Search results for: supplementary variable

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: Pallabi Kalita, Hui Tag, Loxmi Jamoh, H. N. Sarma, A. K. Das

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Wild edible food plants contain a number of organic phytochemical that have been linked to the promotion of good health. These plants used by the local people of Arunachal Pradesh (Northeast India) are found to have high nutritional potential to maintain general balance diet. A study was conducted to evaluate the nutritional potential of five commonly found, unexplored wild food plants namely, Piper pedicellatum C. DC (leaves), Gonostegia hirta (Blume ex Hassk.) Miq. (leaves), Mussaenda roxburghii Hook. f. (leaves), Solanum spirale Roxb. (leaves and fruits) and Cyathea spinulosa Wall. ex Hook. (pith portion and tender rachis) from East Siang District of Arunachal Pradesh Northeast (India) for ascertaining their suitability for utilization as supplementary food. Results of study revealed that P. pedicellatum, C. spinulosa, and S. spirale (leaves) are the most promising species which have high nutritional content out of the five wild food plants investigated which is required for the normal growth and development of human.

Keywords: wild edible plants, gross energy, Gonostegia hirta, Cyathea spinulosa

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Authors: Sulaem Musaddiq Laskar, Sudip Talukdar

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Sustainable supplementary cementitious material is the prime need in the construction industry. Geopolymer has strong potential for replacing the conventional Portland cement used in mortar and concrete in the industry. This study deals with experimental investigations performed on geopolymer mixes prepared from both ultra-fine ground granulated blast furnace slag and fly ash in a certain proportion. Geopolymer mixes were prepared with alkali activator composed of sodium hydroxide solution and varying amount of superplasticizer. The mixes were tested to study fresh and hardened state properties such as setting time, workability and compressive strength. Influence of concentration of alkali activator on effectiveness of superplasticizer in modifying the properties of geopolymer mixes was also investigated. Results indicated that addition of superplasticizer to ultra-fine slag-fly ash based geopolymer is advantageous in terms of setting time, workability and strength performance but up to certain dosage level. Higher concentration of alkali activator renders ineffectiveness in superplasticizer in improving the fresh and hardened state properties of geopolymer mixes.

Keywords: ultra-fine slag, fly ash, superplasticizer, setting time, workability, compressive strength

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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. Derrouazin, N. Mekkakia-M, R. Taleb, M. Helaimi, A. Benbouali

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Nowadays the use of different sources of renewable energy for the production of electricity is the concern of everyone, as, even impersonal domestic use of the electricity in isolated sites or in town. As the conventional sources of energy are shrinking, a need has arisen to look for alternative sources of energy with more emphasis on its optimal use. This paper presents design of a sustainable Hybrid Power System (PV-Wind-Storage) assisted by grid as supplementary sources applied to case study residential house, to meet its entire energy demand. A Fuzzy control system model has been developed to optimize and control flow of power from these sources. This energy requirement is mainly fulfilled from PV and Wind energy stored in batteries module for critical load of a residential house and supplemented by grid for base and peak load. The system has been developed for maximum daily households load energy of 3kWh and can be scaled to any higher value as per requirement of individual /community house ranging from 3kWh/day to 10kWh/day, as per the requirement. The simulation work, using intelligent energy management, has resulted in an optimal yield leading to average reduction in cost of electricity by 50% per day.

Keywords: photovoltaic (PV), wind turbine, battery, microcontroller, fuzzy control (FC), Matlab

Procedia PDF Downloads 627

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: Akram Salah Eddine Belaidi, Said Kenai, El-Hadj Kadri, Benchaâ Benabed, Hamza Soualhi

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Self-compacting concrete (SCC) was developed in the middle of the 1980’s in Japan. SCC flows alone under its dead weight and consolidates itself without any entry of additional compaction energy and without segregation. As an integral part of a SCC, self-compacting mortars (SCM) may serve as a basis for the mix design of concrete since the measurement of the rheological properties of SCCs. This paper discusses the effect of using natural pozzolana (PZ) and marble powder (MP) in two alternative systems ratios PZ/MP = 1 and 1/3 of the performance of the SCC. A total of 11 SCC’s were prepared having a constant water-binder (w/b) ratio of 0.40 and total cementitious materials content of 475 kg/m3. Then, the fresh properties of the mortars were tested for mini-slump flow diameter and mini-V-funnel flow time for SCMs and Slumps flow test, L-Box height ratio, V-Funnel flow time and sieve stability for SCC. Moreover, the development in the compressive strength was determined at 3, 7, 28, 56, and 90 days. Test results have shown that using of ternary blends improved the fresh properties of the mixtures. The compressive strength of SCC at 90 days with 30% of PZ and MP was similar to those of ordinary concrete use in situ.

Keywords: self-compacting mortar, self-compacting concrete, natural pozzolana, marble powder, rheology, compressive strength

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Authors: Julian Pigott

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This paper introduces the Language Learning as a Means of Drive Engagement (LLMDE) theory, derived from a grounded theory analysis of interviews with Japanese university students. According to LLMDE theory, language learning can be understood as a means of engaging one or more of four self-fulfillment drives: the drive to expand one’s horizons (perspective drive); the drive to make a success of oneself (status drive); the drive to engage in interaction with others (communication drive); and the drive to obtain intellectual and affective stimulation (entertainment drive). While many theories of learner psychology focus on conscious agency, LLMDE theory addresses the role of the unconscious. In addition, supplementary thematic analysis of the data revealed the role of context in mediating drive engagement. Unexpected memorable events, for example, play a key role in instigating and, indirectly, in regulating learning, as do institutional and cultural contexts. Given the apparent importance of such factors beyond the immediate control of the learner, and given the pervasive role of habit and drives, it is argued that the concept of motivation merits theoretical reappraisal. Rather than an underlying force determining language learning success or failure, it can be understood to emerge sporadically in consciousness to promote behavioral change, or to protect habitual behavior from disruption.

Keywords: drives, grounded theory, motivation, significant events

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Authors: Ali Reza Ghaffari, Hassan Saghi

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Given the limitation of fossil resources to supply energy to buildings, recent years have seen a revival of interest in new technologies that produce the energy using new forms of energy in many developed countries. In this research, first the potentials of new energies in Iran are discussed and then based on case studies undertaken in a building in Tehran, the effects of utilizing new solar energy technology for supplying the energy of buildings are investigated. Then, by analyzing the data recorded over a four-year period, the technical performance of this system is investigated. According to the experimental operation plan, this system requires an auxiliary heating circuit for continuous operation over a year. Also, in the economic analysis, real conditions are considered and the results are recorded based on long-term data. Considering the purchase and commissioning building, supplementary energy consumption, etc. a comparison is drawn between the costs of using a solar water heater in a residential unit with the energy costs of a similar unit equipped with a conventional gas water heater. Given the current price of energy, using a solar water heater in the country will not economical, but considering the global energy prices, this system will have a return on investment after 4.5 years. It also produces 81% less pollution and saves about $21.5 on environmental pollution cleanup.

Keywords: energy supply, new energies, new technologies, buildings

Procedia PDF Downloads 142

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: 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: Upvan Chobera

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India bears the highest burden of tuberculosis globally, facing a significant incidence rate. To combat this public health challenge, the Ministry of Health and Family Welfare in India has launched an ambitious national strategic plan with the aim of achieving END TB targets by 2025. Addressing tuberculosis requires a comprehensive, multi-sectoral approach that encompasses factors such as nutritional support, living and working conditions, and improved access to diagnostics and treatment services. This study delves into the burden of tuberculosis in India, examining the government's strategic plan to combat the disease. Additionally, it explores the role of Ni-Kshay Mitra (community support) in this fight, encompassing various entities such as cooperative societies, corporations, elected representatives, individuals, institutions, non-government organizations, and political parties or individual donors. These efforts aim to enhance the response against tuberculosis, complementing the government's initiatives and catering to district-specific requirements, all coordinated with the district administration. It is important to note that the support provided under the Ni-Kshay Mitra initiative is supplementary to the free services offered by the National TB Elimination Program (NTEP) available to all patients.

Keywords: end TB targets, Ni-kshay Mitra, NTEP, tuberculosis burden in India

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Authors: Alireza Barari, Maryam Firozi-Niyaki, Maryam Kamarlouei

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Background: Herbs have a strong anti-cancer effect. Also, exercise is one of several lifestyle factors known to lower the risk of developing cancer. The aim of this study was to investigate the effect of endurance training and taxol on cyclooxygenase-2 and prostaglandin E2 in the liver tissue of mice with cervical cancer. Materials and Methods: In this experimental study, 35 female C57 mice were randomly divided into 5 groups (n=7 in each group): control (healthy), control (cancer), complement (cancer), training-supplementary (cancer) and training (cancer). The implantation of cancerous tumors was performed under the skin of the upper pelvis. The training group completed the endurance training protocol, which included 3 sessions per week, 50 minutes per session, at a speed of 14-18 m/s for six weeks. A dose of 60 mg/kg/day of pure taxol was injected intra peritoneally. The dependent variables of this study were measured 24 hours after the last training session by ELISA. Results: The results showed that the use of taxol and endurance training reduced the levels of cyclooxygenase-2 and prostaglandin E2 in the liver tissues of C57 mice with cervical cancer. Conclusion: Induction of the cancerous tissue in mice with cervical cancer increases the levels of cyclooxygenase-2 and prostaglandin E2 and endurance training along with taxol may reduce these levels.

Keywords: cervical cancer, taxol, endurance training, cyclooxygenase-2, prostaglandin E2

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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: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel

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Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.

Keywords: craniofacial, gender, odontometric, stature

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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: Bohsiu Wu

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This study compares the differences in social dynamics between rural and urban areas in California to explain homicides involving family members. It is hypothesized that rural homicides are better explained by social isolation and lack of intervention resources, whereas urban homicides are attributed to social disadvantage factors. Several critical social dynamics including social isolation, social disadvantages, acculturation, and intervention resources were entered in a hierarchical linear model (HLM) to examine whether county-level factors affect how each specific dynamic performs at the ZIP code level, a proxy measure for communities. Homicide data are from the Supplementary Homicide Report for all 58 counties in California from 1997 to 1999. Predictors at both the county and ZIP code levels are derived from the 2000 US census. Preliminary results from a HLM analysis show that social isolation is a significant but moderate predictor to explain rural family homicide and various social disadvantage factors are significant factors accounting for urban family homicide. Acculturation has little impact. Rurality and urbanity appear to interact with various social dynamics in explaining family homicide. The implications for prevention at both the county and community level as well as directions for future study on the differences between rural and urban locales are explored in the paper.

Keywords: communities, family, HLM, homicide, rural, urban

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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: Heeyeul Kwon, Yongtae Park

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Despite the highly touted benefits, emerging technologies have unleashed pervasive concerns regarding unintended and unforeseen social impacts. Thus, those wishing to create safe and socially acceptable products need to identify such side effects and mitigate them prior to the market proliferation. Various methodologies in the field of technology assessment (TA), namely Delphi, impact assessment, and scenario planning, have been widely incorporated in such a circumstance. However, literatures face a major limitation in terms of sole reliance on participatory workshop activities. They unfortunately missed out the availability of a massive untapped data source of futuristic information flooding through the Internet. This research thus seeks to gain insights into utilization of futuristic data, future-oriented documents from the Internet, as a supplementary method to generate social impact scenarios whilst capturing perspectives of experts from a wide variety of disciplines. To this end, network analysis is conducted based on the social keywords extracted from the futuristic documents by text mining, which is then used as a guide to produce a comprehensive set of detailed scenarios. Our proposed approach facilitates harmonized depictions of possible hazardous consequences of emerging technologies and thereby makes decision makers more aware of, and responsive to, broad qualitative uncertainties.

Keywords: emerging technologies, futuristic data, scenario, text mining

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Authors: H. Higashiyama, M. Sappakittipakorn, M. Mizukoshi, O. Takahashi

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Ceramic waste aggregates (CWAs) were made from electric porcelain insulator wastes supplied from an electric power company, which were crushed and ground to fine aggregate sizes. In this study, to develop the CWA mortar as an eco–efficient, ground granulated blast–furnace slag (GGBS) as a supplementary cementitious material (SCM) was incorporated. The water–to–binder ratio (W/B) of the CWA mortars was varied at 0.4, 0.5, and 0.6. The cement of the CWA mortar was replaced by GGBS at 20 and 40% by volume (at about 18 and 37% by weight). Mechanical properties of compressive and splitting tensile strengths, and elastic modulus were evaluated at the age of 7, 28, and 91 days. Moreover, the chloride ingress test was carried out on the CWA mortars in a 5.0% NaCl solution for 48 weeks. The chloride diffusion was assessed by using an electron probe microanalysis (EPMA). To consider the relation of the apparent chloride diffusion coefficient and the pore size, the pore size distribution test was also performed using a mercury intrusion porosimetry at the same time with the EPMA. The compressive strength of the CWA mortars with the GGBS was higher than that without the GGBS at the age of 28 and 91 days. The resistance to the chloride ingress of the CWA mortar was effective in proportion to the GGBS replacement level.

Keywords: ceramic waste aggregate, chloride diffusion, GGBS, pore size distribution

Procedia PDF Downloads 320