Search results for: strain tuning

Authors: Soma Chatterjee, I. Das

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In the present study, we have investigated the structural, electrical and magneto-transport properties of polycrystalline and nanocrystalline Gd0.5Sr0.5MnO3 compounds. The variation of transport properties is modified by tuning the grain size of the material. In the high-temperature semiconducting region, temperature-dependent resistivity data can be well explained by the non-adiabatic small polaron hopping (SPH) mechanism. In addition, the resistivity data for all compounds in the low-temperature paramagnetic region can also be well explained by the variable range hopping (VRH) model. The parameters obtained from SPH and VRH mechanisms are found to be reasonable. In the case of nanocrystalline compounds, there is an overlapping temperature range where both SPH and VRH models are valid simultaneously, and a new conduction mechanism - variable range hopping of small polaron s(VR-SPH) is satisfactorily valid for the whole temperature range of these compounds. However, for the polycrystalline compound, the overlapping temperature region between VRH and SPH models does not exist and the VR-SPH mechanism is not valid here. Thus, polarons play a leading role in selecting different conduction mechanisms in different temperature ranges.

Keywords: electrical resistivity, manganite, small polaron hopping, variable range hopping, variable range of small polaron hopping

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

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The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Mandar Ghodekar, Sharad Jadhav, Sangram Jadhav

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Speed control of rotor during startup and under varying load conditions is one of the most difficult tasks of gas turbine operation. In this paper, power plant gas turbine (GE9001E) is considered for this purpose and fuzzy and fuzzy-PI rotor speed controllers are designed. The goal of the presented controllers is to keep the turbine rotor speed within predefined limits during startup condition as well as during operating condition. The fuzzy controller and fuzzy-PI controller are designed using Takagi-Sugeno method and Mamdani method, respectively. In applying the fuzzy-PI control to a gas-turbine plant, the tuning parameters (Kp and Ki) are modified online by fuzzy logic approach. Error and rate of change of error are inputs and change in fuel flow is output for both the controllers. Hence, rotor speed of gas turbine is controlled by modifying the fuel ƒflow. The identified linear ARX model of gas turbine is considered while designing the controllers. For simulations, demand power is taken as disturbance input. It is assumed that inlet guide vane (IGV) position is fixed. In addition, the constraint on the fuel flow is taken into account. The performance of the presented controllers is compared with each other as well as with H∞ robust and MPC controllers for the same operating conditions in simulations.

Keywords: gas turbine, fuzzy controller, fuzzy PI controller, power plant

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Authors: Amal A. Hassan, Faten H. Fahmy, Abd El-Shafy A. Nafeh, Hosam K. M. Youssef

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Due to the growing penetration of wind energy into the power grid, it is very important to study its interactions with the power system and to provide good control technique in order to deliver high quality power. In this paper, an intelligent control methodology is proposed for optimizing the controllers’ parameters of doubly fed induction generator (DFIG) based wind turbine generation system (WTGS). The genetic algorithm (GA) and particle swarm optimization (PSO) are employed and compared for the parameters adaptive tuning of the proposed proportional integral (PI) multiple controllers of the back to back converters of the DFIG based WTGS. For this purpose, the dynamic model of WTGS with DFIG and its associated controllers is presented. Furthermore, the simulation of the system is performed using MATLAB/SIMULINK and SIMPOWERSYSTEM toolbox to illustrate the performance of the optimized controllers. Finally, this work is validated to 33-bus test radial system to show the interaction between wind distributed generation (DG) systems and the distribution network.

Keywords: DFIG wind turine, intelligent control, distributed generation, particle swarm optimization, genetic algorithm

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Authors: Sinethemba Yakobi, Lindiwe Zuma, Ofentse Pooe

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Gonococcal infections present a notable public health issue, and the major approach for treatment involves using β-lactam antibiotics that specifically target penicillin-binding protein 2 (PBP2) in Neisseria gonorrhoeae. This study examines the influence of flavonoids, namely rutin, on the structural changes of PBP2 in both penicillin-resistant (FA6140) and penicillin-susceptible (FA19) strains. The research clarifies the structural effects of particular mutations, such as inserting an aspartate residue at position 345 (Asp-345a) in the PBP2 protein. The strain FA6140, which is resistant to penicillin, shows specific changes that lead to a decrease in penicillin binding. These mutations, namely P551S and F504L, significantly impact the pace at which acylation occurs and the stability of the strain under high temperatures. Molecular docking analyses investigate the antibacterial activities of rutin and other phytocompounds, emphasizing its exceptional binding affinity and potential as an inhibitor of PBP2. Quercetin and protocatechuic acid have encouraging antibacterial effectiveness, with quercetin displaying characteristics similar to those of drugs. Molecular dynamics simulations offer a detailed comprehension of the interactions between flavonoids and PBP2, highlighting rutin's exceptional antioxidant effects and strong affinity for the substrate binding site. The study's wider ramifications pertain to the pressing requirement for antiviral treatments in the context of the ongoing COVID-19 epidemic. Flavonoids have a strong affinity for binding to PBP2, indicating their potential as inhibitors to impair cell wall formation in N. gonorrhoeae. Ultimately, this study provides extensive knowledge on the interactions between proteins and ligands, the dynamics of the structure, and the ability of flavonoids to combat penicillin-resistant N. gonorrhoeae bacteria. The verified simulation outcomes establish a basis for creating potent inhibitors and medicinal therapies to combat infectious illnesses.

Keywords: phytochemicals, penicillin-binding protein 2, gonococcal infection, ligand-protein interaction, binding energy, neisseria gonorrhoeae FA19, neisseria gonorrhoeae FA6140, flavonoids

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Authors: Aicha Bouhlala, Sabah Chettibi

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Doping CeO₂ with transition metals is an effective way of tuning its properties. In the present work, we have performed self-consistent ab-initio calculation using the full-potential linearized augmented plane-wave method (FP-LAPW), based on the density functional theory (DFT) as implemented in the Wien2k simulation code to study the structural, electronic, and magnetic properties of the compound Ce₁₋ₓCuₓO₂ (x=12.5%) fluorite type oxide and to explore the effects of dopant Cu in ceria. The exchange correlation potential has been treated using the Perdew-Burke-Eenzerhof revised of solid (PBEsol). In structural properties, the equilibrium lattice constant is observed for the compound, which exists within the value of 5.382 A°. In electronic properties, the spin-polarized electronic bandstructure elucidates the semiconductor nature of the material in both spin channels, with the compound was observed to have a narrow bandgap on the spin-down configuration (0.162 EV) and bandgap on the spin-up (2.067 EV). Hence, the doped atom Cu plays a vital role in increasing the magnetic moments of the supercell, and the value of the total magnetic moment is found to be 2.99438 μB. Therefore, the compound Cu-doped CeO₂ shows a strong ferromagnetic behavior. The predicted results propose the compound could be a good candidate for spintronics applications.

Keywords: Cu-doped CeO₂, DFT, Wien2k, properties

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Authors: Elham Jelodari Mamaghani, Christian Prins, Haoxun Chen

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In this paper, there is concentration on collaborative transportation planning (CTP) among multiple carriers with pickup and delivery requests and time windows. This problem is a vehicle routing problem with constraints from standard vehicle routing problems and new constraints from a real-world application. In the problem, each carrier has a finite number of vehicles, and each request is a pickup and delivery request with time window. Moreover, each carrier has reserved requests, which must be served by itself, whereas its exchangeable requests can be outsourced to and served by other carriers. This collaboration among carriers can help them to reduce total transportation costs. A mixed integer programming model is proposed to the problem. To solve the model, a hybrid algorithm that combines Genetic Algorithm and Simulated Annealing (GASA) is proposed. This algorithm takes advantages of GASA at the same time. After tuning the parameters of the algorithm with the Taguchi method, the experiments are conducted and experimental results are provided for the hybrid algorithm. The results are compared with those obtained by a commercial solver. The comparison indicates that the GASA significantly outperforms the commercial solver.

Keywords: centralized collaborative transportation, collaborative transportation with pickup and delivery, collaborative transportation with time windows, hybrid algorithm of GA and SA

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Authors: Nicanor Garcia Alvarez, Belarmino Adenso-Diaz, Laura Calzada Infante

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In recent years, researchers have shown an interest in modelling maritime traffic as a complex network. In this paper, we propose a bipartite weighted network to model maritime traffic and detect port maritime communities. The bipartite weighted network considers two different types of nodes. The first one represents Spanish ports, while the second one represents the countries with which there is major import/export activity. The flow among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the data is segmented by each type of traffic. This will allow fine tuning and the creation of communities for each type of traffic and therefore finding similar ports for a specific type of traffic, which will provide decision-makers with tools to search for alliances or identify their competitors. The traffic with the greatest impact on the Spanish gross domestic product is selected, and the evolution of the communities formed by the most important ports and their differences between 2019 and 2009 will be analyzed. Finally, the set of communities formed by the ports of the Spanish port system will be inspected to determine global similarities between them, analyzing the sum of the membership of the different ports in communities formed for each type of traffic in particular.

Keywords: bipartite networks, competition, infomap, maritime traffic, port communities

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

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Authors: Rajkumar Ghosh

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This paper focuses on the structural analysis of Chaura Thrust in Himachal Pradesh, India. It investigates mylonitised zones under microscopic observation, characterizes the box fold and its signature in the regional geology of Himachal Himalaya, and documents the Higher Himalayan Out-of-Sequence Thrust (OOST) in the region. The study aims to provide field evidence and documentation for Chaura Thrust (CT), which was previously considered a blind thrust. The research methodology involves geological field observation, microscopic studies, and strain analysis of oriented samples collected along the Jhakri-Chaura transect. The study presents findings such as the activation ages of MCT and STDS, the identification of mylonitised zones and various types of crenulated schistosity, and the manifestation of box folds and OOST. The presence of meso- and micro-scale box folds around Chaura suggests structural upliftment, while kink folds and shear sense indicators were identified. The research highlights the importance of microscopic studies and contributes to the understanding of the structural analysis of CT and its implications in the regional geology of the Himachal Himalaya. Mylonitised zones with S-C fabric were observed under the microscope, along with dynamic and bulging recrystallization and sub-grain formation. Various types of crenulated schistosity were documented, including a rare case of crenulation cleavage and sigmoid Muscovite occurring together. The conclusions emphasize the non-blind nature of Chaura Thrust, the characterization of box folds, the activation timing of different thrusts, and the significance of microscopic observations. Jhakri/Chaura/Sarahan thrusts are the zone of tectonic imbrication that transport Higher Himalayan gneissic rock on Rampur Quartzite. The evidence of frequent earthquakes and landslides in the Jhakri region confirm the study of morphometric conclusion that there is considerable neo-tectonic activity along an active fault in the Sutlej river basin. The study also documents the presence of OOST in Himachal Pradesh and its potential impact on strain accumulation.

Keywords: Main Central Thrust, Jhakri Thrust, Chaura Thrust, Higher Himalaya, Out-of-Sequence Thrust, Sarahan Thrust

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Authors: Minh Chien Vu, Tomoaki Satomi, Hiroshi Takahashi

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As being lack of sufficient strength to support the loading of construction as well as service life cause the clay content and clay mineralogy, soft and highly compressible soils (sludge) constitute a major problem in geotechnical engineering projects. Geopolymer, a kind of inorganic polymer, is a promising material with a wide range of applications and offers a lower level of CO₂ emissions than conventional Portland cement. However, the feasibility of geopolymer in term of modified the soft and highly compressible soil has not been received much attention due to the requirement of heat treatment for activating the fly ash component and the existence of high content of clay-size particles in the composition of sludge that affected on the efficiency of the reaction. On the other hand, the geopolymer modified sludge could be affected by other important factors such as initial curing time, initial water content and apparent water content. Therefore, this paper describes a different potential application of geopolymer: soil stabilization in landslide areas to adapt to the technical properties of sludge so that heavy machines can move on. Sludge condition process is utilized to demonstrate the possibility for stabilizing sludge using fly ash-based geopolymer at ambient curing condition ( ± 20 °C) in term of failure strength, strain and bulk density. Sludge conditioning is a process whereby sludge is treated with chemicals or various other means to improve the dewatering characteristics of sludge before applying in the construction area. The effect of initial curing time, water content and apparent water content on the modification of sludge are the main focus of this study. Test results indicate that the initial curing time has potential for improving failure strain and strength of modified sludge with the specific condition of soft soil. The result further shows that the initial water content over than 50% total mass of sludge could significantly lead to a decrease of strength performance of geopolymer-based modified sludge. The optimum apparent water content of geopolymer modified sludge is strongly influenced by the amount of geopolymer content and initial water content of sludge. The solution to minimize the effect of high initial water content will be considered deeper in the future.

Keywords: landslide, sludge, fly ash, geopolymer, sludge conditioning

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Authors: Muhammad Naveed, Sohail Yousaf, Zahir Ahmad Zahir, Birgit Mitter, Angela Sessitsch

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Most bacterial endophytes originate from the soil and enter plants via the roots followed by further spread through the inner tissues. The mechanisms allowing bacteria to colonize plants endophytically are still poorly understood for most bacterial and plant species. Specific bacterial functions are required for plant colonization, but also the plant itself is a determining factor as bacterial ability to establish endophytic populations is very often dependent on the plant genotype (cultivar) and inoculums density. The effect of inoculum density (107, 108, 109 CFU mL-1) of Burkholderia phytofirmans strain PsJN was evaluated on growth and endophytic colonization of different maize and potato cultivars under axenic and natural soil conditions. PsJN inoculation significantly increased maize seedling growth and tuber yield of potato at all inoculum density compared to uninoculated control. Under axenic condition, PsJN inoculation (108 CFU mL-1) significantly improved the germination, root/shoot length and biomass up to 62, 115, 98 and 135% of maize seedling compared to uninoculated control. In case of potato, PsJN inoculation (109 CFU mL-1) showed maximum response and significantly increased root/shoot biomass and tuber yield under natural soil condition. We confirmed that PsJN is able to colonize the rhizosphere, roots and shoots of maize and potato cultivars. The endophytic colonization increased linearly with increasing inoculum density (within a range of 8 x 104 – 3 x 107 CFU mL-1) and were highest for maize (Morignon) and potato (Romina) as compared to other cultivars. Efficient colonization of cv. Morignon and Romina by strain PsJN indicates the specific cultivar colonizing capacity of the bacteria. The findings of the study indicate the non-significant relationship between colonization and plant growth promotion in maize under axenic conditions. However, the inoculum level (109 CFU mL-1) that promoted colonization of rhizosphere and plant interior (endophytic) also best promoted growth and tuber yield of potato under natural soil conditions.

Keywords: crop genotype, inoculum density, Burkholderia phytofirmans PsJN, colonization, growth, potato

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Authors: Emigdio Mendoza, Patricia Fernandez, Cristian Gomez

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Magnesium alloys have generated great interest for several industrial applications because their high specific strength and low density make them a very attractive alternative for the manufacture of various components; however, these alloys present a limitation with their hexagonal crystal structure that limits the deformation mechanisms at room temperature likewise the molding components alternatives, it is for this reason that severe plastic deformation processes have taken a huge relevance recently because these, allow high deformation rates to be applied that induce microstructural changes where the deficiency in the sliding systems is compensated with crystallographic grains reorientations or crystal twinning. The present study reports a statistical analysis of process temperature, number of passes and shear angle with respect to the shear stress in severe plastic deformation process denominated 'Equal Channel Angular Sheet Drawing (ECASD)' applied to the magnesium alloy AZ31B through Python Statsmodels libraries, additionally a Post-Hoc range test is performed using the Tukey statistical test. Statistical results show that each variable has a p-value lower than 0.05, which allows comparing the average values of shear stresses obtained, which are in the range of 7.37 MPa to 12.23 MPa, lower values in comparison to others severe plastic deformation processes reported in the literature, considering a value of 157.53 MPa as the average creep stress for AZ31B alloy. However, a higher stress level is required when the sheets are processed using a shear angle of 150°, due to a higher level of adjustment applied for the shear die of 150°. Temperature and shear passes are important variables as well, but there is no significant impact on the level of stress applied during the ECASD process. In the processing of AZ31B magnesium alloy sheets, ECASD technique is evidenced as a viable alternative in the modification of the elasto-plastic properties of this alloy, promoting the weakening of the basal texture, which means, a better response to deformation, whereby, during the manufacture of parts by drawing or stamping processes the formation of cracks on the surface can be reduced, presenting an adequate mechanical performance.

Keywords: plastic deformation, strain, sheet drawing, magnesium

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Authors: Johanna Perdomo, Riki Lamont, Edmund Pickering, Naomi C. Paxton, Maria A. Woodruff

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Background: Tissue Engineering (TE) has combined advanced materials, such as biomaterials, to create affordable scaffolds and dynamic systems to generate stimulation of seeded cells on these scaffolds, improving and maintaining the cellular growth process in a cell culture. However, Few TE skin products have been clinically translated, and more research is required to produce highly biomimetic skin substitutes that mimic the native elasticity of skin in a controlled manner. Therefore, this work will be focused on the fabrication of a novel mechanical system to enhance the TE treatment approaches for the reparation of damaged tissue skin. Aims: To archive this, a soft robotic device will be created to emulate different deformation of skin stress. The design of this soft robot will allow the attachment of scaffolds, which will then be mechanically actuated. This will provide a novel and highly adaptable platform for dynamic cell culture. Methods: Novel, low-cost soft robot is fabricated via 3D printed moulds and silicone. A low cost, electro-mechanical device was constructed to actuate the soft robot through the controlled combination of positive and negative air pressure to control the different state of movements. Mechanical tests were conducted to assess the performance and calibration of each electronic component. Similarly, pressure-displacement test was performed on scaffolds, which were attached to the soft robot, applying various mechanical loading regimes. Lastly, digital image correlation test was performed to obtain strain distributions over the soft robot’s surface. Results: The control system can control and stabilise positive pressure changes for long hours. Similarly, pressure-displacement test demonstrated that scaffolds with 5µm of diameter and wavy geometry can displace at 100%, applying a maximum pressure of 1.5 PSI. Lastly, during the inflation state, the displacement of silicone was measured using DIC method, and this showed a parameter of 4.78 mm and strain of 0.0652. Discussion And Conclusion: The developed soft robot system provides a novel and low-cost platform for the dynamic actuation of tissue scaffolds with a target towards dynamic cell culture.

Keywords: soft robot, tissue engineering, mechanical stimulation, dynamic cell culture, bioreactor

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Authors: Banu Pradheepa Kamarajan, Muthusamy Ananthasubramanian

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Biofilm forming Pseudomonads occupy the top third position in causing hospital acquired infections. P. aeruginosa is notoriously known for its tendency to develop drug resistance. Major classes of drug such as β-lactams, aminoglycosides, quinolones, and polymyxins are found ineffective against multi-drug resistance Pseudomonas. To combat the infections, rather than administration of a single antibiotic, use of combinations (tobramycin and essential oils from plants and/or silver nanoparticles, chitosan, nitric oxide, cis-2-decenoic acid) in single formulation are suggested to control P. aeruginosa biofilms. Conventional techniques to prevent hospital-acquired implant infections such as coatings with antibiotics, controlled release of antibiotics from the implant material, contact-killing surfaces, coating the implants with functional DNase I and, coating with glycoside hydrolase are being followed. Coatings with bioactive components besides having limited shelf-life, require cold-chain and, are likely to fail when bacteria develop resistance. Recently identified nano-scale physical architectures on the insect wings are expected to have potential bactericidal property. Nanopillars are bactericidal to Staphylococcus aureus, Bacillus subtilis, K. pnuemoniae and few species of Pseudomonas. Our study aims to investigate the survival rate of biofilm forming Pseudomonas aeruginosa strain over non-biofilm forming strain on the nanopillar architecture of dragonfly (Pantala flavescens) wing. Dragonflies were collected near house-hold areas and, insect identification was carried out by the Department of Entomology, Tamilnadu Agricultural University, Coimbatore, India. Two strains of P. aeruginosa such as PAO1 (potent biofilm former) and MTCC 1688 (non-weak biofilm former) were tested against the glass coverslip (control) and wings of dragonfly (test) for 48 h. The wings/glass coverslips were incubated with bacterial suspension in 48-well plate. The plates were incubated at 37 °C under static condition. Bacterial attachment on the nanopillar architecture of the wing surface was visualized using FESEM. The survival rate of P. aeruginosa was tested using colony counting technique and flow cytometry at 0.5 h, 1 h, 2 h, 7 h, 24 h, and 48 h post-incubation. Cell death was analyzed using propidium iodide staining and DNA quantification. The results indicated that the survival rate of non-biofilm forming P. aeruginosa is 0.2 %, whilst that of biofilm former is 45 % on the dragonfly wings at the end of 48 h. The reduction in the survival rate of biofilm and non-biofilm forming P. aeruginosa was 20% and 40% respectively on the wings compared to the glass coverslip. In addition, Fourier Transformed Infrared Radiation was used to study the modification in the surface chemical composition of the wing during bacterial attachment and, post-sonication. This result indicated that the chemical moieties are not involved in the bactericidal property of nanopillars by the conserved characteristic peaks of chitin pre and post-sonication. The nanopillar architecture of the dragonfly wing efficiently deters the survival of non-biofilm forming P. aeruginosa, but not the biofilm forming strain. The study highlights the ability of biofilm formers to survive on wing architecture. Understanding this survival strategy will help in designing the architecture that combats the colonization of biofilm forming pathogens.

Keywords: biofilm, nanopillars, Pseudomonas aeruginosa, survival rate

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Authors: Ayad Al-Mahturi, Herman Wahid

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This paper presents an optimal state feedback controller based on Linear Quadratic Regulator (LQR) for a two-rotor aero-dynamical system (TRAS). TRAS is a highly nonlinear multi-input multi-output (MIMO) system with two degrees of freedom and cross coupling. There are two parameters that define the behavior of LQR controller: state weighting matrix and control weighting matrix. The two parameters influence the performance of LQR. Particle Swarm Optimization (PSO) is proposed to optimally tune weighting matrices of LQR. The major concern of using LQR controller is to stabilize the TRAS by making the beam move quickly and accurately for tracking a trajectory or to reach a desired altitude. The simulation results were carried out in MATLAB/Simulink. The system is decoupled into two single-input single-output (SISO) systems. Comparing the performance of the optimized proportional, integral and derivative (PID) controller provided by INTECO, results depict that LQR controller gives a better performance in terms of both transient and steady state responses when PSO is performed.

Keywords: LQR controller, optimal control, particle swarm optimization (PSO), two rotor aero-dynamical system (TRAS)

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Authors: Lamia Bouzgarrou, Amira Omrane, Naima Bouatay, Chaima Harrathi, Samia Machroughl, Ahmed Mhalla

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Background and Aims: Professionals of health care sector are exposed to psychosocial constraints like stress, harassment, violence, which can lead to many mental health problems such as, depression, addictive behavior, and burn-out. Moreover, it’s well established that caregivers affected to intensive care units are more likely to experience such constraints and mental health problems. For these caregivers, the mental health state may affect care quality and patient’s safety. This study aims either to identify occupational psychosocial constraints and their mental health consequences among paramedical and medical caregivers affected to intensive units in Tunisian public hospital. Methods: An exhaustive three months cross-sectional study conducted among medical and paramedical staffs of intensive care units in three Tunisian university hospitals. After informed consent collection, we evaluated work-related stress, workplace harassment, depression, anxious troubles, addictive behavior, and self-esteems through an anonymous self-completed inquiry form. Five validated questionnaires and scales were included in this form: Karasek's Job Content Questionnaire, Negative Acts Questionnaire, Rosenberg, Beck depression inventory and Hamilton Anxiety scale. Results: We included 129 intensive unit caregivers; with a mean age of 36.1 ± 1.1 years and a sex ratio of 0.58. Among these caregivers, 30% were specialist or under-specialization doctors. The average seniority in the intensive care was 6.1 ± 1.2 (extremes=1 to 40 years). Atypical working schedules were noted among 36.7% of the subjects with an imposed choice in 52.4% of cases. During the last 12 months preceding the survey, 51.7% of care workers were absent from work because of a health problem with stops exceeding 15 days in 11.7%. Job strain was objective among 15% of caregivers and 38.33% of them were victims of moral harassment. A low or very low self-esteem was noted among 40% of respondents. Moreover, active smoking was reported by 20% subjects, alcohol consumption by 13.3% and psychotropic substance use by 1.7% of them. According to Beck inventory and Hamilton Anxiety scale, we concluded that 61.7% of intensive care providers were depressed, with 'severe' depression in 13.3% of cases and 49.9% of them present anxious disorders. Multivariate analysis objective that, job strain was correlated with young age (p=0.005) and shorter work seniority (p=0.001). Workplace and moral harassment was more prevalent among females (p=0.009), under-specialization doctor (p=0.021), those affected to atypical schedules (p=0.008). Concerning depression, it was more prevalent among staff in job strain situation (p = 0.004), among smokers caregivers (p = 0.048), and those with no leisure activity (p < 0.001). Anxious disorders were positively correlated to chronic diseases history (p = 0.001) and work-bullying exposure (p = 0.004). Conclusions: Our findings reflected a high frequency of caregivers who are under stress at work and those who are victims of moral harassment. These health professionals were at increased risk for developing psychiatric illness such depressive and anxious disorders and addictive behavior. Our results suggest the necessity of preventive strategies of occupational psychosocial constraints in order to preserve professional’s mental health and maximize patient safety and quality of care.

Keywords: health care sector, intensive care units, mental health, psychosocial constraints

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Authors: Samir Lecheb, Ahmed Chellil, Hamza Mechakra, Brahim Safi, Houcine Kebir

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In this paper we studied fracture and dynamic behavior of vertical axis wind turbine blade, the VAWT is a historical machine, it has many properties, structure, advantage, component to be able to produce the electricity. We modeled the blade design then imported to Abaqus software for analysis the modes shapes, frequencies, stress, strain, displacement and stress intensity factor SIF, after comparison we chose the idol material. Finally, the CTS test of glass epoxy reinforced polymer plates to obtain the material fracture toughness Kc.

Keywords: blade, crack, frequency, material, SIF

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Authors: Osman Adiguzel

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Shape memory alloys take place in a class of smart materials by exhibiting a peculiar property called the shape memory effect. This property is characterized by the recoverability of two certain shapes of material at different temperatures. These materials are often called smart materials due to their functionality and their capacity of responding to changes in the environment. Shape memory materials are used as shape memory devices in many interdisciplinary fields such as medicine, bioengineering, metallurgy, building industry and many engineering fields. The shape memory effect is performed thermally by heating and cooling after first cooling and stressing treatments, and this behavior is called thermoelasticity. This effect is based on martensitic transformations characterized by changes in the crystal structure of the material. The shape memory effect is the result of successive thermally and stress-induced martensitic transformations. Shape memory alloys exhibit thermoelasticity and superelasticity by means of deformation in the low-temperature product phase and high-temperature parent phase region, respectively. Superelasticity is performed by stressing and releasing the material in the parent phase region. Loading and unloading paths are different in the stress-strain diagram, and the cycling loop reveals energy dissipation. The strain energy is stored after releasing, and these alloys are mainly used as deformation absorbent materials in control of civil structures subjected to seismic events, due to the absorbance of strain energy during any disaster or earthquake. Thermal-induced martensitic transformation occurs thermally on cooling, along with lattice twinning with cooperative movements of atoms by means of lattice invariant shears, and ordered parent phase structures turn into twinned martensite structures, and twinned structures turn into the detwinned structures by means of stress-induced martensitic transformation by stressing the material in the martensitic condition. Thermal induced transformation occurs with the cooperative movements of atoms in two opposite directions, <110 > -type directions on the {110} - type planes of austenite matrix which is the basal plane of martensite. Copper-based alloys exhibit this property in the metastable β-phase region, which has bcc-based structures at high-temperature parent phase field. Lattice invariant shear and twinning is not uniform in copper-based ternary alloys and gives rise to the formation of complex layered structures, depending on the stacking sequences on the close-packed planes of the ordered parent phase lattice. In the present contribution, x-ray diffraction and transmission electron microscopy (TEM) studies were carried out on two copper-based CuAlMn and CuZnAl alloys. X-ray diffraction profiles and electron diffraction patterns reveal that both alloys exhibit superlattice reflections inherited from the parent phase due to the displacive character of martensitic transformation. X-ray diffractograms taken in a long time interval show that diffraction angles and intensities of diffraction peaks change with the aging duration at room temperature. In particular, some of the successive peak pairs providing a special relation between Miller indices come close to each other. This result refers to the rearrangement of atoms in a diffusive manner.

Keywords: shape memory effect, martensitic transformation, reversibility, superelasticity, twinning, detwinning

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Authors: Waheed Ahmad Safi, Shunichi Nakamura

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Concrete filled steel I-girder (CFIG) bridge was proposed and the bending and shear strength was confirmed by experiments. The area surrounded by the upper and lower flanges and the web is filled with concrete in CFIG, which is used to the intermediate support of a continuous girder. Three-dimensional finite element models were established to simulate the bending and shear behaviors of CFIG and to clarify the load transfer mechanism. Steel plates and filled concrete were modeled as a three-dimensional 8-node solid element and steel reinforcement bars as a three-dimensional 2-node truss element. The elements were mostly divided into the 50 x 50 mm mesh size. The non-linear stress-strain relation is assumed for concrete in compression including the softening effect after the peak, and the stress increases linearly for concrete in tension until concrete cracking but then decreases due to tension stiffening effect. The stress-strain relation for steel plates was tri-linear and that for reinforcements was bi-linear. The concrete and the steel plates were rigidly connected. The developed FEM model was applied to simulate and analysis the bending behaviors of the CFIG specimens. The vertical displacements and the strains of steel plates and the filled concrete obtained by FEM agreed very well with the test results until the yield load. The specimens collapsed when the upper flange buckled or the concrete spalled off. These phenomena cannot be properly analyzed by FEM, which produces a small discrepancy at the ultimate states. The FEM model was also applied to simulate and analysis the shear tests of the CFIG specimens. The vertical displacements and strains of steel and concrete calculated by FEM model agreed well with the test results. A truss action was confirmed by the FEM and the experiment, clarifying that shear forces were mainly resisted by the tension strut of the steel plate and the compression strut of the filled concrete acting in the diagonal direction. A trail design with the CFIG was carried out for a four-span continuous highway bridge and the design method was established. Construction cost was estimated about 12% lower than that of a conventional steel I-section girder.

Keywords: concrete filled steel I-girder, bending strength, FEM, limit states design, steel I-girder, shear strength

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Authors: Ali M. Elgerbi, Obied A. Alwan, Al-Taher O. Alzwei, Abdurrahim A. Elouzi

Abstract:

The binding of AFM1 to bacteria in phosphate buffer solution depended on many factors such as: availability of energy, incubation period, species and strain of bacteria. Increase in concentration of sugar showed higher removal of AFM1 and faster than in phosphate buffer alone. With 1.0% glucose lactic acid bacteria and bifidobacteria showed toxin removal ranging from 7.7 to 39.7% whereas with 10.0% glucose the percentage removal was 21.8 to 45.4% at 96 hours of incubation.

Keywords: aflatoxin M1, lactic acid bacteria, bifidobacteria , binding, phosphate buffer

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Authors: Jiwuer Jilili, Ulrich Eckern, Udo Schwingenschlogl

Abstract:

We present first principles results for the electronic, magnetic, and optical properties of the BiFeO3 /La2/3Sr1/3MnO3 heterostructure as obtained by spin polarized calculations using density functional theory. The electronic states of the heterostructure are compared to those of the bulk compounds. Structural relaxation turns out to have only a minor impact on the chemical bonding, even though the oxygen octahedra in La2/3Sr1/3MnO3 develop some distortions due to the interface strain. While a small charge transfer affects the heterointerfaces, our results demonstrate that the half-metallic character of La2/3Sr1/3MnO3 is fully maintained.

Keywords: BiFeO3, La2/3Sr1/3MnO3, superlattice, half-metallicity

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Authors: Samuel Nii Tackie, Oyebade K. Oyedotun, Ebenezer O. Olaniyi, Adnan Khashman

Abstract:

Artificial neural networks have been used in different fields of artificial intelligence, and more specifically in machine learning. Although, other machine learning options are feasible in most situations, but the ease with which neural networks lend themselves to different problems which include pattern recognition, image compression, classification, computer vision, regression etc. has earned it a remarkable place in the machine learning field. This research exploits neural networks as a data mining tool in predicting the number of times a student repeats a course, considering some attributes relating to the course itself, the teacher, and the particular student. Neural networks were used in this work to map the relationship between some attributes related to students’ course assessment and the number of times a student will possibly repeat a course before he passes. It is the hope that the possibility to predict students’ performance from such complex relationships can help facilitate the fine-tuning of academic systems and policies implemented in learning environments. To validate the power of neural networks in data mining, Turkish students’ performance database has been used; feedforward and radial basis function networks were trained for this task; and the performances obtained from these networks evaluated in consideration of achieved recognition rates and training time.

Keywords: artificial neural network, data mining, classification, students’ evaluation

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Authors: Joseph Fitoussi, Mohammadali Shirinbayan, Abbas Tcharkhtchi

Abstract:

Due to material flow during processing, short fiber reinforced composites structures obtained by injection or compression molding generally present strong spatial microstructure variation. On the other hand, quasi-static, dynamic, and fatigue behavior of these materials are highly dependent on microstructure parameters such as fiber orientation distribution. Indeed, because of complex damage mechanisms, SFRC structures design is a key challenge for safety and reliability. In this paper, we propose a micromechanical model allowing prediction of damage behavior of real structures as a function of microstructure spatial distribution. To this aim, a statistical damage criterion including strain rate and fatigue effect at the local scale is introduced into a Mori and Tanaka model. A critical local damage state is identified, allowing fatigue life prediction. Moreover, the multi-scale model is coupled with an experimental intrinsic link between damage under monotonic loading and fatigue life in order to build an abacus giving Tsai-Wu failure criterion parameters as a function of microstructure and targeted fatigue life. On the other hand, the micromechanical damage model gives access to the evolution of the anisotropic stiffness tensor of SFRC submitted to complex thermomechanical loading, including quasi-static, dynamic, and cyclic loading with temperature and amplitude variations. Then, the latter is used to fill out microstructure dependent material cards in finite element analysis for design optimization in the case of complex loading history. The proposed methodology is illustrated in the case of a real automotive component made of sheet molding compound (PSA 3008 tailgate). The obtained results emphasize how the proposed micromechanical methodology opens a new path for the automotive industry to lighten vehicle bodies and thereby save energy and reduce gas emission.

Keywords: short fiber reinforced composite, structural design, damage, micromechanical modelling, fatigue, strain rate effect

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Authors: Yoshie Asahara, Hidekuni Takao

Abstract:

Non-invasive positive pressure ventilation (NPPV), a type of ventilation therapy, is a treatment in which a mask is attached to the patient's face and delivers gas into the mask to support breathing. The NPPV mask uses a strap, which is necessary to attach and secure the mask in the appropriate facial position, but the tensile strength of the strap is adjusted by the sensation of the hands. The strap uniformity and fine-tuning strap tension are judged by the skill of the operator and the amount felt by the finger. In the future, additional strap operation and adjustment methods will be required to meet the needs for reducing the burden on the patient’s face. In this study, we fabricated a mechanism that can measure, adjust and fix the tension of the straps. A small amount of strap tension can be adjusted by rotating the shaft. This makes it possible to control the slight strap tension that is difficult to grasp with the sense of the operator's hand. In addition, this mechanism allows the operator to control the strap while controlling the movement of the mask body. This leads to the establishment of a suitable mask fitting method for each patient. The developed mechanism enables the operation and fine reproducible adjustment of the strap tension and the mask balance, reducing the burden on the face.

Keywords: balance of the mask strap, fine adjustment, film sensor, mask fitting technique, mask strap tension

Procedia PDF Downloads 223

Authors: Atilla Bayram

Abstract:

This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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Authors: Michael Tupý, Alice Tesaříková-Svobodová, Dagmar Měřínská, Vít Petránek

Abstract:

Polyethylene (PE), Polypropylene (PP), Polyethylene (vinyl acetate) (EVA) and Surlyn (modif-PE) nano composite samples were prepared with montmorillonite fillers Cloisite 93A and Dellite 67G. The amount of modified Na+ montmorillonite (MMT) was fixed to 5 % (w/w). For the compounding of polymer matrix and chosen nano fillers twin-screw kneader was used. The level of MMT intercalation or exfoliation in the nano composite systems was studied by transmission electron microscopy (TEM) observations. The properties of samples were evaluated by dynamical mechanical analysis (E* modulus at 30 °C) and by the measurement of tensile properties (stress and strain at break).

Keywords: polyethylene, polypropylene, polyethylene(vinyl acetate), clay, nanocomposite, montmorillonite

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Authors: Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang

Abstract:

2016 has become the year of the Artificial Intelligence explosion. AI technologies are getting more and more matured that most world well-known tech giants are making large investment to increase the capabilities in AI. Machine learning is the science of getting computers to act without being explicitly programmed, and deep learning is a subset of machine learning that uses deep neural network to train a machine to learn  features directly from data. Deep learning realizes many machine learning applications which expand the field of AI. At the present time, deep learning frameworks have been widely deployed on servers for deep learning applications in both academia and industry. In training deep neural networks, there are many standard processes or algorithms, but the performance of different frameworks might be different. In this paper we evaluate the running performance of two state-of-the-art distributed deep learning frameworks that are running training calculation in parallel over multi GPU and multi nodes in our cloud environment. We evaluate the training performance of the frameworks with ResNet-50 convolutional neural network, and we analyze what factors that result in the performance among both distributed frameworks as well. Through the experimental analysis, we identify the overheads which could be further optimized. The main contribution is that the evaluation results provide further optimization directions in both performance tuning and algorithmic design.

Keywords: artificial intelligence, machine learning, deep learning, convolutional neural networks

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Authors: Manoj M. Sarode, Sharad P. Jadhav, Mukesh D. Patil, Pushparaj S. Suryawanshi

Abstract:

Even though the PID controller is widely used in industrial process, tuning of PID parameters are not easy. It is a time consuming and requires expert people. Another drawback of PID controller is that process dynamics might change over time. This can happen due to variation of the process load, normal wear and tear etc. To compensate for process behavior change over time, expert users are required to recalibrate the PID gains. Implementation of model based controllers usually needs a process model. Identification of process model is time consuming job and no guaranty of model accuracy. If the identified model is not accurate, performance of the controller may degrade. Model based controllers are quite expensive and the whole procedure for the implementation is sometimes tedious. To eliminate such issues Autotuning PID controller becomes vital element. Software based Relay Feedback Autotuning Controller proves to be efficient, upgradable and maintenance free controller. In Relay Feedback Autotune controller PID parameters can be achieved with a very short span of time. This paper presents the real time implementation of LabVIEW based Relay Feedback Autotuning PID controller. It is successfully developed and implemented to control level of a laboratory setup. Its performance is analyzed for different setpoints and found satisfactorily.

Keywords: autotuning, PID, liquid level control, recalibrate, labview, controller

Procedia PDF Downloads 381

Authors: Mohamed I. Mahrous, Mohamed G. Ashmawy

Abstract:

Hybrid genetic algorithm (HGA) is proposed in this paper to determine the economic scheduling of electric power generation over a fixed time period under various system and operational constraints. The proposed technique can outperform conventional genetic algorithms (CGAs) in the sense that HGA make it possible to improve both the quality of the solution and reduce the computing expenses. In contrast, any carefully designed GA is only able to balance the exploration and the exploitation of the search effort, which means that an increase in the accuracy of a solution can only occure at the sacrifice of convergent speed, and vice visa. It is unlikely that both of them can be improved simultaneously. The proposed hybrid scheme is developed in such a way that a simple GA is acting as a base level search, which makes a quick decision to direct the search towards the optimal region, and a local search method (pattern search technique) is next employed to do the fine tuning. The aim of the strategy is to achieve the cost reduction within a reasonable computing time. The effectiveness of the proposed hybrid technique is verified on two real public electricity supply systems with 13 and 40 generator units respectively. The simulation results obtained with the HGA for the two real systems are very encouraging with regard to the computational expenses and the cost reduction of power generation.

Keywords: genetic algorithms, economic dispatch, pattern search

Procedia PDF Downloads 429