Search results for: compound parameter value

Authors: Motahar Reza, Rajni Chahal, Neha Sharma

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This article addresses the boundary layer flow and heat transfer of Casson fluid over a nonlinearly permeable stretching surface with chemical reaction in the presence of variable magnetic field. The effect of thermal radiation is considered to control the rate of heat transfer at the surface. Using similarity transformations, the governing partial differential equations of this problem are reduced into a set of non-linear ordinary differential equations which are solved by finite difference method. It is observed that the velocity at fixed point decreases with increasing the nonlinear stretching parameter but the temperature increases with nonlinear stretching parameter.

Keywords: boundary layer flow, nonlinear stretching, Casson fluid, heat transfer, radiation

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Authors: Muhammad Mustaqeem, Musa Kaleem Baloch, Irfan Ullah, Ammarah Luqman, Afshan Ahmad

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Flurbiprofen is one of the most potent nonsteroidal anti-inflammatory drugs. It is widely used for relief of pain in patients suffering from rheumatic diseases, migraine, sore throat and primary dysmenorrhea. However, its aqueous solubility is very low and hinders the skin permeation. Thus, it is imperative to develop such a drug delivery systems which can improve its aqueous solubility and hence improve the skin permeation and therapeutic compliance. Microemulsions have been also proven to increase the cutaneous absorption of lipophilic drugs as compared to conventional vehicles. Micro-emulsion is thermodynamically stable emulsion that has the capacity to ‘hide/solubilize’ water-insoluble molecules within a continuous oil phase. Therefore, flurbiprofen was converted to Easters through chemical reactions with alcohols such as methanol, ethanol, propanol and butanol. The product was further treated with hydrazine to get hydrazide. The solubility of the parent drug Flurbiprofen and the products were solubilized in microemulsions formed using various surfactants like ionic, non-ionic and zwitterions. It has been concluded that the product was more soluble than the parent compound. The biological activities of these were also investigated. The outcome was very promising and the product was more active than the parent compound. It, therefore, concluded that in this way, we can not only enhance the solubility of the drug and increase its bioactivity, but also reduce the risk of stomach cancer.

Keywords: Flurbiprofen, microemulsion, surfactants, hyrazides

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Authors: Ali Akbar Heydari

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Control charts are an important tool of statistical quality control. Thesecharts are used to detect and eliminate unwanted special causes of variation that occurred during aperiod of time. The design and operation of control charts require the determination of three design parameters: the sample size (n), the sampling interval (h), and the width coefficient of control limits (k). Thevariable parameters (VP) x-bar controlchart is the x-barchart in which all the design parameters vary between twovalues. These values are a function of the most recent process information. In fact, in the VP x-bar chart, the position of each sample point on the chart establishes the size of the next sample and the timeof its sampling. The synthetic x-barcontrol chartwhich integrates the x-bar chart and the conforming run length (CRL) chart, provides significant improvement in terms of detection power over the basic x-bar chart for all levels of mean shifts. In this paper, we introduce the syntheticVP x-bar control chart for monitoring changes in the process mean. To determine the design parameters, we used a statistical design based on the minimum out of control average run length (ARL) criteria. The optimal chart parameters of the proposed chart are obtained using the Markov chain approach. A numerical example is also done to show the performance of the proposed chart and comparing it with the other control charts. The results show that our proposed syntheticVP x-bar controlchart perform better than the synthetic x-bar controlchart for all shift parameter values. Also, the syntheticVP x-bar controlchart perform better than the VP x-bar control chart for the moderate or large shift parameter values.

Keywords: control chart, markov chain approach, statistical design, synthetic, variable parameter

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Authors: Jer Ping Ooi, Shah Rizal Bin Kasim, Nor Aini Saidin

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The objective of this study was to synthesize nano-sized β-tricalcium phosphate (β-TCP) powder and assess its cytotoxic effects on human osteoblast (hFOB1.19) by using four cytotoxicity assays, namely, lactose dehydrogenase (LDHe), tetrazolium hydroxide (XTT), neutral red (NR), and sulforhodamine B (SRB) assays. β-tricalcium phosphate (β-TCP) is a calcium phosphate compound commonly used as an implant material. To date, bulk-sized β-TCP is reported to be readily tolerated by the osteogenic cells and body based on in vitro, in vivo experiments and clinical studies. However, to what extent of nano-sized β-TCP will react in models as compared to bulk β-TCP is yet to be investigated. Thus, in this project, the cells were treated with nano β-TCP powder within a range of concentrations from 0 to 1000 μg/mL for 24, 48, and 72 h. The cytotoxicity tests showed that loss of cell viability ( > 50%) was high for hFOB1.19 cells in all assays. Cell cycle and apoptosis analysis of hFOB1.19 cells revealed that 50 μg/mL of the compound led to 30.5% of cells being apoptotic after 72 h of incubation, and the percentage was increased to 58.6% when the concentration was increased to 200 μg/mL. When the incubation time was increased from 24 to 72 h, the percentage of apoptotic cells increased from 17.3% to 58.6% when the hFOB1.19 were exposed with 200 μg/mL of nano β-TCP powder. Thus, both concentration and exposure duration affected the cytotoxicity effects of the nano β-TCP powder on hFOB1.19. We hypothesize that these cytotoxic effects on hFOB1.19 are related to the nano-scale size of the β-TCP.

Keywords: β-tricalcium phosphate, hFOB1.19, adipose-derived mesenchymal stem cells, cytotoxicity

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Authors: E. E. S. Uy, T. Noda, K. Nakai, J. R. Dungca

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Cyclic threshold shear strain is the cyclic shear strain amplitude that serves as the indicator of the development of pore water pressure. The parameter can be obtained by performing either cyclic triaxial test, shaking table test, cyclic simple shear or resonant column. In a cyclic triaxial test, other researchers install measuring devices in close proximity of the soil to measure the parameter. In this study, an attempt was made to estimate the cyclic threshold shear strain parameter using full-field measurement technique. The technique uses a camera to monitor and measure the movement of the soil. For this study, the technique was incorporated in a strain-controlled consolidated undrained cyclic triaxial test. Calibration of the camera was first performed to ensure that the camera can properly measure the deformation under cyclic loading. Its capacity to measure deformation was also investigated using a cylindrical rubber dummy. Two-dimensional image processing was implemented. Lucas and Kanade optical flow algorithm was applied to track the movement of the soil particles. Results from the full-field measurement technique were compared with the results from the linear variable displacement transducer. A range of values was determined from the estimation. This was due to the nonhomogeneous deformation of the soil observed during the cyclic loading. The minimum values were in the order of 10-2% in some areas of the specimen.

Keywords: cyclic loading, cyclic threshold shear strain, full-field measurement, optical flow

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Authors: Xiang Wang

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In order to validate the efficiency of recognizing the damage initiation and development of a concrete beam using acoustic emission technology, a concrete beam is built and tested in the laboratory. The acoustic emission signals are analyzed based on both parameter and wave information, which is also compared with the beam deflection measured by displacement sensors. The results indicate that using acoustic emission technology can detect damage initiation and development effectively, especially in the early stage of the damage development, which can not be detected by the common monitoring technology. Furthermore, the positioning of the damage based on the acoustic emission signals can be proved to be reasonable. This job can be an important attempt for the future long-time monitoring of the real concrete structure.

Keywords: acoustic emission technology, concrete beam, parameter analysis, wave analysis, positioning

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Authors: Shuafeng Yuan, Bojian Zheng

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The RNA-dependent RNA polymerase of influenza a virus comprises conserved and independently folded subdomains with defined functionalities. The N-terminal domain of the PA subunit (PAN) harbors the endonuclease function so that it can serve as a desired target for drug discovery. To identify a class of anti-influenza inhibitors that impedes PAN endonuclease activity, a screening approach that integrated the fluorescence resonance energy transfer based endonuclease inhibitor assay with the DNA gel-based endonuclease inhibitor assay was conducted, followed by the evaluation of antiviral efficacies and potential cytotoxicity of the primary hits in vitro and in vivo. A small-molecule compound ANA-0 was identified as a potent inhibitor against the replication of multiple subtypes of influenza A virus, including H1N1, H3N2, H5N1, H7N7, H7N9 and H9N2, in cell cultures. Combinational treatment of zanamivir and ANA-0 exerted synergistic anti-influenza effect in vitro. Intranasal administration of ANA-0 protected mice from lethal challenge and reduced lung viral loads in H1N1 virus infected BALB/c mice. Docking analyses predicted ANA-0 bound the endonuclease cavity of PAN by interacting with the metal-binding and catalytic residues. In summary, ANA-0 shows potential to be developed to novel anti-influenza agents.

Keywords: anti-influenza, novel compound, inhibition of endonuclease, PA

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Authors: Bao Li, Aike Qiao, Gaoyang Li, Youjun Liu

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Background: Lumped parameter model (LPM) is a common numerical model for hemodynamic calculation. LPM uses circuit elements to simulate the human blood circulatory system. Physiological indicators and characteristics can be acquired through the model. However, due to the different physiological indicators of each individual, parameters in LPM should be personalized in order for convincing calculated results, which can reflect the individual physiological information. This study aimed to develop an automatic and effective optimization method to personalize the parameters in LPM of the blood circulatory system, which is of great significance to the numerical simulation of individual hemodynamics. Methods: A closed-loop LPM of the human blood circulatory system that is applicable for most persons were established based on the anatomical structures and physiological parameters. The patient-specific physiological data of 5 volunteers were non-invasively collected as personalized objectives of individual LPM. In this study, the blood pressure and flow rate of heart, brain, and limbs were the main concerns. The collected systolic blood pressure, diastolic blood pressure, cardiac output, and heart rate were set as objective data, and the waveforms of carotid artery flow and ankle pressure were set as objective waveforms. Aiming at the collected data and waveforms, sensitivity analysis of each parameter in LPM was conducted to determine the sensitive parameters that have an obvious influence on the objectives. Simulated annealing was adopted to iteratively optimize the sensitive parameters, and the objective function during optimization was the root mean square error between the collected waveforms and data and simulated waveforms and data. Each parameter in LPM was optimized 500 times. Results: In this study, the sensitive parameters in LPM were optimized according to the collected data of 5 individuals. Results show a slight error between collected and simulated data. The average relative root mean square error of all optimization objectives of 5 samples were 2.21%, 3.59%, 4.75%, 4.24%, and 3.56%, respectively. Conclusions: Slight error demonstrated good effects of optimization. The individual modeling algorithm developed in this study can effectively achieve the individualization of LPM for the blood circulatory system. LPM with individual parameters can output the individual physiological indicators after optimization, which are applicable for the numerical simulation of patient-specific hemodynamics.

Keywords: blood circulatory system, individual physiological indicators, lumped parameter model, optimization algorithm

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Authors: Abubaker A. Yousif, Muhamad S. Yasir

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The Effectiveness of lower doses of high-LET radiations is not accurately determined by using energy-based physical parameters such as absorbed dose and radio-sensitivity parameters. Therefore, an attempt has been carried out in this research to propose alternative parameter that capable to quantify the effectiveness of these high LET radiations at lower doses regions. The linear energy transfer and mean free path are employed to achieve this objective. A new mathematical form of the effectiveness of high-LET radiations at lower doses region has been formulated. Based on this parameter, the optimized effectiveness of high-LET radiations occurs when the energy of charged particles is deposited at spacing of 2 nm for primary ionization.

Keywords: effectiveness, low dose, radiation mean free path, linear energy transfer

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Authors: Lokesh Soni, Sushanta Kumar Sethi, Gaurav Manik

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This work attempts to use molecular simulations to create equilibrated structures of a range of commercially used polymers. Generated equilibrated structures for polyvinyl acetate (isotactic), polyvinyl alcohol (atactic), polystyrene, polyethylene, polyamide 66, poly dimethyl siloxane, poly carbonate, poly ethylene oxide, poly amide 12, natural rubber, poly urethane, and polycarbonate (bisphenol-A) and poly ethylene terephthalate are employed to estimate the correct chain length that will correctly predict the chain parameters and properties. Further, the equilibrated structures are used to predict some properties like density, solubility parameter, cohesive energy density, surface energy, and Flory-Huggins interaction parameter. The simulated densities for polyvinyl acetate, polyvinyl alcohol, polystyrene, polypropylene, and polycarbonate are 1.15 g/cm3, 1.125 g/cm3, 1.02 g/cm3, 0.84 g/cm3 and 1.223 g/cm3 respectively are found to be in good agreement with the available literature estimates. However, the critical repeating units or the degree of polymerization after which the solubility parameter showed saturation were 15, 20, 25, 10 and 20 respectively. This also indicates that such properties that dictate the miscibility of two or more polymers in their blends are strongly dependent on the chosen polymer or its characteristic properties. An attempt has been made to correlate such properties with polymer properties like Kuhn length, free volume and the energy term which plays a vital role in predicting the mentioned properties. These results help us to screen and propose a useful library which may be used by the research groups in estimating the polymer properties using the molecular simulations of chains with the predicted critical lengths. The library shall help to obviate the need for researchers to spend efforts in finding the critical chain length needed for simulating the mentioned polymer properties.

Keywords: Kuhn length, Flory Huggins interaction parameter, cohesive energy density, free volume

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Authors: Aicha Bouhlala, Sabah Chettibi

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A systematic investigation on structural, electronic, and magnetic properties of Ce₀.₇₅A₀.₂₅O₂ (A = W, Mo) is performed using first-principles calculations within the framework Full-Potential Linear Augmented Plane Wave (FP-LAPW) method based on the Density Functional Theory (DFT). The exchange-correlation potential has been treated using the generalized gradient approximation (WC-GGA) developed by Wu-Cohen. The host compound CeO2 was doped with transition metal atoms W and Mo in the doping concentration of 25% to replace the Ce atom. In structural properties, the equilibrium lattice constant is observed for the W-doped CeO₂ compound which exists within the value of 5.314 A° and the value of 5.317 A° for Mo-doped CeO2. The present results show that Ce₀.₇₅A₀.₂₅O₂ (A=W, Mo) systems exhibit semiconducting behavior in both spin channels. Although undoped CeO₂ is a non-magnetic semiconductor. The band structure of these doped compounds was plotted and they exhibit direct band gap at the Fermi level (EF) in the majority and minority spin channels. In the magnetic properties, the doped atoms W and Mo play a vital role in increasing the magnetic moments of the supercell and the values of the total magnetic moment are found to be 1.998 μB for Ce₀.₇₅W₀.₂₅O₂ and to be 2.002 μB for Ce₀.₇₅Mo₀.₂₅O₂ compounds. Calculated results indicate that the magneto-electronic properties of the Ce₁₋ₓAₓO₂(A= W, Mo) oxides supply a new way to the experimentalist for the potential applications in spintronics devices.

Keywords: FP-LAPW, DFT, CeO₂, properties

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Authors: M. Bouferhane, A. Boukhebza, L. Hatab

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In this paper, the position control of linear induction motor using fuzzy sliding mode controller design is proposed. First, the indirect field oriented control LIM is derived. Then, a designed sliding mode control system with an integral-operation switching surface is investigated, in which a simple adaptive algorithm is utilized for generalised soft-switching parameter. Finally, a fuzzy sliding mode controller is derived to compensate the uncertainties which occur in the control, in which the fuzzy logic system is used to dynamically control parameter settings of the SMC control law. The effectiveness of the proposed control scheme is verified by numerical simulation. The experimental results of the proposed scheme have presented good performances compared to the conventional sliding mode controller.

Keywords: linear induction motor, vector control, backstepping, fuzzy-sliding mode control

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Authors: K. Jithendra Gowd, Ch. Sai Babu, S. Sivanagaraju

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Electric power systems are daily exposed to service interruption mainly due to faults and human accidental interference. Short circuit currents are responsible for several types of disturbances in power systems. The fault currents are high and the voltages are reduced at the time of fault. This paper presents two suitable methods, consideration of fault resistance and Distributed Generator are implemented and analyzed for the enhancement of voltage profile during fault conditions. Fault resistance is a critical parameter of electric power systems operation due to its stochastic nature. If not considered, this parameter may interfere in fault analysis studies and protection scheme efficiency. The effect of Distributed Generator is also considered. The proposed methods are tested on the IEEE 37 bus test systems and the results are compared.

Keywords: distributed generation, electrical distribution systems, fault resistance

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Authors: Gulshan Mammadova

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This paper presents the results of studying the surface microrelief in 2D and 3D models and analyzing the spectroscopy of a three-junction TlInSe₂ crystal. Analysis of the results obtained showed that with a change in the composition of the TlInSe₂ crystal, sharp changes occur in the microrelief of its surface. An X-ray optical diffraction analysis of the TlInSe₂ crystal was experimentally carried out. Based on ellipsometric data, optical functions were determined - the real and imaginary parts of the dielectric permittivity of crystals, the coefficients of optical absorption and reflection, the dependence of energy losses and electric field power on the effective density, the spectral dependences of the real (σᵣ) and imaginary (σᵢ) parts, optical electrical conductivity were experimentally studied. The fluorescence spectra of the ternary compound TlInSe₂ were isolated and analyzed when excited by light with a wavelength of 532 nm. X-ray studies of TlInSe₂ showed that this phase crystallizes into tetragonal systems. Ellipsometric measurements showed that the real (ε₁) and imaginary (ε₂) parts of the dielectric constant are components of the dielectric constant tensor of the uniaxial joints under consideration and do not depend on the angle. Analysis of the dependence of the real and imaginary parts of the refractive index of the TlInSe₂ crystal on photon energy showed that the nature of the change in the real and imaginary parts of the dielectric constant does not differ significantly. When analyzing the spectral dependences of the real (σr) and imaginary (σi) parts of the optical electrical conductivity, it was noticed that the real part of the optical electrical conductivity increases exponentially in the energy range 0.894-3.505 eV. In the energy range of 0.654-2.91 eV, the imaginary part of the optical electrical conductivity increases linearly, reaches a maximum value, and decreases at an energy of 2.91 eV. At 3.6 eV, an inversion of the imaginary part of the optical electrical conductivity of the TlInSe₂ compound is observed. From the graphs of the effective power density versus electric field energy losses, it is known that the effective power density increases significantly in the energy range of 0.805–3.52 eV. The fluorescence spectrum of the ternary compound TlInSe₂ upon excitation with light with a wavelength of 532 nm has been studied and it has been established that this phase has luminescent properties.

Keywords: optical properties, dielectric permittivity, real and imaginary dielectric permittivity, optical electrical conductivity

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Authors: Michael A. Sprayberry, Vincent C. Paquit

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Process parameter optimization in metal powder bed electron beam melting (MPBEBM) is crucial to ensure the technology's repeatability, control, and industry-continued adoption. Despite continued efforts to address the challenges via the traditional design of experiments and process mapping techniques, there needs to be more successful in an on-the-fly optimization framework that can be adapted to MPBEBM systems. Additionally, data-intensive physics-based modeling and simulation methods are difficult to support by a metal AM alloy or system due to cost restrictions. To mitigate the challenge of resource-intensive experiments and models, this paper introduces a Multi-Objective Reinforcement Learning (MORL) methodology defined as an optimization problem for MPBEBM. An off-policy MORL framework based on policy gradient is proposed to discover optimal sets of beam power (P) – beam velocity (v) combinations to maintain a steady-state melt pool depth and phase transformation. For this, an experimentally validated Eagar-Tsai melt pool model is used to simulate the MPBEBM environment, where the beam acts as the agent across the P – v space to maximize returns for the uncertain powder bed environment producing a melt pool and phase transformation closer to the optimum. The culmination of the training process yields a set of process parameters {power, speed, hatch spacing, layer depth, and preheat} where the state (P,v) with the highest returns corresponds to a refined process parameter mapping. The resultant objects and mapping of returns to the P-v space show convergence with experimental observations. The framework, therefore, provides a model-free multi-objective approach to discovery without the need for trial-and-error experiments.

Keywords: additive manufacturing, metal powder bed fusion, reinforcement learning, process parameter optimization

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Authors: Tengku Muhammad Rafi Nazmi Bin Tengku Razali, Habsah Alwi

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This article based on effect of temperature towards extraction of Aquilaria Subintegra. Aquilaria Subintegra which its main habitat is in Asia-tropical and particularly often found in its native which is Thailand. There is claim which is Aquilaria Subintegra contains antipyretic properties that helps fight fever. Research nowadays also shown that paracetamol consumed bring bad effect towards consumers. This sample will first dry using Vacuum Far Infrared which provides better drying than conventional oven. Soxhlet extractor used to extract oil from sample. Gas Chromatography Mass Spectrometer used to analyze sample to determine its compound. Objective from this research was to determine the active ingredients that exist in the Aquilaria Subintegra leaves and to determine whether compound of Acetaminophen exist or not inside the leaves. Moisture content from 400C was 80%, 500C was 620% and 600C was 36%. The greater temperature resulting lower moisture content inside sample leaves. 7 components were identified in sample T=400C while only 5 components were identified in sample at T=50C and T=60C. Four components were commonly identified in three sample which is 1n-Hexadecanoic acid, 9,12,15-Octadecatrienoic acid, methyl ester (z,z,z), Vitamin E and Squalene. Further studies are needed with new series of temperature to refine the best results.

Keywords: aquilaria subintegra, vacuum far infrared, SOXHLET extractor, gas chromatography mass spectrometer, paracetamol

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Authors: Geetika Vajpayee, Sugandha Asthana, Pratibha Kumari, Shanthy Sundaram

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Pseudomonas species possess a variety of promising properties of antifungal and growth promoting activities in the wheat plant. In the present study, Pseudomonas fluorescens MTCC-9768 is tested against plant pathogenic fungus Tilletia indica, causing Karnal bunt, a quarantine disease of wheat (Triticum aestivum) affecting kernels of wheat. It is one of the 1/A1 harmful diseases of wheat worldwide under EU legislation. This disease develops in the growth phase by the spreading of microscopically small spores of the fungus (teliospores) being dispersed by the wind. The present chemical fungicidal treatments were reported to reduce teliospores germination, but its effect is questionable since T. indica can survive up to four years in the soil. The fungal growth inhibition tests were performed using Dual Culture Technique, and the results showed inhibition by 82.5%. The interaction of antagonist bacteria-fungus causes changes in the morphology of hyphae, which was observed using Lactophenol cotton blue staining and Scanning Electron Microscopy (SEM). The rounded and swollen ends, called ‘theca’ were observed in interacted fungus as compared to control fungus (without bacterial interaction). This bacterium was tested for its antagonistic activity like protease, cellulose, HCN production, Chitinase, etc. The growth promoting activities showed increase production of IAA in bacteria. The bacterial secondary metabolites were extracted in different solvents for testing its growth inhibiting properties. The characterization and purification of the antifungal compound were done by Thin Layer Chromatography, and Rf value was calculated (Rf value = 0.54) and compared to the standard antifungal compound, 2, 4 DAPG (Rf value = 0.54). Further, the in vivo experiments showed a significant decrease in the severity of disease in the wheat plant due to direct injection method and seed treatment. Our results indicate that the extracted and purified compound from the antagonist bacteria, P. fluorescens MTCC-9768 may be used as a potential biocontrol agent against T. indica. This also concludes that the PGPR properties of the bacteria may be utilized by incorporating it into bio-fertilizers.

Keywords: antagonism, Karnal bunt, PGPR, Pseudomonas fluorescens

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Authors: Spandan Sahu, Amiya Kumar Pati, Kishanjit Kumar Khatua

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The river is our main source of water which is a form of open channel flow and the flow in the open channel provides with many complex phenomena of sciences that need to be tackled such as the critical flow conditions, boundary shear stress, and depth-averaged velocity. The development of society, more or less solely depends upon the flow of rivers. The rivers are major sources of many sediments and specific ingredients which are much essential for human beings. During floods, part of a river is carried by the simple main channel and rest is carried by flood plains. For such compound asymmetric channels, the flow structure becomes complicated due to momentum exchange between the main channel and adjoining flood plains. Distribution of boundary shear in subsections provides us with the concept of momentum transfer between the interface of the main channel and the flood plains. Experimentally, to get better data with accurate results are very complex because of the complexity of the problem. Hence, CES software has been used to tackle the complex processes to determine the shear stresses at different sections of an open channel having asymmetric flood plains on both sides of the main channel, and the results are compared with the symmetric flood plains for various geometrical shapes and flow conditions. Error analysis is also performed to know the degree of accuracy of the model implemented.

Keywords: depth average velocity, non prismatic compound channel, relative flow depth, velocity distribution

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Authors: Eliska Oberhofnerova, Milos Panek, Stepan Hysek, Martin Lexa

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Nowadays the use of wood, both indoors and outdoors, is constantly increasing. However wood is a natural organic material and in the exterior is subjected to a degradation process caused by abiotic factors (solar radiation, rain, moisture, wind, dust etc.). This process affects only surface layers of wood but neglecting some of the basic rules of wood protection leads to increased possibility of biological agents attack and thereby influences a function of the wood element. The process of wood degradation can be decreased by proper surface treatment, especially in the case of less naturally durable wood species, as spruce. Modern coating systems are subjected to many requirements such as colour stability, hydrophobicity, low volatile organic compound (VOC) content, long service life or easy maintenance. The aim of this study is to evaluate the colour stability of spruce wood (Picea abies), as the basic parameter indicating the coating durability, treated with two layers of transparent natural oil wood stain and exposed to outdoor conditions. The test specimens were exposed for 2 years to natural weathering and 2000 hours to artificial weathering in UV-chamber. The colour parameters were measured before and during exposure to weathering by the spectrophotometer according to CIELab colour space. The comparison between untreated and treated wood and both testing procedures was carried out. The results showed a significant effect of coating on the colour stability of wood, as expected. Nevertheless, increasing colour changes of wood observed during the exposure to weathering differed according to applied testing procedure - natural and artificial.

Keywords: colour stability, natural and artificial weathering, spruce wood, transparent coating

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Authors: Muhammad Gillfran Samual, Rinaldy Dalimi, Fauzan Hanif Jufri, Budi Sudiarto, Ismi Rosyiana Fitri

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Solar energy is increasingly recognized as an important future energy source due to its abundant availability and renewable nature. However, the intermittent nature of solar energy can cause fluctuations in the electricity produced, making it difficult to guarantee a stable and reliable electricity supply. One solution that can be implemented is to use batteries in a photovoltaic solar power plant system with a Moving Average control algorithm, which can help smooth and reduce fluctuations in solar power output power. The parameter that can be adjusted in the Moving Average algorithm is the window size or the arithmetic average width of the photovoltaic output power over time. This research evaluates the effect of a change of window size parameter in the Moving Average algorithm on the resulting smoothed photovoltaic output power and the technical effects on batteries, i.e., power and energy usage. Based on the evaluation, it is found that the increase of window size parameter will slow down the response of photovoltaic output power to changes in irradiation and increase the smoothing quality of the intermittent photovoltaic output power. In addition, increasing the window size will reduce the maximum power received on the load side, and the amount of energy used by the battery during the power smoothing process will increase, which, in turn, increases the required battery capacity.

Keywords: battery, intermittent, moving average, photovoltaic, power smoothing

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Authors: Tobias Schramm, Günther Prokop

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Degraded vehicle shock absorbers represent a risk for road safety. The exact effect of degraded vehicle dampers on road safety is still the subject of research. This work is intended to contribute to estimating the effect of degraded twin-tube dampers of passenger cars on road safety. An axle model was built using a damper model to simulate different degradation levels. To parameterize the model, a realistic parameter space was estimated based on test rig measurements and database analyses, which is intended to represent the vehicle field in Germany. Within the parameter space, simulations of the axle model were carried out, which calculated the transmittable lateral forces of the various axle configurations as a function of vehicle speed, road surface, damper conditions and axle parameters. A degraded damper has the greatest effect on the transmittable lateral forces at high speeds and in poor road conditions. If a vehicle is traveling at a speed of 100 kph on a Class D road, a degraded damper reduces the transmissible lateral forces of an axle by 20 % on average. For individual parameter configurations, this value can rise to 50 %. The axle parameters that most influence the effect of a degraded damper are the vertical stiffness of the tire, the unsprung mass and the stabilizer stiffness of the axle.

Keywords: vehicle dynamics, vehicle simulation, vehicle component degradation, shock absorber model, shock absorber degradation

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Authors: Suchana Marahatta, Sabina Bhattarai, Bishnu Hari Paudel, Dilip Thakur

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Background: Every year thousands of patients develop nerve damage and disabilities as a result of leprosy which can be prevented by early detection and treatment. So, early detection and treatment of nerve function impairment is of paramount importance in leprosy. Objectives: To assess the electrophysiological pattern of the peripheral nerves in leprosy patients and to compare it with clinical assessment tools. Materials and Methods: In this comparative cross-sectional study, 74 newly diagnosed leprosy patients without reaction were enrolled. They underwent thorough evaluation for peripheral nerve function impairment using clinical tests [i.e. nerve palpation (NP), monofilament (MF) testing, voluntary muscle testing (VMT)] and nerve conduction study (NCS). Clinical findings were compared with that of NCS using SPSS version 11.5. Results: NCS was impaired in 43.24% of leprosy patient at the baseline. Among them, sensory NCS was impaired in more patients (32.4%) in comparison to motor NCS (20.3%). NP, MF, and VMT were impaired in 58.1%, 25.7%, and 9.4% of the patients, respectively. Maximum concordance of monofilament testing and sensory NCS was found for sural nerve (14.7%). Likewise, the concordance of motor NP and motor NCS was the maximum for ulnar nerve (14.9%). When individual parameters of the NCS were considered, amplitude was found to be the most frequently affected parameter for both sensory and motor NCS. It was impaired in 100% of cases with abnormal NCS findings. Conclusion: Since there was no acceptable concordance between NCS findings and clinical findings, we should consider NCS whenever feasible for early detection of neuropathy in leprosy. The amplitude of both sensory nerve action potential (SNAP) and compound nerve action potential (CAMP) could be important determinants of the abnormal NCS if supported by further studies.

Keywords: leprosy, nerve function impairment, neuropathy, nerve conduction study

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Authors: Hichem Boulechfar, Mahfoud Djezzar

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Two-dimensional double diffusive natural convection in an annular elliptical space filled with fluid-saturated porous medium, is analyzed by solving numerically the mass balance, momentum, energy and concentration equations, using Darcy's law and Boussinesq approximation. Both walls delimiting the annular space are maintained at two uniform different temperatures and concentrations. The external parameter considered is the Lewis number. For the present work, the heat and mass transfer for natural convection is studied for the case of aiding buoyancies, where the flow is generated in a cooperative mode by both temperature and solutal gradients. The local Nusselt and Sherwood numbers are presented in term of the external parameter.

Keywords: double diffusive, natural convection, porous media, elliptical annulus

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Authors: James Sinclair, Katy Soapi, Brad Carte

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The marine environment has continuously demonstrated to be a rich source of secondary metabolites and bioactive compounds that can address the many pharmaceutical problems facing mankind. The emergence of multidrug resistant pathogens has caused scientists to explore contemporary ways of combating these super bugs. A red-pigmented bacterial strain isolated from a marine alga collected in Fiji was identified to be Pseudoalteromonas rubra from 16s rRNA sequencing. This bacterial strain was cultured using a yeast-peptone media and incubated for five days. The ethyl acetate extract of this bacterium was subjected to chromatographic separation techniques such as vacuum liquid chromatography, flash chromatography, size exclusion chromatography and high-pressure liquid chromatography to yield the pure compound and a number of semi-pure fractions. The crude extract and subsequent purified fractions were analyzed by ultraviolet/visible spectroscopy and mass spectroscopy and was found to contain the compounds ivermectin, stenothricin, cyclo-L-pro-L-val, prodigiosin, mycophenolic acid, phenazine-1-carboxylic acid, eplerenone, staurosporine and pseudoalteromone A. The structure of the pure compound, pseudoalteromone A, was elucidated using NMR 1H, 13C, 1H-1H COSY, HSQC and HMBC spectroscopic data.

Keywords: Pseudoalteromonas rubra, Pseudoalteromone A, secondary metabolites, structure elucidation

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Authors: Xiaowei Zhang, Min Xu, Saeid Habibi, Fengjun Yan, Ryan Ahmed

Abstract:

Recently, Electric Vehicles (EVs) have received extensive consideration since they offer a more sustainable and greener transportation alternative compared to fossil-fuel propelled vehicles. Lithium-Ion (Li-ion) batteries are increasingly being deployed in EVs because of their high energy density, high cell-level voltage, and low rate of self-discharge. Since Li-ion batteries represent the most expensive component in the EV powertrain, accurate monitoring and control strategies must be executed to ensure their prolonged lifespan. The Battery Management System (BMS) has to accurately estimate parameters such as the battery State-of-Charge (SOC), State-of-Health (SOH), and Remaining Useful Life (RUL). In order for the BMS to estimate these parameters, an accurate and control-oriented battery model has to work collaboratively with a robust state and parameter estimation strategy. Since battery physical parameters, such as the internal resistance and diffusion coefficient change depending on the battery state-of-life (SOL), the BMS has to be adaptive to accommodate for this change. In this paper, an extensive battery aging study has been conducted over 12-months period on 5.4 Ah, 3.7 V Lithium polymer cells. Instead of using fixed charging/discharging aging cycles at fixed C-rate, a set of real-world driving scenarios have been used to age the cells. The test has been interrupted every 5% capacity degradation by a set of reference performance tests to assess the battery degradation and track model parameters. As battery ages, the combined model parameters are optimized and tracked in an offline mode over the entire batteries lifespan. Based on the optimized model, a state and parameter estimation strategy based on the Extended Kalman Filter (EKF) and the relatively new Smooth Variable Structure Filter (SVSF) have been applied to estimate the SOC at various states of life.

Keywords: lithium-ion batteries, genetic algorithm optimization, battery aging test, parameter identification

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Authors: Wael M. Bazzi, Amir Rastegarnia, Azam Khalili

Abstract:

In this paper we consider the issue of reliability of measurements in distributed adaptive estimation problem. To this aim, we assume a sensor network with different observation noise variance among the sensors and propose new estimation method based on incremental distributed least mean-square (IDLMS) algorithm. The proposed method contains two phases: I) Estimation of each sensors observation noise variance, and II) Estimation of the desired parameter using the estimated observation variances. To deal with the reliability of measurements, in the second phase of the proposed algorithm, the step-size parameter is adjusted for each sensor according to its observation noise variance. As our simulation results show, the proposed algorithm considerably improves the performance of the IDLMS algorithm in the same condition.

Keywords: adaptive filter, distributed estimation, sensor network, IDLMS algorithm

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Authors: Kristian Bautista, Ruben A. Idoy

Abstract:

A bio-inspired metaheuristic algorithm inspired by the theory of collective animal behavior (CAB) was integrated to density-based clustering modeled as multimodal optimization problem. The algorithm was tested on synthetic, Iris, Glass, Pima and Thyroid data sets in order to measure its effectiveness relative to CDE-based Clustering algorithm. Upon preliminary testing, it was found out that one of the parameter settings used was ineffective in performing clustering when applied to the algorithm prompting the researcher to do an investigation. It was revealed that fine tuning distance δ3 that determines the extent to which a given data point will be clustered helped improve the quality of cluster output. Even though the modification of distance δ3 significantly improved the solution quality and cluster output of the algorithm, results suggest that there is no difference between the population mean of the solutions obtained using the original and modified parameter setting for all data sets. This implies that using either the original or modified parameter setting will not have any effect towards obtaining the best global and local animal positions. Results also suggest that CDE-based clustering algorithm is better than CAB-density clustering algorithm for all data sets. Nevertheless, CAB-density clustering algorithm is still a good clustering algorithm because it has correctly identified the number of classes of some data sets more frequently in a thirty trial run with a much smaller standard deviation, a potential in clustering high dimensional data sets. Thus, the researcher recommends further investigation in the post-processing stage of the algorithm.

Keywords: clustering, metaheuristics, collective animal behavior algorithm, density-based clustering, multimodal optimization

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Authors: Dalvinder Kaur Mangal

Abstract:

For the past decade, noise corrupted output measurements have been a fundamental research problem to be investigated. On the other hand, the estimation of the parameters for linear dynamic systems when also the input is affected by noise is recognized as more difficult problem which only recently has received increasing attention. Representations where errors or measurement noises/disturbances are present on both the inputs and outputs are usually called errors-in-variables (EIV) models. These disturbances may also have additive effects which are also considered in this paper. Parameter estimation of false EIV problem using equation error, output error and iterative prefiltering identification schemes with and without additive uncertainty, when only the output observation is corrupted by noise has been dealt in this paper. The comparative study of these three schemes has also been carried out.

Keywords: errors-in-variable (EIV), false EIV, equation error, output error, iterative prefiltering, Gaussian noise

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Authors: Madhu Aneja, Sapna Sharma

Abstract:

Thermal conductivity of ordinary heat transfer fluids is not adequate to meet today’s cooling rate requirements. Nanoparticles have been shown to increase the thermal conductivity and convective heat transfer to the base fluids. One of the possible mechanisms for anomalous increase in the thermal conductivity of nanofluids is the Brownian motions of the nanoparticles in the basefluid. In this paper, the natural convection of incompressible nanofluid over a nonlinear stretching sheet in the presence of magnetic field is studied. The flow and heat transfer induced by stretching sheets is important in the study of extrusion processes and is a subject of considerable interest in the contemporary literature. Appropriate similarity variables are used to transform the governing nonlinear partial differential equations to a system of nonlinear ordinary (similarity) differential equations. For computational purpose, Finite Element Method is used. The effective thermal conductivity and viscosity of nanofluid are calculated by KKL (Koo – Klienstreuer – Li) correlation. In this model effect of Brownian motion on thermal conductivity is considered. The effect of important parameter i.e. nonlinear parameter, volume fraction, Hartmann number, heat source parameter is studied on velocity and temperature. Skin friction and heat transfer coefficients are also calculated for concerned parameters.

Keywords: Brownian motion, convection, finite element method, magnetic field, nanofluid, stretching sheet

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Authors: Choy Sonny Yip Hong

Abstract:

This abstract presents an exploration into the creation of a sustainable bio-polymer compound for additive manufacturing, specifically 3D printing, with a focus on eggshells and polylactide (PLA) polymer. The project initially conducted experiments using a variety of food by-products to create bio-polymers, and promising results were obtained when combining eggshells with PLA polymer. The research journey involved precise measurements, drying of PLA to remove moisture, and the utilization of a filament-making machine to produce 3D printable filaments. The project began with exploratory research and experiments, testing various combinations of food by-products to create bio-polymers. After careful evaluation, it was discovered that eggshells and PLA polymer produced promising results. The initial mixing of the two materials involved heating them just above the melting point. To make the compound 3D printable, the research focused on finding the optimal formulation and production process. The process started with precise measurements of the PLA and eggshell materials. The PLA was placed in a heating oven to remove any absorbed moisture. Handmade testing samples were created to guide the planning for 3D-printed versions. The scrap PLA was recycled and ground into a powdered state. The drying process involved gradual moisture evaporation, which required several hours. The PLA and eggshell materials were then placed into the hopper of a filament-making machine. The machine's four heating elements controlled the temperature of the melted compound mixture, allowing for optimal filament production with accurate and consistent thickness. The filament-making machine extruded the compound, producing filament that could be wound on a wheel. During the testing phase, trials were conducted with different percentages of eggshell in the PLA mixture, including a high percentage (20%). However, poor extrusion results were observed for high eggshell percentage mixtures. Samples were created, and continuous improvement and optimization were pursued to achieve filaments with good performance. To test the 3D printability of the DIY filament, a 3D printer was utilized, set to print the DIY filament smoothly and consistently. Samples were printed and mechanically tested using a universal testing machine to determine their mechanical properties. This testing process allowed for the evaluation of the filament's performance and suitability for additive manufacturing applications. In conclusion, the project explores the creation of a sustainable bio-polymer compound using eggshells and PLA polymer for 3D printing. The research journey involved precise measurements, drying of PLA, and the utilization of a filament-making machine to produce 3D printable filaments. Continuous improvement and optimization were pursued to achieve filaments with good performance. The project's findings contribute to the advancement of additive manufacturing, offering opportunities for design innovation, carbon footprint reduction, supply chain optimization, and collaborative potential. The utilization of eggshell PLA polymer in additive manufacturing has the potential to revolutionize the manufacturing industry, providing a sustainable alternative and enabling the production of intricate and customized products.

Keywords: additive manufacturing, 3D printing, eggshell PLA polymer, design innovation, carbon footprint reduction, supply chain optimization, collaborative potential

Procedia PDF Downloads 55