Search results for: moderator variables

Authors: Naveed Ul Hassan, Bilal Aziz, Maryam Mushtaq, Imran Ameen Khan

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Equity risk premium (ERP) is the stock return in excess of risk free return. Even though it is an essential topic of finance but still there is no common consensus upon its forecasting. For forecasting ERP, apart from the macroeconomic variables attention is devoted to technical indicators as well. For this purpose, set of 14 technical and 14 macro-economic variables is selected and all forecasts are generated based on a standard predictive regression framework, where ERP is regressed on a constant and a lag of a macroeconomic variable or technical indicator. The comparative results showed that technical indicators provide better indications about ERP estimates as compared to macro-economic variables. The relative strength of ERP predictability is also investigated by using National Bureau of Economic Research (NBER) data of business cycle expansion and recessions and found that ERP predictability is more than twice for recessions as compared to expansions.

Keywords: equity risk premium, forecasting, macroeconomic indicators, technical indicators

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Authors: Nisith K. Datta, Rakesh Bharti

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The purpose of the study was to find out the effects of Aquatic and Land plyometric training on selected physical variables in intercollegiate male handball players. To achieve this purpose of the study, forty five handball players of Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat were selected as players at random and their age ranged between 18 to 21 years. The selected players were divided into three equal groups of fifteen players each. Group I underwent Aquatic plyometric training, Group II underwent Land plyometric training and Group III Control group for three days per week for twelve weeks. Control Group did not participate in any special training programme apart from their regular activities as per their curriculum. The following physical fitness variables namely speed; leg explosive power and agility were selected as dependent variables. All the players of three groups were tested on selected dependent variables prior to and immediately after the training programme. The analysis of covariance was used to analyze the significant difference, if any among the groups. Since, three groups were compared, whenever the obtained ‘F’ ratio for adjusted post test was found to be significant, the Scheffe’s test to find out the paired mean differences, if any. The 0.05 level of confidence was fixed as the level of significance to test the ‘F’ ratio obtained by the analysis of covariance, which was considered as an appropriate. The result of the study indicates due to Aquatic and Land plyometric training on speed, explosive power, and agility has been improved significantly.

Keywords: aquatic training, explosive power, plyometric training, speed

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Authors: E. Tchandao Mangamana, V. Cariou, E. Vigneau, R. Glele Kakai, E. M. Qannari

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A new definition of a latent variable associated with a dataset makes it possible to propose variants of the PLS2 regression and the multi-block PLS (MB-PLS). We shall refer to these variants as Rd-PLS regression and Rd-MB-PLS respectively because they are inspired by both Redundancy analysis and PLS regression. Usually, a latent variable t associated with a dataset Z is defined as a linear combination of the variables of Z with the constraint that the length of the loading weights vector equals 1. Formally, t=Zw with ‖w‖=1. Denoting by Z' the transpose of Z, we define herein, a latent variable by t=ZZ’q with the constraint that the auxiliary variable q has a norm equal to 1. This new definition of a latent variable entails that, as previously, t is a linear combination of the variables in Z and, in addition, the loading vector w=Z’q is constrained to be a linear combination of the rows of Z. More importantly, t could be interpreted as a kind of projection of the auxiliary variable q onto the space generated by the variables in Z, since it is collinear to the first PLS1 component of q onto Z. Consider the situation in which we aim to predict a dataset Y from another dataset X. These two datasets relate to the same individuals and are assumed to be centered. Let us consider a latent variable u=YY’q to which we associate the variable t= XX’YY’q. Rd-PLS consists in seeking q (and therefore u and t) so that the covariance between t and u is maximum. The solution to this problem is straightforward and consists in setting q to the eigenvector of YY’XX’YY’ associated with the largest eigenvalue. For the determination of higher order components, we deflate X and Y with respect to the latent variable t. Extending Rd-PLS to the context of multi-block data is relatively easy. Starting from a latent variable u=YY’q, we consider its ‘projection’ on the space generated by the variables of each block Xk (k=1, ..., K) namely, tk= XkXk'YY’q. Thereafter, Rd-MB-PLS seeks q in order to maximize the average of the covariances of u with tk (k=1, ..., K). The solution to this problem is given by q, eigenvector of YY’XX’YY’, where X is the dataset obtained by horizontally merging datasets Xk (k=1, ..., K). For the determination of latent variables of order higher than 1, we use a deflation of Y and Xk with respect to the variable t= XX’YY’q. In the same vein, extending Rd-MB-PLS to the path modeling setting is straightforward. Methods are illustrated on the basis of case studies and performance of Rd-PLS and Rd-MB-PLS in terms of prediction is compared to that of PLS2 and MB-PLS.

Keywords: multiblock data analysis, partial least squares regression, path modeling, redundancy analysis

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Authors: J. Cabral, C. Barreto Carvalho, C. da Motta, M. Sousa

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Community integration is a construct that an increasing body of research has shown to have a significant impact in well-being and recovery of people with psychiatric problems. However, there are few studies that explore which factors can be associated and predict community integration. Moreover, community integration has been mostly studied in minority groups, and currently literature on the definition and manifestation of community integration in the more general population is scarce. Thus, the current study aims to characterize community integration and explore possible predictor variables in a sample of participants with psychiatric problems (PP, N=183) and a sample of participants from the general population (GP, N=211). Results show that people with psychiatric problems present above average values of community integration, but are significantly lower than their healthy counterparts. It was also possible to observe that community integration does not vary in terms of the socio-demographic characteristics of both groups in this study. Correlation and multiple regression showed that, among several variables that literature present as relevant in the community integration process, only three variables emerged as having the most explanatory value in community integration of both groups: sense of community, basic needs satisfaction and submission. These results also shown that those variables have increased explanatory power in the PP sample, which leads us to emphasize the need to address this issue in future studies and increase the understanding of the factors that can be involved in the promotion of community integration, in order to devise more effective interventions in this field.

Keywords: community integration, mental illness, predictors, psychiatric problems

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Authors: Muhamad Syafiq Hakimi Kamaruddin, Norhidayah Suleiman

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Ginger extracts (Zingiber officinale Rosc.) have been attributed therapeutic properties primarily as antioxidant, anticancer, and anti-inflammatory properties. Conventional extractions including Soxhlet and maceration are commonly used to extract the bioactive compounds from plant material. Nevertheless, high energy consumption and being non-environmentally friendly are the predominant limitations of the conventional extractions method. Herein, green technology, namely supercritical carbon dioxide (scCO2) extraction, is used to study process variables' effects on extract yields. Herein, green technology, namely supercritical carbon dioxide (scCO2) extraction, is used to study process variables' effects on extract yields. A pressure (10-30 MPa), temperature (40-60 °C), and median particle size (300-600 µm) were conducted at a CO2 flow rate of 0.9 ± 0.2 g/min for 120 mins. The highest overall yield was 4.58% obtained by the scCO2 extraction conditions of 300 bar and 60 °C with 300µm of ginger powder for 120 mins. In comparison, the yield of the extract was increased considerably within a short extraction time. The results show that scCO2 has a remarkable ability over ginger extract and is a promising technology for extracting bioactive compounds from plant material.

Keywords: conventional, ginger, non-environmentally, supercritical carbon dioxide, technology

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Authors: Manan Aslam, Shafqat Rasool

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This paper attempts to examine impact of major factors affecting marketed surplus of seed cotton in district Khanewal (Punjab) using primary source of data. A representative sample of 40 cotton farmers was selected using stratified random sampling technique. The impact of major factors on marketed surplus of seed cotton growers was estimated by employing double log form of regression analysis. The value of adjusted R2 was 0.64 whereas the F-value was 10.81. The findings of analysis revealed that experience of farmers, education of farmers, area under cotton crop and distance from wholesale market were the significant variables affecting marketed surplus of cotton whereas the variables (marketing cost and sale price) showed insignificant impact. The study suggests improving prevalent marketing practices to increase volume of marketed surplus of cotton in district Khanewal.

Keywords: seed cotton, marketed surplus, double log regression analysis

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Authors: Rim Baroudi

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The notion of the context-induced metaphors refers to the role of different contextual aspects (socio-cultural, linguistic, bodily-physical, and ideological) in affecting metaphor production. This has not been investigated in visual discourse. This paper intends to extend the focus of this research interest to study context-induced metaphors in newspapers’ cartoons. It seeks to account for different contextual variables influencing the production of metaphors in cartoons placing special focus on the ideological variable. The aim is to demonstrate how different contextual aspects are conditioned by the ideological variable. The study applied critical metaphor approach to analyse contextual variables shaping the conceptualization of ‘the Islamic State’ in the cartoons of 3 newspapers (Al-Ryadh newspaper, Tehran Times, and The New York Times). Findings have revealed the decisive role of the ideological context in conditioning and priming the rest of contextual variables in the conceptualisation of ‘the Islamic State’ in political cartoons of the three newspapers. These findings bear special importance to the study of bodily-physical and socio-cultural variables inducing and shaping political cognition in political cartoons in a way consistent with the ideological framework within which newspapers operate.

Keywords: context-induced metaphors, ideological context, the Islamic State, political cartoons

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Authors: M. I. Abdelhamid, A. O. Ghallab, R. S. Ettouney, M. A. El-Rifai

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An optimization scheme based on COM server is suggested for communication between Genetic Algorithm (GA) toolbox of MATLAB and Aspen HYSYS. The structure and details of the proposed framework are discussed. The power of the developed scheme is illustrated by its application to the optimization of a recently developed natural gas liquefaction process in which Aspen HYSYS was used for minimization of the power consumption by optimizing the values of five operating variables. In this work, optimization by coupling between the GA in MATLAB and Aspen HYSYS model of the same process using the same five decision variables enabled improvements in power consumption by 3.3%, when 77% of the natural gas feed is liquefied. Also on inclusion of the flow rates of both nitrogen and carbon dioxide refrigerants as two additional decision variables, the power consumption decreased by 6.5% for a 78% liquefaction of the natural gas feed.

Keywords: stranded gas liquefaction, genetic algorithm, COM server, single nitrogen expansion, carbon dioxide pre-cooling

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Authors: Menan M. Elsayed, Hussein A. Heshmat

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The aim of the study is to determine the effect of 100 mg/d Pregnenolone on biological variables after plyometric training for volleyball players. Methods: 15 male volleyball players participated in this study. Serum levels of testosterone, creatine phosphokinase (CPK), lactate, and glucose were measured before and post-exercise. Results: Testosterone was not altered, while creatine phosphokinase (CPK), lactate, and glucose levels significantly decreased. It is recommended to use Pregnenolone administration to decreased muscle damage and delayed fatigue for volleyball players after plyometric training. In conclusion, this study demonstrated that oral Pregnenolone administration of 100 mg/d might decrease muscle damage and delayed fatigue which may affect positively the volleyball players after a plyometric training bout.

Keywords: biological variables, plyometric exercise program, pregnenolone, volleyball player

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Authors: A. J. Francisco, K. C. Gallosa, R. J. Gasacao, J. R. Ros, B. J. Viado

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The study focuses on the use of quality indicators (QI)s based on the standards made by the (IFCC), that could effectively identify and minimize errors occurring throughout the total testing process (TTP), in order to improve patient safety. The study was conducted through a survey questionnaire that was given to a random sample of 19 respondents (eight privately-owned and eleven government-owned hospitals), mainly CMTs, MTs, and Supervisors from UST-affiliated hospitals. The pre-analytical laboratory errors, which include misidentification errors, transcription errors, sample collection errors and sample handling and transportation errors, were considered as variables according to the IFCC WG-LEPS. Data gathered were analyzed using the Mann-Whitney U test, Percentile, Linear Regression, Percentage, and Frequency. The laboratory performance of both hospitals is High level. There is no significant difference between the laboratory performance between the two stated variables. Moreover, among the four QIs, sample handling and transportation errors contributed most to the difference between the two variables. Outcomes indicate satisfactory performance between both variables. However, in order to ensure high-quality and efficient laboratory operation, constant vigilance and improvements in pre-analytical QI are still needed. Expanding the coverage of the study, the inclusion of other phases, utilization of parametric tests are recommended.

Keywords: pre-analytical phase, quality indicators, laboratory performance, pre-analytical error

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Authors: Abdreheman Seid Abdella

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This study examined instructors willingness, self-efficacy beliefs, attitudes and knowledge about provisions of instructional accommodations for students with disabilities in universities. Major concepts used in this study operationally defined and some models of disability were reviewed. Questionnaires were distributed to a total of 181 instructors from four universities and quantitative data was generated. Then to analyze the data, appropriate methods of data analysis were employed. The result indicated that on average instructors had positive willingness, strong self-efficacy beliefs and positive attitudes towards providing instructional accommodations. In addition, the result showed that the majority of participants had moderate level of knowledge about provision of instructional accommodations. Concerning the relationship between instructors background variables and dependent variables, the result revealed that location of university and awareness raising training about Inclusive Education showed statistically significant relationship with all dependent variables (willingness, self-efficacy beliefs, attitudes and knowledge). On the other hand, gender and college/faculty did not show a statistically significant relationship. In addition, it was found that among the inter-correlation of dependent variables, the correlation between attitudes and willingness to provide accommodations was the strongest. Furthermore, using multiple linear regression analysis, this study also indicated that predictor variables like self-efficacy beliefs, attitudes, knowledge and teaching methodology training made statistically significant contribution to predicting the criterion willingness. Predictor variables like willingness and attitudes made statistically significant contribution to predicting self-efficacy beliefs. Predictor variables like willingness, Special Needs Education course and self-efficacy beliefs made statistically significant contribution to predict attitudes. Predictor variables like Special Needs Education courses, the location of university and willingness made statistically significant contribution to predicting knowledge. Finally, using exploratory factor analysis, this study showed that there were four components or factors each that represent the underlying constructs of willingness and self-efficacy beliefs to provide instructional accommodations items, five components for attitudes towards providing accommodations items and three components represent the underlying constructs for knowledge about provisions of instructional accommodations items. Based on the findings, recommendations were made for improving the situation of instructional accommodations in Ethiopian universities.

Keywords: willingness, self-efficacy belief, attitude, knowledge

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Authors: Liang-Hsuan Chen, Chia-Jung Chang

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Fuzzy random variables have been introduced as an imprecise concept of numeric values for characterizing the imprecise knowledge. The descriptive parameters can be used to describe the primary features of a set of fuzzy random observations. In fuzzy environments, the expected values are usually represented as fuzzy-valued, interval-valued or numeric-valued descriptive parameters using various metrics. Instead of the concept of area metric that is usually adopted in the relevant studies, the numeric expected value is proposed by the concept of distance metric in this study based on two characters (fuzziness and randomness) of FRVs. Comparing with the existing measures, although the results show that the proposed numeric expected value is same with those using the different metric, if only triangular membership functions are used. However, the proposed approach has the advantages of intuitiveness and computational efficiency, when the membership functions are not triangular types. An example with three datasets is provided for verifying the proposed approach.

Keywords: fuzzy random variables, distance measure, expected value, descriptive parameters

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Authors: K. Shyamnath, K. Suresh Kutty

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The purpose of the study was to find out the effect of three resistance training methods on performance-related variables of powerlifters. A total of forty male students (N=40) who had participated in Kannur University powerlifting championship were selected as subjects. The age group of the subjects ranged from 18 years old to 25 years old. The selected subjects were equally divided into four groups (n=10) of three experimental groups and a control group. The experimental Group I underwent traditional resistance training (TRTG), Group II underwent combined traditional resistance training and plyometrics (TRTPG), and Group III underwent combined traditional resistance training and resistance training with high rhythm (TRTHRG). Group IV acted as the control group (CG) receiving no training during the experimental period. The duration of the experimental period was sixteen weeks, five days per week. Powerlifting performance was assessed by the 1RM test in the squat, bench press and deadlift. Performance-related variables assessed were chest girth, arm girth, forearm girth, thigh girth, and calf girth. Pre-test and post-test were conducted a day before and two days after the experimental period on all groups. Analysis of covariance (ANCOVA) was applied to analyze the significant difference. The 0.05 level of confidence was fixed as the level of significance to test the F ratio obtained by the analysis of covariance. The result indicates that there is a significant effect of all the selected resistance training methods on the performance and selected performance-related variables of powerlifters. Combined traditional resistance training and plyometrics and combined traditional resistance training and resistance training with high rhythm proved better than the traditional resistance training in improving performance and selected performance-related variables of powerlifters. There was no significant difference between combined traditional resistance training and plyometrics and combined traditional resistance training and resistance training with high rhythm in improving performance and selected performance-related variables of powerlifters.

Keywords: girth, plyometrics, powerlifting, resistance training

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Authors: Nabeel Abdulkadhim Athab

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The purpose of this research is to conduct a comparative study according analysis of programmed to some of physical and mechanical variables for joint wrist injury. As it can be through this research to distinguish between the amount of variation in the work of the joint after sample underwent rehabilitation program to improve the effectiveness of the joint and naturally restore its effectiveness. Supposed researcher that there is statistically significant differences between the results of the tests pre and post the members research sample, as a result of submission the sample to the program of rehabilitation, which led to the development of muscle activity that are working on wrist joint and this is what led to note the differences between the results of the tests pre and post. The researcher used the descriptive method. The research sample included (6) of injured players in the wrist joint, as the average age (21.68) and standard deviation (1.13) either length average (178cm) and standard deviation (2.08). And the sample as evidenced homogeneous among themselves. And where the data were collected, introduced in program for statistical processing to get to the most important conclusions and recommendations and that the most important: 1-The commitment of the sample program the qualifying process variables studied in the search for the heterogeneity of study activity and effectiveness of wrist joint for injured players. 2-The analysis programmed a high accuracy in the measurement of the research variables, and which led to the possibility of discrimination into account differences in motor ability camel and injured in the wrist joint. To search recommendations including: 1-The use of computer systems in the scientific research for the possibility of obtaining accurate research results. 2-Programming exercises rehabilitation according to an expert system for possible use by patients without reference to the person processor.

Keywords: analysis of joint wrist injury, physical and mechanical variables, wrist joint, wrist injury

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Authors: Alma Lucero Ortiz, Mario Gomez

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Technological advances contribute to the well-being of humanity by allowing man to perform in a more efficient way. Technology offers tangible advantages to countries with the adoption of information technologies, communication, and the Internet in all social and productive sectors. The Internet is a networking infrastructure that allows the communication of people throughout the world, exceeding the limits of time and space. Nowadays the internet has changed the way of doing business leading to a digital economy. In this way, e-commerce has emerged as a commercial transaction conducted over the Internet. For this inquiry e-commerce is seen as a source of economic growth for the country. Thereby, these research aims to answer the research question, which are the main variables that have affected the development of e-commerce in Mexico. The research includes a period of study from 1990 to 2017. This inquiry aims to get insight on how the independent variables influence the e-commerce development. The independent variables are information infrastructure construction, urbanization level, economic level, technology level, human capital level, educational level, standards of living, and price index. The results suggest that the independent variables have an impact on development of the e-commerce in Mexico. The present study is carried out in five parts. After the introduction, in the second part, a literature review about the main qualitative and quantitative studies to measure the variables subject to the study is presented. After, an empirical study is applied through time series data, and to process the data an econometric model is performed. In the fourth part, the analysis and discussion of results are presented, and finally, some conclusions are included.

Keywords: digital economy, e-commerce, econometric model, economic growth, internet

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Authors: Funmilayo Sarah Eguakun, Peter Oluremi Adesoye

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One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV oxide (CO2) to the atmosphere. Carbon IV oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest landsare major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine)and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influencesthe carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density speciescould be relevant for management strategy to increase carbon storage.

Keywords: adaptation, carbon sequestration, climate change, growth variables, wood density

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Authors: Mequanent Wale Mekonen, Edoardo Otranto, Angela Alibrandi

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Diabetic kidney disease is one of the main microvascular complications caused by diabetes. Several clinical and biochemical variables are reported to be associated with diabetic kidney disease in people with type 2 diabetes. However, their interrelations could distort the effect estimation of these variables for the disease's progression. The objective of the study is to determine how the biochemical and clinical variables in people with type 2 diabetes are interrelated with each other and their effects on kidney disease progression through advanced statistical methods. First, principal component analysis was used to explore how the biochemical and clinical variables intercorrelate with each other, which helped us reduce a set of correlated biochemical variables to a smaller number of uncorrelated variables. Then, ordered logit regression models (cumulative, stage, and adjacent) were employed to assess the effect of biochemical and clinical variables on the order-level response variable (progression of kidney function) by considering the proportionality assumption for more robust effect estimation. This retrospective cross-sectional study retrieved data from a type 2 diabetic cohort in a polyclinic hospital at the University of Messina, Italy. The principal component analysis yielded three uncorrelated components. These are principal component 1, with negative loading of glycosylated haemoglobin, glycemia, and creatinine; principal component 2, with negative loading of total cholesterol and low-density lipoprotein; and principal component 3, with negative loading of high-density lipoprotein and a positive load of triglycerides. The ordered logit models (cumulative, stage, and adjacent) showed that the first component (glycosylated haemoglobin, glycemia, and creatinine) had a significant effect on the progression of kidney disease. For instance, the cumulative odds model indicated that the first principal component (linear combination of glycosylated haemoglobin, glycemia, and creatinine) had a strong and significant effect on the progression of kidney disease, with an effect or odds ratio of 0.423 (P value = 0.000). However, this effect was inconsistent across levels of kidney disease because the first principal component did not meet the proportionality assumption. To address the proportionality problem and provide robust effect estimates, alternative ordered logit models, such as the partial cumulative odds model, the partial adjacent category model, and the partial continuation ratio model, were used. These models suggested that clinical variables such as age, sex, body mass index, medication (metformin), and biochemical variables such as glycosylated haemoglobin, glycemia, and creatinine have a significant effect on the progression of kidney disease.

Keywords: diabetic kidney disease, ordered logit model, principal component analysis, type 2 diabetes

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Authors: Erdinc Ozturk, Gizem Akcan

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The aim of this study was to determine some psychosocial variables that predict childhood trauma and dissociation in university students. These psychosocial variables were perceived social support, relationship status, gender and life satisfaction. 250 (125 males, 125 females) university students (bachelor, master and postgraduate degree) were enrolled in this study. They were chosen from universities in Istanbul at the education year of 2016-2017. Dissociative Experiences Scale (DES), Childhood Trauma Questionnaire (CTQ), Multidimensional Perceived Social Support Scale, Life Satisfaction Scale and Relationship Scales Questionnaire were used to assess related variables. Demographic information form was given to students in order to have their demographic information. Frequency distribution, multiple linear regression, and t-test analysis were used for statistical analysis. As together, perceived social support, relationship status and life satisfaction were found to have predictive value on trauma among university students. However, as together, these psychosocial variables did not have predictive value on dissociation. Only, trauma and relationship status had significant predictive value on dissociation. Moreover, there was significant difference between males and females in terms of trauma; however, dissociation scores of participants were not significantly different in terms of gender.

Keywords: childhood trauma, dissociation, perceived social support, relationship status, life satisfaction

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Authors: Nurul Hidayat

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Based on the data from the Indonesian Tax Authority, the contribution of self-employed taxpayers in Indonesia is just approximately 1-2 percent of total tax revenues during 2013 - 2015. This phenomenon requires greater attention to understand what factors that may affect it. The fact that Indonesia has the most prominent Muslim population in the world makes it important to analyze whether there potentially exists a correlation between Islamic religiosity and low tax contribution. The low level of tax contribution may provide an initial indication of low tax morale and tax compliance. This study will extend the existing literature by investigating the influence of Islamic religiosity as a moderating effect on the relationship between the perceptions of government legitimacy and tax morale among self-employed taxpayers. There are some factors to consider when taking into account the issue of Islamic religiosity and its relationship with tax morale in this study. Firstly, in Islam, there is a debate surrounding the lawfulness of tax. Some argue that Muslims should not have to pay tax; while others argue that the imposition of the tax is legitimate in circumstances. These views may have an impact on government legitimacy and tax morale. Secondly, according to Islamic sharia, Islam recognizes another compulsory payment, i.e. zakat, which to some extent has similar characteristics to tax. According to Indonesian Income Tax Law, zakat payment has just been accommodated as a deduction from taxable income. As a comparison, Malaysia treats zakat as a tax rebate. The treatment of zakat only as a taxable income deduction may also lead to a conflicting issue regarding the perception of tax fairness that possibly erode the perception of government legitimacy and tax morale. Based on the considerations above, perceptions of government legitimacy become important to influence the willingness of people to pay tax while the level of Islamic religiosity has a potential moderator effect on that correlation. In terms of measuring the relationship among the variables, this study utilizes mixed-quantitative and qualitative methods. The quantitative methods use surveys to approximately 400 targeted taxpayers while the qualitative methods employ in-depth interviews with 12 people, consist of experts, Islamic leaders and selected taxpayers. In particular, the research is being conducted in Indonesia, the country with the largest Muslim population in the world which has not fully implemented Islamic law as state law. The result indicates that Islamic religiosity becomes a moderating effect on the way taxpayers perceived government legitimacy that finally influences on tax morale. The findings of this study are supportive for the improvement of tax regulations by specifically considering tax deductions for zakat.

Keywords: Islamic religiosity, tax morale, government legitimacy, zakat

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Authors: Ebru Ozgur Guler, Huseyin Guler, Sera Sanli

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Social Progress Index (SPI) whose fundamentals have been thrown in the World Economy Forum is an index which aims to form a systematic basis for guiding strategy for inclusive growth which requires achieving both economic and social progress. In this research, it has been aimed to determine the relations among “Basic Human Needs” (BHN) (including four variables of ‘Nutrition and Basic Medical Care’, ‘Water and Sanitation’, ‘Shelter’ and ‘Personal Safety’) and “Opportunity” (OPT) (that is composed of ‘Personal Rights’, ‘Personal Freedom and Choice’, ‘Tolerance and Inclusion’, and ‘Access to Advanced Education’ components) dimensions of 2016 SPI for 138 countries which take place in the website of Social Progress Imperative by carrying out canonical correlation analysis (CCA) which is a data reduction technique that operates in a way to maximize the correlation between two variable sets. In the interpretation of results, the first pair of canonical variates pointing to the highest canonical correlation has been taken into account. The first canonical correlation coefficient has been found as 0.880 indicating to the high relationship between BHN and OPT variable sets. Wilk’s Lambda statistic has revealed that an overall effect of 0.809 is highly large for the full model in order to be counted as statistically significant (with a p-value of 0.000). According to the standardized canonical coefficients, the largest contribution to BHN set of variables has come from ‘shelter’ variable. The most effective variable in OPT set has been detected to be ‘access to advanced education’. Findings based on canonical loadings have also confirmed these results with respect to the contributions to the first canonical variates. When canonical cross loadings (structure coefficients) are examined, for the first pair of canonical variates, the largest contributions have been provided by ‘shelter’ and ‘access to advanced education’ variables. Since the signs for structure coefficients have been found to be negative for all variables; all OPT set of variables are positively related to all of the BHN set of variables. In case canonical communality coefficients which are the sum of the squares of structure coefficients across all interpretable functions are taken as the basis; amongst all variables, ‘personal rights’ and ‘tolerance and inclusion’ variables can be said not to be useful in the model with 0.318721 and 0.341722 coefficients respectively. On the other hand, while redundancy index for BHN set has been found to be 0.615; OPT set has a lower redundancy index with 0.475. High redundancy implies high ability for predictability. The proportion of the total variation in BHN set of variables that is explained by all of the opposite canonical variates has been calculated as 63% and finally, the proportion of the total variation in OPT set that is explained by all of the canonical variables in BHN set has been determined as 50.4% and a large part of this proportion belongs to the first pair. The results suggest that there is a high and statistically significant relationship between BHN and OPT. This relationship is generally accounted by ‘shelter’ and ‘access to advanced education’.

Keywords: canonical communality coefficient, canonical correlation analysis, redundancy index, social progress index

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Authors: Rhea Mathews

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The purpose of the study is to investigate the effects of perceived social support and cultural self-efficacy on the acculturative stress of international postgraduate students in the United Kingdom. The study adopted Berry, Kim, Minde & Mok’s (1987) acculturative framework on acculturative stress and examined the relationship between the variables. The study hypothesized that perceived social support and cultural self-efficacy would predict lower levels of acculturative stress among students. Postgraduate students in the United Kingdom (N = 76) completed three surveys measuring the variables; Acculturative Stress Scale for International Students, Multidimensional Scale of Perceived Social Support, and Cultural Self-efficacy for Adolescents. To evaluate the role of the perceived social support and cultural self-efficacy in determining the acculturative stress level of international students, multiple linear regression was employed. Both independent variables exhibited a significant, negative relationship with acculturative stress (p < 0.001; p < 0.01). Results described that cultural self-efficacy and perceived social support significantly predicted acculturative stress (p < 0.01). Together, the variables accounted for 22% of the variance in acculturative stress scores (adjusted R² = 0.22), with cultural self-efficacy playing a larger role in predicting the dependent variable. Limitations and implications of the study are noted. The findings of the study are discussed in relation to enhancing international students’ acculturative experience when relocating to a new environment.

Keywords: acculturative stress, coping, cultural adjustment, cultural self-efficacy, international education, international students, migration, perceived social support

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Authors: Bediru Abamecha

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Background: Domestic violence is a global problem that occurs regardless of culture, ethnicity or socio-economic class. It is known to be responsible for numerous hospital visits undertaken by women. Violence on pregnant women is a health and social problem that poses particular risks to the woman and her unborn child. Objective: The Objective of this study will be to assess prevalence of domestic violence and its correalates among pregnant women in Manna Woreda of Jimma Zone. Methods: Simple Random Sampling technique will be used to select 12 kebeles (48% of the study area) and Systematic Sampling will be used to reach to the house hold in selected kebeles in manna woreda of Jimma zone, south west Ethiopia from february 15-25, 2011. An in-depth interview will be conducted on Women affairs, police office and Nurses working and minimum of 4FGD with 6-8 members on pregnant women and selected male from the community. SPSS version 16.0 will be used to enter, clean and analyze the data. Descriptive statistics such as mean or median for continuous variables and percent for categorical variables will be made. Bivariate analysis will be used to check the association between independent variables and domestic violence. Variables found to have association with domestic violence will be entered to multiple logistic regressions for controlling the possible effect of confounders and finally the variables which had significance association will be identified on basis of OR, with 95% CI. All statistical significance will be considered at p<0.05. The qualitative data will be summarized manually and thematic analysis will be performed and finally both will be triangulated.

Keywords: ante natal care, ethiopian demographic and health survey, domestic violence, statistical package for social science

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Authors: Pedram Saadati, Zahra Nazari

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Anticipating and identifying future opportunities and challenges facing industry activists for the emergence and entry of new knowledge and technologies of personal financial planning, and providing practical solutions is one of the goals of this research. For this purpose, a future research tool based on receiving opinions from the main players of the insurance industry has been used. The research method in this study was in 4 stages; including 1- a survey of the specialist salesforce of life insurance in order to identify the variables 2- the ranking of the variables by experts selected by a researcher-made questionnaire 3- holding a panel of experts with the aim of understanding the mutual effects of the variables and 4- statistical analyzes of the mutual effects matrix in Mick Mac software is done. The integrated analysis of influencing variables in the future has been done with the method of Structural Analysis, which is one of the efficient and innovative methods of future research. A list of opportunities and challenges was identified through a survey of best-selling life insurance representatives who were selected by snowball sampling. In order to prioritize and identify the most important issues, all the issues raised were sent to selected experts who were selected theoretically through a researcher-made questionnaire. The respondents determined the importance of 36 variables through scoring, so that the prioritization of opportunity and challenge variables can be determined. 8 of the variables identified in the first stage were removed by selected experts, and finally, the number of variables that could be examined in the third stage became 28 variables, which, in order to facilitate the examination, were divided into 6 categories, respectively, 11 variables of organization and management. Marketing and sales 7 cases, social and cultural 6 cases, technological 2 cases, rebranding 1 case and insurance 1 case were divided. The reliability of the researcher-made questionnaire was confirmed with the Cronbach's alpha test value of 0.96. In the third stage, by forming a panel consisting of 5 insurance industry experts, the consensus of their opinions about the influence of factors on each other and the ranking of variables was entered into the matrix. The matrix included the interrelationships of 28 variables, which were investigated using the structural analysis method. By analyzing the data obtained from the matrix by Mic Mac software, the findings of the research indicate that the categories of "correct training in the use of the software, the weakness of the technology of insurance companies in personalizing products, using the approach of equipping the customer, and honesty in declaring no need Customer to Insurance", the most important challenges of the influencer and the categories of "salesforce equipping approach, product personalization based on customer needs assessment, customer's pleasant experience of being consulted with consulting robots, business improvement of the insurance company due to the use of these tools, increasing the efficiency of the issuance process and optimal customer purchase" were identified as the most important opportunities for influence.

Keywords: personal financial planning, wealth management, advisor robots, life insurance, digital transformation

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Authors: Xinyuan Y. Song, Kai Kang

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Joint models for analyzing longitudinal and survival data are widely used to investigate the relationship between a failure time process and time-variant predictors. A common assumption in conventional joint models in the survival analysis literature is that all predictors are observable. However, this assumption may not always be supported because unobservable traits, namely, latent variables, which are indirectly observable and should be measured through multiple observed variables, are commonly encountered in the medical, behavioral, and financial research settings. In this study, a joint modeling approach to deal with this feature is proposed. The proposed model comprises three parts. The first part is a dynamic factor analysis model for characterizing latent variables through multiple observed indicators over time. The second part is a random coefficient trajectory model for describing the individual trajectories of latent variables. The third part is a proportional hazard model for examining the effects of time-invariant predictors and the longitudinal trajectories of time-variant latent risk factors on hazards of interest. A Bayesian approach coupled with a Markov chain Monte Carlo algorithm to perform statistical inference. An application of the proposed joint model to a study on the Alzheimer's disease neuroimaging Initiative is presented.

Keywords: Bayesian analysis, joint model, longitudinal data, time-to-event data

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Authors: B. Seetanah, H. Neeliah

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This paper investigates the relationship among energy, emissions and economic growth in Mauritius in the presence of trade activities, with capital and labour as other control variables. Using annual data from 1960 to 2011, it is found that the variables are non-stationary and cointegrated. The relationship among the various variables are thus examined in a dynamic VECM framework. Our empirical results comply with the growth hypothesis. Output elasticities of 0.17, 0.25 and 0.43 show that increases in energy consumption cause increases in economic growth, capital accumulation and trade in the long run. We also found that CO2 negatively affects output, but has no significant effect on trade. Findings for the long-run generally tend to tally with those in the short-run. Interestingly we found that energy consumption has a significant impact on CO2 emissions. Our results tend to suggest that implementing energy conservation strategies to mitigate the negative impact of CO2 emissions can dent economic growth, and that promoting cleaner energy production could be a better alternative for Mauritius.

Keywords: energy, emissions, economic growth, export, VECM

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Authors: Enrique Nunez L., Maria Cortes L., Sandra Laffon L., Ana M. Cupul V.

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The phytoplankton community composition was studied in a tropical coastal lagoon of Mexico and relationships with environmental variables were evaluated. Six sites inside the tropical Terminos Lagoon were sampled in order to determine abundances and ecological indexes for phytoplankton from May to December 2017. Water samples were also collected to determine the values of pigments, nutrients, and water solids. Results showed that the composition and abundance of the phytoplankton community were influenced by physicochemical factors, nutrients, water solids, and climate seasons. Sixty-six species were identified as potential HAB producers (44.29% from total). However, abundances were not related to the occurrence of HAB during the study. Multidimensional ANOVA indicated no significant differences between sites while some months revealed significant differences. The canonical analysis suggested that environmental variables explained 49% of community variation of potential phytoplankton species producers of HAB.

Keywords: phytoplankton, environment, lagoon, biodiversity

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Authors: Mei-Se Chien, Chien-Chiang Lee, Sin-Jie Cai

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The main purpose of this paper is to investigate the long-run equilibrium and short-run dynamics of international housing prices when macroeconomic variables change. We apply the Pedroni’s, panel cointegration, using the unbalanced panel data analysis of 33 countries over the period from 1980Q1 to 2013Q1, to examine the relationships among house prices and macroeconomic variables. Our empirical results of panel data cointegration tests support the existence of a cointegration among these macroeconomic variables and house prices. Besides, the empirical results of panel DOLS further present that a 1% increase in economic activity, long-term interest rates, and construction costs cause house prices to respectively change 2.16%, -0.04%, and 0.22% in the long run. Furthermore, the increasing economic activity and the construction cost would cause stronger impacts on the house prices for lower income countries than higher income countries. The results lead to the conclusion that policy of house prices growth can be regarded as economic growth for lower income countries. Finally, in America region, the coefficient of economic activity is the highest, which displays that increasing economic activity causes a faster rise in house prices there than in other regions. There are some special cases whereby the coefficients of interest rates are significantly positive in America and Asia regions.

Keywords: house prices, macroeconomic variables, panel cointegration, dynamic OLS

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Authors: Rabeeya Raoof, Abrar Ul-Haq, Muhammad Arshad

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The current study is trying to explain the relationship between entrepreneurial education and entrepreneurial passion. This study introduces multiple mechanisms by which entrepreneurial education may induce entrepreneurial passion in business graduates. With the help of expectancy theory, we proposed that entrepreneurial education develops entrepreneurial passion through the mediation of desirability and feasibility. Furthermore, desirability is also influencing feasibility. Therefore, desirability and feasibility may also play their role as double mediators in the relationship between entrepreneurial education and passion. The role of gender has become very vital in entrepreneurship studies. Therefore, we also incorporated the role of gender as a moderator while studying the indirect effect of entrepreneurial education on entrepreneurial passion via desirability and feasibility. We proposed that entrepreneurial education may influence the passion of male individuals primarily through feasibility. On the other hand, entrepreneurial education may impact on the entrepreneurial passion of female individuals primarily through the mediation of desirability. Learning orientation may increase the direct effect of entrepreneurial education on entrepreneurial passion.

Keywords: entrepreneurial passion, perceived desirability, perceived feasibility, entrepreneurial intention

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Authors: Vahid Nourani, Atefeh Ashrafi

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Prediction of treated wastewater quality is a matter of growing importance in water treatment procedure. In this way artificial neural network (ANN), as a robust data-driven approach, has been widely used for forecasting the effluent quality of wastewater treatment. However, developing ANN model based on appropriate input variables is a major concern due to the numerous parameters which are collected from treatment process and the number of them are increasing in the light of electronic sensors development. Various studies have been conducted, using different clustering methods, in order to classify most related and effective input variables. This issue has been overlooked in the selecting dominant input variables among wastewater treatment parameters which could effectively lead to more accurate prediction of water quality. In the presented study two ANN models were developed with the aim of forecasting effluent quality of Tabriz city’s wastewater treatment plant. Biochemical oxygen demand (BOD) was utilized to determine water quality as a target parameter. Model A used Principal Component Analysis (PCA) for input selection as a linear variance-based clustering method. Model B used those variables identified by the mutual information (MI) measure. Therefore, the optimal ANN structure when the result of model B compared with model A showed up to 15% percent increment in Determination Coefficient (DC). Thus, this study highlights the advantage of PCA method in selecting dominant input variables for ANN modeling of wastewater plant efficiency performance.

Keywords: Artificial Neural Networks, biochemical oxygen demand, principal component analysis, mutual information, Tabriz wastewater treatment plant, wastewater treatment plant

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Authors: H. Khomri, A. Bentellis

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Since century of the Development Activities extraction and a dispersed mineral processing Toxic metals and much more contaminated vast areas occupied by what they natural outcrops. New types of metalliferous habitats are so appeared. A species that is Lygeum spartum attracted our curiosity because apart from its valuable role in desertification, it is apparently able to exclude antimony and other metals can be. This species, green leaf blades which are provided as cattle feed, would be a good subject for phytoremediation of mineral soils. The study of absorption and translocation of chromium by the Lygeum spartum in the mining region of Djebel Hamimat and the interaction soil-plant, revealed that soils of this species living in this region are alkaline, calcareous majority in their fine texture medium and saline in their minority. They have normal levels of organic matter. They are moderately rich in nitrogen. They contain total chromium content reaches a maximum of 66,80 mg Kg^(-1) and a total absence of soluble chromium. The results of the analysis of variance of the difference between bare soils and soils appear Lygeum spartum made a significant difference only for the silt and organic matter. But for the other variables analyzed this difference is not significant. Thus, this plant has only one action on the amendment, only the levels of silt and organic matter in soils. The results of the multiple regression of the chromium content of the roots according to all soil variables studied did appear that among the studied variables included in the model, only the electrical conductivity and clay occur in the explanation of contents chromium in roots. The chromium content of the aerial parts analyzed by regression based on all studied soil variables allows us to see only the variables: electrical conductivity and content of chromium in the root portion involved in the explanation of the content chromium in the aerial part.

Keywords: absorption, translocation, analysis of variance, chrome, Lygeum spartum, multiple regression, the soil variables

Procedia PDF Downloads 269