its RNA targets. Specificity of tRNA modification by hTRMT2A is achieved by a combination of modest binding preference and presence of a uridine in position 54 of tRNAs. Mutational analysis together with cross-linking experiments identified a large hTRMT2A–tRNA binding surface. Furthermore, complementing hTRMT2A interactome studies revealed that hTRMT2A interacts with proteins involved in RNA biogenesis. Finally, we addressed the question of the importance of hTRMT2A function by showing that its knockdown reduces translation fidelity. These findings extend the role of hTRMT2A beyond tRNA modification towards a role in translation

LTE and NB-IoT Performance Estimation Based on Indicators Measured by the Radio Module

Monitoring the operating parameters of power grids is extremely important for their proper functioning as well as for ensuring the security of the entire infrastructure. As the idea of the Internet of Things becomes more ubiquitous, there are tools for monitoring the state of the complex electrical grid and means to control it. There are also developed new measuring devices and transmission technologies allowing for the transfer of performed measurements from many places to the network management center. However, there are still no devices that act as data concentrators, which would integrate many transmission technologies and protocols in one device, supporting the communication between those different transmission technologies and which would realize edge computing to assist the management center by prioritizing and combining transmitted data. In this article, the authors present a device that meets the above-mentioned requirements. There are presented research results leading to the development of a decision algorithm, called Multilink—ML, dedicated to the presented device. This algorithm enables the selection between LTE and NB-IoT interfaces for packet transmission without the need to burden the communication system with additional transmissions

LTE and NB-IoT Performance Estimation Based on Indicators Measured by the Radio Module

Monitoring the operating parameters of power grids is extremely important for their proper functioning as well as for ensuring the security of the entire infrastructure. As the idea of the Internet of Things becomes more ubiquitous, there are tools for monitoring the state of the complex electrical grid and means to control it. There are also developed new measuring devices and transmission technologies allowing for the transfer of performed measurements from many places to the network management center. However, there are still no devices that act as data concentrators, which would integrate many transmission technologies and protocols in one device, supporting the communication between those different transmission technologies and which would realize edge computing to assist the management center by prioritizing and combining transmitted data. In this article, the authors present a device that meets the above-mentioned requirements. There are presented research results leading to the development of a decision algorithm, called Multilink—ML, dedicated to the presented device. This algorithm enables the selection between LTE and NB-IoT interfaces for packet transmission without the need to burden the communication system with additional transmissions

Channel State Estimation in LTE-Based Heterogenous Networks Using Deep Learning

Following the continuous development of the information technology, the concept of dense urban networks has evolved as well. The powerful tools, like machine learning, break new ground in smart network and interface design. In this paper the concept of using deep learning for estimating the radio channel parameters of the LTE (Long Term Evolution) radio interface is presented. It was proved that the deep learning approach provides a significant gain (almost 40%) with 10.7% compared to the linear model with the lowest RMSE (Root Mean Squared Error) 17.01%. The solution can be adopted as a part of the data allocation algorithm implemented in the telemetry devices equipped with the 4G radio interface, or, after the adjustment, the NB-IoT (Narrowband Internet of Things), to maximize the reliability of the services in harsh indoor or urban environments. Presented results also prove the existence of the inverse proportional dependence between the number of hidden layers and the number of historical samples in terms of the obtained RMSE. The increase of the historical data memory allows using models with fewer hidden layers while maintaining a comparable RMSE value for each scenario, which reduces the total computational cost

General solution to the band-broadening problem in polymer molecular weight distributions

A method is developed for overcoming the problem of band broadening ( where a sample which is monodisperse in molecularweight elutes over a range of elution volumes) in order to obtain accurate molecularweight distributions of polymers using size exclusion chromatography ( SEC). It is proved that the SEC signal from an exponential number distribution ( as obtained from free-radical polymerization under certain conditions) has the same functional form at the maximum, irrespective of band broadening. This leads to a method for quantifying the band broadening from any SEC trace, and hence for deconvoluting the trace to obtain the true distribution - by free- radical polymerization one should synthesize 'standards' which have exponential distributions and then carry out least-squares fitting to find the corresponding broadening function. The new method opens the way for mechanistic understanding and rate parameters to be obtained from the full detail that has hitherto been inaccessible in molecular weight distributions