Search results for: sum conditional variance

Authors: Elihasridas, Rusmana Wijaya Setia Ninggrat

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This research aims to study the utilization of ammoniated corn waste complete ration for substitution basal ration of natural grass in Bali cattle. Four treatments (complete feed ration consisted of: R1=40% natural grass + 60% concentrate (control), R2= 50% natural grass+50% concentrate, R3=60% natural grass+40% concentrate and R4=40% ammoniated corn waste+60% concentrate) were employed in this experiment. This experiment was arranged in a latin square design. Observed variables included dry matter intake (DMI), average daily gain and feed conversion. Data were analyzed by using the Analysis of Variance following a 4 x 4 Latin Square Design. The DMI for R1was 7,15kg/day which was significantly (P < 0,05) higher than R2 (6,32 kg/day) and R3(6,07 kg/day), but was not significantly different (P < 0,05) from R4 (7,01 kg/day). Average daily gain for R1(0,75 kg/day) which was significantly (P < 0,05) higher than R2(0,66 kg/day) and R3 (0,61 kg/day),but was not significantly different (P > 0,05) from R4(0,74 kg/day). Feed conversion was not significantly affected (P > 0,05) by ration. It was concluded that ammoniated corn waste complete ration (40% ammoniated corn waste + 60% concentrate) could be utilized for substitution natural grass basal ration.

Keywords: ammoniated corn waste, bali cattle, complete feed, daily gain

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Authors: Zach Banzon, Marina Caculitan, Gianne Laisac, Stephanie Lopez, Marguerite Villegas

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The role of incidental positive emotions and gender on people’s trust decisions have been established by existing research. The aim of this experiment is to address the gap in the literature by examining whether these factors will have a similar effect on trust behavior even after the experience of betrayal. A total of 144 undergraduate students participated in a trust game involving the anonymous interaction of a participant and a transgressor. Of these participants, only 125 (63 males and 62 females) were included in the data analyses. A story was used to prime incidental positive emotions or emotions originally unrelated to the trustee. Recovered trust was measured by relating the proportion of the money passed before and after betrayal. Data was analyzed using two-way analysis of variance having two levels for gender (male, female) and two for priming (with, without), with trust propensity scores entered as a covariate. It was predicted that trust recovery will be more apparent in females than in males but the data obtained was not significantly different between the genders. Induced positive emotions, however, had a statistically significant effect on trust behavior even after betrayal. No significant interaction effect was found between induced positive emotion and gender. The experiment provides evidence that the manipulation of situational variables, to a certain extent, can facilitate the reparation of trust.

Keywords: gender effect, positive emotions, trust game, trust recovery

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Authors: Henok Metaferia Gebremariam

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Worldwide, considerable resources are spent implementing public health interventions that are interrupted soon after the initial funding ends. However, ambiguity remains as to how health programs can be effectively sustained over time because of the diversity of perspectives, definitions, study methods, outcomes measures and timeframes. From all the above-mentioned research challenges, standardized measures of sustainability should ultimately become a key research issue. To resolve this key challenge, the objective of the study was to adapt a tool for measuring the program’s capacity for sustainability and evaluating its reliability and validity. To adapt and validate the tool, a cross-sectional and cohort study design was conducted at 26 programs in Addis Ababa between September 2014 and May 2015. An adapted version of the tool after the pilot test was administered to 220 staff. The tool was analyzed for reliability and validity. Results show that a 40-item PSAT tool had been adapted into the Amharic version with good internal consistency (Cronbach’s alpha= 0.80), test-retest reliability(r=0.916) and construct validity. Factor analysis resulted in 7 components explaining 56.67 % of the variance. In conclusion, it was found that the Amharic version of PAST was a reliable and valid tool for measuring the program’s capacity for sustainability.

Keywords: program sustainability, public health interventions, reliability, validity

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Authors: Mehdi Basirat, Mohammad Rouhani, Shahla Borzouei, Majid Zarangi, Asma Abolghasemi, Mohammad Fazel Soltani, Mohammad Gorji, Mohammad Amin Samih

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The common pistachio psylla, Agonoscena pistaciae Burckhardt and Lauterer (Hemiptera: Aphalaridae), as one of the most detrimental pests in all pistachio producing regions, causes great economic damages to pistachio trees. Nowadays, various pesticides are used to control the common pistachio psylla and robust pesticide exposure has occurred in orchards. In this study, field experiments were conducted during 2018–2021 to assess the effects of sulfur on A. pistaciae. This study compared sulfur with asafoetida extract and pesticide (acetamiprid) on A. pistaciae based on complete randomized blocks with three replications. The analysis results of variance showed that the effect of treatments on egg (F2,24 = 17.61, P = 0.00) and nymphs (F2,24 = 18.29, P = 0.00) had a significant difference at a 1% level. The results demonstrated that sulfur had the highest measure of control on eggs and nymphs significantly compared to the plant extract and pesticide (negative control). These results provide support to the potential use of sulfur as an alternative pest management tool against A. pistaciae. The results clearly indicated that sulfur could control the common pistachio psylla population for six weeks at least.

Keywords: Agonoscena pistaciae, pesticide exposure, pistachio, sulfur

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Authors: F. Marchini, A. Caputo, J. Balonan, F. Fedele, A. Napoli, V. Langher

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Aim: The present study aims to explore the specific role of defense mechanisms in persons with type 2 diabetes mellitus in treatment adherence. Materials and methods: A correlational study design was employed. Thirty-two persons with type 2 diabetes mellitus were enrolled and assessed with Defense Mechanism Inventory, Beck Depression Inventory-II, Toronto Alexithymia Scale and Self-Care Inventory-Revised. Bivariate correlation and two-step regression analyses were performed. Results: Treatment adherence negatively correlates with hetero-directed hostility (r= -.537; p < .01), whereas it is positively associated with principalization (r= .407; p < .05). These two defense mechanisms overall explain an incremental variance of 26.9% in treatment adherence (ΔF=4.189, df1=2, df2 =21, p < .05), over and above the control variables for depression and alexithymia. However, only higher hetero-directed hostility is found to be a solid predictor of a decreased treatment adherence (β=-.497, p < .05). Conclusions: Despite providing preliminary results, this pilot study highlights the original contribution of defense mechanisms in adherence to type 2 diabetes regimens. Specifically, hetero-directed hostility may relate to an unconscious process, according to which disease-related painful feelings are displaced onto care relationships with negative impacts on adherence.

Keywords: alexithymia, defense mechanisms, treatment adherence, type 2 diabetes mellitus

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Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

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In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

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Authors: Farzad Khajavi

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Studies about the interaction between active pharmaceutical ingredients (API) and excipients are so important in the pre-formulation stage of development of all dosage forms. Analytical techniques such as differential scanning calorimetry (DSC), Thermal gravimetry (TG), and Furrier transform infrared spectroscopy (FTIR) are commonly used tools for investigating regarding compatibility and incompatibility of APIs with excipients. Sometimes the interpretation of data obtained from these techniques is difficult because of severe overlapping of API spectrum with excipients in their mixtures. Principal component analysis (PCA) as a powerful factor analytical method is used in these situations to resolve data matrices acquired from these analytical techniques. Binary mixtures of API and interested excipients are considered and produced. Peaks of FTIR, DSC, or TG of pure API and excipient and their mixtures at different mole ratios will construct the rows of the data matrix. By applying PCA on the data matrix, the number of principal components (PCs) is determined so that it contains the total variance of the data matrix. By plotting PCs or factors obtained from the score of the matrix in two-dimensional spaces if the pure API and its mixture with the excipient at the high amount of API and the 1:1mixture form a separate cluster and the other cluster comprise of the pure excipient and its blend with the API at the high amount of excipient. This confirms the existence of compatibility between API and the interested excipient. Otherwise, the incompatibility will overcome a mixture of API and excipient.

Keywords: API, compatibility, DSC, TG, interactions

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Authors: Gamze Karanfil Celep, Kevser Dincer

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The effects of polymer concentration and electrospinning process parameters on the average diameters of electrospun polyacrylonitrile (PAN) nanofibers were experimentally investigated. Besides, mechanical and thermal properties of PAN nanofibers were examined by tensile test and thermogravimetric analysis (TGA), respectively. For this purpose, the polymer concentration, solution feed rate, supply voltage and tip-to-collector distance were determined as the control factors. To succeed these aims, Taguchi’s L16 orthogonal design (4 parameters, 4 level) was employed for the experimental design. Optimal electrospinning conditions were defined using the signal-to-noise (S/N) ratio that was calculated from diameters of the electrospun PAN nanofibers according to "the-smaller-the-better" approachment. In addition, analysis of variance (ANOVA) was evaluated to conclude the statistical significance of the process parameters. The smallest diameter of PAN nanofibers was observed. According to the S/N ratio response results, the most effective parameter on finding out of nanofiber diameter was determined. Finally, the Taguchi design of experiments method has been found to be an effective method to statistically optimize the critical electrospinning parameters used in nanofiber production. After determining the optimum process parameters of nanofiber production, electrical conductivity and fuel cell performance of electrospun PAN nanofibers on the carbon papers will be evaluated.

Keywords: nanofiber, electrospinning, polyacrylonitrile, Taguchi method

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Authors: Nursuhaili Najwa Masrol, Nur Hafizah Mohammed, Nur Nadhirah Rusyda Rosnan, Vijaya Subramaniam, Sim Choon Cheak

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Replanting in oil palm cultivation is vital to enable the introduction of planting materials and provides an opportunity to improve the road, drainage, terrace design, and planting density. Oil palm replanting is fundamentally necessary every 25 years. The adoption of the digital replanting blueprint is imperative as it can assist the Malaysia Oil Palm industry in addressing challenges such as labour shortages and limited expertise related to replanting tasks. Effective replanting planning should commence at least 6 months prior to the actual replanting process. Therefore, this study will help to plan and design the replanting blueprint with high-precision translation on the ground. With the advancement of geospatial technology, it is now feasible to engage in thoroughly researched planning, which can help maximize the potential yield. A blueprint designed before replanting is to enhance management’s ability to optimize the planting program, address manpower issues, or even increase productivity. In terrace planting blueprints, geographic tools have been utilized to design the roads, drainages, terraces, and planting points based on the ARM standards. These designs are mapped with location information and undergo statistical analysis. The geospatial approach is essential in precision agriculture and ensuring an accurate translation of design to the ground by implementing high-accuracy technologies. In this study, geospatial and remote sensing technologies played a vital role. LiDAR data was employed to determine the Digital Elevation Model (DEM), enabling the precise selection of terraces, while ortho imagery was used for validation purposes. Throughout the designing process, Geographical Information System (GIS) tools were extensively utilized. To assess the design’s reliability on the ground compared with the current conventional method, high-precision GPS instruments like EOS Arrow Gold and HIPER VR GNSS were used, with both offering accuracy levels between 0.3 cm and 0.5cm. Nearest Distance Analysis was generated to compare the design with actual planting on the ground. The analysis revealed that it could not be applied to the roads due to discrepancies between actual roads and the blueprint design, which resulted in minimal variance. In contrast, the terraces closely adhered to the GPS markings, with the most variance distance being less than 0.5 meters compared to actual terraces constructed. Considering the required slope degrees for terrace planting, which must be greater than 6 degrees, the study found that approximately 65% of the terracing was constructed at a 12-degree slope, while over 50% of the terracing was constructed at slopes exceeding the minimum degrees. Utilizing blueprint replanting promising strategies for optimizing land utilization in agriculture. This approach harnesses technology and meticulous planning to yield advantages, including increased efficiency, enhanced sustainability, and cost reduction. From this study, practical implementation of this technique can lead to tangible and significant improvements in agricultural sectors. In boosting further efficiencies, future initiatives will require more sophisticated techniques and the incorporation of precision GPS devices for upcoming blueprint replanting projects besides strategic progression aims to guarantee the precision of both blueprint design stages and its subsequent implementation on the field. Looking ahead, automating digital blueprints are necessary to reduce time, workforce, and costs in commercial production.

Keywords: replanting, geospatial, precision agriculture, blueprint

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Authors: Keven A. Prusak, William F. Christensen, Zack Beddoes

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Background: For more than a decade, the Sport Motivation Scale (SMS) has been used to measure contextual motivation across a variety of sporting and physical education (PE) settings but not without criticism as to its tenability. Consequently, a new version of the sport motivation scale (SMS-II) was created to address certain weakness of the original SMS. Purpose: The purpose of this study is to assess the suitability of the SMS-II in the secondary PE setting. Methods: Three hundred and twenty (204 females, and 116 males; grades 7-9) completed the 18-item, six-subscale SMS-II at the end of a required PE class. Factor means, standard deviations, and correlations were calculated and further examined via confirmatory factor analysis (CFA). Model parameters were estimated maximum likelihood function. Results: Results indicate that participants held generally positive perceptions toward PE as a context (more so for males than females). Reliability analysis yielded adequate alphas (rα = 0.71 to 0.87, Mα = 0.78) with the exception of the AM subscale (αAM = .64). Correlation analysis indicated some support for the SIMPLEX pattern, but distal ends of the motivation continuum displayed no relationship. CFA yielded robust fit indices to the proposed structure of the SMS-II for PE. A small but significant variance across genders was noted and discussed. Conclusions: In all, the SMS-II suitably accesses PE context-specific motivational indices within Jr. High PE.

Keywords: motivation, self-determination theory, physical education, confirmatory factor analysis

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Authors: Abdulaziz Almustafa

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Considering the critical role permanence has on predictions related to the contextual interference effect on laboratory and field research, this study sought to determine whether the paradigm of the effect depends on the complexity of the skill during the acquisition and transfer phases. The purpose of the present study was to investigate the effects of contextual interference CI by extending previous laboratory and field research with adult athletes through the acquisition and transfer phases. Male (n=60) athletes age 18-22 years-old, were chosen randomly from Eastern Province Clubs. They were assigned to complete blocked, random, or serial practices. Analysis of variance with repeated measures MANOVA indicated that, the results did not support the notion of CI. There were no significant differences in acquisition phase between blocked, serial and random practice groups. During the transfer phase, there were no major differences between the practice groups. Apparently, due to the task complexity, participants were probably confused and not able to use the advantages of contextual interference. This is another contradictory result to contextual interference effects in acquisition and transfer phases in sport settings. One major factor that can influence the effect of contextual interference is task characteristics as the nature of level of difficulty in sport-related skill.

Keywords: contextual interference, acquisition, transfer, task difficulty

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Authors: Ruangdech Sirikit

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The purposes of this study were analyzed differential item functioning and differential test functioning of SWUSAT aptitude test classification by sex variable. The data used in this research is the secondary data from Srinakharinwirot University Scholastic Aptitude Test 2011 (SWUSAT 2011) SWUSAT test consists of four subjects. There are verbal ability test, number ability test, reasoning ability test and spatial ability test. The data analysis was carried out in 2 steps. The first step was analyzing descriptive statistics. In the second step were analyzed differential item functioning (DIF) and differential test functioning (DTF) by using the DIFAS program. The research results were as follows: The results of data analysis for all 10 tests in year 2011. Sex was the characteristic that found DIF all 10 tests. The percentage of item number that found DIF was between 10% - 46.67%. There are 4 tests that most of items favors female group. There are 3 tests that most of items favors male group and there are 3 tests that the number of items favors female group equal favors male group. For Differential test functioning (DTF), there are 8 tests that have small DIF effect variance.

Keywords: differential item functioning, differential test functioning, SWUSAT, aptitude test

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Authors: Malarvizhi Selvaraj, Paul Fergus, Andy Shaw

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Uterine contractions produced during labour have the potential to damage the foetus by diminishing the maternal blood flow to the placenta. In order to observe this phenomenon labour and delivery are routinely monitored using cardiotocography monitors. An obstetrician usually makes the diagnosis of foetus hypoxia by interpreting cardiotocography recordings. However, cardiotocography capture and interpretation is time-consuming and subjective, often lead to misclassification that causes damage to the foetus and unnecessary caesarean section. Both of these have a high impact on the foetus and the cost to the national healthcare services. Automatic detection of foetal heart rate may be an objective solution to help to reduce unnecessary medical interventions, as reported in several studies. This paper aim is to provide a system for better identification and interpretation of abnormalities of the fetal heart rate using RStudio. An open dataset of 552 Intrapartum recordings has been filtered with 0.034 Hz filters in an attempt to remove noise while keeping as much of the discriminative data as possible. Features were chosen following an extensive literature review, which concluded with FIGO features such as acceleration, deceleration, mean, variance and standard derivation. The five features were extracted from 552 recordings. Using these features, recordings will be classified either normal or abnormal. If the recording is abnormal, it has got more chances of hypoxia.

Keywords: cardiotocography, foetus, intrapartum, hypoxia

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Authors: Nithipattara Balsiri

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The purposes of this research was to develop instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge of undergraduate students. The sample consisted of 307 undergraduate students. Critical thinking and cognitive skills test were employed for data collection. Second-order confirmatory factor analysis, t-test, and one-way analysis of variance were employed for data analysis using SPSS and LISREL programs. The major research results were as follows; 1) the instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge should be consists of 6 sequential steps, namely (1) the setting research problem (2) the setting research hypothesis (3) the data collection (4) the data analysis (5) the research result conclusion (6) the application for problem solving, and 2) after the treatment undergraduate students possessed a higher scores in critical thinking and cognitive skills than before treatment at the 0.05 level of significance.

Keywords: critical thinking, cognitive skills, culture and local wisdom knowledge

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Authors: Ishapathik Das

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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.

Keywords: model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs

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Authors: Mojtaba Esmaeilzad Limoudehi, Ebrahim Amiri

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Water scarcity is now one of the leading challenges for human societies. In this regard, recognizing the relationship between soil, water, plant growth, and plant response to stress is very significant. In this paper, considering the importance of drought stress and the role of choosing suitable cultivars in resistance against drought, a split-plot experiment using early, intermediate, and late-maturing cultivars was carried out in Katul filed, Golestan province during two cultivation years of 2015 and 2016. The main factor was irrigation intervals at four levels, including 7 days, 14 days, 21 days, and 28 days. The subfactor was the subplot of six maize cultivars (two early maturing cultivars, two medium maturing cultivars, and two late-maturing cultivars). The results of variance analysis have revealed that irrigation interval and cultivars treatment have significant effects on the number of grain in each corn, number of rows in each corn, number of grain per row, the weight of 1000 grains, grain yield, and biomass yield. Although, the interaction of these two factors on the mentioned attributes was meaningful. The best grain yield was achieved at 7 days irrigation interval and late maturing maize cultivars treatment, which was equal to 12301 kg/ha.

Keywords: corn, growth period, optimization, stress

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Authors: Amir Wahid, Fazal Hadi, Amin Ullah Jan

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Tomato and Cauliflower seedlings were grown in-vitro under salt concentrations (0, 2, 4, 8, and 10 dSm-1) with objectives to investigate; (1) The effect of salinity on seedling growth and free proline production, (2) the correlation between seedling growth and proline contents, (3) comparative salt tolerance of both species. Different concentrations of salt showed considerable effect on percent (%) germination of seeds, length and biomass of shoot and root and also showed effect on percent water content of both plants seedlings. Germination rate in cauliflower was two times higher than tomato even at highest salt concentration (10 dSm-1). Seedling growth of both species was less effected at low salt concentrations (2 and 4 dSm-1) but at high concentrations (6 and 8 dSm-1) the seedling growth of both species was significantly decreased. Particularly the tomato root was highly significantly reduced. The proline level linearly increased in both species with increasing salt concentrations up-to 4 dSm-1 and then declined. The cauliflower showed higher free proline level than tomato under all salt treatments. Overall, the cauliflower seedlings showed better growth response along with higher proline contents on comparison with tomato seedlings.

Keywords: NaCl (Sodium Chloride), EC (Electrical Conductivity), MS (Murashig and Skoog), ANOVA (Analysis of Variance), LSD (Least Significant Differences)

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Authors: Sadık Ata, Kevser Dincer

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In this study, performance of proton exchange membrane (PEM) fuel cell was experimentally investigated and modelled with Rule-Based Mamdani-Type Fuzzy (RBMTF) modelling technique. Coating on the anode side of the PEM fuel cell was accomplished with the spin method by using Yttria-stabilized zirconia (YSZ). Input parameters voltage density (V/cm2), and current density (A/cm2), temperature (°C), time (s); output parameter power density (W/cm2) were described by RBMTF if-then rules. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. The comparison between experimental data and RBMTF is done by using statistical methods like absolute fraction of variance (R2). The actual values and RBMTF results indicated that RBMTF can be successfully used for the analysis of performance of PEM fuel cell.

Keywords: proton exchange membrane (PEM), fuel cell, rule-based Mamdani-type fuzzy (RMBTF) modeling, yttria-stabilized zirconia (YSZ)

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

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Authors: Mohd Radzi Hilmi, Mohd Zulfaezal Che Azemin, Khairidzan Mohd Kamal, Azrin Esmady Ariffin, Mohd Izzuddin Mohd Tamrin, Norfazrina Abdul Gaffur, Tengku Mohd Tengku Sembok

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Purpose: The purpose of this study is to predict optical quality changes after pterygium surgery using tissue redness grading. Methods: Sixty-eight primary pterygium participants were selected from patients who visited an ophthalmology clinic. We developed a semi-automated computer program to measure the pterygium fibrovascular redness from digital pterygium images. The outcome of this software is a continuous scale grading of 1 (minimum redness) to 3 (maximum redness). The region of interest (ROI) was selected manually using the software. Reliability was determined by repeat grading of all 68 images and its association with contrast sensitivity function (CSF) and visual acuity (VA) was examined. Results: The mean and standard deviation of redness of the pterygium fibrovascular images was 1.88 ± 0.55. Intra- and inter-grader reliability estimates were high with intraclass correlation ranging from 0.97 to 0.98. The new grading was positively associated with CSF (p<0.01) and VA (p<0.01). The redness grading was able to predict 25% and 23% of the variance in the CSF and the VA respectively. Conclusions: The new grading of pterygium fibrovascular redness can be reliably measured from digital images and show a good correlation with CSF and VA. The redness grading can be used in addition to the existing pterygium grading.

Keywords: contrast sensitivity, pterygium, redness, visual acuity

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Authors: Abdulrazaq O. Raji, Abba Mohammed, Ibrahim D. Mohammed

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This study was conducted to investigate foetal loss among slaughtered livestock species at the Maiduguri abattoir from 2009 to 2013. Record of animals slaughtered monthly and fetuses recovered were collected from the management of the Maiduguri abattoir. Data was subjected to Analysis of Variance using the General Linear Model of SPSS 13.0 with Season, Species and their interaction as fixed factors. Average yearly slaughter at the Maiduguri abattoir was 63,225 animals with cattle, camel, goat and sheep accounting for 19737, 7374, 19281 and 17540 of the total. The corresponding number of those pregnant were 3117, 839, 2281 and 2432 out of a total of 8522 animals. Thus, cattle, camel, goat and sheep accounted for 30.87, 11.53, 30.16 and 27.44%, respectively of the animals slaughtered at the Abattoir and 35.96, 9.68, 26.31 and 28.05% of the foetal loss. The effect of season and species on foetal loss was significant (P < 0.05). The number of pregnant animals slaughtered and foetal loss were higher during wet than dry season. Similarly, foetal loss at the abattoir was higher in the month of May in respect of camel, goat and sheep, and August for cattle. Camel was the least slaughtered animal and had the least number of pregnant females. Foetal loss (%) was higher (P < 0.05) for cattle compared to other species. The interaction showed that camel was the least slaughtered species in both seasons and cattle in the wet season had the highest foetal loss.

Keywords: abattoir, foetal loss, season, species

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Authors: Nahid Ehsani, Amir Hossein Rezvanfar

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The main objective of this study is to investigate psychological and socio-cultural factors effective on the tendency of the villagers to use e-banking services. The current paper is an applied study considering its objectives. The main data gathering tool in the current study is a made questionnaire which is designed and executed based on the conceptual background of the subject matter and the objectives and hypotheses of the study. The statistical population of this study includes all the customers of rural branches of Agricultural Bank in Ilam Province (N=82885). Among these 120 participants were chosen through sample size determination formula and they were studied using stratified random sampling method. In the analytical statistics level the results obtained from calculating Spearman’s Correlative Coefficient showed that socio-cultural and psychological factors had a significant impact of the extent of the tendency of the villagers to use e-banking services of the Agricultural Bank at the 99% level. Furthermore, stepwise multiple regression analysis showed that both sets of psychological factors as well as socio-economic factors were able to explain 50 percent of the variance of the independent variable; namely the tendency of villagers to use e-banking services.

Keywords: e-banking, agricultural bank, tendency, socio-economic factors, psychological factors

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Authors: Giorgia Zotti

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This research comprehensively investigates the multifaceted interplay determining school performance, individual backgrounds, and regional disparities within the landscape of Italian secondary education. Leveraging data gleaned from the INVALSI 2021-2022 database, the analysis meticulously scrutinizes two fundamental distributions of educational achievements: the standardized Invalsi test scores and official grades in Italian and Mathematics, focusing specifically on final-year secondary school students in Italy. Applying a comprehensive methodology, the study initially employs Data Envelopment Analysis (DEA) to assess school performances. This methodology involves constructing a production function encompassing inputs (hours spent at school) and outputs (Invalsi scores in Italian and Mathematics, along with official grades in Italian and Math). The DEA approach is applied in both of its versions: traditional and conditional. The latter incorporates environmental variables such as school type, size, demographics, technological resources, and socio-economic indicators. Additionally, the analysis delves into regional disparities by leveraging the Theil Index, providing insights into disparities within and between regions. Moreover, in the frame of the inequality of opportunity theory, the study quantifies the inequality of opportunity in students' educational achievements. The methodology applied is the Parametric Approach in the ex-ante version, considering diverse circumstances like parental education and occupation, gender, school region, birthplace, and language spoken at home. Consequently, a Shapley decomposition is applied to understand how much each circumstance affects the outcomes. The outcomes of this comprehensive investigation unveil pivotal determinants of school performance, notably highlighting the influence of school type (Liceo) and socioeconomic status. The research unveils regional disparities, elucidating instances where specific schools outperform others in official grades compared to Invalsi scores, shedding light on the intricate nature of regional educational inequalities. Furthermore, it emphasizes a heightened inequality of opportunity within the distribution of Invalsi test scores in contrast to official grades, underscoring pronounced disparities at the student level. This analysis provides insights for policymakers, educators, and stakeholders, fostering a nuanced understanding of the complexities within Italian secondary education.

Keywords: inequality, education, efficiency, DEA approach

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Authors: Maryam Khazaee-Pool, Tahereh Pashaei, Koen Ponnet

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Background: The global prevalence and morbidity of Coronavirus disease 2019 (COVID-19) are high. Preventive behaviors are proven to reduce the damage caused by the disease. There is a paucity of information on determinants of preventive behaviors in response to COVID-19 in Mazandaran province, north of Iran. So, we aimed to evaluate the protection motivation theory (PMT) in promoting preventive behaviors of COVID-19 in Mazandaran province. Materials and Methods: In this descriptive cross-sectional study, 1220 individuals participated. They were selected via social networks using convenience sampling in 2020. Data were collected online using a demographic questionnaire and a valid and reliable scale based on PMT. Data analysis was done using the Pearson correlation coefficient and linear regression in SPSS V24. Result: The mean age of the participants was 39.34±8.74 years. The regression model showed perceived threat (ß =0.033, P =0.007), perceived costs (ß=0.039, P=0.045), perceived self-efficacy (ß =0.116, P>0.001), and perceived fear (ß=0.131, P>0.001) as the significant predictors of COVID-19 preventive behaviors. This model accounted for 78% of the variance in these behaviors. Conclusion: According to constructs of the PMT associated with protection against COVID-19, educational programs and health promotion based on the theory and benefiting from social networks could be helpful in increasing the motivation of people towards protective behaviors against COVID-19.

Keywords: questionnaire development, validation, intention, prevention, covid-19

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Authors: Mehmet Bekmezci, Ismail Celik, Ismail Sahin, Ahmet Kiray, A. Oguz Akturk

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In this research, students’ scientific attitude, computer anxiety, educational use of the Internet, academic achievement, and problematic use of the Internet are analyzed based on different variables (gender, parents’ educational level and daily access to the Internet). The research group involves 361 students from two middle schools which are located in the center of Konya. The “general survey method” is adopted in the research. In accordance with the purpose of the study, percentage, mean, standard deviation, independent samples t--‐test, ANOVA (variance) are employed in the study. A total of four scales are implemented. These four scales include a total of 13 sub-dimensions. The scores from these scales and their subscales are studied in terms of various variables. In the research, students’ scientific attitude, computer anxiety, educational use of the Internet, the problematic Internet use and academic achievement (gender, parent educational level, and daily access to the Internet) are investigated based on various variables and some significant relations are found.

Keywords: scientific attitude, educational use of the internet, computer anxiety, problematic use of the internet, academic achievement

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Authors: Shourav Ahmed, M. Gulam Kibria, Kais Zaman

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Control charts graphically verify variation in quality parameters. Attribute type control charts deal with quality parameters that can only hold two states, e.g., good or bad, yes or no, etc. At present, p-control chart is most commonly used to deal with attribute type data. In construction of p-control chart using binomial distribution, the value of proportion non-conforming must be known or estimated from limited sample information. As the probability distribution of fraction non-conforming (p) is considered in hyperbinomial distribution unlike a constant value in case of binomial distribution, it reduces the risk of false detection. In this study, a statistical control chart is proposed based on hyperbinomial distribution when prior estimate of proportion non-conforming is unavailable and is estimated from limited sample information. We developed the control limits of the proposed modified p-chart using the mean and variance of hyperbinomial distribution. The proposed modified p-chart can also utilize additional sample information when they are available. The study also validates the use of modified p-chart by comparing with the result obtained using cumulative distribution function of hyperbinomial distribution. The study clearly indicates that the use of hyperbinomial distribution in construction of p-control chart yields much accurate estimate of quality parameters than using binomial distribution.

Keywords: binomial distribution, control charts, cumulative distribution function, hyper binomial distribution

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Authors: Takele Nemomsa, Girma Mamo, Tesfaye Balemi

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Climate change refers to a change in the state of the climate that can be identified (e.g. using statistical tests) by changes in the mean and/or variance of its properties and that persists for an extended period, typically decades or longer. In Ethiopia; Maize production in relation to climate change at regional and sub- regional scales have not been studied in detail. Thus, this study was aimed to analyse the impact of climate change on maize yield in Ambo Districts, Central Ethiopia. To this effect, weather data, soil data and maize experimental data for Arganne hybrid were used. APSIM software was used to investigate the response of maize (Zea mays) yield to different agronomic management practices using current and future (2020s–2080s) climate data. The climate change projections data which were downscaled using SDSM were used as input of climate data for the impact analysis. Compared to agronomic practices the impact of climate change on Arganne in Central Ethiopia is minute. However, within 2020s-2080s in Ambo area; the yield of Arganne hybrid is projected to reduce by 1.06% to 2.02%, and in 2050s it is projected to reduce by 1.56 While in 2080s; it is projected to increase by 1.03% to 2.07%. Thus, to adapt to the changing climate; farmers should consider increasing plant density and fertilizer rate per hectare.

Keywords: APSIM, downscaling, response, SDSM

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Authors: Mitra Mesgar

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Online learning environment is becoming more popular among learners because of their multiple information representations. Despite the growing importance of online reading strategies among adult learners, little attention has been carried out to postgraduate EFL learners. This study is quantitative research designed and aimed to investigate metacognitive reading strategies employed by Iranian postgraduate learners to read online academic texts. This study is conducted by over 50 Iranian postgraduate students studying in different Malaysian universities. This study used two different survey questionnaires, namely, 1) background questionnaire and 2) OSORS questionnaire. The collected data were analyzed using SPSS. The findings of the study emphasized metacognitive reading strategies used by different aged adult learners. The results of the survey questionnaires revealed that adult learners use global reading strategies as well as problem-solving strategies and support reading strategies. Also, through one-way analysis of variance toward age factor revealed that it has no meaningful changes on metacognitive reading strategy usage. This means that metacognitive reading strategies used by adult learners are independent of age variable. Drawing from findings, adult learners have learning goals, and since they have more exposure to online academic texts, they are able to use different metacognitive online reading strategies that affect their understanding of academic texts.

Keywords: online reading strategies, metacognitive strategies, online learning, independent students, locus of control

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Authors: Gautier Viaud, Paul-Henry Cournède

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Plant growth models have been used extensively for the prediction of the phenotypic performance of plants. However, they remain most often calibrated for a given genotype and therefore do not take into account genotype by environment interactions. One way of achieving such an objective is to consider Bayesian hierarchical models. Three levels can be identified in such models: The first level describes how a given growth model describes the phenotype of the plant as a function of individual parameters, the second level describes how these individual parameters are distributed within a plant population, the third level corresponds to the attribution of priors on population parameters. Thanks to the Bayesian framework, choosing appropriate priors for the population parameters permits to derive analytical expressions for the full conditional distributions of these population parameters. As plant growth models are of a nonlinear nature, individual parameters cannot be sampled explicitly, and a Metropolis step must be performed. This allows for the use of a hybrid Gibbs--Metropolis sampler. A generic approach was devised for the implementation of both general state space models and estimation algorithms within a programming platform. It was designed using the Julia language, which combines an elegant syntax, metaprogramming capabilities and exhibits high efficiency. Results were obtained for Arabidopsis thaliana on both simulated and real data. An organ-scale Greenlab model for the latter is thus presented, where the surface areas of each individual leaf can be simulated. It is assumed that the error made on the measurement of leaf areas is proportional to the leaf area itself; multiplicative normal noises for the observations are therefore used. Real data were obtained via image analysis of zenithal images of Arabidopsis thaliana over a period of 21 days using a two-step segmentation and tracking algorithm which notably takes advantage of the Arabidopsis thaliana phyllotaxy. Since the model formulation is rather flexible, there is no need that the data for a single individual be available at all times, nor that the times at which data is available be the same for all the different individuals. This allows to discard data from image analysis when it is not considered reliable enough, thereby providing low-biased data in large quantity for leaf areas. The proposed model precisely reproduces the dynamics of Arabidopsis thaliana’s growth while accounting for the variability between genotypes. In addition to the estimation of the population parameters, the level of variability is an interesting indicator of the genotypic stability of model parameters. A promising perspective is to test whether some of the latter should be considered as fixed effects.

Keywords: bayesian, genotypic differentiation, hierarchical models, plant growth models

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Authors: Nam-Seok Joo, Da-Eun Jung, Beom-Hee Choi

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Background and Objectives: Recently, the triglyceride/high-density lipoprotine cholesterol (TG/HDL) ratio and pericardial adipose tissue (PAT) has gained attention as an indicator related to metabolic syndrome (MS). To date, there has been no research on the relationship between TG/HDL and PAT, we aimed to investigate the association between the TG/HDL and PAT. Methods: In this cross-sectional study, we investigated 627 patients who underwent coronary multidetector computed tomography and metabolic parameters. We divided subjects into two groups according to the cut-off PAT volume associated with MS, which is 142.2 cm³, and we compared metabolic parameters between those groups. We divided the TG/HDL ratio into tertiles according to Log(TG/HDL) and compared PAT-related parameters by analysis of variance. Finally, we applied logistic regression analysis to obtain the odds ratio of high PAT (PAT volume≥142.2 cm³) in each tertile, and we performed receiver operating characteristic (ROC) analysis to get the cut-off of TG/HDL ratio according to high PAT. Results: The mean TG/ HDL ratio of the high PAT volume group was 3.6, and TG/ HDL ratio had a strong positive correlation with various metabolic parameters. In addition, in the Log (TG/HDL) tertile groups, the higher tertile had more metabolic derangements, including PAT, and showed higher odds ratios of having high PAT (OR=4.10 in the second tertile group and OR=5.06 in their third tertile group, respectively) after age, sex, smoking adjustments. TG/HDL ratio according to the having increased PAT by ROC curve showed 1.918 (p < 0.001). Conclusion: TG/HDL ratio and high PAT volume have a significant positive correlation, and higher TG/HDL ratio showed high PAT. The cut-off value of the TG/HDL ratio was 1.918 to have a high PAT.

Keywords: triglyceride, high-density lipoprotein, pericardial adipose tissue, cut-off value

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