Search results for: function approximation

Authors: Ranadhir Roy

Abstract:

Inverse problems arise in medical (molecular) imaging. These problems are characterized by large in three dimensions, and by the diffusion equation which models the physical phenomena within the media. The inverse problems are posed as a nonlinear optimization where the unknown parameters are found by minimizing the difference between the predicted data and the measured data. To obtain a unique and stable solution to an ill-posed inverse problem, a priori information must be used. Mathematical conditions to obtain stable solutions are established in Tikhonov’s regularization method, where the a priori information is introduced via a stabilizing functional, which may be designed to incorporate some relevant information of an inverse problem. Effective determination of the Tikhonov regularization parameter requires knowledge of the true solution, or in the case of optical imaging, the true image. Yet, in, clinically-based imaging, true image is not known. To alleviate these difficulties we have applied the penalty/modified barrier function (PMBF) method instead of Tikhonov regularization technique to make the inverse problems well-posed. Unlike the Tikhonov regularization method, the constrained optimization technique, which is based on simple bounds of the optical parameter properties of the tissue, can easily be implemented in the PMBF method. Imposing the constraints on the optical properties of the tissue explicitly restricts solution sets and can restore uniqueness. Like the Tikhonov regularization method, the PMBF method limits the size of the condition number of the Hessian matrix of the given objective function. The accuracy and the rapid convergence of the PMBF method require a good initial guess of the Lagrange multipliers. To obtain the initial guess of the multipliers, we use a least square unconstrained minimization problem. Three-dimensional images of fluorescence absorption coefficients and lifetimes were reconstructed from contact and noncontact experimentally measured data.

Keywords: constrained minimization, ill-conditioned inverse problems, Tikhonov regularization method, penalty modified barrier function method

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Authors: Constanza A. Barriga, Rafael Bernardi, Amokrane Berdja, Christian D. Guzman

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Most image restoration methods in astronomy rely upon probabilistic tools that infer the best solution for a deconvolution problem. They achieve good performances when the point spread function (PSF) is spatially invariable in the image plane. However, this latter condition is not always satisfied with real optical systems. PSF angular variations cannot be evaluated directly from the observations, neither be corrected at a pixel resolution. We have developed a method for the restoration of images affected by static and anisotropic aberrations using deep neural networks that can be directly applied to sky images. The network is trained using simulated sky images corresponding to the T-80 telescope optical system, an 80 cm survey imager at Cerro Tololo (Chile), which are synthesized using a Zernike polynomial representation of the optical system. Once trained, the network can be used directly on sky images, outputting a corrected version of the image, which has a constant and known PSF across its field-of-view. The method was tested with the T-80 telescope, achieving better results than with PSF deconvolution techniques. We present the method and results on this telescope.

Keywords: aberrations, deep neural networks, image restoration, variable point spread function, wide field images

Procedia PDF Downloads 134

Authors: Jéssica Ferreira Rodrigues, Júlio Silvio De Sousa Bueno Filho, Vanessa Rios De Souza, Ana Carla Marques Pinheiro

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This study aimed to evaluate the implications of the block size and testing order on efficiency and precision of preference estimation for Dulce de leche samples. Efficiency was defined as the inverse of the average variance of pairwise comparisons among treatments. Precision was defined as the inverse of the variance of treatment means (or effects) estimates. The experiment was originally designed to test 16 treatments as a series of 8 Sudoku 16x16 designs being 4 randomized independently and 4 others in the reverse order, to yield balance in testing order. Linear mixed models were assigned to the whole experiment with 112 testers and all their grades, as well as their partially balanced subgroups, namely: a) experiment with the four initial EU; b) experiment with EU 5 to 8; c) experiment with EU 9 to 12; and b) experiment with EU 13 to 16. To record responses we used a nine-point hedonic scale, it was assumed a mixed linear model analysis with random tester and treatments effects and with fixed test order effect. Analysis of a cumulative random effects probit link model was very similar, with essentially no different conclusions and for simplicity, we present the results using Gaussian assumption. R-CRAN library lme4 and its function lmer (Fit Linear Mixed-Effects Models) was used for the mixed models and libraries Bayesthresh (default Gaussian threshold function) and ordinal with the function clmm (Cumulative Link Mixed Model) was used to check Bayesian analysis of threshold models and cumulative link probit models. It was noted that the number of samples tested in the same session can influence the acceptance level, underestimating the acceptance. However, proving a large number of samples can help to improve the samples discrimination.

Keywords: acceptance, block size, mixed linear model, testing order, testing order

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Authors: Nicholas Pearce, Eun-jin Kim

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Pathologies of the cardiovascular (CV) system remain a serious and deadly health problem for human society. Computational modelling provides a relatively accessible tool for diagnosis, treatment, and research into CV disorders. However, numerical models of the CV system have largely focused on the function of the ventricles, frequently overlooking the behaviour of the atria. Furthermore, in the study of the pressure-volume relationship of the heart, which is a key diagnosis of cardiac vascular pathologies, previous works often evoke popular yet questionable time-varying elastance (TVE) method that imposes the pressure-volume relationship instead of calculating it consistently. Despite the convenience of the TVE method, there have been various indications of its limitations and the need for checking its validity in different scenarios. A model of the combined left ventricle (LV) and left atrium (LA) is presented, which consistently considers various feedback mechanisms in the heart without having to use the TVE method. Specifically, a synergistic model of the left ventricle is extended and modified to include the function of the LA. The synergy of the original model is preserved by modelling the electro-mechanical and chemical functions of the micro-scale myofiber for the LA and integrating it with the microscale and macro-organ-scale heart dynamics of the left ventricle and CV circulation. The atrioventricular node function is included and forms the conduction pathway for electrical signals between the atria and ventricle. The model reproduces the essential features of LA behaviour, such as the two-phase pressure-volume relationship and the classic figure of eight pressure-volume loops. Using this model, disorders in the internal cardiac electrical signalling are investigated by recreating the mechano-electric feedback (MEF), which is impossible where the time-varying elastance method is used. The effects of AV node block and slow conduction are then investigated in the presence of an atrial arrhythmia. It is found that electrical disorders and arrhythmia in the LA degrade the CV system by reducing the cardiac output, power, and heart rate.

Keywords: cardiovascular system, left atrium, numerical model, MEF

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Authors: Yuyang Cheng, Marcos Escobar-Anel

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This paper introduces a multivariate 4/2 stochastic covariance process generalizing the one-dimensional counterparts presented in Grasselli (2017). Our construction permits stochastic correlation not only among stocks but also among volatilities, also known as co-volatility movements, both driven by more convenient 4/2 stochastic structures. The parametrization is flexible enough to separate these types of correlation, permitting their individual study. Conditions for proper changes of measure and closed-form characteristic functions under risk-neutral and historical measures are provided, allowing for applications of the model to risk management and derivative pricing. We apply the model to an expected utility theory problem in incomplete markets. Our analysis leads to closed-form solutions for the optimal allocation and value function. Conditions are provided for well-defined solutions together with a verification theorem. Our numerical analysis highlights and separates the impact of key statistics on equity portfolio decisions, in particular, volatility, correlation, and co-volatility movements, with the latter being the least important in an incomplete market.

Keywords: stochastic covariance process, 4/2 stochastic volatility model, stochastic co-volatility movements, characteristic function, expected utility theory, verication theorem

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Authors: J. Y. Sun, H. Z. Shen

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We study the photon blockade at exceptional points for a non-Hermitian optomechanical system coupled to the driven whispering-gallery-mode microresonator with two nanoparticles under the weak optomechanical coupling approximation, where exceptional points emerge periodically by controlling the relative angle of the nanoparticles. We find that conventional photon blockade occurs at exceptional points for the eigenenergy resonance of the single-excitation subspace driven by a laser field and discuss the physical origin of conventional photon blockade. Under the weak driving condition, we analyze the influences of the different parameters on conventional photon blockade. We investigate conventional photon blockade at nonexceptional points, which exists at two optimal detunings due to the eigenstates in the single-excitation subspace splitting from one (coalescence) at exceptional points to two at nonexceptional points. Unconventional photon blockade can occur at nonexceptional points, while it does not exist at exceptional points since the destructive quantum interference cannot occur due to the two different quantum pathways to the two-photon state not being formed. The realization of photon blockade in our proposal provides a viable and flexible way for the preparation of single-photon sources in the non-Hermitian optomechanical system.

Keywords: optomechanical systems, photon blockade, non-hermitian, exceptional points

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Authors: Henrik L. Funke, Lars Ulke-Winter, Sandra Gelbrich, Lothar Kroll

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This work reports about an approach for an automatic adaptation of concrete formulations based on genetic algorithms (GA) to optimize a wide range of different fit-functions. In order to achieve the goal, a method was developed which provides a numerical description of a fibre reinforced concrete (FRC) mixture regarding the production technology and the property spectrum of the concrete. In a first step, the FRC mixture with seven fixed components was characterized by varying amounts of the components. For that purpose, ten concrete mixtures were prepared and tested. The testing procedure comprised flow spread, compressive and bending tensile strength. The analysis and approximation of the determined data was carried out by GAs. The aim was to obtain a closed mathematical expression which best describes the given seven-point cloud of FRC by applying a Gene Expression Programming with Free Coefficients (GEP-FC) strategy. The seven-parametric FRC-mixtures model which is generated according to this method correlated well with the measured data. The developed procedure can be used for concrete mixtures finding closed mathematical expressions, which are based on the measured data.

Keywords: concrete design, fibre reinforced concrete, genetic algorithms, GEP-FC

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Authors: Raja Chinnappan, Huda Alanazi, Shanmugam Easwaramoorthi, Tanveer Mir, Balamurugan Kanagasabai, Ahmed Yaqinuddin, Sandhanasamy Devanesan, Mohamad S. AlSalhi

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Serum albumin (SA) is a highly rich water-soluble protein in plasma. It is known to maintain the living organisms' health and help to maintain the proper liver function, kidney function, and plasma osmolality in the body. Low levels of serum albumin are an indication of liver failure and chronic hepatitis. Therefore, it is important to have a low-cost, accurate and rapid method. In this study, we designed a fluorescent probe, triphenylamine rhodanine-3-acetic acid (mRA), which triggers the fluorescence signal upon binding with serum albumin (SA). mRA is a bifunctional molecule with twisted intramolecular charge transfer (TICT)-induced emission characteristics. An aqueous solution of mRA has an insignificant fluorescence signal; however, when mRA binds to SA, it undergoes TICT and turns on the fluorescence emission. A SA dose-dependent fluorescence signal was performed, and the limit of detection was found to be less than ng/mL. The specific binding of SA was tested from the cross-reactivity study using similar structural or functional proteins.

Keywords: serum albumin, fluorescent sensing probe, liver diseases, twisted intramolecular charge transfer

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Authors: Adineh Tajmousavilangerudi, Ali Zein Alabiden Tlais, Raffaella Di Cagno

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The SARS-Cov-2 pandemic has exposed our vulnerability to new illnesses and novel viruses that attack our immune systems, particularly in the elderly. The vaccine is being gradually introduced over the world, but new strains of the virus and COVID-19 will emerge and continue to cause illness. Aging is associated with significant changes in intestinal physiology, which increases the production of inflammatory products, alters the gut microbiota, and consequently establish inadequate immune response to minimize symptoms and disease development. In this context, older people who followed a Mediterranean-style diet, rich in polyphenols and dietary fiber, performed better physically and mentally (1,2). This demonstrates the importance of the human gut microbiome in transforming complex dietary macromolecules into the most biologically available and active nutrients, which in turn help to regulate metabolism and both intestinal and systemic immune function (3,4). The role of lactic acid fermentation is prominent also as a powerful tool for improving the nutritional quality of the human diet by releasing nutrients and boosting the complex bioactive compounds and vitamin content. the PhD project aims to design fermented and functional foods/beverages capable of modulating human immune function via the gut microbiome.

Keywords: functional bevarage, fermented beverage, gut microbiota functionality, immun system

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Authors: A. Preetha Priyadharshini, S. B. M. Priya

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In this paper, we consider the MU-MISO downlink scenario, under imperfect channel state information (CSI). The main issue in imperfect CSI is to keep the probability of each user achievable outage rate below the given threshold level. Such a rate outage constraints present significant and analytical challenges. There are many probabilistic methods are used to minimize the transmit optimization problem under imperfect CSI. Here, decomposition based large deviation inequality and Bernstein type inequality convex restriction methods are used to perform the optimization problem under imperfect CSI. These methods are used for achieving improved output quality and lower complexity. They provide a safe tractable approximation of the original rate outage constraints. Based on these method implementations, performance has been evaluated in the terms of feasible rate and average transmission power. The simulation results are shown that all the two methods offer significantly improved outage quality and lower computational complexity.

Keywords: imperfect channel state information, outage probability, multiuser- multi input single output, channel state information

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Authors: Jiahui You, Kyung Jae Lee

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Hydraulic fracturing fluid (HFF) is widely used in shale reservoir productions. HFF contains diverse chemical additives, which result in the dissolution and precipitation of minerals through multiple chemical reactions. In this study, a new pore-scale Darcy–Brinkman–Stokes (DBS) model coupled with Level Set Method (LSM) is developed to address the microscopic phenomena occurring during the iron–HFF interaction, by numerically describing mass transport, chemical reactions, and pore structure evolution. The new model is developed based on OpenFOAM, which is an open-source platform for computational fluid dynamics. Here, the DBS momentum equation is used to solve for velocity by accounting for the fluid-solid mass transfer; an advection-diffusion equation is used to compute the distribution of injected HFF and iron. The reaction–induced pore evolution is captured by applying the LSM, where the solid-liquid interface is updated by solving the level set distance function and reinitialized to a signed distance function. Then, a smoothened Heaviside function gives a smoothed solid-liquid interface over a narrow band with a fixed thickness. The stated equations are discretized by the finite volume method, while the re-initialized equation is discretized by the central difference method. Gauss linear upwind scheme is used to solve the level set distance function, and the Pressure–Implicit with Splitting of Operators (PISO) method is used to solve the momentum equation. The numerical result is compared with 1–D analytical solution of fluid-solid interface for reaction-diffusion problems. Sensitivity analysis is conducted with various Damkohler number (DaII) and Peclet number (Pe). We categorize the Fe (III) precipitation into three patterns as a function of DaII and Pe: symmetrical smoothed growth, unsymmetrical growth, and dendritic growth. Pe and DaII significantly affect the location of precipitation, which is critical in determining the injection parameters of hydraulic fracturing. When DaII<1, the precipitation uniformly occurs on the solid surface both in upstream and downstream directions. When DaII>1, the precipitation mainly occurs on the solid surface in an upstream direction. When Pe>1, Fe (II) transported deeply into and precipitated inside the pores. When Pe<1, the precipitation of Fe (III) occurs mainly on the solid surface in an upstream direction, and they are easily precipitated inside the small pore structures. The porosity–permeability relationship is subsequently presented. This pore-scale model allows high confidence in the description of Fe (II) dissolution, transport, and Fe (III) precipitation. The model shows fast convergence and requires a low computational load. The results can provide reliable guidance for injecting HFF in shale reservoirs to avoid clogging and wellbore pollution. Understanding Fe (III) precipitation, and Fe (II) release and transport behaviors give rise to a highly efficient hydraulic fracture project.

Keywords: reactive-transport , Shale, Kerogen, precipitation

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Authors: Mohammad Mohammadzadeh, Alireza Ghasempour

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In this paper, a new design of monopole antenna has been proposed that increases the contrast of intravascular magnetic resonance images through increasing the homogeneity of the intrinsic signal-to-noise ratio (ISNR) distribution around the antenna. The antenna is made of a coaxial cable with three parasitic elements. Lengths and positions of the elements are optimized by the improved genetic algorithm (IGA) for 1.5, 3, 4.7, and 7Tesla MRI systems based on a defined cost function. Simulations were also conducted to verify the performance of the designed antenna. Our simulation results show that each time IGA is executed different values for the parasitic elements are obtained so that the cost functions of those antennas are high. According to the obtained results, IGA can also find the best values for the parasitic elements (regarding cost function) in the next executions. Additionally, two dimensional and one-dimensional maps of ISNR were drawn for the proposed antenna and compared to the previously published monopole antenna with one parasitic element at the frequency of 64MHz inside a saline phantom. Results verified that in spite of ISNR decreasing, there is a considerable improvement in the homogeneity of ISNR distribution of the proposed antenna so that their multiplication increases.

Keywords: intravascular MR antenna, monopole antenna, parasitic elements, signal-to-noise ratio (SNR), genetic algorithm

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Authors: M. Yushalify Misro, Ahmad Ramli, Jamaludin M. Ali

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Bezier curves have useful properties for path generation problem, for instance, it can generate the reference trajectory for vehicles to satisfy the path constraints. Both algorithms join cubic Bezier curve segment smoothly to generate the path. Some of the useful properties of Bezier are curvature. In mathematics, the curvature is the amount by which a geometric object deviates from being flat, or straight in the case of a line. Another extrinsic example of curvature is a circle, where the curvature is equal to the reciprocal of its radius at any point on the circle. The smaller the radius, the higher the curvature thus the vehicle needs to bend sharply. In this study, we use Bezier curve to fit highway-like curve. We use the different approach to finding the best approximation for the curve so that it will resemble highway-like curve. We compute curvature value by analytical differentiation of the Bezier Curve. We will then compute the maximum speed for driving using the curvature information obtained. Our research works on some assumptions; first the Bezier curve estimates the real shape of the curve which can be verified visually. Even, though, the fitting process of Bezier curve does not interpolate exactly on the curve of interest, we believe that the estimation of speed is acceptable. We verified our result with the manual calculation of the curvature from the map.

Keywords: speed estimation, path constraints, reference trajectory, Bezier curve

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Authors: Shweda Mohan, J. L. Nandagopal, S. Amritha

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This paper focuses on the dynamic modelling of unicycle robot. Two main concepts used for balancing unicycle robot are: reaction wheel pendulum and inverted pendulum. The pitch axis is modelled as inverted pendulum and roll axis is modelled as reaction wheel pendulum. The unicycle yaw dynamics is not considered which makes the derivation of dynamics relatively simple. For the roll controller, sliding-mode controller has been adopted and optimal methods are used to minimize switching-function chattering. For pitch controller, an LQR controller has been implemented to drive the unicycle robot to follow the desired velocity trajectory. The pitching and rolling balance could be achieved by two DC motors. Unicycle robot is a non-holonomic, non-linear, static unbalance system that has the minimal number of point contact to the ground, therefore, it is a perfect platform for researchers to study motion and balance control. These real-time solutions will be a viable solution for advanced robotic systems and controls.

Keywords: decoupled dynamics, linear quadratic regulator (LQR) control, Lyapunov function sliding mode control, unicycle robot, velocity and trajectory control

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Authors: Loredana Elena Nita, Maria Bercea, Aurica P. Chiriac, Iordana Neamtu

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The paper is devoted to the behavior of gels based on poly(itaconic anhydride-co-3, 9-divinyl-2, 4, 8, 10-tetraoxaspiro (5.5) undecane) copolymers, with different ratio between the comonomers, and hyaluronic acid (HA). The gel formation was investigated by small-amplitude oscillatory shear measurements following the viscoelastic behavior as a function of gel composition, temperature and shear conditions. Hyaluronic acid was investigated in the same conditions and its rheological behavior is typical to viscous fluids. In the case of the copolymers, the ratio between the two comonomers influences the viscoelastic behavior, a higher content of itaconic anhydride favoring the gel formation. Also, the sol-gel transition was evaluated according to Winter-Chambon criterion that identifies the gelation point when the viscoelastic moduli (G’ and G”) behave similarly as a function of oscillation frequency. From rheological measurements, an optimum composition was evidenced for which the system presents a typical gel-like behavior at 37 °C: the elastic modulus is higher than the viscous modulus and they are not dependent on the oscillation frequency. The formation of the 3D macroporous network was also evidenced by FTIR spectra, SEM microscopy and chemical imaging. These hydrogels present a high potential as drug delivery systems.

Keywords: copolymer, viscoelasticity, gelation, 3D network

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Authors: Kaushalendra K. Khadanga, Lee Hee Hyol

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Passenger comfort has been paramount in the design of suspension systems of high speed cars. To analyze the effect of vibration on vehicle ride quality, a vertical model of a six degree of freedom railway passenger vehicle, with front and rear suspension, is built. It includes car body flexible effects and vertical rigid modes. A second order linear shaping filter is constructed to model Gaussian white noise into random rail excitation. The temporal correlation between the front and rear wheels is given by a second order Pade approximation. The complete track and the vehicle model are then designed. An active secondary suspension system based on a Linear Quadratic Gaussian (LQG) optimal control method is designed. The results show that the LQG control method reduces the vertical acceleration, pitching acceleration and vertical bending vibration of the car body as compared to the passive system.

Keywords: active suspension, bending vibration, railway vehicle, vibration control

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Authors: Yung Gi Wu

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With the growing of computer and network, digital data can be spread to anywhere in the world quickly. In addition, digital data can also be copied or tampered easily so that the security issue becomes an important topic in the protection of digital data. Digital watermark is a method to protect the ownership of digital data. Embedding the watermark will influence the quality certainly. In this paper, Vector Quantization (VQ) is used to embed the watermark into the image to fulfill the goal of data hiding. This kind of watermarking is invisible which means that the users will not conscious the existing of embedded watermark even though the embedded image has tiny difference compared to the original image. Meanwhile, VQ needs a lot of computation burden so that we adopt a fast VQ encoding scheme by partial distortion searching (PDS) and mean approximation scheme to speed up the data hiding process. The watermarks we hide to the image could be gray, bi-level and color images. Texts are also can be regarded as watermark to embed. In order to test the robustness of the system, we adopt Photoshop to fulfill sharpen, cropping and altering to check if the extracted watermark is still recognizable. Experimental results demonstrate that the proposed system can resist the above three kinds of tampering in general cases.

Keywords: data hiding, vector quantization, watermark, color image

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Authors: Apisaraporn Baicharoen, Prapasiri Pongprayoon

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Betaine aldehyde dehydrogenase 2 (BADH2) is an enzyme that inhibits the accumulation of 2-acetyl-1-pyrroline (2AP), a potent flavor compound in rice fragrance. BADH2 contains three domains (NAD-binding, substrate-binding, and oligomerization domains). It catalyzes the oxidation of amino aldehydes. The lack of BADH2 results in the formation of 2AP and consequently an increase in rice fragrance. To date, inadequate data on BADH2 structure and function are available. An insight into the nature of BADH2 can serve as one of key starting points for the production of high quality fragrant rice. In this study, we therefore constructed the homology model of BADH2 and employed 500-ns Molecular Dynamics simulations (MD) to primarily understand the structural and dynamic properties of BADH2. Initially, Ramachandran plot confirms the good quality of modeled protein structure. Principle Component Analysis (PCA) was also calculated to capture the protein dynamics. Among 3 domains, the results show that NAD binding site is found to be more flexible. Moreover, interactions from key amino acids (N162, E260, C294, and Y419) that are crucial for function are investigated.

Keywords: betaine aldehyde dehydrogenase 2, fragrant rice, homology modeling, molecular dynamics simulations

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Authors: Yomna Ibrahim El-Gazzar, Hussien Ibrahim El-Subbagh, Hanan Hanaa Georgey, Ghada S. Hassan Hassan

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Dihydrofolate reductase (DHFR) is an enzyme that has pivotal importance in biochemistry and medicinal chemistry. It catalyzes the reduction of dihydrofolate to tetrahydrofolate and intimately couples with thymidylate synthase. Thymidylate synthase is a crucial enzyme that catalyzes the reductive methylation of (dUMP) to (dTMP) utilizing N5, N10-methylenetetrahydrofolate as a cofactor. A new series of 2-substituted thio-quinazolin-4-one analogs was designed that possessed electron withdrawing or donating functional groups (Cl or OCH3) at position 6- or 7-, 4-methoxyphenyl function at position 3-.The thiol function is used to connect to either 1,2,4-triazole, or 1,3,4-thiadiazole via a methylene bridge. Most of the functional groups designed to be accommodated on the quinazoline ring such as thioether, alkyl to increase lipid solubility of polar compounds, a character very much needed in the nonclassical DHFR inhibitors. The target compounds were verified with spectral data and elemental analysis. DHFR inhibitions, as well as antitumor activity, were applied on three cell lines (MCF-7, CACO-2, HEPG-2).

Keywords: nonclassical antifolates, DHFR Inhibitors, antitumor activity, quinazoline ring

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Authors: Victoria Goodall, Paul Fatti, Norman Owen-Smith

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Hidden Markov Models have become popular for the analysis of animal tracking data. These models are being used to model the movements of a variety of species in many areas around the world. A common assumption of the model is that the observations need to have regular time steps. In many ecological studies, this will not be the case. The objective of the research is to modify the movement model to allow for irregularly spaced locations and investigate the effect on the inferences which can be made about the latent states. A modification of the likelihood function to allow for these irregular spaced locations is investigated, without using interpolation or averaging the movement rate. The suitability of the modification is investigated using GPS tracking data for lion (Panthera leo) in South Africa, with many observations obtained during the night, and few observations during the day. Many nocturnal predator tracking studies are set up in this way, to obtain many locations at night when the animal is most active and is difficult to observe. Few observations are obtained during the day, when the animal is expected to rest and is potentially easier to observe. Modifying the likelihood function allows the popular Hidden Markov Model framework to be used to model these irregular spaced locations, making use of all the observed data.

Keywords: hidden Markov Models, irregular observations, animal movement modelling, nocturnal predator

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Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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Authors: Y. Ruchi, A. Prerna, S. Deepshikha

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Amyotrophic lateral sclerosis (ALS), also known as “Lou Gehrig’s disease”. It is a neurodegenerative disease associated with degeneration of motor neurons in the cerebral cortex, brain stem, and spinal cord characterized by distal muscle weakness, atrophy, normal sensation, pyramidal signs and progressive muscular paralysis reflecting. ALS2 is a juvenile autosomal recessive disorder, slowly progressive, that maps to chromosome 2q33 and is associated with mutations in the alsin gene, a putative GTPase regulator. In this paper we have done homology modeling of alsin2 protein using multiple templates (3KCI_A, 4LIM_A, 402W_A, 4D9S_A, and 4DNV_A) designed using the Prime program in Schrödinger software. Further modeled structure is used to identify effective binding sites on the basis of structural and physical properties using sitemap program in Schrödinger software, structural and function analysis is done by using Prosite and ExPASy server that gives insight into conserved domains and motifs that can be used for protein classification. This paper summarizes the structural, functional and binding site property of alsin2 protein. These binding sites can be potential drug target sites and can be used for docking studies.

Keywords: ALS, binding site, homology modeling, neuronal degeneration

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: stochastic models, ARIMA, extreme streamflow, Karkheh river

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Authors: Wasi Khan, Suboohi Shervani, Swaleha Naseem, Mohd. Shoeb, J. A. Khan, B. R. Singh, A. H. Naqvi

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We have successfully synthesized ZnO/TiO2 nanocomposite using a two-step solochemical synthesis method. The influence of annealing temperature on microstructural, optical, anticandidal, photocatalytic activities and dielectric properties were investigated. X-ray diffraction (XRD) and scanning electron microscopy (SEM) show the formation of nanocomposite and uniform surface morphology of all samples. The UV-Vis spectra indicate decrease in band gap energy with increase in annealing temperature. The anticandidal activity of ZnO/TiO2 nanocomposite was evaluated against MDR C. albicans 077. The in-vitro killing assay revealed that the ZnO/TiO2 nanocomposite efficiently inhibit the growth of the C. albicans 077. The nanocomposite also exhibited the photocatalytic activity for the degradation of methyl orange as a function of time at 465 nm wavelength. The electrical behaviour of composite has been studied over a wide range of frequencies at room temperature using complex impedance spectroscopy. The dielectric constants, dielectric loss and ac conductivity (σac) were studied as the function of frequency, which have been explained by ‘Maxwell Wagner Model’. The data reveals that the dielectric constant and loss (tanδ) exhibit the normal dielectric behavior and decreases with the increase in frequency.

Keywords: ZnO/TiO2 nanocomposites, SEM, photocatalytic activity, dielectric properties

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Authors: Bin Wang, Jian Kang

Abstract:

After years of development, the study of soundscape has been refined to the types of urban space and building. Traffic complex takes traffic function as the core, with obvious design features of architectural space combination and traffic streamline. The acoustic environment is strongly characterized by function, space, material, user and other factors. Traffic complex integrates various functions of business, accommodation, entertainment and so on. It has various forms, complex and varied experiences, and its acoustic environment is turned rich and interesting with distribution and coordination of various functions, division and unification of the mass, separation and organization of different space and the cross and the integration of multiple traffic flow. In this study, it made field recordings of each space of various traffic complex, and extracted and analyzed different acoustic elements, including changes in sound pressure, frequency distribution, steady sound source, sound source information and other aspects, to make cluster analysis of each independent traffic complex buildings. It divided complicated traffic complex building space into several typical sound space from acoustic environment perspective, mainly including stable sound space, high-pressure sound space, rhythm sound space and upheaval sound space. This classification can further deepen the study of subjective evaluation and control of the acoustic environment of traffic complex.

Keywords: soundscape, traffic complex, cluster analysis, classification

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Authors: W. K. Zahra, M. A. El-Beltagy, R. R. Elkhadrawy

Abstract:

So many practical problems in science and technology developed over the past decays. For instance, the mathematical boundary layer theory or the approximation of solution for different problems described by differential equations. When such problems consider large or small parameters, they become increasingly complex and therefore require the use of asymptotic methods. In this work, we consider the singularly perturbed boundary value problems which contain very small parameters. Moreover, we will consider these perturbation parameters as random variables. We propose a numerical method to solve this kind of problems. The proposed method is based on an exponential spline, Shishkin mesh discretization, and polynomial chaos expansion. The polynomial chaos expansion is used to handle the randomness exist in the perturbation parameter. Furthermore, the Monte Carlo Simulations (MCS) are used to validate the solution and the accuracy of the proposed method. Numerical results are provided to show the applicability and efficiency of the proposed method, which maintains a very remarkable high accuracy and it is ε-uniform convergence of almost second order.

Keywords: singular perturbation problem, polynomial chaos expansion, Shishkin mesh, two small parameters, exponential spline

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Authors: Yan Li, Yujiang Gao

Abstract:

Passengers are the main users of the airport. Whether the travel experience of passengers in the airport is comfortable or not is an important indicator for evaluating the reasonableness of airport design. Taking the Terminal 3 of Beijing Capital International Airport as an example, this paper analyzes the airport’s solution to the problem of passengers’ inconvenience caused by lost directions, excessive congestion, and excessively long streamlines during passenger use. First of all, by using the method of analyzing the design of architectural function streamlines, the design of interior spaces of buildings, and the interrelationship between interior design and passenger experience, it was first concluded that the airport is capable of performing the two major problems of easy disorientation and excessive congestion. Later, by using the method of analyzing architectural function streamlines and collecting passenger experience evaluations, it was concluded that the airport could not solve the inconvenience caused by excessively long streamlines to passengers. Finally came to the conclusion that the airport design meets the demand in terms of the overall design of the passenger experience, but the boarding line is still relatively long and some fly in the ointment.

Keywords: passengers’ experience, terminal 3 of Beijing capital international airport, lost directions, excessive congestion, excessively long streamlines

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

Abstract:

Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: local nonlinear estimation, LWPR algorithm, online training method, locally weighted projection regression method

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Authors: Emmanuel Ifeanyi Ugwu

Abstract:

Calcium Sulphide which is one of Chalcogenide group of thin films has been analyzed in this work using a theoretical approach in which a scalar wave was propagated through the material thin film medium deposited on a glass substrate with the assumption that the dielectric medium has homogenous reference dielectric constant term, and a perturbed dielectric function, representing the deposited thin film medium on the surface of the glass substrate as represented in this work. These were substituted into a defined scalar wave equation that was solved first of all by transforming it into Volterra equation of second type and solved using the method of separation of variable on scalar wave and subsequently, Green’s function technique was introduced to obtain a model equation of wave propagating through the thin film that was invariably used in computing the propagated field, for different input wavelengths representing UV, Visible and Near-infrared regions of field considering the influence of the dielectric constants of the thin film on the propagating field. The results obtained were used in turn to compute the band gaps, solid state and optical properties of the thin film.

Keywords: scalar wave, dielectric constant, calcium sulphide, solid state, optical properties

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Authors: Sahar Jahani, Meryem Ayse Yucel, David Boas, Seyed Kamaledin Setarehdan

Abstract:

Near-infrared spectroscopy allows monitoring of oxy- and deoxy-hemoglobin concentration changes associated with hemodynamic response function (HRF). HRF is usually affected by natural physiological hemodynamic (systemic interferences) which occur in all body tissues including brain tissue. This makes HRF extraction a very challenging task. In this study, we used Kalman filter based on a general linear model (GLM) of brain activity to define the proportion of systemic interference in the brain hemodynamic. The performance of the proposed algorithm is evaluated in terms of the peak to peak error (Ep), mean square error (MSE), and Pearson’s correlation coefficient (R2) criteria between the estimated and the simulated hemodynamic responses. This technique also has the ability of real time estimation of single trial functional activations as it was applied to classify finger tapping versus resting state. The average real-time classification accuracy of 74% over 11 subjects demonstrates the feasibility of developing an effective functional near infrared spectroscopy for brain computer interface purposes (fNIRS-BCI).

Keywords: hemodynamic response function, functional near-infrared spectroscopy, adaptive filter, Kalman filter

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