Design a robust sliding mode controller based on the state and parameter estimation for the nonlinear epidemiological model of Covid-19

In this research, the challenging problem of Covid-19 mitigation is looked at from an engineering point of view. At first, the behavior of coronavirus in the Iranian and Russian societies is expressed by a set of ordinary differential equations. In the proposed model, the control input signals are vaccination, social distance and facial masks, and medical treatment. The unknown parameters of the system are estimated by long short-term memory (LSTM) algorithm. In the LSTM algorithm, the problem of long-term dependency is prevented. The uncertainty and measurement noises are inherent characteristics of epidemiological models. For this reason, an extended Kalman filter (EKF) is developed to estimate the state variables of the proposed model. In continuation, a robust sliding mode controller is designed to control the spread of coronavirus under vaccination, social distance and facial masks, and medical treatment. The stability of the closed-loop system is guaranteed by the Lyapunov theorems. The official confirmed data provided by the Iranian and Russian ministries of health are employed to simulate the proposed algorithms. It is understood from simulation results that global vaccination has the potential to create herd immunity in long term. Under the proposed controller, daily Covid-19 infections and deaths become less than 500 and 10 people, respectively.

     

Electrocatalytic Oxidation of Ethanol on Flexible Three‐dimensional Interconnected Nickel/Gold Composite Foams in Alkaline Media

In this work, a porous and flexible three‐dimensional (3D) nickel/gold nanoparticle electrode (NiF/AuNPs) is presented as an efficient electrocatalyst for ethanol oxidation in alkaline media. The 3D nanocomposite electrode consists of interconnected porous nickel foam (NiF) with large pores (500±200 μm diameter) surrounded by interconnected struts (～100 μm) that are decorated with gold nanoparticles (AuNPs, 37±8 nm) through in‐situ electrochemical deposition. The catalytic performance of the 3D electrode was evaluated by different electrochemical methods. An enhancement in the performance (about 253 %) and a remarkable decline in onset potential (about ～0.63 V) in comparison with pristine NiF for ethanol oxidation are demonstrated. This potential is lower than many reported results except palladium‐ and platinum‐based catalysts, which are expensive. It is shown that both hydroxyl anions and cations affect the ethanol oxidation on the 3D electrode. The interconnected porous structure provides efficient mass diffusivity, which along with its high specific surface area combined with the catalytic nature of AuNPs, may open new opportunities for in‐inexpensive and highly efficient electro‐oxidation of ethanol for energy applications.     

Low-frequency Vibrational Modes in Small Polypeptides of Essential Amino Acids

Optics and Spectroscopy - The length-dependent low-frequency terahertz absorption spectrum of the essential amino acid chains has been investigated. Since this special type of amino acids cannot be...     

Preparation and characterization of a composite PDMS membrane on CA support

Polydimethylsiloxane (PDMS) is the most commonly used membrane material for the separation of condensable vapors from lighter gases. In this study, a composite PDMS membrane was prepared and its gas permeation properties were investigated at various upstream pressures. A microporous cellulose acetate (CA) support was initially prepared and characterized. Then, PDMS solution, containing crosslinker and catalyst, was cast over the support. Sorption and permeation of C₃H₈, CO₂, CH₄, and H₂ in the prepared composite membrane were measured. Using sorption and permeation data of gases, diffusion coefficients were calculated based on solution‐diffusion mechanism. Similar to other rubbery membranes, the prepared PDMS membrane advantageously exhibited less resistance to permeation of heavier gases, such as C₃H₈, compared to the lighter ones, such as CO₂, CH₄, and H₂. This result was attributed to the very high solubility of larger gas molecules in the hydrocarbon‐based PDMS membrane in spite of their lower diffusion coefficients relative to smaller molecules. Increasing feed pressure increased permeability, solubility, and diffusion coefficients of the heavier gases while decreased those of the lighter ones. At constant temperature (25°C), empirical linear relations were proposed for permeability, solubility, and diffusion coefficients as a function of transmembrane pressure. C₃H₈/gas solubility, diffusivity, and overall selectivities were found to increase with increasing feed pressure. Ideal selectivity values of 9, 30, and 82 for C₃H₈ over CO₂, CH₄, and H₂, respectively, at an upstream pressure of 8 atm, confirmed the outstanding separation performance of the prepared membrane. Copyright © 2009 John Wiley & Sons, Ltd.     

A new and reliable model for predicting methane viscosity at high pressures and high temperatures

In recent years, there has been an increase of interest in the flow of gases at relatively high pressures and high temperatures. Hydrodynamic calculation of the energy losses in the flow of gases in conduits, as well as through the porous media constituting natural petroleum reservoirs, requires knowledge of the viscosity of the fluid at the pressure and temperature involved. Although there are numerous publications concerning the viscosity of methane at atmospheric pressure, there appears to be little information available relating to the effect of pressure and temperature upon the viscosity. A survey of the literature reveals that the disagreements between published data on the viscosity of methane are common and that most investigations have been conducted over restricted temperature and pressure ranges. Experimental viscosity data for methane are presented for temperatures from 320 to 400 K and pressures from 3000 to 140000 kPa by using falling body viscometer. A summary is given to evaluate the available data for methane, and a comparison is presented for that data common to the experimental range reported in this paper. A new and reliable correlation for methane gas viscosity is presented. Predicted values are given for temperatures up to 400 K and pressures up to 140000 kPa with Average Absolute Percent Relative Error (EABS) of 0.794.     

Octadecyltrichlorosilane (OTS): a resist for OMCVD gold nanoparticle growth

One application of octadecyltrichlorosilane (OTS) self‐assembled monolayers (SAMs) is its use as thin film resists. In this work, we demonstrated that OTS SAMs can be reliable resists for organo‐metallic chemical vapor deposition (OMCVD) grown gold nanoparticles (Au NPs). In optical sensing applications based on Au NPs, one candidate system consists of patterned OTS SAMs and precisely grown OMCVD Au NPs for achieving a high sensitivity. As an initial step, the OTS SAMs need to perfectly resist the OMCVD Au NP growth. Hence the optimized formation of the OTS SAMs affected by different assembly times and baking temperatures was studied by contact angle, ellipsometry, XPS, SEM, and atomic force microscopy (AFM). To demonstrate the ability of the OTS SAMs to resist OMCVD Au NP growth, the OMCVD process was carried out on two sets of samples: OTS SAMs fabricated under optimized conditions on one set and the other set without OTS SAMs. High‐resolution XPS, RBS, SEM, and ultraviolet‐visible (UV‐Vis) spectroscopy were applied to study the growth of Au NPs on the samples with and without OTS SAM resists. Copyright © 2009 John Wiley & Sons, Ltd.     

Stability of preserving lattice cubic functional equation in Menger probabilistic normed Riesz spaces

The aim of this paper is to investigate Hyers–Ulam–Rassias stability of preserving lattice functional equation in various spaces. First, we prove stability of generalized preserving lattice functional equation in Banach lattices. Next, we show stability of preserving lattice cubic functional equation in Menger probabilistic normed Riesz spaces.     

Interval estimation of $$$$ in ranked set sampling

This article deals with constructing a confidence interval for the reliability parameter using ranked set sampling. Some asymptotic and resampling-based intervals are suggested, and compared with their simple random sampling counterparts using Monte Carlo simulations. Finally, the methods are applied on a real data set in the context of agriculture.     

Magnetic resonance T1ρ imaging of osteoarthritis: a rabbit ACL transection model

Objective

The objective of this study was to develop quantitative T_1ρ-weighted magnetic resonance imaging methodology for the detection and characterization of cartilage degeneration in a rabbit anterior cruciate ligament (ACL) transection model.

Methods

The right knee ACLs of 18 adult female New Zealand white rabbits were transected. The left knee joint served as a sham control. The rabbits were euthanized at 3 (Group 1), 6 (Group 2) and 12 (Group 3) weeks postoperatively. High-resolution 3D fat-saturated spoiled gradient echo images and T_1ρ-weighted images were obtained in both the sagittal and axial planes at 3 T using a quadrature wrist coil. Following MR analysis, histological slides from the lateral femoral condyle cartilage were graded using the Mankin grading system.

Results

For all three groups, the average overall T_1ρ values were significantly higher in the ACL-transected knee compared to control knee, and the percentage differences in T_1ρ values between ACL-transected and control increased with the duration of time after transection. The average Mankin score for ACL-transected knees was higher than that for control for each time point, but this difference was statistically significant only for all groups combined.

Conclusions

This study demonstrates the feasibility of using T_1ρ-weighted imaging as a useful tool in the detection and quantification of cartilage damage in all knee compartments in an ACL-transected rabbit model of cartilage degeneration.