In this work, the essential oils (EOs) from Eriocephalus africanus leaf, Vitex agnus-castus leaf and fruit, Cymbopogon citratus leaf, and Rosmarinus officinalis leaf were used as antifungal agents against isolated Aspergillus flavus, Cladosporium cladosporioides, and Penicillium chrysogenum from an ancient Egyptian child’s mummy. The isolated fungi were used to colonize the samples of linen fibers. The best oil was used as a novel natural product for the cleaner production of model linen fibers similar to those used in ancient Egyptian mummification. Standard and original linen fibers were compared with the infected Linen samples using Fourier transform infrared (FTIR) and X-ray diffraction (XRD) analyses. The FTIR revealed the changes in the molecular structure of the cellulose, hemicellulose, and lignin of the infected linen fibers. The cellulose crystallinity indices decreased to 64.61%, 52.69%, and 54.63% in the linen inoculated with A. flavus, C. cladosporioides, and P. chrysogenu... [more]

Human cancer and pathogenic microbes cause a significant number of deaths every year. Modulating current sources of natural products that control such diseases becomes essential. Natural algae, such as Ascophyllum nodosum and Ecklonia maxima, can modulate the metabolic processes as well the bioactivities of Ruta graveolens L. The R. graveolens plants were subjected to nine soil drenches of A. nodosum (7 mL L−1), E. maxima (7 mL L−1), or both extracts. Morphological performance, gas exchange parameters, and essential oils (EOs) composition (GC-MS) were studied and the bioactivity was assessed against several cancer cells and pathogenic bacteria or fungi. Treatment with A. nodosum + E. maxima seaweed extracts (SWE) led to the highest morphological performance and gas exchange parameters. The highest antiproliferative, apoptotic, and caspase-3/7 activities of EO were against HeLa in SWE mixture treated plants. The best EO antimicrobial activities were obtained against Staphylococcus aureu... [more]

The rising global warming concerns and explosive degradation of the environment requires the mainstream utilization of alternative fuels, such as hydroxy gas (HHO) which presents itself as a viable substitute for extracting the benefits of hydrogen. Therefore, an experimental study of the performance and emission characteristics of alternative fuels in contrast to conventional gasoline was undertaken. For experimentation, a spark ignition engine was run on a multitude of fuels comprising of gasoline, Liquefied petroleum gas (LPG) and hybrid blend of HHO with LPG. The engine was operated at 60% open throttle with engine speed ranging from 1600 rpm to 3400 rpm. Simultaneously, the corresponding performance parameters including brake specific fuel consumption, brake power and brake thermal efficiency were investigated. Emission levels of CO, CO2, HC and NOx were quantified in the specified speed range. To check the suitability of the acquired experimental data, it was subjected to a Weibu... [more]

The postharvest physiology of cut flowers is largely dependent on vase life, which is the maximum number of days before flower senescence. The use of tree bark extracts (major forest plant residues), as an eco-friendly and natural antioxidant preservative in holding solutions, is a novel tool for extending flower longevity. The morphological, physiological, biochemical, and genetic responses of Gladiolus grandiflorus cut spikes to Magnolia acuminata and Taxus cuspidata bark extracts as additives in holding solutions were investigated. G. grandiflorus subjected to bark extracts as well as catechin and protocatechuic acid (main phenols) displayed significant increased longevity (up to 18 days), an increased number of open florets, and increased floret fresh weight. Increases in the relative water content, leaf chlorophyll, carotenoids, soluble sugars, and protein content were observed in addition to a reduction in microbial growth in the cut spikes. Gas exchange parameters were higher in... [more]

By mimicking the biological evolution process, genetic algorithm (GA) methodology has the advantages of creating and updating new elite parameters for optimization processes, especially in controller design technique. In this paper, a GA improvement that can speed up convergence and save operation time by neglecting chromosome decoding step is proposed to find the optimized fuzzy-proportional-integral-derivative (fuzzy-PID) control parameters. Due to minimizing tracking error of the controller design criterion, the fitness function integral of square error (ISE) was employed to utilize the advantages of the modified GA. The proposed method was then applied to a novel autonomous hovercraft motion model to display the superiority to the standard GA.

To study the appropriate numerical simulation methods for venturi injectors, including the investigation of the hydraulic performance, mixing process, and the flowing law of the two internal fluids, simulations and experiments were conducted in this study. In the simulations part, the cavitation model based on the standard k−ε turbulence and mixture models was added, after convergence of the calculations. The results revealed that the cavitation model has good agreement with the experiment. However, huge deviations occurred between the experimental results and the ones from the calculation when not considering the cavitation model after cavitation. Thus, it is inferred that the cavitation model can exactly predict the hydraulic performance of a venturi injector. In addition, the cavitation is a crucial factor affecting the hydraulic performance of a venturi injector. The cavitation can ensure the stability of the fertilizer absorption of the venturi injector and can realize the precise... [more]

This paper presents a simultaneous state variables and system and actuator fault estimation, based on an unknown input interval observer design for a discrete-time parametric uncertain Takagi−Sugeno system under actuator fault, with disturbances in the process and measurement noise. The observer design is synthesized by considering unknown but bounded process disturbances, output noise, as well as bounded parametric uncertainties. By taking into account these considerations, the upper and lower bounds of the considered faults are estimated. The gain of the unknown input interval observer is computed through a linear matrix inequalities (LMIs) approach using the robust H ∞ criteria in order to ensure attenuation of process disturbances and output noise. The interval observer scheme is experimentally evaluated by estimating the upper and lower bounds of a torque load perturbation, a friction parameter and a fault in the input voltage of a permanent magnet DC motor.

This paper presents an economic reliability-aware model predictive control (MPC) for the management of drinking water transport networks (DWNs). The proposed controller includes a new goal to increase the system and components reliability based on a finite horizon stochastic optimization problem with joint probabilistic (chance) constraints. The proposed approach is based on a single-layer economic optimization problem with dynamic constraints. The inclusion of components and system reliability in the MPC model using an Linear Parameter Varying (LPV) modeling approach aims to maximize the availability of the system by estimating system reliability. On the other hand, the use of a LPV-MPC control approach allows the controller to consider nonlinearities in the model in a linear like way. Moreover, the resulting MPC optimization problem can be formulated as a Quadratic Programming (QP) problem at each sampling time reducing the computational burden/time compared to solving a nonlinear pr... [more]

In this paper, we propose a triple-mode model predictive control (MPC) algorithm that uses future target information to improve tracking performance. To explicitly take into account the future target information in the MPC optimization, the proposed triple-mode control law encompasses three parts: (i) the future target information feedforward, (ii) the output feedback, and (iii) the extra degrees of freedom for constraint satisfaction. The first two parts of the control law are off-line designed through unconstrained MPC, and the optimal future trajectory horizon is obtained by golden section search based on the integral of squared error (ISE) criterion. The final part is calculated by the on-line MPC algorithm aiming to satisfy constraints. Furthermore, we analyze the feasibility and convergence properties of the proposed algorithm. The method is demonstrated by the simulation of the shell fundamental control problem and also tested on the coordinated control problem in the power plan... [more]

Artificial neural networks (ANNs), which have excellent self-learning performance, have been applied to various applications, such as target detection and industrial control. In this paper, a reference-model-based ANN controller with integral-proportional-derivative (I-PD) compensation has been proposed for temperature control systems. To improve the ANN self-learning efficiency, a reference model is introduced for providing the teaching signal for the ANN. System simulations were carried out in the MATLAB/SIMULINK environment and experiments were carried out on a digital-signal-processor (DSP)-based experimental platform. The simulation and experimental results were compared with those for a conventional I-PD control system. The effectiveness of the proposed method was verified.

With the decentralization of the electricity market and the plea for a carbon-neutral ecosystem, more and more distributed generation (DG) has been incorporated in the power distribution grid, which is then known as active distribution network (ADN). The addition of DGs causes numerous control and protection confronts to the traditional distribution network. For instance, two-way power flow, small fault current, persistent fluctuation of generation and demand, and uncertainty of renewable energy sources (RESs). These problems are more challenging when the distribution network hosts many converter-coupled DGs. Hence, the traditional protection schemes and relaying methods are inadequate to protect ADNs against short-circuit faults and disturbances. We propose a robust communication-assisted fault protection technique for safely operating ADNs with high penetration of converter-coupled DGs. The proposed technique is realizable by employing digital relays available in the recent market an... [more]

The incidence of diabetes is on the rise and one of the medically active plants used for the treatment of diabetes in South Africa is Lauridia tetragona. The aim of this study is to investigate the antidiabetic property of the polyphenolics (PP) compounds isolated from the methanolic extract of Lauridia tetragona. The α-amylase, α-glucosidase, dipeptidyl peptidase IV (DPPIV), lipase inhibitory activities, and glucose uptake in HepG2 were investigated. The methanolic extract fractions of L. tetragona yielded six fractions (PP1−PP6) all of which showed weak inhibition against DPPIV and lipase compared to the standards. However, PP4 and PP6 showed the best inhibition against α-amylase (IC50 of 359.3 ± 2.11 and 416.82 ± 2.58 μg/mL, respectively) and α-glucosidase (IC50 of 95.93 ± 2.34 and 104.49 ± 2.21 μg/mL, respectively) and only PP4 (173.6%) resulted in enhanced glucose uptake in HepG2 cells compared to berberine (129.89%) and metformin (187.16%) used as positive controls. The previous... [more]

The residue hydrotreating process plays a significant role in the petroleum refining industry. In this process, modeling and simulation have critical importance for process development, control, and optimization. However, there is a lack of relevant reports of plant scale due to complexity in characterizing feedstock and determining reaction mechanisms. In this paper, reaction and fractionation models are constructed and simulated for a real-life industrial residue hydrotreating process based on Aspen HYSYS/Refining. Considering the heavier and inferior residue, analytical characterization is carried out for feedstock characterization based on laboratory analysis data. Moreover, two reactor models with parallel structures are proposed to implement the intricate reaction network, namely, a hydrocracker reactor and a plug flow reactor. The former simulates lighter petroleum hydrotreating based on the built-in reaction network. The latter emulates the conversion of a peculiar, heavier res... [more]

This paper investigates the vibration control, stability, and energy transfer of the offshore wind turbine tower system with control force and nonlinearity terms. A nonlinear proportional derivative (NPD) controller was connected to the system to reduce a high oscillation amplitude and to transfer the energy in the wind turbine system. Furthermore, the averaging method and Poincaré maps were used with respect to the controlled system to study the stability and bifurcation analysis in the worst resonance cases. The curves of force response and frequency response were plotted before and after the control unit was added to the wind turbine system. In addition, we discuss the performances of the control parameters on the vibration magnitudes. Numerical simulations were carried out with Maple and Matlab algorithms to confirm the analytical results. The results show the effectiveness of the NPD controller in suppressing the nonlinear oscillations of the wind turbine system.

Deadlock control approaches based on Petri nets are usually implemented by adding control places and related arcs to the Petri net model of a system. The main disadvantage of the existing policies is that many control places and associated arcs are added to the initially constructed Petri net model, which significantly increases the complexity of the supervisor of the Petri net model. The objective of this study is to develop a two-step robust deadlock control approach. In the first step, we use a method of deadlock prevention based on strict minimal siphons (SMSs) to create a controlled Petri net model. In the second step, all control places obtained in the first step are merged into a single control place based on the colored Petri net to mark all SMSs. Finally, we compare the proposed method with the existing methods from the literature.

There is currently a lack of understanding of the deposition profile in a batch atomic layer deposition (ALD) process. Also, no on-line control scheme has been proposed to resolve the prevalent disturbances. Motivated by this, we develop a computational fluid dynamics (CFD) model and an integrated online run-to-run and feedback control scheme. Specifically, we analyze a furnace reactor for a SiO2 thin-film ALD with BTBAS and ozone as precursors. Initially, a high-fidelity 2D axisymmetric multiscale CFD model is developed using ANSYS Fluent for the gas-phase characterization and the surface thin-film deposition, based on a kinetic Monte-Carlo (kMC) model database. To deal with the disturbance during reactor operation, a proportional integral (PI) control scheme is adopted, which manipulates the inlet precursor concentration to drive the precursor partial pressure to the set-point, ensuring the complete substrate coverage. Additionally, the CFD model is utilized to investigate a wide ran... [more]

Cyber-attacks threaten the safety of cyber physical systems (CPSs) as a result of the existence of weaknesses in the multiple structural units constituting them. In this paper, three cyber physical systems case studies of a pressurized water nuclear power plant (NPP), an industrial control system (ICS), and a vehicular network system (VNS) are examined, formally presented, and implemented utilizing Architecture Analysis and Design Language, determining system design, links, weaknesses, resources, potential attack instances, and their pre-and post-conditions. Then, the developed plant models are checked with a security property using JKind model checker embedded software. The attack graphs causing plants disruptions for the three applications are graphically visualized using a new graphical user interface (GUI) windows application.

The present research provides a numerical investigation of two dimensional nanofluid flow over an inverted cone inside a porous medium. The model is developed to incorporate non-spherical shapes of C d T e -nanoparticles in water based fluid. Simultaneous effects of pertinent parameters like volume fraction, Reynold number, Hartmann number, porosity, Grashof number, radiation parameter and Peclet number on temperature distribution and velocity profile are studied and illustrated graphically. In addition, the corresponding computational results of Nusselt number and skin frication for regulating parameters are also presented in graphs and tables. The highest Nusselt number is observed for blade-shaped C d T e particles. Furthermore, the thermal conductivity and viscosity are also calculated for non-spherical shapes of C d T e nanoparticles. The result showed that the thermal conductivity of nanofluid with blade-shaped particles is 0.94 % and 1.93 %... [more]

The peel of Gac fruit (Momordica cochinchinensis Spreng.), which is considered as waste of Gac processing, has been found to possess high levels of carotenoids and other antioxidants. This study aimed at determining the optimal conditions of an ultrasound-assisted extraction for recovering carotenoids and antioxidant capacity from Gac peel. A response surface methodology using the Box−Behnken design was employed to investigate the impact of extraction time, temperature and ultrasonic power on the recovery of total carotenoid and antioxidant capacity. The results showed that an extraction time of 76 min, temperature of 50 °C and ultrasonic power of 250 W were the optimal conditions for the extraction. The experimental carotenoid yield and antioxidant capacity obtained under the optimal extraction conditions were validated as 269 mg/100 g DW (dry weight) and 822 µM TE (Trolox equivalent)/100 g DW, respectively. These values were not significantly different from the values predicted by th... [more]

The objective of this paper was to develop a prediction tool for the burden distribution in a charging process of a bell-less-type blast furnace using the discrete element method (DEM). The particle behavior on the rotating chute and on the burden surface was modeled, and the burden distribution was analyzed. Furthermore, the measurements of the burden distribution in a 1/3-scale experimental blast furnace were performed to validate the simulated results. Particle size segregation occurred during conveying to the experimental blast furnace. The smaller particles were initially discharged followed by the larger ones later. This result was used as an input in the simulation. The burden profile simulated using DEM was similar to the experimental one. The terrace was found at the burden surface subsequent to ore-charging, and its simulated position simulated agreed with that of the experimental result. The surface angle of the ore layer was mostly similar. The simulated ore to coke mass ra... [more]

Because of its effectiveness in organic pollutant degradation, manganese peroxidase (MnP) enzyme has attracted significant attention in recent years regarding its use for wastewater treatment. Herein, MnP was extracted from Anthracophyllum discolor fungi and immobilized on the surface of magnetic nanocomposite Fe3O4/chitosan. The prepared nanocomposite offered a high surface area for MnP immobilization. The influence of several environmental factors like temperature, pH, as well as storage duration on the activity of the extracted enzyme has been studied. Fourier transmission infrared spectroscopy (FT-IR), scanning electron microscope (SEM), X-ray diffraction (XRD), and transmission electron microscope (TEM) techniques were used for the characterization of the prepared MnP/Fe3O4/chitosan nanocomposite. The efficiencies of the prepared MnP/Fe3O4/chitosan nanocomposite for the elimination of reactive orange 16 (RO 16) and methylene blue (MB) industrial dyes were determined. According to... [more]

The performance of cross-flow ultrafiltration is greatly influenced by permeate flux behavior, which depends on many factors, including solution properties, membrane characteristics, and operating conditions. Currently, most research focuses on improving membrane performance, both in terms of permeability and selectivity. Only a few studies have paid attention to how the membrane module is configured and operated. In this study, the geometric design and operating conditions of a membrane module are considered as multivariable optimization variables. The objective function is the annual cost. The cost consists of a capital investment depending on the plant scale and an operating expense associated with energy consumption. In the optimization problem, the channel dimensions (width × length × height), and operating conditions (the inlet pressure and recirculation flow rate) were considered as decision variables. The operating configuration of the membrane plant is assumed to be feed and b... [more]

Grinding is widely used in mechanical manufacturing to obtain both precision and part requirements. In order to achieve carbon efficiency improvement and save costs, carbon emission and processing cost models of the grinding process are established in this study. In the modeling process, a speed-change-based adjustment function was introduced to dynamically derive the change of the target model. The carbon emission model was derived from the grinding force using regression. Considering the constraints of machine tool equipment performance and processing quality requirements, the grinding wheel’s linear velocity, cutting feed rate, and the rotation speed of the workpiece were selected as the optimization variables, and the improved NSGA-II algorithm was applied to solve the optimization model. Finally, fuzzy matter element analysis was used to evaluate the most optimal processing plan.

In order to maximize the operating flexibility and optimize the system performance of a battery energy storage system (BESS), developing a reliable real-time estimation method for the state of charge (SOC) of a BESS is one of the crucial tasks. In practice, the accuracy of real-time SOC detection can be interfered with by various factors, such as battery’s intrinsic nonlinearities, working current, temperature, and aging level, etc. Considering the feasibility in practical applications, this paper proposes a hybrid real-time SOC estimation scheme for BESSs based on an adaptive network-based fuzzy inference system (ANFIS) and Coulomb counting method, where a commercially available lead-acid battery-based BESS is used as the research target. The ANFIS allows effective learning of the nonlinear characteristics in charging and discharging processes of a battery. In addition, the Coulomb counting method with an efficiency adjusting mechanism is simultaneously used in the proposed scheme to... [more]

The traditional two-column reactive distillation (RD) process is used for the production of butyric anhydride, which is synthesized with butyric acid and acetic anhydride via a reversible reaction. In this work, a novel process with a single RD column (SRDC) is designed for the production of butyric anhydride, where the second distillation column for separating excess reactant is removed based on the boiling point profile of the reaction system. Two applications of the proposed SRDC process, namely SRDC with excess butyric acid or acetic anhydride circulating internally, are economically optimized, and the results show that both SRDC processes have a lower total annual cost (TAC) than the traditional two-column process. Furthermore, from the perspective of TAC, the application with an excess feed of butyric acid is better than the application with excess acetic anhydride. The developed technique may also be applied to retrofit other traditional two-column RD processes, where the overhe... [more]