Addition of g-C3N4 to ZnO and ZnFe2O4 to improve photocatalytic degradation of emerging organic pollutants

The use of heterojunctions with different semiconductors has shown to be an important strategy to increase the efficiency of heterogeneous photocatalytic processes. In this regard, heterojunctions consisting of ZnO/g-C 3 N 4 (x-Zn/gCN) and ZnFe 2 O 4 /g-C 3 N 4 (x-ZF/gCN) were synthesized in different mass proportions of g-C 3 N 4 (x = 10, 50 and 80%) through the following simple methods combination: mixture, sonication and thermal treatment. Observations from X-ray diffractometry (XRD), Fourier-transform infrared spectra (FTIR) and field emission scanning electron microscope (FESEM) analyses confirmed that the materials were successfully formed. The g-C 3 N 4 incorporation was important in the textural and optical properties modification of the heterojunctions produced. In addition, in the photoluminescence spectroscopy (PL), it was possible to observe g-C 3 N 4 influence in the 50-Zn/gCN emission profile changing, reducing the direct recombination rate of the photogenerated charges due to a probable Z-scheme mechanism. This catalyst demonstrated greater efficiency of photocatalytic degradation when compared to the remaining materials, both for cefazolin (CFZ) and reactive black 5 (RB5), reaching 78% and 95%, respectively, after 120 min. Moreover, it also revealed good photostability after five successive cycles. 50-Zn/gCN heterojunction presents a promising character in photocatalytic reactions mediated by solar light for contaminants degradation such as pharmaceutical products and dyes and can be used as an alternative to minimize the effects of water pollution caused during the COVID-19 pandemic. [Display omitted] • ZnO/g-C 3 N 4 and ZnFe 2 O 4 /g-C 3 N 4 heterojunctions were obtained by a facile method. • Reduction in the direct recombination rate of photogenerated charges in 50-Zn/gCN. • Charge transfer in 50-Zn/gCN according to the Z-scheme mechanism. • 50-Zn/gCN photocatalytic degradation of 78% for cefazolin and 95% for RB5. • 50-Zn/gCN can reduce water pollution generated during the COVID-19 pandemic. [ FROM AUTHOR]

How Special is New Year Eve Traffic? Insights from Four Years 3G/4G/5G User Measurements

The specialness of New Year eve traffic is a telecoms industry fable. But how true is it, and what's the impact on user experience? We investigate this on the four UK cellular networks, in London, on New Year eve in 2016/17, 2017/18, 2018/19 and 2019/20 (covid cancelled 2020/21 & 2021/22). Overall, we captured 544,560 readings across 14 categories using 3G/4G/5G devices. This paper summarises our longitudinal readings into 10 observations on the nature of network performance, from a user's perspective, on special days such as New Year eve. Based on these, we confirm that mature 3G/4G networks are unable to deliver a consistent user experience, especially on atypical days. For example, on 4G, a user had a 60% chance to get a latency below 50 ms and 90% chance for 500ms. If repeated in mature 5G networks, it suggests that it is inadequate to support safety-critical 5G use cases. © 2022 IEEE.

Plasma-induced nanoparticle aggregation for stratifying COVID-19 patients according to disease severity.

Stratifying patients according to disease severity has been a major hurdle during the COVID-19 pandemic. This usually requires evaluating the levels of several biomarkers, which may be cumbersome when rapid decisions are required. In this manuscript we show that a single nanoparticle aggregation test can be used to distinguish patients that require intensive care from those that have already been discharged from the intensive care unit (ICU). It consists of diluting a platelet-free plasma sample and then adding gold nanoparticles. The nanoparticles aggregate to a larger extent when the samples are obtained from a patient in the ICU. This changes the color of the colloidal suspension, which can be evaluated by measuring the pixel intensity of a photograph. Although the exact factor or combination of factors behind the different aggregation behavior is unknown, control experiments demonstrate that the presence of proteins in the samples is crucial for the test to work. Principal component analysis demonstrates that the test result is highly correlated to biomarkers of prognosis and inflammation that are commonly used to evaluate the severity of COVID-19 patients. The results shown here pave the way to develop nanoparticle aggregation assays that classify COVID-19 patients according to disease severity, which could be useful to de-escalate care safely and make a better use of hospital resources.

A Low Cost Yagi Log-periodic Antenna for 4G/LTE

This paper presents the design of a low cost Yagi log-periodic antenna to extend the coverage of 4G/LTE reception. In recent times, there has been an overwhelming demand for such solutions due to the COVID-19 pandemic as a good internet connection was essential for online teaching/learning activities and for employees working from home. This paper presents the design of a single low cost antenna solution covering common frequency bands used in 4G/LTE networks to the problem without increasing the number of base stations to improve coverage. The performance of the designed antenna is analyzed using the high frequency structure analyzer (HFSS) software from ANSYS and results are presented. © 2021 IEEE.

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.

Implementation of Cloud Computing Protocol in E-Learning for Future Wireless Systems

Schooling system is rapidly shifting according to time. The 4G and 5G machineries are engineered to work flawlessly in heterogeneous platforms unlike 2G, 3G, and 4G wireless networks. New educational techniques are introduced for different environmental needs and E-learning, which is getting popular around the world, and wireless networking plays the vital role in it. E-learning is the requirement of every educational institute. There are a number of problems in the existing prototypes which need to be addressed and improved. This study provides the prototype for E-learning to make the higher education system more efficient. Especially, for the students who need distance learning and an online learning system, this research proposes a user-friendly cloud network infrastructure environment. Machine learning and cloud have strong relation in cloud computing;we store big amount of customer data but to analyze the data and create chatbots, we need machine learning algorithms. We need to enhance the existing prototype for the betterment of the higher education system in rural areas such a time of this COVID-19 pandemic. For this purpose, the existing prototype is critically examined. To achieve this factor why and how E-learning is familiar to the students of rural areas in developing countries, it was analyzed, as the method of education using a platform and interpreting the results. The researcher tried to discover the reason why E-learning is not being applied in higher education. Furthermore, attempts were made to change the existing model by adding the component “Cloud-based structure” that complements and fits the environment of the education system and benefits the long-term sustainability of higher education.

Impact on Higher Education in Pandemic: Analysis K-Means Clustering Using Urban & Rural Areas

The corona pandemic shook the world in 2019 to till from lockdowns to late night curfews, corona virus also impacted the education sector. The shift from the traditional offline education to the new digital online education was adopted by most universities and colleges but many students faced problems due to the difference in socio economic backgrounds and the availability of internet in rural areas. The Indian government is still working on complete digitalization of India and it plans to provide internet to every rural area by 2022 which shows that India still has a long way to go. India is a developing country and it faces many problems in the education sector. This research paper introduces and represented the word pandemic and gives brief information about management of a pandemic. Moreover a data analytics term clustering is defined with its two types, i.e. inclusive and exclusive clustering. Further the K-means algorithm is explained and we have discussed about the impact of pandemic on higher education and how it has affected the students living in urban areas and rural areas with lack of internet services with the help of a clustering technique called k-means clustering representing various densities of the population having access to the internet in urban areas and rural areas. Analyzing the graph we have briefly introduced the 3G and 4G mobile technologies and discussed 3G architecture and 4G architectureand reached a possible solution where areas in dire need of the internet facilities are brought into light and efforts being made by the concerned authorities are told. © 2021 IEEE.

A Novel SNOW3G-M Algorithm and Medical

In the past two years, the demand for the use of mobile networks has increased, due to what the world has been exposed to in the face of the COVID-19 pan-demic and the lack of communication between people. People resorted to using of mobile networks in light of the pandemic, and their importance has appeared in several aspects, such as automotives, media and entertainment, and healthcare. This growing demand for the mobile network led to the actual development of the 4G network in terms of providing the speed of transmission and encryption data to maintain security. In this paper, a new member of the SNOW 3G family was proposed, which is one of the fourth generation algorithms called SNOW 3G-M, which has a higher encryption speed in line with the capacity of modern CPUs and is expected to be a move to the fifth generation communication system in the future. The SNOW 3G-M keystream passes all of the tests for long key stream data, short key stream data, and initialization vector data sets.

Self-Organizing Networks for 5G and Beyond: A View from the Top

We describe self-organizing network (SON) concepts and architectures and their potential to play a central role in 5G deployment and next-generation networks. Our focus is on the basic SON use case applied to radio access networks (RAN), which is self-optimization. We analyze SON applications’ rationale and operation, the design and dimensioning of SON systems, possible deficiencies and conflicts that occur through the parallel operation of functions, and describe the strong reliance on machine learning (ML) and artificial intelligence (AI). Moreover, we present and comment on very recent proposals for SON deployment in 5G networks. Typical examples include the binding of SON systems with techniques such as Network Function Virtualization (NFV), Cloud RAN (C-RAN), Ultra-Reliable Low Latency Communications (URLLC), massive Machine-Type Communication (mMTC) for IoT, and automated backhauling, which lead the way towards the adoption of SON techniques in Beyond 5G (B5G) networks.

Modelling the Inhibitors of Online Learning Over 4G Networks: ISM-MICMAC and FMICMAC Analysis

Online learning is a well-proven application in all walks of the teaching–learning process that depends on wireless mobile technology and Internet connectivity. It is accomplished through mobile handheld devices and wireless networks. It has proved its importance in this COVID pandemic era for distant learning to facilitate online classes for all university students. The first evolution of remote Internet-based learning was termed electronic learning (e-learning) with wired net-connected desktop computers. Mobile learning or m-learning is accomplished with wireless Internet connectivity-enabled laptops or mobile handheld devices. Now, this technology of the teaching–learning process is widely accepted as the education system of pandemic-affected world and is termed online learning. Online learning is a subset of mobile learning over wireless networks using portable electronic devices. Inhibitors caused due to the existing 4G wireless networks, mobile handheld devices, and the outlook of end users are the main factors selected for this particular study. Inhibitors of online learning over 4G networks were identified through an intensive study conducted by discussions with experts, end users, designers and learners. The methodology adopted for this research work is the fuzzy matrix of cross-impact multiplications applied to classification (MICMAC). The fuzzy-MICMAC method is used to analyse the selected inhibitors of online learning over wireless networks. A digraph with all possible interconnections, correlation study and the comparative analysis of fuzzy logic approach to the binary logic ISM-MICMAC method were implemented. More outlined results were achieved with the fuzzy analysis. The driving power-dependence abilities of these inhibitors were recorded, which will resolve many undue variables in the future implementation of the system. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Measuring and Assessing Performance of Mobile Broadband Networks and Future 5G Trends

Mobile broadband (MBB) is one of the critical goals in fifth-generation (5G) networks due to rising data demand. MBB provides very high-speed internet access with seamless connections. Existing MBB, including third-generation (3G) and fourth-generation (4G) networks, also requires monitoring to ensure good network performance. Thus, performing analysis of existing MBB assists mobile network operators (MNOs) in further improving their MBB networks’ capabilities to meet user satisfaction. In this paper, we analyzed and evaluated the multidimensional performance of existing MBB in Oman. Drive test measurements were carried out in four urban and suburban cities: Muscat, Ibra, Sur and Bahla. This study aimed to analyze and understand the MBB performance, but it did not benchmark the performance of MNOs. The data measurements were collected through drive tests from two MNOs supporting 3G and 4G technologies: Omantel and Ooredoo. Several performance metrics were measured during the drive tests, such as signal quality, throughput (downlink and unlink), ping and handover. The measurement results demonstrate that 4G technologies were the dominant networks in most of the tested cities during the drive test. The average downlink and uplink data rates were 18 Mbps and 13 Mbps, respectively, whereas the average ping and pong loss were 53 ms and 0.9, respectively, for all MNOs.

Optimising Building-to-Building and Building-for-Grid Services under Uncertainty: A Robust Rolling Horizon Approach

Energy systems are undergoing radical changes that have resulted in buildings being regarded as proactive players with the potential to contribute positively to energy networks. This study investigates the role of active buildings (ABs) as prosumers in energy systems by introducing a building-to-building (B2B) strategy for energy exchange between residential units, as well as a building-for-grid (B4G) model by exploiting the demand flexibility of residential microgrids (RMGs). The mid-market rate mechanism is adopted to produce local market price signals at RMG level. A robust rolling horizon controller is developed for real-time energy management of a community of ABs. This control philosophy can improve the robustness of the RMG in face of real-time weather and energy price prediction errors. The proposed method is a multi-level optimisation which pursues multiple goals while making a trade-off between operational cost and occupant comfort. Finally, the repercussions of COVID-19 induced power consumption resulting from changing lifestyle and building occupancy profile is analysed by the proposed method as a case study. The results show that the proposed B2B and B4G strategy can reduce energy bills by 18.45%, while notable robust real-time control and computational efficiencies are achieved when benchmarked against conventional methods. IEEE

C-type Lectin CD209L/L-SIGN and CD209/DC-SIGN: Cell Adhesion Molecules Turned to Pathogen Recognition Receptors.

C-type lectin CD209/DC-SIGN and CD209L/L-SIGN proteins are distinct cell adhesion and pathogen recognition receptors that mediate cellular interactions and recognize a wide range of pathogens, including viruses such as SARS, SARS-CoV-2, bacteria, fungi and parasites. Pathogens exploit CD209 family proteins to promote infection and evade the immune recognition system. CD209L and CD209 are widely expressed in SARS-CoV-2 target organs and can contribute to infection and pathogenesis. CD209 family receptors are highly susceptible to alternative splicing and genomic polymorphism, which may influence virus tropism and transmission in vivo. The carbohydrate recognition domain (CRD) and the neck/repeat region represent the key features of CD209 family proteins that are also central to facilitating cellular ligand interactions and pathogen recognition. While the neck/repeat region is involved in oligomeric dimerization, the CRD recognizes the mannose-containing structures present on specific glycoproteins such as those found on the SARS-CoV-2 spike protein. Considering the role of CD209L and related proteins in diverse pathogen recognition, this review article discusses the recent advances in the cellular and biochemical characterization of CD209 and CD209L and their roles in viral uptake, which has important implications in understanding the host-pathogen interaction, the viral pathobiology and driving vaccine development of SARS-CoV-2.