Search results for: response model

Authors: Moshe Mello, Hilary Rutto, Tumisang Seodigeng

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The adsorptive ability of different carbon materials, tire char (TC), demineralized tire char (DTC), activated tire char (ATC) and Aldrich supplied commercial activated carbon (CAC) was studied for desulfurization of tire pyrolytic oil (TPO). TPO with an initial sulfur content of 7767.7 ppmw was used in this present study. Preparation of ATC was achieved by chemical treatment of raw TC using a potassium hydroxide (KOH) solution and subsequent activation at 800°C in the presence of nitrogen. The thermal behavior of TC, surface microstructure, and the surface functional groups of the carbon materials was investigated using TGA, SEM, and FTIR, respectively. Adsorptive desulfurization of TPO using the carbon materials was performed and they performed in the order of CAC>ATC>DTC>TC. Adsorption kinetics were studied, and pseudo-first order kinetic model displayed a better fit compared to pseudo-second order model. For isotherm studies, the Freundlich isotherm model fitted to the equilibrium data better than the Langmuir isotherm model.

Keywords: ATC, desulfurization, pyrolysis, tire, TPO

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Authors: Sarita Kumari, Ranjit Kumar Upadhyay

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This paper deals with plankton-fish dynamics where the fish population is growing logistically and nonlinearly harvested. The interaction between phytoplankton and zooplankton population is considered to be Crowley-Martin type functional response. It has been assumed that phytoplankton grows logistically and is affected by a space-dependent growth rate. Conditions for the existence of a positive equilibrium point and their stability analysis (both local and global) have been discussed for the non-spatial system. We have discussed maximum sustainable yields as well as optimal harvesting policy for maximizing the economic gain. The stability and existence of Hopf –bifurcation analysis have been discussed for the spatial system. Different conditions for turning pattern formation have been established through diffusion-driven instability analysis. Numerical simulations have been carried out for both non-spatial and spatial models. Phase plane analysis, the largest Lyapunov exponent, and bifurcation theory are used to numerically analyzed the non-spatial system. Our study shows that spatial heterogeneity, the mortality rate of phytoplankton, and constant harvesting of the fish population each play an important role in the dynamical behavior of the marine system.

Keywords: optimal harvesting, pattern formation, spatial heterogeneity, Crowley-Martin functional response

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Authors: Habib Alah Dadgar, Nasim Norouzbeigi

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The precise definition margin of high and low-grade gliomas is crucial for treatment. We aimed to assess the feasibility of assessment of the resection legions with post-operative positron emission tomography (PET) using [18F]O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET). Four patients with the suspicion of high and low-grade were enrolled. Patients underwent post-operative [18F]FET-PET, pre-operative magnetic resonance imaging (MRI) and CT for clinical evaluations. In our study, three patients had negative response to recurrence and progression and one patient indicated positive response after surgery. [18F]FET-PET revealed a legion of increased radiotracer uptake in the dura in the craniotomy site for patient 1. Corresponding to the patient history, the study was negative for recurrence of brain tumor. For patient 2, there was a lesion in the right parieto-temporal with slightly increased uptake in its posterior part with SUVmax = 3.79, so the study was negative for recurrence evaluation. In patient 3 there was no abnormal uptake with negative result for recurrence of brain tumor. Intense radiotracer uptake in the left parietal lobe where in the MRI there was a lesion with no change in enhancement in the post-contrast image is indicated in patient 4. Assessment of the resection legions in high and low-grade gliomas with [18F]FET-PET seems to be useful.

Keywords: FET-PET, CT, glioma, MRI

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Authors: Wanwadee Neamsakul

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VARK learning style is an effective method of learning that could enhance all skills of the students like visual (V), auditory (A), read/write (R), and kinesthetic (K). This learning style benefits the students in terms of professional competencies, critical thinking and lifelong learning which are the desirable characteristics of the nursing students. This study aimed to develop a model of teaching and learning clinical practicum at postpartum ward for nursing students by using VARK learning styles, and evaluate the nursing students’ opinions about the developmental model. A methodology used for this study was research and development (R&D). The model was developed by focus group discussion with five obstetric nursing instructors who have experiences teaching Maternal Newborn and Midwifery I subject. The activities related to practices in the postpartum (PP) ward including all skills of VARK were assigned into the matrix table. The researcher asked the experts to supervise the model and adjusted the model following the supervision. Subsequently, it was brought to be tried out with the nursing students who practiced on the PP ward. Thirty third year nursing students from one of the northern Nursing Colleges, Academic year 2015 were purposive sampling. The opinions about the satisfaction of the model were collected using a questionnaire which was tested for its validity and reliability. Data were analyzed using descriptive statistics. The developed model composed of 27 activities. Seven activities were developed as enhancement of visual skills for the nursing students (25.93%), five activities as auditory skills (18.52%), six activities as read and write skills (22.22%), and nine activities as kinesthetic skills (33.33%). Overall opinions about the model were reported at the highest level of average satisfaction (mean=4.63, S.D=0.45). In the aspects of visual skill (mean=4.80, S.D=0.45) was reported at the highest level of average satisfaction followed by auditory skill (mean=4.62, S.D=0.43), read and write skill (mean=4.57, S.D=0.46), and kinesthetic skill (mean=4.53, S.D=0.45) which were reported at the highest level of average satisfaction, respectively. The nursing students reported that the model could help them employ all of their skills during practicing and taking care of the postpartum women and newborn babies. They could establish self-confidence while providing care and felt proud of themselves by the benefits of the model. It can be said that using VARK learning style to develop the model could enhance both nursing students’ competencies and positive attitude towards the nursing profession. Consequently, they could provide quality care for postpartum women and newborn babies effectively in the long run.

Keywords: model, nursing students, postpartum ward, teaching and learning clinical practicum

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Authors: Daniel Fundi Murithi

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Missing data is a real bane in many surveys. To overcome the problems caused by missing data, partial deletion, and single imputation methods, among others, have been proposed. However, problems such as discarding usable data and inaccuracy in reproducing known population parameters and standard errors are associated with them. For regression and stochastic imputation, it is assumed that there is a variable with complete cases to be used as a predictor in estimating missing values in the other variable, and the relationship between the two variables is linear, which might not be realistic in practice. In this project, we estimate population total in presence of missing values in two-phase sampling. Instead of regression or stochastic models, non-parametric model based regression model is used in imputing missing values. Empirical study showed that nonparametric model-based regression imputation is better in reproducing variance of population total estimate obtained when there were no missing values compared to mean, median, regression, and stochastic imputation methods. Although regression and stochastic imputation were better than nonparametric model-based imputation in reproducing population total estimates obtained when there were no missing values in one of the sample sizes considered, nonparametric model-based imputation may be used when the relationship between outcome and predictor variables is not linear.

Keywords: finite population total, missing data, model-based imputation, two-phase sampling

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Authors: Snezana Mugosa, Zoran Todorovic, Zoran Bukumiric, Ivan Radosavljevic, Natasa Djordjevic

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Introduction: Various studies have shown that the frequency of clopidogrel resistance ranges from 4-40%. The aim of this study was to provide in depth analysis of genetic and non-genetic factors that influence clopidogrel resistance in cardiology patients. Methods: We have conducted a prospective study in 200 hospitalized patients hospitalized at Cardiology Centre of the Clinical Centre of Montenegro. CYP2C19 genetic testing was conducted, and the PREDICT score was calculated in 102 out of 200 patients treated with clopidogrel in order to determine the influence of genetic and non-genetic factors on outcomes of interest. Adverse cardiovascular events and adverse reactions to clopidogrel were assessed during 12 months follow up period. Results: PREDICT score and CYP2C19 enzymatic activity were found to be statistically significant predictors of expressing lack of therapeutic efficacy of clopidogrel by multivariate logistic regression, without multicollinearity or interaction between the predictors (p = 0.002 and 0.009, respectively). Conclusions: Pharmacogenetics analyses that were done in the Montenegrin population of patients for the first time suggest that these analyses can predict patient response to the certain therapy. Stepwise approach could be used in assessing the clopidogrel resistance in cardiology patients, combining the PREDICT score, platelet aggregation test, and genetic testing for CYP2C19 polymorphism.

Keywords: clopidogrel, pharmacogenetics, pharmacotherapy, PREDICT score

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Authors: Kongngern K., Homwonk C., Theerakulpisut P., Roytrakul R.

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Rice cultivation is crucial globally, especially in Asia. Soil salinity poses a significant challenge for agricultural lands. Understanding the expression patterns of different rice varieties under salt stress can provide insights for developing more salt-tolerant cultivars. This study aims to compare the expression patterns of two rice varieties, Thai moderately salt-tolerant rice (Leaung Anan) and high salt-tolerant rice (Pokkali), in response to salt stress. By analyzing protein expression, the research seeks to identify key proteins associated with salt tolerance in rice. The expression patterns of the two rice varieties under salt stress were analyzed using 1D-SDS-PAGE, NanoLC-MS/MS, and MEV software. These methods enabled the researchers to assess the differential expression of proteins in the leaf sheaths of the rice plants. These results indicate that the study identified 18 proteins, exhibited significantly different expression patterns between the two rice cultivars under salt stress. Notably, certain proteins, such as Os05g0364500 and pr1-like protein, showed contrasting expression profiles in the two varieties. The up-regulated proteins, predominantly observed in the salt-tolerant rice, may contribute to the survival of rice plants under salt stress and may provide valuable insights for breeding programs aiming to enhance salt tolerancein rice cultivars.

Keywords: mass spectrometry, proteomics, rice leaf sheaths, salt stress

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Authors: Farah Nameni, Hamidreza Poursadra, Maasumeh Nurani Pilehrud

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Exercise training induced Inflammation and stress. Antioxidant, for example L- Carnitine has beneficial effects in immune system and increased antioxidant enzymes activity. L- Carnitine protects the tissue against the oxidative side effect and helps the body to protect against stress during and after acute exercise. The aim of this study was to determine the effect of L-Carnitine on the blood enzymes: GPX SOD, CAT and GR response. In this study, 20 basketball players girls participated. Subjects were randomly assigned into two groups; placebo and supplementation. Antioxidadision enzymes (Superoxide Dismutase, Catalase, Glutathione Reductase, Glutathione Peroxidase) evaluated. L-Carnitine supplement group orally daily received 3000 mg powder for 14 dys. Then all participates trained basketball exercise acute. Blood samples were drawn vein before and immediately after exercise. Superoxide Dismutase, Catalase, Glutathione Reductase, Glutathione Peroxidase were measured, and data was analyzed using repeated measure ANOVA, Bonferroni and t-test. Our results showed: SOD, GPX and GPX (P < 0.05) have a significant increase. These results suggest L-Carnitine supplementation may increase GPX SOD, CAT, and basal anti oxidative capacity. L-Carnitine can modulate the alterations of exercise oxidative damage in girl basketball players.

Keywords: l-carnitine, GPX, SOD, CAT, exercise, GR, anti-oxidant

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Authors: Ammar Boudaka, Maryam Al-Suleimani, Hajar BaOmar, Intisar Al-Lawati, Fahad Zadjali

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Background: Hypertension is increasingly becoming a matter of medical and public health importance. The maintenance of normal blood pressure requires a balance between cardiac output and total peripheral resistance. The endothelium, through the release of vasodilating factors, plays an important role in the control of total peripheral resistance and hence blood pressure homeostasis. Transient Receptor Potential Vanilloid type 4 (TRPV4) is a mechanosensitive non-selective cation channel that is expressed on the endothelium and contributes to endothelium-mediated vasodilation. So far, no data are available about the morphological and functional status of this channel in hypertensive cases. Objectives: This study aimed to investigate whether there is any difference in the morphological and functional features of TRPV4 in the mesenteric artery of normotensive and hypertensive rats. Methods: Functional feature of TRPV4 in four experimental animal groups: young and adult Wistar-Kyoto rats (WKY-Y and WKY-A), young and adult spontaneously hypertensive rats (SHR-Y and SHR-A), was studied by adding 5 µM 4αPDD (TRPV4 agonist) to mesenteric arteries mounted in a four-chamber wire myograph and pre-contracted with 4 µM phenylephrine. The 4αPDD-induced response was investigated in the presence and absence of 1 µM HC067047 (TRPV4 antagonist), 100 µM L-NAME (nitric oxide synthase inhibitor), and endothelium. The morphological distribution of TRPV4 in the wall of rat mesenteric arteries was investigated by immunostaining. Real-time PCR was used in order to investigate mRNA expression level of TRPV4 in the mesenteric arteries of the four groups. The collected data were expressed as mean ± S.E.M. with n equal to the number of animals used (one vessel was taken from each rat). To determine the level of significance, statistical comparisons were performed using the student’s t-test and considered to be significantly different at p<0.05. Results: 4αPDD induced a relaxation response in the mesenteric arterial preparations (WKY-Y: 85.98% ± 4.18; n = 5) that was markedly inhibited by HC067047 (18.30% ± 2.86; n= 5; p<0.05), endothelium removal (19.93% ± 1.50; n = 5; p<0.05) and L-NAME (28.18% ± 3.09; n = 5; p<0.05). The 4αPDD-induced relaxation was significantly lower in SHR-Y compared to WKY-Y (SHR-Y: 70.96% ± 3.65; n = 6, WKY-Y: 85.98% ± 4.18; n = 5-6, p<0.05. Moreover, the 4αPDD-induced response was significantly lower in WKY-A than WKY-Y (WKY-A: 75.58 ± 1.30; n = 5, WKY-Y: 85.98% ± 4.18; n = 5, p<0.05). Immunostaining study showed immunofluorescent signal confined to the endothelial layer of the mesenteric arteries. The expression of TRPV4 mRNA in SHR-Y was significantly lower than in WKY-Y (SHR-Y; 0.67RU ± 0.34; n = 4, WKY-Y: 2.34RU ± 0.15; n = 4, p<0.05). Furthermore, TRPV4 mRNA expression in WKY-A was lower than its expression in WKY-Y (WKY-A: 0.62RU ± 0.37; n = 4, WKY-Y: 2.34RU ± 0.15; n = 4, p<0.05). Conclusion: Stimulation of TRPV4, which is expressed on the endothelium of rat mesenteric artery, triggers an endothelium-mediated relaxation response that markedly decreases with hypertension and growing up changes due to downregulation of TRPV4 expression.

Keywords: hypertension, endothelium, mesenteric artery, TRPV4

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Authors: Ilhem Ouelhazi, Mouna Elakhdar, Lakdar Kairouani

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A computer simulation model for a combined ejector-vapor compression cycle that uses working fluid R134a. A refrigeration system was developed which combines a basic vapor compression refrigeration cycle with an ejector cooling cycle. A one-dimensional mathematical model was developed using the equations governing the flow and thermodynamics based on the constant area ejector flow model. The effects of the operating parameters on the cooling capacity, the performance coefficient, and the entrainment ratio are studied. The current model is based on the NIST-REFPROP database for refrigerants properties calculations. The simulated performance is compared with the available experimental data from the literature for validation.

Keywords: combined refrigeration cycle, constant area ejector, R134a, ejector-cooling cycle, performance, mathematical simulation, vapor compression cycle

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Authors: Luigi Delle Rose, Oliver Fischer, Ahmed Hammad

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In this article, we study the prospects of the proposed Large Hadron electron Collider (LHeC) in the search for heavy neutral scalar particles. We consider a minimal model with one additional complex scalar singlet that interacts with the Standard Model (SM) via mixing with the Higgs doublet, giving rise to an SM-like Higgs boson and a heavy scalar particle. Both scalar particles are produced via vector boson fusion and can be tested via their decays into pairs of SM particles, analogously to the SM Higgs boson. Using multivariate techniques, we show that the LHeC is sensitive to heavy scalars with masses between 200 and 800 GeV down to scalar mixing of order 0.01.

Keywords: beyond the standard model, large hadron electron collider, multivariate analysis, scalar singlet

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Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Hossein Shokouhmand, Masoomeh Shadab, Rohallah Torabi

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Turbulent flow inside the seal chamber of a pump operating at nearly high Reynolds number is investigated. A comparison of a 3-D computational model for flow and thermal analysis of a mechanical seal with experimental thermal results is presented. The computational model adequately predicts the flow field in the seal chamber and thermal characteristics with the rotating and stationary rings and the twister flow around the seal parts by solving N-S and energy equations in ANSYS-CFX software. The Reynolds stress model (RSM) is applied as a turbulence model for this purpose. Experimental work is discussed which quantifies the temperature of five different points of the working fluid in chamber, mass flow at inlet and the fluid pressure at inlet and outlet. Experimental measurements are combined with computational modeling to obtain local and average heat transfer characteristics. Numerical results of three cases including different flush rates are reported.

Keywords: mechanical seal, CFD_CFX, reynolds stress model, flow field, heat transfer analysis, stream line, heat transfer coefficient, heat flux, nusselt

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Authors: J. R. Wang, H. C. Chang, A. L. Ho, J. H. Yang, S. W. Chen, C. Shih

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The purpose of the study is to analyze the load rejection transient of ABWR by using TRACE, PARCS, and SNAP codes. This study has some steps. First, using TRACE, PARCS, and SNAP codes establish the model of ABWR. Second, the key parameters are identified to refine the TRACE/PARCS/SNAP model further in the frame of a steady state analysis. Third, the TRACE/PARCS/SNAP model is used to perform the load rejection transient analysis. Finally, the FSAR data are used to compare with the analysis results. The results of TRACE/PARCS are consistent with the FSAR data for the important parameters. It indicates that the TRACE/PARCS/SNAP model of ABWR has a good accuracy in the load rejection transient.

Keywords: ABWR, TRACE, PARCS, SNAP

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Authors: Victor Arokia Doss, Kuberapandian Dharaniyambigai, K. Julia Rose Mary

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Advanced Glycation End (AGE) products are the end products due to the reaction between excess reducing sugar present in diabetes and free amino group in protein lipids and nucleic acids. Thus, non-enzymic glycation of molecules such as hemoglobin, collagen, and other structurally and functionally important proteins add to the pathogenic complications such as diabetic retinopathy, neuropathy, nephropathy, vascular changes, atherosclerosis, Alzheimer's disease, rheumatoid arthritis, and chronic heart failure. The most common non-cross linking AGE, carboxymethyl lysine (CML) is formed by the oxidative breakdown of fructosyllysine, which is a product of glucose and lysine. CML is formed in a wide variety of tissues and is an index to assess the extent of glycoxidative damage. Thus we have constructed a mathematical and computational model that predicts the effect of temperature differences in vivo, on the formation of CML, which is now being considered as an important intracellular milieu. This hybrid model that had been tested for its parameter fitting and its sensitivity with available experimental data paves the way for designing novel laboratory experiments that would throw more light on the pathological formation of AGE adducts and in the pathophysiology of diabetic complications.

Keywords: advanced glycation end-products, CML, mathematical model, computational model

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Authors: Roengchai Tansuchat, Woraphon Yamaka, Paravee Maneejuk

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From the past recent, the global financial crisis, economic instability, and large fluctuation in agricultural commodity price have led to increased concerns about the volatility transmission among them. The problem is further exacerbated by commodities volatility caused by other commodity price fluctuations, hence the decision on hedging strategy has become both costly and useless. Thus, this paper is conducted to analysis the volatility spillover effect among major agriculture including corn, soybeans, wheat and rice, to help the commodity suppliers hedge their portfolios, and manage the risk and co-volatility of them. We provide a switching regime approach to analyzing the issue of volatility spillovers in different economic conditions, namely upturn and downturn economic. In particular, we investigate relationships and volatility transmissions between these commodities in different economic conditions. We purposed a Copula-based multivariate Markov Switching GARCH model with two regimes that depend on an economic conditions and perform simulation study to check the accuracy of our proposed model. In this study, the correlation term in the cross-hedge ratio is obtained from six copula families – two elliptical copulas (Gaussian and Student-t) and four Archimedean copulas (Clayton, Gumbel, Frank, and Joe). We use one-step maximum likelihood estimation techniques to estimate our models and compare the performance of these copula using Akaike information criterion (AIC) and Bayesian information criteria (BIC). In the application study of agriculture commodities, the weekly data used are conducted from 4 January 2005 to 1 September 2016, covering 612 observations. The empirical results indicate that the volatility spillover effects among cereal futures are different, as response of different economic condition. In addition, the results of hedge effectiveness will also suggest the optimal cross hedge strategies in different economic condition especially upturn and downturn economic.

Keywords: agricultural commodity futures, cereal, cross-hedge, spillover effect, switching regime approach

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Authors: Mike Tsionas

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The paper develops new indices of financial stability based on an explicit model of expected utility maximization by financial institutions subject to the classical technology restrictions of neoclassical production theory. The model can be estimated using standard econometric techniques, like GMM for dynamic panel data and latent factor analysis for the estimation of co-variance matrices. An explicit functional form for the utility function is not needed and we show how measures of risk aversion and prudence (downside risk aversion) can be derived and estimated from the model. The model is estimated using data for Eurozone countries and we focus particularly on (i) the use of the modeling approach as an “early warning mechanism”, (ii) the bank- and country-specific estimates of risk aversion and prudence (downside risk aversion), and (iii) the derivation of a generalized measure of risk that relies on loan-price uncertainty.

Keywords: financial stability, banking, expected utility maximization, sub-prime crisis, financial crisis, eurozone, PIIGS

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Authors: Anita Paddy, Millicent Obodai, Lebbaeus Asamani

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The management of sickle cell disease requires a multidisciplinary team for better outcomes. Thus, literature on the application of the biopsychosocial model for the management and explanation of chronic pain in sickle cell disease (SCD) and other chronic diseases abound. However, there is limited research on the use of the biopsychosocial model, together with a spiritual component (biopsychosocial-spiritual model). The study investigated the extent to which healthcare providers utilized the biopsychosocial-spiritual model in the management of chronic pain to improve the quality of life (QoL) of patients with SCD. This study employed the descriptive survey design involving a consecutive sampling of 261 patients with SCD who were between the ages of 18 to 79 years and were accessing hematological services at the Clinical Genetics Department of the Korle Bu Teaching Hospital. These patients willingly consented to participate in the study by appending their signatures. The theory of integrated quality of life, the gate control theory of pain and the biopsychosocial(spiritual) model were tested. An instrument for the biopsychosocial-spiritual model was developed, with a basis from the literature reviewed, while the World Health Organisation Quality of Life BREF (WHOQoLBref) and the spirituality rating scale were adapted and used for data collection. Data were analyzed using descriptive statistics (means, standard deviations, frequencies, and percentages) and partial least square structural equation modeling. The study revealed that healthcare providers had a great leaning toward the biological domain of the model compared to the other domains. Hence, participants’ QoL was not fully improved as suggested by the biopsychosocial(spiritual) model. Again, the QoL and spirituality of patients with SCD were quite high. A significant negative impact of spirituality on QoL was also found. Finally, the biosocial domain of the biopsychosocial-spiritual model was the most significant predictor of QoL. It was recommended that policymakers train healthcare providers to integrate the psychosocial-spiritual component in health services. Also, education on SCD and its resultant impact from the domains of the model should be intensified while health practitioners consider utilizing these components fully in the management of the condition.

Keywords: biopsychosocial (spritual), sickle cell disease, quality of life, healthcare, accra

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Authors: N. David, H. O. Gao

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Air pollution is a serious environmental threat on a global scale and can cause harm to human health, morbidity and premature mortality. Reliable monitoring and control systems are therefore necessary to develop coping skills against the hazards associated with this phenomenon. However, existing environmental monitoring means often do not provide a sufficient response due to practical and technical limitations. Commercial microwave links that form the infrastructure for transmitting data between cell phone towers can be harnessed to map rain at high tempo-spatial resolution. Rainfall causes a decrease in the signal strength received by these wireless communication links allowing it to be used as a built-in sensor network to map the phenomenon. In this study, we point to the potential that lies in this system to indirectly monitor areas where air pollution is reduced. The relationship between pollutant wash-off and rainfall provides an opportunity to acquire important spatial information about air quality using existing cell-phone tower signals. Since the density of microwave communication networks is high relative to any dedicated sensor arrays, it could be possible to rely on this available observation tool for studying precipitation scavenging on air pollutants, for model needs and more.

Keywords: air pollution, commercial microwave links, rainfall, washout

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

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Authors: Pinki Sharma, Himanshu Joshi

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Distillery spentwash contains high chemical oxygen demand (COD), biological oxygen demand (BOD), color, total dissolved solids (TDS) and other contaminants even after biological treatment. The effluent can’t be discharged as such in the surface water bodies or land without further treatment. Reverse osmosis (RO) treatment plants have been installed in many of the distilleries at tertiary level. But at most of the places these plants are not properly working due to high concentration of organic matter and other contaminants in biologically treated spentwash. To make the membrane treatment proven and reliable technology, proper pre-treatment is mandatory. In the present study, ultra-filtration (UF) as pre-treatment of RO at tertiary stage was performed. Operating parameters namely initial pH (pHo: 2–10), trans-membrane pressure (TMP: 4-20 bars) and temperature (T: 15- 43°C) used for conducting experiments with UF system. Experiments were optimized at different operating parameters in terms of COD, color, TDS and TOC removal by using response surface methodology (RSM) with central composite design. The results showed that removal of COD, color and TDS by 62%, 93.5% and 75.5%, with UF, respectively at optimized conditions with increased permeate flux from 17.5 l/m2/h (RO) to 38 l/m2/h (UF-RO). The performance of the RO system was greatly improved both in term of pollutant removal as well as water recovery.

Keywords: bio-digested distillery spentwash, reverse osmosis, response surface methodology, ultra-filtration

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Authors: Sourour Ramzi, Claudia Sarrico

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Little has been done on network DEA in education, and nobody has attempted to model the whole education supply chain using network DEA. As such the contribution of the present paper is to propose a model for measuring the efficiency of education supply chains using network DEA. First, we use a general survey of data envelopment analysis (DEA) to establish the emergent themes for research in DEA, and focus on the theme of Network DEA. Second, we use a survey on two-stage DEA models, and Network DEA to write a state of the art on Network DEA, particularly applied to supply chain management. Third, we use a survey on DEA applications to establish the most influential papers on DEA education applications, in order to establish the state of the art on applications of DEA in education, in general, and applications of DEA to education using network DEA, in particular. Finally, we propose a model for measuring the performance of education supply chains of different education systems (countries or states within a country, for instance). We then use this model on some empirical data.

Keywords: supply chain, education, data envelopment analysis, network DEA

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Authors: C. Pearcy, C. Rees

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Cognitive behavioural therapy (CBT) and exposure and response prevention (ERP) are currently the most efficacious treatments for Obsessive-compulsive disorder (OCD). Many clients, however, remain symptomatic following treatment. As a result, refusal of treatment, withdrawal from treatment, and partial adherence to treatment are common amongst ERP. Such limitations have caused few professionals to actually engage in ERP therapy, which has warranted the exploration of alternative treatments. This study evaluated an online self-help treatment program for OCD (the OCD Doctor Online); a 4-week Metacognitive Therapy (MCT) program which has implemented strategies from Wells’ Metacognitive model of OCD. The aim of the present study was to investigate whether an online self-help treatment using MCT would reduce symptoms of OCD, reduce unhelpful metacognitions and improve quality of life. Treatment effectiveness was assessed using a case series methodology in 3 consecutively referred individuals. At post-treatment, all participants showed reductions in unhelpful metacognitive beliefs (MCQ-30) and improvements in quality of life (Q-LES-Q), which were maintained through to 4 week follow-up. Two of the three participants showed reductions in OCD symptomology (OCI-R), which were further reduced at 4-week follow-up. The present study suggests that internet-based self-help treatment may be an effective means of delivering MCT to adults with OCD.

Keywords: internet-based, metacognitive therapy, obsessive-compulsive disorder, self-help

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Authors: M. Ndaw, G. Mendy, S. Ouya

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Information system risk management helps to reduce or eliminate risk by implementing appropriate controls. In this paper, we propose a quantification model of controls impact on information system risks by automatizing the residual criticality estimation step of FMECA which is based on a inductive reasoning. For this, we defined three equations based on type and maturity of controls. For testing, the values obtained with the model were compared to estimated values given by interlocutors during different working sessions and the result is satisfactory. This model allows an optimal assessment of controls maturity and facilitates risk analysis of information system.

Keywords: information system, risk, control, FMECA method

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Authors: Maryam Kheirollahpour, Mahmoud Danaee, Amir Faisal Merican, Asma Ahmad Shariff

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Background: The presence of nonlinearity among the risk factors of eating behavior causes a bias in the prediction models. The accuracy of estimation of eating behaviors risk factors in the primary prevention of obesity has been established. Objective: The aim of this study was to explore the potential of a hybrid model of structural equation modeling (SEM) and Artificial Neural Networks (ANN) to predict eating behaviors. Methods: The Partial Least Square-SEM (PLS-SEM) and a hybrid model (SEM-Artificial Neural Networks (SEM-ANN)) were applied to evaluate the factors affecting eating behavior patterns among university students. 340 university students participated in this study. The PLS-SEM analysis was used to check the effect of emotional eating scale (EES), body shape concern (BSC), and body appreciation scale (BAS) on different categories of eating behavior patterns (EBP). Then, the hybrid model was conducted using multilayer perceptron (MLP) with feedforward network topology. Moreover, Levenberg-Marquardt, which is a supervised learning model, was applied as a learning method for MLP training. The Tangent/sigmoid function was used for the input layer while the linear function applied for the output layer. The coefficient of determination (R²) and mean square error (MSE) was calculated. Results: It was proved that the hybrid model was superior to PLS-SEM methods. Using hybrid model, the optimal network happened at MPLP 3-17-8, while the R² of the model was increased by 27%, while, the MSE was decreased by 9.6%. Moreover, it was found that which one of these factors have significantly affected on healthy and unhealthy eating behavior patterns. The p-value was reported to be less than 0.01 for most of the paths. Conclusion/Importance: Thus, a hybrid approach could be suggested as a significant methodological contribution from a statistical standpoint, and it can be implemented as software to be able to predict models with the highest accuracy.

Keywords: hybrid model, structural equation modeling, artificial neural networks, eating behavior patterns

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Authors: Golden J. Zhang, Dongbao Zhou

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Darcy’s law is the fundamental theory in fluid dynamics and engineering applications. Although Darcy linearity was found to be valid for slow, viscous flow, non-linear and non-Darcian flow has been well documented under both small and large velocity fluid flow. Various classical models were proposed and used widely to quantify non-Darcian flow, including the well-known Forchheimer, Izbash, and Swartzendruber models. Applications, however, revealed limitations of these models. Here we propose a general model built upon the Caputo fractional derivative to quantify non-Darcian flow for various flows (laminar to turbulence).Real-world applications and model comparisons showed that the new fractional-derivative model, which extends the fractional model proposed recently by Zhou and Yang (2018), can capture the non-Darcian flow in the relatively small velocity in low-permeability deposits and the relatively high velocity in high-permeability sand. A scale effect was also identified for non-Darcian flow in fractured rocks. Therefore, fractional calculus may provide an efficient tool to improve classical models to quantify fluid dynamics in aquatic environments.

Keywords: fractional derivative, darcy’s law, non-darcian flow, fluid dynamics

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Authors: Irene T. Ho

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Students with Autism Spectrum Disorder (ASD) studying in mainstream schools often face difficulties adjusting to school life and teachers often find it challenging to meet the needs of these students. The Hong Kong Jockey Club Autism Support Network (JC A-Connect) is an initiative launched in 2015 to enhance support for students with ASD as well as their families and schools. The School Support Programme of the Project aims at building the capacity of schools to provide quality education for these students. The present report provides a summary of the main features of the support model and the related evaluation results. The school support model was conceptualized in response to four observed needs: (1) inadequate teacher expertise in dealing with the related challenges, (2) the need to promote evidence-based practices in schools, (3) less than satisfactory home-school collaboration and whole-school participation, and (4) lack of concerted effort by different parties involved in providing support to schools. The resulting model had partnership and capacity building as two guiding tenets for the School Support Programme. There were two levels of partnership promoted in the project. At the programme support level, a platform that enables effective collaboration among major stakeholders was established, including the funding body that provides the necessary resources, the Education Bureau that helps to engage schools, university experts who provide professional leadership and research support, as well as non-governmental organization (NGO) professionals who provide services to the schools. At the programme implementation level, tripartite collaboration among teachers, parents and professionals was emphasized. This notion of partnership permeated efforts at capacity building targeting students with ASD, school personnel, parents and peers. During 2015 to 2018, school-based programmes were implemented in over 400 primary and secondary schools with the following features: (1) spiral Tier 2 (group) training for students with ASD to enhance their adaptive skills, led by professionals but with strong teacher involvement to promote transfer of knowledge and skills; (2) supplementary programmes for teachers, parents and peers to enhance their capability to support students with ASD; and (3) efforts at promoting continuing or transfer of learning, on the part of both students and teachers, to Tier 1 (classroom practice) and Tier 3 (individual training) contexts. Over 5,000 students participated in the Programme, representing about 50% of students diagnosed with ASD in mainstream public sector schools in Hong Kong. Results showed that the Programme was effective in helping students improve to various extents at three levels: achievement of specific training goals, improvement in adaptive skills in school, and change in ASD symptoms. The sense of competence of teachers and parents in dealing with ASD-related issues, measured by self-report rating scales, was also significantly enhanced. Moreover, effects on enhancing the school system to provide support for students with ASD, assessed according to indicators of inclusive education, were seen. The process and results of this Programme illustrate how obstacles to inclusive education for students with ASD could be overcome by strengthening the necessary partnerships and building the required capabilities of all parties concerned.

Keywords: autism, school support, skills training, teacher development, three-tier model

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Authors: Jae Won Shin, Chang Ho Hyun

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A disintegration of deuterons by photons (dγ → np) reaction model for GEANT4 is developed in this work. An effective field theory with dibaryon fields Introducing a dibaryon field, we can take into account the effective range contribution to the propagator up to infinite order, and it consequently makes the convergence of the theory better than the pionless effective field theory without dibaryon fields. We develop a hadronic model for GEANT4 which is specialized for the disintegration of the deuteron by photons, dγ → np. For the description of two-nucleon interactions, we employ an effective field theory so called pionless theory with dibaryon fields (dEFT). In spite of its simplicity, the theory has proven very effective and useful in the applications to various two-nucleon systems and processes at low energies. We apply the new model of GEANT4 (G4dEFT) to the calculation of total and differential cross sections in dγ → np, and obtain good agreements to experimental data for a wide range of incoming photon energies.

Keywords: dγ → np, dibaryon fields, effective field theory, GEANT4

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Authors: Kodo Sektani, Apostolos Tsouvalas, Andrei Metrikine

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The reassessment of existing movable bridges in The Netherlands has created the need for acceptance/rejection criteria to assess whether the machineries are meet certain design demands. However, the existing design code defines a different limit state design, meant for new machineries which is based on a simple linear spring-mass model. Observations show that existing bridges do not confirm the model predictions. In fact, movable bridges are nonlinear systems consisting of mechanical components, such as, gears, electric motors and brakes. Next to that, each movable bridge is characterized by a unique set of parameters. However, in the existing code various variables that describe the physical characteristics of the bridge are neglected or replaced by partial factors. For instance, the damping ratio ζ, which is different for drawbridges compared to bascule bridges, is taken as a constant for all bridge types. In this paper, a model is developed that overcomes some of the limitations of existing modelling approaches to capture the dynamics of the powertrain of a class of bridge machineries First, a semidefinite dynamic model is proposed, which accounts for stiffness, damping, and some additional variables of the physical system, which are neglected by the code, such as nonlinear braking torques. The model gives an upper bound of the peak forces/torques occurring in the powertrain during emergency braking. Second, a discrete nonlinear dynamic model is discussed, with realistic motor torque characteristics during normal operation. This model succeeds to accurately predict the full time history of the occurred stress state of the opening and closing cycle for fatigue purposes.

Keywords: Dynamics of movable bridges, Bridge machinery, Powertrains, Torque measurements

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Authors: Luziane De Fatima Kirchner, Maria De Jesus Dutra Dos Reis, Francine Nathalie Ferraresi Rodrigues Queluz

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This study evaluated the effect of two components of analytic-behavioral intervention (1-management of conditions of the physical environment, 2-management of the interpersonal relationship) of women with fibromyalgia (FM), besides Clinical Significance and Reliable Change at the end of the intervention. Self-report instruments were used to evaluate stress, anxiety, depression, social skills and disability due to pain and Cortisol Awakening Response (CAR). Four women with a medical diagnosis of FM (mean age 52.7; sd = 6.65), participated of the following procedures: initial evaluation, 10 sessions of component 1, intermediate evaluation, 10 sessions of component 2, and final evaluation. The 20 sessions were effective, with positive changes in the scores of all the self-report instruments, highlighting the results of the stress symptoms that had improvement in the intermediate evaluation. There was, however, no change in the cortisol response on awakening. The Clinical Significance or Reliable Change observed, according to the scores of the stress, anxiety, depression and social skills instruments, corroborated the reports of the participants in the session and the objectives of the treatment. Implications for future studies are discussed, above all, the importance in conducting evaluations with the use of direct measures together with self-report measures.

Keywords: behavioral intervention, clinical significance, fibromyalgia, reliable change

Procedia PDF Downloads 136