Search results for: predictive density functions

Authors: Samir Hmaimou, Marouane Ait Lahcen, Mohamed Adardour, Mohamed Maatallah, Abdesselam Baouid

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Due to (3 + 2) cycloaddition and condensation reaction, a wide range of synthetic routes can be used to obtain biologically active heterocyclic compounds. Condensation and (3+2) cycloaddition reactions in heterocyclic syntheses are versatile due to the wide variety of possible combinations of several atoms of the reactants. In this article, we first outline the synthesis of benzodiazepine 4 with two dipolarophilic centers (C=C and C=N) by condensation reaction. Then, we use it for cycloaddition reactions (3+2) with nitrile oxides to prepare oxadiazole-benzodiazepines and pyrazole-benzodiazepine compounds. ¹H and ¹³C NMR are used to establish all the structures of the synthesized products. These condensation and cycloaddition reactions were then analyzed using density functional theory (DFT) calculations at the B3LYP/6-311G(d,p) theoretical level. In this study, the mechanism of the one-step cycloaddition reaction was investigated. Molecular electrostatic potential (MEP) was used to identify the electrophilic and nucleophilic attack sites of the molecules studied. Additionally, Fukui investigations (electrophilic f- and nucleophilic f+) in the various reaction centers of the reactants demonstrate that, whether in the condensation reaction or cycloaddition, the reaction proceeds through the atomic centers with the most important Fukui functions, which is in full agreement with experimental observations. In the condensation reaction, thermodynamic control of regio, chemo, and stereoselectivity is observed, while those of cycloaddition are subject to kinetic control.

Keywords: cycloaddition reaction, regioselectivity, mechanism reaction, NMR analysis

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Authors: Seyedeh Fatemeh Nabavi, Hamid Dalir, Anooshiravan Farshidianfar

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Laser welding is pivotal in modern manufacturing, offering unmatched precision, speed, and efficiency. Its versatility in minimizing heat-affected zones, seamlessly joining dissimilar materials, and working with various metals makes it indispensable for crafting intricate automotive components. Integration into automated systems ensures consistent delivery of high-quality welds, thereby enhancing overall production efficiency. Noteworthy are the safety benefits of laser welding, including reduced fumes and consumable materials, which align with industry standards and environmental sustainability goals. As the automotive sector increasingly demands advanced materials and stringent safety and quality standards, laser welding emerges as a cornerstone technology. A comprehensive model encompassing thermal dynamic and characteristics models accurately predicts geometrical, metallurgical, and mechanical aspects of the laser beam welding process. Notably, Model 2 showcases exceptional accuracy, achieving remarkably low error rates in predicting primary and secondary dendrite arm spacing (PDAS and SDAS). These findings underscore the model's reliability and effectiveness, providing invaluable insights and predictive capabilities crucial for optimizing welding processes and ensuring superior productivity, efficiency, and quality in the automotive industry.

Keywords: laser welding process, geometrical characteristics, mechanical characteristics, metallurgical characteristics, comprehensive model, thermal dynamic

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Authors: Elyas Shivanian

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In this paper, the spectral meshless radial point interpolation (SMRPI) technique is applied to the Cauchy problems of two-dimensional elliptic PDEs in doubly connected domains. It is obtained the unknown data on the inner boundary of the domain while overspecified boundary data are imposed on the outer boundary of the domain by using the SMRPI. Shape functions, which are constructed through point interpolation method using the radial basis functions, help us to treat problem locally with the aim of high order convergence rate. In this way, localization in SMRPI can reduce the ill-conditioning for Cauchy problem. Furthermore, we improve previous results and it is revealed the SMRPI is more accurate and stable by adding strong perturbations.

Keywords: cauchy problem, doubly connected domain, radial basis function, shape function

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Authors: Haci Mehmet Guzey, Levent Acar

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In this paper, a novel decentralized controller is developed for linear systems with nonlinear unknown interconnections. A model linear decoupled system is assigned for each system. By using the difference actual and model state dynamics, the problem is formulated as inverse problem. Then, the interconnected dynamics are approximated by using Galerkin’s expansion method for inverse problems. Two different sets of orthogonal basis functions are utilized to approximate the interconnected dynamics. Approximated interconnections are utilized in the controller to cancel the interconnections and decouple the systems. Subsequently, the interconnected systems behave as a collection of decoupled systems.

Keywords: decentralized control, inverse problems, large scale systems, nonlinear interconnections, basis functions, system identification

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Authors: Ella Tyuryumina, Alexey Neznanov

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This study is an attempt to obtain reliable data on the natural history of breast cancer growth. We analyze the opportunities for using classical mathematical models (exponential and logistic tumor growth models, Gompertz and von Bertalanffy tumor growth models) to try to describe growth of the primary tumor and the secondary distant metastases of human breast cancer. The research aim is to improve predicting accuracy of breast cancer progression using an original mathematical model referred to CoMPaS and corresponding software. We are interested in: 1) modelling the whole natural history of the primary tumor and the secondary distant metastases; 2) developing adequate and precise CoMPaS which reflects relations between the primary tumor and the secondary distant metastases; 3) analyzing the CoMPaS scope of application; 4) implementing the model as a software tool. The foundation of the CoMPaS is the exponential tumor growth model, which is described by determinate nonlinear and linear equations. The CoMPaS corresponds to TNM classification. It allows to calculate different growth periods of the primary tumor and the secondary distant metastases: 1) ‘non-visible period’ for the primary tumor; 2) ‘non-visible period’ for the secondary distant metastases; 3) ‘visible period’ for the secondary distant metastases. The CoMPaS is validated on clinical data of 10-years and 15-years survival depending on the tumor stage and diameter of the primary tumor. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer growth models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. The CoMPaS model and predictive software: a) fit to clinical trials data; b) detect different growth periods of the primary tumor and the secondary distant metastases; c) make forecast of the period of the secondary distant metastases appearance; d) have higher average prediction accuracy than the other tools; e) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoMPaS: the number of doublings for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of the secondary distant metastases. The CoMPaS enables, for the first time, to predict ‘whole natural history’ of the primary tumor and the secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on the primary tumor sizes. Summarizing: a) CoMPaS describes correctly the primary tumor growth of IA, IIA, IIB, IIIB (T1-4N0M0) stages without metastases in lymph nodes (N0); b) facilitates the understanding of the appearance period and inception of the secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, metastases in lymph nodes, primary tumor, survival

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Authors: A. D. Loureiro, L. Ventura

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Exposure to high-energy blue light has been strongly linked to the development of some eye diseases, such as age-related macular degeneration. Over the past few years, people have become more and more concerned about eye damage from blue light and how it can be prevented. We developed a prototype that allows users to self-check the blue light protection of their sunglasses and determines if the protection is adequate. Weighting functions approximating those defined in ISO 12312-1 were used to measure the luminous transmittance and blue light transmittance of sunglasses. The blue light transmittance value must be less than 1.2 times the luminous transmittance to be considered adequate. The prototype consists of a Golden Dragon Ultra White LED from OSRAM and a TCS3472 photodetector from AMS TAOS. Together, they provide four transmittance values weighted with different functions. These four transmittance values were then linearly combined to produce transmittance values with weighting functions close to those defined in ISO 12312-1 for luminous transmittance and for blue light transmittance. To evaluate our prototype, we used a VARIAN Cary 5000 spectrophotometer, a gold standard in the field, to measure the luminous transmittance and the blue light transmittance of 60 sunglasses lenses. (and Bland-Altman analysis was performed) Bland-Altman analysis was performed and showed non-significant bias and narrow 95% limits of agreement within predefined tolerances for both luminous transmittance and blue light transmittance. The results show that the prototype is a viable means of providing blue light protection information to the general public and a quick and easy way for industry and retailers to test their products. In addition, our prototype plays an important role in educating the public about a feature to look for in sunglasses before purchasing.

Keywords: blue light, sunglasses, eye protective devices, transmittance measurement, standards, ISO 12312-1

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Authors: Zahra Ashraf

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Flax and pumpkin seeds are a rich source of unsaturated fatty acids, antioxidants and fiber, known to have anti-atherogenic properties. Hypercholesterolemia is a state characterized by the elevated level of cholesterol in the blood. This research was designed to study the effect of flax and pumpkin seeds powder mixture on hypercholesterolemia and body weight. Rat’s species were selected as human representative. Thirty male albino rats were divided into three groups: a control group, a CD-chol group (control diet+cholesterol) fed with 1.5% cholesterol and FP-chol group (flaxseed and pumpkin seed powder+ cholesterol) fed with 1.5% cholesterol. Flax and pumpkin seed powder mixed at proportion of (5/1) (omega-3 and omega-6). Blood samples were collected to examine lipid profile and body weight was also measured. Thus the data was subjected to analysis of variance. In CD-chol group, body weight, total cholesterol TC, triacylglycerides TG in plasma, plasma LDL-C, ratio significantly increased with a decrease in plasma HDL (good cholesterol). In FP-chol group lipid parameters and body weights were decreased significantly with an increase in HDL and decrease in LDL (bad cholesterol). The mean values of body weight, total cholesterol, triglycerides, low density lipoprotein and high density lipoproteins in FP-chol group were 240.66±11.35g, 59.60±2.20mg/dl, 50.20±1.79 mg/dl, 36.20±1.62mg/dl, 36.40±2.20 mg/dl, respectively. Flaxseed and pumpkin seeds powder mixture showed reduction in body weight, serum cholesterol, low density lipoprotein and triglycerides. While significant increase was shown in high density lipoproteins when given to hypercholesterolemic rats. Our results suggested that flax and pumpkin seed mixture has hypocholesterolemic effects which were probably mediated by polyunsaturated fatty acids (omega-3 and omega-6) present in seed mixture.

Keywords: hypercolesterolemia, omega 3 and omega 6 fatty acids, cardiovascular diseases

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Authors: Farah Marsusi, Mohammad Qasemnazhand

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Density-functional theory (DFT) was applied to investigate the geometry and electronic properties H-terminated Si-fullerene (Si-fullerane). Natural bond orbital (NBO) analysis confirms sp3 hybridization nature of Si-Si bonds in Si-fulleranes. Quantum confinement effect (QCE) does not affect band gap (BG) so strongly in the size between 1 to 1.7 nm. In contrast, the geometry and symmetry of the cage have significant influence on BG. In contrast to their carbon analogues, pentagon rings increase the stability of the cages. Functionalized Si-cages are stable and can be chemically very active. The electronic properties are highly sensitive to the surface chemistry via functionalization with different chemical groups. As a result, BGs and chemical activities of these cages can be drastically tuned through the chemistry of the surface.

Keywords: density functional theory, sila-fullerens, NBO analysis, opto-electronic properties

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Authors: Hanizam Awang, Mohammed Zuhear Al-Mulali

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In this study, the possibility of using unground oil palm ash (UOPA) for producing foamed concrete is investigated. The UOPA used in this study is produced by incinerating palm oil biomass at a temperature exceeding 1000ºC. A semi-structural density of 1300kg/m3 was used with filler to binder ratio of 1.5 and preliminary water to binder ratio of 0.45. Cement was replaced by UOPA at replacement levels of 0, 25, 35, 45, 55 and 65% by weight of binder. Properties such as density, compressive strength, drying shrinkage and water absorption were investigated to the age of 90 days. The mix with a 35% of UOPA content was chosen to be used as the base material of a newly designed interlocking, mortar-less block system.

Keywords: foamed concrete, oil palm ash, strength, interlocking block

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Authors: Nadia Ezzat Al-Kirbasee, Ahlam Hussein Hassan, Shatha Raheem Helal Alhimidi, Doaa Ezzat Al-Kirbasee, Muhsen Abood Muhsen Al-Ibadi

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Through DFT/QTAIM calculations, we have provided new insights into the nature of the M-M, M-H, M-O, and M-C bonds of the (Cp*Ru)n(Cp*Os)3−n(μ3-O)2(μ-H)(Cp* = η5-C5Me5, n= 3,2,1,0). The topological analysis of the electron density reveals important details of the chemical bonding interactions in the clusters. Calculations confirm the absence of bond critical points (BCP) and the corresponding bond paths (BP) between Ru-Ru, Ru-Os, and Os-Os. The position of bridging hydrides and Oxo atoms coordinated to Ru-Ru, Ru-Os, and Os-Os determines the distribution of the electron densities and which strongly affects the formation of the bonds between these transition metal atoms. On the other hand, the results confirm that the four clusters contain a 6c–12e and 4c–2e bonding interaction delocalized over M3(μ-H)(μ-O)2 and M3(μ-H), respectively, as revealed by the non-negligible delocalization indexes calculations. The small values for electron density ρ(b) above zero, together with the small values, again above zero, for laplacian ∇2ρ(b) and the small negative values for total energy density H(b) are shown by the Ru-H, Os-H, Ru-O, and Os-O bonds in the four clusters are typical of open shell interactions. Also, the topological data for the bonds between Ru and Os atoms with the C atoms of the pentamethylcyclopentadienyl (Cp*) ring ligands are basically similar and show properties very consistent with open shell interactions in the QTAIM classification.

Keywords: metal-metal and metal-ligand interactions, organometallic complexes, topological analysis, DFT and QTAIM analyses

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Authors: Mehdi Montakhabrazlighi, Ercan Balikci

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The neural network (NN) method is applied to alloy development of single crystal Ni-base Superalloys with low density and improved mechanical strength. A set of 1200 dataset which includes chemical composition of the alloys, applied stress and temperature as inputs and density and time to rupture as outputs is used for training and testing the network. Thermodynamic phase diagram modeling of the screened alloys is performed with Thermocalc software to model the equilibrium phases and also microsegregation in solidification processing. The model is first trained by 80% of the data and the 20% rest is used to test it. Comparing the predicted values and the experimental ones showed that a well-trained network is capable of accurately predicting the density and time to rupture strength of the Ni-base superalloys. Modeling results is used to determine the effect of alloying elements, stress, temperature and gamma-prime phase volume fraction on rupture strength of the Ni-base superalloys. This approach is in line with the materials genome initiative and integrated computed materials engineering approaches promoted recently with the aim of reducing the cost and time for development of new alloys for critical aerospace components. This work has been funded by TUBITAK under grant number 112M783.

Keywords: neural network, rupture strength, superalloy, thermocalc

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Authors: Helene Thieblemont, Fariborz Haghighat

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Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expand the use of renewable energies in buildings. To provide a high building thermal performance, the energy storage system has to be properly controlled to insure a good energy performance while maintaining a satisfactory thermal comfort for building’s occupant. In the case of passive discharge storages, defining in advance the required amount of energy is required to avoid overheating in the building. Consequently, anticipatory supervisory control strategies have been developed forecasting future energy demand and production to coordinate systems. Anticipatory supervisory control strategies are based on some predictions, mainly of the weather forecast. However, if the forecasted hourly outdoor temperature may be found online with a high accuracy, solar radiations predictions are most of the time not available online. To estimate them, this paper proposes an advanced approach based on the forecast of weather conditions. Several methods to correlate hourly weather conditions forecast to real hourly solar radiations are compared. Results show that using weather conditions forecast allows estimating with an acceptable accuracy solar radiations of the next day. Moreover, this technique allows obtaining hourly data that may be used for building models. As a result, this solar radiation prediction model may help to implement model-based controller as Model Predictive Control.

Keywords: anticipatory control, model predictive control, solar radiation forecast, thermal storage

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Authors: H. Yazdani, K. Ghorbanian

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This paper deals with modeling and simulation of the plasma actuator with OpenFOAM. Plasma actuator is one of the newest devices in flow control techniques which can delay separation by inducing external momentum to the boundary layer of the flow. The effects of the plasma actuators on the external flow are incorporated into Navier-Stokes computations as a body force vector which is obtained as a product of the net charge density and the electric field. In order to compute this body force vector, the model solves two equations: One for the electric field due to the applied AC voltage at the electrodes and the other for the charge density representing the ionized air. The simulation result is compared to the experimental and typical values which confirms the validity of the modeling.

Keywords: active flow control, flow-field, OpenFOAM, plasma actuator

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Authors: Alexander Heckman, Rohan Goswami, Zachi Attia, Paul Friedman, Peter Noseworthy, Demilade Adedinsewo, Pablo Moreno-Franco, Rickey Carter, Tathagat Narula

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Background: Postoperative atrial fibrillation (POAF) is associated with adverse health consequences, higher costs, and longer hospital stays. Utilizing existing predictive models that rely on clinical variables and circulating biomarkers, multiple societies have published recommendations on the treatment and prevention of POAF. Although reasonably practical, there is room for improvement and automation to help individualize treatment strategies and reduce associated complications. Methods and Results: In this retrospective cohort study of solid organ transplant recipients, we evaluated the diagnostic utility of a previously developed AI-based ECG prediction for silent AF on the development of POAF within 30 days of transplant. A total of 2261 non-cardiac transplant patients without a preexisting diagnosis of AF were found to have a 5.8% (133/2261) incidence of POAF. While there were no apparent sex differences in POAF incidence (5.8% males vs. 6.0% females, p=.80), there were differences by race and ethnicity (p<0.001 and 0.035, respectively). The incidence in white transplanted patients was 7.2% (117/1628), whereas the incidence in black patients was 1.4% (6/430). Lung transplant recipients had the highest incidence of postoperative AF (17.4%, 37/213), followed by liver (5.6%, 56/1002) and kidney (3.6%, 32/895) recipients. The AUROC in the sample was 0.62 (95% CI: 0.58-0.67). The relatively low discrimination may result from undiagnosed AF in the sample. In particular, 1,177 patients had at least 1 AI-ECG screen for AF pre-transplant above .10, a value slightly higher than the published threshold of 0.08. The incidence of POAF in the 1104 patients without an elevated prediction pre-transplant was lower (3.7% vs. 8.0%; p<0.001). While this supported the hypothesis that potentially undiagnosed AF may have contributed to the diagnosis of POAF, the utility of the existing AI-ECG screening algorithm remained modest. When the prediction for POAF was made using the first postoperative ECG in the sample without an elevated screen pre-transplant (n=1084 on account of n=20 missing postoperative ECG), the AUROC was 0.66 (95% CI: 0.57-0.75). While this discrimination is relatively low, at a threshold of 0.08, the AI-ECG algorithm had a 98% (95% CI: 97 – 99%) negative predictive value at a sensitivity of 66% (95% CI: 49-80%). Conclusions: This study's principal finding is that the incidence of POAF is rare, and a considerable fraction of the POAF cases may be latent and undiagnosed. The high negative predictive value of AI-ECG screening suggests utility for prioritizing monitoring and evaluation on transplant patients with a positive AI-ECG screening. Further development and refinement of a post-transplant-specific algorithm may be warranted further to enhance the diagnostic yield of the ECG-based screening.

Keywords: artificial intelligence, atrial fibrillation, cardiology, transplant, medicine, ECG, machine learning

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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: Jungeun Cho

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Social finance has received increasing attention as a means to promote the growth of regional economies. Despite the plenty of research discussed their critical role and functions in regional economic development such as the financing and promotion of co-operatives or social enterprises and the offering credit to the financially excluded in the region, however, rarely are efforts made to measure the contribution of social finance in the regional economy. It is essential to establish an evaluation model in order to encourage social finance institutions to perform their supposed role and functions on regional economic development. The objective of this paper is to formulate an evaluation model of the contribution of social finance to the regional economy through an analytic hierarchy process (AHP) approach. This study is expected to provide useful guidelines for social finance institutions’ strategies and the policies of local or central government regarding social finance.

Keywords: social finance, regional economy, social economy, policies of local or central government

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Authors: Nwadike Emmanuel Chinagoron, Achebe Chukwunonso, Ezeliora Chukwuemeka Daniel, Azaka Onyemazuwa Andrew

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In this research work, the process of biodiesel production in a pilot plant was studied using cow tallow as raw material, methanol as the solvent and potassium hydroxide as catalysts. The biodiesel quality was determined by characterization. The tallow used in the production had a molecular weight of 860g. Its oil had a density value of 0.8g/ml, iodine value of 63.45, viscosity at 300C was 9.83pas, acid value was 1.96, free fatty acid (FFA) of 0.98%, saponification value of 82.75mleq/kg, specific gravity of 0.898, flash point of 1100C, cloud point of 950C and Calorific value also called Higher Heating Value (HHV) of 38.365MJ/Kg. The produced biodiesel had a density of 0.82g/ml, iodine value of 126.9, viscosity of 4.32pas at 300C, acid value of 0.561, FFA of 0.2805%, saponification value of 137.45 mleq/kg.Flash point, cloud point and centane number of the biodiesel produced are 1390C, 980C and 57.5 respectively, with fat content, protein content, ash content, moisture content, fiber content and carbohydrate content values of 10%, 2.8%, 5%, 5%, 20%, and 37.2% respectively. The biodiesel higher heating values (calorific values) when estimated from viscosity, density and flash points were 41.4MJ/Kg, 63.8MJ/Kg, and 34.6MJ/Kg respectively. The biodiesel was blended with conventional diesel. The blend B-10 had values of 1320C and 960C for flash and cloud points, with Calorific value (or HHV) of 34.6 MJ/Kg (when estimated from its Flash point) and fat content, protein content, ash content, moisture content, fiber content and carbohydrate content values of 5%, 2.1%,10%, 5%, 15%, and 62.9% respectively.

Keywords: biodiesel, characterization, cow-tallow, cetane rating

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Authors: Bina Kumari, Subir K. Sarkar, Pradipta Bandyopadhyay

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The autocorrelation function of the density fluctuation is studied in each of the two phases in a Gibbs Ensemble Monte Carlo (GEMC) simulation of the problem of phase separation for a square well potential with various values of its range. We find that the normalized autocorrelation function is described very well as a linear combination of an exponential function with a time scale τ₂ and a stretched exponential function with a time scale τ₁ and an exponent α. Dependence of (α, τ₁, τ₂) on the parameters of the GEMC algorithm and the range of the square well potential is investigated and interpreted. We also analyse the issue of how to choose the parameters of the GEMC simulation optimally.

Keywords: autocorrelation function, density fluctuation, GEMC, simulation

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Authors: Alexsandro Bayestorff da Cunha, Dpebora Caline de Mello, Camila Alves Corrêa

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In the production of fiberboards, an adhesive based on urea-formaldehyde resin is used, which has the advantages of low cost, homogeneity of distribution, solubility in water, high reactivity in an acid medium, and high adhesion to wood. On the other hand, as a disadvantage, there is low resistance to humidity and the release of formaldehyde. The objective of the study was to determine the viability of adding industrial boiler ash to the urea formaldehyde-based adhesive for the production of medium-density fiberboard. The raw material used was composed of Pinus spp fibers, urea-formaldehyde resin, paraffin emulsion, ammonium sulfate, and boiler ash. The experimental plan, consisting of 8 treatments, was completely randomized with a factorial arrangement, with 0%, 1%, 3%, and 5% ash added to the adhesive, with and without the application of a catalyst. In each treatment, 4 panels were produced with density of 750 kg.m⁻³, dimensions of 40 x 40 x 1,5 cm, 12% urea formaldehyde resin, 1% paraffin emulsion and hot pressing at a temperature of 180ºC, the pressure of 40 kgf/cm⁻² for a time of 10 minutes. The different compositions of the adhesive were characterized in terms of viscosity, pH, gel time and solids, and the panels by physical and mechanical properties, in addition to evaluation using the IMAL DPX300 X-ray densitometer and formaldehyde emission by the perforator method. The results showed a significant reduction of all adhesive properties with the use of the catalyst, regardless of the treatment; while the percentage increase of ashes provided an increase in the average values of viscosity, gel time, and solids and a reduction in pH for the panels with a catalyst; for panels without catalyst, the behavior was the opposite, with the exception of solids. For the physical properties, the results of the variables of density, compaction ratio, and thickness were equivalent and in accordance with the standard, while the moisture content was significantly reduced with the use of the catalyst but without the influence of the percentage of ash. The density profile for all treatments was characteristic of medium-density fiberboard, with more compacted and dense surfaces when compared to the central layer. For thickness, the swelling was not influenced by the catalyst and the use of ash, presenting average values within the normalized parameters. For mechanical properties, the influence of ashes on the adhesive was negatively observed in the modulus of rupture from 1% and in the traction test from 3%; however, only this last property, in the percentages of 3% and 5%, were below the minimum limit of the norm. The use of catalyst and ashes with percentages of 3% and 5% reduced the formaldehyde emission of the panels; however, only the panels that used adhesive with catalyst presented emissions below 8mg of formaldehyde / 100g of the panel. In this way, it can be said that boiler ash can be added to the adhesive with a catalyst without impairing the technological properties by up to 1%.

Keywords: reconstituted wood panels, formaldehyde emission, technological properties of panels, perforator

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Authors: Majid Moshirfar, Kyle Margulies, Yasmyne C. Ronquillo, Phillip Hoopes

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A total of 66 articles were reviewed to compare glaucoma and its associated surgeries' effect on central corneal endothelium cell density (CECD). The paper reports the average reported central CECD loss at 3-, 6-, 12-, 24-, 36-, 48-, and 60-month post-operation for each glaucoma surgery. ALT, MLT, SLT, CS AGV, VC BGI, Hydrus + phaco, XEN gel + phaco, PRESERFLO, Dual iStent, or Trabectome had no significant impact on postoperative CECD compared to either preoperative CECD or control group CECD. The highest CECD loss was found to be EXPRESS-phaco, AC AGV, CS BGI, CS BGI, AC BGI, and AC BGI at the 3-, 6-, 12-, 24-, 36-, 48-, and 60-month follow-ups, respectively. AC AGV, Trab + MMC, Trab, AC BGI, Trab + MMC, Cypass, and Cypass showed the smallest reduction of CECD at the 3-, 6-, 12-, 24-, 36-, 48-, and 60-month follow-ups.

Keywords: glaucoma, corneal endothelium, cell density, surgery outcome

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Authors: A. Yonetken, A. Erol, M. Cakmakkaya

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Intermetallic materials are among advanced technology materials that have outstanding mechanical and physical properties for high temperature applications. Especially creep resistance, low density and high hardness properties stand out in such intermetallics. The microstructure, mechanical properties of %88Ni-%10Cr and %2Mn powders were investigated using specimens produced by tube furnace sintering at 900-1300°C temperature. A composite consisting of ternary additions, a metallic phase, Fe ,Cr and Mn have been prepared under Ar shroud and then tube furnace sintered. XRD, SEM (Scanning Electron Microscope), were investigated to characterize the properties of the specimens. Experimental results carried out for composition %88Ni-%10Cr and %2Mn at 1300°C suggest that the best properties as 138,80HV and 6,269/cm3 density were obtained at 1300°C.

Keywords: composite, high temperature, intermetallic, sintering

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Authors: Kim Byung-Kon, Kim Young-Jin

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As project opportunities for the Architecture, Engineering and Construction (AEC) industry have grown more complex and larger, the utilization of BIM (Building Information Modeling) technologies for 3D design and simulation practices has been increasing significantly; the typical applications of the BIM technologies include clash detection and design alternative based on 3D planning, which have been expanded over to the technology of construction management in the AEC industry for virtual design and construction. As for now, commercial BIM software has been operated under a single-user environment, which is why initial costs for its introduction are very high. Cloud computing, one of the most promising next-generation Internet technologies, enables simple Internet devices to use services and resources provided with BIM software. Recently in Korea, studies to link between BIM and cloud computing technologies have been directed toward saving costs to build BIM-related infrastructure, and providing various BIM services for small- and medium-sized enterprises (SMEs). This study addressed how to develop the usage metering functions of BIM software under cloud computing architecture in order to archive and use BIM data and create an optimal revenue structure so that the BIM services may grow spontaneously, considering a demand for cloud resources. To this end, the author surveyed relevant cases, and then analyzed needs and requirements from AEC industry. Based on the results & findings of the foregoing survey & analysis, the author proposed herein how to optimally develop the usage metering functions of cloud BIM software.

Keywords: construction IT, BIM (Building Information Modeling), cloud computing, BIM-based cloud computing, 3D design, cloud BIM

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Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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Authors: Miloš Matúš, Peter Križan, Ľubomír Šooš, Juraj Beniak

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The moisture content of densified biomass is a limiting parameter influencing the quality of this solid biofuel. It influences its calorific value, density, mechanical strength and dimensional stability as well as affecting its production process. This paper deals with experimental research into the effect of moisture content of the densified material on the final quality of biofuel in the form of logs (briquettes or pellets). Experiments based on the single-axis densification of the spruce sawdust were carried out with a hydraulic piston press (piston and die), where the densified logs were produced at room temperature. The effect of moisture content on the qualitative properties of the logs, including density, change of moisture, expansion and physical changes, and compressive and impact resistance were studied. The results show the moisture ranges required for producing good-quality logs. The experiments were evaluated and the moisture content of the tested material was optimized to achieve the optimum value for the best quality of the solid biofuel. The dense logs also have high-energy content per unit volume. The research results could be used to develop and optimize industrial technologies and machinery for biomass densification to achieve high quality solid biofuel.

Keywords: biomass, briquettes, densification, fuel quality, moisture content, density

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Authors: Han Yan, Jieren Luo, Qiuhui Yan, Xiaoqing Li

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The thermal conductivity of porous materials is closely related to the thermal and moisture environment and the overall energy consumption of the building. The study of thermal conductivity of porous materials has great significance for the realization of low energy consumption building and economic construction building. Based on the study of effective thermal conductivity of porous materials at home and abroad, the thermal conductivity under a variety of different density of polystyrene board (EPS), plastic extruded board (XPS) and polyurethane (PU) and phenolic resin (PF) in wet state through theoretical analysis and experimental research has been studied. Initially, the moisture absorption and desorption properties of specimens had been discussed under different density, which led a result indicates the moisture absorption of four porous materials all have three stages, fast, stable and gentle. For the moisture desorption, there are two types. One is the existence of the rapid phase of the stage, such as XPS board, PU board. The other one does not have the fast desorption, instead, it is more stabilized, such as XPS board, PF board. Furthermore, the relationship between water content and thermal conductivity of porous materials had been studied and fitted, which figured out that in the wake of the increasing water content, the thermal conductivity of porous material is continually improving. At the same time, this result also shows, in different density, when the same kind of materials decreases, the saturated moisture content increases. Finally, the moisture absorption and desorption properties of the four kinds of materials are compared comprehensively, and it turned out that the heat preservation performance of PU board is the best, followed by EPS board, XPS board, PF board.

Keywords: porous materials, thermal conductivity, moisture content, transient hot-wire method

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Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, implementation, MATLAB

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Authors: Mohamad Saab, Florent Real, Francois Virot, Laurent Cantrel, Valerie Vallet

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All spent nuclear fuel reprocessing plants use the PUREX process (Plutonium Uranium Refining by Extraction), which is a liquid-liquid extraction method. The organic extracting solvent is a mixture of tri-n-butyl phosphate (TBP) and hydrocarbon solvent such as hydrogenated tetra-propylene (TPH). By chemical complexation, uranium and plutonium (from spent fuel dissolved in nitric acid solution), are separated from fission products and minor actinides. During a normal extraction operation, uranium is extracted in the organic phase as the UO₂(NO₃)₂(TBP)₂ complex. The TBP solvent can form an explosive mixture called red oil when it comes in contact with nitric acid. The formation of this unstable organic phase originates from the reaction between TBP and its degradation products on the one hand, and nitric acid, its derivatives and heavy metal nitrate complexes on the other hand. The decomposition of the red oil can lead to violent explosive thermal runaway. These hazards are at the origin of several accidents such as the two in the United States in 1953 and 1975 (Savannah River) and, more recently, the one in Russia in 1993 (Tomsk). This raises the question of the exothermicity of reactions that involve TBP and all other degradation products, and calls for a better knowledge of the underlying chemical phenomena. A simulation tool (Alambic) is currently being developed at IRSN that integrates thermal and kinetic functions related to the deterioration of uranyl nitrates in organic and aqueous phases, but not of the n-butyl phosphate. To include them in the modeling scheme, there is an urgent need to obtain the thermodynamic and kinetic functions governing the deterioration processes in liquid phase. However, little is known about the thermodynamic properties, like standard enthalpies of formation, of the n-butyl phosphate molecules and of the UO₂(NO₃)₂(TBP)₂ UO₂(NO₃)₂(HDBP)(TBP) and UO₂(NO₃)₂(HDBP)₂ complexes. In this work, we propose to estimate the thermodynamic properties with Quantum Methods (QM). Thus, in the first part of our project, we focused on the mono, di, and tri-butyl complexes. Quantum chemical calculations have been performed to study several reactions leading to the formation of mono-(H₂MBP), di-(HDBP), and TBP in gas and liquid phases. In the gas phase, the optimal structures of all species were optimized using the B3LYP density functional. Triple-ζ def2-TZVP basis sets were used for all atoms. All geometries were optimized in the gas-phase, and the corresponding harmonic frequencies were used without scaling to compute the vibrational partition functions at 298.15 K and 0.1 Mpa. Accurate single point energies were calculated using the efficient localized LCCSD(T) method to the complete basis set limit. Whenever species in the liquid phase are considered, solvent effects are included with the COSMO-RS continuum model. The standard enthalpies of formation of TBP, HDBP, and H2MBP are finally predicted with an uncertainty of about 15 kJ mol⁻¹. In the second part of this project, we have investigated the fundamental properties of three organic species that mostly contribute to the thermal runaway: UO₂(NO₃)₂(TBP)₂, UO₂(NO₃)₂(HDBP)(TBP), and UO₂(NO₃)₂(HDBP)₂ using the same quantum chemical methods that were used for TBP and its derivatives in both the gas and the liquid phase. We will discuss the structures and thermodynamic properties of all these species.

Keywords: PUREX process, red oils, quantum chemical methods, hydrolysis

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Jiahau Guo, Yihe Zhang

Abstract:

This paper proposes solutions for pricing options on stocks paying discrete dividends in markets with daily price limits. We first extend the intraday density function of Guo and Chang (2020) to a multi-day one and use the framework of Haug et al. (2003) to value European options on stocks paying discrete dividends. Next, we adopt the fast Fourier transform (FFT) to derive accurate and efficient formulae for American options and further employ the three-point Richardson extrapolation to accelerate the computation. Finally, the accuracy of our proposed methods is verified by simulations.

Keywords: daily price limit, discrete dividend, early exercise, fast Fourier transform, multi-day density function, Richardson extrapolation

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Authors: Olga Kruzhkova, Irina Vorobyeva, Roman Porozov

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Vandalism is a common phenomenon, but its definition is still not clearly defined. In the public sense, vandalism is the blatant cases of pogroms in cemeteries, destruction of public places (regardless of whether these actions are authorized), damage to significant objects of culture and history (monuments, religious buildings). From a legal point of view, only such an act can be called vandalism, which is aimed at 'desecrating buildings or other structures, damaging property on public transport or in other public places'. The key here is the notion of public property that is being damaged. In addition, the principal is the semantics of messages, expressed in a kind of sign system (drawing, inscription, symbol), which initially threatens public order, the calmness of citizens, public morality. Because of this, the legal qualification of vandalism doesn’t include a sufficiently wide layer of environmental destructions that are common in modern urban space (graffiti and other damage to private property, broken shop windows, damage to entrances and elevator cabins), which in ordinary consciousness are seen as obvious facts of vandalism. At the same time, the understanding of vandalism from the position of psychology implies an appeal to the question of the limits of the activity of the subject of vandalism and his motivational basis. Also recently, the discourse on the positive meaning of some forms of vandalism (graffiti, street-art, etc.) has been activated. But there is no discussion of the role and significance of vandalism in public and individual life, although, like any socio-cultural and socio-psychological phenomenon, vandalism is not groundless and meaningless. Our aim of the study was to identify and describe the functions of vandalism as a socio-cultural and socio-psychological phenomenon of the life of the urban community, as well as personal determinants of its manifestations. The study was conducted in the spatial environment of the Russian megalopolis (Ekaterinburg) by photographing visual results of vandal acts (6217 photos) with subsequent trace-assessment and image content analysis, as well as diagnostics of personal characteristics and motivational basis of vandal activity of possible subjects of vandalism among youth. The results of the study allowed to identify the functions of vandalism at the socio-environmental and individual-subjective levels. The socio-environmental functions of vandalism include the signaling function, the function of preparing of social changes, the constructing function, and the function of managing public moods. The demonstrative-protest function, the response function, the refund function, and the self-expression function are assigned to the individual-subjective functions of vandalism. A two-dimensional model of vandal functions has been formed, where functions are distributed in the spaces 'construction reconstruction', 'emotional regulation/moral regulation'. It is noted that any function of vandal activity at the individual level becomes a kind of marker of 'points of tension' at the social and environmental level. Acknowledgment: The research was supported financially by Russian Science Foundation, (Project No. 17-18-01278).

Keywords: destruction, urban environment, vandal behavior, vandalism, vandalism functions

Procedia PDF Downloads 195