Search results for: multivariate failure-time data

Authors: Salako Rotimi, Oshungade Stephen, Ojewoye Opeyemi

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The maintenance of price stability is one of the macroeconomic challenges facing Nigeria as a nation. This paper attempts to build a co-integration multivariate time series model for inflation movement in Nigeria using data extracted from the abstract of statistics of the Central Bank of Nigeria (CBN) from 2008 to 2017. The Johansen cointegration test suggests at least one co-integration vector describing the long run relationship between Consumer Price Index (CPI), Food Price Index (FPI) and Non-Food Price Index (NFPI). All three series show increasing pattern, which indicates a sign of non-stationary in each of the series. Furthermore, model predictability was established with root-mean-square-error, mean absolute error, mean average percentage error, and Theil’s unbiased statistics for n-step forecasting. The result depicts that the long run coefficient of a consumer price index (CPI) has a positive long-run relationship with the food price index (FPI) and non-food price index (NFPI).

Keywords: economic, inflation, model, series

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Authors: Kamel Malik Bensafta, Gervasio Semedo

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The purpose of this paper is to investigate the relationship between oil prices and socks markets. The empirical analysis in this paper is conducted within the context of Multivariate GARCH models, using a transform version of the so-called BEKK parameterization. We show that mean and uncertainty of US market are transmitted to oil market and European market. We also identify an important transmission from WTI prices to Brent Prices.

Keywords: oil volatility, stock markets, MGARCH, transmission, structural break

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Authors: Seyed Sajjad Habibi

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The aim of this study is to investigate the impact of global financial crises and corporate financial crisis on tax evasion of companies listed on the Tehran Stock Exchange. For this purpose, panel data in the periods of financial crisis period (2007 to 2012) and without a financial crisis (2004, 2005, 2006, 2013, 2014, and 2015) was analyzed using multivariate linear regression. The results indicate a significant relationship between the corporate financial crisis (bankruptcy risk) and tax evasion in the global financial crisis period. The results also showed a significant relationship between the corporate bankruptcy risk and tax evasion in the period with no global financial crisis. A significant difference was found between the bankruptcy risk and tax evasion in the period of the global financial crisis and that with no financial crisis so that tax evasion increased in the financial crisis period.

Keywords: global financial crisis, corporate financial crisis, bankruptcy risk, tax evasion risk, emerging markets

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Authors: Esmail Sadipour

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The use of social networks is increasing day by day in all societies. The purpose of this research was to know the relationship between the use of social networks (Instagram, WhatsApp, and Telegram) with executive functions and academic performance in first-year female high school students. This research was applied in terms of purpose, quantitative in terms of data type, and correlational in terms of technique. The population of this research consisted of all female high school students in the first year of district 2 of Tehran. Using Green's formula, the sample size of 150 people was determined and selected by cluster random method. In this way, from all 17 high schools in district 2 of Tehran, 5 high schools were selected by a simple random method and then one class was selected from each high school, and a total of 155 students were selected. To measure the use of social networks, a researcher-made questionnaire was used, the Barclay test (2012) was used for executive functions, and last semester's GPA was used for academic performance. Pearson's correlation coefficient and multivariate regression were used to analyze the data. The results showed that there is a negative relationship between the amount of use of social networks and self-control, self-motivation and time self-management. In other words, the more the use of social networks, the fewer executive functions of students, self-control, self-motivation, and self-management of their time. Also, with the increase in the use of social networks, the academic performance of students has decreased.

Keywords: social networks, executive function, academic performance, working memory

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Authors: Amin Amani, Masomeh Reihany Shirvan, Mahla Nabizadeh Mashizi, Mohadese Khoshtinat, Mohammad Elyas Ansarinia

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The purpose of this study is the relationship between a healthy lifestyle and risky behavior in physical education students of Bojnourd schools. The study sample consisted of teenagers studying in second and third grade of Bojnourd's high schools. According to level sampling, 604 students studying in the second grade, and 600 students studying in third grade were tested from physical education schools in Bojnourd. For sample selection, populations were divided into 4 area including north, East, West and South. Then according to the number of students of each area, sample size of each level was determined. Two questionnaires were used to collect data in this study which were consisted of three parts: The demographic data, Iranian teenagers' risk taking (IARS) and prevention methods with emphasize on the importance of family role were examined. The Central and dispersion indices, such as standard deviation, multiple variance analysis, and multivariate regression analysis were used. Results showed that the observed F is significant (P ≤ 0.01) and 21% of variance related to risky behavior is explained by the lack of awareness. Given the significance of the regression, the coefficients of risky behavior in teenagers in prediction equation showed that each of teenagers' risky behavior can have an impact on healthy lifestyle.

Keywords: healthy lifestyle, high-risk behavior, students, physical education

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Authors: Balasaheb Bansode, L. Ladusingh

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The public distribution system is an important component of food security. It is a massive welfare program undertaken by Government of India and implemented by state government since India being a federal state; for achieving multiple objectives like eliminating hunger, reduction in malnutrition and making food consumption affordable. This program reaches at the community level through the various agencies of the government. The paper focuses on the accessibility of PDS at household level and how the present policy framework results in exclusion and inclusion errors. It tries to explore the sanctioned food grain quantity received by differentiated ration cards according to income criterion at household level, and also it has highlighted on the type of corruption in food distribution that is generated by the PDS system. The data used is of secondary nature from NSSO 68 round conducted in 2012. Bivariate and multivariate techniques have been used to understand the working and consumption of food for this paper.

Keywords: calories intake, entitle food quantity, poverty aliviation through PDS, target error

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Authors: Peri Harish Kumar, Sai Sharan Dwarka, Tajbinder Singh Bains, Suneet John Joseph, Chaitanya Kiran, Sambhu Dutta, Sarah Makram, Mohamed Sayed Zaazouee, Alaa Ahmed Elshanbary

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Objective: To identify cancer and non-cancer causes of death in hepatocellular carcinoma (HCC) patients over different time periods after diagnosis and to compare the mortality risk of each cause in HCC patients with the general population. Methods: In this retrospective cohort study, data of 67,637 HCC patients from 1975 to 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. We investigated the association between different causes of death and the following variables: age, race, tumor stage at diagnosis, and treatment (surgery, chemotherapy, and radiotherapy); each according to the periods of <1 year, 1-5 years, 5-10 years, and >10 years following the diagnosis. Standardized mortality ratios (SMRs) and their 95% confidence intervals (CIs) were calculated for cancer and non-cancer deaths in each of the mentioned periods following diagnosis. Results: Data of 67,637 patients, of whom 50,571 patients died during the follow-up period, were analyzed. Most deaths were due to HCC itself (35,535, 70.3%), followed by other cancers (3,983, 7.9%). Common causes of non-cancer mortality included infectious and parasitic diseases including HIV (2,823 patients, SMR=105.68, 95% CI: 101.82-109.65), chronic liver disease (2,719 patients, SMR=76.56, 95% CI: 73.71,79.5), and heart diseases (1,265 patients, SMR=2.26, 95% CI: 2.14-2.39), with higher mortality risk in HCC patients than in the general population. Conclusion: Cancers stand for most deaths in patients with HCC. Besides, infectious, and parasitic diseases including HIV represent the commonest non-cancer cause of mortality.

Keywords: hepatocellular carcinoma, seer, causes of death, mortality

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Authors: Tya M. Arthur

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Purpose: BIPOC (Black, Indigenous, and People of Color) adolescents face racism and discrimination at a young age. These early experiences have short- and long-term impacts on their health and overall well-being. The purpose of this study was to determine the relationships between perceived racial discrimination at school and health risk behaviors and experiences of BIPOC adolescents. Methods: Data from the 2021 Adolescent Behaviors and Experiences Survey (ABES) were analyzed. All demographic data were summarized using frequencies and chi-squared tests. A univariate and multivariate logistic regression model was used to test the relationship between perceived racial discrimination and selected health risk factors. All analyses were conducted using STATA SE 18. Results: A total of 42.2% of the BIPOC adolescents in the study indicated being treated unfairly at school due to their race. The majority of those who reported being discriminated against were Black/African American or Multiple Race-Hispanic. Asian adolescents were almost 5 times more likely to face racial discrimination at school compared to their American Indian/Alaska Native counterparts (OR = 4.86, 95% CI [2.69-8.77], p < 0.001). Other risk predictors of racial discrimination included being female (OR = 1.38, 95% CI [1.13-1.68], p = 0.002) and feeling disconnected at school (OR = 1.76, 95% CI [1.30-2.38], p < 0.001). After adjustment for health risk behaviors and experiences, BIPOC adolescents were still more likely to face racial discrimination with even higher odds. Conclusions: The results of this study highlight the depth of racial discrimination faced by BIPOC adolescents at school. Greater attention should be placed on racial discrimination as a social determinant of health and a public health crisis.

Keywords: racial discrimination, adolescents, heath risk factors, BIPOC

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Authors: Vineet Agrawal, Deepanjali S., Medha R., Subitha L.

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Background. Hospital malnutrition is a highly prevalent issue and is known to increase the morbidity, mortality, length of hospital stay, and cost of care. In India, studies on hospital malnutrition have been restricted to ICU, post-surgical, and cancer patients. We designed this study to assess the impact of hospital malnutrition on 30-day post-discharge and in-hospital mortality in patients admitted in the general medicine department, irrespective of diagnosis. Methodology. All patients aged above 18 years admitted in the medicine wards, excluding medico-legal cases, were enrolled in the study. Nutritional assessment was done within 72 h of admission, using Subjective Global Assessment (SGA), which classifies patients into three categories: Severely malnourished, Mildly/moderately malnourished, and Normal/well-nourished. Anthropometric measurements like Body Mass Index (BMI), Triceps skin-fold thickness (TSF), and Mid-upper arm circumference (MUAC) were also performed. Patients were followed-up during hospital stay and 30 days after discharge through telephonic interview, and their final diagnosis, comorbidities, and cause of death were noted. Multivariate logistic regression and cox regression model were used to determine if the nutritional status at admission independently impacted mortality at one month. Results. The prevalence of malnourishment by SGA in our study was 67.3% among 395 hospitalized patients, of which 155 patients (39.2%) were moderately malnourished, and 111 (28.1%) were severely malnourished. Of 395 patients, 61 patients (15.4%) expired, of which 30 died in the hospital, and 31 died within 1 month of discharge from hospital. On univariate analysis, malnourished patients had significantly higher morality (24.3% in 111 Cat C patients) than well-nourished patients (10.1% in 129 Cat A patients), with OR 9.17, p-value 0.007. On multivariate logistic regression, age and higher Charlson Comorbidity Index (CCI) were independently associated with mortality. Higher CCI indicates higher burden of comorbidities on admission, and the CCI in the expired patient group (mean=4.38) was significantly higher than that of the alive cohort (mean=2.85). Though malnutrition significantly contributed to higher mortality on univariate analysis, it was not an independent predictor of outcome on multivariate logistic regression. Length of hospitalisation was also longer in the malnourished group (mean= 9.4 d) compared to the well-nourished group (mean= 8.03 d) with a trend towards significance (p=0.061). None of the anthropometric measurements like BMI, MUAC, or TSF showed any association with mortality or length of hospitalisation. Inference. The results of our study highlight the issue of hospital malnutrition in medicine wards and reiterate that malnutrition contributes significantly to patient outcomes. We found that SGA performs better than anthropometric measurements in assessing under-nutrition. We are of the opinion that the heterogeneity of the study population by diagnosis was probably the primary reason why malnutrition by SGA was not found to be an independent risk factor for mortality. Strategies to identify high-risk patients at admission and treat malnutrition in the hospital and post-discharge are needed.

Keywords: hospitalization outcome, length of hospital stay, mortality, malnutrition, subjective global assessment (SGA)

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Authors: Jeetendra Yadav, Geetha Menon, Anita Pal, Rajkumar Verma

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Even after encouraging maternal and child wellness programs at worldwide level, lower-middle income nations are not reached the goal set by the UN yet. This study quantified the contribution of socioeconomic determinants of inequality to the utilization of Antenatal Care in South Asian Countries. This study used data from Demographic Health Survey (DHS) of the selected countries were used, and Oaxaca decomposing were applied for socioeconomic inequalities in utilization of antenatal care. Finding from the multivariate analysis shows that mother’s age at the time of birth, birth order and interval, mother’s education, mass media exposure and economic status were significant determinants of the utilization of antenatal care services in South Asian countries. Considering, concentration index curve, the line of equity was greatest in Pakistan which followed by India and Nepal.

Keywords: antenatal care, decomposition, inequalities, South Asian countries

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Authors: Faisal Kalota

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Big Data and analytics have gained a huge momentum in recent years. Big Data feeds into the field of Learning Analytics (LA) that may allow academic institutions to better understand the learners’ needs and proactively address them. Hence, it is important to have an understanding of Big Data and its applications. The purpose of this descriptive paper is to provide an overview of Big Data, the technologies used in Big Data, and some of the applications of Big Data in education. Additionally, it discusses some of the concerns related to Big Data and current research trends. While Big Data can provide big benefits, it is important that institutions understand their own needs, infrastructure, resources, and limitation before jumping on the Big Data bandwagon.

Keywords: big data, learning analytics, analytics, big data in education, Hadoop

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Authors: Andrew Green, Jiaming Liu, Kellathur Srinivasan, Raymond Chua

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Introduction: The size of Singapore’s online health product (HP) market (e-commerce) is largely unknown. However, it is recognized that a large majority comes from overseas and thus, unregulated. As buying HP from unauthorized sources significantly compromises public health safety, understanding e-commerce users’ demographics and their perceptions on online HP purchasing becomes a pivotal first step to form a basis for recommendations in Singapore’s pharmacovigilance efforts. Objective: To assess the prevalence of online HP purchasing behaviour among Singaporean e-commerce users. Methodology: This is a cross-sectional study targeting Singaporean e-commerce users recruited from various local websites and online forums. Participants were not randomized into study arms but instead stratified by random sampling method based on participants’ age. A self-administered anonymous questionnaire was used to explore participants' demographics, online HP purchasing behaviour, knowledge and attitude. The association of different variables with online HP purchasing behaviour was analysed using logistic regression statistics. Main outcome measures: Prevalence of HP e-commerce users in Singapore (%) and variables that contribute to the prevalence (adjusted prevalent ratio). Results: The study recruited 372 complete and valid responses. The prevalence of online HP consumers among e-commerce users in Singapore is estimated to be 55.9% (1.7 million consumers). Online purchasing of complementary HP (46.9%) was the most prevalent, followed by medical devices (21.6%) and Western medicine (20.5%). Multivariate analysis showed that age is an independent variable that correlates with the likelihood of buying HP online. The prevalence of HP e-commerce users is highest in the 35-44 age group (64.1%) and lowest among the 16-24 age group (36.4%). The most bought HP through the internet are vitamins and minerals (21.5%), non-herbal (15.9%), herbal (13.9%), weight loss (8.7%) and sports (8.4%) supplements. While the top 3 products are distributed equally between the genders, there is a skew towards female respondents (12.4% in females vs. 4.9% in males) for weight loss supplements and towards males (13.2% in males vs. 3.7% in females) for sports supplements. Even though online consumers are in the younger age brackets, our study found that up to 72.0% of HP bought online are bought for others (buyer’s family and/or friends). Multivariate analysis showed a statistically significant association between purchasing HP through online means and the perceptions that 'internet is safe' (adjusted Prevalence Ratio=1.15, CI 1.03-1.28), 'buying HP online is time saving' (PR=1.17, CI 1.01-1.36), and 'recognition of HP brand' (PR=1.21 CI 1.06-1.40). Conclusions: This study has provided prevalence data for online HP market in Singapore, and has allowed the country’s regulatory body to formulate a targeted pharmacovigilance approach to this growing problem.

Keywords: e-commerce, pharmaceuticals, pharmacovigilance, Singapore

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Authors: Parul Jindal, Shubhi Singh, Priya Ramakrishnan, Shailender Raghuvanshi

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Background: Knowledge of the influence of the age of the child on laryngeal dimensions is essential for all practitioners who are dealing with paediatric airway. Choosing the correct endotracheal tube (ETT) size is a crucial step in pediatric patients because a large-sized tube may cause complications like post-extubation stridor and subglottic stenosis. On the other hand with a smaller tube, there will be increased gas flow resistance, aspiration risk, poor ventilation, inaccurate monitoring of end-tidal gases and reintubation may also be required with a different size of the tracheal tube. Recent advancement in ultrasonography (USG) techniques should now allow for accurate and descriptive evaluation of pediatric airway. Aims and objectives: This study was planned to determine the accuracy of Ultrasonography (USG) to assess the appropriate ETT size and compare it with physical indices based formulae. Methods: After obtaining approval from Institute’s Ethical and Research committee, and parental written and informed consent, the study was conducted on 100 subjects of either sex between 12-60 months of age, undergoing various elective surgeries under general anesthesia requiring endotracheal intubation. The same experienced radiologist performed ultrasonography. The transverse diameter was measured at the level of cricoids cartilage by USG. After USG, general anesthesia was administered using standard techniques followed by the institute. An experienced anesthesiologist performed the endotracheal intubations with uncuffed endotracheal tube (Portex Tracheal Tube Smiths Medical India Pvt. Ltd.) with Murphy’s eye. He was unaware of the finding of the ultrasonography. The tracheal tube was considered best fit if air leak was satisfactory at 15-20 cm H₂O of airway pressure. The obtained values were compared with the values of endotracheal tube size calculated by ultrasonography, various age, height, weight-based formulas and diameter of right and left little finger. The correlation of the size of the endotracheal tube by different modalities was done and Pearson's correlation coefficient was obtained. The comparison of the mean size of the endotracheal tube by ultrasonography and by traditional formula was done by the Friedman’s test and Wilcoxon sign-rank test. Results: The predicted tube size was equal to best fit and best determined by ultrasonography (100%) followed by comparison to left little finger (98%) and right little finger (97%) and age-based formula (95%) followed by multivariate formula (83%) and body length (81%) formula. According to Pearson`s correlation, there was a moderate correlation of best fit endotracheal tube with endotracheal tube size by age-based formula (r=0.743), body length based formula (r=0.683), right little finger based formula (r=0.587), left little finger based formula (r=0.587) and multivariate formula (r=0.741). There was a strong correlation with ultrasonography (r=0.943). Ultrasonography was the most sensitive (100%) method of prediction followed by comparison to left (98%) and right (97%) little finger and age-based formula (95%), the multivariate formula had an even lesser sensitivity (83%) whereas body length based formula was least sensitive with a sensitivity of 78%. Conclusion: USG is a reliable method of estimation of subglottic diameter and for prediction of ETT size in children.

Keywords: endotracheal intubation, pediatric airway, subglottic diameter, traditional formulas, ultrasonography

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Authors: Yonas Shuke Kitawa

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Background: Although malaria incidence has substantially fallen sharply over the past few years, the rate of decline varies by district, time, and malaria type. Despite this turn-down, malaria remains a major public health threat in various districts of Ethiopia. Consequently, the present study is aimed at developing a predictive model that helps to identify the spatio-temporal variation in malaria risk by multiple plasmodium species. Methods: We propose a multivariate spatio-temporal Bayesian model to obtain a more coherent picture of the temporally varying spatial variation in disease risk. The spatial autocorrelation in such a data set is typically modeled by a set of random effects that assign a conditional autoregressive prior distribution. However, the autocorrelation considered in such cases depends on a binary neighborhood matrix specified through the border-sharing rule. Over here, we propose a graph-based optimization algorithm for estimating the neighborhood matrix that merely represents the spatial correlation by exploring the areal units as the vertices of a graph and the neighbor relations as the series of edges. Furthermore, we used aggregated malaria count in southern Ethiopia from August 2013 to May 2019. Results: We recognized that precipitation, temperature, and humidity are positively associated with the malaria threat in the area. On the other hand, enhanced vegetation index, nighttime light (NTL), and distance from coastal areas are negatively associated. Moreover, nonlinear relationships were observed between malaria incidence and precipitation, temperature, and NTL. Additionally, lagged effects of temperature and humidity have a significant effect on malaria risk by either species. More elevated risk of P. falciparum was observed following the rainy season, and unstable transmission of P. vivax was observed in the area. Finally, P. vivax risks are less sensitive to environmental factors than those of P. falciparum. Conclusion: The improved inference was gained by employing the proposed approach in comparison to the commonly used border-sharing rule. Additionally, different covariates are identified, including delayed effects, and elevated risks of either of the cases were observed in districts found in the central and western regions. As malaria transmission operates in a spatially continuous manner, a spatially continuous model should be employed when it is computationally feasible.

Keywords: disease mapping, MSTCAR, graph-based optimization algorithm, P. falciparum, P. vivax, waiting matrix

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Authors: Celina Pestano-Gabino, Concepcion Gonzalez-Concepcion, M. Candelaria Gil-Fariña

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Some estimation methods for VARMA models, and Multivariate Time Series Models in general, rely on the use of a Hankel matrix. It is known that if the data sample is populous enough and the dimension of the Hankel matrix is unnecessarily large, this may result in an unnecessary number of computations as well as in numerical problems. In this sense, the aim of this paper is two-fold. First, we provide some theoretical results for these matrices which translate into a lower dimension for the matrices normally used in the algorithms. This contribution thus serves to improve those methods from a numerical and, presumably, statistical point of view. Second, we have chosen an estimation algorithm to illustrate in practice our improvements. The results we obtained in a simulation of VARMA models show that an increase in the size of the Hankel matrix beyond the theoretical bound proposed as valid does not necessarily lead to improved practical results. Therefore, for future research, we propose conducting similar studies using any of the linear system estimation methods that depend on Hankel matrices.

Keywords: covariances Hankel matrices, Kronecker indices, system identification, VARMA models

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Authors: Wudneh Asegedech Ayele

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Background: Dietary diversity is strongly related with non-communicable disease (NCDs). Diet plays a key role as a risk factor for hypertension. Diets rich in fruits, vegetables, and low-fat dairy products that include whole grains, poultry, fish, and nuts, that contain only small amounts of red meat, sweets, and sugar-containing beverages, and that contain decreased amounts of total and saturated fat and cholesterol have been found to have a protective effect against hypertension. Methods: hospital based Cross-sectional study design was employed from June 1-June 25, 2021. Sampling technique was Systematic random sampling and data were collected using an interview method. Data were entered into Epi Data version 3.1 and exported to SPSS version 25 for processed and analysis respectively. Descriptive statistics were used to summarize data. Bivariate and multivariate logistic regression will employed to determine dietary diversity among hypertension patients. Results: Adequate dietary diversity score were 96 (24.68%). Most of them cereal, white roots and tubers, dark green leafy vegetables, Vitamin A rich fruits ,meat, egg and coffee or tea more intakes. Hypertensive patients who didn’t consume cereals four times less likely adequate dietary diversity than who consumed cereals [AOR= 4.083, 95%: CI (2.096 -7.352)]. Hypertensive patients who didn’t consume white roots and tubers 14 times less likely adequate dietary diversity than who consumed white roots and tubers [AOR= 13.733, 95% CI: (5.388-34.946)]. Conclusion and recommendation the study showed one of fourth part reported adequate dietary diversity score. Cereals, fruits, vegetables and milk and milk products were statistically associated with dietary diversity practice. Health education about dietary modifications and behavioral change to dietary diversity

Keywords: dietary diversity practice and associated facrors among hypertension patients at tirunesh beijing hospital, hypertension, dietary, diversity and tirunesh beijing hospital, associated facrors among hypertension patient, at tirunesh beijing hospita

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Authors: Stephanie Chen, Mitja Echim, Christof Büskens

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To describe and propagate the behavior of a system mathematical models are formulated. Parameter identification is used to adapt the coefficients of the underlying laws of science. For complex systems this approach can be incomplete and hence imprecise and moreover too slow to be computed efficiently. Therefore, these models might be not applicable for the numerical optimization of real systems, since these techniques require numerous evaluations of the models. Moreover not all quantities necessary for the identification might be available and hence the system must be adapted manually. Therefore, an approach is described that generates models that overcome the before mentioned limitations by not focusing on physical laws, but on measured (sensor) data of real systems. The approach is more general since it generates models for every system detached from the scientific background. Additionally, this approach can be used in a more general sense, since it is able to automatically identify correlations in the data. The method can be classified as a multivariate data regression analysis. In contrast to many other data regression methods this variant is also able to identify correlations of products of variables and not only of single variables. This enables a far more precise and better representation of causal correlations. The basis and the explanation of this method come from an analytical background: the series expansion. Another advantage of this technique is the possibility of real-time adaptation of the generated models during operation. Herewith system changes due to aging, wear or perturbations from the environment can be taken into account, which is indispensable for realistic scenarios. Since these data driven models can be evaluated very efficiently and with high precision, they can be used in mathematical optimization algorithms that minimize a cost function, e.g. time, energy consumption, operational costs or a mixture of them, subject to additional constraints. The proposed method has successfully been tested in several complex applications and with strong industrial requirements. The generated models were able to simulate the given systems with an error in precision less than one percent. Moreover the automatic identification of the correlations was able to discover so far unknown relationships. To summarize the above mentioned approach is able to efficiently compute high precise and real-time-adaptive data-based models in different fields of industry. Combined with an effective mathematical optimization algorithm like WORHP (We Optimize Really Huge Problems) several complex systems can now be represented by a high precision model to be optimized within the user wishes. The proposed methods will be illustrated with different examples.

Keywords: adaptive modeling, automatic identification of correlations, data based modeling, optimization

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Authors: Roya Maqami, Kaveh Qaderi Bagajan, Mohammad Mahdi Yousefi, Saeed Moradi

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The purpose of this study is to investigate the efficacy of solution-focused group therapy on improving the depressed mothers of child abuser families. This study was carried out in the form of a semi-pilot, pre-test and post-test on two groups (experimental and control). Subjects include all mothers and their children that are the members of Shush and Naser Khosro child home. Beck Depression Inventory and Child Trauma Questionnaire were used to collect data. First, child abuse questionnaire was completed by children, Then Beck Depression Inventory was completed by their mothers that 22 of them were recognized as depressed and randomly divided in two groups of experimental and control. After applying pre-test for both of these groups, the intervention of solution- focused group therapy was performed in five sessions on experimental group. Finally, post-test was applied on both groups and subsequently in a month, follow-up test was performed. T-test, multivariate variance, and repeated measurement analysis of variance were used to analyze the data. According to the findings, it can be concluded that this therapy leads to the improvement of depressed mother's mood. As a result, the intervention of solution-focused group therapy is useful in order to improve the depressing mood of mothers of child abuser families.

Keywords: child abuse, depressed mothers, child abuser families, solution focused group therapy

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Authors: Samuel Kwaku Essien, Catherine Trask, Niels Koehncke, Brenna Bath

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Background: Low back disorder (LBD) is the most common musculoskeletal problem among farmers, with higher prevalence than other occupations. Operators of tractors and other farm machinery such as combines or all-terrain vehicles (ATV) can have considerable cumulative exposure to whole body vibration (WBV). Although there appears to be an association between LBD and WBV, lack of prospective studies makes the relationship between LBD and WBV unclear. Purpose: This study investigates the association between WBV and LBD among Saskatchewan farmers using a prospective cohort study Methods: The Saskatchewan Farm Injury Cohort Study Phase I (2007) and II (2013) data were used. Baseline data were collected via postal questionnaire on accumulated yearly tractor, combine, and ATV use as well as several covariates to support a biopsychosocial model of LBD. Follow-up data on musculoskeletal symptoms were collected for the 6-year with sample size of 1149. Questions on ‘low back trouble’ (ache, pain, discomfort) experienced in the last 12 months answered by farmer participants as ‘yes’ or ‘no’. A GEE-modified Poisson approach was performed using SPSS 22 and SAS 9.4. Results: Twelve-month Prevalence of LBD was 59.8%. In multivariate analysis of the 6-year follow-up, LBD was associated with ATV operation and tractor operation, with a dose-response relationship for annual accumulated tractor operation. Although combine operation ≥ 61 hrs/year was related to LBD in bivariate analysis, this difference did not persist after adjustment for confounder. Age was found to be a confounder in relationship between WBV and LBD and no interactions were found. Conclusion: Longer annual tractor operation and older age are important predictors of LBD symptoms in farmers. Future research involving direct measurement can help identify appropriate prevention strategies.

Keywords: agriculture, low back disorder, low back pain, occupational health

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Authors: Gulnara Moldasheva

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The research explores the relationship between management responsibility and corporate governance of listed companies in Kazakhstan. This research employs firm level data of randomly selected listed non-financial firms and firm level data “operational” financial sector, consisted from banking sector, insurance companies and accumulated pension funds using multivariate regression analysis under fixed effect model approach. Ownership structure includes institutional ownership, managerial ownership and private investor’s ownership. Management responsibility of the firm is expressed by the decision of the firm on amount of leverage. Results of the cross sectional panel study for non-financial firms showed that only institutional shareholding is significantly negatively correlated with debt to equity ratio. Findings from “operational” financial sector show that leverage is significantly affected only by the CEO/Chair duality and the size of financial institutions, and insignificantly affected by ownership structure. Also, the findings show, that there is a significant negative relationship between profitability and the debt to equity ratio for non-financial firms, which is consistent with pecking order theory. Generally, the found results suggest that corporate governance and a management responsibility play important role in corporate performance of listed firms in Kazakhstan.

Keywords: ownership, corporate governance, debt to equity ratio, corporate performance

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Authors: Kamakshaiah Kolli, R. Seshadri

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Water is a key resource in all economic activities ranging from agriculture to industry. Only a tiny fraction of the planet's abundant water is available to us as fresh water. Assessment of water quality has always been paramount in the field of environmental quality management. It is the foundation for health, hygiene, progress and prosperity. With ever increasing pressure of human population, there is severe stress on water resources. Therefore efficient water management is essential to civil society for betterment of quality of life. The present study emphasizes on the groundwater quality, sources of ground water contamination, variation of groundwater quality and its spatial distribution. The bases for groundwater quality assessment are groundwater bodies and representative monitoring network enabling determination of chemical status of groundwater body. For this study, water samples were collected from various areas of the entire corporation area of Guntur. Water is required for all living organisms of which 1.7% is available as ground water. Water has no calories or any nutrients, but essential for various metabolic activities in our body. Chemical and physical parameters can be tested for identifying the portability of ground water. Electrical conductivity, pH, alkalinity, Total Alkalinity, TDS, Calcium, Magnesium, Sodium, Potassium, Chloride, and Sulphate of the ground water from Guntur district: Different areas of the District were analyzed. Our aim is to check, if the ground water from the above areas are potable or not. As multivariate are present, Data mining technique using JRIP rules was employed for classifying the ground water.

Keywords: groundwater, water quality standards, potability, data mining, JRIP, PCA, classification

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Authors: Sandeep Sharma, Sarabjit Singh

Abstract:

As per the user demand and growth trends of large free data the storage solutions are now becoming more challenge-able to protect, store and to retrieve data. The days are not so far when the storage companies and organizations are start saying 'no' to store our valuable data or they will start charging a huge amount for its storage and protection. On the other hand as per the environmental conditions it becomes challenge-able to maintain and establish new data warehouses and data centers to protect global warming threats. A challenge of small data is over now, the challenges are big that how to manage the exponential growth of data. In this paper we have analyzed the growth trend of big data and its future implications. We have also focused on the impact of the unstructured data on various concerns and we have also suggested some possible remedies to streamline big data.

Keywords: big data, unstructured data, volume, variety, velocity

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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: Bry X., Trottier C., Mortier F., Cornu G., Verron T.

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We address component-based regularization of a Multivariate Generalized Linear Model (MGLM). A set of random responses Y is assumed to depend, through a GLM, on a set X of explanatory variables, as well as on a set T of additional covariates. X is partitioned into R conceptually homogeneous blocks X1, ... , XR , viewed as explanatory themes. Variables in each Xr are assumed many and redundant. Thus, Generalised Linear Regression (GLR) demands regularization with respect to each Xr. By contrast, variables in T are assumed selected so as to demand no regularization. Regularization is performed searching each Xr for an appropriate number of orthogonal components that both contribute to model Y and capture relevant structural information in Xr. We propose a very general criterion to measure structural relevance (SR) of a component in a block, and show how to take SR into account within a Fisher-scoring-type algorithm in order to estimate the model. We show how to deal with mixed-type explanatory variables. The method, named THEME-SCGLR, is tested on simulated data.

Keywords: Component-Model, Fisher Scoring Algorithm, GLM, PLS Regression, SCGLR, SEER, THEME

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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: Chunhua Liao, Jinfei Wang, Bo Shan, Yang Song, Yongjun He, Taifeng Dong

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Winter wheat is one of the main crops in Canada. Forecasting of within-field variability of yield in winter wheat at the early stages is essential for precision farming. However, the crop yield modelling based on high spatial resolution satellite data is generally affected by the lack of continuous satellite observations, resulting in reducing the generalization ability of the models and increasing the difficulty of crop yield forecasting at the early stages. In this study, the correlations between Sentinel-2 data (vegetation indices and reflectance) and yield data collected by combine harvester were investigated and a generalized multivariate linear regression (MLR) model was built and tested with data acquired in different years. It was found that the four-band reflectance (blue, green, red, near-infrared) performed better than their vegetation indices (NDVI, EVI, WDRVI and OSAVI) in wheat yield prediction. The optimum phenological stage for wheat yield prediction with highest accuracy was at the growing stages from the end of the flowering to the beginning of the filling stage. The best MLR model was therefore built to predict wheat yield before harvest using Sentinel-2 data acquired at the end of the flowering stage. Further, to improve the ability of the yield prediction at the early stages, three simple unsupervised domain adaptation (DA) methods were adopted to transform the reflectance data at the early stages to the optimum phenological stage. The winter wheat yield prediction using multiple vegetation indices showed higher accuracy than using single vegetation index. The optimum stage for winter wheat yield forecasting varied with different fields when using vegetation indices, while it was consistent when using multispectral reflectance and the optimum stage for winter wheat yield prediction was at the end of flowering stage. The average testing RMSE of the MLR model at the end of the flowering stage was 604.48 kg/ha. Near the booting stage, the average testing RMSE of yield prediction using the best MLR was reduced to 799.18 kg/ha when applying the mean matching domain adaptation approach to transform the data to the target domain (at the end of the flowering) compared to that using the original data based on the models developed at the booting stage directly (“MLR at the early stage”) (RMSE =1140.64 kg/ha). This study demonstrated that the simple mean matching (MM) performed better than other DA methods and it was found that “DA then MLR at the optimum stage” performed better than “MLR directly at the early stages” for winter wheat yield forecasting at the early stages. The results indicated that the DA had a great potential in near real-time crop yield forecasting at the early stages. This study indicated that the simple domain adaptation methods had a great potential in crop yield prediction at the early stages using remote sensing data.

Keywords: wheat yield prediction, domain adaptation, Sentinel-2, within-field scale

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Authors: Nulu Nanono

Abstract:

Background: The Ugandan national health policy and the national population policy all recognize the need to increase access to quality, affordable, acceptable and sustainable contraceptive services for all people but provision and utilization of quality services remains low. Two contraceptive methods are categorized as long-acting temporary methods: intrauterine contraceptive devices (IUCDs) and implants. Copper-containing IUCDs, generally available in Ministry of Health (MoH) family planning programs and is effective for at least 12 years while Implants, depending on the type, last for up to three to seven years. Uganda’s current policy and political environment are favorable towards achieving national access to quality and safe contraceptives for all people as evidenced by increasing government commitments and innovative family planning programs. Despite the increase of modern contraception use from 14% to 26%, long acting reversible contraceptive (LARC) utilization has relatively remained low with less than 5% using IUDs & Implants which in a way explains Uganda’s persistent high fertility rates. Main question/hypothesis: The purpose of the study was to examine relationship between the demographic, socio-economic characteristics of women, health facility factors and long acting reversible contraception utilization. Methodology: LARC utilization was investigated comprising of the two questions namely are you or your partner currently doing something or using any method to delay or avoid getting pregnant? And which method or methods are you using? Data for the study was sourced from the 2016 Uganda Performance Monitoring and Accountability 2020 Survey comprising of 3816 female respondents aged 15 to 49 years. The analysis was done using the Chi-squared tests and the probit regression at bivariate and multivariate levels respectively. The model was further tested for validity and normality of the residuals using the Sharipo wilks test and test for kurtosis and skewness. Results: The results showed the model the age, parity, marital status, region, knowledge of LARCs, availability of LARCs to be significantly associated with long acting contraceptive utilization with p value of less than 0.05. At the multivariate analysis level, women who had higher parities (0.000) tertiary education (0.013), no knowledge about LARCs (0.006) increases their probability of using LARCs. Furthermore while women age 45-49, those who live in the eastern region reduces their probability of using LARCs. Knowledge contribution: The findings of this study join the debate of prior research in this field and add to the body of knowledge related to long acting reversible contraception. An outstanding and queer finding from the study is the non-utilization of LARCs by women who are aware and have knowledge about them, this may be an opportunity for further research to investigate the attribution to this.

Keywords: contraception, long acting, utilization, women (15-49)

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Authors: Maria de Nazaré Moraes Soares, Silvia Maria Dias Pedro Rebouças, José Carlos Lázaro

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The Solidarity Economy (SE) acts in the re-articulation of the economic field to the other spheres of social action. The significant participation of women in SE resulted in the formation of a national network of self-managed enterprises in Brazil: The Solidarity and Feminist Economy Network (SFEN). The objective of the research is to identify factors of gender justice and feminist self-management practices that adhere to the reality of women in SE enterprises. The conceptual apparatus related to feminist studies in this research covers Nancy Fraser approaches on gender justice, and Patricia Yancey Martin approaches on feminist management practices, and authors of postcolonial feminism such as Mohanty and Maria Lugones, who lead the discussion to peripheral contexts, a necessary perspective when observing the women’s movement in SE. The research has a quantitative nature in the phases of data collection and analysis. The data collection was performed through two data sources: the database mapped in Brazil in 2010-2013 by the National Information System in Solidary Economy and 150 questionnaires with women from 16 enterprises in SFEN, in a state of Brazilian northeast. The data were analyzed using the multivariate statistical technique of Factor Analysis. The results show that the factors that define gender justice and feminist self-management practices in SE are interrelated in several levels, proving statistically the intersectional condition of the issue of women. The evidence from the quantitative analysis allowed us to understand the dimensions of gender justice and feminist management practices intersectionality; in this sense, the non-distribution of domestic work interferes in non-representation of women in public spaces, especially in peripheral contexts. The study contributes with important reflections to the studies of this area and can be complemented in the future with a qualitative research that approaches the perspective of women in the context of the SE self-management paradigm.

Keywords: feminist management practices, gender justice, self-management, solidarity economy

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Authors: Yang Bao, Shi Wei Deng, WangQun Lin

Abstract:

This paper introduces the concept and principle of data cleaning, analyzes the types and causes of dirty data, and proposes several key steps of typical cleaning process, puts forward a well scalability and versatility data cleaning framework, in view of data with attribute dependency relation, designs several of violation data discovery algorithms by formal formula, which can obtain inconsistent data to all target columns with condition attribute dependent no matter data is structured (SQL) or unstructured (NoSQL), and gives 6 data cleaning methods based on these algorithms.

Keywords: data cleaning, dependency rules, violation data discovery, data repair

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Authors: William Elnemer, Nauman Hussain, Samir Al-Ali, Henry Shu, Diane Ghanem, Babar Shafiq

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Introduction: The incidence of infection in open tibial shaft injuries varies depending on the severity of the injury, with rates ranging from 1.8% for Gustilo-Anderson type I to 42.9% for type IIIB fractures. The timely administration of antibiotics upon presentation to the emergency department (ED) is an essential component of fracture management, and evidence indicates that prompt delivery of antibiotics is associated with improved outcomes. The objective of this study is to identify factors that contribute to the expedient administration of antibiotics. Methods: This is a retrospective study of open tibial shaft fractures at an academic Level I trauma center. Current Procedural Terminology (CPT) codes identified all patients treated for open tibial shaft fractures between 2015 and 2021. Open fractures were identified by reviewing ED and provider notes, and with ballistic fractures were considered open. Chart reviews were performed to extract demographics, fracture characteristics, postoperative outcomes, time to operative room, time to antibiotic order, and delivery. Univariate statistical analysis compared patients who received early antibiotics (EA), which were delivered within one hour of ED presentation, and those who received late antibiotics (LA), which were delivered outside of one hour of ED presentation. A multivariate analysis was performed to investigate patient, fracture, and transport/ED characteristics contributing to faster delivery of antibiotics. The multivariate analysis included the dependent variables: ballistic fracture, activation of Delta Trauma, Gustilo-Andersen (Type III vs. Type I and II), AO-OTA Classification (Type C vs. Type A and B), arrival between 7 am and 11 pm, and arrival via Emergency Medical Services (EMS) or walk-in. Results: Seventy ED patients with open tibial shaft fractures were identified. Of these, 39 patients (55.7%) received EA, while 31 patients (44.3%) received LA. Univariate analysis shows that the arrival via EMS as opposed to walk-in (97.4% vs. 74.2%, respectively, p = 0.01) and activation of Delta Trauma (89.7% vs. 51.6%, respectively, p < 0.001) was significantly higher in the EA group vs. the LA group. Additionally, EA cases had significantly shorter intervals between the antibiotic order and delivery when compared to LA cases (0.02 hours vs. 0.35 hours, p = 0.007). No other significant differences were found in terms of postoperative outcomes or fracture characteristics. Multivariate analysis shows that a Delta Trauma Response, arrival via EMS, and presentation between 7 am and 11 pm were independent predictors of a shorter time to antibiotic administration (Odds Ratio = 11.9, 30.7, and 5.4, p = 0.001, 0.016, and 0.013, respectively). Discussion: Earlier antibiotic delivery is associated with arrival to the ED between 7 am and 11 pm, arrival via EMS, and a coordinated Delta Trauma activation. Our findings indicate that in cases where administering antibiotics is critical to achieving positive outcomes, it is advisable to employ a coordinated Delta Trauma response. Hospital personnel should be attentive to the rapid administration of antibiotics to patients with open fractures who arrive via walk-in or during late-night hours.

Keywords: antibiotics, emergency department, fracture management, open tibial shaft fractures, orthopaedic surgery, time to or, trauma fractures

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