Search results for: variable shunt reactors

Authors: Janne Engblom, Elias Oikarinen

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A panel dataset is one that follows a given sample of individuals over time, and thus provides multiple observations on each individual in the sample. Panel data models include a variety of fixed and random effects models which form a wide range of linear models. A special case of panel data models are dynamic in nature. A complication regarding a dynamic panel data model that includes the lagged dependent variable is endogeneity bias of estimates. Several approaches have been developed to account for this problem. In this paper, the panel models were estimated using the Arellano-Bover/Blundell-Bond Generalized method of moments (GMM) estimator which is an extension of the Arellano-Bond model where past values and different transformations of past values of the potentially problematic independent variable are used as instruments together with other instrumental variables. The Arellano–Bover/Blundell–Bond estimator augments Arellano–Bond by making an additional assumption that first differences of instrument variables are uncorrelated with the fixed effects. This allows the introduction of more instruments and can dramatically improve efficiency. It builds a system of two equations—the original equation and the transformed one—and is also known as system GMM. In this study, Finnish housing price dynamics were examined empirically by using the Arellano–Bover/Blundell–Bond estimation technique together with ordinary OLS. The aim of the analysis was to provide a comparison between conventional fixed-effects panel data models and dynamic panel data models. The Arellano–Bover/Blundell–Bond estimator is suitable for this analysis for a number of reasons: It is a general estimator designed for situations with 1) a linear functional relationship; 2) one left-hand-side variable that is dynamic, depending on its own past realizations; 3) independent variables that are not strictly exogenous, meaning they are correlated with past and possibly current realizations of the error; 4) fixed individual effects; and 5) heteroskedasticity and autocorrelation within individuals but not across them. Based on data of 14 Finnish cities over 1988-2012 differences of short-run housing price dynamics estimates were considerable when different models and instrumenting were used. Especially, the use of different instrumental variables caused variation of model estimates together with their statistical significance. This was particularly clear when comparing estimates of OLS with different dynamic panel data models. Estimates provided by dynamic panel data models were more in line with theory of housing price dynamics.

Keywords: dynamic model, fixed effects, panel data, price dynamics

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Authors: Pablo Ignacio Hernández Arango, Niels Lindemeyer

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Chlorine, as Sodium Hypochlorite (NaClO) solution in water, is an effective, worldwide spread, and economical substance to eliminate germs in the water. The disinfection potential of chlorine lies in its ability to degrade the outer surfaces of bacterial cells and viruses. This contribution reports the main parameters of the brine electrolysis for the production of NaClO, which is afterward used for the disinfection of water either for drinking or recreative uses. Herein, the system design was simulated, optimized, build, and tested based on titanium electrodes. The process optimization considers the whole process, from the salt (NaCl) dilution tank in order to maximize its operation time util the electrolysis itself in order to maximize the chlorine production reducing the energy and raw material (salt and water) consumption. One novel idea behind this optimization process is the modification of the flow pattern inside the electrochemical reactors. The increasing turbulence and residence time impact positively the operations figures. The operational parameters, which are defined in this study were compared and benchmarked with the parameters of actual commercial systems in order to validate the pertinency of those results.

Keywords: electrolysis, water disinfection, sodium hypochlorite, process optimization

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Authors: Mehdi Destani, Asghar Heydari

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Objective: The present study aimed to investigate the association between pathological personality dimensions and emotion dysregulation through the mediating role of Cyberchondria behaviors among users of virtual networks. Materials and methods: A descriptive–correlational research method was used in this study, and the statistical population consisted of all people active on social network sites in 2020. The sample size was 300 people who were selected through Convenience Sampling. Data collection was carried out in a survey method using online questionnaires, including the "Difficulties in Emotion Regulation Scale" (DERS), Personality Inventory for DSM-5 Brief Form (PID-5-BF), and Cyberchondria Severity Scale Brief Form (CSS-12). Data analysis was conducted using Pearson's Correlation Coefficient and Structural Equation Modeling (SEM). Findings: Findings suggested that pathological personality dimensions and Cyberchondria behaviors have a positive and significant association with emotion dysregulation (p<0.001). The presented model had a good fit with the data. The variable “pathological personality dimensions” with an overall effect (p<0.001, β=0.658), a direct effect (p<0.001, β=0.528), and an indirect mediating effect through Cyberchondria Behaviors (p<.001), β=0.130), accounted for emotion dysregulation among virtual network users. Conclusion: The research findings showed a necessity to pay attention to the pathological personality dimensions as a determining variable and Cyberchondria behaviors as a mediator in the vulnerability of users of social network sites to emotion dysregulation.

Keywords: cyberchondria, emotion dysregulation, pathological personality dimensions, social networks

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Authors: Getachew Adugna

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Background: Chronic energy malnutrition and human immune deficiency virus among pregnant women are highly prevalent in Sub-Saharan Africa, and they are interrelated in a vicious cycle. However, the prevalence of chronic energy malnutrition and its determinant factors among human immune deficiency virus-positive pregnant women is not well studied in Ethiopia and Addis Ababa in particular. Objective: To determine the prevalence & associated factors of chronic energy malnutrition among human immune deficiency virus-positive pregnant women in health centres of Addis Ababa Ethiopia. Methods: An institution-based cross-sectional study was conducted and a systematic random sampling technique was used to select study subjects. A total of 253 study subjects were enrolled in the study—a structured and pre-tested questionnaire collected sociodemographic, maternal health-related, and nutritional-related variables. MUAC measurements were taken and medical charts were reviewed. Bi-variable and multi-variable logistic regression analyses were used to assess the effect of different factors on chronic energy malnutrition. Result: The overall prevalence of chronic energy malnutrition was 32.0%. It was significantly associated with dietary counselling (AOR: 0.062; 95%CI: 0.007, 0.549), CD4 level (AOR: 0.219; 95%CI: 0.025, 1.908), and clinical stage (AOR: 0.127; 95%CI: 0.053, 0.305). Conclusions: The prevalence of chronic energy malnutrition among Human Immune deficiency virus-infected pregnant women in Addis Ababa was high and Nutritional Intervention should be an integral part of the HIV care program.

Keywords: chronic energy malnutrition, HIV, MUAC, Addis Ababa

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Authors: Yungtai Lo

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Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

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Authors: Lovro Štefan

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The main purpose of the present study was to investigate the associations between the overweight/obesity status and lifestyle factors. In this cross-sectional study, participants were 1950 urban secondary-school students (54.7% of female students) aged 17-18 years old. Dependent variable was body-mass index status derived from self-reported height and weight. The outcome was binarised, where participants with value <25 kg/m2 were collapsed into „normal“, while those ≥25 kg/m2 into „overweight/obesity“ category. Independent variables were gender, type of school, physical activity, sedentary behaviour, self-rated health, self-perceived socioeconomic status and psychological distress. The associations between the dependent and independent variables were analyzed by using multiple logistic regression analysis. In the univariate model, being overweight/obese was significantly associated with being a male student (OR 0.31; 95% CI 0.23 to 0.42), attending a vocational school (OR 1.87; 95% CI 1.42 to 2.48), not meeting the recommendations for moderate-to-vigorous physical activity (OR 0.44; 95% CI 0.22 to 0.88), more time spending in sedentary behaviour (OR 1.53; 95% CI 1.07 to 2.19), poor self-rated health (OR 0.35, 95% CI 0.20 to 0.56) and lower socioeconomic status (OR 0.63; 95% CI 0.48 to 0.84). In the multivariate model, the same associations occured between the dependent and independent variable. In both models, psychological distress was not associated with being overweight/obese. In conclusion, our findings suggest, that lifestyle factors are independently associated with body-mass index

Keywords: body mass index, secondary-school students, Croatia, physical activity, sedentary behaviour, logistic regression

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Authors: N.Revathy, C.Gomathi

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This work aims for a tunable capacitor as a sensor which can vary the control voltage of a voltage control oscillator in a ultra wide band (UWB) transmitter. In this paper power consumption is concentrated. The reason for choosing a capacitive sensing is it give slow temperature drift, high sensitivity and robustness. Previous works report a resistive sensing in a voltage control oscillator (VCO) not aiming at power consumption. But this work aims for power consumption of a capacitive sensing in ultra wide band transmitter. The ultra wide band transmitter to be used is a direct modulation of pulses. The VCO which is the heart of pulse generator of UWB transmitter works on the principle of voltage to frequency conversion. The VCO has and odd number of inverter stages which works on the control voltage input this input is now from a variable capacitor and the buffer stages is reduced from the previous work to maintain the oscillating frequency. The VCO is also aimed to consume low power. Then the concentration in choosing a variable capacitor is aimed. A compact model of a capacitor with the transient characteristics is to be designed with a movable dielectric and multi metal membranes. Previous modeling of the capacitor transient characteristics is with a movable membrane and a fixed membrane. This work aims at a membrane with a wide tuning suitable for ultra wide band transmitter.This is used in this work because a capacitive in a ultra wide transmitter need to be tuned in such a way that all satisfies FCC regulations.

Keywords: capacitive sensing, ultra wide band transmitter, voltage control oscillator, FCC regulation

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Authors: Alexander Cho, Harsho Sanyal, Joseph Cataldo

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A quantitative analysis of the different variables on both the South and North green roofs of the Jacob K. Javits Convention Center was taken to find mathematical relationships between net radiation and evapotranspiration (ET), average outside temperature, and the lysimeter weight. Groups of datasets were analyzed, and the relationships were plotted on linear and semi-log graphs to find consistent relationships. Antecedent conditions for each rainstorm were also recorded and plotted against the volumetric water difference within the lysimeter. The first relation was the inverse parabolic relationship between the lysimeter weight and the net radiation and ET. The peaks and valleys of the lysimeter weight corresponded to valleys and peaks in the net radiation and ET respectively, with the 8/22/15 and 1/22/16 datasets showing this trend. The U-shaped and inverse U-shaped plots of the two variables coincided, indicating an inverse relationship between the two variables. Cross variable relationships were examined through graphs with lysimeter weight as the dependent variable on the y-axis. 10 out of 16 of the plots of lysimeter weight vs. outside temperature plots had R² values > 0.9. Antecedent conditions were also recorded for rainstorms, categorized by the amount of precipitation accumulating during the storm. Plotted against the change in the volumetric water weight difference within the lysimeter, a logarithmic regression was found with large R² values. The datasets were compared using the Mann Whitney U-test to see if the datasets were statistically different, using a significance level of 5%; all datasets compared showed a U test statistic value, proving the null hypothesis of the datasets being different from being true.

Keywords: green roof, green infrastructure, Javits Center, evapotranspiration, net radiation, lysimeter

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Authors: Mohammad Didar Hossain

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Background/Purpose: The purpose of this study was to examine the associations between productive engagements and the psychological well-being of older adults in the U.S by analyzing cross-sectional data from a secondary dataset. Specifically, this paper analyzed the associations of 4 different types of productive engagements, including current work status, caregiving to the family members, volunteering and religious strengths with the psychological well-being as an outcome variable. Methods: Data and sample: The study used the data from the Health and Retirement Study (HRS). The HRS is a nationally representative prospective longitudinal cohort study that has been conducting biennial surveys since 1992 to community-dwelling individuals 50 years of age or older on diverse issues. This analysis was based on the 2016 wave (cross-sectional) of the HRS dataset and the data collection period was April 2016 through August 2017. The samples were recruited from a multistage, national area-clustered probability sampling frame. Measures: Four different variables were considered as the predicting variables in this analysis. Firstly, current working status was a binary variable that measured by 0=Yes and 1= No. The second and third variables were respectively caregiving and volunteering, and both of them were measured by; 0=Regularly, 1= Irregularly. Finally, find in strength was measured by 0= Agree and 1= Disagree. Outcome (Wellbeing) variable was measured by 0= High level of well-being, 1= Low level of well-being. Control variables including age were measured in years, education in the categories of 0=Low level of education, 1= Higher level of education and sex r in the categories 0=male, 1= female. Analysis and Results: Besides the descriptive statistics, binary logistic regression analyses were applied to examine the association between independent and dependent variables. The results showed that among the four independent variables, three of them including working status (OR: .392, p<.001), volunteering (OR: .471, p<.003) and strengths in religion (OR .588, p<.003), were significantly associated with psychological well-being while controlling for age, gender and education factors. Also, no significant association was found between the caregiving engagement of older adults and their psychological well-being outcome. Conclusions and Implications: The findings of this study are mostly consistent with the previous studies except for the caregiving engagements and their impact on older adults’ well-being outcomes. Therefore, the findings support the proactive initiatives from different micro to macro levels to facilitate opportunities for productive engagements for the older adults, and all of these may ultimately benefit their psychological well-being and life satisfaction in later life.

Keywords: productive engagements, older adults, psychological wellbeing, productive aging

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Authors: Rachid Belhachemi, Pierre Rostan, Alexandra Rostan

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This paper develops a discrete-time option pricing model for index options. The model consists of two key ingredients. First, daily stock return innovations are driven by a continuous hidden threshold mixed skew-normal (HTSN) distribution which generates conditional non-normality that is needed to fit daily index return. The most important feature of the HTSN is the inclusion of a latent state variable with a continuum of states, unlike the traditional mixture distributions where the state variable is discrete with little number of states. The HTSN distribution belongs to the class of univariate probability distributions where parameters of the distribution capture the dependence between the variable of interest and the continuous latent state variable (the regime). The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. It has been shown empirically that this distribution outperforms its main competitor, the mixed normal (MN) distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence. Second, heteroscedasticity in the model is captured by a threeexogenous-factor GARCH model (GARCHX), where the factors are taken from the principal components analysis of various world indices and presents an application to option pricing. The factors of the GARCHX model are extracted from a matrix of world indices applying principal component analysis (PCA). The empirically determined factors are uncorrelated and represent truly different common components driving the returns. Both factors and the eight parameters inherent to the HTSN distribution aim at capturing the impact of the state of the economy on price levels since distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. The PCA identifies statistically independent factors affecting the random evolution of a given pool of assets -in our paper a pool of international stock indices- and sorting them by order of relative importance. The PCA computes a historical cross asset covariance matrix and identifies principal components representing independent factors. In our paper, factors are used to calibrate the HTSN-GARCHX model and are ultimately responsible for the nature of the distribution of random variables being generated. We benchmark our model to the MN-GARCHX model following the same PCA methodology and the standard Black-Scholes model. We show that our model outperforms the benchmark in terms of RMSE in dollar losses for put and call options, which in turn outperforms the analytical Black-Scholes by capturing the stylized facts known for index returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.

Keywords: continuous hidden threshold, factor models, GARCHX models, option pricing, risk-premium

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Authors: A. Bachrata, N. Marie, F. Bertrand, J. B. Droin

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The in-depth understanding of severe accident propagation in Generation IV of nuclear reactors is important so that appropriate risk management can be undertaken early in their design process. This paper is focused on model improvements in the SIMMER code in order to perform studies of severe accident mitigation of Sodium Fast Reactor. During the design process of the mitigation devices dedicated to extraction of molten fuel from the core region, the molten fuel propagation from the core up to the core catcher has to be studied. In this aim, analytical as well as the complex thermo-hydraulic simulations with SIMMER-III code are performed. The studies presented in this paper focus on physical phenomena and associated physical models that influence the corium relocation. Firstly, the molten pool heat exchange with surrounding structures is analysed since it influences directly the instant of rupture of the dedicated tubes favouring the corium relocation for mitigation purpose. After the corium penetration into mitigation tubes, the fuel-coolant interactions result in formation of debris bed. Analyses of debris bed fluidization as well as sinking into a fluid are presented in this paper.

Keywords: corium, mitigation tubes, SIMMER-III, sodium fast reactor

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Authors: Michael C. Barbecho, Romeo B. Morcilla

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This study focused on the development of a solar powered front wheel drive electric trike for personal use and short distance travel, utilizing solar power and a variable speed transmission to adapt in places where varying road grades and unavailability of plug-in charging stations are of great problems. The actual performance of the vehicle was measured in terms of duration of charging using solar power, distance travel and battery power duration, top speed developed at full power, and load capacity. This project followed the research and development process which involved planning, designing, construction, and testing. Solar charging tests revealed that the vehicle requires 6 to 8 hours sunlight exposure to fully charge the batteries. At full charge, the vehicle can travel 35 km utilizing battery power down to 42%. Vehicle showed top speed of 25 kph at 0 to 3% road grade carrying a maximum load of 122 kg. The maximum climbing grade was 23% with the vehicle carrying a maximum load of 122 kg. Technically the project was feasible and can be a potential model for possible conversion of traditional Philippine made “pedicabs” and gasoline engine powered tricycle into modern electric vehicles. Moreover, it has several technical features and advantages over a commercialized electric vehicle such as the use solar charging system and variable speed power transmission and front drive power train for adaptability in any road gradient.

Keywords: electric vehicle, solar vehicles, front drive, solar, solar power

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Authors: Milica Karadžić, Lidija Jevrić, Sanja Podunavac-Kuzmanović, Strahinja Kovačević, Anamarija Mandić, Aleksandar Oklješa, Andrea Nikolić, Marija Sakač, Katarina Penov Gaši

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Using chemometric approach, the relationships between the chromatographic lipophilicity and in silico molecular descriptors for twenty-nine selected steroid derivatives were studied. The chromatographic lipophilicity was predicted using artificial neural networks (ANNs) method. The most important in silico molecular descriptors were selected applying stepwise selection (SS) paired with partial least squares (PLS) method. Molecular descriptors with satisfactory variable importance in projection (VIP) values were selected for ANN modeling. The usefulness of generated models was confirmed by detailed statistical validation. High agreement between experimental and predicted values indicated that obtained models have good quality and high predictive ability. Global sensitivity analysis (GSA) confirmed the importance of each molecular descriptor used as an input variable. High-quality networks indicate a strong non-linear relationship between chromatographic lipophilicity and used in silico molecular descriptors. Applying selected molecular descriptors and generated ANNs the good prediction of chromatographic lipophilicity of the studied steroid derivatives can be obtained. This article is based upon work from COST Actions (CM1306 and CA15222), supported by COST (European Cooperation and Science and Technology).

Keywords: artificial neural networks, chemometrics, global sensitivity analysis, liquid chromatography, steroids

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Authors: Su-Ning Wang, Yao-Qiang Chen

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The CeO2-ZrO2-La2O3-Al2O3 composite oxides are synthesized using co-precipitation method by two different reactors (i.e. continuous stirred-tank reactor and batch reactor), and the corresponding Rh-only three-way catalysts are obtained by wet-impregnation approach. The textural, structural, morphology and redox properties of the support materials, as well as the catalytic performance of the Rh-only catalyst are investigated systematically. The results reveal that the materials (CZLA-C) synthesized by continuous stirred-tank reactor have a better physic-chemical properties than the counterpart material (CZLA-B) prepared by batch reactor. After aging treatment at 1000 ℃ for 5 h, the BET surface area and pore volume of S1 reach up to 76 m2 g-1 and 0.36 mL/g, respectively, which is higher than that of S2. The XRD and Raman results demonstrate that a high structural stability is obtained by S1 because of the negligible lattice variation and the slight grain growth after aging treatment. The SEM and TEM images display that the morphology of S1 is assembled by many homogeneous primary nanoparticles (about 6.12 nm) that are connected to form mesoporous structure The TPR measurement shows that S1 possesses a higher reduction ability than S2. Compared with the catalyst supported on the CZLA-B, the as-prepared CZLA-C demonstrates an improved three-way catalytic activity both before and after aging treatment.

Keywords: composite oxides, reactor, catalysis, catalytic performance

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Authors: Maha Zouaoui Khalifa, Hakim Ben Othman, Hussaney Khaled

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

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Authors: Ali Reza Tahavvor‚ Saeed Hosseini, Behnam Amiri

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Concentric and eccentric annulus is used frequently in technical and industrial applications such as nuclear reactors, thermal storage system and etc. In this paper, computational fluid dynamics (CFD) is used to investigate two dimensional free convection of laminar flow in annulus with isotherm cylinders surface and cooler inner surface. Problem studied in thirty different cases. Due to natural convection continuity and momentum equations are coupled and must be solved simultaneously. Finite volume method is used for solving governing equations. The purpose was to obtain the eccentricity effect on Nusselt number in different Rayleight numbers, so streamlines and temperature fields must be determined. Results shown that the highest Nusselt number values occurs in degree of eccentricity equal to 0.5 upward for inner cylinder and degree of eccentricity equal to 0.3 upward for outer cylinder. Side eccentricity reduces the outer cylinder Nusselt number but increases inner cylinder Nusselt number. The trend in variation of Nusselt number with respect to eccentricity remain similar in different Rayleight numbers. Correlations are included to calculate the Nusselt number of the cylinders.

Keywords: natural convection, concentric, eccentric, Nusselt number, annulus

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Authors: Nasrin Bakhshizadeh, Ashkan Forootan

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A major problem that affects the quality control of polymer in the industrial polymerization is the lack of suitable on-line measurement tools to evaluate the properties of the polymer such as melt and density indices. Controlling the polymerization in ordinary method is performed manually by taking samples, measuring the quality of polymer in the lab and registry of results. This method is highly time consuming and leads to producing large number of incompatible products. An online application for estimating melt index and density proposed in this study is a neural network based on the input-output data of the polyethylene production plant. Temperature, the level of reactors' bed, the intensity of ethylene mass flow, hydrogen and butene-1, the molar concentration of ethylene, hydrogen and butene-1 are used for the process to establish the neural model. The neural network is taught based on the actual operational data and back-propagation and Levenberg-Marquart techniques. The simulated results indicate that the neural network process model established with three layers (one hidden layer) for forecasting the density and the four layers for the melt index is able to successfully predict those quality properties.

Keywords: polyethylene, polymerization, density, melt index, neural network

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. To achieve this, more resources should be consumed and, besides other environmental concerns, highlight sustainable agricultural development. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for ten different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: land suitability, machine learning, random forest, sustainable agriculture

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Authors: Monika Gałwa-Widera, Anna Kwarciak–Kozłowska, Lucyna Sławik-Dembiczak

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Issues relating to management of sewage sludge from small and medium-sized wastewater treatment plants is a vital issue, which deal with such scholars as well as those directly involved in the issue of wastewater treatment and management of sedimentary. According to the Law on Waste generating waste is responsible for such processing to the product obtained impacted on the environment minimally. In small and medium-sized wastewater treatment plants have to deal with the technology of sludge management technology is far from drying and incineration of sewage sludge. So here you can use other technologies. One of them is the composting of sewage sludge. It is a process of processing and disposal of sewage sludge that effectively their disposal. By composting, we can obtain a product that contains significant amounts of organic matter to assess the fertilizing qualities. Modifications to the ongoing process in biological reactors allow for more rapid receipt of a wholesome product. The research presented and discussed in this publication relate to assist the composting process of sewage sludge and biomass structural material in the shares of rates: 35% biomass, 55% sludge, 10% structural material using a method which involves the re-spawning batch composting physical methods leachate from the composting process.

Keywords: biomass, composting, industry, sewage sludge

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Authors: Hakim Derradji, M’Hammedi Yousra, Sabrou Abdelmalek, Tabet Nacer

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Introduction: This is a retrospective study carried out at the Central Hospital of Army from 2017 to 2022. Its objective is to demonstrate the best surgical method for the management of obstructive hydrocephalus secondary to a posterior fossa tumor in children, in pre, per, and post-operative. Patients and Methods: During this period, 24 children (over 1 year old) were admitted for treatment of the posterior fossa tumor with obstructive secondary hydrocephalus and the majority of whom benefited from VCS followed by surgery and excision, the rest, received after evacuation from other hospital structures, were managed there beforehand with ventriculoperitoneal diversion or external drainage. We found that the way hydrocephalus is managed has implications for subsequent management, hence the need for this study to determine the effectiveness of different surgical procedures used in the treatment of hydrocephalus in these patients. The evaluation is made on the basis of revision rate, complications, survival, and radiological evaluation. Results: 6 patients (25%) received a ventriculoperitoneal shunt (VPD), 15 patients (62%) underwent a ventriculocysternostomy (VCS), and 3 patients (12.5%) received temporary ventricular drainage before or during tumor excision. The post-operative results were almost similar. Nevertheless, a high failure rate (25%) was observed. No deaths are recorded. In total, 75% of children who had a DVP were reoperated. The revision by VCS was performed, in addition to the 4 patients benefiting from a DVP, with one patient having received external drainage, and only one revision of a VCS was recorded. In the two patients who received external drainage, restoration of CSF outflow was observed following tumor resection. Conclusion: VCS is indicated in the first intention in the treatment of hydrocephalus secondary to a posterior fossa tumor, in view of the satisfactory results obtained and the high failure rate in DVP, especially with the presence of metastatic cells in the peritoneum, but can be considered as a second-line treatment.

Keywords: posterior fossa tumor, obstructive hydrocephalus, DVP, VCS

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Authors: Yahya Al-Gabri

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This study aimed to identify the availability degree of transformational leadership dimensions among heads of scientific departments in the Education Faculty at King Saud University. It also aimed to identify the degree of opinions divergence of the study sample on the availability degree of transformational leadership dimensions among the department heads according to the variable of scientific rank. The researcher used the descriptive approach. The study sample consisted of (34) members of education faculty which chosen randomly. To collect the data, the researcher developed a questionnaire consisting of (47) items distributed on four areas after ensuring validity and reliability. Results showed that the degree of practicing the dimensions of transformational leadership by the heads of scientific departments was medium and the mean was (3.21). The dimension of Individualized consideration came first and had a high degree of availability with a mean of (3.31) and the dimension of idealized influence came secondly and had a medium degree (near of high) of availability with a mean of (3.25), also and the dimension of inspirational motivation came thirdly and had a medium degree of availability with a mean of (3.16), whereas the dimension of intellectual stimulation came finally and had a medium degree of availability with a mean of (3.13). The study also showed that there are no statistically significant differences at the level of significance (0.05) in the availability degree of transformational leadership dimensions among the heads of scientific departments at the Faculty of Education according to the scientific rank variable. Finally, the researcher made a number of recommendations and suggestions.

Keywords: transformational leadership, heads of scientific departments, individualized consideration, idealized influence, inspirational motivation, intellectual stimulation

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Authors: Khalifa Maha, Ben Othman Hakim, Khaled Hussainey

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

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Authors: Nitza Davidovitch, Yael Yossel-Eisenbach

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The purpose of the study was to inquire whether there was a change in the shaping of undergraduate students’ digitally-oriented study pattern in the pre-Covid (2016-2017) versus post-Covid period (2022-2023), as affected by three factors: social background characteristics, high school, and academic background characteristics. These two-time points were cauterized by dramatic changes in teaching and learning at institutions of higher education. The data were collected via cross-sectional surveys at two-time points, in the 2016-2017 academic school year (N=443) and in the 2022-2023 school year (N=326). The questionnaire was distributed on social media and it includes questions on demographic background characteristics, previous studies in high school and present academic studies, and questions on learning and reading habits. Method of analysis: A. Statistical descriptive analysis, B. Mean comparison tests were conducted to analyze the variations in the mean score for the digitally-oriented learning pattern variable at two-time points (pre- and post-Covid) in relation to each of the independent variables. C. Analysis of variance was performed to test the main effects and the interactions. D. Applying linear regression, the research aimed to examine the combined effect of the independent variables on shaping students' digitally-oriented learning habits. The analysis includes four models. In all four models, the dependent variable is students’ perception of digitally oriented learning. The first model included social background variables; the second model included scholastic background as well. In the third model, the academic background variables were added, and the fourth model includes all the independent variables together with the variable of period (pre- and post-COVID). E. Factor analysis confirms using the principal component method with varimax rotation; the variables were constructed by a weighted mean of all the relevant statements merged to form a single variable denoting a shared content world. The research findings indicate a significant rise in students’ perceptions of digitally-oriented learning in the post-COVID period. From a gender perspective, the impact of COVID on shaping a digital learning pattern was much more significant for female students. The socioeconomic status perspective is eliminated when controlling for the period, and the student’s job is affected - more than all other variables. It may be assumed that the student’s work pattern mediates effects related to the convenience offered by digital learning regarding distance and time. The significant effect of scholastic background on shaping students’ digital learning patterns remained stable, even when controlling for all explanatory variables. The advantage that universities had over colleges in shaping a digital learning pattern in the pre-COVID period dissipated. Therefore, it can be said that after COVID, there was a change in how colleges shape students’ digital learning patterns in such a way that no institutional differences are evident with regard to shaping the digital learning pattern. The study shows that period has a significant independent effect on shaping students’ digital learning patterns when controlling for the explanatory variables.

Keywords: learning pattern, COVID, socioeconomic status, digital learning

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Authors: Takuma Yamamoto

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Present study investigated the relationship between elementary school children’s prosocial behavior in classroom and satisfaction with school life (approval and victimization from other children) with considering from the perspective of classroom social goal structures (prosocial and compliance goal structures). Participants were 755 elementary school children (393 boys, 362 girls, mean range= 10-12, 5th grader and 6th grader) who were living in Chugoku District, Japan. They filled up questionnaire which was consisted of Murakami, Nishimura and Sakurai’s (2016) prosocial behavior toward friend scale, Kawamura and Tagami’s (1997) satisfaction in classroom scale and Ohtani, Okada, Nakaya and Ito’s (2016) classroom social goal structures scale. Regression lines that satisfaction in classroom is dependent variable and prosocial behavior is independent variable for each class were drawn. There were two types of classroom which children’s prosocial behavior correlated with satisfaction positively and did not. Then one-way MANOVA was conducted to further describe two types of classroom which prosocial behavior increased satisfaction in classroom (type 1) and prosocial behavior decreased satisfaction (type 2). MANOVA for Prosocial goal structure was significant, type 1 > type 2. There were two key findings from this study. First, MANOVA for prosocial goal structure was significant. Second, high score of prosocial goal structure was not necessary condition for the classroom type which children’s prosocial behavior correlated with satisfaction. The implications from these key findings were: (1) in the low prosocial goal structure classroom, children will not behave prosocially because of their negative expectation for the effect of prosocial behavior, (2) this study can be a contribution for classroom management that teachers need to consider about the negative possibilities of prosocial behavior when they try to increase the amount of children’s positive behavior.

Keywords: elementary school children, classroom social goal structure, satisfaction with school life, prosocial behavior

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Authors: Esther M. Folarin, Evans Osabuohien, Ademola Onabote

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Agriculture constitutes an important part of development and poverty mitigation in lower-middle-income countries, like Nigeria. The level of agricultural productivity in the Nigerian economy in line with the level of demand necessary to meet the desired expectation of the Nigerian populace is threatening to meeting the standard of the United Nations (UN) Sustainable Development Goals (SDGs); This includes the SDG-2 (achieve food security through agricultural productivity). The overall objective of the study is to reveal the performance of the interaction variable in the model among other factors that help in the achievement of greater Nigerian agricultural productivity. The study makes use of Wave 4 (2018/2019) of the Living Standard Measurement Studies, Integrated Survey on Agriculture (LSMS-ISA). Qualitative analysis of the information was also used to provide complimentary answers to the quantitative analysis done in the study. The study employed human capital theory and Grossman’s theory of health Demand in explaining the relationships that exist between the variables within the model of the study. The study engages the Instrumental Variable Regression technique in achieving the broad objectives among other techniques for the other specific objectives. The estimation results show that there exists a positive relationship between female healthcare and the level of female agricultural productivity in Nigeria. In conclusion, the study emphasises the need for more provision and empowerment for greater female access to healthcare and educational attainment levels that aids higher female agricultural productivity and consequently an improvement in the total agricultural productivity of the Nigerian economy.

Keywords: agricultural productivity, education, female, healthcare, investment

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Authors: Levent Dumenci, Laura A. Siminoff

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Health literacy has been shown to predict a variety of health outcomes. Reliable identification of persons with limited cancer health literacy (LCHL) has been proved questionable with existing instruments using an arbitrary cut point along a continuum. The CHLT-6, however, uses a latent mixture modeling approach to identify persons with LCHL. The purpose of this study was to estimate two-week and six-month stability of identifying persons with LCHL using the CHLT-6 with a discrete latent variable approach as the underlying measurement structure. Using a test-retest design, the CHLT-6 was administered to cancer patients with two-week (N=98) and six-month (N=51) intervals. The two-week and six-month latent test-retest agreements were 89% and 88%, respectively. The chance-corrected latent agreements estimated from Dumenci’s latent kappa were 0.62 (95% CI: 0.41 – 0.82) and .47 (95% CI: 0.14 – 0.80) for the two-week and six-month intervals, respectively. High levels of latent test-retest agreement between limited and adequate categories of cancer health literacy construct, coupled with moderate to good levels of change-corrected latent agreements indicated that the CHLT-6 classification of limited versus adequate cancer health literacy is relatively stable over time. In conclusion, the measurement structure underlying the instrument allows for estimating classification errors circumventing limitations due to arbitrary approaches adopted by all other instruments. The CHLT-6 can be used to identify persons with LCHL in oncology clinics and intervention studies to accurately estimate treatment effectiveness.

Keywords: limited cancer health literacy, the CHLT-6, discrete latent variable modeling, latent agreement

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Authors: Shalluf Milad

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Tomatoes are widely produced and consumed due to their nutritional content and versatility. However, the tomato is a soft fruit liable to damage and flavour deterioration. Hence, the main challenge for the tomato producing industry is to prevent the high loss incurred during harvest, handling and transportation of the crops. The objective of this study was to investigate the overall nutritional implication of controlled storage of tomatoes using ozone on the basic nutritional components of tomatoes. This investigation was also designed to focus on the effect of different ozone doses on the basic components (antioxidant activity). Green, yellow and red stages of ripeness (elegance tomatoes), were harvested at different dates for each experiment. The tomatoes were cleaned and placed inside the glass reactors and ozonated at 0.25, 0.50 and 1 mg O3/g tomatoes and clean air respectively for 5 days at 15°C ± 2 and 90-95 % relative humidity respectively. The fruits were analysed for total antioxidant activity. Analysis of the fruits clearly showed that antioxidant activity in the pericarp tissue was the lowest (P<0.001) compared with the pulp tissue of tomatoes during storage in the red stage of maturity, after being treated with ozone in the atmosphere of storage in a dose of 1.00 mgO3/g tomatoes. It can be concluded from this study that the use of ozone in the atmospheres of storage and handling of fresh products maintains the important compounds of these products while maintaining the nutritional value and health quality.

Keywords: post-harvest treatment, controlled atmosphere storage, ozone, tomatoes, antioxidant activity

Procedia PDF Downloads 327

Authors: Vinod B. Suryawanshi, Ajit D. Kelkar

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Glass fiber reinforced composites materials, due their unique properties such as high mechanical strength to weight ratio, corrosion resistance, and impact resistance have huge potential as structural materials in automotive, construction and transportation applications. However, these properties often come at higher cost owing to complex design methods, difficult manufacturing processes and raw material cost. In this paper, a cost effective design and manufacturing approach for a composite cantilever beam structure is presented. A constant stress (variable cross section) beam concept has been used to design and optimize the shape of composite cantilever beam and thus obtain the reduction in material used. The variable cross section beam was fabricated from the glass epoxy prepregs using cost effective out of autoclave process. The drop ply technique has been successfully used to obtain the variation in the cross section along the span of the beam. In order to test the beam and validate the design, the beam was subjected to different end loads. Strain gauges were mounted along the length of the beam to obtain strains in the beam at different sections and loads. The strain values were used to calculate the flexural strength and bending stresses in the beam. The stresses obtained through strain measurements from the experiment were found to be uniform along the span of the beam, and thus validates the design. Finally, the finite element model for the constant stress beam was developed using commercial finite element simulation software. It was observed that the simulation results agreed very well with the experimental results.

Keywords: beams, composites, constant cross-section, structures

Procedia PDF Downloads 349

Authors: A. Pokharel, A. Farooque, B. Acharya

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Pyrolysis can be used for energy production from waste biomass of agriculture and forestry. Biochar is the solid byproduct of pyrolysis and its cascading use can offset the cost of the process. A wide variety of research on biochar has highlighted its ability to absorb nutrients, metal and complex compounds; filter suspended solids; enhance microorganisms’ growth; retain water and nutrients as well as to increase carbon content of soil. In addition, sustainable biochar systems are an attractive approach for carbon sequestration and total waste management cycle. Commercially available biochar from Sigma Aldrich was studied for adsorption of nitrogen from effluent of municipal wastewater treatment plant. Adsorption isotherm and breakthrough curve were determined for the biochar. Similarly, biochar’s effects in aerobic as well as anaerobic bioreactors were also studied. In both cases, the biomass was increased in presence of biochar. The amount of gas produced for anaerobic digestion of fruit mix (apple and banana) was similar but the rate of production was significantly faster in biochar fed reactors. The cumulative goal of the study is to use biochar in various wastewater treatment units like aeration tank, secondary clarifier and tertiary nutrient recovery system as well as in anaerobic digestion of the sludge to optimize utilization and add value before being used as a soil amendment.

Keywords: biochar, nutrient recyling, wastewater treatment, soil amendment

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Authors: Monika Szymańska-Czerwińska, Agnieszka Jodełko, Krzysztof Niemczuk

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Q fever (coxiellosis) is an infectious disease of animals and humans causes by C. burnetii and widely distributed throughout the world. Cattle and small ruminants are commonly known as shedders of C. burnetii. The aims of this study were the evaluation of seroprevalence and shedding of C. burnetii in cattle. Genotypes of the pathogen present in the tested specimens were also identified using MLVA (Multiple Locus Variable-Number Tandem Repeat Analysis) and MST (multispacer sequence typing) methods. Sampling was conducted in different regions of Poland in 2018-2021. In total, 2180 bovine serum samples from 801 cattle herds were tested by ELISA (enzyme-linked immunosorbent assay). 489 specimens from 157 cattle herds such as: individual milk samples (n=407), bulk tank milk (n=58), vaginal swabs (n=20), placenta (n=3) and feces (n=1) were subjected to C. burnetii specific qPCR. The qPCR (IS1111 transposon-like repetitive region) was performed using Adiavet COX RealTime PCR kit. Genotypic characterization of the strains was conducted utilizing MLVA and MST methods. MLVA was performed using 6 variable loci. The overall herd-level seroprevalence of C. burnetii infection was 36.74% (801/2180). Shedders were detected in 29.3% (46/157) cattle herds in all tested regions. ST 61 sequence type was identified in 10 out of 18 genotyped strains. Interestingly one strain represents sequence type which has never been recorded previously. MLVA method identified three previously known genotypes: most common was J but also I and BE were recognized. Moreover, a one genotype has never been described previously. Seroprevalence and shedding of C. burnetii in cattle is common and strains are genetically diverse.

Keywords: Coxiella burnetii, cattle, MST, MLVA, Q fever

Procedia PDF Downloads 86