Search results for: squared prediction risk
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8082

Search results for: squared prediction risk

6462 A Convolutional Neural Network-Based Model for Lassa fever Virus Prediction Using Patient Blood Smear Image

Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

Abstract:

A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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6461 Revisiting the Fiscal Theory of Sovereign Risk from the DSGE View

Authors: Eiji Okano, Kazuyuki Inagaki

Abstract:

We revisit Uribe's `Fiscal Theory of Sovereign Risk' advocating that there is a trade-off between stabilizing inflation and suppressing default. We develop a class of dynamic stochastic general equilibrium (DSGE) model with nominal rigidities and compare two de facto inflation stabilization policies, optimal monetary policy and optimal monetary and fiscal policy with the minimizing interest rate spread policy which completely suppress the default. Under the optimal monetary and fiscal policy, not only the nominal interest rate but also the tax rate work to minimize welfare costs through stabilizing inflation. Under the optimal monetary both inflation and output gap are completely stabilized although those are fluctuating under the optimal monetary policy. In addition, volatility in the default rate under the optimal monetary policy is considerably lower than one under the optimal monetary policy. Thus, there is not the SI-SD trade-off. In addition, while the minimizing interest rate spread policy makes inflation rate severely volatile, the optimal monetary and fiscal policy stabilize both the inflation and the default. A trade-off between stabilizing inflation and suppressing default is not so severe what pointed out by Uribe.

Keywords: sovereign risk, optimal monetary policy, fiscal theory of the price level, DSGE

Procedia PDF Downloads 318
6460 Management of Blood Exposure Risk: Knowledge and Attitudes of Caregivers in Pediatric Dapartments

Authors: Hela Ghali, Oumayma Ben Amor, Salwa Khefacha, Mohamed Ben Rejeb, Sirine Frigui, Meriam Tourki Dhidah, Lamine Dhidah, Houyem Said Laatiri

Abstract:

Background: Blood exposure accidents are the most common problem in hospitals that threaten healthcare professionals with a high risk of infectious complications which weighs heavily on health systems worldwide. Paramedics are the highest risk group due to the nature of their daily activities. We aimed to determine knowledge and attitudes about the management of blood-exposure accidents among nurses and technicians in two pediatric departments. Materials/Methods: This is a cross-sectional descriptive study conducted on March 2017, carried out with the care staff of the pediatric ward of the Farhat Hached Teaching Hospital of Sousse and pediatric surgery of the Fattouma Bourguiba University Hospital in Monastir, using a pre- tested and self-administered questionnaire. Data entry and analysis were performed using Excel software. Results: The response rate was 85.1%. A female predominance (82.5%) was reported among respondents with a sex ratio of 0.21. 80% of the participants were under 35 years old. Seniority of less than 10 years was found in 77.5% of respondents. Only 22.5% knew the definition of a blood- exposure accident. 100% and 95% of participants reported the relative risk, respectively, to hepatitis and AIDS viruses. However, only 15% recognized the severity factors of a blood-exposure accident. Hygiene compliance was the most important dimension for almost the entire population for the prevention. On the other hand, only 12.5% knew the meaning of 'standard precautions' and ¼ considered them necessary for at-risk patients only. 40% reported being exposed at least once, among them, 87.5% used betadine, and 77.5% said that anti-infectious chemoprophylaxis is necessary regardless of the patient's serological status. However, 52.5% did not know the official reporting circuit of management of blood-exposure accident in their institutions. Conclusion: For better management of risks in hospitals and an improvement of the safety of the care, a reinforcement of the sensibilization of the caregivers with regard to the risks of blood exposure accident is necessary, while developing their knowledge to act in security.

Keywords: attitudes, blood-exposure accident, knowledge, pediatric department

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6459 Integrating Artificial Neural Network and Taguchi Method on Constructing the Real Estate Appraisal Model

Authors: Mu-Yen Chen, Min-Hsuan Fan, Chia-Chen Chen, Siang-Yu Jhong

Abstract:

In recent years, real estate prediction or valuation has been a topic of discussion in many developed countries. Improper hype created by investors leads to fluctuating prices of real estate, affecting many consumers to purchase their own homes. Therefore, scholars from various countries have conducted research in real estate valuation and prediction. With the back-propagation neural network that has been popular in recent years and the orthogonal array in the Taguchi method, this study aimed to find the optimal parameter combination at different levels of orthogonal array after the system presented different parameter combinations, so that the artificial neural network obtained the most accurate results. The experimental results also demonstrated that the method presented in the study had a better result than traditional machine learning. Finally, it also showed that the model proposed in this study had the optimal predictive effect, and could significantly reduce the cost of time in simulation operation. The best predictive results could be found with a fewer number of experiments more efficiently. Thus users could predict a real estate transaction price that is not far from the current actual prices.

Keywords: artificial neural network, Taguchi method, real estate valuation model, investors

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6458 Seismic Preparedness Challenge in Ionian Islands (Greece) through 'Telemachus' Project

Authors: A. Kourou, M. Panoutsopoulou

Abstract:

Nowadays, disaster risk reduction requires innovative ways of working collaboratively, monitoring tools, management methods, risk communication, and knowledge, as key factors for decision-making actors. Experience has shown that the assessment of seismic risk and its effective management is still an important challenge. In Greece, Ionian Islands region is characterized as the most seismic area of the country and one of the most active worldwide. It is well known that in case of a disastrous earthquake the local authorities need to assess the situation in the affected area and coordinate the disaster response. In particular, the main outcomes of 'Telemachus' project are the development of an innovative operational system that hosts the needed data of seismic risk management in the Ionian Islands and the implementation of educational actions for the involved target groups. This project is funded in the Priority Axis 'Environmental Protection and Sustainable Development' of Operational Plan 'Ionian Islands 2014-2020'. EPPO is one of the partners of the project and it is responsible, among others, for the development of proper training material. This paper presents the training material of 'Telemachus' and its usage as a helpful, managerial tool in case of earthquake emergency. This material is addressed to different target groups, such as civil protection staff, people that involved with the tourism industry, educators of disabled people, etc. Very positive aspect of the project is the involvement of end-users that should evaluate the training products; test standards; clarify the personnel’s roles and responsibilities; improve interagency coordination; identify gaps in resources; improve individual performance; and identify opportunities for improvement. It is worth mentioning that even though the abovementioned material developed is useful for the training of specific target groups on emergency management issues within Ionian Islands Region, it could be used throughout Greece and other countries too.

Keywords: education of civil protection staff, Ionian Islands Region of Greece, seismic risk, training material

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6457 A Holistic Analysis of the Emergency Call: From in Situ Negotiation to Policy Frameworks and Back

Authors: Jo Angouri, Charlotte Kennedy, Shawnea Ting, David Rawlinson, Matthew Booker, Nigel Rees

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Ambulance services need to balance the large volume of emergency (999 in the UK) calls they receive (e.g., West Midlands Ambulance Service reports per day about 4,000 999 calls; about 679,000 calls per year are received in Wales), with dispatching limited resource for on-site intervention to the most critical cases. The process by which Emergency Medical Dispatch (EMD) decisions are made is related to risk assessment and involves the caller and call-taker as well as clinical teams negotiating risk levels on a case-by-case basis. Medical Priority Dispatch System (MPDS – also referred to as Advanced Medical Priority Dispatch System AMPDS) are used in the UK by NHS Trusts (e.,g WAST) to process and prioritise 999 calls. MPDS / AMPDS provide structured protocols for call prioritisation and call management. Protocols/policy frameworks have not been examined before in the way we propose in our project. In more detail, the risk factors that play a role in the EMD negotiation between the caller and call-taker have been analysed in both medical and social science research. Research has focused on the structural, morphological and phonological aspects that could improve, and train, human-to-human interaction or automate risk detection, as well as the medical factors that need to be captured from the caller to inform the dispatch decision. There are two significant gaps in our knowledge that we address in our work: 1. the role of backstage clinical teams in translating the caller/call-taker interaction in their internal risk negotiation and, 2. the role of policy frameworks, protocols and regulations in the framing of institutional priorities and resource allocation. We take a multi method approach and combine the analysis of 999 calls with the analysis of policy documents. We draw on interaction analysis, corpus methodologies and thematic analysis. In this paper, we report on our preliminary findings and focus in particular on the risk factors we have identified and the relationship with the regulations that create the frame within which teams operate. We close the paper with implications of our study for providing evidence-based policy intervention and recommendations for further research.

Keywords: emergency (999) call, interaction analysis, discourse analysis, ambulance dispatch, medical discourse

Procedia PDF Downloads 98
6456 Stroke Prevention in Patients with Atrial Fibrillation and Co-Morbid Physical and Mental Health Problems

Authors: Dina Farran, Mark Ashworth, Fiona Gaughran

Abstract:

Atrial fibrillation (AF), the most prevalent cardiac arrhythmia, is associated with an increased risk of stroke, contributing to heart failure and death. In this project, we aim to improve patient safety by screening for stroke risk among people with AF and co-morbid mental illness. To do so, we started by conducting a systematic review and meta-analysis on prevalence, management, and outcomes of AF in people with Serious Mental Illness (SMI) versus the general population. We then evaluated oral anticoagulation (OAC) prescription trends in people with AF and co-morbid SMI in King’s College Hospital. We also evaluated the association between mental illness severity and OAC prescription in eligible patients in South London and Maudsley (SLaM) NHS Foundation Trust. Next, we implemented an electronic clinical decision support system (eCDSS) consisting of a visual prompt on patient electronic Personal Health Records to screen for AF-related stroke risk in three Mental Health of Older Adults wards at SLaM. Finally, we assessed the feasibility and acceptability of the eCDSS by qualitatively investigating clinicians’ perspectives of the potential usefulness of the eCDSS (pre-intervention) and their experiences and their views regarding its impact on clinicians and patients (post-intervention). The systematic review showed that people with SMI had low reported rates of AF. AF patients with SMI were less likely to receive OAC than the general population. When receiving warfarin, people with SMI, particularly bipolar disorder, experienced poor anticoagulation control compared to the general population. Meta-analysis showed that SMI was not significantly associated with an increased risk of stroke or major bleeding when adjusting for underlying risk factors. The main findings of the first observational study were that among AF patients having a high stroke risk, those with co-morbid SMI were less likely than non-SMI to be prescribed any OAC, particularly warfarin. After 2019, there was no significant difference between the two groups. In the second observational study, patients with AF and co-morbid SMI were less likely to be prescribed any OAC compared to those with dementia, substance use disorders, or common mental disorders, adjusting for age, sex, stroke, and bleeding risk scores. Among AF patients with co-morbid SMI, warfarin was less likely to be prescribed to those having alcohol or substance dependency, serious self-injury, hallucinations or delusions, and activities of daily living impairment. In the intervention, clinicians were asked to confirm the presence of AF, clinically assess stroke and bleeding risks, record risk scores in clinical notes, and refer patients at high risk of stroke to OAC clinics. Clinicians reported many potential benefits for the eCDSS, including improving clinical effectiveness, better identification of patients at risk, safer and more comprehensive care, consistency in decision making and saving time. Identified potential risks included rigidity in decision-making, overreliance, reduced critical thinking, false positive recommendations, annoyance, and increased workload. This study presents a unique opportunity to quantify AF patients with mental illness who are at high risk of severe outcomes using electronic health records. This has the potential to improve health outcomes and, therefore patients' quality of life.

Keywords: atrial fibrillation, stroke, mental health conditions, electronic clinical decision support systems

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6455 A Comparative Time-Series Analysis and Deep Learning Projection of Innate Radon Gas Risk in Canadian and Swedish Residential Buildings

Authors: Selim M. Khan, Dustin D. Pearson, Tryggve Rönnqvist, Markus E. Nielsen, Joshua M. Taron, Aaron A. Goodarzi

Abstract:

Accumulation of radioactive radon gas in indoor air poses a serious risk to human health by increasing the lifetime risk of lung cancer and is classified by IARC as a category one carcinogen. Radon exposure risks are a function of geologic, geographic, design, and human behavioural variables and can change over time. Using time series and deep machine learning modelling, we analyzed long-term radon test outcomes as a function of building metrics from 25,489 Canadian and 38,596 Swedish residential properties constructed between 1945 to 2020. While Canadian and Swedish properties built between 1970 and 1980 are comparable (96–103 Bq/m³), innate radon risks subsequently diverge, rising in Canada and falling in Sweden such that 21st Century Canadian houses show 467% greater average radon (131 Bq/m³) relative to Swedish equivalents (28 Bq/m³). These trends are consistent across housing types and regions within each country. The introduction of energy efficiency measures within Canadian and Swedish building codes coincided with opposing radon level trajectories in each nation. Deep machine learning modelling predicts that, without intervention, average Canadian residential radon levels will increase to 176 Bq/m³ by 2050, emphasizing the importance and urgency of future building code intervention to achieve systemic radon reduction in Canada.

Keywords: radon health risk, time-series, deep machine learning, lung cancer, Canada, Sweden

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6454 Assessment Using Copulas of Simultaneous Damage to Multiple Buildings Due to Tsunamis

Authors: Yo Fukutani, Shuji Moriguchi, Takuma Kotani, Terada Kenjiro

Abstract:

If risk management of the assets owned by companies, risk assessment of real estate portfolio, and risk identification of the entire region are to be implemented, it is necessary to consider simultaneous damage to multiple buildings. In this research, the Sagami Trough earthquake tsunami that could have a significant effect on the Japanese capital region is focused on, and a method is proposed for simultaneous damage assessment using copulas that can take into consideration the correlation of tsunami depths and building damage between two sites. First, the tsunami inundation depths at two sites were simulated by using a nonlinear long-wave equation. The tsunamis were simulated by varying the slip amount (five cases) and the depths (five cases) for each of 10 sources of the Sagami Trough. For each source, the frequency distributions of the tsunami inundation depth were evaluated by using the response surface method. Then, Monte-Carlo simulation was conducted, and frequency distributions of tsunami inundation depth were evaluated at the target sites for all sources of the Sagami Trough. These are marginal distributions. Kendall’s tau for the tsunami inundation simulation at two sites was 0.83. Based on this value, the Gaussian copula, t-copula, Clayton copula, and Gumbel copula (n = 10,000) were generated. Then, the simultaneous distributions of the damage rate were evaluated using the marginal distributions and the copulas. For the correlation of the tsunami inundation depth at the two sites, the expected value hardly changed compared with the case of no correlation, but the damage rate of the ninety-ninth percentile value was approximately 2%, and the maximum value was approximately 6% when using the Gumbel copula.

Keywords: copulas, Monte-Carlo simulation, probabilistic risk assessment, tsunamis

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6453 Comprehensive Machine Learning-Based Glucose Sensing from Near-Infrared Spectra

Authors: Bitewulign Mekonnen

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Context: This scientific paper focuses on the use of near-infrared (NIR) spectroscopy to determine glucose concentration in aqueous solutions accurately and rapidly. The study compares six different machine learning methods for predicting glucose concentration and also explores the development of a deep learning model for classifying NIR spectra. The objective is to optimize the detection model and improve the accuracy of glucose prediction. This research is important because it provides a comprehensive analysis of various machine-learning techniques for estimating aqueous glucose concentrations. Research Aim: The aim of this study is to compare and evaluate different machine-learning methods for predicting glucose concentration from NIR spectra. Additionally, the study aims to develop and assess a deep-learning model for classifying NIR spectra. Methodology: The research methodology involves the use of machine learning and deep learning techniques. Six machine learning regression models, including support vector machine regression, partial least squares regression, extra tree regression, random forest regression, extreme gradient boosting, and principal component analysis-neural network, are employed to predict glucose concentration. The NIR spectra data is randomly divided into train and test sets, and the process is repeated ten times to increase generalization ability. In addition, a convolutional neural network is developed for classifying NIR spectra. Findings: The study reveals that the SVMR, ETR, and PCA-NN models exhibit excellent performance in predicting glucose concentration, with correlation coefficients (R) > 0.99 and determination coefficients (R²)> 0.985. The deep learning model achieves high macro-averaging scores for precision, recall, and F1-measure. These findings demonstrate the effectiveness of machine learning and deep learning methods in optimizing the detection model and improving glucose prediction accuracy. Theoretical Importance: This research contributes to the field by providing a comprehensive analysis of various machine-learning techniques for estimating glucose concentrations from NIR spectra. It also explores the use of deep learning for the classification of indistinguishable NIR spectra. The findings highlight the potential of machine learning and deep learning in enhancing the prediction accuracy of glucose-relevant features. Data Collection and Analysis Procedures: The NIR spectra and corresponding references for glucose concentration are measured in increments of 20 mg/dl. The data is randomly divided into train and test sets, and the models are evaluated using regression analysis and classification metrics. The performance of each model is assessed based on correlation coefficients, determination coefficients, precision, recall, and F1-measure. Question Addressed: The study addresses the question of whether machine learning and deep learning methods can optimize the detection model and improve the accuracy of glucose prediction from NIR spectra. Conclusion: The research demonstrates that machine learning and deep learning methods can effectively predict glucose concentration from NIR spectra. The SVMR, ETR, and PCA-NN models exhibit superior performance, while the deep learning model achieves high classification scores. These findings suggest that machine learning and deep learning techniques can be used to improve the prediction accuracy of glucose-relevant features. Further research is needed to explore their clinical utility in analyzing complex matrices, such as blood glucose levels.

Keywords: machine learning, signal processing, near-infrared spectroscopy, support vector machine, neural network

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6452 Contrasted Mean and Median Models in Egyptian Stock Markets

Authors: Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

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Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits.

Keywords: Egyptian stock exchange, emerging markets, higher moment models, median models, mixed-integer linear programming, non-linear programming

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6451 Predicting of Hydrate Deposition in Loading and Offloading Flowlines of Marine CNG Systems

Authors: Esam I. Jassim

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The main aim of this paper is to demonstrate the prediction of the model capability of predicting the nucleation process, the growth rate, and the deposition potential of second phase particles in gas flowlines. The primary objective of the research is to predict the risk hazards involved in the marine transportation of compressed natural gas. However, the proposed model can be equally used for other applications including production and transportation of natural gas in any high-pressure flow-line. The proposed model employs the following three main components to approach the problem: computational fluid dynamics (CFD) technique is used to configure the flow field; the nucleation model is developed and incorporated in the simulation to predict the incipient hydrate particles size and growth rate; and the deposition of the gas/particle flow is proposed using the concept of the particle deposition velocity. These components are integrated in a comprehended model to locate the hydrate deposition in natural gas flowlines. The present research is prepared to foresee the deposition location of solid particles that could occur in a real application in Compressed Natural Gas loading and offloading. A pipeline with 120 m length and different sizes carried a natural gas is taken in the study. The location of particle deposition formed as a result of restriction is determined based on the procedure mentioned earlier and the effect of water content and downstream pressure is studied. The critical flow speed that prevents such particle to accumulate in the certain pipe length is also addressed.

Keywords: hydrate deposition, compressed natural gas, marine transportation, oceanography

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6450 Physical Activity Self-Efficacy among Pregnant Women with High Risk for Gestational Diabetes Mellitus: A Cross-Sectional Study

Authors: Xiao Yang, Ji Zhang, Yingli Song, Hui Huang, Jing Zhang, Yan Wang, Rongrong Han, Zhixuan Xiang, Lu Chen, Lingling Gao

Abstract:

Aim and Objectives: To examine physical activity self-efficacy, identify its predictors, and further explore the mechanism of action among the predictors in mainland Chinese pregnant women with high risk for gestational diabetes mellitus (GDM). Background: Physical activity could protect pregnant women from developing GDM. Physical activity self-efficacy was the key predictor of physical activity. Design: A cross-sectional study was conducted from October 2021 to May 2022 in Zhengzhou, China. Methods: 252 eligible pregnant women completed the Pregnancy Physical Activity Self-efficacy Scale, the Social Support for Physical Activity Scale, the Knowledge on Physical Activity Questionnaire, the 7-item Generalized Anxiety Disorder scale, the Edinburgh Postnatal Depression Scale, and a socio-demographic data sheet. Multiple linear regression was applied to explore the predictors of physical activity self-efficacy. Structural equation modeling was used to explore the mechanism of action among the predictors. Results: Chinese pregnant women with a high risk for GDM reported a moderate level of physical activity self-efficacy. The best-fit regression analysis revealed four variables explained 17.5% of the variance in physical activity self-efficacy. Social support for physical activity was the strongest predictor, followed by knowledge of the physical activity, intention to do physical activity, and anxiety symptoms. The model analysis indicated that knowledge of physical activity could release anxiety and depressive symptoms and then increase physical activity self-efficacy. Conclusion: The present study revealed a moderate level of physical activity self-efficacy. Interventions targeting pregnant women with high risk for GDM need to include the predictors of physical activity self-efficacy. Relevance to clinical practice: To facilitate pregnant women with high risk for GDM to engage in physical activity, healthcare professionals may find assess physical activity self-efficacy and intervene as soon as possible on their first antenatal visit. Physical activity intervention programs focused on self-efficacy may be conducted in further research.

Keywords: physical activity, gestational diabetes, self-efficacy, predictors

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6449 Safety Climate Assessment and Its Impact on the Productivity of Construction Enterprises

Authors: Krzysztof J. Czarnocki, F. Silveira, E. Czarnocka, K. Szaniawska

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Research background: Problems related to the occupational health and decreasing level of safety occur commonly in the construction industry. Important factor in the occupational safety in construction industry is scaffold use. All scaffolds used in construction, renovation, and demolition shall be erected, dismantled and maintained in accordance with safety procedure. Increasing demand for new construction projects unfortunately still is linked to high level of occupational accidents. Therefore, it is crucial to implement concrete actions while dealing with scaffolds and risk assessment in construction industry, the way on doing assessment and liability of assessment is critical for both construction workers and regulatory framework. Unfortunately, professionals, who tend to rely heavily on their own experience and knowledge when taking decisions regarding risk assessment, may show lack of reliability in checking the results of decisions taken. Purpose of the article: The aim was to indicate crucial parameters that could be modeling with Risk Assessment Model (RAM) use for improving both building enterprise productivity and/or developing potential and safety climate. The developed RAM could be a benefit for predicting high-risk construction activities and thus preventing accidents occurred based on a set of historical accident data. Methodology/Methods: A RAM has been developed for assessing risk levels as various construction process stages with various work trades impacting different spheres of enterprise activity. This project includes research carried out by teams of researchers on over 60 construction sites in Poland and Portugal, under which over 450 individual research cycles were carried out. The conducted research trials included variable conditions of employee exposure to harmful physical and chemical factors, variable levels of stress of employees and differences in behaviors and habits of staff. Genetic modeling tool has been used for developing the RAM. Findings and value added: Common types of trades, accidents, and accident causes have been explored, in addition to suitable risk assessment methods and criteria. We have found that the initial worker stress level is more direct predictor for developing the unsafe chain leading to the accident rather than the workload, or concentration of harmful factors at the workplace or even training frequency and management involvement.

Keywords: safety climate, occupational health, civil engineering, productivity

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6448 A Semantic and Concise Structure to Represent Human Actions

Authors: Tobias Strübing, Fatemeh Ziaeetabar

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Humans usually manipulate objects with their hands. To represent these actions in a simple and understandable way, we need to use a semantic framework. For this purpose, the Semantic Event Chain (SEC) method has already been presented which is done by consideration of touching and non-touching relations between manipulated objects in a scene. This method was improved by a computational model, the so-called enriched Semantic Event Chain (eSEC), which incorporates the information of static (e.g. top, bottom) and dynamic spatial relations (e.g. moving apart, getting closer) between objects in an action scene. This leads to a better action prediction as well as the ability to distinguish between more actions. Each eSEC manipulation descriptor is a huge matrix with thirty rows and a massive set of the spatial relations between each pair of manipulated objects. The current eSEC framework has so far only been used in the category of manipulation actions, which eventually involve two hands. Here, we would like to extend this approach to a whole body action descriptor and make a conjoint activity representation structure. For this purpose, we need to do a statistical analysis to modify the current eSEC by summarizing while preserving its features, and introduce a new version called Enhanced eSEC or (e2SEC). This summarization can be done from two points of the view: 1) reducing the number of rows in an eSEC matrix, 2) shrinking the set of possible semantic spatial relations. To achieve these, we computed the importance of each matrix row in an statistical way, to see if it is possible to remove a particular one while all manipulations are still distinguishable from each other. On the other hand, we examined which semantic spatial relations can be merged without compromising the unity of the predefined manipulation actions. Therefore by performing the above analyses, we made the new e2SEC framework which has 20% fewer rows, 16.7% less static spatial and 11.1% less dynamic spatial relations. This simplification, while preserving the salient features of a semantic structure in representing actions, has a tremendous impact on the recognition and prediction of complex actions, as well as the interactions between humans and robots. It also creates a comprehensive platform to integrate with the body limbs descriptors and dramatically increases system performance, especially in complex real time applications such as human-robot interaction prediction.

Keywords: enriched semantic event chain, semantic action representation, spatial relations, statistical analysis

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6447 Shear Stress and Effective Structural Stress ‎Fields of an Atherosclerotic Coronary Artery

Authors: Alireza Gholipour, Mergen H. Ghayesh, Anthony Zander, Stephen J. Nicholls, Peter J. Psaltis

Abstract:

A three-dimensional numerical model of an atherosclerotic coronary ‎artery is developed for the determination of high-risk situation and ‎hence heart attack prediction. Employing the finite element method ‎‎(FEM) using ANSYS, fluid-structure interaction (FSI) model of the ‎artery is constructed to determine the shear stress distribution as well ‎as the von Mises stress field. A flexible model for an atherosclerotic ‎coronary artery conveying pulsatile blood is developed incorporating ‎three-dimensionality, artery’s tapered shape via a linear function for ‎artery wall distribution, motion of the artery, blood viscosity via the ‎non-Newtonian flow theory, blood pulsation via use of one-period ‎heartbeat, hyperelasticity via the Mooney-Rivlin model, viscoelasticity ‎via the Prony series shear relaxation scheme, and micro-calcification ‎inside the plaque. The material properties used to relate the stress field ‎to the strain field have been extracted from clinical data from previous ‎in-vitro studies. The determined stress fields has potential to be used as ‎a predictive tool for plaque rupture and dissection.‎ The results show that stress concentration due to micro-calcification ‎increases the von Mises stress significantly; chance of developing a ‎crack inside the plaque increases. Moreover, the blood pulsation varies ‎the stress distribution substantially for some cases.‎

Keywords: atherosclerosis, fluid-structure interaction‎, coronary arteries‎, pulsatile flow

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6446 A Fuzzy TOPSIS Based Model for Safety Risk Assessment of Operational Flight Data

Authors: N. Borjalilu, P. Rabiei, A. Enjoo

Abstract:

Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

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6445 Stress Concentration and Strength Prediction of Carbon/Epoxy Composites

Authors: Emre Ozaslan, Bulent Acar, Mehmet Ali Guler

Abstract:

Unidirectional composites are very popular structural materials used in aerospace, marine, energy and automotive industries thanks to their superior material properties. However, the mechanical behavior of composite materials is more complicated than isotropic materials because of their anisotropic nature. Also, a stress concentration availability on the structure, like a hole, makes the problem further complicated. Therefore, enormous number of tests require to understand the mechanical behavior and strength of composites which contain stress concentration. Accurate finite element analysis and analytical models enable to understand mechanical behavior and predict the strength of composites without enormous number of tests which cost serious time and money. In this study, unidirectional Carbon/Epoxy composite specimens with central circular hole were investigated in terms of stress concentration factor and strength prediction. The composite specimens which had different specimen wide (W) to hole diameter (D) ratio were tested to investigate the effect of hole size on the stress concentration and strength. Also, specimens which had same specimen wide to hole diameter ratio, but varied sizes were tested to investigate the size effect. Finite element analysis was performed to determine stress concentration factor for all specimen configurations. For quasi-isotropic laminate, it was found that the stress concentration factor increased approximately %15 with decreasing of W/D ratio from 6 to 3. Point stress criteria (PSC), inherent flaw method and progressive failure analysis were compared in terms of predicting the strength of specimens. All methods could predict the strength of specimens with maximum %8 error. PSC was better than other methods for high values of W/D ratio, however, inherent flaw method was successful for low values of W/D. Also, it is seen that increasing by 4 times of the W/D ratio rises the failure strength of composite specimen as %62.4. For constant W/D ratio specimens, all the strength prediction methods were more successful for smaller size specimens than larger ones. Increasing the specimen width and hole diameter together by 2 times reduces the specimen failure strength as %13.2.

Keywords: failure, strength, stress concentration, unidirectional composites

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6444 Protection from Risks of Natural Disasters and Social and Economic Support to the Native Population

Authors: Maria Angela Bedini, Fabio Bronzini

Abstract:

The risk of natural disasters affects all the countries of the world, whether it refers to seismic events or tsunamis or hydrogeological disasters. In most cases, the risk can be considered in its three components: hazard, exposure, vulnerability (and urban vulnerability). The aim of this paper is to evaluate how the Italian scientific community has related the contribution of these three components, superimposing the three different maps that summarize the fundamental structure of the risk. Based on the three components considered, the study applies the Regional Planning methodology on the three phases of the risk protection and mitigation process: the prevention phase, the emergency intervention phase, the post-disaster phase. The paper illustrates the Italian experience of the pre-during-post-earthquake intervention. Main results: The study deepens these aspects in the belief that “a historical center” and an “island” can present similar problems at the international level, both in the phase of prevention (earthquake, tsunamis, hydrogeological disasters), in emergency phase (protocols and procedures of intervention) and in the post-disaster phase. The conclusions of the research identify the need to plan in advance how to deal with the post-disaster phase and consider it a priority with respect to the simple reconstruction of destroyed buildings. In fact the main result of the post-disaster intervention must be the return and the social and economic support of the indigenous population, and not only the construction of new housing and equipment. In this sense, the results of the research show that the elderly inhabitants of a historic center can be compared to the indigenous population of an atoll of fishermen, as both constitute the most important resource: the human resource. Their return in conditions of security testifies, with their presence, the culture, customs, and values rooted in the history of a people.

Keywords: post-disaster interventions, risk of natural disasters in Italy and abroad, seismic events in Italy, social and economic protection and support for the native population of historical centers

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6443 Capacities of Early Childhood Education Professionals for the Prevention of Social Exclusion of Children

Authors: Dejana Bouillet, Vlatka Domović

Abstract:

Both policymakers and researchers recognize that participating in early childhood education and care (ECEC) is useful for all children, especially for those who are exposed to the high risk of social exclusion. Social exclusion of children is understood as a multidimensional construct including economic, social, cultural, health, and other aspects of disadvantage and deprivation, which individually or combined can have an unfavorable effect on the current life and development of a child, as well as on the child’s development and on disadvantaged life chances in adult life. ECEC institutions should be able to promote educational approaches that portray developmental, cultural, language, and other diversity amongst children. However, little is known about the ways in which Croatian ECEC institutions recognize and respect the diversity of children and their families and how they respond to their educational needs. That is why this paper is dedicated to the analysis of the capacities of ECEC professionals to respond to the demands of educational needs of this very diverse group of children and their families. The results obtained in the frame of the project “Models of response to educational needs of children at risk of social exclusion in ECEC institutions,” funded by the Croatian Science Foundation, will be presented. The research methodology arises from explanations of educational processes and risks of social exclusion as a complex and heterogeneous phenomenon. The preliminary results of the qualitative data analysis of educational practices regarding capacities to identify and appropriately respond to the requirements of children at risk of social exclusion will be presented. The data have been collected by interviewing educational staff in 10 Croatian ECEC institutions (n = 10). The questions in the interviews were related to various aspects of inclusive institutional policy, culture, and practices. According to the analysis, it is possible to conclude that Croatian ECEC professionals are still faced with great challenges in the process of implementation of inclusive policies, culture, and practices. There are several baselines of this conclusion. The interviewed educational professionals are not familiar enough with the whole complexity and diversity of needs of children at risk of social exclusion, and the ECEC institutions do not have enough resources to provide all interventions that these children and their families need.

Keywords: children at risk of social exclusion, ECEC professionals, inclusive policies, culture and practices, quallitative analysis

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6442 Reducing Crash Risk at Intersections with Safety Improvements

Authors: Upal Barua

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Crash risk at intersections is a critical safety issue. This paper examines the effectiveness of removing an existing off-set at an intersection by realignment, in reducing crashes. Empirical Bayes method was applied to conduct a before-and-after study to assess the effect of this safety improvement. The Transportation Safety Improvement Program in Austin Transportation Department completed several safety improvement projects at high crash intersections with a view to reducing crashes. One of the common safety improvement techniques applied was the realignment of intersection approaches removing an existing off-set. This paper illustrates how this safety improvement technique is applied at a high crash intersection from inception to completion. This paper also highlights the significant crash reductions achieved from this safety improvement technique applying Empirical Bayes method in a before-and-after study. The result showed that realignment of intersection approaches removing an existing off-set can reduce crashes by 53%. This paper also features the state of the art techniques applied in planning, engineering, designing and construction of this safety improvement, key factors driving the success, and lessons learned in the process.

Keywords: crash risk, intersection, off-set, safety improvement technique, before-and-after study, empirical Bayes method

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6441 Cultural Collisions, Ethics and HIV: On Local Values in a Globalized Medical World

Authors: Norbert W. Paul

Abstract:

In 1988, parts of the scientific community still heralded findings to support that AIDS was likely to remain largely a ‘gay disease’. The value-ladden terminology of some of the articles suggested that rectum and fragile urethra are not sufficiently robust to provide a barrier against infectious fluids, especially body fluids contaminated with HIV while the female vagina, would provide natural protection against injuries and trauma facilitating HIV-infection. Anal sexual intercourse was constituted not only as dangerous but also as unnatural practice, while penile-vaginal intercourse would follow natural design and thus be relatively safe practice minimizing the risk of HIV. Statements like the latter were not uncommon in the early times of HIV/AIDS and contributed to captious certainties and an underestimation of heterosexual risks. Pseudo-scientific discourses on the origin of HIV were linked to local and global health politics in the 1980ies. The pathways of infection were related to normative concepts like deviant, subcultural behavior, cultural otherness, and guilt used to target, tag and separate specific groups at risk from the ‘normal’ population. Controlling populations at risk became the top item on the agenda rather than controlling modes of transmission and the virus. Hence, the Thai strategy to cope with HIV/AIDS by acknowledging social and sexual practices as they were – not as they were imagined – has become a role model for successful prevention in the highly scandalized realm of sexually transmitted disease. By accepting the globalized character of local HIV-risk and projecting the risk onto populations which are neither particularly vocal groups nor vested with the means to strive for health and justice Thailand managed to culturally implement knowledge-based tools of prevention. This paper argues, that pertinent cultural collisions regarding our strategies to cope with HIV/AIDS are deeply rooted in misconceptions, misreadings and scandalizations brought about in the early history of HIV in the 1980ties. The Thai strategy is used to demonstrate how local values can be balanced against globalized health risk and used to effectuated prevention by which knowledge and norms are translated into local practices. Issues of global health and injustice will be addressed in the final part of the paper dealing with the achievability of health as a human right.

Keywords: bioethics, HIV, global health, justice

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6440 Predicting Stack Overflow Accepted Answers Using Features and Models with Varying Degrees of Complexity

Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

Abstract:

Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

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6439 Corporate Governance and Performance of Islamic Banks in GCC Countries

Authors: Samir Srairi

Abstract:

This paper investigates the impact of the internal corporate governance on bank performance by constructing a corporate governance index (CGI) for 27 Islamic banks operating in five Arab Gulf countries. Using content analysis on the banks’ annual reports for 3 years (2011-2013), the index construction uses information on six important corporate governance mechanisms, namely board structure, risk management, transparency and disclosure, audit committee, Sharia supervisory board and investment account holders. The results demonstrate that Islamic banks adhere to 54% of the attributes addressed in the CGI. The most frequently reported and disclosed elements are Sharia supervisory board followed by board structure and risk management. The findings related to countries revealed that only two countries, the United Arab Emirates and Bahrain, possess a higher level of CGI. Our regression results provide evidence that Islamic banks with higher levels of corporate governance report high operating performance measured by return on assets and net interest margin. Finally, as of the effect of internal and external factors, we identified four variables that were associated with bank performance, namely size, equity, risk and concentration.

Keywords: governance mechanisms, corporate governance index, bank performance, Islamic banks, GCC countries

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6438 Prevalence of Iron Deficiency Anaemia and Its Impact on Nutritional Status of Rural Pregnant Women

Authors: Nuzhat Sultana

Abstract:

Iron deficiency (IDA) is the commonest nutritional anemia present in Indian pregnant women. The overall development of a fetus is determined to a great extent by the type of nourishment mother receives right from its conception. To study the risk factors of iron deficiency anemia, two hundred rural pregnant women in the age of 15-35 years in the second trimester of pregnancy from the countryside of Beed district was selected. These samples were divided into groups 'A' (experimental samples) and 'C' (control samples). Experimental samples were received oral supplementation of iron and folic acid for ninety days, but control samples did not receive any supplementation. All the samples were observed anthropometrically, biochemically and clinically before and after supplementation. The study result shows that maximum numbers of i.e. 75% pregnant women had low levels of weight and hemoglobin as compared to standard weight and HB level. However, after supplementation only in experimental group weight and HB level was increased. It was observed that prevalence of risk factors associated with anemia was higher in rural pregnant women. Poverty, illiteracy, faulty food habits, and poor intake of iron during pregnancy are the main causative factors for iron deficiency anemia in rural pregnant women.

Keywords: iron deficiency, anemia, risk factors, pregnancy

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6437 Self-Disclosure and Suicide

Authors: Netta Horesh Reinman

Abstract:

The inability to communicate feelings and thoughts to people close to oneself may be an important risk factor for suicidal behavior. This inability has been operationalized in the concept of “self-disclosure.” The purpose of this paper was to evaluate the correlation of self-disclosure with suicidal behavior in adolescents. Eighty consecutive admissions to an adolescent psychiatric inpatient unit were evaluated. Thirty-four were suicide attempters, 18 were suicidal ideators, and 18 were non-suicidal. Assessment measures included the Child Suicide Potential Scale, the Suicide Intent Scale, the Suicide Ideation Scale, and the Self-Disclosure Scale. The results show that low self-disclosure levels are associated with suicidal thinking, suicide attempts and suicidal attitudes. Thus, low self-disclosure may well be a risk factor worthy of further evaluation in the attempt to understand adolescent suicidal behavior.

Keywords: self disclosure, suicide, adolescents, treatment

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6436 Correlation between Peripheral Arterial Disease and Coronary Artery Disease in Bangladeshi Population: A Five Years Retrospective Study

Authors: Syed Dawood M. Taimur

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Background: Peripheral arterial disease (PAD) is under diagnosed in primary care practices, yet the extent of unrecognized PAD in patients with coronary artery disease (CAD) is unknown. Objective: To assess the prevalence of previously unrecognized PAD in patients undergoing coronary angiogram and to determine the relationship between the presence of PAD and severity of CAD. Material & Methods: This five years retrospective study was conducted at an invasive lab of the department of Cardiology, Ibrahim Cardiac Hospital & Research Institute from January 2010 to December 2014. Total 77 patients were included in this study. Study variables were age, sex, risk factors like hypertension, diabetes mellitus, dyslipidaemia, smoking habit and positive family history for ischemic heart disease, coronary artery and peripheral artery profile. Results: Mean age was 56.83±13.64 years, Male mean age was 53.98±15.08 years and female mean age was 54.5±1.73years. Hypertension was detected in 55.8%, diabetes in 87%, dyslipidaemia in 81.8%, smoking habits in 79.2% and 58.4% had a positive family history. After catheterization 88.3% had peripheral arterial disease and 71.4% had coronary artery disease. Out of 77 patients, 52 had both coronary and peripheral arterial disease which was statistically significant (p < .014). Coronary angiogram revealed 28.6% (22) patients had triple vessel disease, 23.3% (18) had single vessel disease, 19.5% (15) had double vessel disease and 28.6% (22) were normal coronary arteries. The peripheral angiogram revealed 54.5% had superficial femoral artery disease, 26% had anterior tibial artery disease, 27.3% had posterior tibial artery disease, 20.8% had common iliac artery disease, 15.6% had common femoral artery disease and 2.6% had renal artery disease. Conclusion: There is a strong and definite correlation between coronary and peripheral arterial disease. We found that cardiovascular risk factors were in fact risk factors for both PAD and CAD.

Keywords: coronary artery disease (CAD), peripheral artery disease(PVD), risk, factors, correlation, cathetarization

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6435 Effectiveness of Project Grit in Building Resilience among At-Risk Adolescents: A Case Study

Authors: Narash Narasimman, Calvin Leong Jia Jun, Raksha Karthik, Paul Englert

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Background: Project Grit, a 12-week youth resilience program implemented by Impart and Spartans Boxing Club, aimed to help at-risk adolescents develop resilience through psychoeducation and mental health techniques for dealing with everyday stressors and adversity. The programme consists of two parts-1.5 hours of group therapy followed by 1 hour of boxing. Due to the novelty of the study, 6 male participants, aged 13 to 18, were recruited to participate in the study. Aim: This case study aims to examine the effectiveness of Project Grit in building resilience among at-risk adolescents. Methods: A case study design was employed to capture the complexity and uniqueness of the intervention, without oversimplifying or generalizing it. A 15-year-old male participant with a history of behavioural challenges, delinquency and gang involvement was selected for the study. Teacher, parent and child versions of the Strengths and Difficulties Questionnaire (SDQ) were administered to the facilitators, parents and participants respectively before and after the programme. Relevant themes from the qualitative interviews will be discussed. Results: Scores from all raters revealed improvements in most domains of the SDQ. Total difficulties scores across all raters improved from “very high” to “close to average”. High interrater reliability was observed (κ= .81). The participant reported learning methods to effectively deal with his everyday concerns using healthy coping strategies, developing a supportive social network, and building on his self efficacy. Themes from the subject’s report concurred with the improvement in SDQ scores. Conclusions: The findings suggest that Project Grit is a promising intervention for promoting resilience among at-risk adolescents. The teleological behaviourism framework and the combination of sports engagement and future orientation may be particularly effective in fostering resilience among this population. Further studies need to be conducted with a larger sample size to further validate the effectiveness of Project Grit.

Keywords: resilience, project grit, adolescents, at-risk, boxing, future orientation

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6434 Dermatological Study on Risk Factors for Pruritic Skin: Skin Properties of Elderly

Authors: Dianis Wulan Sari, Takeo Minematsu, Mikako Yoshida, Hiromi Sanada

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Introduction: Pruritus is diagnosed as itching without macroscopic abnormalities on skin. It is the most skin complaint of elderly people. In the present study, we conducted a dermatological study to examine the risk factors of pruritic skin and predicted how to prevent pruritus especially in the elderly population. Pruritus is caused several types of inflammation, including epidermal innate immunity based on keratinocyte responses and acquired immunity regulated by type 1 or 2 helper T (Th) cells. The triggers of pruritus differ among inflammation types, therefore we did separately assess the pruritus-associated factors of each inflammation type in an effort to contribute to the identification of intervention targets for preventing pruritus. Therefore, this study aimed to investigate the factors related with actual condition of pruritic skin by examine the skin properties. Method: This study was conducted in elderly population of Indonesian nursing home. Basic characteristics and behaviors were obtained by interview. The properties of pruritic skin were collected by examination of skin biomarker using skin blotting as novel method of non-invasive skin assessment method and examination of skin barrier function using stratum corneum hydration and skin pH. Result: The average age of participants was 74 years with independent status was 66.8%. Age (β = -0.130, p = 0.044), cumulative lifetime sun exposure (β = 0.145, p = 0.026), bathing duration (β = 0.151, p = 0.022), clothing change frequency (β = 0.135, p = 0.029), and clothing type (β = -0.139, p = 0.021) were risk factors of pruritic skin in multivariate analysis. Conclusion: Risk factors of pruritic skin in elderly population were caused by internal factors such as skin senescence and external factors such as sun exposure, hygiene care and skin care behavior.

Keywords: aging, hygiene care, pruritus, skin care, sun exposure

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6433 Association of MIR146A rs2910164 Variation with a Predisposition to Sporadic Breast Cancer in a Pakistani Cohort

Authors: Mushtaq Ahmad, Bashir Rahman, Taqweem-ul-Haq, Fazal Jalil, Aftab Ali Shah

Abstract:

Single nucleotide polymorphisms (SNPs) in genes coding for microRNAs (miRNAs) play a pivotal role in the progression of breast cancer (BC). We investigated the association of miR-146a rs2910164 G/C polymorphism with the risk of BC in the Pakistani population. The miR-146a rs2910164 polymorphism was genotyped in 300 BC-cases and 300 age- and gender-matched healthy controls using T-ARMS-PCR. Genotype and allele frequencies were calculated, and the association between genotypes and the risk of BC was calculated by odds ratios (OR) and confidence intervals (95%). A significant difference in genotypic frequencies (χ2=63.10; p ≤ 0.0001) and allelic frequencies (OR=0.3955 (0.3132-0.4993); p ≤ 0.0001) was observed between cases and controls. Furthermore, we also found that miR-146 rs2910164 CC homozygote increased the risk of breast cancer in the dominant (OR=0.2397 (0.1629-0.3526); p=0.0001; GG vs GC+CC) and recessive (OR=2.803 (1.865- 4.213); P ≤ 0.0001; CC vs GC+GG) inheritance models. In summary, miR-146a rs2910164 G/C is significantly associated with BC in the Pakistani population. To our knowledge, this is the first study that assessed MIR146a rs2910164 G > C SNP in Pakistani population. By analyzing the secondary structure of MIR146A variant, a significant structural modification was noted. Study with a larger sample size is needed to further confirm these findings.

Keywords: breast cancer, MIR146A, microRNA, SNP

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