Search results for: regression hypothesis

Authors: André Melo Franco Lorena De Barros, Elida Geralda Campos

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The bilingual education has just started in Brazils public schools. This paper is a didactic sequence of biology bilingual lessons about biologic control in the Brazilian Savana. This sequence has been applied in the first year of a bilingual education program in the only public English and Portuguese bilingual high school in Brazil. The aim of this work is to develop and apply a didactic sequence capable of developing the scientific literacy through the bilingual education associated with Problem Based Learning. This didactic sequence was applied in a class of 30 students. It was divided in three lessons. In the first lesson the students were divided in groups and received a fiction Letter from a mayor explaining the problem and asking students for help. The organic soy plantation of the mayor’s is been attacked by caterpillars. The students read the text then raised hypothesis of how they could solve the problem. In the second lesson the students searched online to verify if theirs hypothesis were correct and to find answers for the question proposed. In the third lesson the groups got together and discussed about their results and wrote a final essay with the answers for the problem proposed. The tools used to acquire information about the didactic sequence were: researcher’s diary, survey, interview and essay developed by the students. Most of the initial hypothesis couldn’t answer the problem properly. By the second lesson most of the students could answer properly. During the third lesson all the groups figured out suitable answers. The forms of biological control, birds habits and transgenic were deeply studied by the students. This methodology was successful for developing the scientific literacy with most of the students and also concluded that the quality of learning is directly associated with the effort of each student during the process. [ARAÚJO, Denise Lino de. O que é (e como se faz) sequência didática. Entrepalavras, Fortaleza, v. 3, n. 3, p.322-334, jul. 2013.] [FRANCO, Aline Aparecida et al. Preferência alimentar de Anticarsia gemmatalis Hübner (Lepidoptera: Noctuidae) por cultivares de soja. Científica: Revista de Ciências Agrárias, Jaboticabal, v. 1, n. 42, p.32-38, 29 jan. 2014.] [RIBEIRO, Luis Roberto de Camargo. Aprendizagem baseada em problemas (PBL): Uma experiência no ensino superior. São Carlos: Editora da Universidade Federal de São Carlos Ribeiro, 2008. 151 p.] [TRIVELATO, Sílvia L. Frateschi; TONIDANDEL, Sandra M. Rudella. Ensino Por Investigação: Eixos Organizadores Para Sequências De Ensino De Biologia. Ensaio Pesquisa em Educação em Ciências, Belo Horizonte, v. 17, n. especial, p.97-114, nov. 2015.].

Keywords: Bilingual Education, Environmental Education, Problem Based Learning, Science education

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Authors: Sha Fan, Renuka Mahadevan

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In recent years, the subject of how retirement influences consumption behaviours has garnered attention in economic research. However, a significant gap persists in our understanding of how retirement precisely impacts tourism consumption patterns among the elderly demographic. To address this gap, this research conducts an in-depth exploration into the multifaceted relationship between retirement and elderly tourism consumption.To achieve this, the study employs regression discontinuity design, using three waves of panel data from China covering a span of six years. This approach aims to identify the causality between retirement and tourism consumption. Furthermore, the study scrutinizes the pathways through which retirement's impact on tourism consumption unfolds. It adopts a dual-pronged perspective, examining the roles played by economic status and the availability of leisure time. The economic dimension underscores the financial adjustments that retirees make as they transition into a new phase of life, impacting their propensity to allocate resources towards tourism activities. Meanwhile, considering leisure time recognizes that retirement often heralds an era of newfound freedom, allowing retirees the luxury to engage in leisurely pursuits like tourism.

Keywords: tourism consumption, retirement, the elderly, regression discontinuity design

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Authors: Elnaz Bandeh

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This study aimed to predict marital burnout based on irrational beliefs and sexual dysfunction of couples. The research method was descriptive-correlational, and the statistical population included all couples who consulted to counseling clinics in the fall of 2016. The sample consisted of 200 people who were selected by convenience sampling and answered the Ahwaz Irrational Beliefs Questionnaire, Pines Couple Burnout, and Hudson Marital Satisfaction Questionnaire. The data were analyzed using regression coefficient. The results of regression analysis showed that there was a linear relationship between irrational beliefs and couple burnout and dimensions of helplessness toward change, expectation of approval from others, and emotional irresponsibility were positive and significant predictors of couple burnout. However, after avoiding the problem of power, it was not a significant predictor of marital dissatisfaction. There was also a linear relationship between sexual dysfunction and couple burnout, and sexual dysfunction was a positive and significant predictor of couple burnout. Based on the findings, it can be concluded that irrational beliefs and sexual dysfunction play a role in couple dysfunction.

Keywords: couple burnout, irrational beliefs, sexual dysfunction, marital relationship

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Authors: Mehmet Izzettin Yilmazer, Emin Cadirli

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Zn-7wt.%Al-2.96wt.%Cu eutectic alloy was directionally solidified upwards with different temperature gradients (from 6.70 K/mm to 10.67 K/mm) at a constant growth rate (16.4 Km/s) and also different growth rate (from 8.3 micron/s to 166 micron/s) at a constant temperature gradient (10.67 K/mm) using a Bridgman–type growth apparatus.The values of eutectic spacing were measured from longitudinal and transverse sections of the samples. The dependency of microstructures on the G and V were determined with linear regression analysis and experimental equations were found as λl=8.953xVexp-0.49, λt=5.942xVexp-0.42 and λl=0.008xGexp-1.23, λt=0.024xGexp-0.93. The measurements of microhardness of directionally solidified samples were obtained by using a microhardness test device. The dependence of microhardness HV on temperature gradient and growth rate were analyzed. The dependency of microhardness on the G and V were also determined with linear regression analysis as HVl=110.66xVexp0.02, HVt=111.94xVexp0.02 and HVl=69.66xGexp0.17, HVt=68.86xGexp0.18. The experimental results show that the microhardness of the directionally solidified Zn-Al-Cu alloy increases with increasing the growth rate. The results obtained in this work were compared with the previous similar experimental results.

Keywords: directional solidification, eutectic alloys, microstructure, microhardness

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: machine learning, stock market trading, logistic regression, cluster analysis, factor analysis, decision trees, neural networks, automated stock investment system

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Authors: Pawthawala Nancy Manish, Syed Alay Hashim

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A hybrid rocket is a rocket engine which uses propellants in two different states of matter- one is in solid and the other either gas or liquid. A hybrid rocket exhibit advantages over both liquid rockets and solid rockets especially in terms of simplicity, stop-start-restart capabilities, safety and cost. This paper deals the design and development of a hybrid rocket having paraffin wax as solid fuel and liquid oxygen as oxidizer. Due to variation of pressure in combustion chamber there is significantly change in mass flow rate, burning rate and uneven regression along the length of the grain. This project describes the working model of a hybrid propellant rocket motor. We have designed a hybrid rocket thrust chamber based on the predetermined combustion chamber pressure and the properties of hybrid propellant. This project is all ready in working condition with normal oxygen injector. Now we have planned to modify the injector design to improve the combustion property. We will use spray type injector for injecting the oxidizer. This idea will increase the performance followed by the regression rate of the solid fuel. By employing mass conservation law, oxygen mass flux, oxidizer/fuel ratio and regression rate the thrust coefficient can be obtained for our current design. CATIA V5 R20 is our design software for the complete setup. This project is fully based on experimental evaluation and the collection of combustion and flow parameters. The thrust chamber is made of stainless steel and the duration of test is around 15-20 seconds (Maximum). These experiments indicates that paraffin based fuel provides the opportunity to satisfy a broad range of mission requirements for the next generation of the hybrid rocket system.

Keywords: burning rate, liquid oxygen, mass flow rate, paraffin wax and sugar

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Ismatilla Mardanov

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There are three types of countries, the first of which is willing to attract foreign direct investment (FDI) in enormous amounts and do whatever it takes to make this happen. Therefore, FDI pours into such countries. In the second cluster of countries, even if the country is suffering tremendously from the shortage of investments, the governments are hesitant to attract investments because they are at the hands of local oligarchs/cartels. Therefore, FDI inflows are moderate to low in such countries. The third type is countries whose companies prefer investing in the most efficient locations globally and are hesitant to invest in the homeland. Sorting countries into such clusters, the present study examines the essential institutions and economic factors that make these countries different. Past literature has discussed various determinants of FDI in all kinds of countries. However, it did not classify countries based on government motivation, institutional setup, and economic factors. A specific approach to each target country is vital for corporate foreign direct investment risk analysis and decisions. The research questions are 1. What specific institutional and economic factors paint the pictures of the three clusters; 2. What specific institutional and economic factors are determinants of FDI; 3. Which of the determinants are endogenous and exogenous variables? 4. How can institutions and economic and political variables impact corporate investment decisions Hypothesis 1: In the first type, country institutions and economic factors will be favorable for FDI. Hypothesis 2: In the second type, even if country economic factors favor FDI, institutions will not. Hypothesis 3: In the third type, even if country institutions favorFDI, economic factors will not favor domestic investments. Therefore, FDI outflows occur in large amounts. Methods: Data come from open sources of the World Bank, the Fraser Institute, the Heritage Foundation, and other reliable sources. The dependent variable is FDI inflows. The independent variables are institutions (economic and political freedom indices) and economic factors (natural, material, and labor resources, government consumption, infrastructure, minimum wage, education, unemployment, tax rates, consumer price index, inflation, and others), the endogeneity or exogeneity of which are tested in the instrumental variable estimation. Political rights and civil liberties are used as instrumental variables. Results indicate that in the first type, both country institutions and economic factors, specifically labor and logistics/infrastructure/energy intensity, are favorable for potential investors. In the second category of countries, the risk of loss of assets is very high due to governmentshijacked by local oligarchs/cartels/special interest groups. In the third category of countries, the local economic factors are unfavorable for domestic investment even if the institutions are well acceptable. Cluster analysis and instrumental variable estimation were used to reveal cause-effect patterns in each of the clusters.

Keywords: foreign direct investment, economy, institutions, instrumental variable estimation

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Authors: Waseem Al Talalwah, Shorok Al Dorazi, Roger Soames

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Persistent sciatic artery is a rare anatomical vascular variation resulting from a lack of regression of the embryonic dorsal axial artery. The axial artery is the main artery supplying the lower limb during development in the first trimester. The current research includes 206 sciatic artery cases in 171 patients between 1864 and 2012. It aims to identify the risk factor of sciatic artery aneurysm in congenital limb anomalies. Sciatic artery aneurysm was diagnosed incidentally in amniotic band syndrome (ABS) existing with no congenital anomaly in 0.7% or with double knee in 0.7%, with the tibia in 0.7% and with hemihypertrophy or soft tissue hypertrophy in 1.4%. Therefore, the current study indicates a relationship the same gene responsible for the congenital limb deformities may be responsible for non-regression of the sciatic artery. Furthermore, pediatricians should refer cases of congenital limb anomalies for vascular evaluation prior to corrective surgical intervention.

Keywords: amniotic band syndrome, congenital limb deformities, double knee, sciatic artery, sciatic artery aneurysm , soft tissue hypertrophy

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Authors: Mohsen Amiri

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This study aimed at investigating the relationship between familial functioning, child characteristics, demographic variables and parenting stress and mental health among parents of children with mental disabilities. 200 parents (130 mothers and 70 fathers) were studied and they completed the Parenting Stress Index, General Health Questionnaire, Family Assessment Device and demographic questionnaires for parents and children. Data were analyzed using correlation and regression analysis. Regression analysis showed that child characteristics, familial functioning and parents demographic factors could predict 8, 4 and 17 percent of variance in parental stress and 3.6, 16 and 10 percent of variance in mental health, respectively. Familial functioning, child characteristics and parental demographic variables correlated with mental health and parental stress and could predict them.

Keywords: parenting stress, mental health, mentally disabled children, familial functioning, demographic variables

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Authors: Kaisy Xinhong Ye, Su Lin Lim, Jialiang Li, Lei Feng

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background: Multiple healthful dietary patterns have been linked with dementia, but limited studies have looked at the role of diet in cognitive health in Asians whose eating habits are very different from their counterparts in the west. This study aimed to derive a dietary pattern that is associated with the risk of cognitive impairment (CI) in the Singaporean population. Method: The analysis was based on 719 community older adults aged 60 and above. Dietary intake was measured using a validated semi-quantitative food-frequency questionnaire (FFQ). Reduced rank regression (RRR) was used to extract dietary pattern from 45 food groups, specifying sugar, dietary fiber, vitamin A, calcium, and the ratio of polyunsaturated fat to saturated fat intake (P:S ratio) as response variables. The RRR-derived dietary patterns were subsequently investigated using multivariate logistic regression models to look for associations with the risk of CI. Results: A dietary pattern characterized by greater intakes of green leafy vegetables, red-orange vegetables, wholegrains, tofu, nuts, and lower intakes of biscuits, pastries, local sweets, coffee, poultry with skin, sugar added to beverages, malt beverages, roti, butter, and fast food was associated with reduced risk of CI [multivariable-adjusted OR comparing extreme quintiles, 0.29 (95% CI: 0.11, 0.77); P-trend =0.03]. This pattern was positively correlated with P:S ratio, vitamin A, and dietary fiber and negatively correlated with sugar. Conclusion: A dietary pattern providing high P:S ratio, vitamin A and dietary fiber, and a low level of sugar may reduce the risk of cognitive impairment in old age. The findings have significance in guiding local Singaporeans to dementia prevention through food-based dietary approaches.

Keywords: dementia, cognitive impairment, diet, nutrient, elderly

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Authors: Jeeban Amgain

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This paper investigates the impact of the size and composition of government expenditure and tax on GDP per capita growth in 36 Asian economies over the period of 1991-2012. The research employs the technique of panel regression; Fixed Effects and Generalized Method of Moments (GMM) as well as other statistical and descriptive approaches. The finding concludes that the size of government expenditure and tax revenue are generally low in this region. GDP per capita growth is strongly negative in response to Government expenditure, however, no significant relationship can be measured in case of size of taxation although it is positively correlated with economic growth. Panel regression of decomposed fiscal components also shows that the pattern of allocation of expenditure and taxation really matters on growth. Taxes on international trade and property have a significant positive impact on growth. In contrast, a major portion of expenditure, i.e. expenditure on general public services, health and education are found to have significant negative impact on growth, implying that government expenditures are not being productive in the Asian region for some reasons. Comparatively smaller and efficient government size would enhance the growth.

Keywords: government expenditure, tax, GDP per capita growth, composition

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Authors: Davod Ahmadigheidari

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The main objective of this study was to explore prevalence of anthropometric indicators as well the factors associated with the anthropometric indications in Mali. Data on 2015, downloaded from the website of Unicef, were analyzed. A total of 16,467 women (ages 15-49 years) and 16,467 children (ages 0-59 months) were selected for the sample. Different statistical analyses, such as descriptive, crosstabs and binary logistic regression form the basis of this study. Child anthropometric indicators (i.e., wasting, stunting, underweight and BMI for age) were used as the dependent variables. SPSS Syntax from WHO was used to create anthropometric indicators. Different factors, such as child’s sex, child’s age groups, child’s diseases symptoms (i.e., diarrhea, cough and fever), maternal education, household wealth index and area of residence were used as independent variables. Results showed more than forty percent of Malian households were in nutritional crises (stunting (42%) and underweight (34%). Findings from logistic regression analyses indicated that low score of wealth index, low maternal education and experience of diarrhea in last two weeks increase the probability of child malnutrition.

Keywords: Mali, wasting, stunting, underweight, BMI for age and wealth index

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Authors: Arun Dhakal, Geoff Cockfield, Tek Narayan Maraseni

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This paper attempts to fulfil the gap in measuring adoption in agroforestry studies. It explains the derivation of an index of adoption rate in a Nepalese context and examines the factors affecting adoption of agroforestry-based land management practice (AFLMP) in the Dhanusha District of Nepal. Data about the different farm practices and the factors (bio-physical, socio-economic) influencing adoption were collected during focus group discussion and from the randomly selected households using a household survey questionnaire, respectively. A multivariate regression model was used to determine the factors. The factors (variables) found to significantly affect adoption of AFLMP were: farm size, availability of irrigation water, education of household heads, agricultural labour force, frequency of visits by extension workers, expenditure on farm inputs purchase, household’s experience in agroforestry, and distance from home to government forest. The regression model explained about 75% of variation in adoption decision. The model rejected ‘erosion hazard’, ‘flood hazard’ and ‘gender’ as determinants of adoption, which in case of single agroforestry practice were major variables and played positive role. Out of eight variables, farm size played the most powerful role in explaining the variation in adoption, followed by availability of irrigation water and education of household heads. The results of this study suggest that policies to promote the provision of irrigation water, extension services and motivation to obtaining higher education would probably provide the incentive to adopt agroforestry elsewhere in the terai of Nepal.

Keywords: agroforestry, adoption index, determinants of adoption, step-wise linear regression, Nepal

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Authors: Peter Temitope Agboola

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Food insecurity continues to affect a large number of U.S households during this coronavirus COVID-19 pandemic. The pandemic has threatened the livelihoods of people, making them vulnerable to severe hardship and has had an unanticipated impact on the U.S economy. This study attempts to identify the food insecurity status of households and the determinant factors driving household food insecurity. Additionally, it attempts to discover the mitigation measures adopted by households during the pandemic in the city of Huntsville, Texas. A structured online sample survey was used to collect data, with a household expenditures survey used in evaluating the food security status of the household. Most survey respondents disclosed that the COVID-19 pandemic had affected their life and source of income. Furthermore, the main analytical tool used for the study is descriptive statistics and logistic regression modeling. A logistic regression model was used to determine the factors responsible for food insecurity in the study area. The result revealed that most households in the study area are food secure, with the remainder being food insecure.

Keywords: food insecurity, household expenditure survey, COVID-19, coping strategies, food pantry

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Authors: Ali Soroush, Mehdi Mirzaei Alavijeh, Touraj Ahmadi Jouybari, Fazel Zinat-Motlagh, Abbas Aghaei, Mari Ataee

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Diabetes is a disease with long cardiovascular, renal, ophthalmic and neural complications. It is prevalent all around the world including Iran, and its prevalence is increasing. The aim of this study was to determine the factors related to self-care behavior based on health belief model among sample of Iranian diabetic patients. This cross-sectional study was conducted among 301 type 2 diabetic patients in Gachsaran, Iran. Data collection was based on an interview and the data were analyzed by SPSS version 20 using ANOVA, t-tests, Pearson correlation, and linear regression statistical tests at 95% significant level. Linear regression analyses showed the health belief model variables accounted for 29% of the variation in self-care behavior; and perceived severity and perceived self-efficacy are more influential predictors on self-care behavior among diabetic patients.

Keywords: diabetes, patients, self-care behaviors, health belief model

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Authors: Hamed Rashid Sarand, Kemal Selçuk Öğüt

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Speed is one of the fundamental variables of road traffic flow that stands as an important evaluation criterion for traffic analyses in several aspects. In particular, varieties of speed variable, such as average speed, free flow speed, optimum speed (capacity speed), acceleration/deceleration speed and so on, have been explicitly considered in the analysis of not only road safety but also road capacity. In the purpose of realizing 'road speed – maximum speed difference across lanes' and 'road flow rate – maximum speed difference across lanes' relations on freeway traffic, this study presents a case study conducted on a basic freeway segment of O-2 in Istanbul. The traffic data employed in this study have been obtained from 5 remote traffic microwave sensors operated by Istanbul Metropolitan Municipality. The study stretch is located between two successive freeway interchanges: Ümraniye and Kavacık. Daily traffic data of 4 years (2011-2014) summer months, July and August are used. The speed data are analyzed into two main flow areas such as uncongested and congested flows. In this study, the regression analyses were carried out in order to examine the relationship between maximum speed difference across lanes and road speed. These investigations were implemented at uncongested and congested flows, separately. Moreover, the relationship between maximum speed difference across lanes and road flow rate were evaluated by applying regression analyses for both uncongested and congested flows separately. It is concluded that there is the moderate relationship between maximum speed difference across lanes and road speed in 50% cases. Additionally, it is indicated that there is the moderate relationship between maximum speed difference across lanes and road flow rate in 30% cases. The maximum speed difference across lanes decreases as the road flow rate increases.

Keywords: maximum speed difference, regression analysis, remote traffic microwave sensor, speed differentiation, traffic flow

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Authors: Fuchun Li, Hong Xiao

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We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

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Authors: Arvind Salem

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Voters across the country are transferring the power of redistricting from the state legislatures to commissions to secure “fairer” districts by curbing the influence of gerrymandering on redistricting. Gerrymandering, intentionally drawing distorted districts to achieve political advantage, has become extremely prevalent, generating widespread voter dissatisfaction and resulting in states adopting commissions for redistricting. However, the efficacy of these commissions is dubious, with some arguing that they constitute a panacea for gerrymandering, while others contend that commissions have relatively little effect on gerrymandering. A result showing that commissions are effective would allay these fears, supplying ammunition for activists across the country to advocate for commissions in their state and reducing the influence of gerrymandering across the nation. However, a result against commissions may reaffirm doubts about commissions and pressure lawmakers to make improvements to commissions or even abandon the commission system entirely. Additionally, these commissions are publicly funded: so voters have a financial interest and responsibility to know if these commissions are effective. Currently, nine states place commissions in charge of redistricting, Arizona, California, Colorado, Michigan, Idaho, Montana, Washington, and New Jersey (Hawaii also has a commission but will be excluded for reasons mentioned later). This study compares the degree of gerrymandering in the 2022 election (“after”) to the election in which voters decided to adopt commissions (“before”). The before-election provides a valuable benchmark for assessing the efficacy of commissions since voters in those elections clearly found the districts to be unfair; therefore, comparing the current election to that one is a good way to determine if commissions have improved the situation. At the time Hawaii adopted commissions, it was merely a single at-large district, so it is before metrics could not be calculated, and it was excluded. This study will use three methods to quantify the degree of gerrymandering: the efficiency gap, the percentage of seats and the percentage of votes difference, and the mean-median difference. Each of these metrics has unique advantages and disadvantages, but together, they form a balanced approach to quantifying gerrymandering. The study uses a Wilcoxon Signed-Rank Test with a null hypothesis that the value of the metrics is greater than or equal to after the election than before and an alternative hypothesis that the value of these metrics is greater in the before the election than after using a 0.05 significance level and an expected difference of 0. Accepting the alternative hypothesis would constitute evidence that commissions reduce gerrymandering to a statistically significant degree. However, this study could not conclude that commissions are effective. The p values obtained for all three metrics (p=0.42 for the efficiency gap, p=0.94 for the percentage of seats and percentage of votes difference, and p=0.47 for the mean-median difference) were extremely high and far from the necessary value needed to conclude that commissions are effective. These results halt optimism about commissions and should spur serious discussion about the effectiveness of these commissions and ways to change them moving forward so that they can accomplish their goal of generating fairer districts.

Keywords: commissions, elections, gerrymandering, redistricting

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Authors: Nur Sahver Uslu, Ali̇ Hakan Büyüklü

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Maintenance, Repair, and Overhaul (MRO) costs are significant in the aviation industry. On the other hand, companies that provide MRO services to the aviation industry but are not dominant in the sector, need to determine the right strategies for sustainable profitability in a competitive environment. This study examined the operational real data of a small medium enterprise (SME) MRO company where analytical methods are not widely applied. The company's customers were divided into two categories: airline companies and non-airline companies, and the variables that best explained profitability were analyzed with Logistic Regression for each category and the results were compared. First, data reduction was applied to the transformed variables that went through the data cleaning and preparation stages, and the variables to be included in the model were decided. The misclassification rates for the logistic regression results concerning both customer categories are similar, indicating consistent model performance across different segments. Less profit margin is obtained from airline customers, which can be explained by the variables part description, time to quotation (TTQ), turnaround time (TAT), manager, part cost, and labour cost. The higher profit margin obtained from non-airline customers is explained only by the variables part description, part cost, and labour cost. Based on the two models, it can be stated that it is significantly more challenging for the MRO company, which is the subject of our study, to achieve profitability from Airline customers. While operational processes and organizational structure also affect the profit from airline customers, only the type of parts and costs determine the profit for non-airlines.

Keywords: aircraft, aircraft components, aviation, data analytics, data science, gini index, maintenance, repair, and overhaul, MRO, logistic regression, profit, variable clustering, variable reduction

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Authors: Sepinoud Hamedi

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The ponder points to observationally look at the impact of carbon-neutrality approaches on the key assets required for Industry 4.0 driven savvy fabricating and how these assets can give a economical competitive advantage. The hypothetical system is coordinates with the regulation hypothesis and the resource-based see (RBV). The observational strategy is utilized for collecting information through studies and assist covariance-based auxiliary condition modeling is utilized to test the theories. Discoveries demonstrate that carbon–neutral-based government arrangements have a more grounded impact on unmistakable assets and human aptitudes than intangible assets related to Industry 4.0 driven shrewd fabricating. Moment, carbon–neutral arrangement arrangement with the firm’s maintainability destinations plays a directing impact on the relationship between carbon–neutral-based government arrangements and assets (substantial, intangible assets and human abilities) for Industry 4.0 driven shrewd fabricating. Finally, the three assets (substantial, intangible assets and human abilities) for Industry 4.0 driven savvy fabricating play a basic part in creating firms’ carbon–neutral capability and assist improving operational execution. Administrative suggestions incorporate venture in progressed advanced innovations, creating a solid mentality among workers and supply chain partners, and planning preparing programs for upgrading shrewd fabricating execution to create carbon-neutrality capability. This think about proposes a crossover hypothesis within the setting of carbon nonpartisanship by coordination institutional theory and RBV. Typically the primary think about that looks at the impact of carbon neutrality-based government arrangements on crucial Industry 4.0-driven savvy fabricating assets and the circuitous impact on carbon nonpartisanship capability and operational execution.

Keywords: carbon, industry 4.0, neutrality, RBV, nonpartisanship

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: Ahmad Zulfahmi Mohd Kamaruzaman, Mohd Ismail Ibrahim, Ariffin Marzuki Mokhtar, Maizun Mohd Zain, Saiful Nazri Satiman, Mohd Najib Majdi Yaacob

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Background: Aftermath any patient safety incidents, the involved healthcare providers possibly sustained second victim-related distress (second victim distress and reduced their professional efficacy), with subsequent negative work-related outcomes or vice versa cultivating resilience. This study aimed to investigate the factors affecting negative work-related outcomes and resilience, with the triad of support; colleague, supervisor, and institutional support as the hypothetical mediators. Methods: This was a cross sectional study recruiting a total of 733 healthcare providers from three tertiary care in Kelantan, Malaysia. Three steps of hierarchical linear regression were developed for each outcome; negative work-related outcomes and resilience. Then, four multiple mediator models of support triad were analyzed. Results: Second victim distress, professional efficacy, and the support triad contributed significantly for each regression model. In the pathway of professional efficacy on each negative work-related outcomes and resilience, colleague support partially mediated the relationship. As for second victim distress on negative work related outcomes, colleague and supervisor support were the partial mediator, and on resilience; all support triad also produced a similar effect. Conclusion: Second victim distress, professional efficacy, and the support triad influenced the relationship with the negative work-related outcomes and resilience. Support triad as the mediators ameliorated the effect in between and explained the urgency of having good support for recovery post encountering patient safety incidents.

Keywords: second victims, patient safety incidents, hierarchical linear regression, mediation, support

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Authors: Tanusree Moitra, Garga Chatterjee, Diganta Mukherjee, Anjali Ghosh

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Stroop task is considered to be an important measure of selective attention. However, the color – word Stroop task cannot be administered to the illiterate population. Some of the participants in the present study are illiterate, therefore, object – color Stroop task was used among male juvenile delinquents of India and Bangladesh citizenship (IC & BC), housed in delinquent home in India. The purpose of the study is to test the hypothesis that over - selective attention is present among juvenile delinquents across both the countries. Eighty juvenile delinquents and matched control of 12 – 18 years (50 IC juvenile delinquents, 30 BC juvenile delinquents and 50 Indian control) were shown 24 familiar objects in both typical (e.g. a red apple) and atypical (e.g. a blue apple) color. Repeated – measure factorial ANOVA was used and it was found that all the three groups have taken longer response time in the atypical condition compared to the typical condition. However, contrary to the over - selective attention hypothesis, both groups of juvenile delinquents displayed higher Stroop interference in comparison to the matched control group. The findings of the study can be explained on the basis of anxiety score. IC and BC juvenile delinquents have high anxiety score compared to the control group which indicates that increased anxiety is correlated with the interference produced by the atypical color object stimuli when compared with the typical object stimuli. Funding acknowledgement: Authors acknowledge Department of Science and Technology, Government of India for financial support to the first author of the paper vide Reference no. SR/CSRI/PDF -01/2013 under Cognitive Science Research Initiative (CSRI) to carry out this work.

Keywords: Bangladesh, India, male juvenile delinquent, objects - color Stroop task

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Authors: Joshua W. Edefo, Shafiul Azam, Murray D. Smith

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Introduction: In April 2022, the Welsh Government introduced the six goals for urgent and emergency care programs. One of these goals was to provide access to clinically safe alternatives, leading to the establishment of the Same Day Emergency Care (SDEC) program. The SDEC initiative aims to offer viable options that maintain patient safety while avoiding unnecessary hospital stays. The aim of the study is to determine the duration of patient stay in SDEC and compare it with that of Emergency department (ED) stay to ascertain if one of the objectives of SDEC is achieved. Methods: Patient stays and attendance datasets were constructed from Withybush SDEC and ED patient records. These records were provided by Hywel Dda University Health Board Informatics. Some hypothetical pathways were identified, notably SDEC visits involving a single attendance and ED visits then immediately transferred to SDEC. Descriptive statistics were used to summarise the data, and hypothesis tests for mean differences used the student t-test. Propensity scoring was employed to match a set of ED patient stays to SDEC patient stays which were then used to determine the average treatment effect (ATE) to compare durations of stay in SDEC with ED. Regression methods were used to model the natural logarithm of the duration of SDEC attendance, and the level of statistical significance was set to 0.05. Results: SDEC visits involving a single attendance (170 of 384; 44.3%) is the most frequently observed pathway with patient length of stay at 256 minutes (95%CI 237.4 - 275.1). The next most frequently observed pathway of patient stay was SDEC attendance after presenting to ED (80 of 384; 20.8%) and gave the length of stay of 440 minutes (95%CI 351.6 - 529.2). Time spent in this pathway significantly increased by 184 minutes (95%CI 118.0 - 250.2, support for no difference p<0.001) compared to the most seen pathway. When SDEC data were compared with ED, the estimate for the ATE from SDEC single attendance was -272 minutes (95%CI -334.1 - -210.5; p<0.001), while that of ED then SDEC pathway was -50.6 min (95%CI -182.7-81.5; p=0.453). Conclusion: When patients are admitted to SDEC and successfully discharged, their stays are significantly shorter, approximately 4.5 hours, compared to patients who spend their entire stay in the Emergency Department. That difference vanishes when the patient stay includes a period spent previously in ED before transfer to SDEC.

Keywords: attendance, emergency-department, patient-stay, same-day-emergency-care

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Authors: Suryapeta Harini

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Road surface roughness is one of the essential aspects of the road's functional condition, indicating riding comfort in both the transverse and longitudinal directions. The government of India has made maintaining good surface evenness a prerequisite for all highway projects. Pavement distress data was collected with a Network Survey Vehicle (NSV) on a National Highway. It determines the smoothness and frictional qualities of the pavement surface, which are related to driving safety and ease. Based on the data obtained in the field, a regression equation was created with the IRI value and the visual distresses. The suggested system can use wireless acceleration sensors and GPS to gather vehicle status and location data, as well as calculate the international roughness index (IRI). Potholes, raveling, rut depth, cracked area, and repair work are all affected by pavement roughness, according to the current study. The study was carried out in one location. Data collected through using Bump integrator was used for the validation. The bump integrator (BI) obtained using deflection from the network survey vehicle was correlated with the distress parameter to establish an equation.

Keywords: roughness index, network survey vehicle, regression, correlation

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Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

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Authors: Khiari Nor El Houda, Hiouani Amira Sarra

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Many EFL students with high capacities are hidden because they suffer from speaking anxiety (SA). Most of them find public speaking much demanding. They feel unable to communicate, they fear to make mistakes and they fear negative evaluation or being called on. With the growing number of the learners who suffer from foreign language speaking anxiety (FLSA), it is becoming increasingly difficult to ignore its harmful outcomes on their performance and success, especially during their first contact with the pupils, as they will be teaching in the near future. Different researchers suggested different ways to minimize the negative effects of FLSA. The present study sheds light on emotional intelligence skills training as an effective strategy not only to influence public speaking success but also to help pre-service EFL teachers lessen their speaking anxiety and eventually to prepare them for their professional career. A quasi-experiment was used in order to examine the research hypothesis. We worked with two groups of third-year EFL students at Oum El Bouaghi University. The Foreign Language Classroom Anxiety Scale (FLCAS) and the Emotional Quotient Inventory (EQ-i) were used to collect data about the participants’ FLSA and EI levels. The analysis of the data has yielded that the assumption that there is a negative correlation between EI and FLSA was statistically validated by the Pearson Correlation Test, concluding that, the more emotionally intelligent the individual is the less anxious s/he will be. In addition, the lack of amelioration in the results of the control group and the noteworthy improvement in the experimental group results led us to conclude that EI skills training was an effective strategy in minimizing the FLSA level and therefore, we confirmed our research hypothesis.

Keywords: emotional intelligence, emotional intelligence skills training, EQ-I, FLCAS, foreign language speaking anxiety, pre-service EFL teachers

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Authors: Raeed Alanazi

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Introduction: Nursing students have a crucial role to play in the inhibition of infectious diseases and, therefore, must be trained in infection control and prevention modules prior to entering clinical settings. Simulations have been found to have a positive impact on infection control skills and the use of standard precautions. Aim: The purpose of this study was to use the four sources of self-efficacy in explaining the level of clinical self-efficacy and adherence to infection control practices in Saudi nursing students during simulation practice. Method: A cross-sectional design with convenience sampling was used. This study was conducted in all Saudi nursing schools, with a total number of 197 students participated in this study. Three scales were used simulation self- efficacy Scale (SSES), the four sources of self-efficacy scale (SSES), and Compliance with Standard Precautions Scale (CSPS). Multiple linear regression was used to test the use of the four sources of self-efficacy (SSES) in explaining level of clinical self-efficacy and adherence to infection control in nursing students. Results: The vicarious experience subscale (p =.044) was statistically significant. The regression model indicated that for every one unit increase in vicarious experience (observation and reflection in simulation), the participants’ adherence to infection control increased by .13 units (β =.22, t = 2.03, p =.044). In addition, the regression model indicated that for every one unit increase in education level, the participants’ adherence to infection control increased by 1.82 units (beta=.34= 3.64, p <.001). Also, the mastery experience subscale (p <.001) and vicarious experience subscale (p = .020) were shared significant associations with clinical self-efficacy. Conclusion: The findings of this research support the idea that simulation-based learning can be a valuable teaching-learning method to help nursing students develop clinical competence, which is essential in providing quality and safe nursing care.

Keywords: simulation-based learning, clinical self-efficacy, infection control, nursing students

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Authors: Müzeyyen Balçikanli, Erdoğan Özbay, Hakan Tacettin Türker, Okan Karahan, Cengiz Duran Atiş

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In this research, effect of curing time (TC), curing temperature (CT), sodium concentration (SC) and silicate modules (SM) on the compressive strength, chloride ion permeability, and water absorption capacity of alkali activated slag (AAS) concretes were investigated. For maximization of compressive strength while for minimization of chloride ion permeability and water absorption capacity of AAS concretes, best possible combination of CT, CTime, SC and SM were determined. An experimental program was conducted by using the central composite design method. Alkali solution-slag ratio was kept constant at 0.53 in all mixture. The effects of the independent parameters were characterized and analyzed by using statistically significant quadratic regression models on the measured properties (dependent parameters). The proposed regression models are valid for AAS concretes with the SC from 0.1% to 7.5%, SM from 0.4 to 3.2, CT from 20 °C to 94 °C and TC from 1.2 hours to 25 hours. The results of test and analysis indicate that the most effective parameter for the compressive strength, chloride ion permeability and water absorption capacity is the sodium concentration.

Keywords: alkali activation, slag, rapid chloride permeability, water absorption capacity

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