Search results for: risk prediction model

Authors: A. Samer Ezeldin, Jwanda M. El Sarag

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Variation orders are of great importance in any construction project. Variation orders are defined as any change in the scope of works of a project that can be an addition omission, or even modification. This paper investigates the variation orders that occur during construction projects in Egypt. The literature review represents a comparison of causes of variation orders among Egypt, Tanzania, Nigeria, Malaysia and the United Kingdom. A classification of occurrence of variation orders due to owner related factors, consultant related factors and other factors are signified in the literature review. These classified events that lead to variation orders were introduced in a survey with 19 events to observe their frequency of occurrence, and their time and cost impacts. The survey data was obtained from 87 participants that included clients, consultants, and contractors and a database of 42 scenarios was created. A model is then developed to help assist project managers in predicting the frequency of variations and account for a budget for any additional costs and minimize any delays that can take place. Two experts with more than 25 years of experience were given the model to verify that the model was working effectively. The model was then validated on a residential compound that was completed in July 2016 to prove that the model actually produces acceptable results.

Keywords: construction, cost impact, Egypt, time impact, variation orders

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Authors: Yves Lacroix, Van Van Than, Didier Léandri, Pierre Liardet

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The western Tombolo of the Giens peninsula in southern France, known as Almanarre beach, is subject to coastal erosion. We are trying to use computer simulation in order to propose solutions to stop this erosion. Our aim was first to determine the main factors for this erosion and successfully apply a coupled hydro-sedimentological numerical model based on observations and measurements that have been performed on the site for decades. We have gathered all available information and data about waves, winds, currents, tides, bathymetry, coastal line, and sediments concerning the site. These have been divided into two sets: one devoted to calibrating a numerical model using Mike 21 software, the other to serve as a reference in order to numerically compare the present situation to what it could be if we implemented different types of underwater constructions. This paper presents the first part of the study: selecting and melting different sources into a coherent data basis, identifying the main erosion factors, and calibrating the coupled software model against the selected reference period. Our results bring calibration of the numerical model with good fitting coefficients. They also show that the winter South-Western storm events conjugated to depressive weather conditions constitute a major factor of erosion, mainly due to wave impact in the northern part of the Almanarre beach. Together, current and wind impact is shown negligible.

Keywords: Almanarre beach, coastal erosion, hydro-sedimentological, numerical model

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Authors: S. Vavias, T. R. Brewer, T. S. Farewell

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Coastal floods have been identified as an important natural hazard that can cause significant damage to the populated built-up areas, related infrastructure and also ecosystems and habitats. This study attempts to fill the gap associated with the development of preliminary assessments of coastal flood vulnerability for compliance with the EU Directive on the Assessment and Management of Flood Risks (2007/60/EC). In this context, a methodology has been created by taking into account three major parameters; the maximum wave run-up modelled from historical weather observations, the highest tide according to historic time series, and the sea level rise projections due to climate change. A high resolution digital terrain model (DTM) derived from LIDAR data has been used to integrate the estimated flood events in a GIS environment. The flood vulnerability map created shows potential risk areas and can play a crucial role in the coastal zone planning process. The proposed method has the potential to be a powerful tool for policy and decision makers for spatial planning and strategic management.

Keywords: coastal floods, vulnerability mapping, climate change, extreme weather events

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Authors: Rossella Arcucci, Luisa D'Amore, Simone Celestino, Giuseppe Scotti, Giuliano Laccetti

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This work is the first dowel in a rather wide research activity in collaboration with Euro Mediterranean Center for Climate Changes, aimed at introducing scalable approaches in Ocean Circulation Models. We discuss designing and implementation of a parallel algorithm for solving the Variational Data Assimilation (DA) problem on Graphics Processing Units (GPUs). The algorithm is based on the fully scalable 3DVar DA model, previously proposed by the authors, which uses a Domain Decomposition approach (we refer to this model as the DD-DA model). We proceed with an incremental porting process consisting of 3 distinct stages: requirements and source code analysis, incremental development of CUDA kernels, testing and optimization. Experiments confirm the theoretic performance analysis based on the so-called scale up factor demonstrating that the DD-DA model can be suitably mapped on GPU architectures.

Keywords: data assimilation, GPU architectures, ocean models, parallel algorithm

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Authors: İbrahi̇m Kara, Seher Arslankaya

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Frequently preferred in the field of engineering in particular, data mining has now begun to be used in the field of health as well since the data in the health sector have reached great dimensions. With data mining, it is aimed to reveal models from the great amounts of raw data in agreement with the purpose and to search for the rules and relationships which will enable one to make predictions about the future from the large amount of data set. It helps the decision-maker to find the relationships among the data which form at the stage of decision-making. In this study, it is aimed to determine the risk of heart attack at the first stage, to control it, and to make its resource planning with the method of data mining. Through the early and correct diagnosis of heart attacks, it is aimed to reveal the factors which affect the diseases, to protect health and choose the right treatment methods, to reduce the costs in health expenditures, and to shorten the durations of patients’ stay at hospitals. In this way, the diagnosis and treatment costs of a heart attack will be scrutinized, which will be useful to determine the risk of the disease at the first stage, to control it, and to make its resource planning.

Keywords: data mining, decision support systems, heart attack, health sector

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Authors: Rimeyah H. S. Almutairi, Alaa Eldin A. Ayoub

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The aim of this study was to identify empirical and theoretical studies that explored giftedness theories and identification. In order to assess and synthesize the mechanisms, outcomes, and impacts of gifted identification models. Thus, we sought to provide an evidence-informed answer to how does current giftedness theories work and effectiveness. In order to develop a model that incorporates the advantages of existing models and avoids their disadvantages as much as possible. We conducted a systematic literature review (SLR). The disciplined analysis resulted in a final sample consisting of 30 appropriate searches. The results indicated that: (a) there is no uniform and consistent definition of Giftedness; (b) researchers are using several non-consistent criteria to detect gifted, and (d) The detection of talent is largely limited to early ages, and there is obvious neglect of adults. This study contributes to the development of Giftedness Cloud Model (GCM) which defined as a model that attempts to interpretation giftedness within an interactive psychological and ecological framework. GCM aims to help a talented to reach giftedness core and manifestation talent in creative productivity or invention. Besides that, GCM suggests classifying giftedness into four levels of mastery, excellence, creative productivity, and manifestation. In addition, GCM presents an idea to distinguish between talent and giftedness.

Keywords: giftedness cloud model, talent, systematic literature review, giftedness concept

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Authors: Eugen Rusu

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The objective of the work proposed is to perform an analysis of the wave conditions in the Black Sea basin. This is especially focused on the spatial and temporal occurrences and on the dynamics of the most extreme storms in the context of the climate changes. A numerical modelling system, based on the spectral phase averaged wave model SWAN, has been implemented and validated against both in situ measurements and remotely sensed data, all along the sea. Moreover, a successive correction method for the assimilation of the satellite data has been associated with the wave modelling system. This is based on the optimal interpolation of the satellite data. Previous studies show that the process of data assimilation improves considerably the reliability of the results provided by the modelling system. This especially concerns the most sensitive cases from the point of view of the accuracy of the wave predictions, as the extreme storm situations are. Following this numerical approach, it has to be highlighted that the results provided by the wave modelling system above described are in general in line with those provided by some similar wave prediction systems implemented in enclosed or semi-enclosed sea basins. Simulations of this wave modelling system with data assimilation have been performed for the 30-year period 1987-2016. Considering this database, the next step was to analyze the intensity and the dynamics of the higher storms encountered in this period. According to the data resulted from the model simulations, the western side of the sea is considerably more energetic than the rest of the basin. In this western region, regular strong storms provide usually significant wave heights greater than 8m. This may lead to maximum wave heights even greater than 15m. Such regular strong storms may occur several times in one year, usually in the wintertime, or in late autumn, and it can be noticed that their frequency becomes higher in the last decade. As regards the case of the most extreme storms, significant wave heights greater than 10m and maximum wave heights close to 20m (and even greater) may occur. Such extreme storms, which in the past were noticed only once in four or five years, are more recent to be faced almost every year in the Black Sea, and this seems to be a consequence of the climate changes. The analysis performed included also the dynamics of the monthly and annual significant wave height maxima as well as the identification of the most probable spatial and temporal occurrences of the extreme storm events. Finally, it can be concluded that the present work provides valuable information related to the characteristics of the storm conditions and on their dynamics in the Black Sea. This environment is currently subjected to high navigation traffic and intense offshore and nearshore activities and the strong storms that systematically occur may produce accidents with very serious consequences.

Keywords: Black Sea, extreme storms, SWAN simulations, waves

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Authors: A. M. Halahla, M. H. Baluch, M. K. Rahman, A. H. Al-Gadhib, M. N. Akhtar

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In the present study, 3D simulation of a typical exterior (RC) beam–column joint (BCJ) strengthened with carbon fiber-reinforced plastic (CFRP) sheet are carried out. Numerical investigations are performed using a nonlinear finite element ( FE) analysis by incorporating damage plasticity model (CDP), for material behaviour the concrete response in compression, tension softening were used, linear plastic with isotropic hardening for reinforcing steel, and linear elastic lamina material model for CFRP sheets using the commercial FE software ABAQUS. The numerical models developed in the present study are validated with the results obtained from the experiment under monotonic loading using the hydraulic Jack in displacement control mode. The experimental program includes casting of deficient BCJ loaded to failure load for both un-strengthened and strengthened BCJ. The failure mode, and deformation response of CFRP strengthened and un-strengthened joints and propagation of damage in the components of BCJ are discussed. Finite element simulations are compared with the experimental result and are noted to yield reasonable comparisons. The damage plasticity model was able to capture with good accuracy of the ultimate load and the mode of failure in the beam column joint.

Keywords: reinforced concrete, exterior beam-column joints, concrete damage plasticity model, computational simulation, 3-D finite element model

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Authors: Azadeh Malekan, Shahin Rouhani

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Superlubricity is a phenomenon where two surfaces in contact show negligible friction;this may be because the asperities of the two surfaces do not interlock. Two rough surfaces, when pressed against each other, can get into a formation where the summits of asperities of one surface lock into the valleys of the other surface. The amount of interlock depends on the geometry of the two surfaces. We suggest the friction force may then be proportional to the amount of interlock; this explains Superlubricity as the situation where there is little interlock. Then the friction force will be directly proportional to the normal force as it is related to the work necessary to lift the upper surface in order to clear the interlock. To investigate this model, we simulate the contact of two surfaces. In order to validate our model, we first investigate Amontons‘ law. Assuming that asperities retain deformations in the time scale while the top asperity moves across the lattice spacing Amonton’s law is observed. Structural superlubricity is examined by the hypothesis that surfaces are very rigid and there is no deformation in asperities. This may happen at small normal forces. When two identical surfaces come into contact, rotating the top surface we observe a peak in friction force near the angle of orientation where the two surfaces can interlock.

Keywords: friction, amonton`s law, superlubricity, contact model

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Authors: Mei Sze Wong, Huanyu Mou, Wai-Tong Chien

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Background: Breastmilk is the most nutritious food for infants to support their growth and protect them from infection. Therefore, breastfeeding promotion is an important topic for infant health; whereas, different educational and supportive approaches to interventions have been prompted and targeted at antenatal, postnatal, or both periods to promote and sustain exclusive breastfeeding. This systematic review aimed to identify the effective approaches of educational and supportive interventions to improve breastfeeding. Outcome measures were exclusive breastfeeding, partial breastfeeding, and breastfeeding self-efficacy, being analyzed in terms of ≤ 2 months, 3-5 months, and ≥ 6 months postpartum. Method: Eleven electronic databases and the reference lists of eligible articles were searched. English or Chinese articles of randomized controlled trials on educational and supportive intervention with the above breastfeeding outcomes over recent 20 years were searched. Quality appraisal and risk of bias of the studies were checked by Effective Public Health Practice Project tool and Revised Cochrane risk-of-bias tool, respectively. Results: 13 articles that met the inclusion criteria were included; and they had acceptable quality and risk of bias. The optimal structure, format, and delivery of the interventions significantly increased exclusive breastfeeding rate at ≤ 2 months and ≥ 6 months and breastfeeding self-efficacy at ≤ 2 months included: (a) delivering from antenatal to postnatal period, (b) multicomponent involving antenatal group education, postnatal individual breastfeeding coaching and telephone follow-ups, (c) both individual and group basis, (d) being guided by self-efficacy theory, and (e) having ≥ 3 sessions. Conclusion: The findings showed multicomponent theory-based interventions with ≥ 3 sessions that delivered across antenatal and postnatal period; using both face-to-face teaching and telephone follow-ups can be useful to enhance exclusive breastfeeding rate for more than 6 months and breastfeeding self-efficacy over the first two months of postpartum.

Keywords: breastfeeding self-efficacy, education, exclusive breastfeeding, primiparous, support

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Authors: Michael Ricardo Lang, AdriéLle Costa, Ivana Iesbik, Karine Haag, Leonardo Trindade Buffara, Oscar Reimann Junior, Chelin Auswaldt Steclan

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Stroke affects not only the individual, but has significant impacts on the social and family context. Therefore, it is necessary to know the peculiarities of each region, in order to contribute to regional public health policies effectively. Thus, the present study discusses biomarkers in a post-stroke population, admitted to a stroke unit (U-stroke) of reference in the southern region of Brazil. Biomarkers were analyzed, such as age, length of stay, mortality rate, survival time, risk factors and family history of stroke in patients after ischemic stroke. In this studied population, comparing men and women, it was identified that men were more affected than women, and the average age of women affected was higher, as they also had the highest mortality rate and the shortest hospital stay. The risk factors identified here were according to the global scenario; with SAH being the most frequent and those associated with sedentary lifestyle in women the most frequent (dyspilipidemia, heart disease and obesity). In view of this, the importance of studies that characterize populations regionally is evident, strengthening the strategic planning of policies in favor of health care.

Keywords: biomarkers, sex, stroke, stroke unit, population

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Authors: Jean-Philippe Amat, Timothée Vergne, Aymeric Hans, Bénédicte Ferry, Pascal Hendrikx, Jackie Tapprest, Barbara Dufour, Agnès Leblond

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The surveillance of infectious diseases is necessary to describe their occurrence and help the planning, implementation and evaluation of risk mitigation activities. However, the exact number of detected cases may remain unknown whether surveillance is based on serological tests because identifying seroconversion may be difficult. Moreover, incomplete detection of cases or outbreaks is a recurrent issue in the field of disease surveillance. This study addresses these two issues. Using a viral animal disease as an example (equine viral arteritis), the goals were to establish suitable rules for identifying seroconversion in order to estimate the number of cases and outbreaks detected by a surveillance system in France between 2006 and 2013, and to assess the sensitivity of this system by estimating the total number of outbreaks that occurred during this period (including unreported outbreaks) using a capture-recapture model. Data from horses which exhibited at least one positive result in serology using viral neutralization test between 2006 and 2013 were used for analysis (n=1,645). Data consisted of the annual antibody titers and the location of the subjects (towns). A consensus among multidisciplinary experts (specialists in the disease and its laboratory diagnosis, epidemiologists) was reached to consider seroconversion as a change in antibody titer from negative to at least 32 or as a three-fold or greater increase. The number of seroconversions was counted for each town and modeled using a unilist zero-truncated binomial (ZTB) capture-recapture model with R software. The binomial denominator was the number of horses tested in each infected town. Using the defined rules, 239 cases located in 177 towns (outbreaks) were identified from 2006 to 2013. Subsequently, the sensitivity of the surveillance system was estimated as the ratio of the number of detected outbreaks to the total number of outbreaks that occurred (including unreported outbreaks) estimated using the ZTB model. The total number of outbreaks was estimated at 215 (95% credible interval CrI95%: 195-249) and the surveillance sensitivity at 82% (CrI95%: 71-91). The rules proposed for identifying seroconversion may serve future research. Such rules, adjusted to the local environment, could conceivably be applied in other countries with surveillance programs dedicated to this disease. More generally, defining ad hoc algorithms for interpreting the antibody titer could be useful regarding other human and animal diseases and zoonosis when there is a lack of accurate information in the literature about the serological response in naturally infected subjects. This study shows how capture-recapture methods may help to estimate the sensitivity of an imperfect surveillance system and to valorize surveillance data. The sensitivity of the surveillance system of equine viral arteritis is relatively high and supports its relevance to prevent the disease spreading.

Keywords: Bayesian inference, capture-recapture, epidemiology, equine viral arteritis, infectious disease, seroconversion, surveillance

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Authors: Paula Pascoal-Faria, Rúben Pereira, Elodie Pinto, Miguel Belbut, Ana Rosa, Inês Sousa, Nuno Alves

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Apple bruise damage from harvesting, handling, transporting and sorting is considered to be the major source of reduced fruit quality, resulting in loss of profits for the entire fruit industry. The three factors which can physically cause fruit bruising are vibration, compression load and impact, the latter being the most common source of bruise damage. Therefore, prediction of the level of damage, stress distribution and deformation of the fruits under external force has become a very important challenge. In this study, experimental and numerical methods were used to better understand the impact caused when an apple is dropped from different heights onto a plastic surface and a conveyor belt. Results showed that the extent of fruit damage is significantly higher for plastic surface, being dependent on the height. In order to support the development of a biomimetic electronic device for the determination of fruit damage, the mechanical properties of the apple fruit were determined using mechanical tests. Preliminary results showed different values for the Young’s modulus according to the zone of the apple tested. Along with the mechanical characterization of the apple fruit, the development of the first two prototypes is discussed and the integration of the results obtained to construct the final element model of the apple is presented. This work will help to reduce significantly the bruise damage of fruits or vegetables during the entire processing which will allow the introduction of exportation destines and consequently an increase in the economic profits in this sector.

Keywords: apple, fruit damage, impact during crop and post-crop, mechanical characterization of the apple, numerical evaluation of fruit damage, electronic device

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Authors: Allioua Meryem

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Similar to much of the developing world, Algeria is currently undergoing an epidemiological transition. While mal- and under-nutrition and infectious diseases used to be the main causes of poor health, today there is a higher proportion of chronic, non-communicable diseases (NCDs), including cardiovascular disease, diabetes mellitus, cancer, etc. According to estimates for Algeria from the World Health Organization (WHO), NCDs accounted for 63% of all deaths in 2010. The objective of this study was the assessment of eating habits and anthropometric characteristics in a group of youth aged 15 to 19 years in Tlemcen. This study was conducted on a total effective of 806 youth enrolled in a descriptive cross-sectional study; the classification of nutritional status has been established by international standards IOTF, youth were defined as obese if they had a BMI ≥ 95th percentile, and youth with 85th ≤ BMI ≤ 95th percentile were defined as overweight. Wc is classified by the criteria HD, Wc with moderate risk ≥ 90th percentile and Wc with high risk ≥ 95th percentile. The dietary assessment was based on a 24-hour dietary recall assisted by food records. USDA’S nutrient database for Nutrinux® program was used to analyze dietary intake. Nutrients adequacy ratio was calculated by dividing daily individual intake to dietary recommended intake DRI for each nutrient. 9% of the population was overweight, 3% was obese, 7.5% had abdominal obesity, foods eaten in moderation are chips, cookies, chocolate 1-3 times/day and increased consumption of fried foods in the week, almost half of youth consume sugary drinks more than 3 times per week, we observe a decreased intake of energy, protein (P < 0.001, P = 0.003), SFA (P = 0.018), the NAR of phosphorus, iron, magnesium, vitamin B6, vitamin E, folate, niacin, and thiamin reflecting less consumption of fruit, vegetables, milk, and milk products. Youth surveyed have eating habits at risk of developing obesity and chronic disease.

Keywords: food intake, health, anthropometric characteristics, Algeria

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Authors: Patricia Heredia, Isabel Saz, Marta Fernández

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This article proposes that the decision regarding exporting and the choice of export channel are nested and non-independent decisions. We assume that firms make two sequential decisions before arriving at their final choice: the decision to access foreign markets and the decision about the type of channel. This hierarchical perspective of the choices involved in the process is appealing for two reasons. First, it supports the idea that people have a limited analytical capacity. Managers often break down a complex decision into a hierarchical process because this makes it more manageable. Secondly, it recognizes that important differences exist between entry modes. In light of the above, the objective of this study is to test different entry mode choice processes: independent decisions and nested and non-independent decisions. To do this, the methodology estimates and compares the following two models: (i) a simultaneous single-stage model with three entry mode choices (using a multinomial logit model); ii) a two-stage model with the export decision preceding the channel decision using a sequential logit model. The study uses resource-based factors in determining these decision processes concerning internationalization and the study carries out empirical analysis using a DOC Rioja sample of 177 firms.Using the Akaike and Schwarz Information Criteria, the empirical evidence supports the existence of a nested structure, where the decision about exporting precedes the export mode decision. The implications and contributions of the findings are discussed.

Keywords: sequential logit model, two-stage choice process, export mode, wine industry

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Authors: Naso Isaiah Thanavisuth, Patompong Satapornpong

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Introduction: Covid-19 has been a global pandemic for some time now, causing severe symptoms to patients that received the virus. However, there has been no report on this gene in the Thai population. Objective: Our aim in this study is to explore and compare the frequency of HLA-C allele that is associated with severe COVID-19 symptoms in Thais and other populations. Method: 200 general Thai population were enrolled in this study. The genotyping of HLA -C alleles were determined by the polymerase chain reaction with sequence-specific oligonucleotide probes (PCR-SSOP) and Luminex®IS 100 system (Luminex Corporation, Austin, Texas, USA). Results: We found that the frequency of alleles HLA-C* 01:02 (16.00%), HLA-C* 08:01(10.50%), HLA-C* 03:04 (10.25%),HLA-C* 07:02 (10.00%), HLA-C* 03:02 (9.25%), HLA-C* 07:01 (6.75%), HLA-C* 04:01 (5.00%), HLA-C* 06:02 (4.00%), HLA-C* 04:03 (4.00%), and HLA-C* 07:04 (3.75%) were more common in the Thai population. HLA-C* 01:02 (16.00%) allele was the highest frequency in the North, Center, and North East groups in Thailand, but there was the South region that was not significantly different when compared with the other groups of the region. Additionally, HLA-C∗14:02 allele was similarly distributed in Thais (3.00%), African Americans (1.98%), Caucasians (2.08%), Hispanics (1.71%), North American Natives (1.34%) and Asians (5.01%) by p-value = 0.6506, 0.6506, 0.6506, 0.6135 and 0.7182, respectively. Conclusion: Genetic variation database is important to identify HLA can be a risk factor for severe COVID-19 in many populations. In this study, we will support the research of the HLA markers for screening severe COVID-19 in many populations.

Keywords: HLA-C * 14:02, COVID-19, allele frequency, Thailand

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Authors: Muluegziabher Semagne Mekonnen

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This study was intended to show the irrigation water requirements and evaluation of canal hydraulics steady state conditions to improve on scheme performance of the Meki-Ziway irrigation project. The methodology used was the CROPWAT 8.0 model to estimate the irrigation water requirements of five major crops irrigated in the study area. The results showed that for the whole existing and potential irrigation development area of 2000 ha and 2599 ha, crop water requirements were 3,339,200 and 4,339,090.4 m³, respectively. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. Hydraulic simulation models are fundamental tools for understanding the hydraulic flow characteristics of irrigation systems. In this study Hydraulic Analysis of Irrigation Canals Using HEC-RAS Model was conducted in Meki-Ziway Irrigation Scheme. The HEC-RAS model was tested in terms of error estimation and used to determine canal capacity potential.

Keywords: HEC-RAS, irrigation, hydraulic. canal reach, capacity

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Authors: Sheng Yu Chen, Shi-Heng Wang

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Aim: Based on human, animal experiments, and genetic studies, cysteinyl leukotrienes, LTC4, LTD4, and LTE4, are inflammatory substances that are metabolized by 5-lipooxygenase from arachidonic acid, and these substances trigger asthma. In addition, the synthetic pathway of cysteinyl leukotriene is relevant to the increase in cardiovascular diseases such as myocardial ischemia and stroke. Given the situation, we aim to investigate whether cysteinyl leukotrienes receptor antagonist (LTRA), montelukast which cures those who have asthma has potential protective effects on cardiovascular diseases. Method: We conducted a cohort study, and enrolled participants which are newly diagnosed with asthma (ICD-9 CM code 493. X) between 2002 to 2011. The data source is from Taiwan National Health Insurance Research Database Patients with a previous history of myocardial infarction or ischemic stroke were excluded. Among the remaining participants, every montelukast user was matched with two randomly non-users by sex, and age. The incident cardiovascular diseases, including myocardial infarction and ischemic stroke, were regarded as outcomes. We followed the participants until outcomes come first or the end of the following period. To explore the protective effect of montelukast on the risk of cardiovascular disease, we use multivariable Cox regression to estimate the hazard ratio with adjustment for potential confounding factors. Result: There are 55876 newly diagnosed asthma patients who had at least one claim of inpatient admission or at least three claims of outpatient records. We enrolled 5350 montelukast users and 10700 non-users in this cohort study. The following mean (±SD) time of the Montelukast group is 5 (±2.19 )years, and the non-users group is 6.2 5.47 (± 2.641) years. By using multivariable Cox regression, our analysis indicated that the risk of incident cardiovascular diseases between montelukast users (n=43, 0.8%) and non-users (n=111, 1.04%) is approximately equal. [adjusted hazard ratio 0.992; P-value:0.9643] Conclusion: In this population-based study, we found that the use of montelukast is not associated with a decrease in incident MI or IS.

Keywords: asthma, inflammation, montelukast, insurance research database, cardiovascular diseases

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Authors: Norm Josephy, Lucy Kimball, Victoria Steblovskaya

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Hedging of a portfolio of European options under proportional transaction costs is considered. Our discrete time financial market model extends the binomial market model with transaction costs to the case where the underlying stock price ratios are distributed over a bounded interval rather than over a two-point set. An optimal hedging strategy is chosen from a set of admissible non-self-financing hedging strategies. Our approach to optimal hedging of a portfolio of options is based on theoretical foundation that includes determination of a no-arbitrage option price interval as well as on properties of the non-self-financing strategies and their residuals. A computational algorithm for optimizing an investor relevant criterion over the set of admissible non-self-financing hedging strategies is developed. Applicability of our approach is demonstrated using both simulated data and real market data.

Keywords: extended binomial model, non-self-financing hedging, optimization, proportional transaction costs

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Authors: Ali Noorzad, Ehsan Badakhshan, Shima Zameni

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The present paper is focused on a generalized failure criterion for geomaterials with cross-anisotropy. The cyclic behavior of granular material primarily depends on the nature and arrangement of constituent particles, particle size, and shape that affect fabric anisotropy. To account for the influence of loading directions on strength variations, an anisotropic variable in terms of the invariants of the stress tensor and fabric into the failure criterion is proposed. In an extension to original CANAsand constitutive model two concepts namely critical state and compact state play paramount roles as all of the moduli and coefficients are related to these states. The applicability of the present model is evaluated through comparisons between the predicted and the measured results. All simulations have demonstrated that the proposed constitutive model is capable of modeling the cyclic behavior of sand with inherent anisotropy.

Keywords: fabric, cohesionless media, cyclic loading, critical state, compact state, CANAsand constitutive model

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Authors: Yi-Ting Chen, Yu-Fang Huang, Pei-Wei Wang, Hai-Wei Liang, Chun-Hao Lai, Mei-Lien Chen

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Background: Bisphenol A (BPA) is commonly used in consumer products, such as inner coatings of cans and polycarbonated bottles. BPA is considered to be an endocrine disrupting substance (EDs) that affects normal human hormones and may cause adverse effects on human health. Pregnant women and fetuses are susceptible groups of endocrine disrupting substances. Prenatal exposure to BPA has been shown to affect the fetus through the placenta. Therefore, it is important to evaluate the potential health risk of fetal exposure to BPA during pregnancy. The aims of this study were (1) to determine the urinary concentration of BPA in pregnant women, and (2) to investigate the association between BPA exposure during pregnancy and birth outcomes. Methods: This study recruited 117 pregnant women and their fetuses from 2012 to 2014 from the Taiwan Maternal- Infant Cohort Study (TMICS). Maternal urine samples were collected in the third trimester and questionnaires were used to collect socio-demographic characteristics, eating habits and medical conditions of the participants. Information about birth outcomes of the fetus was obtained from medical records. As for chemicals analysis, BPA concentrations in urine were determined by off-line solid-phase extraction-ultra-performance liquid chromatography coupled with a Q-Tof mass spectrometer. The urinary concentrations were adjusted with creatinine. The association between maternal concentrations of BPA and birth outcomes was estimated using the logistic regression model. Results: The detection rate of BPA is 99%; the concentration ranges (μg/g) from 0.16 to 46.90. The mean (SD) BPA levels are 5.37(6.42) μg/g creatinine. The mean ±SD of the body weight, body length, head circumference, chest circumference and gestational age at birth are 3105.18 ± 339.53 g, 49.33 ± 1.90 cm, 34.16 ± 1.06 cm, 32.34 ± 1.37 cm and 38.58 ± 1.37 weeks, respectively. After stratifying the exposure levels into two groups by median, pregnant women in higher exposure group would have an increased risk of lower body weight (OR=0.57, 95%CI=0.271-1.193), smaller chest circumference (OR=0.70, 95%CI=0.335-1.47) and shorter gestational age at birth newborn (OR=0.46, 95%CI=0.191-1.114). However, there are no associations between BPA concentration and birth outcomes reach a significant level (p < 0.05) in statistics. Conclusions: This study presents prenatal BPA profiles and infants in northern Taiwan. Women who have higher BPA concentrations tend to give birth to lower body weight, smaller chest circumference or shorter gestational age at birth newborn. More data will be included to verify the results. This report will also present the predictors of BPA concentrations for pregnant women.

Keywords: bisphenol A, birth outcomes, biomonitoring, prenatal exposure

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Authors: Mohan Li

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Nowadays, intelligent research technology is more and more important than traditional research methods in urban research work, and this proportion will greatly increase in the next few decades. Frequently such analyzing work cannot be carried without some software engineering knowledge. And here, domain models of urban research will be necessary when applying software engineering knowledge to urban work. In many urban plan practice projects, making rational models, feeding reliable data, and providing enough computation all make indispensable assistance in producing good urban planning. During the whole work process, domain models can optimize workflow design. At present, human beings have entered the era of big data. The amount of digital data generated by cities every day will increase at an exponential rate, and new data forms are constantly emerging. How to select a suitable data set from the massive amount of data, manage and process it has become an ability that more and more planners and urban researchers need to possess. This paper summarizes and makes predictions of the emergence of technologies and technological iterations that may affect urban research in the future, discover urban problems, and implement targeted sustainable urban strategies. They are summarized into seven major domain models. They are urban and rural regional domain model, urban ecological domain model, urban industry domain model, development dynamic domain model, urban social and cultural domain model, urban traffic domain model, and urban space domain model. These seven domain models can be used to guide the construction of systematic urban research topics and help researchers organize a series of intelligent analytical tools, such as Python, R, GIS, etc. These seven models make full use of quantitative spatial analysis, machine learning, and other technologies to achieve higher efficiency and accuracy in urban research, assisting people in making reasonable decisions.

Keywords: big data, domain model, urban planning, urban quantitative analysis, machine learning, workflow design

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Authors: Mohammad H. Ruhipour, Mahdi Goharrokhi, Mahsa Ghasemi, Artadokht Ostadsarayi

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In this paper, we are aiming to study the consequences of chlorine gas leak in direct chlorine gas injection compared to using bleach (sodium hypochlorite), studying the negative effects both on the environment and individuals. This study was performed in the cooling towers of a natural fractioning unit of Bandar-e-IMAM petrochemical plant. Considering that chlorine gas is highly toxic and based on the health regulation, its release into the surrounding environment can be very dangerous for people and even fatal for individuals. We studied performing quantitative studies in the worst cases of event incidence. In addition, studying alternative methods with a lower risk was also on the agenda to select the least likely possible option causing an accident. In this paper chlorine gas release consequences have been evaluated by using PHAST software. Reaching to 10 ppm of chlorine gas concentration was basis of hazardous area determination. The results show that the full chlorine gas line rupture scenario in Pasquill category F, were worst case, and many people could be harmed around cooling towers area because of chlorine gas inhalation.

Keywords: chlorine gas, consequence modeling, cooling towers, direct chlorination, risk assessment, system failure

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Authors: Chiung-Hui Chen

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The Internet of Things (IoT) was designed for widespread convenience. With the smart tag and the sensing network, a large quantity of dynamic information is immediately presented in the IoT. Through the internal communication and interaction, meaningful objects provide real-time services for users. Therefore, the service with appropriate decision-making has become an essential issue. Based on the science of human behavior, this study employed the environment model to record the time sequences and locations of different behaviors and adopted the probability module of the hierarchical Hidden Markov Model for the inference. The statistical analysis was conducted to achieve the following objectives: First, define user behaviors and predict the user behavior routes with the environment model to analyze user purposes. Second, construct the hierarchical Hidden Markov Model according to the logic framework, and establish the sequential intensity among behaviors to get acquainted with the use and activity fabric of the intelligent environment. Third, establish the intensity of the relation between the probability of objects’ being used and the objects. The indicator can describe the possible limitations of the mechanism. As the process is recorded in the information of the system created in this study, these data can be reused to adjust the procedure of intelligent design services.

Keywords: behavior, big data, hierarchical hidden Markov model, intelligent object

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Authors: Jun Ren, Zhen-Hua Ming, He-Feng Huang, Jian-Zhong Sheng

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Adverse intrauterine stimulus during critical or sensitive periods in early life, may lead to health risk not only in later life span, but also further generations. Intrauterine hyperglycaemia, as a major feature of gestational diabetes mellitus (GDM), is a typical adverse environment for both F1 fetus and F1 gamete cells development. However, there is scare information of phenotypic difference of metabolic memory between somatic cells and germ cells exposed by intrauterine hyperglycaemia. The direct transmission effect of intrauterine hyperglycaemia per se has not been assessed either. In this study, we built a GDM mice model and selected male GDM offspring without pre-diabetic phenotype as our founders, to exclude postnatal diabetic influence on gametes, thereby investigate the direct transmission effect of intrauterine hyperglycaemia exposure on F2 offspring, and we further compared the metabolic difference of affected F1-GDM male offspring and F2 offspring. A GDM mouse model of intrauterine hyperglycemia was established by intraperitoneal injection of streptozotocin after pregnancy. Pups of GDM mother were fostered by normal control mothers. All the mice were fed with standard food. Male GDM offspring without metabolic dysfunction phenotype were crossed with normal female mice to obtain F2 offspring. Body weight, glucose tolerance test, insulin tolerance test and homeostasis model of insulin resistance (HOMA-IR) index were measured in both generations at 8 week of age. Some of F1-GDM male mice showed impaired glucose tolerance (p < 0.001), none of F1-GDM male mice showed impaired insulin sensitivity. Body weight of F1-GDM mice showed no significance with control mice. Some of F2-GDM offspring exhibited impaired glucose tolerance (p < 0.001), all the F2-GDM offspring exhibited higher HOMA-IR index (p < 0.01 of normal glucose tolerance individuals vs. control, p < 0.05 of glucose intolerance individuals vs. control). All the F2-GDM offspring exhibited higher ITT curve than control (p < 0.001 of normal glucose tolerance individuals, p < 0.05 of glucose intolerance individuals, vs. control). F2-GDM offspring had higher body weight than control mice (p < 0.001 of normal glucose tolerance individuals, p < 0.001 of glucose intolerance individuals, vs. control). While glucose intolerance is the only phenotype that F1-GDM male mice may exhibit, F2 male generation of healthy F1-GDM father showed insulin resistance, increased body weight and/or impaired glucose tolerance. These findings imply that intrauterine hyperglycaemia exposure affects germ cells and somatic cells differently, thus F1 and F2 offspring demonstrated distinct metabolic dysfunction phenotypes. And intrauterine hyperglycaemia exposure per se has a strong influence on F2 generation, independent of postnatal metabolic dysfunction exposure.

Keywords: inheritance, insulin resistance, intrauterine hyperglycaemia, offspring

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Authors: Farrukh Javed, Krzysztof Podgórski

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We propose a new model that accounts for the asymmetric response of volatility to positive ('good news') and negative ('bad news') shocks in economic time series the so-called leverage effect. In the past, asymmetric powers of errors in the conditionally heteroskedastic models have been used to capture this effect. Our model is using the gamma difference representation of the generalized Laplace distributions that efficiently models the asymmetry. It has one additional natural parameter, the shape, that is used instead of power in the asymmetric power models to capture the strength of a long-lasting effect of shocks. Some fundamental properties of the model are provided including the formula for covariances and an explicit form for the conditional distribution of 'bad' and 'good' news processes given the past the property that is important for the statistical fitting of the model. Relevant features of volatility models are illustrated using S&P 500 historical data.

Keywords: heavy tails, volatility clustering, generalized asymmetric laplace distribution, leverage effect, conditional heteroskedasticity, asymmetric power volatility, GARCH models

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Authors: B. L. Ho, L. Shi, D. F. Wang, V. C. T. Mok

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The brain’s functional connectivity while temporally non-stationary does express consistency at a macro spatial level. The study of stable resting state connectivity patterns hence provides opportunities for identification of diseases if such stability is severely perturbed. A mathematical model replicating the brain’s spatial connections will be useful for understanding brain’s representative geometry and complements the empirical model where it falls short. Empirical computations tend to involve large matrices and become infeasible with fine parcellation. However, the proposed analytical model has no such computational problems. To improve replicability, 92 subject data are obtained from two open sources. The proposed methodology, inspired by financial theory, uses multivariate regression to find relationships of every cortical region of interest (ROI) with some pre-identified hubs. These hubs acted as representatives for the entire cortical surface. A variance-covariance framework of all ROIs is then built based on these relationships to link up all the ROIs. The result is a high level of match between model and empirical correlations in the range of 0.59 to 0.66 after adjusting for sample size; an increase of almost forty percent. More significantly, the model framework provides an intuitive way to delineate between systemic drivers and idiosyncratic noise while reducing dimensions by more than 30 folds, hence, providing a way to conduct attribution analysis. Due to its analytical nature and simple structure, the model is useful as a standalone toolkit for network dependency analysis or as a module for other mathematical models.

Keywords: functional magnetic resonance imaging, multivariate regression, network hubs, resting state functional connectivity

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Authors: Babak Mohajeri

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In recent years, the conventional business model of ownership has been changed towards accessibility in a variety of markets. Two trends can be observed in the evolution of this rental-like business model. Firstly, the technological development that enables the emergence of new business models. These new business models increasingly become agile and flexible. For example Spotify, an online music stream company provides consumers access to over millions of music tracks, conveniently through the smartphone, tablet or computer. Similarly, Car2Go, the car sharing company accesses its members with flexible and nearby sharing cars. The second trend is the increasing communication and connections via social networks. This trend enables a shift to peer-to-peer accessibility based business models. Conventionally, companies provide access for their customers to own companies products or services. In peer-to-peer model, nonetheless, companies facilitate access and connection across their customers to use other customers owned property or skills, competencies or services .The is so-called the sharing economy business model. The aim of this study is to investigate into a new and emerging type of the sharing economy model in which role of customers and service providers may dramatically change. This new model is called Collaborative Service Networks. We propose a mechanism for Collaborative Service Networks business model. Uber and Airbnb, two successful growing companies, have been selected for our case studies and their business models are analyzed. Finally, we study the emergence of the collaborative service networks in the manufacturing domain. Our finding results to a new manufacturing paradigm called social manufacturing.

Keywords: sharing economy, collaborative service networks, social manufacturing, manufacturing development

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Authors: Nop Sopipan

Abstract:

In this paper, we forecast the volatility of Baht/USDs using Markov Regime Switching GARCH (MRS-GARCH) models. These models allow volatility to have different dynamics according to unobserved regime variables. The main purpose of this paper is to find out whether MRS-GARCH models are an improvement on the GARCH type models in terms of modeling and forecasting Baht/USD volatility. The MRS-GARCH is the best performance model for Baht/USD volatility in short term but the GARCH model is best perform for long term.

Keywords: volatility, Markov Regime Switching, forecasting, Baht/USD

Procedia PDF Downloads 291

Authors: M. Eskandarighadi, C. R. McGann

Abstract:

It is observed from past experiences of earthquakes that local site conditions can significantly affect the strong ground motion characteristics experience at the site. One-dimensional seismic site response analysis is the most common approach for investigating site response. This approach assumes that soil is homogeneous and infinitely extended in the horizontal direction. Therefore, tying side boundaries together is one way to model this behavior, as the wave passage is assumed to be only vertical. However, 1D analysis cannot capture the 2D nature of wave propagation, soil heterogeneity, and 2D soil profile with features such as inclined layer boundaries. In contrast, 2D seismic site response modeling can consider all of the mentioned factors to better understand local site effects on strong ground motions. 2D wave propagation and considering that the soil profile on the two sides of the model may not be identical clarifies the importance of a boundary condition on each side that can minimize the unwanted reflections from the edges of the model and input appropriate loading conditions. Ideally, the model size should be sufficiently large to minimize the wave reflection, however, due to computational limitations, increasing the model size is impractical in some cases. Another approach is to employ free-field boundary conditions that take into account the free-field motion that would exist far from the model domain and apply this to the sides of the model. This research focuses on implementing free-field boundary conditions in OpenSees for 2D site response analysisComparisons are made between 1D models and 2D models with various boundary conditions, and details and limitations of the developed free-field boundary modeling approach are discussed.

Keywords: boundary condition, free-field, opensees, site response analysis, wave propagation

Procedia PDF Downloads 138