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A radio communication sensor system is a collection of sensor modules that are connected to one another through wireless communication. It is common for them to be battery-powered and responsive to a nearby controller, referred to as the base station. They are capable of doing basic computations and transferring information to the base station in most scenarios. They are also in charge of transporting data from distant nodes, putting a burden on nodes with limited resources, and contributing to the quick depletion of energy in these nodes in the process. Nodes in close proximity to the base station are responsible for more than only detecting and sending data to the base station; they are also responsible for transmitting data from faraway nodes. To reward nodes that perform well, a protocol known as the Improved Fuzzy Inspired Energy Effective Protocol (IFIEEP) employs three separate sorts of nodes in order to provide more energy to those who do not. It takes into account the remaining node energy, the node's proximity to the base station, the node's neighbor concentration, and the node's centrality in a cluster when determining node viability. All of these assumptions are founded on a shaky understanding of the situation. Adaptive clustering must be applied to the most viable nodes in order to identify cluster leaders and transmit data to the base station, in addition to disseminating data across the rest of the network, in order to achieve success. In addition, the research provides proper heterogeneity parameters, which describe, among other things, the number of nodes as well as the starting energy of each node. The percentage gain in-network lifetime when compared to current approaches is minor for smaller numbers of supernodes; however, the percentage gain in the area covered 12.89 percent and 100% when more significant numbers of super nodes are used. These improvements in stability, residual energy, and throughput are accomplished by combining these improvements while also taking into consideration the previously neglected energy-intensive sensing energy aspect. The protocol that has been presented is meant to be used in conjunction with applications that make use of blockchain technology.

The IoT sensor applications have grown in extreme numbers, generating a large amount of data, and it requires very effective data analysis procedures. However, the different IoT infrastructures and IoT sensor device layers possess protocol limitations in transmitting and receiving messages which generate obstacles in developing the smart IoT sensor applications. This difficulty prohibited existing IoT sensor implementations from adapting to other IoT sensor applications. In this article, we study and analyze how IoT sensor produces data for big data analytics, and it also highlights the existing challenges of intelligent solutions. IoT sensor applications required big data classification and analysis in a Fog computing (FC) environment using computation intelligence (CI). Our proposed Fog big data analysis model (FBDAM) and BPNN analysis model for IoT sensor application using fusion deep learning (FDL) pose new obstacles for potential machine-to-machine communication practices. We have applied our proposed FBDAM on the most significant Fog applications developed on smart city datasets (parking, transportation, security, and sensor IoT dataset) and got improving results. We compared different deep and machine learning algorithms (SVM, SVMG-RBF, BPNN, S3VM, and proposed FDL) on different smart city dataset IoT application environments.

This work introduces a computational method for solving the linear two-dimensional fuzzy Fredholm integral equation of the second form (2D-FFIE-2) based on triangular basis functions. We have used the parametric form of fuzzy functions and transformed a 2D-FFIE-2 with three variables in crisp case to a linear Fredholm integral equation of the second kind. First, a method based on the use of two m-sets of orthogonal functions of triangular form is implemented on the integral equation under study to be changed to coupled algebraic equation system. In order to solve these two schemes, a finite iterative algorithm is then applied to evaluate the coefficients that provided the approximate solution of the integral problems. Three examples are given to clarify the efficiency and accuracy of the method. The obtained numerical results are compared with other direct and exact solutions.

Cylophosphamide (CYCL) is a strong anticancer and immunosuppressive agent but its urotoxicity presents one of the major toxic effects that limit its wide usage particularly in high dose regimens. Therefore, this study aimed to investigate Acacia Senegal gum exudate, Gum Arabic (GA), for its possible role as a natural, nontoxic agent against CYCL-induced urotoxicity. Male Swiss albino rats were exposed to CYCL (150 mg/kg BW, once i.p) with or without GA oral supplementation (7.5 g/kg/day for 6 days) through drinking water. Glutathione (GSH), Malondialdehyde (MDA) and Nitric oxide (NO) bladder contents were assessed. Responsiveness of the bladder rings to acetylcholine (ACh) in vitro, microscopic and macroscopic features are also investigated. CYCL produced pronounced harmful effects on bladder urothelial lining with significant increases in (MDA) and NO levels in the tissue homogenates. Bladder-GSH content is dropped by over 60% following CYCL injection. Bladder contractility, as measured by its responsiveness to ACh, recorded a marked reduction. The isolated bladders exhibited such macroscopic changes as severe edema, inflammation and extravasation. The bladder weight increased as well. Histological changes were evident in the form of severe congestion, petechial hemorrhage and chronic inflammatory reaction in the lamina propria accompanied with desquamated epithelia. GA, a potential protective agent, produced an almost complete reversal of NO induction, lipid peroxidation or cellular GSH bladder contents in the GA + CYCL-treated group. Likewise, bladder inflammation and edema were reduced. Bladder rings showed a remarkable recovery in their responsiveness to ACh. Bladder histological examination showed a near normal configuration and structural integrity, with a significant reduction in inflammation and disappearance of focal erosions. These remarkable effects of GA may be attributed to its ability to neutralize acrolein, the reactive metabolite of CYCL and/or the resultant reactive oxygen metabolites, through a scavenging action. GA may limit the cascading events of CYCL-induced damage, initiating a cytoprotective effect leading to structural and functional recovery of the bladder tissues.

Clinical use of doxorubicin (DOX) is limited by its cardiotoxic side effects. Recent studies established that metformin (MET), an oral antidiabetic drug, possesses an antioxidant activity. However, whether it can protect against DOX-induced energy starvation and mitochondrial damage has not been reported. Our results, in a rat model of DOX-induced cardiotoxicity, show that DOX treatment significantly increased serum levels of LDH and CK-MB, indicators of cardiac injury, and induced expression of hypertrophic gene markers. DOX also caused marked decreases in the cardiac levels of glutathione, CoA-SH and ATP, and mRNA expression of catalase and NQO-1. These biochemical changes were associated with myocardial histopathological and ultrastructural deteriorations, as observed by light and electron microscopy, respectively. Cotreatment with MET (500 mg/kg) eliminated all DOX-induced biochemical, histopathological, and ultrastructural changes. These findings demonstrate that MET successfully prevents DOX-induced cardiotoxicityin vivoby inhibiting DOX-induced oxidative stress, energy starvation, and depletion of intramitochondrial CoA-SH.

The high peak to average power ration (PAR) levels of orthogonal frequency division multiplexing (OFDM) signals attract the attention of many researchers during the past decade. Existing approaches that attack this PAR issue are abundant, but no systematic framework or comparison between them exists to date. They sometimes even differ in the problem definition itself and consequently in the basic approach to follow. In this paper, we propose a new trend in mitigating the peak power problem in OFDM system based on modeling the effects of clipping and amplifier nonlinearities in an OFDM system. We showed that the distortion due to these effects is highly related to the dynamic range itself rather than the clipping level or the saturation level of the nonlinear amplifier, and thus we propose two criteria to reduce the dynamic range of the OFDM, namely, the use of MSK modulation and the use of Hadamard transform. Computer simulations of the OFDM system using Matlab are completely matched with the deduced model in terms of OFDM signal quality metrics such as BER, ACPR, and EVM. Also simulation results show that even the reduction of PAR using the two proposed criteria is not significat, and the reduction in the amount of distortion due to HPA is truley delightful.