Massive Type Research Articles

Performance Comparison of FBMC-OQAM and CP-OFDM Using AWGN Channel

The 5G NR network planning covers the types of use scenarios and applications that include Enhanced Mobile Broadband (eMBB), Ultra-Reliable and Low Latency Communications (URLLC), and Massive Machine Type Communications (MTC). Regarding multicarrier modulation schemes, Orthogonal Frequency Division Multiplexing (OFDM) has become the most popular choice in previous technology, so OFDM is a strong candidate for its 5G NR technology application. However, OFDM has disadvantages such as higher PAPR and decreased bandwidth efficiency due to the addition of CP. These weaknesses can be overcome by the FBMC modulation scheme with Offset Quadrature Amplitude Modulation (OQAM) as a more efficient CP replacement for its implementation in 5G NR. This study analyzed the development of OQAM in Filter Bank multicarrier (FBMC) and compared it with using Cyclic Prefix (CP) based on OFDM using the AWGN channel. The first step of this research is to present an overview of the modulation scheme used. Next, compare the performance of FBMC-OQAM and CP-OFDM by analyzing several Bit Error Rate (BER) simulation results against the SNR value when both systems use the same simulation parameters. Based on the test results of each BER, both methods have different values, almost 2 dB for the same BER results. It indicates that the FBMC-OQAM system reached the BER value of 10-4 at SNR 15 dB. The CP-OFDM system, meanwhile, was able to achieve a BER value of 10-4 at SNR 17 dB. These results indicate that the FBMC-OQAM system is superior to CP-OFDM based on the BER values.

Anti-cell Proliferative Mechanism of Doxazosin on Human Oral Cancer Cells Through the Modulation of Antioxidant and Apoptotic Pathway.

Oral squamous cell carcinoma (OSCC), a global threatening disease, is reported mostly in the middle and elderly male population. Even though the exact cause of OSCC was not known, consumption of tobacco in any form has been reported in most of OSCC patients. OSCC is a massive invasive type of cancer which easily spreads to the distant organs. Hence treating it at appropriate time is necessary and the rate of OSCC incidence is also constantly increasing. At present, chemoradiation is the only therapy prescribed for OSCC patients which renders various side effects. Hence, the treatment with lesser side effect was of current research interest. Doxazosin (α1 adrenorecptor antagonist) had been proven to render anticancer effect in prostate, renal, hepatic, and ovarian cancers but its role in oral cancer cells was not been elucidated. Therefore, we have assessed the anticancer effect of doxazosin on oral squamous cancer cells via through the induction of apoptosis, and antioxidant property. The cytoprotective effect of doxazosin on normal Vero cells and anticancer effect on oral cancer KB cells were analyzed with MTT assay. Doxazosin antioxidant activity were analyzed by their reactivity with free radicals and metal ions by the method of FRAP, DPPH, chemilumiscence, and ORAC assay. The antioxidant levels were also assessed by TBARS, SOD, and glutathione levels, and later on apoptosis staining techniques like DCFH-DA, Rhodamine 123, and AO/EtBr stain were conducted. Apoptosis was confirmed by estimating the levels of apoptotic proteins in doxazosin-treated KB human oral cancer cells by ELISA method. The results from our study show that doxazosin is a potent antioxidant and it significantly induces apoptosis in human oral cancer by altering various cellular molecules at downstream signaling which has been depict in the results. Our study proves doxazosin as a potent anticancer drug which may be used in the treatment of oral carcinoma, if it is subjected to further research using human clinical trials.

Hierarchies of RG flows in 6d (1, 0) massive E-strings

We extend the analysis of [9] to the 6d (1, 0) SCFTs known as massive E-string theories, which can be engineered in massive Type IIA with 8 − n0< 8 D8-branes close to an O8− (or O8* if n0 = 8, 9). For each choice of n0 = 1, …, 9 the massive {E}_{1+left(8-{n}_0right)} -strings (including the more exotic {overset{sim }{E}}_1 and E0) are classified by constrained E8 Kac labels, i.e. a subset of Hom(ℤk, E8), from which one can read off the flavor subalgebra of {E}_{1+left(8-{n}_0right)} of each SCFT. We construct hierarchies for two types of Higgs branch RG flows: flows between massive theories defined by the same n0 but different labels; flows between massive theories with different n0. These latter flows are triggered by T-brane vev’s for the right SU factor of the SCFT global symmetry, whose rank is a function of both k and n0, a situation which has so far remained vastly unexplored.

Approximation Opportunities in Edge Computing Hardware: A Systematic Literature Review

With the increasing popularity of the Internet of Things and massive Machine Type Communication technologies, the number of connected devices is rising. However, although enabling valuable effects to our lives, bandwidth and latency constraints challenge Cloud processing of their associated data amounts. A promising solution to these challenges is the combination of Edge and approximate computing techniques that allows for data processing nearer to the user. This article aims to survey the potential benefits of these paradigms’ intersection. We provide a state-of-the-art review of circuit-level and architecture-level hardware techniques and popular applications. We also outline essential future research directions.

Identification and characterization of thousands of bacteriophage satellites across bacteria.

Bacteriophage-bacteria interactions are affected by phage satellites, elements that exploit phages for transfer between bacteria. Satellites can encode defense systems, antibiotic resistance genes, and virulence factors, but their number and diversity are unknown. We developed SatelliteFinder to identify satellites in bacterial genomes, detecting the four best described families: P4-like, phage inducible chromosomal islands (PICI), capsid-forming PICI, and PICI-like elements (PLE). We vastly expanded the number of described elements to ∼5000, finding bacterial genomes with up to three different families of satellites. Most satellites were found in Proteobacteria and Firmicutes, but some are in novel taxa such as Actinobacteria. We characterized the gene repertoires of satellites, which are variable in size and composition, and their genomic organization, which is very conserved. Phylogenies of core genes in PICI and cfPICI indicate independent evolution of their hijacking modules. There are few other homologous core genes between other families of satellites, and even fewer homologous to phages. Hence, phage satellites are ancient, diverse, and probably evolved multiple times independently. Given the many bacteria infected by phages that still lack known satellites, and the recent proposals for novel families, we speculate that we are at the beginning of the discovery of massive numbers and types of satellites.

Covariance-Free Variational Bayesian Learning for Correlated Block Sparse Signals

We consider the problem of estimating channel in massive machine type communication (mMTC) systems. The sparse device activity in a mMTC system makes the channel block-sparse, with intra-block correlation. Block-sparse Bayesian learning (B-SBL) is a powerful framework for estimating such signals. The existing B-SBL algorithms become computationally expensive for high-dimensional problems, which is common in mMTC systems. This is because of large number of devices in a mMTC system, they invert a large-dimensional matrix to calculate the covariance matrix. To address this problem, we exploit variational Bayesian inference, and design a novel covariance-free variational B-SBL algorithm which inverts multiple small-sized block matrices, instead of inverting a complete big-sized matrix. The complexity is further reduced by avoiding explicit computation of the covariance matrix. The proposed algorithm, instead of performing costly matrix inversions, solves multiple linear systems to calculate an unbiased estimate of the posterior statistics. The proposed algorithm is numerically shown to estimate the mMTC channel with a much lesser complexity, and that too without compromising the reconstruction performance.

Thermal radiation mode: A deployment perspective for 5G New Radio

The 5G New Radio (NR) technology is under a standardization process by the 3rd Generation Partnership Project to provide an outline for a new radio interface for the next generation of cellular networks. The aims of 5G networks include not only providing greater capacity and coverage but also supporting advanced services, such as enhanced mobile broadband, ultrareliable low-latency communication (URLLC), and massive machine type communication.

Американский кинематограф, ФБР и пропаганда: образ внутреннего врага (1941–1942 гг.)

Introduction. The period 1941–1942 became a time when American art was rapidly rebuilt on “military rails.” Cultural figures in every way reinforced the morale of American soldiers and were engaged in justifying various actions of the government through a more accessible and understandable language of artistic narrative. Methods and materials. The rich material of the archive of the FBI, the army and other US security services allows a better look at how the cinema obeyed the propaganda needs of the warring power. The article is based on the principles of historicism and systematics, as well as the methods of historical comparativistics and imagology (discourse-analysis, analysis of audiovisual representation and some others). Analysis and results. It is quite clear that cinema played a special role in these processes – the most massive and popular type of art, which in the previous two decades became the most common form of leisure for Americans. This article is devoted to the use of cinema to justify the initially extremely unpopular measure of the American government to intern the Japanese in concentration camps in the light of the entry of the United States into World War II.

Hybrid optimization using lion and dragonfly for enhanced resource allocation in fifth-generation networks

“5G (Fifth Generation) network promises Enhanced Mobile Communications (EMC), Massive Machine Type Communications (MMTC) and Ultra-Reliable Low Latency ygCommunications (URLLC)”. For enhancing communication, resource allocation is a crucial factor that guarantees the partitioning of channels into resource blocks, which were allocated to diverse users. Different methods have been introduced for improving resource scheduling however, they do not reach the optimum solution. This work aims to scrutinize the resource allocation problems in the “hybrid multi-carrier non-orthogonal multiple access (MC-NOMA) systems” that comprise the OMA and NOMA modes. It is used to achieve the EE and SE trade-off with minimal rate requirements of users. In addition, the total degree of freedom includes “user clustering, power allocation, choice of Multiple Access (MA) modes, and subcarrier assignment as well”. Accordingly, the optimization concept is integrated that offers the most noteworthy way of resolving multi-objective issues. In this context, resource allocation with power allotment is considered a vital factor, which is determined as a single-objective issue. Thereby this paper ensures the optimal allocation of power and subcarriers by a novel algorithm termed as Dragon Levy-based Lion Cub Generation Model (DL-LCG). Finally, the presented model is evaluated over existing models regarding cost analysis

Origin of the post-collisional younger gabbroic rocks and the associated Fe–Ti oxide ores, Abu Ghalaga area, Southern Eastern Desert, Egypt: mineralogical and geochemical constraints

The Abu Ghalaga pluton in the southern eastern desert of Egypt (SED) consists of undeformed norite and hornblende gabbro intruding island arc metavolcanics, ophiolitic rocks, and syn-tectonic older granitic rocks. The Fe-Ti ore (mainly ilmenite) occurs in the form of lenses at the base of the norite. Based on microtextures, mineralogy, and chemical composition, three types of ilmenites are recognized: massive high-Mg type, disseminated high-Mg type, and disseminated low-Mg ilmenite. The three ilmenite types are chemically distinguished by their MgO, MnO, TiO2, Fe2O3, FeO, and V2O3 contents. The variations in the concentration of these oxides are interpreted as a function of variations in T, fO2, and the composition of the parental magma. Reconstruction of the orthomagmatic conditions shows that T and fO2 of the magma from which the norite and its Fe-Ti deposit formed decrease during the course of magmatic differentiation, whereas the hornblende gabbro and its Fe-Ti mineralization have formed from a more evolved magma under relatively lower T and fO2. The REE patterns and variation diagrams support a model of crystal fractionation as the primary means of formation of the Fe-Ti deposits. Chemical features also suggest that the parent magma of both types of gabbroic rocks was generated in the mantle, but in two different pulses. Subduction zone, MORB, and WPB chemical signatures for these gabbroic rocks suggest a complex tectonic history consistent with compression followed by within plate extension possibly contributing to the development of a back-arc/intra-arc basin.

D4-branes wrapped on four-dimensional orbifolds through consistent truncation

We construct a consistent truncation of six-dimensional matter coupled F(4) gauged supergravity on a cornucopia of two-dimensional surfaces including a spindle, disc, domain wall and other novel backgrounds to four-dimensional minimal gauged supergravity. Using our consistent truncation we uplift known AdS2× Σ1 solutions giving rise to four-dimensional orbifold solutions, AdS2× Σ1 ⋉ Σ2. We further uplift our solutions to massive type IIA supergravity by constructing the full uplift formulae for six-dimensional U(1)2-gauged supergravity including all fields and arbitrary Romans mass and gauge coupling. The solutions we construct are naturally interpreted as the near-horizon geometries of asymptotically AdS6 black holes with a four-dimensional orbifold horizon. Alternatively, one may view them as the holographic duals of superconformal quantum mechanical theories constructed by compactifying five-dimensional USp(2N) theory living on a stack of D4-D8 branes on the four-dimensional orbifolds. As a first step to identifying these quantum mechanical theories we compute the Bekenstein-Hawking entropy holographically.

GalCEM. I. An Open-source Detailed Isotopic Chemical Evolution Code

This is the first of a series of papers that will introduce a user-friendly, detailed, and modular Galactic Chemical Evolution Model, GalCEM, that tracks isotope masses as a function of time in a given galaxy. The list of tracked isotopes automatically adapts to the complete set provided by the input yields. The present iteration of GalCEM tracks 86 elements broken down into 451 isotopes. The prescription includes massive stars, low-to-intermediate-mass stars, and Type Ia supernovae as enrichment channels. We have developed a preprocessing tool that extracts multidimensional interpolation curves from the input yield tables. These interpolation curves improve the computation speeds of the full convolution integrals, which are computed for each isotope and for each enrichment channel. We map the integrand quantities onto consistent array grids in order to perform the numerical integration at each time step. The differential equation is solved with a fourth-order Runge–Kutta method. We constrain our analysis to the evolution of all light and intermediate elements from carbon to zinc, and lithium. Our results are consistent up to the extremely metal-poor regime with Galactic abundances. We provide tools to track the mass rate change of individual isotopes on a typical spiral galaxy with a final baryonic mass of 5 × 1010 M ⊙. Future iterations of the work will extend to the full periodic table by including the enrichment from neutron-capture channels as well as spatially dependent treatments of galaxy properties. GalCEM is publicly available at https://github.com/egjergo/GalCEM.

Boost Sum-Product Performance for Multiuser Detection in mMTC at Millimeter Wave

We consider the multiuser detection (MUD) problem, i.e., how to separate and decode colliding data streams, in the uplink of massive Machine Type Communications (mMTC) at millimeter wave (mmWave). Operating on factor-graphs by passing messages, the sum-product algorithm and its variants are widely applied in many other scenarios. However, in this paper, we find that their performance in mMTC at mmWave could be dramatically degraded due to the ill-conditioned MUD channel gain matrix and the existence of enormous short cycles in their corresponding factor-graphs, which are caused by the limited scattering of mmWave and the sharing of a same codebook for error correction among densely located user equipments. Assuming LDPC codes are used for error correction, we further propose a novel sum-product based approach to dealing with the MUD problem in mMTC at mmWave. It first leverages the propagation characteristics of mmWave to optimize the factor-graph for MUD by removing short cycles based on node-split and node-contraction, and then takes a dynamic-programming based method to approximate the messages passing on the resulted factor-graph, which can achieve a higher decoding accuracy. Extensive simulation results show that our approach outperforms the state-of-the-art sum-product based approaches significantly.

A plethora of Type IIA embeddings for d = 5 minimal supergravity

We construct multiple embeddings of all solutions of d = 5 minimal (un)gauged supergravity into massive Type IIA supergravity. The internal spaces and warpings of such embeddings are the same as those of the mathcal{N} = 1 supersymmetric (Mink5) AdS5 vacua, with the slight modification that the U(1) R-symmetry direction becomes fibered over the external space by the d = 5 gauge field. In addition the fluxes are appropriately modified. There are many distinct types of the aforementioned internal spaces and as such many different embeddings of the d = 5 supergravity. As examples of our setup we provide new solutions dual to six-dimensional, mathcal{N} = (1, 0) SCFTs compactified on the product of a constant curvature Riemann surface and a spindle. We also provide a multitude of massive Type IIA embeddings for rotating, asymptotically AdS5 black hole solutions.

A robust transmission with enhancement of 5G PHY using FBMC and AMC for machine-to-machine communication node

Advancement of 5G new radios has enabled more robust communication for the Machine-to-Machine (M2M) communication node, using filter bank multicarrier (FBMC). This paper focuses on robust transmission over random fluctuations of the channel and also enhances the battery life for the massive machine type communication (mMTC) node. Filter bank multicarrier and Adaptive Modulation Coding (AMC) have been utilized together to enhance the performance of the 5G (NR) PHY layer. A frame-to-frame implementation is used to diminish the impact of fading using AMC, while efficient utilization of spectrum is achieved using FBMC. The selection of the AMC profile is obtained through the analysis of uplink packets using the Distance Statistics (DS). The FBMC is incorporated with 5G PHY in place of OFDM to achieve the optimum utilization of spectrum and also obtain a significant reduction in peak to average power ratio (PAPR) for robust transmission, which saves 10% of the battery requirement. On the basis of channel state information, distance statistics were employed to optimize the AMC. The optimum selection of AMC with FBMC will reduce the bit error rate (BER) against multipath fading and ensure the better utilization of available spectrum to attain the optimum utilization of the power amplifier.

5G-enhanced Positioning Accuracy in Smart City

The new 5G mobile network promises to enhance existing services or include new ones to address key challenges presented by smart city stakeholders (citizens, municipalities, politics, industries, architects, etc.) to improve system implementations. These challenges cover various smart city fields such as transportation, environmental monitoring, healthcare, industrial automation, smart grid, etc. Thus, the main objective of 5G functionalities is to provide solutions to the various identified needs, which are defined as constraints and requirements. Therefore, three categories of 5G-based use cases have been defined: Enhanced Mobile Broadband (eMBB), Massive Machine Type Communications (mMTC), and Ultra-reliable and Low Latency Communications (uRLLC). Each group involves a set of use cases and characterized by specific technical features that address the corresponding needs. However, accurate and real-time positioning information is a vital requirement common to all three categories, but the degree of performance varies across scenarios and descriptions. Therefore, this work presents a summary of existing positioning technologies crossed with wireless technologies and smart city use cases to highlight the potential that will add accurate and real-time positioning to 5G capabilities. 5G promises decimeter accuracy in some critical use cases.

Performance Analysis of Support Vector Machine Learning Based Carrier Aggregation Resource scheduling in 5G Mobile Communication

The 5G cellular system will enable heterogeneous networks that incorporate 5G, 4G, Wi-Fi, and other telecommunication connectivity. This will result in huge changes in existing infrastructure and architecture network. Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low Latency Communications (URLLC), and massive Machine Type Communication (mMTC) are some of the 5G's basic application cases. The variety of heterogeneous networks makes it challenging to manage, network traffic, inter-cell, and intra-cell interfaces. Due to diverse interfaces and data transmission rates, network traffic in heterogeneous networks can be difficult to manage and control. Advanced techniques including Machine Learning (ML), Artificial Intelligence (AI), and Deep Learning (DL) are used in the 5G Network to overcome such issues. In this paper, a Support Vector Machine (SVM) learning-based resource allocation approach for heterogeneous networks is designed. A machine learning method is proposed to enhance the performance of 5G NR mobile networks. This method is used to upgrade the throughput of the overall networks. The SVM learning function detects by splitting network data of channel state information (CSI). The considered channel state data of two variables as labels with X1 and X2 and trained using SVM-LINEAR, SVM-RBF, and SVM-SIGMOID. The proposed SVM classifier by splitting data for training 80% and testing 20%. A Static Error rate is set as a threshold limit at 10% (0.10) of BLER (Block Error Rate). If the error rate passed the threshold, then update Carrier Aggregation with aggregated component else set carrier aggregation with ordinary carrier component values to Zero. The proposed approach further compares with the round robin (RR), best channel quality indicator (BCQI), fractional frequency reuse (FFR), MU-MIMO, and beamforming resource scheduling techniques. The innovative results indicated that the proposed approach enhanced spectral efficiency, average cell throughput, edge throughput peak throughput, and fairness index.

What Physical Layer Security Can Do for 6G Security

While existing security protocols were designed with a focus on the core network, the enhancement of the security of the B5G access network becomes of critical importance. Despite the strengthening of 5G security protocols with respect to LTE, there are still open issues that have not been fully addressed. This work is articulated around the premise that rethinking the security design bottom up, starting at the physical layer, is not only viable in 6G but importantly, arises as an efficient way to overcome security hurdles in novel use cases, notably massive machine type communications (mMTC), ultra reliable low latency communications (URLLC) and autonomous cyberphysical systems. Unlike existing review papers that treat physical layer security orthogonally to cryptography, we will try to provide a few insights of underlying connections. Discussing many practical issues, we will present a comprehensive review of the state-of the-art in i) secret key generation from shared randomness, ii) the wiretap channels and fundamental limits, iii) authentication of devices using physical unclonable functions (PUFs), localization and multi-factor authentication, and, iv) jamming attacks at the physical layer. We finally conclude with the proposers' aspirations for the 6G security landscape, in the hyper-connectivity and semantic communications era.

MINERALOGICAL AND PETROLOGICAL CHARACTERISTICS OF GRANITES OF THE SHPOLA-TASHLYK ORE DISTRICT (THE UKRAINIAN SHIELD)

Mineralogical and petrographical research of different types of granites of the Kirovohrad complex, such as of Lypniazhka, Berezivske, Yaroshivka, Dorofiivka, Hlodosy, in the Shpola-Tashlyk ore district of the Ukrainian Shield, has been conducted. It allows to identify them as rare-metal genetic type. The evidence comes from: High silica (SiO2 = 71.70—74.24%), agpaitic index (0.53—0.71) and low iron oxidation (0.16—0.59) in granites. Furthermore, they are enriched with fluorine and boron based on occurrence of accessory fluorite and tourmaline. Characteristic chemical feature of the granites is a prevalence of potassium over sodium. The contents of phosphorus, zirconium, cerium, lanthanum, and lithium in Berezivske granites exceed average contents for such elements of the Ukrainian Shield, due to accessory mineralization — apatite, monazite, and lithium-bearing mica. The most high lithium grades (55 ppm) are specific for Lypniazhka and Yaroshivka granites where at their exocontact zone the lithium deposits and occurrences of niobium, tantalum, and stannum were discovered. Based on structure and texture features, massive, porphyroblastic, gneiss-like, and aplite-pegmatoid types with gradual transitions were distinguished; it is an evidence of their genetic relation. It was defined that Lypniashka granites related to the lithium pegmatite deposit have mineralogical features comparing to other types of granites, such as: a) highest ВаО (0.44—0.53 %) content in microclines; b) most ferrous biotite (f = 0.64 %) with the highest content of fluorine (0.16 %). Isotopic and geochemical research of monazite was conducted. The granites age ranges from 2026 to 2042 Ma. The granites related to rare-metal mineralization yielded ages from 2026 to 2037 Ma comparing to the oreless granites (Smoline urban-type settlement) with age 2042 Ma. On biotite-garnet geothermometer study the granites’ formation temperatures were defined, such as: Dorofiivka granite — 625°С, Berezivske granite — 640ºС, Hlodosy granite — 640ºС, and Yaroshivka granite (Т = 640—750ºС, Р = 500—700 MPa). Considering field observations and facts mentioned above the Berezivske granites belong to rare-metal granite complex of S-type.

Equilibrated and Fast Resources Allocation for Massive and Diversified MTC Services Using Multiagent Deep Reinforcement Learning

Massive and diversified machine type communication (MTC) service is one of the development trends of MTC in Internet of Things (IoT). Meanwhile, realizing network functions virtualization (NFV) is inseparable from reasonable virtual network function (VNF) scheduling and resource allocation. For VNF scheduling and resource allocation of MTC services, recently, deep reinforcement learning (DRL) has become one of the feasible solutions. However, existing DRL solutions have problems of inapplicability to the environment with both discrete and continuous variables, long training, time and nonequilibrium resource allocation. In this article, we first model the end-to-end (E2E) VNF scheduling and resource allocation of core network nodes, links, and access network subcarriers with different strategies, respectively, and propose a compound variable optimization problem aiming at maximizing the net income of the network provider. Then, we propose the mapping scheme of the absolute value of the signum function (ASgn mapping scheme) to simplify the compound variables into continuous variables of the optimization problem, so that the DRL algorithm is applicable. Moreover, we propose a model paralleling multiagent twin delayed deep deterministic (MPMA-TD3) policy gradient algorithm to handle massive services, reduce training time, and action space of agents. Finally, we improve the MPMA-TD3 algorithm to handle diversified services, solve the problem of nonequilibrium resources allocation, and realize the reasonable resource allocation for each service. Simulation results show that the proposed algorithms are better than other algorithms in reward, delay, cost, and training time for massive services. Further, the Improved MPMA-TD3 algorithm has the best service equilibrating ability.