Search results for: binary logistic regression
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3830

Search results for: binary logistic regression

3500 The Influence of Imposter Phenomenon on the Experiences of Intimacy in Non-Binary Young Adults

Authors: Muskan Jain, Baiju Gopal

Abstract:

Objectives: Intimacy in interpersonal relationships is integral to psychological health and everyday wellbeing; the focus is on intimacy, which can be described as feelings of closeness, connection, and belonging within relationships, which is influenced by an individual's gender identity as well as life experiences. The study aims to explore the experiences of intimacy of the non-binary gender; this marginalized community has increased risks of developing the imposter phenomenon. The study explores the influence of IP on the development and sustenance of intimacy in relationships. Methods: The present study accumulates detailed narratives from 10 non-binary young adults ages 18 to 25 in metropolitan cities of India. Thematic analysis was used for the data analysis. Results: Seven major themes have emerged revolving around internalized criticism and self-depreciating behavior, which causes distance between partners. The four themes that result in the internalization of criticism are lack of social stability, invalidation by social units, adverse life experiences, and estrangement due to gender identity. Three themes that encapsulate major difficulties in relationships are limited self-disclosure, inhibition of physical needs, and fear of taking space. The findings have been critically compared and contrasted with the existing body of literature in the domain, which sets the agenda for further inquiry. Conclusion: It is important for future studies to capture the experiences of non-binary genders in India to provide better therapeutic support in order to assist them in forming meaningful and authentic relationships, thus increasing overall wellbeing.

Keywords: imposter phenomenon, intimacy, internalized criticism, marginalized community

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3499 Weighted Rank Regression with Adaptive Penalty Function

Authors: Kang-Mo Jung

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The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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3498 Dietary Pattern derived by Reduced Rank Regression is Associated with Reduced Cognitive Impairment Risk in Singaporean Older Adults

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

Abstract:

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

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

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3497 The Relationship between Self-Injurious Behavior and Manner of Death

Authors: Sait Ozsoy, Hacer Yasar Teke, Mustafa Dalgic, Cetin Ketenci, Ertugrul Gok, Kenan Karbeyaz, Azem Irez, Mesut Akyol

Abstract:

Self-mutilating behavior or self-injury behavior (SIB) is defined as: intentional harm to one’s body without intends to commit suicide”. SIB cases are commonly seen in psychiatry and forensic medicine practices. Despite variety of SIB methods, cuts in the skin is the most common (70-97%) injury in this group of patients. Subjects with SIB have one or more other comorbidities which include depression, anxiety, depersonalization, and feeling of worthlessness, borderline personality disorder, antisocial behaviors, and histrionic personality. These individuals feel a high level of hostility towards themselves and their surroundings. Researches have also revealed a strong relationship between antisocial personality disorder, criminal behavior, and SIB. This study has retrospectively evaluated 6,599 autopsy cases performed at forensic medicine institutes of six major cities (Ankara, Izmir, Diyarbakir, Erzurum, Trabzon, Eskisehir) of Turkey in 2013. The study group consisted of all cases with SIB findings (psychopathic cuts, cigarette burns, scars, and etc.). The relationship between causes of death in the study group (SIB subjects) and the control group was investigated. The control group was created from subjects without signs of SIB. Mann-Whitney U test was used for age variables and Chi-square test for categorical variables. Multinomial logistic regression analysis was used in order to analyze group differences in respect to manner of death (natural, accident, homicide, suicide) and analysis of risk factors associated with each group was determined by the Binomial logistic regression analysis. This study used SPSS statistics 15.0 for all its statistical and calculation needs. The statistical significance was p <0.05. There was no significant difference between accidental and natural death among the groups (p=0.737). Also there was a unit increase in number of cuts in psychopathic group while number of accidental death decreased (95% CI: 0.941-0.993) by 0.967 times (p=0.015). In contrast, there was a significant difference between suicidal and natural death (p<0.001), and also between homicidal and natural death (p=0.025). SIB is often seen with borderline and antisocial personality disorder but may be associated with many psychiatric illnesses. Studies have shown a relationship between antisocial personality disorders with criminal behavior and SIB with suicidal behavior. In our study, rate of suicide, murder and intoxication was higher compared to the control group. It could be concluded that SIB can be used as a predictor of possibility of one’s harm to him/herself and other people.

Keywords: autopsy, cause of death, forensic science, self-injury behaviour

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3496 Nature Writing in Margaret Atwood’s 'The Testaments'

Authors: Natalia Fontes De Oliveira

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Nature and women have a long age association that has persisted throughout history, cultures, literature, and arts. Women’s physiological functions of reproduction and childbearing are viewed as closer to nature as a binary opposition to men, who have metaphorically and historically been associated with culture. To liberate from strictures of phallogocentric rhetoric, a radical critique of the categories of nature and culture must be undertaken. This paper proposes that nature writing in Margaret Atwood’s The Testaments is used subversively as a form of rebellion to disrupt the metaphorical relationship between women and nature. In tune with ecofeminist concerns, the imagery rewrites patriarchal paradigms of binary oppositions as the protagonists narrate a complex and plural relationship between nature and women.

Keywords: ecofeminism, Margaret Atwood, nature writing, women's writing

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3495 Arsenic Contamination in Drinking Water Is Associated with Dyslipidemia in Pregnancy

Authors: Begum Rokeya, Rahelee Zinnat, Fatema Jebunnesa, Israt Ara Hossain, A. Rahman

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Background and Aims: Arsenic in drinking water is a global environmental health problem, and the exposure may increase dyslipidemia and cerebrovascular diseases mortalities, most likely through causing atherosclerosis. However, the mechanism of lipid metabolism, atherosclerosis formation, arsenic exposure and impact in pregnancy is still unclear. Recent epidemiological evidences indicate close association between inorganic arsenic exposure via drinking water and Dyslipidemia. However, the exact mechanism of this arsenic-mediated increase in atherosclerosis risk factors remains enigmatic. We explore the association of the effect of arsenic on serum lipid profile in pregnant subjects. Methods: A total 200 pregnant mother screened in this study from arsenic exposed area. Our study group included 100 exposed subjects were cases and 100 Non exposed healthy pregnant were controls requited by a cross-sectional study. Clinical and anthropometric measurements were done by standard techniques. Lipidemic status was assessed by enzymatic endpoint method. Urinary As was measured by inductively coupled plasma-mass spectrometry and adjusted with specific gravity and Arsenic exposure was assessed by the level of urinary arsenic level > 100 μg/L was categorized as arsenic exposed and < 100 μg/L were categorized as non-exposed. Multivariate logistic regression and Student’s t - test was used for statistical analysis. Results: Systolic and diastolic blood pressure both were significantly higher in the Arsenic exposed pregnant subjects compared to the Non-exposed group (p<0.001). Arsenic exposed subjects had 2 times higher chance of developing hypertensive pregnancy (Odds Ratio 2.2). In parallel to the findings in Ar exposed subjects showed significantly higher proportion of triglyceride and total cholesterol and low density of lipo protein when compare to non- arsenic exposed pregnant subjects. Significant correlation of urinary arsenic level was also found with SBP, DBP, TG, T chol and serum LDL-Cholesterol. On multivariate logistic regression showed urinary arsenic had a positive association with DBP, SBP, Triglyceride and LDL-c. Conclusion: In conclusion, arsenic exposure may induce dyslipidemia like atherosclerosis through modifying reverse cholesterol transport in cholesterol metabolism. For decreasing atherosclerosis related mortality associated with arsenic, preventing exposure from environmental sources in early life is an important element.

Keywords: Arsenic Exposure, Dyslipidemia, Gestational Diabetes Mellitus, Serum lipid profile

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3494 Interference among Lambsquarters and Oil Rapeseed Cultivars

Authors: Reza Siyami, Bahram Mirshekari

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Seed and oil yield of rapeseed is considerably affected by weeds interference including mustard (Sinapis arvensis L.), lambsquarters (Chenopodium album L.) and redroot pigweed (Amaranthus retroflexus L.) throughout the East Azerbaijan province in Iran. To formulate the relationship between four independent growth variables measured in our experiment with a dependent variable, multiple regression analysis was carried out for the weed leaves number per plant (X1), green cover percentage (X2), LAI (X3) and leaf area per plant (X4) as independent variables and rapeseed oil yield as a dependent variable. The multiple regression equation is shown as follows: Seed essential oil yield (kg/ha) = 0.156 + 0.0325 (X1) + 0.0489 (X2) + 0.0415 (X3) + 0.133 (X4). Furthermore, the stepwise regression analysis was also carried out for the data obtained to test the significance of the independent variables affecting the oil yield as a dependent variable. The resulted stepwise regression equation is shown as follows: Oil yield = 4.42 + 0.0841 (X2) + 0.0801 (X3); R2 = 81.5. The stepwise regression analysis verified that the green cover percentage and LAI of weed had a marked increasing effect on the oil yield of rapeseed.

Keywords: green cover percentage, independent variable, interference, regression

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3493 Copula-Based Estimation of Direct and Indirect Effects in Path Analysis Model

Authors: Alam Ali, Ashok Kumar Pathak

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Path analysis is a statistical technique used to evaluate the strength of the direct and indirect effects of variables. One or more structural regression equations are used to estimate a series of parameters in order to find the better fit of data. Sometimes, exogenous variables do not show a significant strength of their direct and indirect effect when the assumption of classical regression (ordinary least squares (OLS)) are violated by the nature of the data. The main motive of this article is to investigate the efficacy of the copula-based regression approach over the classical regression approach and calculate the direct and indirect effects of variables when data violates the OLS assumption and variables are linked through an elliptical copula. We perform this study using a well-organized numerical scheme. Finally, a real data application is also presented to demonstrate the performance of the superiority of the copula approach.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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3492 Factor Associated with Uncertainty Undergoing Hematopoietic Stem Cell Transplantation

Authors: Sandra Adarve, Jhon Osorio

Abstract:

Uncertainty has been studied in patients with different types of cancer, except in patients with hematologic cancer and undergoing transplantation. The purpose of this study was to identify factors associated with uncertainty in adults patients with malignant hemato-oncology diseases who are scheduled to undergo hematopoietic stem cell transplantation based on Merle Mishel´s Uncertainty theory. This was a cross-sectional study with an analytical purpose. The study sample included 50 patients with leukemia, myeloma, and lymphoma selected by non-probability sampling by convenience and intention. Sociodemographic and clinical variables were measured. Mishel´s Scale of Uncertainty in Illness was used for the measurement of uncertainty. A bivariate and multivariate analyses were performed to explore the relationships and associations between the different variables and uncertainty level. For this analysis, the distribution of the uncertainty scale values was evaluated through the Shapiro-Wilk normality test to identify statistical tests to be used. A multivariate analysis was conducted through a logistic regression using step-by-step technique. Patients were 18-74 years old, with a mean age of 44.8. Over time, the disease course had a median of 9.5 months, an opportunity was found in the performance of the transplantation of < 20 days for 50% of the patients. Regarding the uncertainty scale, a mean score of 95.46 was identified. When the dimensions of the scale were analyzed, the mean score of the framework of stimuli was 25.6, of cognitive ability was 47.4 and structure providers was 22.8. Age was identified to correlate with the total uncertainty score (p=0.012). Additionally, a statistically significant difference was evidenced between different religious creeds and uncertainty score (p=0.023), education level (p=0.012), family history of cancer (p=0.001), the presence of comorbidities (p=0.023) and previous radiotherapy treatment (p=0.022). After performing logistic regression, previous radiotherapy treatment (OR=0.04 IC95% (0.004-0.48)) and family history of cancer (OR=30.7 IC95% (2.7-349)) were found to be factors associated with the high level of uncertainty. Uncertainty is present in high levels in patients who are going to be subjected to bone marrow transplantation, and it is the responsibility of the nurse to assess the levels of uncertainty and the presence of factors that may contribute to their presence. Once it has been valued, the uncertainty must be intervened from the identified associated factors, especially all those that have to do with the cognitive capacity. This implies the implementation and design of intervention strategies to improve the knowledge related to the disease and the therapeutic procedures to which the patients will be subjected. All interventions should favor the adaptation of these patients to their current experience and contribute to seeing uncertainty as an opportunity for growth and transcendence.

Keywords: hematopoietic stem cell transplantation, hematologic diseases, nursing, uncertainty

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3491 Performance Analysis of Proprietary and Non-Proprietary Tools for Regression Testing Using Genetic Algorithm

Authors: K. Hema Shankari, R. Thirumalaiselvi, N. V. Balasubramanian

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The present paper addresses to the research in the area of regression testing with emphasis on automated tools as well as prioritization of test cases. The uniqueness of regression testing and its cyclic nature is pointed out. The difference in approach between industry, with business model as basis, and academia, with focus on data mining, is highlighted. Test Metrics are discussed as a prelude to our formula for prioritization; a case study is further discussed to illustrate this methodology. An industrial case study is also described in the paper, where the number of test cases is so large that they have to be grouped as Test Suites. In such situations, a genetic algorithm proposed by us can be used to reconfigure these Test Suites in each cycle of regression testing. The comparison is made between a proprietary tool and an open source tool using the above-mentioned metrics. Our approach is clarified through several tables.

Keywords: APFD metric, genetic algorithm, regression testing, RFT tool, test case prioritization, selenium tool

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3490 The Perspective of Waste Frying Oil in São Paulo and Its Dimensions in the Reverse Logistics of the Production of Biodiesel

Authors: Max Filipe Goncalves, Alessandra Concilio, Rodrigo Shimada

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The waste frying oil is highly pollutant when disposed incorrectly in the environment. Is necessary search of the Reverse Logistics to identify how can be structure to return the waste like this to productive chain and to be used in the new process. In this context, the objective of this paper is to analyze the perspective of the waste frying oil in São Paulo, and its dimensions in the production of biodiesel. Subjacent factors such as the agents, motivators and legal aspects were analyzed to demonstrate it. Then, the SWOT matrix was built with the aspects observed and the forces, weaknesses, opportunities and threats of the reverse logistic chain in São Paulo.

Keywords: biodiesel, perspective, reverse logistic, WFO

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3489 Determinants of Repeated Abortion among Women of Reproductive Age Attending Health Facilities in Northern Ethiopia: A Case-Control Study

Authors: Henok Yebyo Henok, Araya Abrha Araya, Alemayehu Bayray Alemayehu, Gelila Goba Gelila

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Background: Every year, an estimated 19–20 million unsafe abortions take place, almost all in developing countries, leading to 68,000 deaths and millions more injured many permanently. Many women throughout the world, experience more than one abortion in their lifetimes. Repeat abortion is an indicator of the larger problem of unintended pregnancy. This study aimed to identify determinants of repeat abortion in Tigray Region, Ethiopia. Methods: Unmatched case-control study was conducted in hospitals in Tigray Region, Northern Ethiopia, from November 2014 to June 2015. The sample included 105 cases and 204 controls, recruited from among women seeking abortion care at public hospitals. Clients having two or more abortions (“repeat abortion”) were taken as cases, and those who had a total of one abortion were taken as controls (“single abortion”). Cases were selected consecutive based on proportional to size allocation while systematic sampling was employed for controls. Data were analyzed using SPSS version 20.0. Binary and multiple variable logistic regression analyses were calculated with 95% CI. Results: Mean age of cases was 24 years (±6.85) and 22 years (±6.25) for controls. 79.0% of cases had their sexual debut in less than 18 years of age compared to 57% of controls. 42.2% of controls and 23.8% of cases cited rape as the reason for having an abortion. Study participants who did not understand their fertility cycle and when they were most likely to conceive after menstruation (adjusted odds ratio [AOR]=2.0, 95% confidence interval [CI]: 1.1-3.7), having a previous abortion using medication(AOR=3.3, CI: 1.83, 6.11), having multiple sexual partners in the preceding 12 months (AOR=4.4, CI: 2.39,8.45), perceiving that the abortion procedure is not painful (AOR=2.3, CI: 1.31,4.26), initiating sexual intercourse before the age of 18 years (AOR=2.7, CI: 1.49, 5.23) and disclosure to a third-party about terminating the pregnancy (AOR=2.1, CI: 1.2,3.83) were independent predictors of repeat abortion. Conclusion: This study identified several factors correlated with women having repeat abortions. It may be helpful for the Government of Ethiopia to encourage women to delay sexual debut and decrease their number of sexual partners, including by promoting discussion within families about sexuality, to decrease the occurrence of repeated abortion.

Keywords: abortion, Ethiopia, repeated abortion, single abortion

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3488 A Regression Model for Residual-State Creep Failure

Authors: Deepak Raj Bhat, Ryuichi Yatabe

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In this study, a residual-state creep failure model was developed based on the residual-state creep test results of clayey soils. To develop the proposed model, the regression analyses were done by using the R. The model results of the failure time (tf) and critical displacement (δc) were compared with experimental results and found in close agreements to each others. It is expected that the proposed regression model for residual-state creep failure will be more useful for the prediction of displacement of different clayey soils in the future.

Keywords: regression model, residual-state creep failure, displacement prediction, clayey soils

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3487 A Physical Theory of Information vs. a Mathematical Theory of Communication

Authors: Manouchehr Amiri

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This article introduces a general notion of physical bit information that is compatible with the basics of quantum mechanics and incorporates the Shannon entropy as a special case. This notion of physical information leads to the Binary data matrix model (BDM), which predicts the basic results of quantum mechanics, general relativity, and black hole thermodynamics. The compatibility of the model with holographic, information conservation, and Landauer’s principles are investigated. After deriving the “Bit Information principle” as a consequence of BDM, the fundamental equations of Planck, De Broglie, Beckenstein, and mass-energy equivalence are derived.

Keywords: physical theory of information, binary data matrix model, Shannon information theory, bit information principle

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3486 A Fuzzy Nonlinear Regression Model for Interval Type-2 Fuzzy Sets

Authors: O. Poleshchuk, E. Komarov

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This paper presents a regression model for interval type-2 fuzzy sets based on the least squares estimation technique. Unknown coefficients are assumed to be triangular fuzzy numbers. The basic idea is to determine aggregation intervals for type-1 fuzzy sets, membership functions of whose are low membership function and upper membership function of interval type-2 fuzzy set. These aggregation intervals were called weighted intervals. Low and upper membership functions of input and output interval type-2 fuzzy sets for developed regression models are considered as piecewise linear functions.

Keywords: interval type-2 fuzzy sets, fuzzy regression, weighted interval

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3485 The Effect of Non-Surgical Periodontal Therapy on Metabolic Control in Children

Authors: Areej Al-Khabbaz, Swapna Goerge, Majedah Abdul-Rasoul

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Introduction: The most prevalent periodontal disease among children is gingivitis, and it usually becomes more severe in adolescence. A number of intervention studies suggested that resolution of periodontal inflammation can improve metabolic control in patients diagnosed with diabetes mellitus. Aim: to assess the effect of non-surgical periodontal therapy on glycemic control of children diagnosed with diabetes mellitus. Method: Twenty-eight children diagnosed with diabetes mellitus were recruited with established diagnosis diabetes for at least 1 year. Informed consent and child assent form were obtained from children and parents prior to enrolment. The dental examination for the participants was performed on the same week directly following their annual medical assessment. All patients had their glycosylated hemoglobin (HbA1c%) test one week prior to their annual medical and dental visit and 3 months following non-surgical periodontal therapy. All patients received a comprehensive periodontal examination The periodontal assessment included clinical attachment loss, bleeding on probing, plaque score, plaque index and gingival index. All patients were referred for non-surgical periodontal therapy, which included oral hygiene instruction and motivation followed by supra-gingival and subg-ingival scaling using ultrasonic and hand instruments. Statistical Analysis: Data were entered and analyzed using the Statistical Package for Social Science software (SPSS, Chicago, USA), version 18. Statistical analysis of clinical findings was performed to detect differences between the two groups in term of periodontal findings and HbA1c%. Binary logistic regression analysis was performed in order to examine which factors were significant in multivariate analysis after adjusting for confounding between effects. The regression model used the dependent variable ‘Improved glycemic control’, and the independent variables entered in the model were plaque index, gingival index, bleeding %, plaque Statistical significance was set at p < 0.05. Result: A total of 28 children. The mean age of the participants was 13.3±1.92 years. The study participants were divided into two groups; Compliant group (received dental scaling) and non-complaints group (received oral hygiene instructions only). No statistical difference was found between compliant and non-compliant group in age, gender distribution, oral hygiene practice and the level of diabetes control. There was a significant difference between compliant and non-compliant group in term of improvement of HBa1c before and after periodontal therapy. Mean gingival index was the only significant variable associated with improved glycemic control level. In conclusion, this study has demonstrated that non-surgical mechanical periodontal therapy can improve HbA1c% control. The result of this study confirmed that children with diabetes mellitus who are compliant to dental care and have routine professional scaling may have better metabolic control compared to diabetic children who are erratic with dental care.

Keywords: children, diabetes, metabolic control, periodontal therapy

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3484 Formulating a Flexible-Spread Fuzzy Regression Model Based on Dissemblance Index

Authors: Shih-Pin Chen, Shih-Syuan You

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This study proposes a regression model with flexible spreads for fuzzy input-output data to cope with the situation that the existing measures cannot reflect the actual estimation error. The main idea is that a dissemblance index (DI) is carefully identified and defined for precisely measuring the actual estimation error. Moreover, the graded mean integration (GMI) representation is adopted for determining more representative numeric regression coefficients. Notably, to comprehensively compare the performance of the proposed model with other ones, three different criteria are adopted. The results from commonly used test numerical examples and an application to Taiwan's business monitoring indicator illustrate that the proposed dissemblance index method not only produces valid fuzzy regression models for fuzzy input-output data, but also has satisfactory and stable performance in terms of the total estimation error based on these three criteria.

Keywords: dissemblance index, forecasting, fuzzy sets, linear regression

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3483 Image Compression Based on Regression SVM and Biorthogonal Wavelets

Authors: Zikiou Nadia, Lahdir Mourad, Ameur Soltane

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In this paper, we propose an effective method for image compression based on SVM Regression (SVR), with three different kernels, and biorthogonal 2D Discrete Wavelet Transform. SVM regression could learn dependency from training data and compressed using fewer training points (support vectors) to represent the original data and eliminate the redundancy. Biorthogonal wavelet has been used to transform the image and the coefficients acquired are then trained with different kernels SVM (Gaussian, Polynomial, and Linear). Run-length and Arithmetic coders are used to encode the support vectors and its corresponding weights, obtained from the SVM regression. The peak signal noise ratio (PSNR) and their compression ratios of several test images, compressed with our algorithm, with different kernels are presented. Compared with other kernels, Gaussian kernel achieves better image quality. Experimental results show that the compression performance of our method gains much improvement.

Keywords: image compression, 2D discrete wavelet transform (DWT-2D), support vector regression (SVR), SVM Kernels, run-length, arithmetic coding

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3482 Public Preferences for Lung Cancer Screening in China: A Discrete Choice Experiment

Authors: Zixuan Zhao, Lingbin Du, Le Wang, Youqing Wang, Yi Yang, Jingjun Chen, Hengjin Dong

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Objectives: Few results from public attitudes for lung cancer screening are available both in China and abroad. This study aimed to identify preferred lung cancer screening modalities in a Chinese population and predict uptake rates of different modalities. Materials and Methods: A discrete choice experiment questionnaire was administered to 392 Chinese individuals aged 50–74 years who were at high risk for lung cancer. Each choice set had two lung screening options and an option to opt-out, and respondents were asked to choose the most preferred one. Both mixed logit analysis and stepwise logistic analysis were conducted to explore whether preferences were related to respondent characteristics and identify which kinds of respondents were more likely to opt out of any screening. Results: On mixed logit analysis, attributes that were predictive of choice at 1% level of statistical significance included the screening interval, screening venue, and out-of-pocket costs. The preferred screening modality seemed to be screening by low-dose computed tomography (LDCT) + blood test once a year in a general hospital at a cost of RMB 50; this could increase the uptake rate by 0.40 compared to the baseline setting. On stepwise logistic regression, those with no endowment insurance were more likely to opt out; those who were older and housewives/househusbands, and those with a health check habit and with commercial endowment insurance were less likely to opt out from a screening programme. Conclusions: There was considerable variance between real risk and self-perceived risk of lung cancer among respondents, and further research is required in this area. Lung cancer screening uptake can be increased by offering various screening modalities, so as to help policymakers further design the screening modality.

Keywords: lung cancer, screening, China., discrete choice experiment

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3481 A Comparative Study of Additive and Nonparametric Regression Estimators and Variable Selection Procedures

Authors: Adriano Z. Zambom, Preethi Ravikumar

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One of the biggest challenges in nonparametric regression is the curse of dimensionality. Additive models are known to overcome this problem by estimating only the individual additive effects of each covariate. However, if the model is misspecified, the accuracy of the estimator compared to the fully nonparametric one is unknown. In this work the efficiency of completely nonparametric regression estimators such as the Loess is compared to the estimators that assume additivity in several situations, including additive and non-additive regression scenarios. The comparison is done by computing the oracle mean square error of the estimators with regards to the true nonparametric regression function. Then, a backward elimination selection procedure based on the Akaike Information Criteria is proposed, which is computed from either the additive or the nonparametric model. Simulations show that if the additive model is misspecified, the percentage of time it fails to select important variables can be higher than that of the fully nonparametric approach. A dimension reduction step is included when nonparametric estimator cannot be computed due to the curse of dimensionality. Finally, the Boston housing dataset is analyzed using the proposed backward elimination procedure and the selected variables are identified.

Keywords: additive model, nonparametric regression, variable selection, Akaike Information Criteria

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3480 Effect of Serum Electrolytes on a QTc Interval and Mortality in Patients admitted to Coronary Care Unit

Authors: Thoetchai Peeraphatdit, Peter A. Brady, Suraj Kapa, Samuel J. Asirvatham, Niyada Naksuk

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Background: Serum electrolyte abnormalities are a common cause of an acquired prolonged QT syndrome, especially, in the coronary care unit (CCU) setting. Optimal electrolyte ranges among the CCU patients have not been sufficiently investigated. Methods: We identified 8,498 consecutive CCU patients who were admitted to the CCU at Mayo Clinic, Rochester, the USA, from 2004 through 2013. Association between first serum electrolytes and baseline corrected QT intervals (QTc), as well as in-hospital mortality, was tested using multivariate linear regression and logistic regression, respectively. Serum potassium 4.0- < 4.5 mEq/L, ionized calcium (iCa) 4.6-4.8 mg/dL, and magnesium 2.0- < 2.2 mg/dL were used as the reference levels. Results: There was a modest level-dependent relationship between hypokalemia ( < 4.0 mEq/L), hypocalcemia ( < 4.4 mg/dL), and a prolonged QTc interval; serum magnesium did not affect the QTc interval. Association between the serum electrolytes and in-hospital mortality included a U-shaped relationship for serum potassium (adjusted odds ratio (OR) 1.53 and OR 1.91for serum potassium 4.5- < 5.0 and ≥ 5.0 mEq/L, respectively) and an inverted J-shaped relationship for iCa (adjusted OR 2.79 and OR 2.03 for calcium < 4.4 and 4.4- < 4.6 mg/dL, respectively). For serum magnesium, the mortality was greater only among patients with levels ≥ 2.4 mg/dL (adjusted OR 1.40), compared to the reference level. Findings were similar in sensitivity analyses examining the association between mean serum electrolytes and mean QTc intervals, as well as in-hospital mortality. Conclusions: Serum potassium 4.0- < 4.5 mEq/L, iCa ≥ 4.6 mg/dL, and magnesium < 2.4 mg/dL had a neutral effect on QTc intervals and were associated with the lowest in-hospital mortality among the CCU patients.

Keywords: calcium, electrocardiography, long-QT syndrome, magnesium, mortality, potassium

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3479 Delivery System Design of the Local Part to Reduce the Logistic Costs in an Automotive Industry

Authors: Alesandro Romero, Inaki Maulida Hakim

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This research was conducted in an automotive company in Indonesia to overcome the problem of high logistics cost. The problem causes high of additional truck delivery. From the breakdown of the problem, chosen one route, which has the highest gap value, namely for RE-04. Research methodology will be started from calculating the ideal condition, making simulation, calculating the ideal logistic cost, and proposing an improvement. From the calculation of the ideal condition, box arrangement was done on the truck; the average efficiency was 97,4 % with three trucks delivery per day. Route simulation making uses Tecnomatix Plant Simulation software as a visualization for the company about how the system is occurred on route RE-04 in ideal condition. Furthermore, from the calculation of logistics cost of the ideal condition, it brings savings of Rp53.011.800,00 in a month. The last step is proposing improvements on the area of route RE-04. The route arrangement is done by Saving Method and sequence of each supplier with the Nearest Neighbor. The results of the proposed improvements are three new route groups, where was expected to decrease logistics cost Rp3.966.559,40 per day, and increase the average of the truck efficiency 8,78% per day.

Keywords: efficiency, logistic cost, milkrun, saving methode, simulation

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3478 The Impact of Sports Employees' of Perceptions of Organizational Climate and Organizational Trust on Work Motivation

Authors: Bilal Okudan, Omur F. Karakullukcu, Yusuf Can

Abstract:

Work motivation is one of the fundamental elements that determine the attitudes and performance of employees towards work. In this sense, work motivation depends not only on individual and occupational factors but also on employees' perception of organizational climate and organizational trust. Organizations that are aware of this have begun to do more research on work motivation in recent years to ensure that employees have the highest possible performance. In this framework of the purpose of this study is to examine the effect of sports employees' perceptions of organizational climate and organizational trust on work motivation. In the study, it has also been analyzed if there is any significant difference in the department of sports services’ employees’ organizational climate and organizational trust perception, and work motivation levels in terms of gender, age, duty status, year of service and level of education. 278 sports managers, who work in the department of sports service’s central and field organization at least as a chief in the manager position, have been chosen with random sampling method and they have voluntarily participated in the study. In the study, the organizational climate scale which was developed by Bilir (2005), organizational trusts scale developed by koksal (2012) and work motivation scale developed by Mottaz J. Clifford (1985) have been used as a data collection tool. The questionnaire form used as a data collection tool in the study includes a personal information form consisting of 5 questions; questioning gender, age, duty status, years of service and level of education. In the study, Pearson Correlation Analysis has been used for defining the correlation among organizational climate, organizational trust perceptions and work motivation levels in sports managers and regression analysis has been used to identify the effect of organizational climate and organizational trust on work motivation. T-test for binary grouping and ANOVA analysis have been used for more than binary groups in order to determine if there is any significant difference in the level of organizational climate, organizational trust perceptions and work motivations in terms of the participants’ duty status, year of service and level of education. According to the research results, it has been found that there is a positive correlation between the department of sports services’ employees’ organizational climate, organizational trust perceptions and work motivation levels. According to the results of the regression analysis; it is understood that the sports employees’ perception of organizational climate and organizational trust are two main factors which affects the perception of work motivation. Also, the results show that there is a significant difference in the level of organizational climate and organizational trust perceptions and work motivations of the department of sports services’ employees in terms of duty status, year of service, and level of education; however, the results reveal that there is no significant difference in terms of age groups and gender.

Keywords: sports manager, organizational climate, organizational trust, work motivation

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3477 Incidence of Breast Cancer and Enterococcus Infection: A Retrospective Analysis

Authors: Matthew Cardeiro, Amalia D. Ardeljan, Lexi Frankel, Dianela Prado Escobar, Catalina Molnar, Omar M. Rashid

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Introduction: Enterococci comprise the natural flora of nearly all animals and are ubiquitous in food manufacturing and probiotics. However, its role in the microbiome remains controversial. The gut microbiome has shown to play an important role in immunology and cancer. Further, recent data has suggested a relationship between gut microbiota and breast cancer. These studies have shown that the gut microbiome of patients with breast cancer differs from that of healthy patients. Research regarding enterococcus infection and its sequala is limited, and further research is needed in order to understand the relationship between infection and cancer. Enterococcus may prevent the development of breast cancer (BC) through complex immunologic and microbiotic adaptations following an enterococcus infection. This study investigated the effect of enterococcus infection and the incidence of BC. Methods: A retrospective study (January 2010- December 2019) was provided by a Health Insurance Portability and Accountability Act (HIPAA) compliant national database and conducted using a Humans Health Insurance Database. International Classification of Disease (ICD) 9th and 10th codes, Current Procedural Terminology (CPT), and National Drug Codes were used to identify BC diagnosis and enterococcus infection. Patients were matched for age, sex, Charlson Comorbidity Index (CCI), antibiotic treatment, and region of residence. Chi-squared, logistic regression, and odds ratio were implemented to assess the significance and estimate relative risk. Results: 671 out of 28,518 (2.35%) patients with a prior enterococcus infection and 1,459 out of 28,518 (5.12%) patients without enterococcus infection subsequently developed BC, and the difference was statistically significant (p<2.2x10⁻¹⁶). Logistic regression also indicated enterococcus infection was associated with a decreased incidence of BC (RR=0.60, 95% CI [0.57, 0.63]). Treatment for enterococcus infection was analyzed and controlled for in both enterococcus infected and noninfected populations. 398 out of 11,523 (3.34%) patients with a prior enterococcus infection and treated with antibiotics were compared to 624 out of 11,523 (5.41%) patients with no history of enterococcus infection (control) and received antibiotic treatment. Both populations subsequently developed BC. Results remained statistically significant (p<2.2x10-16) with a relative risk of 0.57 (95% CI [0.54, 0.60]). Conclusion & Discussion: This study shows a statistically significant correlation between enterococcus infection and a decrease incidence of breast cancer. Further exploration is needed to identify and understand not only the role of enterococcus in the microbiome but also the protective mechanism(s) and impact enterococcus infection may have on breast cancer development. Ultimately, further research is needed in order to understand the complex and intricate relationship between the microbiome, immunology, bacterial infections, and carcinogenesis.

Keywords: breast cancer, enterococcus, immunology, infection, microbiome

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3476 Application and Verification of Regression Model to Landslide Susceptibility Mapping

Authors: Masood Beheshtirad

Abstract:

Identification of regions having potential for landslide occurrence is one of the basic measures in natural resources management. Different landslide hazard mapping models are proposed based on the environmental condition and goals. In this research landslide hazard map using multiple regression model were provided and applicability of this model is investigated in Baghdasht watershed. Dependent variable is landslide inventory map and independent variables consist of information layers as Geology, slope, aspect, distance from river, distance from road, fault and land use. For doing this, existing landslides have been identified and an inventory map made. The landslide hazard map is based on the multiple regression provided. The level of similarity potential hazard classes and figures of this model were compared with the landslide inventory map in the SPSS environments. Results of research showed that there is a significant correlation between the potential hazard classes and figures with area of the landslides. The multiple regression model is suitable for application in the Baghdasht Watershed.

Keywords: landslide, mapping, multiple model, regression

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3475 Thermodynamic Behaviour of Binary Mixtures of 1, 2-Dichloroethane with Some Cyclic Ethers: Experimental Results and Modelling

Authors: Fouzia Amireche-Ziar, Ilham Mokbel, Jacques Jose

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The vapour pressures of the three binary mixtures: 1, 2- dichloroethane + 1,3-dioxolane, + 1,4-dioxane or + tetrahydropyrane, are carried out at ten temperatures ranging from 273 to 353.15 K. An accurate static device was employed for these measurements. The VLE data were reduced using the Redlich-Kister equation by taking into consideration the vapour pressure non-ideality in terms of the second molar virial coefficient. The experimental data were compared to the results predicted with the DISQUAC and Dortmund UNIFAC group contribution models for the total pressures P and the excess molar Gibbs energies GE.

Keywords: disquac model, dortmund UNIFAC model, excess molar Gibbs energies GE, VLE

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3474 Constraints on IRS Control: An Alternative Approach to Tax Gap Analysis

Authors: J. T. Manhire

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A tax authority wants to take actions it knows will foster the greatest degree of voluntary taxpayer compliance to reduce the “tax gap.” This paper suggests that even if a tax authority could attain a state of complete knowledge, there are constraints on whether and to what extent such actions would result in reducing the macro-level tax gap. These limits are not merely a consequence of finite agency resources. They are inherent in the system itself. To show that this is one possible interpretation of the tax gap data, the paper formulates known results in a different way by analyzing tax compliance as a population with a single covariate. This leads to a standard use of the logistic map to analyze the dynamics of non-compliance growth or decay over a sequence of periods. This formulation gives the same results as the tax gap studies performed over the past fifty years in the U.S. given the published margins of error. Limitations and recommendations for future work are discussed, along with some implications for tax policy.

Keywords: income tax, logistic map, tax compliance, tax law

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3473 Computer Simulation of Hydrogen Superfluidity through Binary Mixing

Authors: Sea Hoon Lim

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A superfluid is a fluid of bosons that flows without resistance. In order to be a superfluid, a substance’s particles must behave like bosons, yet remain mobile enough to be considered a superfluid. Bosons are low-temperature particles that can be in all energy states at the same time. If bosons were to be cooled down, then the particles will all try to be on the lowest energy state, which is called the Bose Einstein condensation. The temperature when bosons start to matter is when the temperature has reached its critical temperature. For example, when Helium reaches its critical temperature of 2.17K, the liquid density drops and becomes a superfluid with zero viscosity. However, most materials will solidify -and thus not remain fluids- at temperatures well above the temperature at which they would otherwise become a superfluid. Only a few substances currently known to man are capable of at once remaining a fluid and manifesting boson statistics. The most well-known of these is helium and its isotopes. Because hydrogen is lighter than helium, and thus expected to manifest Bose statistics at higher temperatures than helium, one might expect hydrogen to also be a superfluid. As of today, however, no one has yet been able to produce a bulk, hydrogen superfluid. The reason why hydrogen did not form a superfluid in the past is its intermolecular interactions. As a result, hydrogen molecules are much more likely to crystallize than their helium counterparts. The key to creating a hydrogen superfluid is therefore finding a way to reduce the effect of the interactions among hydrogen molecules, postponing the solidification to lower temperature. In this work, we attempt via computer simulation to produce bulk superfluid hydrogen through binary mixing. Binary mixture is a technique of mixing two pure substances in order to avoid crystallization and enhance super fluidity. Our mixture here is KALJ H2. We then sample the partition function using this Path Integral Monte Carlo (PIMC), which is well-suited for the equilibrium properties of low-temperature bosons and captures not only the statistics but also the dynamics of Hydrogen. Via this sampling, we will then produce a time evolution of the substance and see if it exhibits superfluid properties.

Keywords: superfluidity, hydrogen, binary mixture, physics

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3472 Determining Variables in Mathematics Performance According to Gender in Mexican Elementary School

Authors: Nora Gavira Duron, Cinthya Moreda Gonzalez-Ortega, Reyna Susana Garcia Ruiz

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This paper objective is to analyze the mathematics performance in the Learning Evaluation National Plan (PLANEA for its Spanish initials: Plan Nacional para la Evaluación de los Aprendizajes), applied to Mexican students who are enrolled in the last elementary-school year over the 2017-2018 academic year. Such test was conducted nationwide in 3,573 schools, using a sample of 108,083 students, whose average in mathematics, on a scale of 0 to 100, was 45.6 points. 75% of the sample analyzed did not reach the sufficiency level (60 points). It should be noted that only 2% got a 90 or higher score result. The performance is analyzed while considering whether there are differences in gender, marginalization level, public or private school enrollment, parents’ academic background, and living-with-parents situation. Likewise, this variable impact (among other variables) on school performance by gender is evaluated, considering multivariate logistic (Logit) regression analysis. The results show there are no significant differences in mathematics performance regarding gender in elementary school; nevertheless, the impact exerted by mothers who studied at least high school is of great relevance for students, particularly for girls. Other determining variables are students’ resilience, their parents’ economic status, and the fact they attend private schools, strengthened by the mother's education.

Keywords: multivariate regression analysis, academic performance, learning evaluation, mathematics result per gender

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3471 Evidence Based Approach on Beliefs and Perceptions on Mental Health Disorder and Substance Abuse: The Role of a Social Worker

Authors: Helena Baffoe

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The US has developed numerous programs over the past 50 years to enhance the lives of those who suffer from mental health illnesses and substance abuse, as well as the effectiveness of their treatments. Despite these advances over the past 50 years, there hasn't been a corresponding improvement in American public attitudes and beliefs about mental health disorders and substance abuse. Highly publicized acts of violence frequently elicit comments that blame the perpetrator's perceived mental health disorder since such people are thought to be substance abusers. Despite these strong public beliefs and perception about mental disorder and substance abuse, concreate empirical evidence that entail this perception is lacking, and evidence of their effectiveness has not been integrated. A rich data was collected from Substance Abuse and Mental Health Services Administration (SAMHSA) with a hypothesis that people who are diagnosed with a mental health disorder are likely to be diagnosed with substance abuse using logit regression analysis and Instrumental Variable. It was found that depressive, anxiety, and trauma/stressor mental disorders constitute the most common mental disorder in the United States, and the study could not find statistically significant evidence that being diagnosed with these leading mental health disorders in the United States does necessarily imply that such a patient is diagnosed with substances abuse. Thus, the public has a misconception of mental health and substance abuse issues, and social workers' responsibilities are outlined in order to assist ameliorate this attitude and perception.

Keywords: mental health disorder, substance use, empirical evidence, logistic regression

Procedia PDF Downloads 62