Search results for: least squares regression

Authors: Semachew M. Kassa, Africa M Geremew, Tezera F. Azmatch, Nandyala Darga Kumar

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Frequency ratio (FR) and analytical hierarchy process (AHP) methods are developed based on past landslide failure points to identify the landslide susceptibility mapping because landslides can seriously harm both the environment and society. However, it is still difficult to select the most efficient method and correctly identify the main driving factors for particular regions. In this study, we used fourteen landslide conditioning factors (LCFs) and five soft computing algorithms, including Random Forest (RF), Support Vector Machine (SVM), Logistic Regression (LR), Artificial Neural Network (ANN), and Naïve Bayes (NB), to predict the landslide susceptibility at 12.5 m spatial scale. The performance of the RF (F1-score: 0.88, AUC: 0.94), ANN (F1-score: 0.85, AUC: 0.92), and SVM (F1-score: 0.82, AUC: 0.86) methods was significantly better than the LR (F1-score: 0.75, AUC: 0.76) and NB (F1-score: 0.73, AUC: 0.75) method, according to the classification results based on inventory landslide points. The findings also showed that around 35% of the study region was made up of places with high and very high landslide risk (susceptibility greater than 0.5). The very high-risk locations were primarily found in the western and southeastern regions, and all five models showed good agreement and similar geographic distribution patterns in landslide susceptibility. The towns with the highest landslide risk include Amhara Saint Town's western part, the Northern part, and St. Gebreal Church villages, with mean susceptibility values greater than 0.5. However, rainfall, distance to road, and slope were typically among the top leading factors for most villages. The primary contributing factors to landslide vulnerability were slightly varied for the five models. Decision-makers and policy planners can use the information from our study to make informed decisions and establish policies. It also suggests that various places should take different safeguards to reduce or prevent serious damage from landslide events.

Keywords: artificial neural network, logistic regression, landslide susceptibility, naïve Bayes, random forest, support vector machine

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Authors: Harshit Vallecha, Prabha Bhola

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‘Energy for all’, is a global issue of concern for the past many years. Despite the number of technological advancements and innovations, significant numbers of people are living without access to electricity around the world. India, an emerging economy, tops the list of nations having the maximum number of residents living off the grid, thus raising global attention in past few years to provide clean and sustainable energy access solutions to all of its residents. It is evident from developed economies that centralized planning and electrification alone is not sufficient for meeting energy security. Implementation of off-grid and consumer-driven energy models like Decentralized Renewable Energy (DRE) systems have played a significant role in meeting the national energy demand in developed nations. Cases of DRE systems have been reported in developing countries like India for the past few years. This paper attempts to profile the status of DRE projects in the Indian context with their scope and relevance to ensure universal electrification. Diversified cases of DRE projects, particularly solar, biomass and micro hydro are identified in different Indian states. Critical factors affecting the sustainability of DRE projects are extracted with their interlinkages in the context of developers, beneficiaries and promoters involved in such projects. Socio-techno-economic indicators are identified through similar cases in the context of DRE projects. Exploratory factor analysis is performed to evaluate the critical sustainability factors followed by regression analysis to establish the relationship between the dependent and independent factors. The generated EFA-Regression model provides a basis to develop the sustainability and replicability framework for broader coverage of DRE projects in developing nations in order to attain the goal of universal electrification with least carbon emissions.

Keywords: climate change, decentralized generation, electricity access, renewable energy

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Authors: Vangmayee. V. Subban, Somashekara H. S, Shwetha Prabhu, Jayashree S. Bhat

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Introduction and Need: Phonological processing is critical in learning to read alphabetical and non-alphabetical languages. However, its role in learning to read Kannada an alphasyllabary is equivocal. The literature has focused on the developmental role of phonological awareness on reading. To the best of authors knowledge, the role of phonological memory and phonological naming has not been addressed in alphasyllabary Kannada language. Therefore, there is a need to evaluate the comprehensive role of the phonological processing skills in Kannada on word decoding skills during the early years of schooling. Aim and Objectives: The present study aimed to explore the phonological processing abilities and their role in learning to decode pseudowords in children learning to read the Kannada language during initial years of formal schooling between 5.6 to 8.6 years. Method: In this cross sectional study, 60 typically developing Kannada speaking children, 20 each from Grade I, Grade II, and Grade III between the age range of 5.6 to 6.6 years, 6.7 to 7.6 years and 7.7 to 8.6 years respectively were selected from Kannada medium schools. Phonological processing abilities were assessed using an assessment tool specifically developed to address the objectives of the present research. The assessment tool was content validated by subject experts and had good inter and intra-subject reliability. Phonological awareness was assessed at syllable level using syllable segmentation, blending, and syllable stripping at initial, medial and final position. Phonological memory was assessed using pseudoword repetition task and phonological naming was assessed using rapid automatized naming of objects. Both phonological awareneness and phonological memory measures were scored for the accuracy of the response, whereas Rapid Automatized Naming (RAN) was scored for total naming speed. Results: The mean scores comparison using one-way ANOVA revealed a significant difference (p ≤ 0.05) between the groups on all the measures of phonological awareness, pseudoword repetition, rapid automatized naming, and pseudoword reading. Subsequent post-hoc grade wise comparison using Bonferroni test revealed significant differences (p ≤ 0.05) between each of the grades for all the tasks except (p ≥ 0.05) for syllable blending, syllable stripping, and pseudoword repetition between Grade II and Grade III. The Pearson correlations revealed a highly significant positive correlation (p=0.000) between all the variables except phonological naming which had significant negative correlations. However, the correlation co-efficient was higher for phonological awareness measures compared to others. Hence, phonological awareness was chosen a first independent variable to enter in the hierarchical regression equation followed by rapid automatized naming and finally, pseudoword repetition. The regression analysis revealed syllable awareness as a single most significant predictor of pseudoword reading by explaining the unique variance of 74% and there was no significant change in R² when RAN and pseudoword repetition were added subsequently to the regression equation. Conclusion: Present study concluded that syllable awareness matures completely by Grade II, whereas the phonological memory and phonological naming continue to develop beyond Grade III. Amongst phonological processing skills, phonological awareness, especially syllable awareness is crucial for word decoding than phonological memory and naming during initial years of schooling.

Keywords: phonological awareness, phonological memory, phonological naming, phonological processing, pseudo-word decoding

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Authors: J.P. Henriques, E. R. Neto, G. Almeida, G. Ribeiro, J.V. Coutinho, A.B. Lugli

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Industry 4.0, or the Fourth Industrial Revolution, is transforming the relationship between people and machines. In this scenario, some technologies such as Cloud Computing, Internet of Things, Augmented Reality, Artificial Intelligence, Additive Manufacturing, among others, are making industries and devices increasingly intelligent. One of the most powerful technologies of this new revolution is the Digital Twin, which allows the virtualization of a real system or process. In this context, the present paper addresses the linear and nonlinear dynamic study of a didactic level plant using Digital Twin. In the first part of the work, the level plant is identified at a fixed point of operation, BY using the existing method of least squares means. The linearized model is embedded in a Digital Twin using Automation Studio® from Famous Technologies. Finally, in order to validate the usage of the Digital Twin in the linearized study of the plant, the dynamic response of the real system is compared to the Digital Twin. Furthermore, in order to develop the nonlinear model on a Digital Twin, the didactic level plant is identified by using the method proposed by Hammerstein. Different steps are applied to the plant, and from the Hammerstein algorithm, the nonlinear model is obtained for all operating ranges of the plant. As for the linear approach, the nonlinear model is embedded in the Digital Twin, and the dynamic response is compared to the real system in different points of operation. Finally, yet importantly, from the practical results obtained, one can conclude that the usage of Digital Twin to study the dynamic systems is extremely useful in the industrial environment, taking into account that it is possible to develop and tune controllers BY using the virtual model of the real systems.

Keywords: industry 4.0, digital twin, system identification, linear and nonlinear models

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Authors: Pallavi Gajjar, Vinayak Malhotra

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Rockets have been known to have played a predominant role in spacecraft propulsion. The quintessential aspect of combustion-related requirements of a rocket engine is the minimization of the surrounding risks/hazards. Over time, it has become imperative to understand the combustion rate variation in presence of external energy source(s). Rocket propulsion represents a special domain of chemical propulsion assisted by high speed flows in presence of acoustics and thermal source(s). Jet noise leads to a significant loss of resources and every year a huge amount of financial aid is spent to prevent it. External heat source(s) induce high possibility of fire risk/hazards which can sufficiently endanger the operation of a space vehicle. Appreciable work had been done with justifiable simplification and emphasis on the linear variation of external energy source(s), which yields good physical insight but does not cater to accurate predictions. Present work experimentally attempts to understand the correlation between inter-energy conversions with the non-linear placement of external energy source(s). The work is motivated by the need to have better fire safety and enhanced combustion. The specific objectives of the work are a) To interpret the related energy transfer for combustion in presence of alternate external energy source(s) viz., thermal and acoustic, b) To fundamentally understand the role of key controlling parameters viz., separation distance, the number of the source(s), selected configurations and their non-linear variation to resemble real-life cases. An experimental setup was prepared using incense sticks as potential fuel and paraffin wax candles as the external energy source(s). The acoustics was generated using frequency generator, and source(s) were placed at selected locations. Non-equidistant parametric experimentation was carried out, and the effects were noted on regression rate changes. The results are expected to be very helpful in offering a new perspective into futuristic rocket designs and safety.

Keywords: combustion, acoustic energy, external energy sources, regression rate

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Authors: Katja Siefken, Astrid Junge

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Background: Research indicates that physical activity (PA) protects us from developing mental disorders. The knowledge regarding optimal domain, intensity, type, context, and amount of PA promotion for the prevention of mental disorders is sparse and incoherent. The objective of this study is to determine the relationship between PA domains and mental well-being, and whether associations vary by domain, amount, context, intensity, and type of PA. Methods: 310 individuals (age: 25 yrs., SD 7; 73% female) completed a questionnaire on personal patterns of their PA behaviour (IPQA) and their mental health (Centre of Epidemiologic Studies Depression Scale (CES-D), Generalized Anxiety Disorder (GAD-7) scale, the subjective physical well-being (FEW-16)). Linear and multiple regression were used for analysis. Findings: Individuals who met the PA recommendation (N=269) reported higher scores on subjective physical well-being than those who did not meet the PA recommendations (N=41). Whilst vigorous intensity PA predicts subjective well-being (β = .122, p = .028), it also correlates with depression. The more vigorously physically active a person is, the higher the depression score (β = .127, p = .026). The strongest impact of PA on mental well-being can be seen in the transport domain. A positive linear correlation on subjective physical well-being (β =.175, p = .002), and a negative linear correlation for anxiety (β =-.142, p = .011) and depression (β = -.164, p = .004) was found. Multiple regression analysis indicates similar results: Time spent in active transport on the bicycle significantly lowers anxiety and depression scores and enhances subjective physical well-being. The more time a participant spends using the bicycle for transport, the lower the depression (β = -.143, p = .013) and anxiety scores (β = -.111,p = .050). Conclusions: Meeting the PA recommendations enhances subjective physical well-being. Active transport has a substantial impact on mental well-being. Findings have implications for policymakers, employers, public health experts and civil society. A stronger focus on the promotion and protection of health through active transport is recommended. Inter-sectoral exchange, outside the health sector, is required. Health systems must engage other sectors in adopting policies that maximize possible health gains.

Keywords: active transport, mental well-being, health promotion, psychological disorders

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Authors: Adebiyi Sunday Adeyanju, Kola Benson Ajeigbe, Fortune Ganda

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In the past three decades, there has been a notable increase in the number of firms delisting from the Johannesburg Stock Exchange (JSE) in South Africa. The recent increasing rate of delisting waves of corporate listed firms motivated this study. This study aims to explore the influence of institutional investor perceptions on the financial distress experienced by delisted firms within the South African market. The study further examined the impact of financial distress on the corporate performance of delisted firms. Using the data of delisted firms spanning from 2000 to 2023 and the FGLS (Feasible Generalized Least Squares) for the short run and PCSE (Panel-Corrected Standard Errors) for the long run effects of the relationship. The finding indicated that a decline in institutional investors’ perceptions was associated with the corporate financial distress of the delisted firms, particularly during the delisting year and the few years preceding the announcement of the delisting. This study addressed the importance of investor recognition in corporate financial distress and the delisting wave among listed firms- a finding supporting the stakeholder theory. This study is an insight for companies’ managements, investors, governments, policymakers, stockbrokers, lending institutions, bankers, the stock market, and other stakeholders in their various decision-making endeavours. Based on the above findings, it was recommended that corporate managements should improve their governance strategies that can help companies’ financial performances. Accountability and transparency through governance must also be improved upon with government support through the introduction of policies and strategies and enabling an easy environment that can help companies perform better.

Keywords: delisting wave, institutional investors, financial distress, corporate performance, investors’ perceptions

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Authors: Shaban Saad, Syed Ahmed, Suher Aburawi, Isabel Fong

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Ruta graveolens is a plant commonly found in north Africa and south Europe. It is reported that Ruta graveolens is used traditionally for epilepsy and some other illnesses. The acute and sub-acute effects of alcoholic extract residue were tested for possible anti-epileptic and skeletal muscle relaxation activity. The effect of extract on rat spontaneous motor activity (SMA) was also investigated using open filed. We previously proved the anti convulsant activity of the plant against pentylenetetrazol and electrically induced convulsions. Therefore in this study strychnine was used to induce convulsions in order to explore the mechanism of anti-convulsant activity of the plant. The skeletal muscle relaxation activity of Ruta graveolens was studied using pull-up and rod hanging tests in rats. At concentration of 5%w/v the extract protected mice against strychnine induced myoclonic jerks and death. The pull-up and rod hanging tests pointed to a skeletal muscle relaxant activity at higher concentrations. Ruta graveolens extract also significantly decreased the number of squares visited by rats in open field apparatus at all tested concentrations (3.5-20%w/v). However, the significant decrease in number of rearings was only noticed at concentrations of (15 and 20%w/v). The results indicate that Ruta graveolens contains compound(s) capable to inhibit convulsions, decrease SMA and/or diminish skeletal muscle tone in animal models. This data and the previously generated data together point to a general depression trend of CNS produced by Ruta graveolens.

Keywords: Ruta graveolens, open field, skeletal muscle relaxation

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Authors: Longxiang Guo, Haoyan Hao, Xueli Sheng, Hanjun Yu, Jingwei Yin

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In order to prevent target splitting and ensure the accuracy of fusion, system error registration is an important step in multi-static sonar fusion detection system. To eliminate the inherent system errors including distance error and angle error of each sonar in detection, this paper uses offline estimation method for error registration. Suppose several sonars from different platforms work together to detect a target. The target position detected by each sonar is based on each sonar’s own reference coordinate system. Based on the two-dimensional stereo projection method, this paper uses real-time quality control (RTQC) method and least squares (LS) method to estimate sensor biases. The RTQC method takes the average value of each sonar’s data as the observation value and the LS method makes the least square processing of each sonar’s data to get the observation value. In the underwater acoustic environment, matlab simulation is carried out and the simulation results show that both algorithms can estimate the distance and angle error of sonar system. The performance of the two algorithms is also compared through the root mean square error and the influence of measurement noise on registration accuracy is explored by simulation. The system error convergence of RTQC method is rapid, but the distribution of targets has a serious impact on its performance. LS method can not be affected by target distribution, but the increase of random noise will slow down the convergence rate. LS method is an improvement of RTQC method, which is widely used in two-dimensional registration. The improved method can be used for underwater multi-target detection registration.

Keywords: data fusion, multi-static sonar detection, offline estimation, sensor registration problem

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Authors: Tchapo Tchaga Sophia, Cai Chun

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This study measures the efficiency level of corporate governance to improve the quality level of value relevance in the resolution of market value efficiency increase issues, transparency problems, risk frauds, agency problems, investors' confidence, and decision-making issues using IFRS and Corporate Governance Acts (CGA). The final sample of this study contains 3660 firms from ten countries' stock markets from 2010 to 2020. Based on the efficiency market theory and the positive accounting theory, this paper uses multiple econometrical methods (DID method, multivariate and univariate regression methods) and models (Ohlson model and compliance index model) regression to see the incidence results of corporate governance mechanisms on the value relevance level under the influence of IFRS and corporate governance regulations act framework in Africa's stock exchanges for non-financial firms. The results on value relevance show that the corporate governance system, strengthened by the adoption of IFRS and enforcement of new corporate governance regulations, produces better financial statement information when its compliance level is high. And that is both value-relevant and comparable to results in more developed markets. Similar positive and significant results were obtained when predicting future book value per share and earnings per share through the determination of stock price and stock return. The findings of this study have important implications for regulators, academics, investors, and other users regarding the effects of IFRS and the Corporate Governance Act (CGA) on the relationship between corporate governance and accounting information relevance in the African stock market. The contributions of this paper are also based on the uniqueness of the data used in this study. The unique data is from Africa, and not all existing findings provide evidence for Africa and of the DID method used to examine the relationship between corporate governance and value relevance on African stock exchanges.

Keywords: corporate governance value, market efficiency value, value relevance, African stock market, stock return-stock price

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Authors: Laraib Niaz

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This paper analyzes the ways in which education and economic deprivation are linked to terrorism in Pakistan using data for terrorist incidents from the Global Terrorism Database (GTD). It employs the technique of negative binomial regression for the years between 1990 and 2013, presenting evidence for a positive association between education and terrorism. Conversely, a negative correlation with economic deprivation is signified in the results. The study highlights the element of radicalization as witnessed in the curriculum and textbooks of public schools as a possible reason for extremism, which in turn may lead to terrorism.

Keywords: education, Pakistan, terrorism, poverty

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Authors: Filimonova Alexanra

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Inviscid incompressible fluid flows are considered. The object of the study is a vortex parquet – a structure consisting of distributed vortex spots of different directions, occupying the entire plane. The main attention is paid to the study of advection processes of passive particles in the corresponding velocity field. The dynamics of the vortex structures is considered in a rectangular region under the assumption that periodic boundary conditions are imposed on the stream function. Numerical algorithms are based on the solution of the initial-boundary value problem for nonstationary Euler equations in terms of vorticity and stream function. For this, the spectral-vortex meshless method is used. It is based on the approximation of the stream function by the Fourier series cut and the approximation of the vorticity field by the least-squares method from its values in marker particles. A vortex configuration, consisting of four vortex patches is investigated. Results of a numerical study of the dynamics and interaction of the structure are presented. The influence of the patch radius and the relative position of positively and negatively directed patches on the processes of interaction and mixing is studied. The obtained results correspond to the following possible scenarios: the initial configuration does not change over time; the initial configuration forms a new structure, which is maintained for longer times; the initial configuration returns to its initial state after a certain period of time. The processes of mass transfer of vorticity by liquid particles on a plane were calculated and analyzed. The results of a numerical analysis of the particles dynamics and trajectories on the entire plane and the field of local Lyapunov exponents are presented.

Keywords: ideal fluid, meshless methods, vortex structures in liquids, vortex parquet.

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Authors: Bilgen Ozluk, Ayfer Karaaslan

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Introduction: Adaptation to university life is a difficult process for students. In peer support, students are expected to help other students or sometimes adults using their helping skills. Therefore, it is expected that peer support will have significant effect on students’ adaptation to university life. Aim: This study was conducted with the aim of determining the effect of peer support on adaptation to university life in the first year students of the faculty of health sciences. Methods: The population consists of 340 first year university students receiving education in the departments of nursing, health management, social services, nutrition and dietetics, physiotherapy and rehabilitation at an university located in the province of Konya. The sample of the study consisted of 274 students who voluntarily participated in the study. The data were collected between the dates 23 May 2016 and 3 June 2016. The data were collected using the socio-demographic information, the peer support scale and the university life adaptation scale. Ethical approvals for the study and permission from the university were taken. Numbers, percentages, averages, one-Way ANOVA, pearson correlation analysis and regression analysis have been used in assessing the data. Findings: When the problems most frequently encountered by students just starting the university were ordered, problems regarding their classes took the first place by 41.6%, socio-cultural problems took the second place by 38.7%, and economic problems took the third place by 37.6%. The mean total score of the Adaptation to University Life Scale was found to be 216.78±32.15. Considering that the lowest and highest scores that can be gained from the scale are 132 and 289 respectively, it was found that the adaptation to university life levels of the students were higher than the average. The mean adaptation to university life score of the nursing students was higher than those of the students of other departments. The mean score of ‘the Peer Support Scale’ was found to be 47.24±10.27. Considering that the lowest and highest scores that can be gained from the scale are 17 and 68 respectively, it was found that the peer support levels of the students were higher than the average. As a result of the regression analysis, it was found that 20% of the total variance regarding adaptation to university life was explained by peer support. Conclution: Receiving the support peer groups becomes highly important in the university adaptation process of first-year students. Peer support will create the means for easier completion of this difficult transition process.

Keywords: adaptation to university life, first years, peer support, university student

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Authors: Piotr A. Kowalski, Kasper Sapala, Wiktor Warchalowski

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PM10 is a suspended dust that primarily has a negative effect on the respiratory system. PM10 is responsible for attacks of coughing and wheezing, asthma or acute, violent bronchitis. Indirectly, PM10 also negatively affects the rest of the body, including increasing the risk of heart attack and stroke. Unfortunately, Poland is a country that cannot boast of good air quality, in particular, due to large PM concentration levels. Therefore, based on the dense network of Airly sensors, it was decided to deal with the problem of prediction of suspended particulate matter concentration. Due to the very complicated nature of this issue, the Machine Learning approach was used. For this purpose, Convolution Neural Network (CNN) neural networks have been adopted, these currently being the leading information processing methods in the field of computational intelligence. The aim of this research is to show the influence of particular CNN network parameters on the quality of the obtained forecast. The forecast itself is made on the basis of parameters measured by Airly sensors and is carried out for the subsequent day, hour after hour. The evaluation of learning process for the investigated models was mostly based upon the mean square error criterion; however, during the model validation, a number of other methods of quantitative evaluation were taken into account. The presented model of pollution prediction has been verified by way of real weather and air pollution data taken from the Airly sensor network. The dense and distributed network of Airly measurement devices enables access to current and archival data on air pollution, temperature, suspended particulate matter PM1.0, PM2.5, and PM10, CAQI levels, as well as atmospheric pressure and air humidity. In this investigation, PM2.5, and PM10, temperature and wind information, as well as external forecasts of temperature and wind for next 24h served as inputted data. Due to the specificity of the CNN type network, this data is transformed into tensors and then processed. This network consists of an input layer, an output layer, and many hidden layers. In the hidden layers, convolutional and pooling operations are performed. The output of this system is a vector containing 24 elements that contain prediction of PM10 concentration for the upcoming 24 hour period. Over 1000 models based on CNN methodology were tested during the study. During the research, several were selected out that give the best results, and then a comparison was made with the other models based on linear regression. The numerical tests carried out fully confirmed the positive properties of the presented method. These were carried out using real ‘big’ data. Models based on the CNN technique allow prediction of PM10 dust concentration with a much smaller mean square error than currently used methods based on linear regression. What's more, the use of neural networks increased Pearson's correlation coefficient (R²) by about 5 percent compared to the linear model. During the simulation, the R² coefficient was 0.92, 0.76, 0.75, 0.73, and 0.73 for 1st, 6th, 12th, 18th, and 24th hour of prediction respectively.

Keywords: air pollution prediction (forecasting), machine learning, regression task, convolution neural networks

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Authors: Fouzia Khanam, Belal Hossain, Kaosar Afsana, Mahfuzar Rahman

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Aim: Although cardiovascular diseases (CVD) has already been recognized as a major cause of death in developed countries, its prevalence is rising in developing countries as well, and engendering a challenge for the health sector. Bangladesh has experienced an epidemiological transition from communicable to non-communicable diseases over the last few decades. So, the rising prevalence of CVD and its risk factors are imposing a major problem for the country. We aimed to examine the prevalence of CVDs and socioeconomic and lifestyle factors related to it from a population-based survey. Methods: The data used for this study were collected as a part of a large-scale cross-sectional study conducted to explore the overall health status of children, mothers and senior citizens of Bangladesh. Multistage cluster random sampling procedure was applied by considering unions as clusters and households as the primary sampling unit to select a total of 11,428 households for the base survey. Present analysis encompassed 12338 respondents of ≥ 35 years, selected from both rural areas and urban slums of the country. Socio-economic, demographic and lifestyle information were obtained through individual by a face-to-face interview which was noted in ODK platform. And height, weight, blood pressure and glycosuria were measured using standardized methods. Chi-square test, Univariate modified Poisson regression model, and multivariate modified Poisson regression model were done using STATA software (version 13.0) for analysis. Results: Overall, the prevalence of CVD was 4.51%, of which 1.78% had stroke and 3.17% suffered from heart diseases. Male had higher prevalence of stroke (2.20%) than their counterparts (1.37%). Notably, thirty percent of respondents had high blood pressure and 5% population had diabetes and more than half of the population was pre-hypertensive. Additionally, 20% were overweight, 77% were smoker or consumed smokeless tobacco and 28% of respondents were physically inactive. Eighty-two percent of respondents took extra salt while eating and 29% of respondents had deprived sleep. Furthermore, the prevalence of risk factor of CVD varied according to gender. Women had a higher prevalence of overweight, obesity and diabetes. Women were also less physically active compared to men and took more extra salt. Smoking was lower in women compared to men. Moreover, women slept less compared to their counterpart. After adjusting confounders in modified Poisson regression model, age, gender, occupation, wealth quintile, BMI, extra salt intake, daily sleep, tiredness, diabetes, and hypertension remained as risk factors for CVD. Conclusion: The prevalence of CVD is significant in Bangladesh, and there is an evidence of rising trend for its risk factors such as hypertension, diabetes especially in older population, women and high-income groups. Therefore, in this current epidemiological transition, immediate public health intervention is warranted to address the overwhelming CVD risk.

Keywords: cardiovascular diseases, diabetes, hypertension, stroke

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Authors: Csaba Kalman

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In spite of the existence of numerous second language (L2) motivation theories, the teacher’s role in motivating learners has remained an under-researched niche to this day. If we narrow down our focus on the teacher’s role on motivating adult learners of English in an English as a Foreign Language (EFL) context in corporate environments, empirical research is practically non-existent. This study fills the above research niche by exploring the most motivating aspects of the teacher’s personality, behaviour, and teaching practices that affect adult learners’ L2 motivation in corporate contexts in Hungary. The study was conducted in a wide range of industries in 18 organisations that employ over 250 people in Hungary. In order to triangulate the research, 21 human resources managers, 18 language teachers, and 466 adult learners of English were involved in the investigation by participating in interview studies, and quantitative questionnaire studies that measured ten scales related to the teacher’s role, as well as two criterion measure scales of intrinsic and extrinsic motivation. The qualitative data were analysed using a template organising style, while descriptive, inferential statistics, as well as multivariate statistical techniques, such as correlation and regression analyses, were used for analysing the quantitative data. The results showed that certain aspects of the teacher’s personality (thoroughness, enthusiasm, credibility, and flexibility), as well as preparedness, incorporating English for Specific Purposes (ESP) in the syllabus, and focusing on the present, proved to be the most salient aspects of the teacher’s motivating influence. The regression analyses conducted with the criterion measure scales revealed that 22% of the variance in learners’ intrinsic motivation could be explained by the teacher’s preparedness and appearance, and 23% of the variance in learners’ extrinsic motivation could be attributed to the teacher’s personal branding and incorporating ESP in the syllabus. The findings confirm the pivotal role teachers play in motivating L2 learners independent of the context they teach in; and, at the same time, call for further research so that we can better conceptualise the motivating influence of L2 teachers.

Keywords: adult learners, corporate contexts, motivation, teacher’s role

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Authors: Wenpeng You, Maciej Henneberg

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Background: Sugar consumption has been overwhelmingly advocated as a major dietary offender to obesity prevalence. Meat intake has been hypothesized as an obesity contributor in previous publications, but a moderate amount of meat to be included in our daily diet still has been suggested in many dietary guidelines. Comparable sugar and meat exposure data were obtained to assess the difference in relationships between the two major food groups and obesity prevalence at population level. Methods: Population level estimates of obesity and overweight rates, per capita per day exposure of major food groups (meat, sugar, starch crops, fibers, fats and fruits) and total calories, per capita per year GDP, urbanization and physical inactivity prevalence rate were extracted and matched for statistical analysis. Correlation coefficient (Pearson and partial) comparisons with Fisher’s r-to-z transformation and β range (β ± 2 SE) and overlapping in multiple linear regression (Enter and Stepwise) were used to examine potential differences in the relationships between obesity prevalence and sugar exposure and meat exposure respectively. Results: Pearson and partial correlations (controlled for total calories, physical inactivity prevalence, GDP and urbanization) analyses revealed that sugar and meat exposures correlated to obesity and overweight prevalence significantly. Fisher's r-to-z transformation did not show statistically significant difference in Pearson correlation coefficients (z=-0.53, p=0.5961) or partial correlation coefficients (z=-0.04, p=0.9681) between obesity prevalence and both sugar exposure and meat exposure. Both Enter and Stepwise models in multiple linear regression analysis showed that sugar and meat exposure were most significant predictors of obesity prevalence. Great β range overlapping in the Enter (0.289-0.573) and Stepwise (0.294-0.582) models indicated statistically sugar and meat exposure correlated to obesity without significant difference. Conclusion: Worldwide sugar and meat exposure correlated to obesity prevalence at the same extent. Like sugar, minimal meat exposure should also be suggested in the dietary guidelines.

Keywords: meat, sugar, obesity, energy surplus, meat protein, fats, insulin resistance

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Authors: Tondani Mudau, Sherine B. Van Wyk, Zuhayr Kafaar, Janan Dietrich

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Female adolescents residing in a patriarchal society such as South Africa are more inclined to embrace feminine ideologies. Internalizing these ideologies may expose female adolescents to mental health challenges such as depression and anxiety. This study explored whether the internalisation of adolescent femininity ideologies namely, objectified relationship with own body (ORB) and inauthentic self in relationships (ISR) predicted anxiety and depression in late female adolescents at Stellenbosch University. The sample of the study consisted of 1451 (18-24) female undergraduate and postgraduate students enrolled at Stellenbosch University. The mean age of the participants was 20 (SD=1.46), and most participants (39.7%) were first-year students. The study employed a cross-sectional quantitative research design. Data was collected through an online self-completion survey, the survey consisted of three sections, the first section asked biographical questions regarding age, gender, race and family background. The second section measured the internalisation of feminine ideologies by using the adolescent femininity ideology scale which has two subscales namely inauthentic self in relationship with others (ISR) and objectified relationship with one’s own body (ORB). The ISR scale had the Cronbach Alpha of 0.76, and the ORB scale had the Cronbach Alpha of 0.83. The third section measured mental health (depression and anxiety) by using the Hopkins Symptoms 25-checklist which had the Cronbach Alpha of 0.93. Data were analysed through multiple linear regression from IBM SPSS (Statistical Package for the Social Sciences Version 24). The overall results of the multiple linear regression showed that The AFIS combination accounted for 14% for anxiety as measured by the Hopkins Symptoms Checklist R² = .142, F (2, 682) = 56.431, p < .001. The combination also accounted for 24% for depression as measured by the Hopkins Symptoms Checklist R² = .239, F (2, 682) = 106.971, p < .0. The findings in this study affirm the objectification and feminist theory contentions that internalising femininity ideologies (ISR and ORB) predict negative mental health in female adolescents.

Keywords: adolescents, anxiety, depression, feminine ideologies, inauthentic self, mental health, self-objectification, South Africa

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Authors: Fatemeh Abdollahi, Munn-Sann Lye, Jamshid Yazdani Charati, Mehran Zarghami

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Fathers are at risk of depression during the postpartum period. Some studies have been reported maternal depression is the key predictor of paternal postpartum depression (PPD). This study aimed to estimate the prevalence and predictors of parental PPD and its association with maternal PPD. In a cross-sectional study, via a stratified random and convenience sampling method, participants referring to health centers during 2-8 weeks postpartum were recruited from March to October 2017. Paternal PPD and its relation to maternal PPD and other related factors were assessed using multiple logistic regression. Participants were 591 literate couples who referred to Mazandaran province primary health centers during to study period. Couples were screened for depression using Edinburgh Postnatal Depression Scale (EPDS). Fathers provided information on socio-demographic characteristics, life events, neonatal stressor, perceived stress (Perceived Stress Scale), social support (Multidimensional Scale of Perceived Social Support), and general health status using General Health Questionnaire (GHQ) as well. Data on mothers ‘demographic characteristics and obstetrics factors was also gathered. Overall, 93 fathers (15.7%) and 188 mothers (31.8%) reported depressive symptoms above the cut-off EPDS score of 12. In the multiple logistic regression model, older age [OR=1.20, (95%CI: 1.05- 1.36)], maternal depressive symptoms [OR=1.15, (95%CI: 1.04-1.27)], higher GHQ scores [OR=1.21, (95%CI: 1.11-1.33)] and increased recent life events [OR=1.42, (95%CI: 1.01-1.2.00)] were related to paternal PPD. A significant inverse association was found between number of children and paternal PPD [OR=0.20, (95%CI: 0.07-0.53)]. Depressive symptoms, especially in first-time fathers following the birth of a child, are not uncommon. Maternal depressive symptoms and paternal well-being were strong predictors of parental PPD. Creating opportunities for men to access special health care services, parental education to help adapting to parenthood, screening programs, and psychiatric/psychosocial interventions to decrease the suffering of depression for both depressed parents are recommended.

Keywords: depression, men, postpartum, risk factors, women

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Authors: Semaw A., Awet H., Yohannes M.

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Background: Hepatitis B Virus (HBV) is a major global public health problem. Individuals living in Sub-Sahara Africa have 60% lifetime risk of acquiring HBV infection. Evidences showed that 80-90% of those born from infected mothers developed chronic HBV. Perinatal HBV transmission is a major determinant of HBV carrier status, its chronic squeal and maintains HBV transmission across generations. Method: Institution based cross-sectional study was conducted among 406 pregnant mothers attending Antenatal clinics at Mekelle and Ayder referral hospital from January 30 to April 1/2014. Epidata version 3.1 was used for data entry and SPSS version 21 statistical software was used for data cleaning, management and finally determine associated factors of hepatitis B surface antigen adjusting important confounders using multivariable logistic regression analysis at 5% level of significance. Result: The overall prevalence of hepatitis B surface antigen among pregnant women was 33 (8.1%). The socio-demographic characteristic of the study population showed that there is high positivity among secondary school 189 (46.6%). In the multivariable logistic regression analysis, history of a contact with individuals who had history of hepatitis B infection or jaundice and lifetime number of multiple sexual partners were found to be significantly associated with HBsAg positivity at AOR = 3.73 95%C.I (1.373-10.182) and AOR = 2.57 95%C.I (1.173-5.654), respectively. Moreover, Human Immunodeficiency Virus (HIV) and HBV confection rate was found 3.6%. Conclusion: This study has shown that HBV prevalence in pregnant women is highly prevalent (8.1%) in the study area. Contact with individuals who had a history of hepatitis or have jaundice and report of multiple lifetime sexual partnership were associated with hepatitis B infection. Education about HBV transmission and prevention as well as screening all pregnant mothers shall be sought to reduce the serious public health crisis of HBV.

Keywords: HBsAg, hepatitis B, pregnant women, prevalence

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Authors: Swati Srivastava, Ashish Kumar Upadhyay

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Background: According to United Nation Children’s Fund, it has been estimated that worldwide about 165 million children were stunted in 2012 and India alone accounts for 38% of global burden of stunting. In terms of incidence, India is home of more than 60 million stunted children worldwide. Our study aims to examine the effect of pregnancy intention and maternal postnatal depressive symptoms on early childhood stunting in India. We hypothesized that effect of pregnancy intention and postnatal maternal depressive symptoms were mediated by social support. Methods: We used data from first wave of Young Lives Study India. Out of 2011 children recruited in original cohort, 1833 children had complete information on pregnancy intention, maternal depression and other variables. A series of multivariate logistic regression model were used to examine the effect of pregnancy intention and postnatal depressive symptoms on early childhood stunting. Results: Bivariate result indicates that a higher percent of children born after unintended pregnancy (40%) were stunted than children of intended pregnancy (26%). Likewise, proportion of stunted children was also higher among women of high postnatal depressive symptoms (35%) than low level of depression (24%). Results of multivariate logistic regression model indicate that children born after unintended pregnancy were significantly more likely to be stunted than children born after intended pregnancy (Coefficient: 1.70, CI: 1.17, 2.48). Likewise, early childhood stunting was also associated with maternal postnatal depressive symptoms among women (Coefficient: 1.48, CI: 1.16, 1.88). The effect of pregnancy intention and postnatal depressive symptoms on early childhood stunting remains unchanged after controlling for social support and other variables. Conclusions: The findings of this study provide conclusive evidence regarding consequences of pregnancy intention and postnatal depressive symptoms on early childhood stunting in India. Therefore, there is need to identify the women with unintended pregnancy and incorporate the promotion of mental health into their national reproductive and child health programme.

Keywords: pregnancy intention, postnatal depressive symptoms, social support, childhood stunting, young lives study, India

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Authors: Prateek Singh, Dilshad Ahmad

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Growing demand for high-quality steel products has inspired researchers to investigate the unit operations involved in the manufacturing of these products (slabs, rods, sheets, etc.). One such operation is tundish operation, in which a vessel (tundish) acts as a buffer of molten steel for the solidification operation in mold. It is observed that tundish also plays a crucial role in the quality and cleanliness of the steel produced, besides merely acting as a reservoir for the mold. It facilitates removal of dissolved oxygen (inclusions) from the molten steel thus improving its cleanliness. Inclusion removal can be enhanced by increasing the residence time of molten steel in the tundish by incorporation of flow modifiers like dams, weirs, turbo-pad, etc. These flow modifiers also help in reducing the dead or short circuit zones within the tundish which is significant for maintaining thermal and chemical homogeneity of molten steel. Thus, it becomes important to analyze the flow of molten steel in the tundish for different configuration of flow modifiers. In the present work, effect of varying positions and heights/depths of dam and weir on the dead volume in tundish is studied. Steady state thermal and flow profiles of molten steel within the tundish are obtained using OpenFOAM. Subsequently, Residence Time Distribution analysis is performed to obtain the percentage of dead volume in the tundish. Design of Experiment method is then used to configure different tundish geometries for varying positions and heights/depths of dam and weir, and dead volume for each tundish design is obtained. A second-degree polynomial with two-term interactions of independent variables to predict the dead volume in the tundish with positions and heights/depths of dam and weir as variables are computed using Multiple Linear Regression model. This polynomial is then used in an optimization framework to obtain the optimal tundish geometry for minimizing dead volume using Sequential Quadratic Programming optimization.

Keywords: design of experiments, multiple linear regression, OpenFOAM, residence time distribution, sequential quadratic programming optimization, steel, tundish

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

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

Keywords: online shopping, purchase evaluation, regret, satisfaction

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Authors: Olawale Babatunde Olatinsu, Deborah Oluwaseun Olorode

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Industrial rocks were collected from a quarry site at Ewekoro in south-western Nigeria and analysed using Nuclear Magnetic Resonance (NMR) technique. NMR measurement was conducted on the samples in partial water-saturated and full brine-saturated conditions. Raw NMR data were analysed with the aid of T2 curves and T2 spectra generated by inversion of raw NMR data using conventional regularized least-squares inversion routine. Results show that NMR transverse relaxation (T2) signatures fairly adequately distinguish between the rock types. Similar T2 curve trend and rates at partial saturation suggests that the relaxation is mainly due to adsorption of water on micropores of similar sizes while T2 curves at full saturation depict relaxation decay rate as: 1/T2(shale)>1/ T2(glauconite)>1/ T2(limestone) and 1/T2(sandstone). NMR T2 distributions at full brine-saturation show: unimodal distribution in shale; bimodal distribution in sandstone and glauconite; and trimodal distribution in limestone. Full saturation T2 distributions revealed the presence of well-developed and more abundant micropores in all the samples with T2 in the range, 402-504 μs. Mesopores with amplitudes much lower than those of micropores are present in limestone, sandstone and glauconite with T2 range: 8.45-26.10 ms, 6.02-10.55 ms, and 9.45-13.26 ms respectively. Very low amplitude macropores of T2 values, 90.26-312.16 ms, are only recognizable in limestone samples. Samples with multiple peaks showed well-connected pore systems with sandstone having the highest degree of connectivity. The difference in T2 curves and distributions for the rocks at full saturation can be utilised as a potent diagnostic tool for discrimination of these rock types found at Ewekoro.

Keywords: Ewekoro, NMR techniques, industrial rocks, characterization, relaxation

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Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

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Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

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Authors: Michelle R. Sullivan

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Positive romantic relationships and marriages offer a buffer against a host of physical and emotional difficulties. Conversely, poor relationship quality and marital discord can have deleterious consequences for individuals and families. Research has described non-monogamy, infidelity, and consensual non-monogamy, as both consequential and causal of relationship difficulty, or as a unique way a couple strives to make a relationship work. Much research on consensual non-monogamy has built on feminist theory and critique. To the author’s best knowledge, to date, no studies have examined the predictive relationship between individual and relationship characteristics and expectations of non-monogamy. The current longitudinal study: 1) estimated the prevalence of expectations of partner non-monogamy and 2) evaluated whether gender, sexual identity, age, education, how a couple met, and relationship quality were predictive expectations of partner non-monogamy. This study utilized the publically available longitudinal dataset, How Couples Meet and Stay Together. Adults aged 18- to 98-years old (n=4002) were surveyed by phone over 5 waves from 2009-2014. Demographics and how a couple met were gathered through self-report in Wave 1, and relationship quality and expectations of partner non-monogamy were gathered through self-report in Waves 4 and 5 (n=1047). The prevalence of expectations of partner non-monogamy (encompassing both infidelity and consensual non-monogamy) was 4.8%. Logistic regression models indicated that sexual identity, gender, education, and relationship quality were significantly predictive of expectations of partner non-monogamy. Specifically, male gender, lower education, identifying as lesbian, gay, or bisexual, and a lower relationship quality scores were predictive of expectations of partner non-monogamy. Male gender was not predictive of expectations of partner non-monogamy in the follow up logistic regression model. Age and whether a couple met online were not associated with expectations of partner non-monogamy. Clinical implications include awareness of the increased likelihood of lesbian, gay, and bisexual individuals to have an expectation of non-monogamy and the sequelae of relationship dissatisfaction that may be related. Future research directions could differentiate between non-monogamy subtypes and the person and relationship variables that lead to the likelihood of consensual non-monogamy and infidelity as separate constructs, as well as explore the relationship between predicting partner behavior and actual partner behavioral outcomes.

Keywords: open relationship, polyamory, infidelity, relationship satisfaction

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Authors: N. Haj Salem, M. Belhadj, S. Ben Jomâa, R. Dhouieb, S. Saadi, M. A. Mesrati, A. Chadly

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Introduction: The hyoid bone is considered as one of many bones used to identify a missed person. There is a specificity of each population group in human identifications. Objective: To analyze the relationship between age, sex and metric parameters of hyoid bone in Tunisian population sample, using CT-scan. Materials and Methods: A prospective study was conducted in the Department of Forensic Medicine of FattoumaBourguiba Hospital of Monastir-Tunisia during 4 years. A total of 240 samples of hyoid bone were studied. The age of cases ranged from 18 days to 81 years. The specimens were collected only from the deceased of known age. Once dried, each hyoid bone was scanned using CT scan. For each specimen, 10 measurements were taken using a computer program. The measurements consisted of 6 lengths and 4 widths. A regression analysis was used to estimate the relationship between age, sex, and different measurements. For age estimation, a multiple logistic regression was carried out for samples ≤ 35 years. For sex determination, ROC curve was performed. Discriminant value finally retained was based on the best specificity with the best sensitivity. Results: The correlation between real age and estimated age was good (r²=0.72) for samples aged 35 years or less. The unstandardised canonical function equation was estimated using three variables: maximum length of the right greater cornua, length from the middle of the left joint space to the middle of the right joint space and perpendicular length from the centre point of a line between the distal ends of the right and left greater cornua to the centre point of the anterior view of the body of the hyoid bone. For sex determination, the ROC curve analysis reveals that the area under curve was at 81.8%. Discriminant value was 0.451 with a specificity of 73% and sensibility of 79%. The equation function was estimated based on two variables: maximum length of the greater cornua and maximum length of the hyoid bone. Conclusion: The findings of the current study suggest that metric analysis of the hyoid bone may predict the age ≤ 35 years. Sex estimation seems to be more reliable. Further studies dealing with the fusion of the hyoid bone and the current study could help to achieve more accurate age estimation rates.

Keywords: anthropology, age estimation, CT scan, sex determination, Tunisia

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Authors: Serena Salvi

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

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

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Authors: Michiko Iwasaki, Jane M. Endres, Julia Y. Richards, Andrew Futterman

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The present study aimed to examine college students’ happiness during COVID19-pandemic. Using the online survey data from 96 college students in the U.S., a regression analysis was conducted to predict college students’ happiness. The results indicated that a four-predictor model (optimism, college students’ subjective wellbeing, coronavirus stress, and spirituality) explained 57.9% of the variance in student’s subjective happiness, F(4,77)=26.428, p<.001, R2=.579, 95% CI [.41,.66]. The study suggests the importance of learned optimism among college students.

Keywords: COVID-19, optimism, spirituality, well-being

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Authors: Davies Obaromi, Qin Yongsong, James Ndege

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To interpolate scattered or regularly distributed data, there are imprecise or exact methods. However, there are some of these methods that could be used for interpolating data in a regular grid and others in an irregular grid. In spatial epidemiology, it is important to examine how a disease prevalence rates are distributed in space, and how they relate with each other within a defined distance and direction. In this study, for the geographic and graphic representation of the disease prevalence, linear and biharmonic spline methods were implemented in MATLAB, and used to identify, localize and compare for smoothing in the distribution patterns of tuberculosis (TB) in Eastern Cape Province. The aim of this study is to produce a more “smooth” graphical disease map for TB prevalence patterns by a 3-D curve fitting techniques, especially the biharmonic splines that can suppress noise easily, by seeking a least-squares fit rather than exact interpolation. The datasets are represented generally as a 3D or XYZ triplets, where X and Y are the spatial coordinates and Z is the variable of interest and in this case, TB counts in the province. This smoothing spline is a method of fitting a smooth curve to a set of noisy observations using a spline function, and it has also become the conventional method for its high precision, simplicity and flexibility. Surface and contour plots are produced for the TB prevalence at the provincial level for 2012 – 2015. From the results, the general outlook of all the fittings showed a systematic pattern in the distribution of TB cases in the province and this is consistent with some spatial statistical analyses carried out in the province. This new method is rarely used in disease mapping applications, but it has a superior advantage to be assessed at subjective locations rather than only on a rectangular grid as seen in most traditional GIS methods of geospatial analyses.

Keywords: linear, biharmonic splines, tuberculosis, South Africa

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