Search results for: association analysis

Authors: Lu Yung-Hsiang, Chang Kuming, Dai Yi-Fang, Liao Ching-Yi

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According to Taiwan’s administrative division of future land planning may lead farmer association and service areas facing recombination or merger. Thus, merger combination and the economic benefit of the farmer association are worth to be discussed. The farmer association in the merger, which may cause some then will not be consolidated, or consolidate two, or ever more to one association. However, under what condition to merge is greatest, as one of observation of this study. In addition, research without using simulation methods and only on the credit department rather whole farmer association. Therefore, this paper will use the simulation approach, and examine both the merge of farmer association and the condition under which the benefits are the greatest. The data of this study set include 266 farmer associations in Taiwan period 2012 to 2013. Empirical results showed that the number of the farmer association optimal simulation combination is 108.After the merger from the first stage can be reduced by 60% of the farmers’ association. The cost saving effects of the post-merger is not different. The cost efficiency of the farmers’ association improved it. The economies of scale and scope would decrease by the merger. The research paper hopes the finding will benefit the future merger of the farmers’ association.

Keywords: simulation merger, farmer association, assurance region, data envelopment analysis

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Authors: Shiva Ebrahimian Dehaghani, Afsaneh Doosti, Morteza Zare

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Background: There is no consensus regarding the association between dysphagia and cognition. Purpose: The aim of this study was to quantitatively and qualitatively analyze the available evidence on the direction and strength of association between dysphagia and cognition. Methodology: PubMed, Scopus, Embase and Web of Science were searched about the association between dysphagia and cognition. A random-effects model was used to determine weighted odds ratios (OR) and 95% confidence intervals (CI). Sensitivity analysis was performed to determine the impact of each individual study on the pooled results. Results: A total of 1427 participants showed that some cognitive disorders were significantly associated with dysphagia (OR = 3.23; 95% CI, 2.33–4.48). Conclusion: The association between cognition and swallowing disorders suggests that multiple neuroanatomical systems are involved in these two functions.

Keywords: adult, association, cognitive impairment, dysphagia, systematic review

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Authors: Feng Zhang

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Kashin-Beck disease (KBD) is a chronic osteochondropathy. The mechanism of hand growth and development failure of KBD remains elusive now. In this study, we conducted a two-stage genome-wide association study (GWAS) of palmar length-width ratio (LWR) of KBD, totally involving 493 Chinese Han KBD patients. Affymetrix Genome Wide Human SNP Array 6.0 was applied for SNP genotyping. Association analysis was conducted by PLINK software. Imputation analysis was performed by IMPUTE against the reference panel of the 1000 genome project. In the GWAS, the most significant association was observed between palmar LWR and rs2071358 of COL2A1 gene (P value = 4.68×10-8). Imputation analysis identified 3 SNPs surrounding rs2071358 with significant or suggestive association signals. Replication study observed additional significant association signals at both rs2071358 (P value = 0.017) and rs4760608 (P value = 0.002) of COL2A1 gene after Bonferroni correction. Our results suggest that COL2A1 gene was a novel susceptibility gene involved in the growth and development failure of hand of KBD.

Keywords: Kashin-Beck disease, genome-wide association study, COL2A1, hand

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Authors: B. Suraj Aravind, M. H. M. Krishna Prasad

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There exist emerging applications of data streams that require association rule mining, such as network traffic monitoring, web click streams analysis, sensor data, data from satellites etc. Data streams typically arrive continuously in high speed with huge amount and changing data distribution. This raises new issues that need to be considered when developing association rule mining techniques for stream data. This paper proposes to introduce an improved data stream association rule mining algorithm by eliminating the limitation of resources. For this, the concept of cloud computing is used. Inclusion of this may lead to additional unknown problems which needs further research.

Keywords: data stream, association rule mining, cloud computing, frequent itemsets

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Authors: Sangdeok Lee, Sangwon Han, Changtaek Hyun

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Construction defects are major components that result in negative impacts on project performance including schedule delays and cost overruns. Since construction defects generally occur when a few associated causes combine, a thorough understanding of defect causality is required in order to more systematically prevent construction defects. To address this issue, this paper uses association rule mining (ARM) to quantify the causality between defect causes, and social network analysis (SNA) to find indirect causality among them. The suggested approach is validated with 350 defect instances from concrete works in 32 projects in Korea. The results show that the interrelationships revealed by the approach reflect the characteristics of the concrete task and the important causes that should be prevented.

Keywords: causality, defect causes, social network analysis, association rule mining

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Authors: Diego De Castro Rodrigues, Marcelo Lisboa Rocha, Daniela M. De Q. Trevisan, Marcos Dias Da Conceicao, Gabriel Rosa, Rommel M. Barbosa

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The use of association rules algorithms within data mining is recognized as being of great value in the knowledge discovery in databases. Very often, the number of rules generated is high, sometimes even in databases with small volume, so the success in the analysis of results can be hampered by this quantity. The purpose of this research is to present a method for reducing the quantity of rules generated with association algorithms. Therefore, a computational algorithm was developed with the use of a Weka Application Programming Interface, which allows the execution of the method on different types of databases. After the development, tests were carried out on three types of databases: synthetic, model, and real. Efficient results were obtained in reducing the number of rules, where the worst case presented a gain of more than 50%, considering the concepts of support, confidence, and lift as measures. This study concluded that the proposed model is feasible and quite interesting, contributing to the analysis of the results of association rules generated from the use of algorithms.

Keywords: data mining, association rules, rules reduction, artificial intelligence

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Authors: Triano Nurhikmat

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Along with the progress of science and technology, the development of the industrialized world in Indonesia took place very rapidly. This leads to a process of industrialization of society Indonesia faster with the establishment of the company and the workplace are diverse. Development of the industry relates to the activity of the worker. Where in these work activities do not cover the possibility of an impending crash on either the workers or on a construction project. The cause of the occurrence of industrial accidents was the fault of electrical damage, work procedures, and error technique. The method of an association rule is one of the main techniques in data mining and is the most common form used in finding the patterns of data collection. In this research would like to know how relations of the association between the incidence of any industrial accidents. Therefore, by using methods of analysis association rule patterns associated with combination obtained two iterations item set (2 large item set) when every factor of industrial accidents with a West Jakarta so industrial accidents caused by the occurrence of an electrical value damage = 0.2 support and confidence value = 1, and the reverse pattern with value = 0.2 support and confidence = 0.75.

Keywords: association rule, data mining, industrial accidents, rules

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Authors: B. Chandra

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In Association Rule Mining, much attention has been paid for developing algorithms for large (frequent/closed/maximal) itemsets but very little attention has been paid to improve the performance of rule generation algorithms. Rule generation is an important part of Association Rule Mining. In this paper, a novel approach named NARG (Association Rule using Antecedent Support) has been proposed for rule generation that uses memory resident data structure named FCET (Frequent Closed Enumeration Tree) to find frequent/closed itemsets. In addition, the computational speed of NARG is enhanced by giving importance to the rules that have lower antecedent support. Comparative performance evaluation of NARG with fast association rule mining algorithm for rule generation has been done on synthetic datasets and real life datasets (taken from UCI Machine Learning Repository). Performance analysis shows that NARG is computationally faster in comparison to the existing algorithms for rule generation.

Keywords: knowledge discovery, association rule mining, antecedent support, rule generation

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Authors: Saima Suleman, Kalsoom Sughra, Naeem Mahmood Ashraf

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Mycobacterium tuberculosis is a communicable chronic illness. This disease is being highly focused by researchers as it is present approximately in one third of world population either in active or latent form. The genetic makeup of a person plays an important part in producing immunity against disease. And one important factor association is single nucleotide polymorphism of relevant gene. In this study, we have studied association between single nucleotide polymorphism of CD-209 gene (encode DC-SIGN receptor) and patients of tuberculosis. Dry lab (in silico) and wet lab (RFLP) analysis have been carried out. GWAS catalogue and GEO database have been searched to find out previous association data. No association study has been found related to CD-209 nsSNPs but role of CD-209 in pulmonary tuberculosis have been addressed in GEO database.Therefore, CD-209 has been selected for this study. Different databases like ENSEMBLE and 1000 Genome Project has been used to retrieve SNP data in form of VCF file which is further submitted to different software to sort SNPs into benign and deleterious. Selected SNPs are further annotated by using 3-D modeling techniques using I-TASSER online software. Furthermore, selected nsSNPs were checked in Gujrat and Faisalabad population through RFLP analysis. In this study population two SNPs are found to be associated with tuberculosis while one nsSNP is not found to be associated with the disease.

Keywords: association, CD209, DC-SIGN, tuberculosis

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Authors: Kanyarat Bussaban, Kunyanuth Kularbphettong

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This research aims to create a model for analysis of student behavior using Library resources based on data mining technique in case of Suan Sunandha Rajabhat University. The model was created under association rules, apriori algorithm. The results were found 14 rules and the rules were tested with testing data set and it showed that the ability of classify data was 79.24 percent and the MSE was 22.91. The results showed that the user’s behavior model by using association rule technique can use to manage the library resources.

Keywords: behavior, data mining technique, a priori algorithm, knowledge discovery

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Authors: Abir Derouiche, Abdesslem Layeb

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Association Rule Mining (ARM) is one of the most popular data mining tasks and it is widely used in various areas. The search for association rules is an NP-complete problem that is why metaheuristics have been widely used to solve it. The present paper presents the ARM as an optimization problem and surveys the proposed approaches in the literature based on metaheuristics.

Keywords: Optimization, Metaheuristics, Data Mining, Association rules Mining

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Authors: Qiao Fan, Xiaobo Guo, Junxian Zhu, Xiaohu Ding, Ching-Yu Cheng, Tien-Yin Wong, Mingguang He, Heping Zhang, Xueqin Wang

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A systematic, simultaneous analysis of multiple phenotypes in genome-wide association studies (GWASs) draws a great attention to integrate the signals from single phenotypes with increased power. However, lacking an interpretable and efficient multivariate GWAS analysis impede the application of such approach. In this study, we propose to decompose the multivariate model into a series of simple univariate models. This transformation illuminates what exactly the individual trait contributes to the significant signals from the multivariate analyses. By employing our approach in the analysis of three myopia-related endophenotypes from the Singapore Malay Eye Study (SIMES), we identify novel candidate loci which were successfully validated in an independent Guangzhou Twin Eye Study (GTES).

Keywords: GWAS multivariate, multiple traits, myopia, association

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Authors: Foad Alzoughool

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Conflicting studies on the association between the rs5219 polymorphism and type 2 diabetes, some studies have confirmed a strong relationship between this variant and type2 diabetes, on the other hand, many studies denied the existence of this association. This study aimed to provide evidence about whether the rs5219 polymorphism has or hasn't a role as a risk factor for diabetes and meta-analysis to investigate the role of the control age group in the association. Genotyping of the rs5219 polymorphism was performed in a cohort of 266 healthy elderly subjects with a mean age (60.2 ± 5.1) with no history of diabetes (HbA1c < 6%) using standard Sanger sequencing methods. Lys/Lys alleles were detected in 20 persons (7.5%), Lys/Glu alleles in 96 persons (36.1%), and Glu/Glu in 150 persons (56.4%). The genotype distribution was consistent with Hardy–Weinberg equilibrium (P =0.7). Meta-analysis notably indicates no association between rs5219 polymorphism and type 2 diabetes in all studies used the younger age of the control group compared to the patient's age. In conclusion, our study sheds light on the importance of age factor among the control group recruited in case-control studies.

Keywords: Type 2 diabetes, rs5219 polymorphism, E23K, KCNJ11 gene

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Authors: Hongxin Zhao, Shibing Yang, Bingming Yi, Yi Ning

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Background: A few studies have found evidence that exposure to endogenous or postmenopausal exogenous estrogens may be associated with a lower prevalence of age-related macular degeneration (AMD), but dispute over this association is ongoing due to inconsistent results reported by different studies. Objectives: To conduct a systematic review and meta-analysis to investigate the association between hormone replacement therapy (HRT) use and AMD. Methods: Relevant studies that assessed the association between HRT and AMD were searched through four databases (PubMed, Web of Science, Cochrane Library, EMBASE) and reference lists of retrieved studies. Study selection, data extraction and quality assessment were conducted by three independent reviewers. The fixed-effect meta-analyses were performed to estimate the association between HRT ever-use and AMD by pooling risk ratio (RR) or odds ratio (OR) across studies. Results: The review identified 2 prospective and 7 cross-sectional studies with 93992 female participants that reported an estimate of the association between HRT ever-use and presence of early AMD or late AMD. Meta-analyses showed that there were no statistically significant associations between HRT ever-use and early AMD (pooled RR for cohort studies was 1.04, 95% CI 0.86 - 1.24; pooled OR for cross-sectional studies was 0.91, 95% CI 0.82 - 1.01). The pooled results from cross-sectional studies also showed no statistically significant association between HRT ever-use and late AMD (OR 1.01; 95% CI 0.89 - 1.15). Conclusions: The pooled effects from observational studies published to date indicate that HRT use is associated with neither early nor late AMD. Exposure to HRT may not protect women from developing AMD.

Keywords: hormone replacement therapy, age-related macular degeneration, meta-analysis, systematic review

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Authors: Archana Singh, Jyoti Agarwal, Ajay Rana

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Data Mining is an efficient technology to discover patterns in large databases. Association Rule Mining techniques are used to find the correlation between the various item sets in a database, and this co-relation between various item sets are used in decision making and pattern analysis. In recent years, the problem of finding association rules from large datasets has been proposed by many researchers. Various research papers on association rule mining (ARM) are studied and analyzed first to understand the existing algorithms. Apriori algorithm is the basic ARM algorithm, but it requires so many database scans. In DIC algorithm, less amount of database scan is needed but complex data structure lattice is used. The main focus of this paper is to propose a new optimized algorithm (Friendly Algorithm) and compare its performance with the existing algorithms A data set is used to find out frequent itemsets and association rules with the help of existing and proposed (Friendly Algorithm) and it has been observed that the proposed algorithm also finds all the frequent itemsets and essential association rules from databases as compared to existing algorithms in less amount of database scan. In the proposed algorithm, an optimized data structure is used i.e. Graph and Adjacency Matrix.

Keywords: association rules, data mining, dynamic item set counting, FP-growth, friendly algorithm, graph

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Authors: Ikhlas Ahmed, Jamillah Zamoon

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The human receptor for advanced glycation end product is a plasma membrane receptor with an intrinsically disordered region. The protein consists of three extracellular domains, a single membrane spanning transmembrane domain, and a cytosolic domain which is intrinsically disordered and responsible for signaling. The disordered nature of the cytosolic domain allows it to be dynamic in solution. This receptor self-associates to higher forms. The association is triggered by ligand, metal or by the extracellular domain. Fluorescence spectroscopy technique is used to test the self-association of the different concentrations of the cytosolic domain. This work has concluded that the cytosolic domain of this receptor also self-associates. Moreover, the self-association does not require ligand or metal.

Keywords: fluorescence spectroscopy, hRAGE, IDP, Self-association

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Authors: Heejin Yun, Juanjuan Zang

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This study aims to analyze the text terms posted on an online community of people from the same hometown and to understand the topic and trend of nostalgia composed online. For this purpose, this study collected 144 writings which the natives of Yeongjong Island, Incheon, South-Korea have posted on an online community. And it analyzed association relations. As a result, online community texts means that just defining nostalgia as ‘a mind longing for hometown’ is not an enough explanation. Second, texts composed online have abstractness rather than persons’ individual stories. This study figured out the relationship that had the most critical and closest mutual association among the terms that constituted nostalgia through literature research and association rule concerning nostalgia. The result of this study has a characteristic that it summed up the core terms and emotions related to nostalgia.

Keywords: nostalgia, cultural memory, data mining, association rule

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Authors: Ke Qiu, Minzi Mao, Jianjun Ren, Yu Zhao

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Although much has been done to investigate the influence of obstructive sleep apnea (OSA) on cognitive function, little attention has been paid to the role which gender differences play in this association. In the present study, we aim to explore the gender-specific association between OSA and cognitive impairment. Participants from UK biobank who have completed at least one of the five baseline cognitive tests (visuospatial memory, prospective memory, fluid intelligence, short numeric memory and reaction time) were included and were further categorized into three groups: (1) OSA, (2) self-reported snoring but without OSA, and (3) healthy controls (without OSA or snoring). Multivariable regression analysis was performed to examine the associations among snoring, OSA and performance of each of the five cognitive domains. A total of 267,889 participants (47% male, mean age: 57 years old) were included in our study. In the multivariable regression analysis, female participants in the OSA group had a higher risk of having poor prospective memory (OR: 1.24, 95% CI: 1.02～1.50, p = 0.03). Meanwhile, among female participants, OSA were inversely associated with the performances of fluid intelligence (β: -0.29, 95% CI: -0.46～-0.13, p < 0.001) and short-numeric memory (β: -0.14, 95% CI: -0.35～0.08, p = 0.02). In contrast, among male participants, no significant association was observed between OSA and impairment of the five cognitive domains. Overall, OSA was significantly associated with cognitive impairment in female participants rather than in male participants, indicating that more special attention and timely interventions should be given to female OSA patients to prevent further cognitive impairment.

Keywords: obstructive sleep apnea (OSA), cognitive impairment, gender-specific association, UK biobank

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Authors: Rizka Aisha Rahmi Hariadi, Chao Ou-Yang, Han-Cheng Wang, Rajesri Govindaraju

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As the increasing of medical check-up popularity, there are a huge number of medical check-up data stored in database and have not been useful. These data actually can be very useful for future strategic planning if we mine it correctly. In other side, a lot of patients come with unpredictable coming and also limited available facilities make medical check-up service offered by hospital not maximal. To solve that problem, this study used those medical check-up data to predict patient re-coming. Sequential pattern mining (SPM) and association rules method were chosen because these methods are suitable for predicting patient re-coming using sequential data. First, based on patient personal information the data was grouped into … groups then discriminant analysis was done to check significant of the grouping. Second, for each group some frequent patterns were generated using SPM method. Third, based on frequent patterns of each group, pairs of variable can be extracted using association rules to get general pattern of re-coming patient. Last, discussion and conclusion was done to give some implications of the results.

Keywords: patient re-coming, medical check-up, health examination, data mining, sequential pattern mining, association rules, discriminant analysis

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Authors: Sahar Shams

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Coeliac disease (CD) is a widely reported disease particularly in countries with predominant Caucasian populations. It presents with many signs and symptoms including iron deficiency (ID) and iron deficiency anaemia/anaemia (IDA/A). The exact association between ID, IDA/A and CD and how accurate these signs are in diagnosing CD is not fully known. This systematic review was conducted to investigate the accuracy of both ID & IDA/A as a diagnostic indicator for CD and whether it warrants point of care testing. A systematic review was performed looking at studies published in MEDLINE, Embase, Cochrane Library, and Web of Science. QUADAS-2 tool was used to assess risk of bias in each study. ROC curve and forest plots were generated as part of the meta-analysis after data extraction. 16 studies were identified in total, 13 of which were IDA/A studies and 3 ID studies. The prevalence of CD regardless of diagnostic indicator was assumed as 1%. The QUADAS-2 tool indicated most of studies as having high risk of bias. The PPV for CD was higher in those with ID than for those with IDA/A. Meta-analysis showed the overall odds of having CD is 5 times higher in individuals with ID & IDA/A. The ROC curve showed that there is definitely an association between both diagnostic indicators and CD, the association is not a particularly strong one due to great heterogeneity between studies. Whilst an association between IDA/A & ID and coeliac disease was evident, the results were not deemed significant enough to prompt coeliac disease testing in those with IDA/A & ID.

Keywords: anemia, iron deficiency anemia, coeliac disease, point of care testing

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Authors: Zaky Musyarof, Dwi Yono Sutarto, Dwima Rindy Atika, R. B. Fajriya Hakim

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Each country should be responsible for the safety of people, especially responsible for the safety of people living in disaster-prone areas. One of those services is provides evacuation route for them. But all this time, the selection of evacuation route is seem doesn’t well organized, it could be seen that when a disaster happen, there will be many accumulation of people on the steps of evacuation route. That condition is dangerous to people because hampers evacuation process. By some methods in Statistical analysis, author tries to give a suggestion how to prepare evacuation route which is organized and based on people habit. Those methods are association rules, sequential pattern mining, hierarchical cluster analysis and fuzzy logic.

Keywords: association rules, sequential pattern mining, cluster analysis, fuzzy logic, evacuation route

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Authors: Yuqing Zou, Chunrui Zou, Yichong Cao

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Previous research has revealed relationships between self-efficacy (SE), engagement, and academic achievement among students in Western countries, but these relationships remain unknown in college math courses among college students in China. In addition, previous research has shown that test anxiety has a direct effect on engagement and academic achievement. However, how test anxiety affects the relationships between SE, engagement, and academic achievement is still unknown. In this study, the authors aimed to explore the mediating roles of behavioral engagement (BE), emotional engagement (EE), and cognitive engagement (CE) in the association between SE and academic achievement and the moderating role of test anxiety in college math courses. Our hypotheses are that the association between SE and academic achievement was mediated by engagement and that test anxiety played a moderating role in the association. To explore the research questions, the authors collected data through self-reported surveys among 147 students at a northwestern university in China. Self-reported surveys were used to collect data. The motivated strategies for learning questionnaire (MSLQ) (Pintrich, 1991), the metacognitive strategies questionnaire (Wolters, 2004), and the engagement versus disaffection with learning scale (Skinner et al., 2008) were used to assess SE, CE, and BE and EE, respectively. R software was used to analyze the data. The main analyses used were reliability and validity analysis of scales, descriptive statistics analysis of measured variables, correlation analysis, regression analysis, and structural equation modeling (SEM) analysis and moderated mediation analysis to look at the structural relationships between variables at the same time. The SEM analysis indicated that student SE was positively related to BE, EE, and CE and academic achievement. BE, EE, and CE were all positively associated with academic achievement. That is, as the authors expected, higher levels of SE led to higher levels of BE, EE, and CE, and greater academic achievement. Higher levels of BE, EE, and CE led to greater academic achievement. In addition, the moderated mediation analysis found that the path of SE to academic achievement in the model was as significant as expected, as was the moderating effect of test anxiety in the SE-Achievement association. Specifically, test anxiety was found to moderate the association between SE and BE, the association between SE and CE, and the association between EE and Achievement. The authors investigated possible mediating effects of BE, EE, and CE in the associations between SE and academic achievement, and all indirect effects were found to be significant. As for the magnitude of mediations, behavioral engagement was the most important mediator in the SE-Achievement association. This study has implications for college teachers, educators, and students in China regarding ways to promote academic achievement in college math courses, including increasing self-efficacy and engagement and lessening test anxiety toward math.

Keywords: academic engagement, self-efficacy, test anxiety, academic achievement, college math courses, behavioral engagement, cognitive engagement, emotional engagement

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Authors: Amdouni Hamida, Gammoudi Mohamed Mohsen

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In order to help the expert to validate association rules extracted from data, some quality measures are proposed in the literature. We distinguish two categories: objective and subjective measures. The first one depends on a fixed threshold and on data quality from which the rules are extracted. The second one consists on providing to the expert some tools in the objective to explore and visualize rules during the evaluation step. However, the number of extracted rules to validate remains high. Thus, the manually mining rules task is very hard. To solve this problem, we propose, in this paper, a semi-automatic method to assist the expert during the association rule's validation. Our method uses rule-based classification as follow: (i) We transform association rules into classification rules (classifiers), (ii) We use the generated classifiers for data classification. (iii) We visualize association rules with their quality classification to give an idea to the expert and to assist him during validation process.

Keywords: association rules, rule-based classification, classification quality, validation

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Authors: Diriba Dereje

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Background: Cardiac and renal disease are the most prevalent chronic non-communicable diseases (CNCD) affecting the community in a significant manner. The best and recommended method in halting CNCD is by working on prevention as early as possible. This is only possible if early surrogate markers are identified. As part of the stated solution, this study will identify an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Objective: The main aim of this study was to assess an association between microalbuminuria (an early surrogate marker of renal and cardiac disease) and lung function test among adult in the community. Methodology: Community based cross sectional study was conducted among 384 adult in Jimma town. A systematic sampling technique was used in selecting participants to the study. In searching for the possible association, binary and multivariate logistic regression and t-test was conducted. Finally, the association between microalbuminuria and lung function test was well stated in the form of figures and written description. Result and Conclusion: A significant association was found between microalbuminuria and different lung function test parameters.

Keywords: microalbuminuria, lung function, association, test

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Authors: Zi-Han Li, Zi-Jun Sun, Dong-Yuan Chang, Li Zhu, Min Chen, Ming-Hui Zhao

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Aims: A genome-wide association study (GWAS) reported that patients with the rs55703767 minor allele in collagen type IV α3 chain encoding gene COL4A3 showed protection against diabetic kidney disease (DKD) in type 1 diabetes mellitus (T1DM). However, the role of rs55703767 in type 2 DKD has not been elucidated. The aim of the current study was to investigate the association between COL4A3 variant rs55703767 and DKD risk in Chinese patients with type 2 diabetes mellitus (T2DM). Methods: This nested case-control study was performed on 1311 patients who had T2DM for at least 10 years, including 580 with DKD and 731 without DKD. We detected the genotypes of all patients by TaqMan SNP Genotyping Assay and analyzed the association between COL4A3 variant rs55703767 and DKD risk. Results: Genetic analysis revealed that there was no significant difference between T2DM patients with DKD and those without DKD regarding allele or genotype frequencies of rs55703767, and the effect of this variant was not hyperglycemia specific. Conclusion: Our findings suggested that there was no detectable association between the COL4A3 variant rs55703767 and the susceptibility to DKD in the Chinese T2DM population.

Keywords: collagen type IV α3 chain, gene polymorphism, type 2 diabetes, diabetic kidney disease

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Authors: Atefeh Esmailnejad, Gholam Reza Nikbakht Brujeni

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The major histocompatibility complex (MHC) is the best-characterized genetic region associated with susceptibility and/or resistance to a wide range of infectious diseases, autoimmune diseases and immune responses to vaccines. It has been demonstrated that there is an association between the MHC and resistance to Marek disease, Newcastle disease, Rous sarcoma tumor, Avian leucosis, Fowl cholera, Salmonellosis and Pasteurellosis in chicken. The present study evaluated the MHC polymorphism and its association with antibody response to Newcastle (ND) vaccine in Iranian native chickens. The MHC polymorphism was investigated using LEI0258 microsatellite locus by PCR-based fragment analysis. LEI0258 microsatellite marker is a genetic indicator for MHC, which is located on microchromosome 16 and strongly associated with serologically defined MHC haplotypes. Antibody titer against ND vaccine was measured by Haemaglutination Inhibition (HI) assay. Statistical analysis was performed using SPSS software (version 21). Total of 13 LEI0258 microsatellite alleles were identified in 72 samples which indicated a high genetic diversity in the population. The association study revealed a significant influence of MHC alleles on immune responses to Newcastle vaccine. 311 and 313 bp alleles were significantly associated with elevated immune responses to Newcastle vaccine (p<0.05). These results would be applicable in designing and improving the populations under selective breeding.

Keywords: chicken, LEI0258, MHC, Newcastle vaccine

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Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

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Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

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Authors: Oladele V. Adeniyi, B. Longo-Mbenza, Daniel T. Goon

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Background: Lipids are often low or in the normal ranges and controversial in the atherogenesis among Black Africans. The effect of the severity of obesity on some traditional and novel cardiovascular disease risk factors is unclear before and after a diet and exercise maintenance programme among obese black South Africans with type 2 diabetes mellitus (T2DM). Therefore, this study aimed to identify the risk factors to discriminate obesity classes among patients with T2DM before and after a diet and exercise programme. Methods: This interventional cohort of Black South Africans with T2DM was followed by a very – low calorie diet and exercise programme in Mthatha, between August and November 2013. Gender, age, and the levels of body mass index (BMI), blood pressure, monthly income, daily frequency of meals, blood random plasma glucose (RPG), serum creatinine, total cholesterol (TC), triglycerides (TG), LDL –C, HDL – C, Non-HDL, ratios of TC/HDL, TG/HDL, and LDL/HDL were recorded. Univariate analysis (ANOVA) and multivariate discriminant analysis were performed to separate obesity classes: normal weight (BMI = 18.5 – 24.9 kg/m2), overweight (BMI = 25 – 29.9 kg/m2), obesity Class 1 (BMI = 30 – 34.9 kg/m2), obesity Class 2 (BMI = 35 – 39.9 kg/m2), and obesity Class 3 (BMI ≥ 40 kg/m2). Results: At the baseline (1st Month September), all 327 patients were overweight/obese: 19.6% overweight, 42.8% obese class 1, 22.3% obese class 2, and 15.3% obese class 3. In discriminant analysis, only systolic blood pressure (SBP with positive association) and LDL/HDL ratio (negative association) significantly separated increasing obesity classes. At the post – evaluation (3rd Month November), out of all 327 patients, 19.9%, 19.3%, 37.6%, 15%, and 8.3% had normal weight, overweight, obesity class 1, obesity class 2, and obesity class 3, respectively. There was a significant negative association between serum creatinine and increase in BMI. In discriminant analysis, only age (positive association), SBP (U – shaped relationship), monthly income (inverted U – shaped association), daily frequency of meals (positive association), and LDL/HDL ratio (positive association) classified significantly increasing obesity classes. Conclusion: There is an epidemic of diabesity (Obesity + T2DM) in this Black South Africans with some weight loss. Further studies are needed to understand positive or negative linear correlations and paradoxical curvilinear correlations between these markers and increase in BMI among black South African T2DM patients.

Keywords: atherogenic dyslipidaemia, dietary interventions, obesity, south africans

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Authors: Souhir Chelly, Asma Ben Cheikh, Hela Ghali, Salwa Khefacha, Lamine Dhidah, Mohamed Ben Rejeb, Houyem Said Latiri

Abstract:

The hospital risk management department is firstly involved in the methodological analysis of grade zero sterilization incidents. The system is based on a subsequent analysis process in compliance with the ongoing requirements of the Haute Autorité de santé (HAS) for a reactive approach to risk, allowing to identify failures and start the appropriate preventive and corrective measures. The use of the association of litigation and risk management (ALARM) method makes easier the grade zero analysis and brings to light the team or institutional, organizational, temporal, individual factors representative of undesirable effects. Two main factors come out again from this analysis, pre-disinfection step of the emergency block unsupervised instrumentalist intern was poorly done since she did not remove the battery from micro air motor. At the sterilization unit, the worker who was not supervised by the nurse did the conditioning of the motor without having checked it if it still contained the battery. The main cause is that the management of human resources was inadequate at both levels, the instrumental trainee in the block who was not supervised by his supervisor and the worker of the sterilization unit who was not supervised by the responsible nurse. There is a lack of research help, advice, and collaboration. The difficulties encountered during this type of analysis are multiple. The first is based on its necessary acceptance by the various actors of care involved, which should not perceive it as a tool leading to individual punishment, but rather as a means to improve their practices.

Keywords: ALARM (Association of Litigation and Risk Management Method), incident, risk management, sterilization

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Authors: Jiajia Peng, Yijun Dong, Jianjun Ren, Yu Zhao

Abstract:

Objectives: Understanding the association between sleep traits and tinnitus could help prevent and provide appropriate interventions against tinnitus. Therefore, this study aimed to assess the relationship between different sleep patterns and tinnitus. Design: A cross-sectional analysis using baseline data (2006–2010, n=168,064) by logistic regressions was conducted to evaluate the association between sleep traits (including the overall health sleep score and five sleep behaviors), and the occurrence (yes/no), frequency (constant/transient), and severity (upsetting/not upsetting) of tinnitus. Further, a prospective analysis of participants without tinnitus at baseline (n=9,581) was performed, who had been followed up for seven years (2012–2019) to assess the association between new-onset tinnitus and sleep characteristics. Moreover, a subgroup analysis was also carried out to estimate the differences in sex by dividing the participants into male and female groups. A sensitivity analysis was also conducted by excluding ear-related diseases to avoid their confounding effects on tinnitus (n=102,159). Results: In the cross-sectional analysis, participants with “current tinnitus” (OR: 1.13, 95% CI: 1.04–1.22, p=0.004) had a higher risk of having a poor overall healthy sleep score and unhealthy sleep behaviors such as short sleep durations (OR: 1.09, 95% CI: 1.04–1.14, p<0.001), late chronotypes (OR: 1.09, 95% CI: 1.05–1.13, p<0.001), and sleeplessness (OR: 1.16, 95% CI: 1.11–1.22, p<0.001) than those participants who “did not have current tinnitus.” However, this trend was not obvious between “constant tinnitus” and “transient tinnitus.” When considering the severity of tinnitus, the risk of “upsetting tinnitus” was obviously higher if participants had lower overall healthy sleep scores (OR: 1.31, 95% CI: 1.13–1.53, p<0.001). Additionally, short sleep duration (OR: 1.22, 95% CI: 1.12–1.33, p<0.001), late chronotypes (OR: 1.13, 95% CI: 1.04–1.22, p=0.003), and sleeplessness (OR: 1.43, 95% CI: 1.29–1.59, p<0.001) showed positive correlations with “upsetting tinnitus.” In the prospective analysis, sleeplessness presented a consistently significant association with “upsetting tinnitus” (RR: 2.28, P=0.001). Consistent results were observed in the sex subgroup analysis, where a much more pronounced trend was identified in females compared with males. The results of the sensitivity analysis were consistent with those of the cross-sectional and prospective analyses. Conclusions: Different types of sleep disturbance may be associated with the occurrence and severity of tinnitus; therefore, precise interventions for different types of sleep disturbance, particularly sleeplessness, may help in the prevention and treatment of tinnitus.

Keywords: tinnitus, sleep, sleep behaviors, sleep disturbance

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