Search results for: moderating variables

Authors: S. Boria

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In the last years, the crashworthiness of an automotive body structure can be improved, since the beginning of the design stage, thanks to the development of specific optimization tools. It is well known how the finite element codes can help the designer to investigate the crashing performance of structures under dynamic impact. Therefore, by coupling nonlinear mathematical programming procedure and statistical techniques with FE simulations, it is possible to optimize the design with reduced number of analytical evaluations. In engineering applications, many optimization methods which are based on statistical techniques and utilize estimated models, called meta-models, are quickly spreading. A meta-model is an approximation of a detailed simulation model based on a dataset of input, identified by the design of experiments (DOE); the number of simulations needed to build it depends on the number of variables. Among the various types of meta-modeling techniques, Kriging method seems to be excellent in accuracy, robustness and efficiency compared to other ones when applied to crashworthiness optimization. Therefore the application of such meta-model was used in this work, in order to improve the structural optimization of a bumper for a racing car in composite material subjected to frontal impact. The specific energy absorption represents the objective function to maximize and the geometrical parameters subjected to some design constraints are the design variables. LS-DYNA codes were interfaced with LS-OPT tool in order to find the optimized solution, through the use of a domain reduction strategy. With the use of the Kriging meta-model the crashworthiness characteristic of the composite bumper was improved.

Keywords: composite material, crashworthiness, finite element analysis, optimization

Procedia PDF Downloads 239

Authors: Mohammad Azam

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This work is an endeavor to empirically investigate the Gross Domestic Product-Growth as mediating variable between various factors and portfolio returns using a broad sample of 522 financial and non-financial firms enlisted on Pakistan Stock Exchange between January-1993 and June-2022. The study employs the Structural Equation modeling and Ordinary Least Square regression to determine the findings before and during the Covid-19 epidemiological situation, which has not received due attention by researchers. The analysis reveals that market and investment factors are redundant, whereas size and value show significant results, whereas Gross Domestic Product-Growth performs significant mediating impact for the whole time frame. Using before Covid-19 period, the results reveal that market, value, and investment are redundant, but size, profitability, and Gross Domestic Product-Growth are significant. During the Covid-19, the statistics indicate that market and investment are redundant, though size and Gross Domestic Product-Growth are highly significant, but value and profitability are moderately significant. The Ordinary Least Square regression shows that market and investment are statistically insignificant, whereas size is highly significant but value and profitability are marginally significant. Using the Gross Domestic Product-Growth augmented model, a slight growth in R-square is observed. The size, value and profitability factors are recommended to the investors for Pakistan Stock Exchange. Conclusively, in the Pakistani market, the Gross Domestic Product-Growth indicates a feeble moderating effect between risk-premia and portfolio returns.

Keywords: asset pricing puzzle, mediating role of GDP-growth, structural equation modeling, COVID-19 pandemic, Pakistan stock exchange

Procedia PDF Downloads 53

Authors: Hanifa Taher, Sulaiman Al-Zuhair, Ali H. Al-Marzouqi, Yousef Haik, Mohammed Farid

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Biodiesel, as an alternative renewable fuel, has been receiving increasing attention due to the limited supply of fossil fuels and the increasing need for energy. Microalgae is a promising source for lipids, which can be converted to biodiesel. The biodiesel production from microalgae lipids using lipase catalyzed reaction in supercritical CO2 medium has several advantages over conventional production processes. However, identifying the optimum microalgae lipid extraction and transesterification conditions is still a challenge. In this study, the lipids extracted from Scenedesmus sp. and their enzymatic transesterification using supercritical carbon dioxide have been investigated. The effect of extraction variables (temperature, pressure and solvent flow rate) and reaction variables (enzyme loading, incubation time, methanol to lipids molar ratio and temperature) were considered. Process parameters and their effects were studied using a full factorial analysis of both. Response Surface Methodology (RSM) and was used to determine the optimum conditions for the extraction and reaction steps. For extraction, the optimum conditions were 53 °C and 500 bar, whereas for the reaction the optimum conditions were 35% enzyme loading, 4 h reaction, 9:1 molar ratio and 50 oC. At these optimum conditions, the highest biodiesel production yield was found to be 82 %. The fuel properties of the produced biodiesel, at optimum reaction condition, were determined and compared to ASTM standards. The properties were found to comply with the limits, and showed a low glycerol content, without any separation step.

Keywords: biodiesel, lipase, supercritical CO2, standards

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Authors: Magda Milleyde de Sousa Lima, Letícia Lima Aguiar, Marina Guerra Martins, Erika Veríssimo Dias Sousa, Lizandra Sampaio de Oliveira, Lívia Moreira Barros, Joselany Áfio Caetano

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Patients with chronic kidney disease are vulnerable to episodes which make the safety of their health vulnerable, mainly due to the treatment process that exposes them to high rates of interventions during hemodialysis sessions. Some factors associated with health care contribute to the risk of death and complications. However, there are a small number of scientific studies evaluating the level of safety of hemodialysis clinics, and the sociodemographic characteristics of patients and professionals associated with this safety. Therefore, the present study aims to examine the level of patient safety in hemodialysis clinics in the Brazilian capital, to identify the sociodemographic and clinical factors of patients and nursing staff associated with the level of safety. This is an observational, descriptive and quantitative research conducted in three hemodialysis clinics placed in the city of Fortaleza-CE, Brazil, from September to November 2019. The sample was formed after a sample calculation for finite inhabitants of correlation with 200 chronic renal patients, 30 nursing technicians and seven nurses. Conventional sampling was used based on the inclusion criteria: being present at the hemodialysis session on the day the researcher performed the data collection and being 18 years of age or older. Participants who presented communication difficulties to listen to and/or answer the sociodemographic and clinical questionnaire were excluded. Two instruments were applied: sociodemographic and clinical characterization form and Chronic Renal Patient Safety Assessment Scale on Hemodialysis (EASPRCH). The data were analyzed using the Kruskal Walls Test for categorical variables and Spearman correlation coefficient for non-categorical variables, using the Statistical Package SPSS version 20.0. The present study respected the ethical and legal principles determined by resolution 466/2012 of the National Health Council, under the approval of the Ethics and Research Committee with an opinion number: 3,255,635. The results showed that a hemodialysis clinic presented unsafe care practices of 32 points in the EASPRCH (p=0.001). A statistical association was identified between the level of safety and the variables of the patients: level of education (p=0.018), family income (p=0.049), type of employment (p=0.012), venous access site (p=0.009), use of medication during the session (p=0.008) and time of hemodialysis (p=0.002). When evaluating the profile of nurses, a statistical association was evidenced between the level of safety with the variables: marital status (p=0.000), race (p=0.017), schooling (p= 0.000), income (p=0.013), age (p=0.000), clinic workload (p=0.000), time working with hemodialysis (p=0.000), time working in the clinic (p= 0.007) and clinic sizing (p=0.000). In order, the sociodemographic factors of nursing technicians associated with the level of patient safety were: race (p= 0.001) and weekly workload at (p=0.010). Therefore, it is concluded that there is a non-conformity in the level of patient safety in one of the clinics studied and, that sociodemographic and clinical factors of patients and health professionals corroborate the level of safety of the health unit.

Keywords: hemodialysis, nursing, patient safety, quality improvement

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Authors: Simao E. Luis

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From the 1960s to the 1990s, the social-psychological framework of language attitudes that emerged from the Canadian research tradition was very influential. Integrativeness was one of the main variables in Gardner’s theory because refugees and immigrants were motivated to learn English and French to integrate into the Canadian community. Second language (L2) scholars have expressed concerns over integrativeness because it cannot explain the motivation of L2 learners in global contexts. This study aims to investigate student motivation to learn English as a foreign language in Mozambique, and to contribute to the ongoing validation of the L2 Motivational Self System theory in an under-researched country. One hundred thirty-seven (N=137) university students completed a well-established motivation questionnaire. The data were analyzed with SPSS, and descriptive statistics, correlations, multiple regressions, and MANOVA were conducted. Results show that many variables contribute to motivated learning behavior, particularly the L2 learning experience and attitudes towards the English language. Statistically significant differences were found between males and females, with males expressing more motivation to learn the English language for personal interests. Statistically significant differences were found between older and younger students, with older students reporting more vivid images of themselves as future English language users. These findings have pedagogical implications because motivational strategies are positively correlated with student motivated learning behavior. Therefore, teachers should design L2 tasks that can help students to develop their future L2 selves.

Keywords: English as a foreign language, L2 motivational self system, Mozambique, university students

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Authors: Jumel Christian P. Nicha, Severino G. Salmo III

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This study investigated the concentration of heavy metals (HM) in mangrove sediments of Lake Uacon, Zambales, Philippines. The relationship among the studied HM (Cr, Ni, Pb, Cu, Cd, Fe) and the mangrove vegetation and sediment characteristics were assessed. Fourteen sampling plots were designated across the lake (10 vegetated and 4 un-vegetated) based on distance from the mining effluents. In each plot, three sediment cores were collected at 20 cm depth. Among the dominant mangrove species recorded were (in order of dominance): Sonneratia alba, Rhizophora stylosa, Avicennia marina, Excoecaria agallocha and Bruguiera gymnorrhiza. Sediment samples were digested with aqua regia, and the HM concentrations were quantified using Atomic Absorption Spectroscopy (AAS). Results showed that HM concentrations were higher in the vegetated plots as compared to the un-vegetated sites. Vegetated sites had high Ni (mean: 881.71 mg/kg) and Cr (mean: 776.36 mg/kg) that exceeded the threshold values (cf. by the United States Environmental Protection Agency; USEPA). Fe, Pb, Cu and Cd had a mean concentration of 2597.92 mg/kg, 40.94 mg/kg, 36.81 mg/kg and 2.22 mg/kg respectively. Vegetation variables were not significantly correlated with HM concentration. However, the HM concentration was significantly correlated with sediment variables particularly pH, redox, particle size, nitrogen, phosphorus, moisture and organic matter contents. The Pollution Load Index (PLI) indicated moderate to high pollution in the lake. Risk assessment and management should be designed in order to mitigate the ecological risk posed by HM. The need of a regular monitoring scheme for lake and mangrove rehabilitation programs and management should be designed.

Keywords: heavy metals, mangrove vegetation, mining, Philippines, sediment

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Authors: Chechen Liao, Pui-Lai To, Chuang-Chun Liu

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Online shopping has become very popular recently. In today’s highly competitive online retail environment, retaining existing customers is a necessity for online retailers. This study focuses on the antecedents and consequences of Internet buyer regret and satisfaction in the online consumer purchasing process. This study examines the roles that online consumer’s purchasing process evaluations (i.e., search experience difficulty, service-attribute evaluations, product-attribute evaluations and post-purchase price perceptions) and alternative evaluation (i.e., alternative attractiveness) play in determining buyer regret and satisfaction in e-commerce. The study also examines the consequences of regret, satisfaction and habit in regard to repurchase intention. In addition, this study attempts to investigate the moderating role of habit in attaining a better understanding of the relationship between repurchase intention and its antecedents. Survey data collected from 431 online customers are analyzed using structural equation modeling (SEM) with partial least squares (PLS) and support provided for the hypothesized links. These results indicate that online consumer’s purchasing process evaluations (i.e., search experience difficulty, service-attribute evaluations, product-attribute evaluations and post-purchase price perceptions) have significant influences on regret and satisfaction, which in turn influences repurchase intention. In addition, alternative evaluation (i.e., alternative attractiveness) has a significant positive influence on regret. The research model can provide a richer understanding of online customers’ repurchase behavior and contribute to both research and practice.

Keywords: online shopping, purchase evaluation, regret, satisfaction

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Authors: Swapnila V. Shinde, Hemant P. Joshi, Sumit R. Dhas, Dhananjaysingh B. Rajput

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The objective of the present study is to develop hydro-dynamically balanced system for atenolol, β-blocker as a single unit floating tablet. Atenolol shows pH dependent solubility resulting into a bioavailability of 36%. Thus, site specific oral controlled release floating drug delivery system was developed. Formulation includes novice use of rate controlling polymer such as locust bean gum (LBG) in combination of HPMC K4M and gas generating agent sodium bicarbonate. Tablet was prepared by direct compression method and evaluated for physico-mechanical properties. The statistical method was utilized to optimize the effect of independent variables, namely amount of HPMC K4M, LBG and three dependent responses such as cumulative drug release, floating lag time, floating time. Graphical and mathematical analysis of the results allowed the identification and quantification of the formulation variables influencing the selected responses. To study the gastrointestinal transit of the optimized gastro-retentive formulation, in vivo gamma scintigraphy was carried out in six healthy rabbits, after radio labeling the formulation with 99mTc. The transit profiles demonstrated that the dosage form was retained in the stomach for more than 5 hrs. The study signifies the potential of the developed system for stomach targeted delivery of atenolol with improved bioavailability.

Keywords: floating tablet, factorial design, gamma scintigraphy, antihypertensive model drug, HPMC, locust bean gum

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Authors: Jarrod Sio Jyh Lih

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This paper discusses the factors contributing to student achievement in literacy and numeracy in primary schools within Sibu division. The study involved 694 level 1 primary schoolteachers. Using descriptive statistics, the study observed high levels of practice for teacher efficacy, instructional leadership and professional learning communities (PLCs). The differences between gender, teaching experience and academic qualification were analyzed using the t-test and one-way analysis of variance (ANOVA). The study reported significant differences in respondent perceptions based on teaching experience vis-à-vis teacher efficacy. Here, the post hoc Tukey test revealed that efficaciousness grows with experience. A correlation test observed positive and significant correlations between all independent variables. Binary logistic regression was applied to predict the independent variables’ influence on student achievement. The findings revealed that a dimension of instructional leadership – ‘monitoring student progress’ - emerged as the best predictor of student achievement for literacy and numeracy. The result indicated the students were more than 4 times more likely to achieve the national key performance index for both literacy and numeracy when student progress was monitored. In conclusion, ‘monitoring student progress’ had a positive influence on students’ achievement for literacy and numeracy, hence making it a possible course of action for school heads. However, more comprehensive studies are needed to ascertain its consistency within the context of Malaysia.

Keywords: efficacy, instructional, literacy, numeracy

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Authors: Baljinder Singh, Navneet Sharma

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Chromium is an essential nutrient involved in normal carbohydrate and lipid metabolism. It influences glucose metabolism by potentiating the action as taking part in insulin signal amplification mechanism. A placebo-controlled single blind, prospective study was carried out to investigate the effect of chromium supplementation on blood glucose, HbA1C and lipid profile in newly onset patients with type-2 diabetes. Total 40 newly onset type-2 diabetics were selected and after one month stabilization further randomly divided into two groups viz. study group and placebo group. The study group received 9 gm brewer’s yeast (42 μ Cr) daily and the other placebo group received yeast devoid of chromium for 3 months. Subjects were instructed not to change their normal eating and living habits. Fasting blood glucose, HbA1C and lipid profile were analyzed at beginning and completion of the study. Results revealed that fasting blood glucose level significantly reduced in the subjects consuming yeast supplemented with chromium (197.65±6.68 to 103.68±6.64 mg/dl; p<0.001). HbA1C values improved significantly from 9.51±0.26% to 6.86±0.28%; p<0.001 indicating better glycaemic control. In experimental group total cholesterol, TG and LDL levels were also significantly reduced from 199.66±3.11 to 189.26±3.01 mg/dl; p<0.02, 144.94±8.31 to 126.01±8.26; p<0.05 and 119.19±1.71 to 99.58±1.10; p<0.001 respectively. These data demonstrate beneficial effect of chromium supplementation on glycaemic control and lipid variables in subjects with newly onset type-2 diabetes.

Keywords: type-2 diabetes, chromium, glucose, HbA1C

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Authors: Hussaini Tunde Subairu

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Small and Medium Enterprises (SMEs) sectors serve as catalyst for employment generation, national growth, poverty reduction and economic development in developing and developed countries. However, in Nigeria despite copious and plethora of government policies and stimulus schemes directed at SMEs, the sector is still characterized by high rate of failure and discontinuities. This study therefore investigated owners/managers profile, firms characteristics and external factors as possible determinants of SMEs growth from selected SMEs in Kwara State. Primary data were sourced from 200 SMEs respondents registered with the National Association of Small and Medium Enterprises (NASMES) in Kwara State Central Senatorial District. Multiple Regressions Analysis (MRA) was used to analyze the relationship between dependent and independent variables, and pair wise correlation was employed to examine the relationship among independent variables. The Analysis of Variable (ANOVA) was employed to indicate the overall significant of the model The findings revealed that Analysis of variance (ANOVA) put the value of F-statistics at 420.45 and p-value at 0.000 was significant. The values of R2 and Adjusted R2 of 0.9643 and 0.9620 respectively suggested that 96 percent of variations in employment growth were explained by the explanatory variables. The level of technical and managerial education has t- value of 24.14 and p-value of 0.001, length of managers/owners experience in similar trade with t- value of 21.37 and p-value of 0.001, age of managers/owners with t- value of 42.98 and p-value of 0.001, firm age with t- value of 25.91 and p-value of 0.001, numbers of firms in a cluster with t- value of 7.20 and p-value of 0.001, access to formal finance with t-value of 5.56 and p-value of 0.001, firm technology innovation with t- value of 25.32 and p-value of 0.01, institutional support with t- value of 18.89 and p-value of 0.01, globalization with t- value of 9.78 and p-value of 0.01, and infrastructure with t-value of 10.75 and p-value of 0.01. The result also indicated that initial size has t-value of -1.71 and p-value of 0.090 which is consistent with Gibrat’s Law. The study concluded that owners/managers profile, firm specific characteristics and external factors substantially influenced employment growths of SMEs in the study area. Therefore, policy implication should enhance human capital development of SMEs owners/managers, and strengthen fiscal policy thrust through imposition on tariff regime to minimize effect of globalization. Governments at all level must support SMEs growth radically and enhance institutional support for SMEs growth and radically and significantly upgrading key infrastructure as rail/roads, rail, telecommunications, water and power.

Keywords: external factors, firm specific characteristics, owners / manager profile, small and medium enterprises

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Authors: Edokpa Idemudia Waziri, Salisu S. Umar

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The Hotellng’s T^2 is a well-known statistic for detecting a shift in the mean vector of a multivariate normal distribution. Control charts based on T have been widely used in statistical process control for monitoring a multivariate process. Although it is a powerful tool, the T statistic is deficient when the shift to be detected in the mean vector of a multivariate process is small and consistent. The Multivariate Exponentially Weighted Moving Average (MEWMA) control chart is one of the control statistics used to overcome the drawback of the Hotellng’s T statistic. In this paper, the probability distribution of the Average Run Length (ARL) of the MEWMA control chart when the quality characteristics exhibit substantial cross correlation and when the process is in-control and out-of-control was derived using the Markov Chain algorithm. The derivation of the probability functions and the moments of the run length distribution were also obtained and they were consistent with some existing results for the in-control and out-of-control situation. By simulation process, the procedure identified a class of ARL for the MEWMA control when the process is in-control and out-of-control. From our study, it was observed that the MEWMA scheme is quite adequate for detecting a small shift and a good way to improve the quality of goods and services in a multivariate situation. It was also observed that as the in-control average run length ARL0¬ or the number of variables (p) increases, the optimum value of the ARL0pt increases asymptotically and as the magnitude of the shift σ increases, the optimal ARLopt decreases. Finally, we use the example from the literature to illustrate our method and demonstrate its efficiency.

Keywords: average run length, markov chain, multivariate exponentially weighted moving average, optimal smoothing parameter

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Authors: Gulcin Satir, Ahmet Yildirim

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Globally, including Turkey, health problems associated with malnutrition and nutrient deficiencies in childhood will remain major public health problems in future. Nutrition is a major environmental influence on physical and mental growth and development in early life. Many studies support the fact that nutritional knowledge makes contribution to wellbeing of children and their school performance. The purpose of this study was to examine nutritional knowledge and eating habits of primary school children and to investigate differences in these variables by socioeconomic status. A quasi-experimental one group pretest/posttest design study was conducted in five primary schools totaling 200 children aging 9-10 years in grade 4 to determine the effect of nutritional awareness programme on eating habits of primary school children. The schools were chosen according to parents’ social and demographic characteristics. The implemented nutritional awareness education programme focused on healthy lifestyle such as beneficial foods, eating habits, personal hygiene, physical activity and the programme consisted of eight lessons. The teaching approaches used included interactive teaching, role-playing, demonstration, small group discussions, questioning, and feedback. The lessons were given twice a week for four weeks totaling eight lessons. All lessons lasted 45-60 minutes and first 5 minutes of this was pre-assessment and last 5 minutes post assessment evaluation. The obtained data were analyzed for normality, and the distribution of the variables was tested by the Kolmogorov-Smirnov test. Paired t-test was used to evaluate the effectiveness of education programme and to compare the above-mentioned variables in each school separately before and after the lessons. The result of the paired t-test conducted separately for each school showed that on average after eight lessons, there was a 25-32% increase in nutritional knowledge of students regardless of the school they attend to and this rate was significant (P < 0.01). This shows that increase in nutritional awareness in these five schools having different socio-economic status was similar to each other. This study suggests that having children involved directly in lessons help to achieve nutritional awareness leading to healthy eating habits. It is concluded that nutritional awareness is a valuable tool to change eating habits. Study findings will provide information for developing nutrition education programmes for the healthy life and obesity prevention in children.

Keywords: children, nutritional awareness, obesity, socioeconomic status

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Authors: F. Bellali, M. Kharroubi, M. Loutfi, N.Bourhim

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In Morocco, fish processing industry is an important source income for a large amount of byproducts including skins, bones, heads, guts and scales. Those underutilized resources particularly scales contain a large amount of proteins and calcium. Scales from Sardina plichardus resulting from the transformation operation have the potential to be used as raw material for the collagen production. Taking into account this strong expectation of the regional fish industry, scales sardine upgrading is well justified. In addition, political and societal demands for sustainability and environment-friendly industrial production systems, coupled with the depletion of fish resources, drive this trend forward. Therefore, fish scale used as a potential source to isolate collagen has a wide large of applications in food, cosmetic and bio medical industry. The main aim of this study is to isolate and characterize the acid solubilize collagen from sardine fish scale, Sardina pilchardus. Experimental design methodology was adopted in collagen processing for extracting optimization. The first stage of this work is to investigate the optimization conditions of the sardine scale deproteinization on using response surface methodology (RSM). The second part focus on the demineralization with HCl solution or EDTA. Moreover, the last one is to establish the optimum condition for the isolation of collagen from fish scale by solvent extraction. The basic principle of RSM is to determinate model equations that describe interrelations between the independent variables and the dependent variables.

Keywords: Sardina pilchardus, scales, valorization, collagen extraction, response surface methodology

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Authors: Chen Zhang, Nan Chen

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High-dimensional process monitoring becomes increasingly important in many application domains, where usually the process distribution is unknown and much more complicated than the normal distribution, and the between-stream correlation can not be neglected. However, since the process dimension is generally much bigger than the reference sample size, most traditional nonparametric multivariate control charts fail in high-dimensional cases due to the curse of dimensionality. Furthermore, when the process goes out of control, the influenced variables are quite sparse compared with the whole dimension, which increases the detection difficulty. Targeting at these issues, this paper proposes a new nonparametric monitoring scheme for high-dimensional processes. This scheme first projects the high-dimensional process into several subprocesses using random projections for dimension reduction. Then, for every subprocess with the dimension much smaller than the reference sample size, a local nonparametric control chart is constructed based on the spatial rank test to detect changes in this subprocess. Finally, the results of all the local charts are fused together for decision. Furthermore, after an out-of-control (OC) alarm is triggered, a diagnostic framework is proposed. using the square-root LASSO. Numerical studies demonstrate that the chart has satisfactory detection power for sparse OC changes and robust performance for non-normally distributed data, The diagnostic framework is also effective to identify truly changed variables. Finally, a real-data example is presented to demonstrate the application of the proposed method.

Keywords: random projection, high-dimensional process control, spatial rank, sequential change detection

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Authors: Fang Yao, Minglei Chen

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City shrinkage is one of the thorny problems that many European cities have to face with nowadays. It is mainly expressed as the decrease of population in these cities. Eastern Germany is one of the pioneers of European shrinking cities with long shrinking history. Selecting one representative shrinking city Halle(Saale) in eastern Germany as research objective, collecting and investigating nearly 20 years (1993-2010) municipal data after the reunification of Germany. These data based on five dimensions, which are demographic, economic, social, spatial and environmental and total 16 eligible variables. Using Factor Analysis to dealing with these variables in order to assess the most important factors affecting shrinking Halle. The Factor Analysis shows that there are three main factors determine the shrinkage of Halle, namely demographical and economical factor, social stability factor, and city vitality factor. Three factors acts at different period of Halle’s shrinkage: from 1993 to 1997 the demographical and economical factor played an important role; from 1997 to 2004 the social stability is significant to city shrinkage; since 2005 city vitality factors determines the shrinkage of Halle. In recent years, the shrinkage in Halle mitigates that shows the sign of growing population. Thus the city Halle should focus on attaching more importance on the city vitality factor to prevent the city from shrinkage. Meanwhile, the city should possess a positive perspective that to shift the growth-oriented development to tap the potential of shrinking cities. This method is expected to apply to further research and other shrinking cities.

Keywords: demography, factor analysis, Halle, shrinking cities

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Authors: Seema Kaushik

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Skinfold measurements provide considerably meaningful and consistent information about subcutaneous fat and its distribution. Physical activities in the form of conditioning and/or training leads to various structural, functional and mechanical changes and numerous training programmes exist for the improvement of physical fitness, however, most of the studies are conducted on foreign soil with foreign population as sample, which may/may not be applicable to the Indian conditions. Moreover, there is not even a single training/ conditioning programme that caters to the need of male students of University of Delhi with regard to various skinfold thickness measurements. Hence, the present study aimed at studying the effect of progressive and constant load training on selected skinfold measurements of male students of University of Delhi in form of percentage change. The sample size for the study was 90 having three groups of male; 30 samples in each group (mean age = 20.04±0.49 years). The variables included triceps, sub-scapular, supra-iliac and calf skinfolds. The experimental design adopted for the study was multi-group repeated measure design. Three different groups were measured four times repeatedly at an interval of 6 weeks, on completion of each of the three meso-cycles. Standard landmarks and protocols were followed to measure the selected variables. Mean, standard deviation and percentage were computed to analyze the data statistically. The study concluded that both the progressive and constant load of physical training bring changes in the skinfold thickness measurements of male students of University of Delhi.

Keywords: constant load, progressive load, physical training, skinfold measurements

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Authors: Yoshinori Wakatake

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Many defects after the release of software packages are caused due to omissions of sufficient test items in test specifications. Poor test specifications are detected by manual review, which imposes a high human load. The prevention of omissions depends on the end-user awareness of test specification writers. If test specifications were written while envisioning the behavior of end-users, the number of omissions in test items would be greatly reduced. The paper pays attention to the point that writers who can achieve it differ from those who cannot in not only the description richness but also their gaze information. It proposes a method to estimate the degree of user-awareness of writers through the analysis of their gaze information when writing test specifications. We conduct an experiment to obtain the gaze information of a writer of the test specifications. Test specifications are automatically classified using gaze information. In this method, a Random Forest model is constructed for the classification. The classification is highly accurate. By looking at the explanatory variables which turn out to be important variables, we know behavioral features to distinguish test specifications of high quality from others. It is confirmed they are pupil diameter size and the number and the duration of blinks. The paper also investigates test specifications automatically classified with gaze information to discuss features in their writing ways in each quality level. The proposed method enables us to automatically classify test specifications. It also prevents test item omissions, because it reveals writing features that test specifications of high quality should satisfy.

Keywords: blink, eye tracking, gaze information, pupil diameter, quality improvement, specification document, user-awareness

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Authors: Rajesh Chakraborty, Dibyendu Das, Rabindra Nath Barman, Uttam Kumar Mandal

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In the present study, the objective is to find out the most effective zone causing soil erosion in the Gumati river basin located in the state of Tripura, a north eastern state of India using analytical hierarchy process (AHP) and multi-objective optimization on the basis of ratio analysis (MOORA).The watershed is segmented into 20 zones based on Area. The watershed is considered by pointing the maximum elevation from sea lever from Google earth. The soil erosion is determined using the universal soil loss equation. The different independent variables of soil loss equation bear different weightage for different soil zones. And therefore, to find the weightage factor for all the variables of soil loss equation like rainfall runoff erosivity index, soil erodibility factor etc, analytical hierarchy process (AHP) is used. And thereafter, multi-objective optimization on the basis of ratio analysis (MOORA) approach is used to select the most effective zone causing soil erosion. The MCDM technique concludes that the maximum soil erosion is occurring in the zone 14.

Keywords: soil erosion, analytic hierarchy process (AHP), multi criteria decision making (MCDM), universal soil loss equation (USLE), multi-objective optimization on the basis of ratio analysis (MOORA)

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Authors: Namik Kemal Sonmez, Sahriye Sonmez, Hasan Rasit Turkkan, Hatice Tuba Selcuk

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In this study, the spatial variation of plant and soil nutrition contents of tomato plants grown in greenhouses was investigated in Elmalı region of Antalya. For this purpose, total of 19 sampling points were determined. Coordinates of each sampling points were recorded by using a hand-held GPS device and were transferred to satellite data in GIS. Soil samples were collected from two different depths, 0-20 and 20-40 cm, and leaf were taken from different tomato greenhouses. The soil and plant samples were analyzed for N, P and K. Then, attribute tables were created with the analyses results by using GIS. Data were analyzed and semivariogram models and parameters (nugget, sill and range) of variables were determined by using GIS software. Kriged maps of variables were created by using nugget, sill and range values with geostatistical extension of ArcGIS software. Kriged maps of the N, P and K contents of plant and soil samples showed patchy or a relatively smooth distribution in the study areas. As a result, the N content of plants were sufficient approximately 66% portion of the tomato productions. It was determined that the P and K contents were sufficient of 70% and 80% portion of the areas, respectively. On the other hand, soil total K contents were generally adequate and available N and P contents were found to be highly good enough in two depths (0-20 and 20-40 cm) 90% portion of the areas.

Keywords: Elmali, nutrients, springs greenhouses, spatial variation, tomato

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Authors: Samuel Fekadu A., Esayas Alemayehu B., Bultum Oljira D., Seid Tiku D., Dessalegn Dadi D., Bart Van Der Bruggen A.

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The peroxi-photoelectrocoagulation process was evaluated for the removal of chemical oxygen demand (COD) and color from healthcare wastewater. A 2-level full factorial design with center points was created to investigate the effect of the process parameters, i.e., initial COD, H₂O₂, pH, reaction time and current density. Furthermore, the total energy consumption and average current efficiency in the system were evaluated. Predictive models for % COD, % color removal and energy consumption were obtained. The initial COD and pH were found to be the most significant variables in the reduction of COD and color in peroxi-photoelectrocoagulation process. Hydrogen peroxide only has a significant effect on the treated wastewater when combined with other input variables in the process like pH, reaction time and current density. In the peroxi-photoelectrocoagulation process, current density appears not as a single effect but rather as an interaction effect with H₂O₂ in reducing COD and color. Lower energy expenditure was observed at higher initial COD, shorter reaction time and lower current density. The average current efficiency was found as low as 13 % and as high as 777 %. Overall, the study showed that hybrid electrochemical oxidation can be applied effectively and efficiently for the removal of pollutants from healthcare wastewater.

Keywords: electrochemical oxidation, UV, healthcare pollutants removals, factorial design

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Authors: Nida B. Syed

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Following second wave of the current pandemic COVID-19, education transmission is occurring via both the modes of education, that is, online as well as offline in the college. The aim of the current study was, therefore, to bring forth the comparative analysis of both the modes of education and their impact on the levels of academic stress and states of the mental wellbeing of the students amidst the current pandemic. Measures of the constructs were obtained by the online Google forms, which consist of the Perceptions of Academic Stress Scale (PASS) by and Warwick-Edinburg Mental Well-being Scale, from a sample of 100 undergraduate students aged 19-25 years studying in different colleges of Bengaluru, India. Modes of education were treated as the predictor variables whilst academic stress, and mental wellbeing constituted the criterion variables. Two-way ANOVA was employed. Results show that the levels of academic stress are found to be a bit higher in students attending online classes as compared to those taking offline classes in college (MD = 1.10, df = 98, t = 0.590, p > 0.05), whereas mental wellbeing is found to be low in students attending offline classes in colleges than those taking online classes (MD = 5.180, df = 98, t =2.340, p > 0.05 level). The combined interactional effect of modes of education and academic stress on the states of the mental wellbeing of the students is found to be low (R2 = 0.053), whilst the combined impact of modes of education and mental wellbeing on the levels of academic stress was found to be quite low (R2 = 0.014). It was concluded that modes of education have an impact on levels of academic stress and states of the mental well-being of the students amidst the current pandemic, but it is low.

Keywords: modes of education, online learning, offline learning, pandemic

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Authors: Huijie Wang, Bin Zhang

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In China, the middle reaches of the Yangtze River are well-developed, boasting a wealth of different types of watershed landscape. In this regard, landscape character assessment (LCA) can serve as a basis for protection, management and planning of trans-regional watershed landscape types. For this study, we chose the middle reaches of the Yangtze River in Wuhan metropolitan area as our study site, wherein the water system consists of rich variety in landscape types. We analyzed trans-regional data to cluster and identify types of landscape characteristics at two levels. 55 basins were analyzed as variables with topography, land cover and river system features in order to identify the watershed landscape character types. For watershed landscape, drainage density and degree of curvature were specified as special variables to directly reflect the regional differences of river system features. Then, we used the principal component analysis (PCA) method and hierarchical clustering algorithm based on the geographic information system (GIS) and statistical products and services solution (SPSS) to obtain results for clusters of watershed landscape which were divided into 8 characteristic groups. These groups highlighted watershed landscape characteristics of different river systems as well as key landscape characteristics that can serve as a basis for targeted protection of watershed landscape characteristics, thus helping to rationally develop multi-value landscape resources and promote coordinated development of trans-regions.

Keywords: GIS, hierarchical clustering, landscape character, landscape typology, principal component analysis, watershed

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Authors: Enas El Sayed Abutaleb, Mohamed Taher Eldesoky, Shahenda Abd El Rasol

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Background: Muscle energy techniques (MET) have been widely used by manual therapists over the past years, but still limited research validated its use and there was limited evidence to substantiate the theories used to explain its effects. Objective: To investigate the effect of muscle energy technique (MET) on anterior pelvic tilt in patients with lumbar spondylosis. Design: Randomized controlled trial. Subjects: Thirty patients with anterior pelvic tilt from both sexes were involved, aged between 35 to 50 years old and they were divided into MET and control groups with 15 patients in each. Methods: All patients received 3 sessions/week for 4 weeks where the study group received MET, Ultrasound and Infrared, and the control group received U.S and I.R only. Pelvic angle was measured by palpation meter, pain severity by the visual analogue scale and functional disabilities by the Oswestry disability index. Results: Both groups showed significant improvement in all measured variables. The MET group was significantly better than the control group in pelvic angle, pain severity, and functional disability as p-value were (0.001, 0.0001, 0.0001) respectively. Conclusion and implication: The study group fulfilled greater improvement in all measured variables than the control group which implies that application of MET in combination with U.S and I.R were more effective in improving pelvic tilting angle, pain severity and functional disabilities than using electrotherapy only.

Keywords: anterior pelvic tilt, lumbar spondylosis, muscle energy technique exercise, pelvic tilting angle

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Authors: Wlodzimierz Ogryczak, Michal Przyluski, Tomasz Sliwinski

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In problems of portfolio selection, the reward-risk ratio criterion is optimized to search for a risky portfolio with the maximum increase of the mean return in proportion to the risk measure increase when compared to the risk-free investments. In the classical model, following Markowitz, the risk is measured by the variance thus representing the Sharpe ratio optimization and leading to the quadratic optimization problems. Several Linear Programming (LP) computable risk measures have been introduced and applied in portfolio optimization. In particular, the Mean Absolute Deviation (MAD) measure has been widely recognized. The reward-risk ratio optimization with the MAD measure can be transformed into the LP formulation with the number of constraints proportional to the number of scenarios and the number of variables proportional to the total of the number of scenarios and the number of instruments. This may lead to the LP models with huge number of variables and constraints in the case of real-life financial decisions based on several thousands scenarios, thus decreasing their computational efficiency and making them hardly solvable by general LP tools. We show that the computational efficiency can be then dramatically improved by an alternative model based on the inverse risk-reward ratio minimization and by taking advantages of the LP duality. In the introduced LP model the number of structural constraints is proportional to the number of instruments thus not affecting seriously the simplex method efficiency by the number of scenarios and therefore guaranteeing easy solvability. Moreover, we show that under natural restriction on the target value the MAD risk-reward ratio optimization is consistent with the second order stochastic dominance rules.

Keywords: portfolio optimization, reward-risk ratio, mean absolute deviation, linear programming

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Authors: Serena Salvi

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Ageistic stereotypes and practices have become a normal and therefore pervasive phenomenon in various aspects of everyday life. Over the past years, renewed awareness towards self-directed age stereotyping in older adults has given rise to a line of research focused on the potential role of attitudes towards ageing on seniors’ health and functioning. This set of studies has showed how a negative internalisation of ageistic stereotypes would discourage older adults in seeking medical advice, in addition to be associated to negative subjective health evaluation. An important dimension of mental health that is often affected in older adults is represented by sleep quality. Self-reported sleep quality among older adults has shown to be often unreliable when compared to their objective sleep measures. Investigations focused on self-reported sleep quality among older adults have suggested how this portion of the population would tend to accept disrupted sleep if believed to be up to standard for their age. On the other hand, unrealistic expectations, and dysfunctional beliefs towards sleep in ageing, might prompt older adults to report sleep disruption even in the absence of objective disrupted sleep. Objective of this study is to examine an association between personal attitudes towards ageing in adults aged 60+ and dysfunctional sleep related cognition. More in detail, this study aims to investigate a potential association between personal attitudes towards ageing, sleep locus of control and dysfunctional beliefs towards sleep among this portion of the population. Data in this study were statistically analysed in SPSS software. Participants were recruited through the online participants recruitment system Prolific. Inclusion of attention check questions throughout the questionnaire and consistency of responses were looked at. Prior to the commencement of this study, Ethical Approval was granted (ref. 39396). Descriptive statistics were used to determine the frequency, mean, and SDs of the variables. Pearson coefficient was used for interval variables, independent T-test for comparing means between two independent groups, analysis of variance (ANOVA) test for comparing the means in several independent groups, and hierarchical linear regression models for predicting criterion variables based on predictor variables. In this study self-perceptions of ageing were assessed using APQ-B’s subscales, while dysfunctional sleep related cognition was operationalised using the SLOC and the DBAS16 scales. Of the final subscales taken in consideration in the brief version of the APQ questionnaire, Emotional Representations (ER), Control Positive (PC) and Control and Consequences Negative (NC) have shown to be of particularly relevance for the remits of this study. Regression analysis show how an increase in the APQ-B subscale Emotional Representations (ER) predicts an increase in dysfunctional beliefs and attitudes towards sleep in this sample, after controlling for subjective sleep quality, level of depression and chronological age. A second regression analysis showed that APQ-B subscales Control Positive (PC) and Control and Consequences Negative (NC) were significant predictors in the change of variance of SLOC, after controlling for subjective sleep quality, level of depression and dysfunctional beliefs about sleep.

Keywords: sleep-related cognition, perceptions of aging, older adults, sleep quality

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Authors: Muhammad Imran, Iqra Basit, Mobushir Riaz Khan, Sajid Rasheed Ahmad

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The present study investigates the space-time impact of climate change on the rice crop calendar in tropical Gujranwala, Pakistan. The climate change impact was quantified through the climatic variables, whereas the existing calendar of the rice crop was compared with the phonological stages of the crop, depicted through the time series of the Normalized Difference Vegetation Index (NDVI) derived from Landsat data for the decade 2005-2015. Local maxima were applied on the time series of NDVI to compute the rice phonological stages. Panel models with fixed and cross-section fixed effects were used to establish the relation between the climatic parameters and the time-series of NDVI across villages and across rice growing periods. Results show that the climatic parameters have significant impact on the rice crop calendar. Moreover, the fixed effect model is a significant improvement over cross-sectional fixed effect models (R-squared equal to 0.673 vs. 0.0338). We conclude that high inter-annual variability of climatic variables cause high variability of NDVI, and thus, a shift in the rice crop calendar. Moreover, inter-annual (temporal) variability of the rice crop calendar is high compared to the inter-village (spatial) variability. We suggest the local rice farmers to adapt this change in the rice crop calendar.

Keywords: Landsat NDVI, panel models, temperature, rainfall

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Authors: Nnadi Ezekiel Oluwaseun Ejiofor

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The foundation of this study is the identification of risk variables and their implications on abandoned construction projects in Nigeria. The study's particular goals are to pinpoint the risk factors that lead to the abandonment of public building projects in Nigeria. This study used a hybrid research design that included case studies and descriptive survey research methods. Professionals who work directly in the built environment and are employed by Ministries and Departmental Agencies (MDAs), the public sector, or the private sector are the study's target demographic. This study used a descriptive survey and case study research design to gather data. Nigeria is experiencing a high rate of project abandonment due to housing deficit issues. Factors contributing to this include The study reveals factors contributing to public project abandonment in Abuja FCT include poor cashflow 4.96, inconsistent government policies 4.89, lack of accountability, high corruption, incompetent contractors, non-availability of building materials, lack of utilities, wrong materials, infrastructural facilities, poor planning, and undefined contracts. The study reveals that abandoned projects have a huge impact on the construction industry, such as wastage of resources with a mean value of 3.35, distrust of economic growth, 3.28, and so on. The study found a significant relationship between risk factors and public building construction in Abuja through a T-test value of 0.037, rejecting the null hypothesis and indicating a positive correlation.

Keywords: cost, tetfund, construction projects, public university

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Authors: Patrick Weber, Daniel Gredig

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Background and Purpose: Research has well documented the impact of discrimination and micro-aggressions on the wellbeing of gay men and, especially, adolescents. For the prevention of homophobic behavior against gay adolescents, however, the focus has to shift on those who discriminate: For the design and tailoring of prevention and intervention, it is important to understand the factors responsible for homophobic behavior such as, for example, verbal abuse. Against this background, the present study aimed to assess homophobic – in terms of verbally abusive – behavior against gay people among high school students. Furthermore, it aimed to establish the predictors of the reported behavior by testing an explanatory model. This model posits that homophobic behavior is determined by negative attitudes and knowledge. These variables are supposed to be predicted by the acceptance of traditional gender roles, religiosity, orientation toward social dominance, contact with gay men, and by the perceived expectations of parents, friends and teachers. These social-cognitive variables in turn are assumed to be determined by students’ gender, age, immigration background, formal school level, and the discussion of gay issues in class. Method: From August to October 2016, we visited 58 high school classes in 22 public schools in a county in Switzerland, and asked the 8th and 9th year students on three formal school levels to participate in survey about gender and gay issues. For data collection, we used an anonymous self-administered questionnaire filled in during class. Data were analyzed using descriptive statistics and structural equation modelling (Generalized Least Square Estimates method). The sample included 897 students, 334 in the 8th and 563 in the 9th year, aged 12–17, 51.2% being female, 48.8% male, 50.3% with immigration background. Results: A proportion of 85.4% participants reported having made homophobic statements in the 12 month before survey, 4.7% often and very often. Analysis showed that respondents’ homophobic behavior was predicted directly by negative attitudes (β=0.20), as well as by the acceptance of traditional gender roles (β=0.06), religiosity (β=–0.07), contact with gay people (β=0.10), expectations of parents (β=–0.14) and friends (β=–0.19), gender (β=–0.22) and having a South-East-European or Western- and Middle-Asian immigration background (β=0.09). These variables were predicted, in turn, by gender, age, immigration background, formal school level, and discussion of gay issues in class (GFI=0.995, AGFI=0.979, SRMR=0.0169, CMIN/df=1.199, p>0.213, adj. R2 =0.384). Conclusion: Findings evidence a high prevalence of homophobic behavior in the responding high school students. The tested explanatory model explained 38.4% of the assessed homophobic behavior. However, data did not found full support of the model. Knowledge did not turn out to be a predictor of behavior. Except for the perceived expectation of teachers and orientation toward social dominance, the social-cognitive variables were not fully mediated by attitudes. Equally, gender and immigration background predicted homophobic behavior directly. These findings demonstrate the importance of prevention and provide also leverage points for interventions against anti-gay bias in adolescents – also in social work settings as, for example, in school social work, open youth work or foster care.

Keywords: discrimination, high school students, gay men, predictors, Switzerland

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Authors: Golnush Masghati-Amoli, Paul Chin

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Over the past recent years, with the rapid increases in data availability and computing power, Machine Learning (ML) techniques have been called on in a range of different industries for their strong predictive capability. However, the use of Machine Learning in commercial banking has been limited due to a special challenge imposed by numerous regulations that require lenders to be able to explain their analytic models, not only to regulators but often to consumers. In other words, although Machine Leaning techniques enable better prediction with a higher level of accuracy, in comparison with other industries, they are adopted less frequently in commercial banking especially for scoring purposes. This is due to the fact that Machine Learning techniques are often considered as a black box and fail to provide information on why a certain risk score is given to a customer. In order to bridge this gap between the explain-ability and performance of Machine Learning techniques, a Hybrid Model is developed at Dun and Bradstreet that is focused on blending Machine Learning algorithms with traditional approaches such as scorecards. The Hybrid Model maximizes efficiency of traditional scorecards by merging its practical benefits, such as explain-ability and the ability to input domain knowledge, with the deep insights of Machine Learning techniques which can uncover patterns scorecard approaches cannot. First, through development of Machine Learning models, engineered features and latent variables and feature interactions that demonstrate high information value in the prediction of customer risk are identified. Then, these features are employed to introduce observed non-linear relationships between the explanatory and dependent variables into traditional scorecards. Moreover, instead of directly computing the Weight of Evidence (WoE) from good and bad data points, the Hybrid Model tries to match the score distribution generated by a Machine Learning algorithm, which ends up providing an estimate of the WoE for each bin. This capability helps to build powerful scorecards with sparse cases that cannot be achieved with traditional approaches. The proposed Hybrid Model is tested on different portfolios where a significant gap is observed between the performance of traditional scorecards and Machine Learning models. The result of analysis shows that Hybrid Model can improve the performance of traditional scorecards by introducing non-linear relationships between explanatory and target variables from Machine Learning models into traditional scorecards. Also, it is observed that in some scenarios the Hybrid Model can be almost as predictive as the Machine Learning techniques while being as transparent as traditional scorecards. Therefore, it is concluded that, with the use of Hybrid Model, Machine Learning algorithms can be used in the commercial banking industry without being concerned with difficulties in explaining the models for regulatory purposes.

Keywords: machine learning algorithms, scorecard, commercial banking, consumer risk, feature engineering

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