Search results for: multivariate logistic regression

Authors: Bo-Jian Wu, Si-Heng Wu

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Objectives: Frailty is a condition of a person who has chronic health problems complicated by a loss of physiological reserve and deteriorating functional abilities. The frailty syndrome was defined by Fried and colleagues, i.e., weight loss, fatigue, decreased grip strength, slow gait speed, and low physical activity. However, to our best knowledge, there have been rare studies exploring the prevalence of frailty and its association with falls in patients with schizophrenia. Methods: A total of 559 hospitalized patients were recruited from a public psychiatric hospital in 2013. The majority of the subjects were males (361, 64.6%). The average age was 53.5 years. All patients received the assessment of frailty status defined by Fried and colleagues. The status of a fall within one year after the assessment of frailty, clinical and demographic data was collected from medical records. Logistic regression was used to calculate the odds ratio of associated factors. Results : A total of 9.2% of the participants met the criteria of frailty. The percentage of patients having a fall was 7.2%. Age were significantly associated with frailty (odds ratio = 1.057, 95% confidence interval = 1.025-1.091); however, sex was not associated with frailty (p = 0.17). After adjustment for age and sex, frailty status was associated with a fall (odds ratio = 3.62, 95% confidence interval = 1.58-8.28). Concerning the components of frailty, decreased grip strength (odds ratio = 2.44, 95% confidence interval = 1.16-5.14), slow gait speed (odds ratio = 2.82, 95% confidence interval = 1.21-6.53), and low physical activity (odds ratio = 2.64, 95% confidence interval = 1.21-5.78) were found to be associated with a fall. Conclusions: Our findings suggest the prevalence of frailty was about 10% in hospitalized patients with chronic patients with schizophrenia, and frailty status was significant with a fall in this group. By using the status of frailty, it may be beneficial to potential target candidates having fallen in the future as early as possible. The effective intervention of prevention of further falls may be given in advance. Our results bridge this gap and open a potential avenue for the prevention of falls in patients with schizophrenia. Frailty is certainly an important factor for maintaining wellbeing among these patients.

Keywords: fall, frailty, schizophrenia, Taiwan

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Authors: Seyedeh Khadijeh Amirian, Seyed Mohammad Reza Amirian, Narges Hekmati

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The current study aims at examining the relationship between English as a foreign language (EFL) students' self-concept and their willingness to communicate (WTC) in EFL classes. To this effect, two questionnaires, namely 'Willingness to Communicate' (MacIntyre et al., 2001) and 'Self-Concept Scale' (Liu and Wang, 2005), were distributed among 174 (45 males and 129 females) Iranian EFL university students. Correlation and regression analyses were conducted to examine the relationship between the two variables. The results indicated that there was a significantly positive correlation between EFL students' self-concept and their WTC in EFL classes (p < .0.05). Moreover, regression analyses indicated that self-concept has a significantly positive influence on students’ WTC in language classes (B= .302, p < .0.05) and explains .302 percent of the variance in the dependent variable (WTC). The results are discussed with regards to the individual differences in educational contexts, and implications are offered.

Keywords: EFL students, language classes, willingness to communicate, self-concept

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Authors: Asma Alzahrani, Elizabeth Stojanovski

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This study investigated factors that influence mathematics achievement based on a sample of ninth-grade students (N  =  21,444) from the High School Longitudinal Study of 2009 (HSLS09). Key aspects studied included efficacy in mathematics, interest and enjoyment of mathematics, identity with mathematics and future utility beliefs and how these influence mathematics achievement. The predictability of mathematics achievement based on these factors was assessed using correlation coefficients and multiple linear regression. Spearman rank correlations and multiple regression analyses indicated positive and statistically significant relationships between the explanatory variables: mathematics efficacy, identity with mathematics, interest in and future utility beliefs with the response variable, achievement in mathematics.

Keywords: Mathematics achievement, math efficacy, mathematics interest, factors influence

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Authors: Shlomit Hon-Snir, Sharon Teitler-Regev, Anabel Lifszyc Friedlander

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Tourism, one of the world's largest and fastest growing industries, exerts a major economic influence. The number of international tourists is growing every year, and the relative portion of independent (FIT) tourists is growing as well. The characteristics of independent tourists differ from those of tourists who travel in organized trips. The purpose of the research is to identify the factors that affect the individual tourist's expenses in Israel: total expenses, expenses per day, expenses per tourist, expenses per day per tourist, accommodation expenses, dining expenses and transportation expenses. Most of the research analyzed the total expenses using OLS regression. The determinants influencing expenses were divided into four groups: budget constraints, socio-demographic data, psychological characteristics and travel-related characteristics. Since the effect of each variable may change over different levels of total expenses the quantile regression (QR) theory will be applied. The current research will use data collected by the Israeli Ministry of Tourism in 2015 from individual independent tourists at the end of their visit to Israel. Preliminary results show that: At lower levels of expense, only income has a (positive) effect on total expenses, while at higher levels of expense, both income and length of stay have (positive) effects. -The effect of income on total expenses is higher for higher levels of expenses than for lower level of expenses. -The number of sites visited during the trip has a (negative) effect on tourist accommodation expenses only for tourists with a high level of total expenses. Due to the increasing share of independent tourism in Israel and around the world and due to the importance of tourism to Israel, it is very important to understand the factors that influence the expenses and behavior of independent tourists. Understanding the factors that affect independent tourists' expenses in Israel can help Israeli policymakers in their promotional efforts to attract tourism to Israel.

Keywords: independent tourist, quantile regression theory, tourism expenses, tourism

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Authors: Mahmoud Ahmad Mahmoud

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The surge in unemployment among nations and the understanding of the important role played by entrepreneurship in job creation by researchers and policy makers have steered to the postulation that entrepreneurship activities can be spurred through the development of entrepreneurial intentions. Notwithstanding, entrepreneurial intention studies are very scarce in the developing world especially in the African continent. Even among the developed countries, studies of entrepreneurial intention were mostly focused on the undergraduate candidates. This paper therefore, aimed at filling the gap by employing the descriptive quantitative survey method to examine the entrepreneurial intention of 158 Nigerian postgraduate candidates of Universiti Utara Malaysia (UUM), comprising 46 Masters and 112 PhD candidates who are studying in the College of Business (COB), College of Arts and Sciences (CAS) and College of Legal, Government and International Studies (COLGIS), the theory of planned behaviour (TPB) model was used due its reputable validity, with attitudes, subjective norms and perceived behavioural control as the independent variables. Preliminary analysis and data screening were conducted which qualifies the data to the multivariate analysis assumptions. The reliability test was performed using the Cronbach Alpha method which shows all variables as reliable with a value of >0.70. However, the data is free from the multicollinearity issue with all factors in the Pearson correlation having <0.9 value and the VIF having <10. Regression analysis has shown the sufficiency and predictive capability of the TPB model to entrepreneurship intention with attitude, subjective norms and perceived behavioural control being positively and significantly related to the entrepreneurial intention of Nigerian postgraduates. Considering the Beta values, perceived behavioural control emerged as the strongest factor that influences the postgraduates entrepreneurial intention. Developing countries are therefore, recommended to make efforts in redesigning their entrepreneurship development policies to fit candidates of the highest level of academia. Further studies should replicate in a larger sample that comprises more than one university and more than one developing country.

Keywords: attitude, entrepreneurial intention, Nigeria, perceived behavioral control, postgraduates, subjective norms

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Authors: Roza Dzierzak, Waldemar Wojcik, Piotr Kacejko

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Analysis of the texture of medical images consists of determining the parameters and characteristics of the examined tissue. The main goal is to assign the analyzed area to one of two basic groups: as a healthy tissue or a tissue with pathological changes. The CT images of the thoracic lumbar spine from 15 healthy patients and 15 with confirmed osteoporosis were used for the analysis. As a result, 120 samples with dimensions of 50x50 pixels were obtained. The set of features has been obtained based on the histogram, gradient, run-length matrix, co-occurrence matrix, autoregressive model, and Haar wavelet. As a result of the image analysis, 290 descriptors of textural features were obtained. The dimension of the space of features was reduced by the use of three selection methods: Fisher coefficient (FC), mutual information (MI), minimization of the classification error probability and average correlation coefficients between the chosen features minimization of classification error probability (POE) and average correlation coefficients (ACC). Each of them returned ten features occupying the initial place in the ranking devised according to its own coefficient. As a result of the Fisher coefficient and mutual information selections, the same features arranged in a different order were obtained. In both rankings, the 50% percentile (Perc.50%) was found in the first place. The next selected features come from the co-occurrence matrix. The sets of features selected in the selection process were evaluated using six classification tree methods. These were: decision stump (DS), Hoeffding tree (HT), logistic model trees (LMT), random forest (RF), random tree (RT) and reduced error pruning tree (REPT). In order to assess the accuracy of classifiers, the following parameters were used: overall classification accuracy (ACC), true positive rate (TPR, classification sensitivity), true negative rate (TNR, classification specificity), positive predictive value (PPV) and negative predictive value (NPV). Taking into account the classification results, it should be stated that the best results were obtained for the Hoeffding tree and logistic model trees classifiers, using the set of features selected by the POE + ACC method. In the case of the Hoeffding tree classifier, the highest values of three parameters were obtained: ACC = 90%, TPR = 93.3% and PPV = 93.3%. Additionally, the values of the other two parameters, i.e., TNR = 86.7% and NPV = 86.6% were close to the maximum values obtained for the LMT classifier. In the case of logistic model trees classifier, the same ACC value was obtained ACC=90% and the highest values for TNR=88.3% and NPV= 88.3%. The values of the other two parameters remained at a level close to the highest TPR = 91.7% and PPV = 91.6%. The results obtained in the experiment show that the use of classification trees is an effective method of classification of texture features. This allows identifying the conditions of the spongy tissue for healthy cases and those with the porosis.

Keywords: classification, feature selection, texture analysis, tree algorithms

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Authors: Teklay Gebrecherkos, Dawit Wolday, Muhamud Abdulkader

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Background: COVID-19 symptomatology in Africa appears significantly less serious than in the industrialized world. Our hypothesis for this phenomenon, being a different, more activated immune system due to parasite infections contributes to reduced COVID-19 outcome. We investigated this hypothesis in an endemic area in sub sub-saharan Africa. Methods: Ethiopian COVID-19 patients were enrolled and screened for intestinal parasites, between July 2020 and March 2021. The primary outcome was the proportion of patients with severe COVID-19. SARS-CoV-2 infection was confirmed by RT-PCR on samples obtained from nasopharyngeal swabs, while direct microscopic examination, modified Ritchie concentration, and Kato-Katz methods were used to identify parasites and ova from a fresh stool sample. Ordinal logistic regression models were used to estimate the association between parasite infection and COVID-19 severity. Models were adjusted for sex, age, residence, education level, occupation, body mass index, and comorbidities. Data were analyzed using STATA version 14. P-value <0.05 was considered statistically significant. Results: A total of 751 SARS-CoV-2 infected patients were enrolled, of whom 284 (37•8%) had an intestinal parasitic infection. Only 27/255 (10•6%) severe COVID-19 patients were co-infected with intestinal parasites, while 257/496 (51•8%) non-severe COVID-19 patients appeared parasite positive (p<0.0001). Patients co-infected with parasites had lower odds of developing severe COVID-19, with an adjusted odds ratio (AOR) of 0•14 (95% CI 0•09–0•24; p<0•0001) for all parasites, AOR 0•20 ([95% CI 0•11–0•38]; p<0•0001) for protozoa, and AOR 0•13 ([95% CI 0•07–0•26]; p<0•0001) for helminths. When stratified by species, co-infection with Entamoeba spp., Hymenolopis nana, and Schistosoma mansoni implied a lower probability of developing severe COVID-19. There were 11 deaths (1•5%), and all were among patients without parasites (p=0•009). Conclusions: Parasite co-infection is associated with a reduced risk of severe COVID-19 in African patients. Parasite-driven immunomodulatory responses may mute hyper-inflammation associated with severe COVID-19.

Keywords: COVID-19, SARS-COV-2, intestinal parasite, RT-PCR, co-infection

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Authors: Emmanuel Abayomi Rotimi

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Context: Rabbits production plays important role in increasing animal protein supply in Nigeria. Rabbit production provides a cheap, affordable, and healthy source of meat. The growth of animals involves an increase in body weight, which can change the conformation of various parts of the body. Live weight and linear measurements are indicators of growth rate in rabbits and other farm animals. Aims: This study aimed to define the body dimensions of New Zealand rabbits and also to investigate the morphometric traits variables that contribute to body conformation by the use of principal component analysis (PCA). Methods: Data were obtained from 80 New Zealand rabbits (40 bucks and 40 does) raised in Livestock Teaching and Research Farm, Federal University Dutsinma. Data were taken on body weight (BWT), body length (BL), ear length (EL), tail length (TL), heart girth (HG) and abdominal circumference (AC). Data collected were subjected to multivariate analysis using SPSS 20.0 statistical package. Key results: The descriptive statistics showed that the mean BWT, BL, EL, TL, HG, and AC were 0.91kg, 27.34cm, 10.24cm, 8.35cm, 19.55cm and 21.30cm respectively. Sex showed significant (P<0.05) effect on all the variables examined, with higher values recorded for does. The phenotypic correlation coefficient values (r) between the morphometric traits were all positive and ranged from r = 0.406 (between EL and BL) to r = 0.909 (between AC and HG). HG is the most correlated with BWT (r = 0.786). The principal component analysis with variance maximizing orthogonal rotation was used to extract the components. Two principal components (PCs) from the factor analysis of morphometric traits explained about 80.42% of the total variance. PC1 accounted for 64.46% while PC2 accounted for 15.97% of the total variances. Three variables, representing body conformation, loaded highest in PC1. PC1 had the highest contribution (64.46%) to the total variance, and it is regarded as body conformation traits. Conclusions: This component could be used as selection criteria for improving body weight of rabbits.

Keywords: conformation, multicollinearity, multivariate, rabbits and principal component analysis

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Authors: Melkamu A., Woldu B., Sitotaw C., Seyoum M., Aynalem M.

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Background: Liver disease is any condition that affects the liver cells and their function. It is directly linked to coagulation disorders since most coagulation factors are produced by the liver. Therefore, this study aimed to assess the magnitude and associated factors of coagulation abnormalities among liver disease patients. Methods: A cross-sectional study was conducted from August to October 2022 among 307 consecutively selected study participants at the University of Gondar Comprehensive Specialized Hospital. Sociodemographic and clinical data were collected using a structured questionnaire and data extraction sheet, respectively. About 2.7 mL of venous blood was collected and analyzed by the Genrui CA51 coagulation analyzer. Data was entered into Epi-data and exported to STATA version 14 software for analysis. The finding was described in terms of frequencies and proportions. Factors associated with coagulation abnormalities were analyzed by bivariable and multivariable logistic regression. Result: In this study, a total of 307 study participants were included. Of them, the magnitude of prolonged Prothrombin Time (PT) and Activated Partial Thromboplastin Time (APTT) were 68.08% and 63.51%, respectively. The presence of anemia (AOR = 2.97, 95% CI: 1.26, 7.03), a lack of a vegetable feeding habit (AOR = 2.98, 95% CI: 1.42, 6.24), no history of blood transfusion (AOR = 3.72, 95% CI: 1.78, 7.78), and lack of physical exercise (AOR = 3.23, 95% CI: 1.60, 6.52) were significantly associated with prolonged PT. While the presence of anaemia (AOR = 3.02; 95% CI: 1.34, 6.76), lack of vegetable feeding habit (AOR = 2.64; 95% CI: 1.34, 5.20), no history of blood transfusion (AOR = 2.28; 95% CI: 1.09, 4.79), and a lack of physical exercise (AOR = 2.35; 95% CI: 1.16, 4.78) were significantly associated with abnormal APTT. Conclusion: Patients with liver disease had substantial coagulation problems. Being anemic, having a transfusion history, lack of physical activity, and lack of vegetables showed significant association with coagulopathy. Therefore, early detection and management of coagulation abnormalities in liver disease patients are critical.

Keywords: coagulation, liver disease, PT, Aptt

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Authors: Yibeltal T. Bayou, Yohana S. Mashalla, Gloria Thupayagale-Tshweneagae

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Background: Maternal mortality has been shown to be lower in urban areas than in rural areas. However, disparities for the fast-growing population of urban poor who struggle as much their rural counterparts to access quality healthcare are masked by the urban averages. The aim of this paper is to report on the findings of antenatal adequacy among slum residents in Addis Ababa, Ethiopia. Methods and Materials: A quantitative and cross-sectional community-based study design was employed. A stratified two-stage cluster sampling technique was used to determine the sample and data was collected using structured questionnaire administered to 837 women aged 15-49 years. Binary logistic regression models were employed to identify predictors of adequacy of antenatal care. Results: The majority of slum residents did not have adequate antenatal care services i.e., only 50.7%, 19.3% and 10.2% of the slum resident women initiated early antenatal care, received adequate antenatal care service contents and had overall adequate antenatal care services. Pregnancy intention, educational status and place of ANC visits were important determinant factors for adequacy of ANC in the study area. Women with secondary and above educational status were 2.9 times more likely to have overall adequate care compared to those with no formal education. Similarly, women whose last pregnancy was intended and clients of private healthcare facilities were 1.8 and 2.8 times more likely to have overall adequate antenatal care compared to those whose last pregnancy was unintended and clients of public healthcare facilities respectively. Conclusion: In order to improve ANC adequacy in the study area, the policymaking, planning, and implementation processes should focus on the poor adequacy of ANC among the disadvantaged groups in particular and the slum residents in general.

Keywords: Addis Ababa, adequacy of antenatal care, slum residents, maternal mortality

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Authors: Yildiz Stella Dak, Jale Tezcan

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Ground motion models that relate a strong motion parameter of interest to a set of predictive seismological variables describing the earthquake source, the propagation path of the seismic wave, and the local site conditions constitute a critical component of seismic hazard analyses. When a sufficient number of strong motion records are available, ground motion relations are developed using statistical analysis of the recorded ground motion data. In regions lacking a sufficient number of recordings, a synthetic database is developed using stochastic, theoretical or hybrid approaches. Regardless of the manner the database was developed, ground motion relations are developed using regression analysis. Development of a ground motion relation is a challenging process which inevitably requires the modeler to make subjective decisions regarding the inclusion criteria of the recordings, the functional form of the model and the set of seismological variables to be included in the model. Because these decisions are critically important to the validity and the applicability of the model, there is a continuous interest on procedures that will facilitate the development of ground motion models. This paper proposes the use of the Least Absolute Shrinkage and Selection Operator (LASSO) in selecting the set predictive seismological variables to be used in developing a ground motion relation. The LASSO can be described as a penalized regression technique with a built-in capability of variable selection. Similar to the ridge regression, the LASSO is based on the idea of shrinking the regression coefficients to reduce the variance of the model. Unlike ridge regression, where the coefficients are shrunk but never set equal to zero, the LASSO sets some of the coefficients exactly to zero, effectively performing variable selection. Given a set of candidate input variables and the output variable of interest, LASSO allows ranking the input variables in terms of their relative importance, thereby facilitating the selection of the set of variables to be included in the model. Because the risk of overfitting increases as the ratio of the number of predictors to the number of recordings increases, selection of a compact set of variables is important in cases where a small number of recordings are available. In addition, identification of a small set of variables can improve the interpretability of the resulting model, especially when there is a large number of candidate predictors. A practical application of the proposed approach is presented, using more than 600 recordings from the National Geospatial-Intelligence Agency (NGA) database, where the effect of a set of seismological predictors on the 5% damped maximum direction spectral acceleration is investigated. The set of candidate predictors considered are Magnitude, Rrup, Vs30. Using LASSO, the relative importance of the candidate predictors has been ranked. Regression models with increasing levels of complexity were constructed using one, two, three, and four best predictors, and the models’ ability to explain the observed variance in the target variable have been compared. The bias-variance trade-off in the context of model selection is discussed.

Keywords: ground motion modeling, least absolute shrinkage and selection operator, penalized regression, variable selection

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Authors: Kiurski S. Jelena, Kecić S. Vesna, Aksentijević M. Snežana

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Samples of tap and wastewater were collected in three offset printing facilities in Novi Sad, Serbia. Ten physicochemical parameters were analyzed within all collected samples: pH, conductivity, m - alkalinity, p - alkalinity, acidity, carbonate concentration, hydrogen carbonate concentration, active oxygen content, chloride concentration and total alkali content. All measurements were conducted using the standard analytical and instrumental methods. Comparing the obtained results for tap water and wastewater, a clear quality difference was noticeable, since all physicochemical parameters were significantly higher within wastewater samples. The study also involves the application of simple linear regression analysis on the obtained dataset. By using software package ORIGIN 5 the pH value was mutually correlated with other physicochemical parameters. Based on the obtained values of Pearson coefficient of determination a strong positive correlation between chloride concentration and pH (r = -0.943), as well as between acidity and pH (r = -0.855) was determined. In addition, statistically significant difference was obtained only between acidity and chloride concentration with pH values, since the values of parameter F (247.634 and 182.536) were higher than F_critical (5.59). In this way, results of statistical analysis highlighted the most influential parameter of water contamination in offset printing, in the form of acidity and chloride concentration. The results showed that variable dependence could be represented by the general regression model: y = a₀ + a₁x+ k, which further resulted with matching graphic regressions.

Keywords: pollution, printing industry, simple linear regression analysis, wastewater

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Authors: Parvin Mirmiran, Zahra Bahadoran, Sahar Mirzae, Fereidoun Azizi

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Background and aim: Lifestyle factors, especially dietary intakes play an important role in metabolism of lipids and lipoproteins. In this study, we assessed the association between dietary factors and 3-year changes of serum triglycerides (TG), HDL-C and the atherogenic index of plasma among Iranian adults. This longitudinal study was conducted on 1938 subjects, aged 19-70 years, who participated in the Tehran Lipid and Glucose Study. Demographics, anthropometrics and biochemical measurements including serum TG were assessed at baseline (2006-2008) and after a 3-year follow-up (2009-2011). Dietary data were collected by using a 168-food item, validated semi-quantitative food frequency questionnaire at baseline. The risk of hypertriglyceridemia in the quartiles of dietary factors was evaluated using logistic regression models with adjustment for age, gender, body mass index, smoking, physical activity and energy intakes. Results: Mean age of the participants at baseline was 41.0±13.0 y. Mean TG and HDL-C at baseline was 143±86 and 42.2±10.0 mg/dl, respectively. Three-year change of serum TG were inversely related energy intake from phytochemical rich foods, whole grains, and legumes (P<0.05). Higher intakes compared to lower ones of dietary fiber and phytochemical-rich foods had similar impact on decreased risk of hyper-triglyceridemia (OR=0.58, 95% CI=0.34-1.00). Higher- compared to lower-dietary sodium to potassium ratios (Na/K ratio) increased the risk of hypertriglyceridemia by 63% (OR=0.1.63, 95% CI= 0.34-1.00). Conclusion: Findings showed that higher intakes of fiber and phytochemical rich foods especially whole grain and legumes could have protective effects against lipid disorders; in contrast higher sodium to potassium ratio had undesirable effect on triglycerides.

Keywords: lipid disorders, hypertriglyceridemia, diet, food science

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Authors: Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu, Costel Anton

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Natural sciences provide a wide range of experimental data whose related problems require study and modeling beyond the capabilities of conventional methodologies. Such problems have solution spaces whose complexity and high dimensionality require correspondingly complex regression methods for proper characterization. In this context, we propose an optimization method which consists in a hybrid dual optimizer setup: a global optimizer based on a modified variant of the popular Imperialist Competitive Algorithm (ICA), and a local optimizer based on a gradient descent approach. The ICA is modified such that intermediate solution populations are more quickly and efficiently pruned of low-fitness individuals by appropriately altering the assimilation, revolution and competition phases, which, combined with an initialization strategy based on low-discrepancy sampling, allows for a more effective exploration of the corresponding solution space. Subsequently, gradient-based optimization is used locally to seek the optimal solution in the neighborhoods of the solutions found through the modified ICA. We use this combined approach to find the optimal configuration and weights of a fully-connected neural network, resulting in regression models used to characterize the process of obtained bricks using silicon-based materials. Installations in the raw ceramics industry, i.e., bricks, are characterized by significant energy consumption and large quantities of emissions. Thus, the purpose of our approach is to determine by simulation the working conditions, including the manufacturing mix recipe with the addition of different materials, to minimize the emissions represented by CO and CH4. Our approach determines regression models which perform significantly better than those found using the traditional ICA for the aforementioned problem, resulting in better convergence and a substantially lower error.

Keywords: optimization, biologically inspired algorithm, regression models, bricks, emissions

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Authors: Kehinde Peter Oyeduntan, Kayode Oshinubi

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The west African ports have been experiencing large inflow and outflow of containerized cargo in the last decades, and this has created a quest amongst the countries to attain the status of hub port for the sub-region. This study analyzed the relationship between the container throughput and Gross Domestic Products (GDP) of nine west African countries, using Simple Linear Regression (SLR), Polynomial Regression Model (PRM) and Support Vector Machines (SVM) with a time series of 20 years. The results showed that there exists a high correlation between the GDP and container throughput. The model also predicted the container throughput in west Africa for the next 20 years. The findings and recommendations presented in this research will guide policy makers and help improve the management of container ports and terminals in west Africa, thereby boosting the economy.

Keywords: container, ports, terminals, throughput

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Authors: Jian-Heng Wu, Bor-Shen Lin

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The temperature-salinity relationship is one of the most important characteristics used for identifying water masses in marine research. Temperature-salinity characteristics, however, may change dynamically with respect to the geographic location and is quite sensitive to the depth at the same location. When depth is taken into consideration, however, it is not easy to compare the characteristics of different water masses efficiently for a wide range of areas of the ocean. In this paper, the Gaussian mixture model was proposed to analyze the temperature-salinity-depth characteristics of water masses, based on which comparison between water masses may be conducted. Gaussian mixture model could model the distribution of a random vector and is formulated as the weighting sum for a set of multivariate normal distributions. The temperature-salinity-depth data for different locations are first used to train a set of Gaussian mixture models individually. The distance between two Gaussian mixture models can then be defined as the weighting sum of pairwise Bhattacharyya distances among the Gaussian distributions. Consequently, the distance between two water masses may be measured fast, which allows the automatic and efficient comparison of the water masses for a wide range area. The proposed approach not only can approximate the distribution of temperature, salinity, and depth directly without the prior knowledge for assuming the regression family, but may restrict the complexity by controlling the number of mixtures when the amounts of samples are unevenly distributed. In addition, it is critical for knowledge discovery in marine research to represent, manage and share the temperature-salinity-depth characteristics flexibly and responsively. The proposed approach has been applied to a real-time visualization system of ocean data, which may facilitate the comparison of water masses by aggregating the data without degrading the discriminating capabilities. This system provides an interface for querying geographic locations with similar temperature-salinity-depth characteristics interactively and for tracking specific patterns of water masses, such as the Kuroshio near Taiwan or those in the South China Sea.

Keywords: water mass, Gaussian mixture model, data visualization, system framework

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Authors: Uraib Sharaha, Ahmad Salman, Eladio Rodriguez-Diaz, Elad Shufan, Klaris Riesenberg, Irving J. Bigio, Mahmoud Huleihel

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Antimicrobial drugs have played an indispensable role in controlling illness and death associated with infectious diseases in animals and humans. However, the increasing resistance of bacteria to a broad spectrum of commonly used antibiotics has become a global healthcare problem. Many antibiotics had lost their effectiveness since the beginning of the antibiotic era because many bacteria have adapted defenses against these antibiotics. Rapid determination of antimicrobial susceptibility of a clinical isolate is often crucial for the optimal antimicrobial therapy of infected patients and in many cases can save lives. The conventional methods for susceptibility testing require the isolation of the pathogen from a clinical specimen by culturing on the appropriate media (this culturing stage lasts 24 h-first culturing). Then, chosen colonies are grown on media containing antibiotic(s), using micro-diffusion discs (second culturing time is also 24 h) in order to determine its bacterial susceptibility. Other methods, genotyping methods, E-test and automated methods were also developed for testing antimicrobial susceptibility. Most of these methods are expensive and time-consuming. Fourier transform infrared (FTIR) microscopy is rapid, safe, effective and low cost method that was widely and successfully used in different studies for the identification of various biological samples including bacteria; nonetheless, its true potential in routine clinical diagnosis has not yet been established. The new modern infrared (IR) spectrometers with high spectral resolution enable measuring unprecedented biochemical information from cells at the molecular level. Moreover, the development of new bioinformatics analyses combined with IR spectroscopy becomes a powerful technique, which enables the detection of structural changes associated with resistivity. The main goal of this study is to evaluate the potential of the FTIR microscopy in tandem with machine learning algorithms for rapid and reliable identification of bacterial susceptibility to antibiotics in time span of few minutes. The UTI E.coli bacterial samples, which were identified at the species level by MALDI-TOF and examined for their susceptibility by the routine assay (micro-diffusion discs), are obtained from the bacteriology laboratories in Soroka University Medical Center (SUMC). These samples were examined by FTIR microscopy and analyzed by advanced statistical methods. Our results, based on 700 E.coli samples, were promising and showed that by using infrared spectroscopic technique together with multivariate analysis, it is possible to classify the tested bacteria into sensitive and resistant with success rate higher than 90% for eight different antibiotics. Based on these preliminary results, it is worthwhile to continue developing the FTIR microscopy technique as a rapid and reliable method for identification antibiotic susceptibility.

Keywords: antibiotics, E.coli, FTIR, multivariate analysis, susceptibility, UTI

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Authors: Alongkorn Pekalee, Rossarin Gray

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Various determinants associated with older health include socio-demographic factors and health-promoting behaviors but lack in scholars recommended what factors associated with health status in specific sub-groups of older adults. The current study aims to explore the health-promoting behaviors and to examine and compare the associations of these factors with self-rated health status among three older age cohorts in Thai traditional context. Methods: This study is based on the Survey of Older Persons in Thailand (SOPT), in 2017, conducted by the National Statistical Office (NSO) of Thailand. Participants were classified into three groups by using the Thai contextual recommendation: youngest-old cohort (60-69), old-old cohort (70-79) and oldest old cohort (80 or older). Health promoting behaviors are the behaviors which associated with the health status of older adults include alcohol consumption, smoking, diet, and physical activity. Health status was defined as a subjective measurement by using self-rated health, a simple measure of general health. The socio-demographic factors, health-promoting behaviors, and health status were explained and summarized by descriptive statistics. The binary logistic regression was performed to analyze the data and evaluate the associations between independent and dependent variables. Results: Increase of age contributes to a higher proportion of health-promoting behaviors. All variables were associated with self-reported health status as good health among three older age cohorts statistically significant (p-value = 0.000). However, the influence of income sufficiency on health status is more notable, especially in older adults who aged 60-69 and 70-79. The influence of dietary and physical activity on health status became greater as age increased. Conclusion: the results suggest that income sufficiency should be noted in a plan to promote healthy aging, and co-residence should be more concerned especially in the oldest old cohort. Moreover, the interventions or policies to promote older health behaviors like diet and physical activity should be emphasized in the oldest old cohort more than others.

Keywords: health-promoting behaviors, older adults, self- rated health, Thailand

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Authors: Elucir Gir, Laelson Rochelle Milanês Sousa, Renata Karina Reis, Soraia Assad Nasbine Rabeh, Mayra Gonçalves Menegueti, Ana Cristina de Oliveira e Silva, Sheila Araújo Teles

Abstract:

Context and significance: Nursing team professionals faced challenges in combating the COVID-19 pandemic around the world. They were subjected to exhausting workloads and prolonged use of Personal Protective Equipment. Using N95 masks for long periods of time can cause skin changes. In this context, health professionals who worked on the front lines of fighting the pandemic were more exposed to possible physical and psychological changes. Objective: The aim of the study was to analyze the factors associated with skin lesions resulting from the use of N95 masks among nursing team professionals. Method: The study was carried out in all regions of Brazil from October to December 2020, with professionals from the nursing team who worked in health care during the COVID-19 pandemic. Participants were recruited via social media, and information was collected electronically and stored on the Survey Monkey platform. Descriptive statistics were used to characterize the sample, association tests (Chi-square), with a statistical significance level of p < 0.05. Factors associated with skin lesions resulting from the use of an N95 mask were determined by Binary Logistic Regression, with a significance level of 5% (α = 0.05). Results: 8,405 nursing professionals participated in the study, 5,492 nurses (65.3%), 2,747 nursing technicians (32.7%), and 7,084 females (84.3%). Female nursing team professionals were 1.4 times more likely to develop skin lesions due to the use of N95 masks when compared to males (OR 1.4 [CI95% 1.22 – 1.59] p < 0.001). The following protective factors were identified: nursing technician (ORA 0.608 [CI95% 0.43 – 0.86] p = 0.005) and not having provided assistance in field hospitals for COVID-19 (0.73 [CI95% 0.65-0.81] p<0.000). Conclusion: It was concluded that female nursing team professionals were more likely to have skin changes related to the use of N95 masks. The need for intervention studies is emphasized in order to explore measures to prevent these types of injuries. Descritores: Nursing professionals; COVID-19; SARS-CoV-2; Brazil.

Keywords: nursing professionals, COVID-19, SARS-CoV-2, Brazil

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Authors: Abdul Haris Setiawan

Abstract:

Teachers empowerment is one of the important factors considered to contribute significantly to the achievement of the national education goals. This study was conducted to determine the influence on the vocational teachers empowerment toward the performance of the vocational high schools based on the Education National Standards of Indonesia. The population of the study was all vocational teachers at the State Vocational High schools in Surakarta, Central Java Province, Indonesia. The sampling technique used proportional random sampling technique. This study used a quantitative descriptive statistical analysis techniques. The data was collected using questionnaires. The data has been collected and then tested using analysis requirements test. Having tested using the requirements analysis and then the data processed using regression analysis between the independent and dependent variables to determine the effect and the regression equation. The results of the study found that the level of vocational high schools’ performance based on the Education National Standards of Indonesia was 74.29%, including in the high category; the level of vocational teachers empowerment was 76.20%, including in the high category; there was a positive influence of vocational teachers empowerment toward the vocational high schools’ performance based on the Education National Standards of Indonesia with a correlation coefficient of 0,886, and a contribution of 78.50% with the regression equation Y = 79.431 +0.534 X.

Keywords: vocational teachers, empowerment, vocational high school, the education national standards

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Authors: İsmail İnce

Abstract:

The aim of this study is to determine index and mechanical properties of pyroclastic rock in a practical way by means of electrical resistivity method. For this purpose, electrical resistivity, uniaxial compressive strength, point load strength, P-wave velocity, density and porosity values of 10 different pyroclastic rocks were measured in the laboratory. A simple regression analysis was made among the index-mechanical properties of the samples compatible with electrical resistivity values. A strong exponentially relation was found between index-mechanical properties and electrical resistivity values. The electrical resistivity method can be used to assess the engineering properties of the rock from which it is difficult to obtain regular shaped samples as a non-destructive method.

Keywords: electrical resistivity, index-mechanical properties, pyroclastic rocks, regression analysis

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Authors: Emmanuel U. Ohaegbulem, Felix N. Nwobi

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Alternative and simple computational arrangements in carrying out multivariate profile analysis when more than two groups (populations) are involved are presented. These arrangements have been demonstrated to not only yield equivalent results for the test statistics (the Wilks lambdas), but they have less computational efforts relative to other arrangements so far presented in the literature; in addition to being quite simple and easy to apply.

Keywords: coincident profiles, g-group profile analysis, level profiles, parallel profiles, repeated measures MANOVA

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Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

Abstract:

Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

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Authors: Bishnu Prasad Dulal, Sushil Chandra Baral, Radheshyam Bhattarai, Meera Tandan

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Background: Non-use of contraceptives is a leading cause of unintended pregnancy. This study was done to explore the potential predictors of contraceptive used by young women, and the findings can inform policy makers to design the program to reduce unintended pregnancy for younger women who have a longer time of fecundity. Methodology: A nationally representative cross-sectional household survey was conducted by Health Research and Social Development Forum in 2012. Total 2259 currently married young women (15-24 years) were selected for the analysis out of 8578 women of reproductive age interviewed from the total 10260 households using systematic sampling. Binary logistic regression was used to identify factors associated with the use of modern contraceptive methods. Findings: The prevalence of modern contraceptive methods among young women was 25.2 %. Use of contraceptives was significantly associated with age at first marriage <15 year of age (OR:1.95) and ever delivered (OR: 1.8). Muslim women were significantly less likely to use contraceptives. Development region, wealth quintile, and awareness of abortion site were also statistically associated factors to use of contraceptives. Conclusion: The prevalence of contraceptives uses among young married women (25.2%) was lower than national prevalence (43%) of contraceptives use among married women of reproductive age. Our analysis focused on examining the association between women’s characteristics-related factors and use and nonuse of modern contraceptives. Awareness of safe abortion site is significantly associated while level of education was not. It is an interesting finding but difficult to interpret which needs further analysis on the basis of education. Maybe due to the underlying socio-religious practice of Muslim people, they had lower use of contraceptives. Programmers and policy makers could better help young women by increasing intervention activities to have a regular use of contraceptive-covering poor, Dalit and Muslim, and low aged women in order to reduce unintended pregnancy.

Keywords: unintended pregnancy, contraceptive, young women, Nepal

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Authors: Naushad Mamode Khan

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The Com-Poisson (CMP) model is one of the most popular discrete generalized linear models (GLMS) that handles both equi-, over- and under-dispersed data. In longitudinal context, an integer-valued autoregressive (INAR(1)) process that incorporates covariate specification has been developed to model longitudinal CMP counts. However, the joint likelihood CMP function is difficult to specify and thus restricts the likelihood based estimating methodology. The joint generalized quasilikelihood approach (GQL-I) was instead considered but is rather computationally intensive and may not even estimate the regression effects due to a complex and frequently ill conditioned covariance structure. This paper proposes a new GQL approach for estimating the regression parameters (GQLIII) that are based on a single score vector representation. The performance of GQL-III is compared with GQL-I and separate marginal GQLs (GQL-II) through some simulation experiments and is proved to yield equally efficient estimates as GQL-I and is far more computationally stable.

Keywords: longitudinal, com-Poisson, ill-conditioned, INAR(1), GLMS, GQL

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Authors: Juan C. Reyes, Linnette Rodríguez, Héctor Villanueva, Jorge Vázquez, Ivonne Rivera

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On July 2020, a private non-profit community health center (HealthProMed) that serves people without a medical insurance plan or with limited resources in one of the most populated areas in San Juan, Puerto Rico, implemented a COVID-19 case investigation and contact-tracing surveillance system. Nursing personnel at the health center completed a computerized case investigation form that was translated, adapted, and modified from CDC’s Patient Under Investigation (PUI) Form. Between July 13, 2020, and March 17, 2022, a total of 9,233 SARS-CoV-2 tests were conducted at the health center, 16.9% of which were classified as confirmed cases (positive molecular test) and 27.7% as probable cases (positive serologic test). Most of the confirmed cases were females (60.0%), under 20 years old (29.1%), and living in their homes (59.1%). In the 14 days before the onset of symptoms, 26.3% of confirmed cases reported going to the supermarket, 22.4% had contact with a known COVID-19 case, and 20.7% went to work. The symptoms most commonly reported were sore throat (33.4%), runny nose (33.3%), cough (24.9%), and headache (23.2%). The most common preexisting medical conditions among confirmed cases were hypertension (19.3%), chronic lung disease including asthma, emphysema, COPD (13.3%), and diabetes mellitus (12.8). Multiple logistic regression analysis revealed that patients who used alcohol frequently during the last two weeks (OR=1.43; 95%CI: 1.15-1.77), those who were in contact with a positive case (OR=1.58; 95%CI: 1.33-1.88) and those who were obese (OR=1.82; 95%CI: 1.24-2.69) were significantly more likely to be a confirmed case after controlling for sociodemographic variables. Implementing a case investigation and contact-tracing component at community health centers can be of great value in the prevention and control of COVID-19 at the community level and could be used in future outbreaks.

Keywords: community health center, Puerto Rico, risk factors, SARS-CoV-2

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Authors: Margaret Elaine J. Villamayor, Lobert A. Padua, Neil S. Bacaltos, Virgilio P. Bañez

Abstract:

Significance: This study aimed to determine the prevalence of Hepatobiliary Tuberculosis (HBTB) with biliary obstruction and to compare the outcomes of ERCP versus PTBD in these patients. Methodology: This is a cross-sectional study involving patients from PGH who underwent biliary drainage from HBTB from January 2009 to June 2014. HBTB was defined as having evidence of TB (culture, smear, PCR, histology) or clinical diagnosis with the triad of jaundice, fever, and calcifications on imaging with other causes of jaundice excluded. The primary outcome was successful drainage and secondary outcomes were mean hospital stay and complications. Simple logistic regression was used to identify factors associated with success of drainage, z-test for two proportions to compare outcomes of ERCP versus PTBD and t-test to compare mean hospital stay post-procedure. Results: There were 441 patients who underwent ERCP and PTBD, 19 fulfilled the inclusion criteria. 11 underwent ERCP while 8 had PTBD. There were more successful cases in PTBD versus ERCP but this was not statistically significant (p-value 0.3615). Factors such as age, gender, location and nature of obstruction, vices, coexisting pulmonary or other extrapulmonary TB and presence of portal hypertension did not affect success rates in these patients. The PTBD group had longer mean hospital stay but this was not significant (p-value 0.1880). There were no complications reported in both groups. Conclusion: HBTB comprises 4.3% of the patients undergoing biliary drainage in PGH. Both ERCP and PTBD are equally safe and effective in the management of biliary obstruction from HBTB.

Keywords: cross-sectional, hepatobiliary tuberculosis, obstructive jaundice, endoscopic retrograde cholangiopancreatography, percutaneous transhepatic biliary drainage

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Authors: Yung-Chung Chuang

Abstract:

The cultural layers of archaeological sites are mainly affected by surface land use, land cover, and root system of surface vegetation. For this reason, continuous monitoring of land use and land cover change is important for archaeological sites protection and management. However, in actual operation, on-site investigation and orthogonal photograph interpretation require a lot of time and manpower. For this reason, it is necessary to perform a good alternative for surface vegetation survey in an automated or semi-automated manner. In this study, we applied semi-automatic digital aerial survey technology and canopy characters classification with very high-resolution aerial photographs for surface vegetation interpretation of archaeological sites. The main idea is based on different landscape or forest type can easily be distinguished with canopy characters (e.g., specific texture distribution, shadow effects and gap characters) extracted by semi-automatic image classification. A novel methodology to classify the shape of canopy characters using landscape indices and multivariate statistics was also proposed. Non-hierarchical cluster analysis was used to assess the optimal number of canopy character clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy character classification (seven categories). Therefore, people could easily predict the forest type and vegetation land cover by corresponding to the specific canopy character category. The results showed that the semi-automatic classification could effectively extract the canopy characters of forest and vegetation land cover. As for forest type and vegetation type prediction, the average prediction accuracy reached 80.3%~91.7% with different sizes of test frame. It represented this technology is useful for archaeological site survey, and can improve the classification efficiency and data update rate.

Keywords: digital aerial survey, canopy characters classification, archaeological sites, multivariate statistics

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Authors: Seyed Sadegh Naseralavi, Najmeh Bemani

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In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.

Keywords: adaptive neuro fuzzy inference system, anticipate method, artificial neural network, concrete design code, multi-variable regression

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Authors: Aleema Rahman

Abstract:

Introduction: This study aims to estimate the prevalence of long-term otitis media with effusion (OME) and hearing loss in a prospective longitudinal cohort studyand to study the relationship between the condition and educational and psychosocial outcomes. Methods: Analysis of data from the Avon Longitudinal Study of Parents and Children (ALSPAC) will be undertaken. ALSPAC is a longitudinal birth cohort study carried out in the UK, which has collected detailed measures of hearing on ~7000 children from the age of seven. A descriptive analysis of the data will be undertaken to estimate the prevalence of OME and hearing loss (defined as having average hearing levels > 20dB and type B tympanogram) at 7, 9, 11, and 15 years as well as that of long-term OME and hearing loss. Logistic and linear regression analyses will be conducted to examine associations between long-term OME and hearing loss and educational outcomes (grades obtained from standardised national attainment tests) and psychosocial outcomes such as anxiety, social fears, and depression at ages 10-11 and 15-16 years. Results: Results will be presented in terms of the prevalence of OME and hearing loss in the population at each age. The prevalence of long-term OME and hearing loss, defined as having OME and hearing loss at two or more time points, will also be reported. Furthermore, any associations between long-term OME and hearing loss and the educational and psychosocial outcomes will be presented. Analyses will take into account demographic factors such as sex and social deprivation and relevant confounders, including socioeconomic status, ethnicity, and IQ. Discussion: Findings from this study will provide new epidemiological information on the prevalence of long-term OME and hearing loss. The research will provide new knowledge on the impact of OME for the small group of children who do not grow out of condition by age 7 but continue to have hearing loss and need clinical care through later childhood. The study could have clinical implications and may influence service delivery for this group of children.

Keywords: educational attainment, hearing loss, otitis media with effusion, psychosocial development

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