Multistate Tuning of Third Harmonic Generation in Fano-Resonant Hybrid Dielectric Metasurfaces

Hybrid dielectric metasurfaces have emerged as a promising approach to enhancing near field confinement and thus high optical nonlinearity by utilizing low loss dielectric rather than relatively high loss metallic resonators. A wider range of applications can be realized if more design dimensions can be provided from material and fabrication perspectives to allow dynamic control of light. Here, tunable third harmonic generation (THG) via hybrid metasurfaces with phase change material Ge₂Sb₂Te₅ (GST) deposited on top of amorphous silicon metasurfaces is demonstrated. Fano resonance is excited to confine the incident light inside the hybrid metasurfaces, and an experimental quality factor (Q-factor ≈ 125) is achieved at the fundamental pump wavelength around 1210 nm. Not only the switching between a turn-on state of Fano resonance in the amorphous state of GST and a turn-off state in its crystalline state are demonstrated, but also gradual multistate tuning of THG emission at its intermediate states. A high THG conversion efficiency of η = 2.9 × 10⁻⁶% is achieved, which is 32 times more than that of a GST-based Fabry–Pèrot cavity under a similar pump laser power. Experimental results show the potential of exploring GST-based hybrid dielectric metasurfaces for tunable nonlinear optical devices.     

Vibrating Particles System Algorithm for Solving Classification Problems

Big data is a term that refers to a set of data that, due to its largeness or complexity, cannot be stored or processed with one of the usual tools or applications for data management, and it has become a prominent word in recent years for the massive development of technology. Almost immediately thereafter, the term “big data mining” emerged, i.e., mining from big data even as an emerging and interconnected field of research. Classification is an important stage in data mining since it helps people make better decisions in a variety of situations, including scientific endeavors, biomedical research, and industrial applications. The probabilistic neural network (PNN) is a commonly used and successful method for handling classification and pattern recognition issues. In this study, the authors proposed to combine the probabilistic neural network (PPN), which is one of the data mining techniques, with the vibrating particles system (VPS), which is one of the metaheuristic algorithms named “VPS-PNN”, to solve classification problems more effectively. The data set is eleven common benchmark medical datasets from the machine-learning library, the suggested method was tested. The suggested VPS-PNN mechanism outperforms the PNN, biogeography-based optimization, enhanced-water cycle algorithm (E-WCA) and the firefly algorithm (FA) in terms of convergence speed and classification accuracy.     

Arabic sentiment analysis using recurrent neural networks: a review

Artificial Intelligence Review - Over the last decade, the amount of Arabic content created on websites and social media has grown significantly. Opinions are shared openly and freely on social...     

Multi-user Shared Access (MUSA) procedure for device discovery in D2D communication

Telecommunication Systems - In a wireless self-organizing and the network-assisted Device-to-Device (D2D) network, proximal Device Discovery (DD) plays a noteworthy role. It is the foundation for...     

Two dimensional Cu based nanocomposite materials for direct urea fuel cell

In this work, Cu₂O nanoparticles were successfully prepared onto the surface of two-dimensional graphitic carbon nitride (g-C₃N₄) by using a simple solution chemistry approach. An environment-friendly reducing agent, glucose, was used for the synthesis of Cu₂O NPs onto the surface of g-C₃N₄ without using any surfactant or additives. The surface composition, crystalline structure, morphology, as well as other properties have been investigated using XPS, XRD, SEM, FTIR, FESEM, EDS, etc. The electrochemical measurements of the prepared materials demonstrated that Cu₂O exhibited a weak oxidation activity towards urea, while g-C₃N₄ has no activity towards urea oxidation. The Cu₂O supported on the surface of g-C₃N₄ (Cu₂O-g-C₃N₄) demonstrated a significant activity towards urea oxidation that reached two times that of the unsupported one. The significant increase in the performance was related to the synergetic effect between the Cu₂O and g-C₃N₄ support. The prepared composite materials demonstrated high stability towards urea oxidation as confirmed from the stable current discharge for around 3 h without any noticeable degradation performance.     

A diagnostic prediction model for chronic kidney disease in internet of things platform

Multimedia Tools and Applications - Chronic Kidney Disease (CKD) is being typically observed as a health threatening issue, especially in developing countries, where receiving proper treatments are...     

Camel milk composition by breed,season, publication year,and country: A global systematic review,meta-analysis,and meta-regression

Camel milk consists of an essential macro/micronutrient for human nutrition in the arid and urban regions. This review study aimed to use meta-analysis statistical techniques for assessment and correction of publication bias, exploration of heterogeneity between studies, and detailed assessment of the effect of a comprehensive set of moderators including breed, season, country, year of publication, and the interaction between composition elements. This could provide a single synthesis of the camel milk composition to warrant strong generalizability of results, examine variability between available studies, and analyze differences in camel milk composition among different exposures. Such a finding will aid future researchers and health professionals in acquiring a more precise understanding of camel milk composition and drawing more clinical implications. Six searching databases and bibliographic were used including PubMed/MEDLINE, ScienceDirect, Springer, EBSCOhost, Scopus, and Web of Science from January 1980 to December 2021. The DerSimonian–Laird estimator was used to create the current random-effects meta-analysis. This systematic review and meta-analysis included a total of 7298 camel milk samples from 23 countries. This review comprises 79 studies published in the English language on or after 1980, including a subgroup of 117 analyses consisting of seasons, sub-breeds, and countries. The contents of macro/micronutrients in camel milk were identified as follows: protein, 3.17%; fat, 3.47%; lactose, 4.28%; ash, 0.78%; and total solids, 11.31%; calcium, 112.93 mg/100 g; iron, 0.45 mg/100 g; potassium, 116.13 mg/100 g; magnesium, 9.65 mg/100 g; sodium, 53.10 mg/100 g; zinc, 1.68 mg/100 g; vitamin C, 5.38 mg/100 g; vitamin A, 0.36 mg/100 g; vitamin B₁,0.05 mg/100 g; vitamin B₂, 0.13 mg/100 g; vitamin B₃, 0.51 mg/100 g; vitamin B₆, 0.09 mg/100 g; and vitamin B₁₂, 0.0039 mg/100 g. Our meta-regression analysis found that fat and total solids were statistically significant moderators of protein; moreover, total solids content is a statistically significant moderator of fat. Discrepancies observed in camel milk profiles are dependent upon several factors, including number of included studies, number of samples, different analytical techniques, feeding patterns, camel's breeds, geographical locations, and seasonal variations.     

Multidimensional frequency estimation using LU decomposition eigenvector–based algorithm

Many algorithms have been proposed for multidimensional frequency estimation from a single snapshot or multiple snapshots of data mixture. Most of these algorithms fail when one or more identical frequencies are found in certain dimensions. In this paper, a multidimensional frequency estimation technique from a single datum snapshot is proposed. It applies LU decomposition (Gaussian Elimination) on an eigenvector-based algorithm for multidimensional frequency estimation. This proposed technique is simulated using a MATLAB code. The average root mean square error (RMSE) is investigated as a performance measure of the proposed technique. A comparison between original eigenvector-based (traditional) and the proposed techniques is introduced. The simulation results show that the RMSE of the proposed technique is less than the original one, and it has a more efficient solution for an identical frequency case but at the expense of complexity.     

Integrated shale gas supply chain design and water management under uncertainty

The development of shale gas resources is subject to technical challenges and markedly affected by volatile markets that can undermine the development of new projects. Consequently, stakeholders can greatly benefit from decision-making support tools that integrate the complexity of the system along with the uncertainties inherent to the problem. Accordingly, a general methodology is proposed in this work for the evaluation of integrated shale gas and water supply chains under uncertainty. First, key parametric uncertainties are identified from a candidate pool via a global sensitivity analysis based on a deterministic optimization model. Then, a two-stage stochastic model is developed considering only the key uncertain parameters in the problem. Moreover, the merits of modeling uncertainty and implementing the stochastic solution approach are evaluated using the expected value of perfect information and the value of the stochastic solution metrics. Furthermore, the conditional value-at-risk approach was implemented to evaluate different risk-aversion levels and the corresponding impacts on the shale gas development plan. The proposed methodology is illustrated through two real-world case studies involving six and eight potential well-pad locations and two options of well-pad layouts. © 2018 American Institute of Chemical Engineers AIChE J, 65: 924–936, 2019     

Modified Orthogonal Frequency Division Multiplexing Technique: A Candidate for the New Generation of Wireless Systems

Wireless Personal Communications - In this work, propositions to enhance the power efficiency of orthogonal frequency division multiplexing (OFDM) have been investigated, which has been considered...