Search results for: penalty modified barrier function method

Authors: Ayse Inel Manav, Saliha Bozdogan Yesilot, Pinar Yesil Demirci, Gursel Oztunc

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Introduction: This study was conducted with a view to evaluating cognitive function level, depression, and quality of life of elderly people living in a nursing home. Methods: This study, which is cross-sectional and descriptive in nature, was conducted in the Nursing and Rehabilitation Center for the Elderly in Adana/Turkey between 1st of May and 1st of August, 2016. The participants included 118 elderly people who were chosen using simple random sampling method. The data were collected using the Personal Information Form, the Standardized Mini Mental State Exam (SMMSE), the Geriatric Depression Scale (GDS), and the World Health Organization Quality of Life-OLD (WHOQOL-OLD) module. The data were analyzed using IBM SPSS Statistics 22 (IBM, SPSS, Turkey) program. Results: Of all the participants, 36,4% (n=43) were female, 63,6% (n=75) were male, and average age was 74,08 ± 8,23 years. The participants’ SMMSE mean score was found 20,37 ± 7,08, GDS mean score was 14,92 ± 4,29, and WHOQOL-OLD module mean score was 69,76 ± 11,54. There was a negative, significant relationship between SMMSE and GDS scores, a positive relationship between WHOQOL-OLD module total scores and a negative, significant relationship between GDS scores and WHOQOL-OLD module total scores. Discussıon and Conclusion: Results showed that more than half of the elderly people living in the nursing home experienced cognitive deterioration and depression; and cognitive state, depression, and quality of life were found to be significantly related to each other.

Keywords: depression, cognitive function level, quality of life

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Authors: I. Domingos, B. Esteves, A. Figueirinha, Luísa P. Cruz-Lopes, J. Ferreira, H. Pereira

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Chromium is one of the most common heavy metals which exist in very high concentrations in wastewater. The removal is very expensive due to the high cost of normal adsorbents. Lignocellulosic materials and mainly treated materials have proven to be a good solution for this problem. Adsorption tests were performed at different pH, different times and with varying concentrations. Results show that is at pH 3 that treated wood absorbs more chromium ranging from 70% (2h treatment) to almost 100% (12 h treatment) much more than untreated wood with less than 40%. Most of the adsorption is made in the first 2-3 hours for untreated and heat treated wood. Modified wood adsorbs more chromium throughout the time. For all the samples, adsorption fitted relatively well the Langmuir model with correlation coefficient ranging from 0.85 to 0.97. The results show that heat treated wood is a good adsorbent ant that this might be a good utilization for sawdust from treating companies.

Keywords: adsorption, chromium, heat treatment, wood modification

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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Authors: Oscar Conrad Pili De Jesus

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In consonance with the UN Convention on Rights for People with Disabilities, countries are mandated to provide a barrier-free environment through adherence to universal design and full participation of persons with disabilities (PWDs) in planning and implementation, but there is little action in incorporating universal design in the public environment. Travelling freely and independently is paramount to the needs of the PWDs to participate in daily activities ahead of them, and it contributes to the advancement of their inclusion in society, in which universal design is a catalyst to provide seamless access and mobility. This study aims to determine the barriers to incorporating the concept of universal design in transportation projects in Southeast Asian countries. Based on a literature review and using the accessible journey chain as a framework, barriers are identified and categorized in the components of public transport within the context of utilization of the transport mode, the built environment within the transport infrastructure, and the first and last miles of travel. Some findings in the study which constitute solutions to creating a barrier-free environment were identified as information to guide the future research agenda in efficiently incorporating universal design in transportation projects in Southeast Asian countries. The study reflected that the focus of most literature is on the built environment, noting that there is a need for future studies to investigate universal design in the context of the public transport component in the active journey chain.

Keywords: public transportation, barriers, universal design, persons with disabilities, accessible journey chain

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Authors: K. Yahia, A. Ghoggal, A. Titaouine, S. E. Zouzou, F. Benchabane

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This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), Inter-turn Short-Circuits Diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

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Authors: Boubaker Fezzani, Ridha Ben Cheikh, Tarek Rouissi

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In this work the original ADM1, implemented in the simulation software package MATLAB/Simulink, was modified and adapted and applied to reproduce the experimental results of the mesophilic anaerobic digestion of Esperto paper industry wastewater in a batch digester. The data set from lab-scale experiment runs were used to calibrate and validate the model. The simulations’ results indicated that the modified ADM1 was able to predict reasonably well the steady state results of gas flows, methane and carbon dioxide contents, pH and total volatile fatty acids (TVFA) observed with all influents concentrations.

Keywords: anaerobic digestion, mathematical modelling, Simulation, ADM1, batch digester, esparto paper industry effluent, mesophilic temperature

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Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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Authors: Ariane C. Lim, Daphne Ashley L. Sze, Kenneth S. Santos

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As women are now given more freedom and choice to pursue employment, the world’s over-all fertility has been decreasing mainly due to the shift in time allocation between working and child-rearing. As such, we study the case of the Philippines, where there exists a decreasing fertility rate and increasing openness for women labor participation. We focused on the distinction between fertility and fecundity, the former being the manifestation of the latter and aim to trace and compare the effects of both fecundity and fertility to women’s employment status through the estimation of the reproduction function and multinomial logistic function. Findings suggest that the perception of women regarding employment opportunities in the Philippines links the negative relationship observed between fertility, fecundity and women’s employment status. Today, there has been a convergence in the traditional family roles of men and women, as both genders now have identical employment opportunities that continue to shape their preferences.

Keywords: multinomial logistic function, tobit, fertility, women employment status, fecundity

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Authors: Giorgio Visentin, Alexei A. Buchachenko

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Recent proposals to use Yb dimer as an optical clock and as a sensor for non-Newtonian gravity imply the knowledge of its interaction potential. Here, the ground-state Born-Oppenheimer Yb₂ potential energy curve is represented by a semi-analytical function, consisting of short- and long-range contributions. For the former, the systematic ab initio all-electron exact 2-component scalar-relativistic CCSD(T) calculations are carried out. Special care is taken to saturate diffuse basis set component with the atom- and bond-centered primitives and reach the complete basis set limit through n = D, T, Q sequence of the correlation-consistent polarized n-zeta basis sets. Similar approaches are used to the long-range dipole and quadrupole dispersion terms by implementing the CCSD(3) polarization propagator method for dynamic polarizabilities. Dispersion coefficients are then computed through Casimir-Polder integration. The semiclassical constraint on the number of the bound vibrational levels known for the ¹⁷⁴Yb isotope is used to scale the potential function. The scaling, based on the most accurate ab initio results, bounds the interaction energy of two Yb atoms within the narrow 734 ± 4 cm⁻¹ range, in reasonable agreement with the previous ab initio-based estimations. The resulting potentials can be used as the reference for more sophisticated models that go beyond the Born-Oppenheimer approximation and provide the means of their uncertainty estimations. The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: ab initio coupled cluster methods, interaction potential, semi-analytical function, ytterbium dimer

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Authors: Kittipong Tripetch

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This paper proposes studies of input impedance of two types of the CMOS active inductor. It derives two input impedance formulas. The first formula is the input impedance of a grounded active inductor. The second formula is an input impedance of floating active inductor. After that, these formulas can be used to simulate magnitude and phase response of input impedance as a function of current consumption with MATLAB. Common mode rejection ratio (CMRR) of a fully differential bandpass amplifier is derived based on superposition principle. CMRR as a function of input frequency is plotted as a function of current consumption

Keywords: grounded active inductor, floating active inductor, fully differential bandpass amplifier

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Authors: Ju-Hong Lee, Yi-Lin Shieh

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Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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Authors: Krupali Mehta, Sandip Bhatt, Umesh Trivedi, Bhavesh Bharatiya, Mukesh Ranjan, Atindra D. Shukla

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Owing to the dominating surface forces and large-scale surface interactions, the nano-scale particles face difficulties in getting suspended in various media. Magnetic nanoparticles of iron oxide offer a great deal of promise due to their ease of preparation, reasonable magnetic properties, low cost and environmental compatibility. We intend to modify the surface of magnetic Fe₂O₃ nanoparticles with selected surface modifying agents using simple and effective single-step chemical reactions in order to enhance dispersibility of magnetic nanoparticles in non-polar media. Magnetic particles were prepared by hydrolysis of Fe²⁺/Fe³⁺ chlorides and their subsequent oxidation in aqueous medium. The dried particles were then treated with Octadecyl quaternary ammonium silane (Terrasil™), stearic acid and gallic acid ester of stearyl alcohol in ethanol separately to yield S-2 to S-4 respectively. The untreated Fe₂O₃ was designated as S-1. The surface modified nanoparticles were then analysed with Dynamic Light Scattering (DLS), Fourier Transform Infrared spectroscopy (FTIR), X-Ray Diffraction (XRD), Thermogravimetric Gravimetric Analysis (TGA) and Scanning Electron Microscopy and Energy dispersive X-Ray analysis (SEM-EDAX). Characterization reveals the particle size averaging 20-50 nm with and without modification. However, the crystallite size in all cases remained ~7.0 nm with the diffractogram matching to Fe₂O₃ crystal structure. FT-IR suggested the presence of surfactants on nanoparticles’ surface, also confirmed by SEM-EDAX where mapping of elements proved their presence. TGA indicated the weight losses in S-2 to S-4 at 300°C onwards suggesting the presence of organic moiety. Hydrophobic character of modified surfaces was confirmed with contact angle analysis, all modified nanoparticles showed super hydrophobic behaviour with average contact angles ~129° for S-2, ~139.5° for S-3 and ~151° for S-4. This indicated that surface modified particles are super hydrophobic and they are easily dispersible in non-polar media. These modified particles could be ideal candidates to be suspended in oil-based fluids, polymer matrices, etc. We are pursuing elaborate suspension/sedimentation studies of these particles in various oils to establish this conjecture.

Keywords: iron nanoparticles, modification, hydrophobic, dispersion

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Authors: Thomas Wimmer, Bernhard Weigand

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The improvement of gas turbine efficiency is one of the main drivers of research and development in the gas turbine market. This has led to elevated gas turbine inlet temperatures beyond the melting point of the utilized materials. The turbine parts need to be actively cooled in order to withstand these harsh environments. However, the usage of compressor air as coolant decreases the overall gas turbine efficiency. Thus, coolant consumption needs to be minimized in order to gain the maximum advantage from higher turbine inlet temperatures. Therefore, sophisticated cooling designs for gas turbine parts aim to minimize coolant mass flow. New design space is accessible as additive manufacturing is maturing to industrial usage for the creation of hot gas flow path parts. By making use of this technology more efficient cooling schemes can be manufacture. In order to find such cooling schemes a generative design method is being developed. It generates cooling schemes randomly which adhere to a set of rules. These assure the sanity of the design. A huge amount of different cooling schemes are generated and implemented in a simulation environment where it is validated. Criteria for the fitness of the cooling schemes are coolant mass flow, maximum temperature and temperature gradients. This way the whole design space is sampled and a Pareto optimum front can be identified. This approach is applied to a flat plate, which resembles a simplified section of a hot gas flow path part. Realistic boundary conditions are applied and thermal barrier coating is accounted for in the simulation environment. The resulting cooling schemes are presented and compared to representative conventional cooling schemes. Further development of this method can give access to cooling schemes with an even better performance having higher complexity, which makes use of the available design space.

Keywords: additive manufacturing, cooling, gas turbine, heat transfer, heat transfer design, optimization

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Authors: M. Babaeipour, M. Vejdanihemmat

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Optical properties of bulk and thin film of 1H-CaAlSi for two directions (1,0,0) and (0,0,1) were studied. The calculations are carried out by Density Functional Theory (DFT) method using full potential. GGA approximation was used to calculate exchange-correlation energy. The calculations are performed by WIEN2k package. The results showed that the absorption edge is shifted backward 0.82eV in the thin film than the bulk for both directions. The static values of the real part of dielectric function for four cases were obtained. The static values of the refractive index for four cases are calculated too. The reflectivity graphs have shown an intensive difference between the reflectivity of the thin film and the bulk in the ultraviolet region.

Keywords: 1H-CaAlSi, absorption, bulk, optical, thin film

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Authors: Lukas Stiburek, Jana Cesnekova, Josef Houstek, Jiri Zeman

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Cellular function depends on mitochondrial function and integrity that is therefore maintained by several classes of proteins possessing chaperone and/or proteolytic activities. In this work, we focused on characterization of LACE1 (lactation elevated 1) function in mitochondrial protein homeostasis maintenance. LACE1 is the human homologue of yeast mitochondrial Afg1 ATPase, a member of SEC18-NSF, PAS1, CDC48-VCP, TBP family. Yeast Afg1 was shown to be involved in mitochondrial complex IV biogenesis, and based on its similarity with CDC48 (p97/VCP) it was suggested to facilitate extraction of polytopic membrane proteins. Here we show that LACE1, which is a mitochondrial integral membrane protein, exists as part of three complexes of approx. 140, 400 and 500 kDa and is essential for maintenance of fused mitochondrial reticulum and lamellar cristae morphology. Using affinity purification of LACE1-FLAG expressed in LACE1 knockdown background we show that the protein physically interacts with mitochondrial inner membrane protease YME1L. We further show that human LACE1 exhibits significant pro-apoptotic activity and that the protein is required for normal function of the mitochondrial respiratory chain. Thus, our work establishes LACE1 as a novel factor with the crucial role in mitochondrial homeostasis maintenance.

Keywords: LACE1, mitochondria, apoptosis, protease

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Authors: Megha, Diksha, Seema Rani, Balwinder Kaur, Harminder Kaur

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Fe₃O₄@SiO₂@SB functionalized magnetic nanoparticles were synthesized and used to detect heavy metal ions such as Pb²⁺, Hg²⁺, and Cd²⁺ in water. The formation of Fe₃O₄@SiO₂@SB nanocatalyst was confirmed by XRD, SEM, TEM, and IR. The simultaneous determination of analyte cations was carried out using square wave anodic stripping voltammetry (SWASV). Investigation and optimisation were done to study how experimental variables affected the performance of the modified magnetic electrode. Pb²⁺, Hg²⁺, and Cd²⁺ were successfully detected using the designed sensor in the presence of various possibly interfering ions. The recovery rate was found to be 97.5% for Pb²⁺, 96.2% for Hg²⁺, 103.5% for Cd²⁺. The electrochemical sensor was also employed to determine the presence of heavy metal ions in drinking water samples, which are well below the World Health Organization (WHO) guidelines.

Keywords: magnetic nanoparticles, heavy metal ions, electrochemical sensor, environmental water samples

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Authors: Rahma Tibigui, Ikram Hadj Said, Rachid Belkada, Dalila Hammoutene

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The vulnerability of industrial facilities is highly concerned with multiple risks from corrosion. The commonly adopted solution is based on the use of organic inhibitors, which are gradually being replaced by environmentally friendly organic inhibitors. In our work, we carried out a quantum chemical study based on the Density Functional Theory (DFT) method at the B3LYP/6-311G (d,p) level of theory. The inhibitory performance of a derivative of the tetrazole molecule has been investigated and reported as a carbon steel-friendly corrosion inhibitor in hydrochloric acid (HCl) medium. The relationship is likely to exist between the molecular structure of this compound as well as its various global reactivity descriptors, and its corrosion inhibition efficiency, which was examined and then discussed. The results show low values of ΔE, which represent strong adsorption of the inhibitor on the steel surface. Moreover, the flat adsorption orientation confirmed the great ability to donate (accept) electrons to (from) steel, fabricating an anchored barrier to prevent steel from corrosion.

Keywords: eco-friendly, corrosion inhibitors, tetrazole, DFT

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Authors: Ewelina Nowak, Anna Wisla-Swider, Krzysztof Danel

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Aqueous suspensions of DNA were illuminated with linearly polarized visible light and ultraviolet for 5, 15, 20 and 40 h. In order to check the nature of modification, DNA interactions were characterized by FTIR spectroscopy. For each illuminated sample, weight average molecular weight and hydrodynamic radius were measured by high pressure size exclusion chromatography. Resulting optical changes for illuminated DNA were investigated using UV-Vis spectra and photoluminescent. Optical properties show potential application in sensors based on modified DNA. Then selected DNA-surfactant complexes were illuminated with electromagnetic radiation for 5h. Molecular structure, optical characteristic were examinated for obtained complexes. Illumination led to changes of complexes physicochemical properties as compared with native DNA. Observed changes were induced by rearrangement of the molecular structure of DNA chains.

Keywords: biopolymers, deoxyribonucleic acid, ionic liquids, linearly polarized visible light, ultraviolet

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Authors: Aiswarea Mathew, Smita Mohanty, Jr., S. K. Nayak

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Polyurethane networks based on castor oil (CO) as a renewable resource polyol were synthesized. Polyurethane/epoxy resin interpenetrating network nanocomposites containing modified montmorillonite organoclay (C30B-PU/EP nanocomposites) were prepared by an in situ intercalation method. The conventional spectroscopic characterization of the synthesized samples using FT-IR confirms the existence of the proposed castor oil based PU structure and also showed that strong interactions existed between C30B and EP/PU matrix. The dispersion degree of C30B in EP/PU matrix was characterized by X-Ray diffraction (XRD) method. Scanning electronic microscopy analysis showed that the interpenetrating process of PU and EP increases the exfoliation degree of C30B, and it improves the compatibility and the phase structure of polyurethane/epoxy resin interpenetrating polymer networks (PU/EP IPNs). The thermal stability improves compared to the polyurethane when the PU/EP IPN is formed. Mechanical properties including the Young’s modulus and tensile strength reflected marked improvement with addition of C30B.

Keywords: castor oil, epoxy, montmorillonite, polyurethane

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Authors: Marwa A. A. Ragab, Hadir M. Maher, Eman I. El-Kimary

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Co-administration of methotrexate (MTX) and aspirin (ASP) can cause a pharmacokinetic interaction and a subsequent increase in blood MTX concentrations which may increase the risk of MTX toxicity. Therefore, it is important to develop a sensitive, selective, accurate and precise method for their simultaneous determination in urine. A new hybrid chemometric method has been applied to the emission response data of the two drugs. Spectrofluorimetric method for determination of MTX through measurement of its acid-degradation product, 4-amino-4-deoxy-10-methylpteroic acid (4-AMP), was developed. Moreover, the acid-catalyzed degradation reaction enables the spectrofluorimetric determination of ASP through the formation of its active metabolite salicylic acid (SA). The proposed chemometric method deals with convolution of emission data using 8-points sin xi polynomials (discrete Fourier functions) after the derivative treatment of these emission data. The first and second derivative curves (D1 & D2) were obtained first then convolution of these curves was done to obtain first and second derivative under Fourier functions curves (D1/FF) and (D2/FF). This new application was used for the resolution of the overlapped emission bands of the degradation products of both drugs to allow their simultaneous indirect determination in human urine. Not only this chemometric approach was applied to the emission data but also the obtained data were subjected to non-parametric linear regression analysis (Theil’s method). The proposed method was fully validated according to the ICH guidelines and it yielded linearity ranges as follows: 0.05-0.75 and 0.5-2.5 µg mL-1 for MTX and ASP respectively. It was found that the non-parametric method was superior over the parametric one in the simultaneous determination of MTX and ASP after the chemometric treatment of the emission spectra of their degradation products. The work combines the advantages of derivative and convolution using discrete Fourier function together with the reliability and efficacy of the non-parametric analysis of data. The achieved sensitivity along with the low values of LOD (0.01 and 0.06 µg mL-1) and LOQ (0.04 and 0.2 µg mL-1) for MTX and ASP respectively, by the second derivative under Fourier functions (D2/FF) were promising and guarantee its application for monitoring the two drugs in patients’ urine samples.

Keywords: chemometrics, emission curves, derivative, convolution, Fourier transform, human urine, non-parametric regression, Theil’s method

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Authors: Asim Olgun, Ali Kara, Vural Butun, Pelin Sevinc, Merve Gungor, Orhan Ornek

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In this study, we investigated the possibility of using waste containing boron impurity (BW) as an adsorbent for the removal of Orange 16 from aqueous solution. Surface properties of the BW, heat treated BW, and diblock copolymer coated BW were examined by using Zeta Meter and scanning electron microscopy (SEM). The polymer modified sample having the highest positive zeta potential was used as an adsorbent. Batch adsorption studies were carried out. The operating variables studied were the initial dye concentration, contact time, solution pH, and adsorbent dosage. It was found that the dye adsorption largely depends on the initial pH of the solution with maximum uptake occurring at pH 3. The adsorption followed pseudo-second-order kinetics and the isotherm fit well to the Langmuir model.

Keywords: zeta potential, adsorption, Orange 16, isotherms

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Authors: Elham Kiyani, S. Mansour Vaezpour, Javad Tavakoli

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In this paper, we first introduce a new distance function in a linear space not necessarily endowed with a topology. The algebraic concepts of interior and closure are useful to study optimization problems without topology. So, we define Q-weak efficient solutions generated by the algebraic interior of a set Q, where Q is not necessarily convex. Studying nonconvex vector optimization is valuable since, for a convex cone K in topological spaces, we have int(K)=cor(K), which means that topological interior of a convex cone K is equal to the algebraic interior of K. Moreover, we used the scalarization technique including the distance function generated by the vectorial closure of a set to characterize these Q-weak efficient solutions. Scalarization is a useful approach for solving vector optimization problems. This technique reduces the optimization problem to a scalar problem which tends to be an optimization problem with a real-valued objective function. For instance, Q-weak efficient solutions of vector optimization problems can be characterized and computed as solutions of appropriate scalar optimization problems. In the convex case, linear functionals can be used as objective functionals of the scalar problems. But in the nonconvex case, we should present a suitable objective function. It is the aim of this paper to present a new distance function that be useful to obtain sufficient and necessary conditions for Q-weak efficient solutions of general optimization problems via scalarization.

Keywords: weak efficient, algebraic interior, vector closure, linear space

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Authors: Pawan S. Nagda, Purnank S. Bhatt, Mit K. Shah

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Earing defect in drawing process is highly undesirable not only because it adds on an additional trimming operation but also because the uneven material flow demands extra care. The objective of this work is to study the earing problem in the Deep Drawing of circular cup and to optimize the blank shape to reduce the earing. A finite element model is developed for 3-D numerical simulation of cup forming process in ABAQUS. Extra-deep-drawing (EDD) steel sheet has been used for simulation. Properties and tool design parameters were used as input for simulation. Earing was observed in the simulated cup and it was measured at various angles with respect to rolling direction. To reduce the earing defect initial blank shape was modified with the help of anisotropy coefficient. Modified blanks showed notable reduction in earing.

Keywords: anisotropy, deep drawing, earing, finite element simulation

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Authors: Kumari Sweta, Ajanta Goswami, Abhilasha Dixit

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Landslide is a geomorphic process that plays an essential role in the evolution of the hill-slope and long-term landscape evolution. But its abrupt nature and the associated catastrophic forces of the process can have undesirable socio-economic impacts, like substantial economic losses, fatalities, ecosystem, geomorphologic and infrastructure disturbances. The estimated fatality rate is approximately 1person /100 sq. Km and the average economic loss is more than 550 crores/year in the Himalayan belt due to landslides. This study presents a comparative performance of a statistical bivariate method and a machine learning technique for landslide susceptibility mapping in and around Dharamshala, Himachal Pradesh. The final produced landslide susceptibility maps (LSMs) with better accuracy could be used for land-use planning to prevent future losses. Dharamshala, a part of North-western Himalaya, is one of the fastest-growing tourism hubs with a total population of 30,764 according to the 2011 census and is amongst one of the hundred Indian cities to be developed as a smart city under PM’s Smart Cities Mission. A total of 209 landslide locations were identified in using high-resolution linear imaging self-scanning (LISS IV) data. The thematic maps of parameters influencing landslide occurrence were generated using remote sensing and other ancillary data in the GIS environment. The landslide causative parameters used in the study are slope angle, slope aspect, elevation, curvature, topographic wetness index, relative relief, distance from lineaments, land use land cover, and geology. LSMs were prepared using information value (Info Val), and Fuzzy Expert System (FES) models. Info Val is a statistical bivariate method, in which information values were calculated as the ratio of the landslide pixels per factor class (Si/Ni) to the total landslide pixel per parameter (S/N). Using this information values all parameters were reclassified and then summed in GIS to obtain the landslide susceptibility index (LSI) map. The FES method is a machine learning technique based on ‘mean and neighbour’ strategy for the construction of fuzzifier (input) and defuzzifier (output) membership function (MF) structure, and the FR method is used for formulating if-then rules. Two types of membership structures were utilized for membership function Bell-Gaussian (BG) and Trapezoidal-Triangular (TT). LSI for BG and TT were obtained applying membership function and if-then rules in MATLAB. The final LSMs were spatially and statistically validated. The validation results showed that in terms of accuracy, Info Val (83.4%) is better than BG (83.0%) and TT (82.6%), whereas, in terms of spatial distribution, BG is best. Hence, considering both statistical and spatial accuracy, BG is the most accurate one.

Keywords: bivariate statistical techniques, BG and TT membership structure, fuzzy expert system, information value method, machine learning technique

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Authors: Bader Alruwaili, Surajit Ray

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Finite mixtures are a flexible and powerful tool that can be used for univariate and multivariate distributions, and a wide range of research analysis has been conducted based on the multivariate normal mixture and multivariate of a t-mixture. Determining the number of modes is an important activity that, in turn, allows one to determine the number of homogeneous groups in a population. Our work currently being carried out relates to the study of the modality of the skew normal distribution in the univariate and multivariate cases. For the skew normal distribution, the aims are associated with studying the modality of the skew normal distribution and providing the ridgeline, the ridgeline elevation function, the $\Pi$ function, and the curvature function, and this will be conducive to an exploration of the number and location of mode when mixing the two components of skew normal distribution. The subsequent objective is to apply these results to the application of real world data sets, such as flow cytometry data.

Keywords: mode, modality, multivariate skew normal, finite mixture, number of mode

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Authors: Paul Shize Li, Frank Alber

Abstract:

A fundamental task of clinical genomics is to unravel the functions of genes and their associations with disorders. Although experimental biology has made efforts to discover and elucidate the molecular mechanisms of individual genes in the past decades, still about 40% of human genes have unknown functions, not to mention the diseases they may be related to. For those biologists who are interested in a particular gene with unknown functions, a powerful computational method tailored for inferring the functions and disease relevance of uncharacterized genes is strongly needed. Studies have shown that genes strongly linked to each other in multiple biological networks are more likely to have similar functions. This indicates that the densely connected subgraphs in multiple biological networks are useful in the functional and phenotypic annotation of uncharacterized genes. Therefore, in this work, we have developed an integrative network approach to identify the frequent local clusters, which are defined as those densely connected subgraphs that frequently occur in multiple biological networks and consist of the query gene that has few or no disease or function annotations. This is a local clustering algorithm that models multiple biological networks sharing the same gene set as a three-dimensional matrix, the so-called tensor, and employs the tensor-based optimization method to efficiently find the frequent local clusters. Specifically, massive public gene expression data sets that comprehensively cover dynamic, physiological, and environmental conditions are used to generate hundreds of gene co-expression networks. By integrating these gene co-expression networks, for a given uncharacterized gene that is of biologist’s interest, the proposed method can be applied to identify the frequent local clusters that consist of this uncharacterized gene. Finally, those frequent local clusters are used for function and disease annotation of this uncharacterized gene. This local tensor clustering algorithm outperformed the competing tensor-based algorithm in both module discovery and running time. We also demonstrated the use of the proposed method on real data of hundreds of gene co-expression data and showed that it can comprehensively characterize the query gene. Therefore, this study provides a new tool for annotating the uncharacterized genes and has great potential to assist clinical genomic diagnostics.

Keywords: local tensor clustering, query gene, gene co-expression network, gene annotation

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Authors: Fatemeh Sadeghi, Peyman Sheikhzadeh

Abstract:

Introduction: Block Sequential Regularized Expectation Maximization (BSREM) reconstruction algorithm was recently developed to suppress excessive noise by applying a relative difference penalty. The aim of this study was to investigate the effect of various strengths of noise penalization factor in the BSREM algorithm under different acquisition duration and lesion sizes in order to determine an optimum penalty factor by considering both quantitative and qualitative image evaluation parameters in clinical uses. Materials and Methods: The NEMA IQ phantom and 15 clinical whole-body patients with prostate cancer were evaluated. Phantom and patients were injected withGallium-68 Prostate-Specific Membrane Antigen(68 Ga-PSMA)and scanned on a non-time-of-flight Discovery IQ Positron Emission Tomography/Computed Tomography(PET/CT) scanner with BGO crystals. The data were reconstructed using BSREM with a β-value of 100-500 at an interval of 100. These reconstructions were compared to OSEM as a widely used reconstruction algorithm. Following the standard NEMA measurement procedure, background variability (BV), recovery coefficient (RC), contrast recovery (CR) and residual lung error (LE) from phantom data and signal-to-noise ratio (SNR), signal-to-background ratio (SBR) and tumor SUV from clinical data were measured. Qualitative features of clinical images visually were ranked by one nuclear medicine expert. Results: The β-value acts as a noise suppression factor, so BSREM showed a decreasing image noise with an increasing β-value. BSREM, with a β-value of 400 at a decreased acquisition duration (2 min/ bp), made an approximately equal noise level with OSEM at an increased acquisition duration (5 min/ bp). For the β-value of 400 at 2 min/bp duration, SNR increased by 43.7%, and LE decreased by 62%, compared with OSEM at a 5 min/bp duration. In both phantom and clinical data, an increase in the β-value is translated into a decrease in SUV. The lowest level of SUV and noise were reached with the highest β-value (β=500), resulting in the highest SNR and lowest SBR due to the greater noise reduction than SUV reduction at the highest β-value. In compression of BSREM with different β-values, the relative difference in the quantitative parameters was generally larger for smaller lesions. As the β-value decreased from 500 to 100, the increase in CR was 160.2% for the smallest sphere (10mm) and 12.6% for the largest sphere (37mm), and the trend was similar for SNR (-58.4% and -20.5%, respectively). BSREM visually was ranked more than OSEM in all Qualitative features. Conclusions: The BSREM algorithm using more iteration numbers leads to more quantitative accuracy without excessive noise, which translates into higher overall image quality and lesion detectability. This improvement can be used to shorter acquisition time.

Keywords: BSREM reconstruction, PET/CT imaging, noise penalization, quantification accuracy

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Authors: Masataka Inada, Masanao Kinoshita, Nobuaki Matsumori

Abstract:

It has been demonstrated that lipid molecules in biological membranes are responsible for the functionalization and structuration of membrane proteins. However, it is still unclear how the interaction of lipid molecules with membrane proteins is correlated with the function of the membrane proteins. Here we first developed an evaluation method for the interaction between membrane proteins and lipid molecules via surface plasmon resonance (SPR) analysis. Bacteriorhodopsin (bR), which was obtained by the culture of halobacteria, was used as a membrane protein. We prepared SPR sensor chips covered with self-assembled monolayer containing mercaptocarboxylic acids, and immobilized bR onto them. Then, we evaluated the interactions with various lipids that have different structures. As a result, the halobacterium-specific glycolipid S-TGA-1 was found to have much higher affinity with bRs than other lipids. This is probably due to not only hydrophobic and electrostatic interactions but also hydrogen bonds with sugar moieties in the glycolipid. Next, we analyzed the roles of the lipid in the structuration and functionalization of bR. CD analysis showed that S-TGA-1 could promote trimerization of bR monomers more efficiently than any other lipids. Flash photolysis further indicated that bR trimers formed by S-TGA-1 reproduced the photocyclic activity of bR in purple membrane, halobacterium-membrane. These results suggest that S-TGA-1 promotes trimerization of bR through strong interactions and consequently fulfills the bR’s function efficiently.

Keywords: membrane protein, lipid, interaction, bacteriorhodopsin, glycolipid

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Authors: Sani M. Lawal, Idris Musa, Aliyu D. Usman

Abstract:

The Pareto approach of optimal solutions in a search space that evolved in multi-objective optimization problems is adopted in this paper, which stands for a set of solutions in the search space. This paper aims at presenting an optimal placement of Distributed Generation (DG) in radial distribution networks with an optimal size for minimization of power loss and voltage deviation as well as maximizing voltage profile of the networks. And these problems are formulated using particle swarm optimization (PSO) as a constraint nonlinear optimization problem with both locations and sizes of DG being continuous. The objective functions adopted are the total active power loss function and voltage deviation function. The multiple nature of the problem, made it necessary to form a multi-objective function in search of the solution that consists of both the DG location and size. The proposed PSO algorithm is used to determine optimal placement and size of DG in a distribution network. The output indicates that PSO algorithm technique shows an edge over other types of search methods due to its effectiveness and computational efficiency. The proposed method is tested on the standard IEEE 34-bus and validated with 33-bus test systems distribution networks. Results indicate that the sizing and location of DG are system dependent and should be optimally selected before installing the distributed generators in the system and also an improvement in the voltage profile and power loss reduction have been achieved.

Keywords: distributed generation, pareto, particle swarm optimization, power loss, voltage deviation

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Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

Abstract:

Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic

Procedia PDF Downloads 443