Search results for: multivariate statistical

Authors: Tzu-Jung Tseng, Pei-Hsuen Han, Tsung-Hsueh Lu

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Background: Ensuring patients with ST-elevation myocardial infarction (STEMI) access to hospitals that could perform percutaneous coronary intervention (PCI) in time is an important concern of healthcare managers. One commonly used the method to assess the coverage of population access to PCI hospital is the use GIS-estimated linear distance (crow's fly distance) between the district centroid and the nearest PCI hospital. If the distance is within a given distance (such as 20 km), the entire population of that district is considered to have appropriate access to PCI. The premise of using district centroid to estimate the coverage of population resident in that district is that the people live in the district are evenly distributed. In reality, the population density is not evenly distributed within the administrative district, especially in rural districts. Fortunately, the Taiwan government released basic statistical area (on average 450 population within the area) recently, which provide us an opportunity to estimate the coverage of population access to PCI services more accurate. Objectives: We aimed in this study to compare the population covered by a give PCI hospital according to traditional administrative district versus basic statistical area. We further examined if the differences between two geographic units used would be larger in a rural area than in urban area. Method: We selected two hospitals in Tainan City for this analysis. Hospital A is in urban area, hospital B is in rural area. The population in each traditional administrative district and basic statistical area are obtained from Taiwan National Geographic Information System, Ministry of Internal Affairs. Results: Estimated population live within 20 km of hospital A and B was 1,515,846 and 323,472 according to traditional administrative district and was 1,506,325 and 428,556 according to basic statistical area. Conclusion: In urban area, the estimated access population to PCI services was similar between two geographic units. However, in rural areas, the access population would be overestimated.

Keywords: accessibility, basic statistical area, modifiable areal unit problem (MAUP), percutaneous coronary intervention (PCI)

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Authors: Mohamed Hrouda

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The Principal Component Analysis (PCA) was performed on a dataset comprising 41 biomarker concentrations from twenty-three core source rocks samples and seven oil samples from different location, with the objective of establishing the major sources of variance within the steranes, tricyclic terpanes, hopanes, and triaromatic steroid. This type of analysis can be used as an aid when deciding which molecular biomarker maturity, source facies or depositional environment parameters should be plotted, because the principal component loadings plots tend to extract the biomarker variables related to maturity, source facies or depositional environment controls. Facies characterization of the source rock samples separate the Silurian and Devonian source rock samples into three groups. Maturity evaluation of source rock samples based on biomarker and aromatic hydrocarbon distributions indicates that not all the samples are strongly affected by maturity, the Upper Devonian samples from wells located in the northern part of the basin are immature, whereas the other samples which have been selected from the Lower Silurian are mature and have reached the main stage of the oil window, the Lower Silurian source rock strata revealed a trend of increasing maturity towards the south and southwestern part of Ghadames Basin. Most of the facies-based parameters employed in this project using biomarker distributions clearly separate the oil samples into three groups. Group I contain oil samples from wells within Al-Wafa oil field Located in the south western part of the basin, Group II contains oil samples collected from Al-Hamada oil field complex in the south and the third group contains oil samples collected from oil fields located in the north

Keywords: Ghadamis basin, geochemistry, silurian, devonian

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Authors: Nargess Fasihmardanloo

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The aim of this study was to comparatively study the motivations of women to physical activity in Iran and selected Arab countries Based on individual, social and Islamic components. The present study was a descriptive comparative study that was performed by field method. The statistical population of the study included female athletes in Iran and Arab countries. A total of 184 people from Iran and 179 people from Arab countries (Iraq, UAE, and Jordan) were selected through available sampling as a research sample. The research tool included a questionnaire. The validity of the questionnaire was confirmed and its reliability in a pilot study was 0.95 through Cronbach's alpha. The questionnaire was translated into Persian in Iran and translated into Arabic for the selected countries and was provided to the participants electronically and through cyberspace. Finally, 363 questionnaires were collected. Manova multivariate analysis of variance using spss22 software was used to analyze the data. Findings showed that between Iranian women athletes and women athletes in selected Arab countries in the components of intrapersonal motivation (p = 0.009 and f = 6.978), interpersonal motivation (p = 0.050 and f = 3.875), There is a significant difference between social motives (p = 0.001 and f = 27.619) and Islamic motives (p = 0.001 and f = 11.339). And this difference is significant at the level of p <0.01 and p <0.05. In other words, in the component of intrapersonal motivations, the average of this component in Iranian female athletes (M = 59.77) was higher than female athletes in selected Arab countries (M = 55.53). In the interpersonal motivations component, the average of this component in Iranian female athletes (M = 26.87) was lower than in female athletes in selected Arab countries (M = 28.62). In the component of social motivations, the average of this component in Iranian female athletes (M = 33.08) was lower than female athletes in selected Arab countries (M = 39.64). In the component of Islamic motives, the average of this component in Iranian female athletes (M = 21.55) was higher than female athletes in selected Arab countries (M = 19.04).

Keywords: athletes, motivation, women, Islamic

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Authors: Kamel Malik Bensafta, Gervasio Bensafta

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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: Eman W. Boghdady, A. R. Shehata, M. A. Azem

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Database (DB) security demands permitting authorized users and prohibiting non-authorized users and intruders actions on the DB and the objects inside it. Organizations that are running successfully demand the confidentiality of their DBs. They do not allow the unauthorized access to their data/information. They also demand the assurance that their data is protected against any malicious or accidental modification. DB protection and confidentiality are the security concerns. There are four types of controls to obtain the DB protection, those include: access control, information flow control, inference control, and cryptographic. The cryptographic control is considered as the backbone for DB security, it secures the DB by encryption during storage and communications. Current cryptographic techniques are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, etc.) and chaos cryptography using continuous (Chau, Rossler, Lorenz, etc.) or discreet (Logistics, Henon, etc.) algorithms. The important characteristics of chaos are its extreme sensitivity to initial conditions of the system. In this paper, DB-security systems based on chaotic algorithms are described. The Pseudo Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented using Matlab and their statistical properties are evaluated using NIST and other statistical test-suits. Then, these algorithms are used to secure conventional DB (plaintext), where the statistical properties of the ciphertext are also tested. To increase the complexity of the PRNGs and to let pass all the NIST statistical tests, we propose two hybrid PRNGs: one based on two chaotic Logistic maps and another based on two chaotic Henon maps, where each chaotic algorithm is running side-by-side and starting from random independent initial conditions and parameters (encryption keys). The resulted hybrid PRNGs passed the NIST statistical test suit.

Keywords: algorithms and data structure, DB security, encryption, chaotic algorithms, Matlab, NIST

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Authors: Mekni Sabrine, Nouira Mariem

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Background and aim: Allogeneic hematopoietic stem cell transplantation is a curative treatment for several hematological diseases; however, it has a non-negligible morbidity and mortality depending on several prognostic factors, including pre-transplant hyperferritinemia. The aim of our study was to estimate the impact of hyperferritinemia on survivals and on the occurrence of post-transplant complications. Methods: It was a longitudinal study conducted over 8 years and including all patients who had a first allograft. The impact of pretransplant hyperferritinemia (ferritinemia ≥1500) on survivals was studied using the Kaplan Meier method and the COX model for uni- and multivariate analysis. The Khi-deux test and binary logistic regression were used to study the association between pretransplant ferritinemia and post-transplant complications. Results: One hundred forty patients were included with an average age of 26.6 years and a sex ratio (M/F)=1.4. Hyperferritinemia was found in 33% of patients. It had no significant impact on either overall survival (p=0.9) or event -free survival (p=0.6). In multivariate analysis, only the type of disease was independently associated with overall survival (p=0.04) and event-free survival (p=0.002). For post-allograft complications: The occurrence of early documented infections was independently associated with pretransplant hyperferritinemia (p=0.02) and the presence of acute graft versus host disease( GVHD) (p<10-3). The occurrence of acute GVHD was associated with early documented infection (p=0.002) and Cytomegalovirus reactivation (p<10-3). The occurrence of chronic GVHD was associated with the presence of Cytomegalovirus reactivation (p=0.006) and graft source (p=0.009). Conclusion: Our study showed the significant impact of pre-transplant hyperferritinemia on the occurrence of early infections but not on survivals. Early and more accurate assessment iron overload by other tests such as liver magnetic resonance imaging with initiation of chelating treatment could prevent the occurrence of such complications after transplantation.

Keywords: allogeneic, transplants, ferritin, survival

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Authors: A. Clementking, C. Jothi Venkateswaran

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Mathematical and computational functionalities such as descriptive mining, optimization, and predictions are espoused to resolve natural resource planning. The water quality prediction and its attributes influence determinations are adopted optimization techniques. The water properties are tainted while merging water resource one with another. This work aimed to predict influencing water resource distribution connectivity in accordance to water quality and sediment using an innovative proposed master-slave neural network back-propagation model. The experiment results are arrived through collecting water quality attributes, computation of water quality index, design and development of neural network model to determine water quality and sediment, master–slave back propagation neural network back-propagation model to determine variations on water quality and sediment attributes between the water resources and the recommendation for connectivity. The homogeneous and parallel biochemical reactions are influences water quality and sediment while distributing water from one location to another. Therefore, an innovative master-slave neural network model [M (9:9:2)::S(9:9:2)] designed and developed to predict the attribute variations. The result of training dataset given as an input to master model and its maximum weights are assigned as an input to the slave model to predict the water quality. The developed master-slave model is predicted physicochemical attributes weight variations for 85 % to 90% of water quality as a target values.The sediment level variations also predicated from 0.01 to 0.05% of each water quality percentage. The model produced the significant variations on physiochemical attribute weights. According to the predicated experimental weight variation on training data set, effective recommendations are made to connect different resources.

Keywords: master-slave back propagation neural network model(MSBPNNM), water quality analysis, multivariate analysis, environmental mining

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Authors: Parimalakrishnan Sundararjan, Madheswaran Murugan, Dhanya Dharman, Yatindra Kumar, Sudhir Singh Gangwar, Guru Prasad Mohanta

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Antibiotic resistance AR is a global issue, India started to redress the issues of antibiotic resistance late and it plans to have: active surveillance of microbial resistance and promote appropriate use of antibiotics. The present study attempted to achieve appropriate use of antibiotics through pharmacists’ intervention at practice point. In a quasi-experimental prospective cohort study, the cases with bacteremia from four hospitals were identified during 2015 and 2016 for intervention. The pharmacists centered intervention: active screening of each prescription and comparing with the selection of antibiotics with susceptibility of the bacteria. Wherever irrationality noticed, it was brought to the notice of the treating physician for making changes. There were two groups: intervention group and control group without intervention. The active screening and intervention in 915 patients has reduced therapeutic regimen time in patients with bacteremia. The intervention group showed the decreased duration of hospital stay 3.4 days from 5.1 days. Further, multivariate modeling of patients who were in control group showed that patients in the intervention group had a significant decrease in both duration of hospital stay and infection-related mortality. Unlike developed countries, pharmacists are not active partners in patient care in India. This unique attempt of pharmacist’ invention was planned in consultation with hospital authorities which proved beneficial in terms of reducing the duration of treatment, hospital stay, and infection-related mortality. This establishes the need for a collaborative decision making among the health workforce in patient care at least for promoting rational use of antibiotics, an attempt to combat resistance.

Keywords: antibiotics resistance, intervention, bacteremia, multivariate modeling

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Authors: Alireza Ansariyar, Safieh Laaly

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Over the last decades, the vehicle industry has shown increased interest in integrating autonomous, connected, and electrical technologies in vehicle design with the primary hope of improving mobility and road safety while reducing transportation’s environmental impact. Using the State of Maryland (M.D.) in the United States as a pilot study, this research investigates CAVs’ fuel consumption and air pollutants (C.O., PM, and NOx) and utilizes meaningful linear regression models to predict CAV’s environmental effects. Maryland transportation network was simulated in VISUM software, and data on a set of variables were collected through a comprehensive survey. The number of pollutants and fuel consumption were obtained for the time interval 2010 to 2021 from the macro simulation. Eventually, four linear regression models were proposed to predict the amount of C.O., NOx, PM pollutants, and fuel consumption in the future. The results highlighted that CAVs’ pollutants and fuel consumption have a significant correlation with the income, age, and race of the CAV customers. Furthermore, the reliability of four statistical models was compared with the reliability of macro simulation model outputs in the year 2030. The error of three pollutants and fuel consumption was obtained at less than 9% by statistical models in SPSS. This study is expected to assist researchers and policymakers with planning decisions to reduce CAV environmental impacts in M.D.

Keywords: connected and autonomous vehicles, statistical model, environmental effects, pollutants and fuel consumption, VISUM, linear regression models

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi

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In this paper, Bayesian online inference in models of data series are constructed by change-points algorithm, which separated the observed time series into independent series and study the change and variation of the regime of the data with related statistical characteristics. variation of statistical characteristics of time series data often represent separated phenomena in the some dynamical system, like a change in state of brain dynamical reflected in EEG signal data measurement or a change in important regime of data in many dynamical system. In this paper, prediction algorithm for studying change point location in some time series data is simulated. It is verified that pattern of proposed distribution of data has important factor on simpler and smother fluctuation of hazard rate parameter and also for better identification of change point locations. Finally, the conditions of how the time series distribution effect on factors in this approach are explained and validated with different time series databases for some dynamical system.

Keywords: time series, fluctuation in statistical characteristics, optimal learning, change-point algorithm

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Authors: Go Bong Choi, Shin Je Lee, Sung Jin Yoo, Gibaek Lee, Jong Min Lee

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In South Korea, it is difficult to obtain data for statistical pipe assessment. In this paper, to address these issues, we find that various statistical model presented before is how data mixed with noise and are whether apply in South Korea. Three major type of model is studied and if data is presented in the paper, we add noise to data, which affects how model response changes. Moreover, we generate data from model in paper and analyse effect of noise. From this we can find robustness and applicability in Korea of each model.

Keywords: proportional hazard model, survival model, water main deterioration, ecological sciences

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Authors: Mohieddine Benghersallah, Lakhdar Boulanouar, Salim Belhadi

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Currently, higher production rate with required quality and low cost is the basic principle in the competitive manufacturing industry. This is mainly achieved by using high cutting speed and feed rates. Elevated temperatures in the cutting zone under these conditions shorten tool life and adversely affect the dimensional accuracy and surface integrity of component. Thus it is necessary to find optimum cutting conditions (cutting speed, feed rate, machining environment, tool material and geometry) that can produce components in accordance with the project and having a relatively high production rate. Response surface methodology is a collection of mathematical and statistical techniques that are useful for modelling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. The work presented in this paper examines the effects of cutting parameters (cutting speed, feed rate and depth of cut) on to the surface roughness through the mathematical model developed by using the data gathered from a series of milling experiments performed.

Keywords: Statistical analysis (RSM), Bearing steel, Coating inserts, Tool life, Surface Roughness, End milling.

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Authors: Rezvan Hosseinian

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Aim: Systemic sclerosis (SSc) is a chronic connective tissue disease with the clinical hallmark of skin thickening and tethering. The correlation of musculoskeletal features with other parameters should be considered in SSc patients. Methods: We reviewed the records of all patients who had more than one visit and standard anteroposterior radiography of hand. We used univariate analysis, and factors with p<0.05 were included in logistic regression to find out dependent factors. Results: Overall, 180 SSc patients were enrolled in our study, 161 (89.4%) of whom were women. The median age (IQR) was 47.0 years (16), and 52% had a diffuse subtype of the disease. In multivariate analysis, tendon friction rubs (TFRs) were associated with the presence of calcinosis, muscle tenderness, and flexion contracture (FC) on physical examination (p<0.05). Arthritis showed no differences in the two subtypes of the disease (p=0.98), and in multivariate analysis, there were no correlations between radiographic arthritis and serological and clinical features. The radiographic results indicated that disease duration correlated with joint erosion, acro-osteolysis, resorption of the distal ulna, calcinosis and radiologic FC (p< 0.05). Acro-osteolysis was more frequent in the dcSSc subtype, TFRs, and anti-TOPO I antibody. Radiologic FC showed an association with skin score, calcinosis and haematocrit <30% (p<0.05). Joint flexion on radiography was associated with disease duration, modified Rodnan skin score, calcinosis, and low hematocrit (P<0.01). Conclusion: Disease duration was a main dependent factor for developing joint erosion, acro-osteolysis, bone resorption, calcinosis, and flexion contracture on hand radiography. Acro-osteolysis presented in the severe form of the disease. Acro-osteolysis was the only dependent variable associated with bone demineralization.

Keywords: disease subsets, hand radiography, joint erosion, sclerosis

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Authors: Nasrin Azarbani

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Aim: Systemic sclerosis (SSc) is a chronic connective tissue disease with the clinical hallmark of skin thickening and tethering. Correlation of musculoskeletal features with other parameters should be considered in SSc patients. Methods: We reviewed the records of all patients who had more than one visit and standard anteroposterior radiography of hand. We used univariate analysis, and factors with p<0.05 were included in logistic regression to find out dependent factors. Results: Overall, 180 SSc patients were enrolled in our study, 161 (89.4%) of whom were women. Median age (IQR) was 47.0 years (16), and 52% had diffuse subtype of the disease. In multivariate analysis, tendon friction rubs (TFRs) was associated with the presence of calcinosis, muscle tenderness, and flexion contracture (FC) on physical examination (p<0.05). Arthritis showed no differences in the two subtypes of the disease (p=0.98), and in multivariate analysis, there were no correlations between radiographic arthritis and serological and clinical features. The radiographic results indicated that disease duration correlated with joint erosion, acro-osteolysis, resorption of distal ulna, calcinosis and radiologic FC (p< 0.05). Acro-osteolysis was more frequent in the dcSSc subtype, TFRs, and anti-TOPO I antibody. Radiologic FC showed an association with skin score, calcinosis and haematocrit <30% (p<0.05). Joint flexion on radiography was associated with disease duration, modified Rodnan skin score, calcinosis, and low haematocrit (P<0.01). Conclusion: Disease duration was a main dependent factor for developing joint erosion, acro-osteolysis, bone resorption, calcinosis, and flexion contracture on hand radiography. Acro-osteolysis presented in the severe form of the disease. Acro-osteolysis was the only dependent variable associated with bone demineralization.

Keywords: sclerosis, disease subsets, joint erosion, musculoskeletal

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Authors: Mahmoud Samkan

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In this paper, the design and assessment of new coordination between Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method are proposed. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is handled as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to seek for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is enhanced. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is executed to validate the robustness of coordinated controller versus uncoordinated one.

Keywords: SVC, PSSs, multimachine power system, coordinated design, bacteria swarm optimization, statistical assessment

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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: Himansu, Bedanga Talukdar

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The aim of present study is to investigate the prevalence of various health outcomes and quality of life and analyzes the moderating role of social capital on health outcomes (i.e., self-rated good health (SRH), depression, functional health and quality of life) among elderly in India. Using WHO Study on Global AGEing and adults health (SAGE) data, with sample of 6559 elderly between 50 and above (Mage=61.81, SD=9.00) age were selected for analysis. Multivariate analysis accessed the prevalence of SRH, depression, functional limitation and quality of life among older adults. Logistic regression evaluates the effect of social capital along with other co-founders on SRH, depression, and functional limitation, whereas linear regression evaluates the effect of social capital with other co-founders on quality of life (QoL) among elderly. Empirical results reveal that (74%) of respondents were married, (70%) having low social action, (46%) medium sociability, (45%) low trust-solidarity, (58%) high safety, (65%) medium civic engagement and 37% reported medium psychological resources. The multivariate analysis, explains (SRH) is associated with age, female, having education, higher social action great trust, safety and greater psychological resources. Depression among elderly is greatly related to age, sex, education and higher wealth, higher sociability, having psychological resources. QoL is negatively associated with age, sex, being Muslim, whereas positive associated with higher education, currently married, civic engagement, having wealth, social action, trust and solidarity, safeness, and strong psychological resources.

Keywords: depressive symptom, functional limitation, older adults, quality of life, self rated health, social capital

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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: Ramkumar Gunasekaran, John Cater, Vinod Suresh, Haribalan Kumar

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The main objective of this project is to develop a statistical shape model using principal component analysis that could be used for analyzing the shape of the human airway. The ultimate goal of this project is to identify geometric risk factors for diagnosis and management of Obstructive Sleep Apnoea (OSA). Anonymous CBCT scans of 25 individuals were obtained from the Otago Radiology Group. The airways were segmented between the hard-palate and the aryepiglottic fold using snake active contour segmentation. The point data cloud of the segmented images was then fitted with a bi-cubic mesh, and pseudo landmarks were placed to perform PCA on the segmented airway to analyze the shape of the airway and to find the relationship between the shape and OSA risk factors. From the PCA results, the first four modes of variation were found to be significant. Mode 1 was interpreted to be the overall length of the airway, Mode 2 was related to the anterior-posterior width of the retroglossal region, Mode 3 was related to the lateral dimension of the oropharyngeal region and Mode 4 was related to the anterior-posterior width of the oropharyngeal region. All these regions are subjected to the risk factors of OSA.

Keywords: medical imaging, image processing, FEM/BEM, statistical modelling

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Authors: Mahnaz Motamedi, Mohammad Shahbazi, Shahrzad Rahimi-Naghani, Mehrdad Salehi

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Introduction and Aim: This study assessed sexual behaviours among men and women aged 15 to 49 years in Tehran. Material and Methods: This was a cross-sectional study conducted on 755 men and women aged 15 to 49 years who were residents of Tehran. To select the participants, a multistage, cluster, random sampling method was used and included different regions of Tehran. The data were collected using the WHO-endorsed Questionnaire of Sexual and Reproductive Health. Descriptive, bivariate, and multivariate analyses were conducted using SPSS version 20. Sexual and reproductive health (SRH) behaviours was a scale variable that was constructed from items of six sections: sexual experiences, characteristics of the first sexual partner, characteristics of the first intercourse, next sexual contact and the consequences of the first sexual contact, homosexual experiences and the causes of sexual abstinence. Results: The mean age at the time of sexual intercourse with penetration (vaginal, anal) was 19.88 in men and 21.82 in women. Multivariate analysis using linear regression showed that by controlling for other variables, gender had a significant relationship with having sexual experience, mean age of first sexual intercourse, and being multi-partner. Thus, women with sexual experience were 0.158 units less than men. The mean age of first intercourse in women was 1.57 units higher than men and being a multi-partner in women was 0.247 less than men (P < 0.001). Sexual experience in very religious and relatively religious individuals was 0.332 and 0.218 units less than those for whom religion did not matter (P < 0.001). 25.6% of men and 40.7% of women who did not have sexual experience at the time of the study stated that their reason for abstinence was their unwillingness to have sex (P < 0.05). 35.9% of men and 16.5% of women stated that the reason for abstinence was not providing a suitable opportunity (P < 0.001). 4.7% of men and 1.7% of women had sexual attraction to the same sex. The difference between men and women was significant (P < 0.001). Conclusion: Sexual relation is also present in singles and younger groups and is not limited to married or final marriage candidates. Therefore, more evaluation should be done in national research and interventions for sexual and reproductive health services should be done at the macro level of policy making.

Keywords: sexual behaviours, Iranian men and women, Iran, cross-sectional study

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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: Adeyinka Adeniran, Omowunmi Bakare, Esther Oluwole, Florence Chieme, Temitope Durojaiye, Modupe Akinyinka, Omobola Ojo, Babatunde Olujobi, Marcus Ilesanmi, Akintunde Ogunsakin

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Introduction: Globally, COVID-19 has greatly impacted the human race physically, socially, mentally, and economically. However, healthcare workers seemed to bear the greatest impact. The study, therefore, sought to assess the impact of COVID-19 on the primary healthcare workers in Ekiti, South-west Nigeria. Methods: The study was a cross-sectional descriptive study using a quantitative data collection method of 716 primary healthcare workers in Ekiti state. Respondents were selected using an online convenience sampling method via their social media platforms. Data was collected, collated, and analyzed using SPSS version 25 software and presented as frequency tables, mean and standard deviation. Bivariate and multivariate analyses were conducted using a t-test, and the level of statistical significance was set at p<0.05. Results: Less than half (47.1%) of respondents were between 41-50 age group and a mean age of 44.4+6.4SD. A majority (89.4%) were female, and almost all (96.2%) were married. More than (90%) had ever heard of Coronavirus, and (85.8%) had to spend more money on activities of daily living such as transportation (90.1%), groceries (80.6%), assisting relations (95.8%) and sanitary measures (disinfection) at home (95.0%). COVID-19 had a huge negative impact on about (89.7%) of healthcare workers, with a mean score of 22+4.8. Conclusion: COVID-19 negatively impacted the daily living and professional duties of primary healthcare workers, which reflected their psychological, physical, social, and economic well-being. Disease outbreaks are unlikely to disappear in the near future. Hence, global proactive interventions and homegrown measures should be adopted to protect healthcare workers and save lives.

Keywords: Covid-19, health workforce, primary health care, health systems, depression

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Authors: Vinicius R. Domingues, Luan C. S. M. Ozelim

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The statistical study has become indispensable for various fields of knowledge. Not any different, in Geotechnics the study of probabilistic and statistical methods has gained power considering its use in characterizing the uncertainties inherent in soil properties. One of the situations where engineers are constantly faced is the definition of a probability distribution that represents significantly the sampled data. To be able to discard bad distributions, goodness-of-fit tests are necessary. In this paper, three non-parametric goodness-of-fit tests are applied to a data set computationally generated to test the goodness-of-fit of them to a series of known distributions. It is shown that the use of normal distribution does not always provide satisfactory results regarding physical and behavioral representation of the modeled parameters.

Keywords: Kolmogorov-Smirnov test, Anderson-Darling test, Cramer-Von-Mises test, nonparametric adherence tests

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Authors: Punam Kumari Mandal, Namita Yangden, Bhumika Rai, Achala Niraula, Sabitra Subedi

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introduction: Family planning not only improves women’s health but also promotes gender equality, better child health, and improved education outcomes, including poverty reduction. The objective of this study is to assess the utilization of family planning methods and associated factors in Sunsari, Nepal. methodology: A cross-sectional analytical study was conducted among women of the reproductive age group (15-49 years) in Sunsari in 2020. Nonprobability purposive sampling was used to collect information from 212 respondents through face-to-face interviews using a Semi-structured interview schedule from ward no 1 of Barju rural municipality. Data processing was done by using SPSS “statistics for windows, version 17.0(SPSS Inc., Chicago, III.USA”). Descriptive analysis and inferential analysis (binary logistic regression) were used to find the association of the utilization of family planning methods with selected demographic variables. All the variables with P-value <0.1 in bivariate analysis were included in multivariate analysis. A P-value of <0.05 was considered to indicate statistical significance at a level of significance of 5%. results: This study showed that the mean age and standard deviation of the respondents were 26±7.03, and 91.5 % of respondent’s age at marriage was less than 20 years. Likewise, 67.5% of respondents use any methods of family planning, and 55.2% of respondents use family planning services from the government health facility. Furthermore, education (AOR 1.579, CI 1.013-2.462)., husband’s occupation (AOR 1.095, CI 0.744-1.610)., type of family (AOR 2.741, CI 1.210-6.210)., and no of living son (AOR 0.259 CI 0.077-0.872)are the factors associated with the utilization of family planning methods. conclusion: This study concludes that two-thirds of reproductive-age women utilize family planning methods. Furthermore, education, the husband’s occupation, the type of family, and no of living sons are the factors associated with the utilization of family planning methods. This reflects that awareness through mass media, including behavioral communication, is needed to increase the utilization of family planning methods.

Keywords: family planning methods, utilization. factors, women, community

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Authors: Yanling Li, Linying Ji, Zita Oravecz, Timothy R. Brick, Michael D. Hunter, Sy-Miin Chow

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Assessing several individuals intensively over time yields intensive longitudinal data (ILD). Even though ILD provide rich information, they also bring other data analytic challenges. One of these is the increased occurrence of missingness with increased study length, possibly under non-ignorable missingness scenarios. Multiple imputation (MI) handles missing data by creating several imputed data sets, and pooling the estimation results across imputed data sets to yield final estimates for inferential purposes. In this article, we introduce dynr.mi(), a function in the R package, Dynamic Modeling in R (dynr). The package dynr provides a suite of fast and accessible functions for estimating and visualizing the results from fitting linear and nonlinear dynamic systems models in discrete as well as continuous time. By integrating the estimation functions in dynr and the MI procedures available from the R package, Multivariate Imputation by Chained Equations (MICE), the dynr.mi() routine is designed to handle possibly non-ignorable missingness in the dependent variables and/or covariates in a user-specified dynamic systems model via MI, with convergence diagnostic check. We utilized dynr.mi() to examine, in the context of a vector autoregressive model, the relationships among individuals’ ambulatory physiological measures, and self-report affect valence and arousal. The results from MI were compared to those from listwise deletion of entries with missingness in the covariates. When we determined the number of iterations based on the convergence diagnostics available from dynr.mi(), differences in the statistical significance of the covariate parameters were observed between the listwise deletion and MI approaches. These results underscore the importance of considering diagnostic information in the implementation of MI procedures.

Keywords: dynamic modeling, missing data, mobility, multiple imputation

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Authors: Santanu Chattopadhyay, Gautam Sarkar, Arabinda Das

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This paper presents wavelet based classification of various heart diseases. Electrocardiogram signals of different heart patients have been studied. Statistical natures of electrocardiogram signals for different heart diseases have been compared with the statistical nature of electrocardiograms for normal persons. Under this study four different heart diseases have been considered as follows: Myocardial Ischemia (MI), Congestive Heart Failure (CHF), Arrhythmia and Sleep Apnea. Statistical nature of electrocardiograms for each case has been considered in terms of kurtosis values of two types of wavelet coefficients: approximate and detail. Nine wavelet decomposition levels have been considered in each case. Kurtosis corresponding to both approximate and detail coefficients has been considered for decomposition level one to decomposition level nine. Based on significant difference, few decomposition levels have been chosen and then used for classification.

Keywords: arrhythmia, congestive heart failure, discrete wavelet transform, electrocardiogram, myocardial ischemia, sleep apnea

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Authors: Badreddine Chemali, Boualem Tiliouine

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This article presents the main results of a numerical investigation on the uncertainty of dynamic response of structures with statistically correlated random damping Gamma distributed. A computational method based on a Linear Statistical Model (LSM) is implemented to predict second order statistics for the response of a typical industrial building structure. The significance of random damping with correlated parameters and its implications on the sensitivity of structural peak response in the neighborhood of a resonant frequency are discussed in light of considerable ranges of damping uncertainties and correlation coefficients. The results are compared to those generated using Monte Carlo simulation techniques. The numerical results obtained show the importance of damping uncertainty and statistical correlation of damping coefficients when obtaining accurate probabilistic estimates of dynamic response of structures. Furthermore, the effectiveness of the LSM model to efficiently predict uncertainty propagation for structural dynamic problems with correlated damping parameters is demonstrated.

Keywords: correlated random damping, linear statistical model, Monte Carlo simulation, uncertainty of dynamic response

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Authors: Edlira Donefski, Lorenc Ekonomi, Tina Donefski

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Edgeworth approximation is one of the most important statistical methods that has a considered contribution in the reduction of the sum of standard deviation of the independent variables’ coefficients in a Quantile Regression Model. This model estimates the conditional median or other quantiles. In this paper, we have applied approximating statistical methods in an economical problem. We have created and generated a quantile regression model to see how the profit gained is connected with the realized sales of the cosmetic products in a real data, taken from a local business. The Linear Regression of the generated profit and the realized sales was not free of autocorrelation and heteroscedasticity, so this is the reason that we have used this model instead of Linear Regression. Our aim is to analyze in more details the relation between the variables taken into study: the profit and the finalized sales and how to minimize the standard errors of the independent variable involved in this study, the level of realized sales. The statistical methods that we have applied in our work are Edgeworth Approximation for Independent and Identical distributed (IID) cases, Bootstrap version of the Model and the Edgeworth approximation for Bootstrap Quantile Regression Model. The graphics and the results that we have presented here identify the best approximating model of our study.

Keywords: bootstrap, edgeworth approximation, IID, quantile

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Authors: Arkaprabha Bhattacharyya, Makarand Hastak

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The COVID-19 pandemic is unprecedented in terms of its global reach and economic impacts. Historically, investment in infrastructure development projects has been touted to boost the economic growth of a nation. The State and Local governments responsible for delivering infrastructure assets work under tight budgets. Therefore, it is important to understand which infrastructure projects have the highest potential of boosting economic growth in the post-pandemic era. This paper presents relationships between infrastructure projects and economic growth. Statistical relationships between investment in different types of infrastructure projects (transit, water and wastewater, highways, power, manufacturing etc.) and indicators of economic growth are presented using historic data between 2002 and 2020 from the U.S. Census Bureau and U.S. Bureau of Economic Analysis (BEA). The outcome of the paper is the comparison of statistical correlations between investment in different types of infrastructure projects and indicators of economic growth. The comparison of the statistical correlations is useful in ranking the types of infrastructure projects based on their ability to influence economic prosperity. Therefore, investment in the infrastructures with the higher rank will have a better chance of boosting the economic growth. Once, the ranks are derived, they can be used by the decision-makers in infrastructure investment related decision-making process.

Keywords: economic growth, infrastructure development, infrastructure projects, strategic investment

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

Procedia PDF Downloads 314