Dielectric,ferroelectric, and energy storage properties in dysprosium doped sodium bismuth titanate ceramics

In this work, Na_0.5(Bi_1-xDy_x)_0.5TiO₃ (0?≤?x?≤?15%) ceramics were prepared via solid state reaction method and were characterized. A stable and pure perovskite phase was revealed by X-ray diffraction analysis for all compositions and a symmetry change from rhombohedral to orthorhombic phase was detected beyond 10% of Dy substitution. The incorporation of Dy³⁺ into Sodium Bismuth Titanate (Na_0.5Bi_0.5TiO₃) matrix allows a substantial decrease of the coercive field, an increase in the resistivity, and leads to a high stability of the dielectric permittivity (??/?_(150?°C) ≤?±?15%) over a wide temperature range. Furthermore, this system was found to exhibit improved energy storage properties at high temperatures with a maximum energy density of 1.2?J/cm³ obtained for 2%Dy composition at 200?°C. The obtained results are very promising for energy storage capacitors operating at high temperatures.     

Effect of doping polyacrylic acid with some dopants as studied by different techniques

The molecular weight of polyacrylic acid (PAA) was determined by a viscometric method using NaNO₃ as solvent at 30°C. The specific electric conductivities (σ) of PAA as well as PAA doped with carbon black (CB), chromium oxide (Cr₂O₃), and cupferron with different concentrations (from 0.25 to 1 wt %) were measured at a temperature range 360–400 K. IR spectra of some polymers were determined and it was shown that when PAA was doped with 0.5 wt % CB, a C? O? C band appeared at 775–875 cm^?1. The positron annihilation lifetime (PAL) spectra in PAA doped with the above‐mentioned dopants were measured as a function of their concentrations. It was observed that the short lifetime intensity I₁ decreased, whereas the intermediate lifetime intensity I₂, which is related to the conductivity of the material, increased with increasing the wt % of Cr₂O₃ and cupferron as well as at low concentrations of CB. These results are discussed in terms of the conducting island model. It was found that there were distinct positive relationships between σ and I₂. © 2002 John Wiley & Sons, Inc. J Appl Polym Sci 84: 877–883, 2002; DOI 10.1002/app.10381     

Anomaly Detection for Industrial Internet of Things Cyberattacks

The evolution of the Internet of Things (IoT) has empowered modern industries with the capability to implement large-scale IoT ecosystems, such as the Industrial Internet of Things (IIoT). The IIoT is vulnerable to a diverse range of cyberattacks that can be exploited by intruders and cause substantial reputational and financial harm to organizations. To preserve the confidentiality, integrity, and availability of IIoT networks, an anomaly-based intrusion detection system (IDS) can be used to provide secure, reliable, and efficient IIoT ecosystems. In this paper, we propose an anomaly-based IDS for IIoT networks as an effective security solution to efficiently and effectively overcome several IIoT cyberattacks. The proposed anomaly-based IDS is divided into three phases: pre-processing, feature selection, and classification. In the pre-processing phase, data cleaning and normalization are performed. In the feature selection phase, the candidates’ feature vectors are computed using two feature reduction techniques, minimum redundancy maximum relevance and neighborhood components analysis. For the final step, the modeling phase, the following classifiers are used to perform the classification: support vector machine, decision tree, k-nearest neighbors, and linear discriminant analysis. The proposed work uses a new data-driven IIoT data set called X-IIoTID. The experimental evaluation demonstrates our proposed model achieved a high accuracy rate of 99.58%, a sensitivity rate of 99.59%, a specificity rate of 99.58%, and a low false positive rate of 0.4%.     

Towards Sustainable Agricultural Systems: A Lightweight Deep Learning Model for Plant Disease Detection

A country’s economy heavily depends on agricultural development. However, due to several plant diseases, crop growth rate and quality are highly suffered. Accurate identification of these diseases via a manual procedure is very challenging and time-consuming because of the deficiency of domain experts and low-contrast information. Therefore, the agricultural management system is searching for an automatic early disease detection technique. To this end, an efficient and lightweight Deep Learning (DL)-based framework (E-GreenNet) is proposed to overcome these problems and precisely classify the various diseases. In the end-to-end architecture, a MobileNetV3Small model is utilized as a backbone that generates refined, discriminative, and prominent features. Moreover, the proposed model is trained over the PlantVillage (PV), Data Repository of Leaf Images (DRLI), and a new Plant Composite (PC) dataset individually, and later on test samples, its actual performance is evaluated. After extensive experimental analysis, the proposed model obtained 1.00%, 0.96% and 0.99% accuracies on all three included datasets. Moreover, the proposed method achieves better inference speed when compared with other State-Of-The-Art (SOTA) approaches. In addition, a comparative analysis is conducted where the proposed strategy shows tremendous discriminative scores as compared to the various pre-trained models and other Machine Learning (ML) and DL methods.     

Modeling and Analysis of UAV-Assisted Mobile Network with Imperfect Beam Alignment

With the rapid development of emerging 5G and beyond (B5G), Unmanned Aerial Vehicles (UAVs) are increasingly important to improve the performance of dense cellular networks. As a conventional metric, coverage probability has been widely studied in communication systems due to the increasing density of users and complexity of the heterogeneous environment. In recent years, stochastic geometry has attracted more attention as a mathematical tool for modeling mobile network systems. In this paper, an analytical approach to the coverage probability analysis of UAV-assisted cellular networks with imperfect beam alignment has been proposed. An assumption was considered that all users are distributed according to Poisson Cluster Process (PCP) around base stations, in particular, Thomas Cluster Process (TCP). Using this model, the impact of beam alignment errors on the coverage probability was investigated. Initially, the Probability Density Function (PDF) of directional antenna gain between the user and its serving base station was obtained. Then, association probability with each tier was achieved. A tractable expression was derived for coverage probability in both Line-of-Sight (LoS) and Non-Line-of-Sight (NLoS) condition links. Numerical results demonstrated that at low UAVs altitude, beam alignment errors significantly degrade coverage performance. Moreover, for a small cluster size, alignment errors do not necessarily affect the coverage performance.     

Building a peer-to-peer content distribution network with high performance,scalability and robustness

Content distribution networks (CDN) are fundamental, yet expensive technologies for distributing the content of web-servers to large audiences. The P2P model is a perfect match to build a low-cost and scalable CDN infrastructure for popular websites by exploiting the underutilized resources of their user communities. However, building a P2P-based CDN is not a straightforward endeavor. In contrast to traditional CDNs, peers are autonomous and volunteer participants with their own heterogeneous interests that should be taken into account in the design of the P2P system. Moreover, churn rate is much higher than in dedicated CDN infrastructures, which can easily destabilize the system and severely degrade the performance. Finally and foremostly, while many P2P systems abstract any topological information about the underlying network, a top priority of a CDN is to incorporate locality-awareness in query routing in order to locate close-by content. This paper aims at building a P2P CDN with high performance, scalability and robustness. Our proposed protocols combine DHT efficiency with gossip robustness and take into account the interests and localities of peers. In short, Flower-CDN provides a hybrid and locality-aware routing infrastructure for user queries. PetalUp-CDN is a highly scalable version of Flower-CDN that dynamically adapts to variable rates of participation and prevent overload situations. In addition, we ensure the robustness of our P2P CDN via low-cost maintenance protocols that can detect and recover from churn and dynamicity. Our extensive performance evaluation shows that our protocols yield high performance gains under both static and highly dynamic environments. Furthermore, they incur acceptable and tunable overhead. Finally we provide main guidelines to deploy Flower-CDN for the public use.     

A Toxoplasma gondii Oxopurine Transporter Binds Nucleobases and Nucleosides Using Different Binding Modes

Toxoplasma gondii is unable to synthesize purines de novo, instead salvages them from its environment, inside the host cell, for which they need high affinity carriers. Here, we report the expression of a T. gondii Equilibrative Nucleoside Transporter, Tg244440, in a Trypanosoma brucei strain from which nucleobase transporters have been deleted. Tg244440 transported hypoxanthine and guanine with similar affinity (K_m ~1 µM), while inosine and guanosine displayed K_i values of 4.05 and 3.30 µM, respectively. Low affinity was observed for adenosine, adenine, and pyrimidines, classifying Tg244440 as a high affinity oxopurine transporter. Purine analogues were used to probe the substrate-transporter binding interactions, culminating in quantitative models showing different binding modes for oxopurine bases, oxopurine nucleosides, and adenosine. Hypoxanthine and guanine interacted through protonated N1 and N9, and through unprotonated N3 and N7 of the purine ring, whereas inosine and guanosine mostly employed the ribose hydroxy groups for binding, in addition to N1H of the nucleobase. Conversely, the ribose moiety of adenosine barely made any contribution to binding. Tg244440 is the first gene identified to encode a high affinity oxopurine transporter in T. gondii and, to the best of our knowledge, the first purine transporter to employ different binding modes for nucleosides and nucleobases.     

Combined Modeling Study of the Binding Characteristics of Natural Compounds,Derived from Psoralea Fruits,to β-Amyloid Peptide Monomer

A dysfunctional protein aggregation in the nervous system can lead to several neurodegenerative disorders that result in intracellular inclusions or extracellular aggregates. An early critical event within the pathogenesis of Alzheimer’s disease is the accumulation of amyloid beta peptide within the brain. Natural compounds isolated from Psoralea Fructus (PF) have significant anti-Alzheimer effects as strong inhibitors of Aβ42 aggregation. Computer simulations provide a powerful means of linking experimental findings to nanoscale molecular events. As part of this research four prenylated compounds, the active ingredients of Psoralea Fructus (PF), were studied as Aβ42 accumulation inhibitors using molecular simulations modeling. In order to resolve the binding modes of the ligands and identify the main interactions of Aβ42 residues, we performed a 100 ns molecular dynamics simulation and binding free energy calculations starting from the model of the compounds obtained from the docking study. This study was able to pinpoint the key amino acid residues in the Aβ42 active site and provide useful information that could benefit the development of new Aβ42 accumulation inhibitors.     

Natural Convection of Nanofluid in Cylindrical Enclosure Filled with Porous Media

A numerical study has been carried out to investigate the effect of aspect ratio on heat transfer by natural convection of nanofluid taking Cu nano particles and the water as based fluid. The flow is laminar, steady state, axisymmetric two-dimensional in a vertical cylindrical channel filled with porous media. Heat is generated uniformly along the center of the channel with its vertical surface remain with cooled constant wall temperature and insulated horizontal top and bottom surfaces. The governing equations which used are continuity, momentum and energy equations using Darcy law and Boussinesq＇s approximation which are transformed to dimensionless equations. The finite difference approach is used to obtain all the computational results using the MATLAB-7 program. The parameters affected on the system are Rayleigh number ranging within （10≤ Ra ≤ 103）, aspect ratio （1 ≤ As 〈 5） and the volume fraction （0 ≤0 〈 0.2）. The results obtained are presented graphically in the form of streamline and isotherm contour plots and the results show that as ~ increase from 0.01 to 0.2 the value of the mean Nusselt number increase 50.4% for Ra = 1,000.     

Restoration of heavily polluted branches of the Shatt Al-Arab river, Iraq

In view of the desire to improve the water quality of the heavily polluted branches of the Shatt al-Arab River at the City of Basrah, it was proposed to maintain effective flushing as well as contracting sewerage system. The present study was conducted in order to examine the water quality of these branches in an attempt to evaluate the effectiveness of the proposed flushing system. It has been found that their waters contained very low levels of dissolved oxygen and relatively high amounts of both COD and BOD₅. The annual average water quality parameters for Basrah Branches were: dissolved oxygen 3.4 ppm; pH 7.67; hydrogen sulphide 1.4 ppm; ammonia 97 μg-at. N l⁻¹; COD 15.9 mg l⁻¹; BOD₅ 12.7 mg l⁻¹; dissolved silicates 202 μg-at. Si l⁻¹; dissolved reactive phosphate 13.4 μg-at. P-PO₄³⁻ l⁻¹; nitrate 10.4 μg-at. N-NO₃⁻ l⁻¹; nitrite 2.1 μg-at. N-NO₂⁻ l⁻¹ and chlorophyll-α 14.3 mg m⁻³. Based on our calculations, it has been concluded that the proposed system is effective, thus within a flushing cycle all of the above mentioned parameters will become within the acceptable values of the Shatt al-Arab water quality. Moreover, this system has no appreciable effect upon the water quality characteristics of the Shatt al-Arab River due to the fact that it discharges a high volume of water annually. However, It has been recommended to dredge the deposited sludge to a minimum depth of 50 cm.