Search results for: predicting factors

Authors: Tassadit Tabouche

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Water sprays pattern, and water droplets size (different droplets diameter) are a key factors in the success of the suppression by water spray. The effects of the two important factors are investigated in this study. However, the fire extinguishing mechanism in such devices is not well understood due to the complexity of the physical and chemical interactions between water spray and fire plume. in this study, 3D, unsteady, two phase flow CFD simulation approach is introduced to provide a quantitative analysis of the complex interactions occurring between water spray and fire plume. Lagrangian Discrete Phase Model (DPM) was used for water droplets and a global one-step reaction mechanism in combustion model was used for fire plume.

Keywords: droplets, water spray, water droplets size, 3D

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Authors: Xiaolian Jiang, Dongling Liu, Kun Liu

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Aims: To examine the prevalence of POST-TRAUMATIC STRESS DISORDER (PTSD) symptoms among Tibetan adolescents in heavily-hit disaster area three years after Yushu earthquake, and to explore the interactions of the psycho-social-genetic risk factors. Methods: This was a three-stage study. Firstly, demographic variables，PTSD Checklist-Civilian Version （PCL-C），the Internality、Powerful other、Chance Scale，（IPC），Coping Style Scale（CSS），and the Social Support Appraisal（SSA）were used to explore the psychosocial factors of PTSD symptoms among adolescent survivors. PCL-C was used to examine the PTSD symptoms among 4072 Tibetan adolescents，and the Structured Clinical Interview for DSM-IV Disorders（SCID）was used by psychiatrists to make the diagnosis precisely. Secondly，a case-control trial was used to explore the relationship between PTSD and gene polymorphisms. 287adolescents diagnosed with PTSD were recruited in study group, and 280 adolescents without PTSD in control group. Polymerase chain reaction-restriction fragment length polymorphism technology（PCR-RFLP）was used to test gene polymorphisms. Thirdly，SPSS 22.0 was used to explore the interactions of the psycho-social-genetic risk factors of PTSD on the basis of the above results. Results and conclusions: 1．The prevalence of PTSD was 9.70%. 2．The predictive psychosocial factors of PTSD included earthquake exposure, support from others, imagine, abreact, tolerant, powerful others and family support. 3．Synergistic interactions between A1 gene of DRD2 TaqIA and the external locus of control, negative coping style, severe earthquake exposure were found. Antagonism interactions between A1 gene of DRD2 TaqIA and poor social support was found. Synergistic interactions between A1/A1 genotype and the external locus of control, negative coping style were found. Synergistic interactions between 12 gene of 5-HTTVNTR and the external locus of control, negative coping style, severe earthquake exposure were found. Synergistic interactions between 12/12 genotype and the external locus of control, negative coping style, severe earthquake exposure were also found.

Keywords: adolescents, earthquake, PTSD, risk factors

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Authors: Mohammad Didar Hossain

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Background/Purpose: The purpose of this study was to examine the associations between productive engagements and the psychological well-being of older adults in the U.S by analyzing cross-sectional data from a secondary dataset. Specifically, this paper analyzed the associations of 4 different types of productive engagements, including current work status, caregiving to the family members, volunteering and religious strengths with the psychological well-being as an outcome variable. Methods: Data and sample: The study used the data from the Health and Retirement Study (HRS). The HRS is a nationally representative prospective longitudinal cohort study that has been conducting biennial surveys since 1992 to community-dwelling individuals 50 years of age or older on diverse issues. This analysis was based on the 2016 wave (cross-sectional) of the HRS dataset and the data collection period was April 2016 through August 2017. The samples were recruited from a multistage, national area-clustered probability sampling frame. Measures: Four different variables were considered as the predicting variables in this analysis. Firstly, current working status was a binary variable that measured by 0=Yes and 1= No. The second and third variables were respectively caregiving and volunteering, and both of them were measured by; 0=Regularly, 1= Irregularly. Finally, find in strength was measured by 0= Agree and 1= Disagree. Outcome (Wellbeing) variable was measured by 0= High level of well-being, 1= Low level of well-being. Control variables including age were measured in years, education in the categories of 0=Low level of education, 1= Higher level of education and sex r in the categories 0=male, 1= female. Analysis and Results: Besides the descriptive statistics, binary logistic regression analyses were applied to examine the association between independent and dependent variables. The results showed that among the four independent variables, three of them including working status (OR: .392, p<.001), volunteering (OR: .471, p<.003) and strengths in religion (OR .588, p<.003), were significantly associated with psychological well-being while controlling for age, gender and education factors. Also, no significant association was found between the caregiving engagement of older adults and their psychological well-being outcome. Conclusions and Implications: The findings of this study are mostly consistent with the previous studies except for the caregiving engagements and their impact on older adults’ well-being outcomes. Therefore, the findings support the proactive initiatives from different micro to macro levels to facilitate opportunities for productive engagements for the older adults, and all of these may ultimately benefit their psychological well-being and life satisfaction in later life.

Keywords: productive engagements, older adults, psychological wellbeing, productive aging

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Authors: Guo Bingkun

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With the rapid development of China's social economy and the continuous improvement of urbanization level, people's living standards have undergone tremendous changes, and more and more people are gathering in cities. The demand for urban residents' housing has been greatly released in the past decade. The demand for housing and related construction land required for urban development has brought huge pressure to urban operations, and land prices have also risen rapidly in the short term. On the other hand, from the comparison of the eastern and western regions of China, there are also great differences in urban socioeconomics and land prices in the eastern, central and western regions. Although judging from the current overall market development, after more than ten years of housing market reform and development, the quality of housing and land use efficiency in Chinese cities have been greatly improved. However, the current contradiction between land demand for urban socio-economic development and land supply, especially the contradiction between land supply and demand for urban residential land, has not been effectively alleviated. Since land is closely linked to all aspects of society, changes in land prices will be affected by many complex factors. Therefore, this paper studies the factors that may affect urban residential land prices and compares them among eastern, central and western cities, and finds the main factors that determine the level of urban residential land prices. This paper provides guidance for urban managers in formulating land policies and alleviating land supply and demand. It provides distinct ideas for improving urban planning and improving urban planning and promotes the improvement of urban management level. The research in this paper focuses on residential land prices. Generally, the indicators for measuring land prices mainly include benchmark land prices, land price level values, parcel land prices, etc. However, considering the requirements of research data continuity and representativeness, this paper chooses to use residential land price level values. Reflects the status of urban residential land prices. First of all, based on the existing research at home and abroad, the paper considers the two aspects of land supply and demand and, based on basic theoretical analysis, determines some factors that may affect urban housing, such as urban expansion, taxation, land reserves, population, and land benefits. Factors of land price and correspondingly selected certain representative indicators. Secondly, using conventional econometric analysis methods, we established a model of factors affecting urban residential land prices, quantitatively analyzed the relationship and intensity of influencing factors and residential land prices, and compared the differences in the impact of urban residential land prices between the eastern, central and western regions. Compare similarities. Research results show that the main factors affecting China's urban residential land prices are urban expansion, land use efficiency, taxation, population size, and residents' consumption. Then, the main reason for the difference in residential land prices between the eastern, central and western regions is the differences in urban expansion patterns, industrial structures, urban carrying capacity and real estate development investment.

Keywords: urban housing, urban planning, housing prices, comparative study

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Authors: Zoe Lynch, Kirsty Zieschank

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There are several factors that compromise the utility and wide-spread use of existing emotional and behavioural distress screening instruments. Some of these factors include lengthy administration times, high costs, feasibility issues, and a lack of self-report options for children under 12 years of age. This animation-based resource was developed to overcome as many of these factors as possible. Developed for educators and medical and mental health professionals, this resource offers children a self-guided mechanism for reporting any current emotional and behavioural distress. An avatar assistant, selected by the child, accompanies them through each stage of the screening process, offering further instruction if prompted. Children enter their age and gender before viewing comparative animations conveying common childhood emotional and behavioural difficulties. The child then selects the most relatable animations, along with the frequency with which they experience the depicted emotions. From a perspective of intellectual development, an engaging, animated format means that outcomes will not be constrained by children’s reading, writing, cognitive, or verbal expression abilities. Having been user-tested with children aged 6 to 12, this resource shows promising results as a self-guided screening instrument.

Keywords: animation-based screening instrument, mental health, primary-aged children, self-guided

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Authors: Vivian Khamis

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Exposure to war and forced migration have been widely linked to child subsequent adaptation. What remains sparse is research spanning multiple risk and protective factors and examining their unique and relative implications to difficulties in mental health among refugee girls. This study investigated the mechanisms through which posttraumatic stress disorder (PTSD), emotion dysregulation , neuroticism, and behavioral and emotional disorders in Syrian refugee girls is impacted by exposure to war traumas, age, and other risk and protective factors such as coping styles, family relationships, and school environment. The sample consisted of 539 Syrian refugee girls who ranged in age from 7 to 18 years attending public schools in various governorates in Lebanon and Jordan. Two school counselors carried out the interviews with children at school. Results indicated that war trauma, older age, and a combination of negative copying style associated with conflict in the family could lead to an overall state of emotion dysregulation, neuroticism, behavioral and emotional disorders, and PTSD in refugee girls. On the other hand, lapse of time since resettlement in host country, positive copying style, cohesion, and expressiveness in the family would lead to more positive mental health status, including lower levels of emotion dysregulation, neuroticism, behavioral and emotional disorders, and PTSD . Enhanced understanding of the mechanistic role of risk and protective factors in contributing to difficulties in mental health in refugee girls may contribute to the development of effective interventions to target the psychological effects of the refugee experience.

Keywords: refugee girls, PTSD, emotion dysregulation, neuroticism, behavioral and emotional disorders

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Authors: Nalanda Matia, Julia Zhao, Amber Jaycocks, Divya Sinha

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Social assistance programs for businesses are intended to improve their survival and growth in the face of catastrophic events like the COVID-19 pandemic. However, that goal remains unfulfilled when the mostwantingbusinesses fail to participate in such programs. Reasons for non-participation can include lack of information, inability to cope with applications and program compliance, as well as some programs’ non-entitlement status. Some of these factors may be associated with the organizational and locational characteristics of these businesses. This research investigates these organizational and locational factorsthat determine receipt and effectiveness of social assistance among the firms that receive it. of A sample of firms from the universe of 3 rounds of Small Business Administration backed Paycheck Protection Program recipient and similarly profiled non recipient businesses are used to analyze this question. Initial results show firm organizational factors like size and spatial factors like broadband coverage at firm location impact application for and subsequent receipt of assistance for digitally administered programs. Further, Line of business and wage structure of recipients’ impact effectiveness of the assistance dollars.

Keywords: public economics, economics of social assistance, firm organizational structure, survival analysis

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Authors: Bellali Assia, Bellali Fatima

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Speaking is one of the most difficult English skills for non-English learners. This study investigated English-speaking difficulties encountered by non-English secondary school students in a private school in Casablanca, Morocco. The subjects were students of 63 (male and female) from 2ed year classes level. It also aims to investigate the degree of main speaking difficulties and the factors effecting non-English students to speak English. This research used a descriptive qualitative and quantitative approach with a questionnaire and an interview to collect the data. In linguistically related difficulties, there were four difficulties, namely vocabulary, grammar, conversation and pronunciation. The results revealed that there were 40.32% of students agreed that they do not have sufficient grammar knowledge, 45.16% of students agreed that they do not have enough vocabulary, 45.90% of students agreed that they have difficulty in conversation, and 39.34% of students agreed that they have poor pronunciation. Also, the results indicated that 63.33 % of students agreed that they have problems with self-confidence. The factors causing the problem of speaking English in this study were lack of general knowledge, lack of speaking practice, fear of mistakes and grammar practice, low participation, shyness, nervousness, fear of criticism, and unfamiliar word pronunciation. Furthermore, recommendations and suggestions were presented to solve the problem and eliminate difficulties for teachers and students.

Keywords: English speaking, difficulties, factors, non-English students

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Authors: Tareg Belali, Mosleh Abomughaid, Muhanad Alhujaily

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HNF4a is one of the steroid hormone receptor family of transcription factors with roles in the development of the liver and the regulation of several critical metabolic pathways, such as glycolysis, drug metabolism, and apolipoproteins and blood coagulation. The transcriptional potency of HNF4a is well known due to its involvement in diabetes and other metabolic diseases. However, recently HNF4a has been discovered to be closely associated with several haematological disorders, mainly because of genetic mutations, drugs, and hepatic disorders. We review HNF4a structure and function and its role in haematological disorders. We discuss possible good therapies that are based on targeting HNF4a.

Keywords: hepatocyte nuclear factor 4 alpha, HNF4a nuclear receptor, steroid hormone receptor family of transcription factors, hematological disorders

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Authors: Amira Touil, Achouak Arfaoui, Ibtissem Mannaii

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The aim of this work is to monitor the process adsorption of nitrates by the biochar via studying the influence of various parameters on the adsorption of this pollutant by biochar in a synthetic aqueous solution. The results which obtained indicate that the 4g/L biochar dose is the most efficient in terms of nitrates removal in aqueous solution. The biochar exhibited a good affinity for nitrates after 1hour of contact. The yield of removal of nitrate by the biochar decreases with the increase of pH of the solution and increases with increasing temperature (60°C>40°C>20°C). The best removal yield is about 80% of the initial concentration introduced (25mg/L) obtained at pH=2, T=60°C, and dose of biochar=4g/L. The second order model fit the nitrate adsorption kinetics of biochar with a high coefficient of determination (R2≥0.997); and a new equation correlating the rate constant of the reaction with temperature and pH was been built. Freundlich isotherms performed well to fit the nitrate adsorption data by biochar (R2>0.96) compared to Langmuir isotherms. The thermodynamic parameters (ΔH°, ΔG°, ΔS°) have been calculated for predicting the nature of adsorption.

Keywords: pollution, biochar, nitrate, adsorption

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Authors: Habte Tadesse Likassa, Bacha Edosa

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Customer’s satisfaction was very important thing that is required for the existence of banks to be more productive and success in any organization and business area. The main goal of the study is assessing and identifying factors that influence customer’s satisfaction in West Shoa Zone of Commercial Bank of Ethiopia (Holeta, Ginchi, Ambo, Gedo and Bako). Stratified random sampling procedure was used in the study and by using simple random sampling (lottery method) 520 customers were drawn from the target population. By using Probability Proportional Size Techniques sample size for each branch of banks were allocated. Both descriptive and inferential statistics methods were used in the study. A binary logistic regression model was fitted to see the significance of factors affecting customer’s satisfaction in this study. SPSS statistical package was used for data analysis. The result of the study reveals that the overall level of customer’s satisfaction in the study area is low (38.85%) as compared those who were not satisfied (61.15%). The result of study showed that all most all factors included in the study were significantly associated with customer’s satisfaction. Therefore, it can be concluded that based on the comparison of branches on their customers satisfaction by using odd ratio customers who were using Ambo and Bako are less satisfied as compared to customers who were in Holeta branch. Additionally, customers who were in Ginchi and Gedo were more satisfied than that of customers who were in Holeta. Since the level of customers satisfaction was low in the study area, it is more advisable and recommended for concerned body works cooperatively more in maximizing satisfaction of their customers.

Keywords: customers, satisfaction, binary logistic, complain handling process, waiting time

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Authors: Debasis Sarkar

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Development of a Smart City would depend upon the development of its infrastructure in a smart way. Primarily based on the ideology of the fourth industrial revolution a Smart City project should have Smart governance, smart health care, smart building, smart transportation, smart mobility, smart energy, smart technology and smart citizen. Considering the Indian scenario of current state of cities in India, it has become very essential to decide the specific parameters which would govern the development of a Smart City project. It has been observed that there are significant parameters beyond Information and Communication Technology (ICT), which govern the development of a Smart City project. This paper is an attempt to identify the Critical Success Factors (CSF) which are significantly responsible for the development of a Smart City project in Western India. Responses to questionnaire survey were analyzed on basis of Likert scale. They were further critically evaluated with help of Factor Comparison Method (FCM) and Analytical Hierarchy Process (AHP). The project authorities need to incorporate Building Information Modeling (BIM) to make the smart city project more collaborative. To make the project more sustainable, use of flyash in the concrete used, reduced usage of cement and steel, use of alternate fuels like biodiesel is recommended.

Keywords: analytical hierarchical process, building information modeling, critical success factors, factor comparison method

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Authors: Lavanya Annadi, Fahimeh Jafari

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Transportation brings immense benefits to society, but it also has its costs. Costs include such as the cost of infrastructure, personnel and equipment, but also the loss of life and property in traffic accidents on the road, delays in travel due to traffic congestion and various indirect costs in terms of air transport. More research has been done to identify the various factors that affect road accidents, such as road infrastructure, traffic, sociodemographic characteristics, land use, and the environment. The aim of this research is to predict the probabilistic crash prediction of vehicles using machine learning due to natural and structural reasons by excluding spontaneous reasons like overspeeding etc., in the United States. These factors range from weather factors, like weather conditions, precipitation, visibility, wind speed, wind direction, temperature, pressure, and humidity to human made structures like road structure factors like bump, roundabout, no exit, turning loop, give away, etc. Probabilities are dissected into ten different classes. All the predictions are based on multiclass classification techniques, which are supervised learning. This study considers all crashes that happened in all states collected by the US government. To calculate the probability, multinomial expected value was used and assigned a classification label as the crash probability. We applied three different classification models, including multiclass Logistic Regression, Random Forest and XGBoost. The numerical results show that XGBoost achieved a 75.2% accuracy rate which indicates the part that is being played by natural and structural reasons for the crash. The paper has provided in-deep insights through exploratory data analysis.

Keywords: road safety, crash prediction, exploratory analysis, machine learning

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Authors: S. Alireza Mirghasemi, Shervin Rashidinia, Mohammad Saleh Sadeghi, Mohsen Talebizadeh, Narges Rahimi Gabaran, Seyed Shahin Eftekhari, Sara Shahmoradi

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Avascular necrosis of femoral head is a pathologic condition that the main cause is decreased blood supply of femoral head. Among predisposing risk factors, chronic use of corticosteroids, alcoholism, smocking and hip traumas have more important role. Also we can mention OCP consumption as a risk factor among less common predisposing factors that lead to AVNF, in this study we introduce another cause of AVNF with a period of treatment with moderate dose of corticosteroids accompanied by OCP as a probable facilitating factor that leads to AVNF.

Keywords: AVN, corticosteroids consumption, femoral head osteonecrosis, OCP

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Authors: Sergio Luna, Raquel Rodríguez-Carvajal

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This research examines the effectiveness of a mindfulness-based intervention in optimizing psychological well-being, with a particular focus on self-esteem, due to the rapid growth and consolidation of social network use and the increased frequency and intensity of upward comparisons of the self. The study aims to assess the potential of a mindfulness-based intervention to improve self-esteem and, in particular, to contribute to its greater stability by reducing levels of contingent self-esteem. Results show that an 8-week mindfulness-based stress reduction program was effective in increasing participants' (n=206) trait mindfulness, explicit self-esteem, and well-being, while decreasing contingent self-esteem. Furthermore, the study found that improvements in both explicit and contingent self-esteem were significantly correlated with increases in psychological well-being, but that contingent self-esteem had a stronger effect on well-being than explicit self-esteem. These findings highlight the importance of considering additional dimensions of self-esteem beyond levels, and suggest that mindfulness-based interventions may be a valuable tool for promoting a healthier form of self-esteem that contributes to personal well-being.

Keywords: MBSR, contingent self-esteem, explicit self-esteem, well-being

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Authors: Nordila Ahmad, Thamer Mohammad, Bruce W. Melville, Zuliziana Suif

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Current methods for predicting local scour at wide bridge piers, were developed on the basis of laboratory studies and very limited scour prediction were tested with field data. Laboratory wide pier scour equation from previous findings with field data were presented. A wide range of field data were used and it consists of both live-bed and clear-water scour. A method for assessing the quality of the data was developed and applied to the data set. Three other wide pier-scour equations from the literature were used to compare the performance of each predictive method. The best-performing scour equation were analyzed using statistical analysis. Comparisons of computed and observed scour depths indicate that the equation from the previous publication produced the smallest discrepancy ratio and RMSE value when compared with the large amount of laboratory and field data.

Keywords: field data, local scour, scour equation, wide piers

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Authors: Shanza Akram, Sameen Toor, Heba Harb Abu Alkass, Zainab Abdulsalam Altaha, Sara Taha Abdulla, Saleem Imran

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Acute pulmonary embolism (PE) is a common disease and can be fatal. The clinical presentation is variable and nonspecific, making accurate diagnosis difficult. Testing patients with suspected acute PE has increased dramatically. However, the overuse of some tests, particularly CT and D-dimer measurement, may not improve care while potentially leading to patient harm and unnecessary expense. CTPA is the investigation of choice for PE. Its easy availability, accuracy and ability to provide alternative diagnosis has lowered the threshold for performing it, resulting in its overuse. Guidelines have recommended the use of clinical pretest probability tools such as ‘Wells score’ to assess risk of suspected PE. Unfortunately, implementation of guidelines in clinical practice is inconsistent. This has led to low risk patients being subjected to unnecessary imaging, exposure to radiation and possible contrast related complications. Aim: To study the diagnostic yield of CT PA, clinical pretest probability of patients according to wells score and to determine whether or not there was an overuse of CTPA in our service. Methods: CT scans done on patients with suspected P.E in our hospital from 1st January 2014 to 31st December 2014 were retrospectively reviewed. Medical records were reviewed to study demographics, clinical presentation, final diagnosis, and to establish if Wells score and D-Dimer were used correctly in predicting the probability of PE and the need for subsequent CTPA. Results: 100 patients (51male) underwent CT PA in the time period. Mean age was 57 years (24-91 years). Majority of patients presented with shortness of breath (52%). Other presenting symptoms included chest pain 34%, palpitations 6%, collapse 5% and haemoptysis 5%. D Dimer test was done in 69%. Overall Wells score was low (<2) in 28 %, moderate (>2 - < 6) in 47% and high (> 6) in 15% of patients. Wells score was documented in medical notes of only 20% patients. PE was confirmed in 12% (8 male) patients. 4 had bilateral PE’s. In high-risk group (Wells > 6) (n=15), there were 5 diagnosed PEs. In moderate risk group (Wells >2 - < 6) (n=47), there were 6 and in low risk group (Wells <2) (n=28), one case of PE was confirmed. CT scans negative for PE showed pleural effusion in 30, Consolidation in 20, atelactasis in 15 and pulmonary nodule in 4 patients. 31 scans were completely normal. Conclusion: Yield of CT for pulmonary embolism was low in our cohort at 12%. A significant number of our patients who underwent CT PA had low Wells score. This suggests that CT PA is over utilized in our institution. Wells score was poorly documented in medical notes. CT-PA was able to detect alternative pulmonary abnormalities explaining the patient's clinical presentation. CT-PA requires concomitant pretest clinical probability assessment to be an effective diagnostic tool for confirming or excluding PE. . Clinicians should use validated clinical prediction rules to estimate pretest probability in patients in whom acute PE is being considered. Combining Wells scores with clinical and laboratory assessment may reduce the need for CTPA.

Keywords: CT PA, D dimer, pulmonary embolism, wells score

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Authors: Mohamed Raouf Benmakrelouf, Wafa Karouche, Joseph Rynkiewicz

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In this paper, we propose an alternative method to construct a Bayesian Network (BN). This method relies on a convolutional neural network (CNN classifier), which determinates the edges of the network skeleton. We train a CNN on a normalized empirical probability density distribution (NEPDF) for predicting causal interactions and relationships. We have to find the optimal Bayesian network structure for causal inference. Indeed, we are undertaking a search for pair-wise causality, depending on considered causal assumptions. In order to avoid unreasonable causal structure, we consider a blacklist and a whitelist of causality senses. We tested the method on real data to assess the influence of education on the voting intention for the extreme right-wing party. We show that, with this method, we get a safer causal structure of variables (Bayesian Network) and make to identify a variable that satisfies the backdoor criterion.

Keywords: Bayesian network, structure learning, optimal search, convolutional neural network, causal inference

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Authors: Asma Ameur, Dhafer Malouche

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Hotel competitiveness research is an essential phase of the marketing strategy for any hotel. Certainly, knowing the hotels' competitors helps the hotelier to grasp its position in the market and the citizen to make the right choice in picking a hotel. Thus, competitiveness is an important indicator that can be influenced by various factors. In fact, the issue of competitiveness, this ability to cope with competition, remains a difficult and complex concept to define and to exploit. Therefore, the purpose of this article is to make an exploratory study to calculate a competitiveness indicator for hotels. Further on, this paper makes it possible to determine the criteria of direct or indirect effect on the image and the perception of a hotel. The actual research is used to look into the right model for hotel ‘competitiveness. For this reason, we exploit different theoretical contributions in the field of machine learning. Thus, we use some statistical techniques such as the Principal Component Analysis (PCA) to reduce the dimensions, as well as other techniques of statistical modeling. This paper presents a survey covering of the techniques and methods in hotel competitiveness research. Furthermore, this study allows us to deduct the significant variables that influence the determination of hotel’s competitors. Lastly, the discussed experiences in this article found that the hotel competitors are influenced by several factors with different rates.

Keywords: competitiveness, e-reputation, hotels' competitors, online hotel’ review, principal component analysis, statistical modeling

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Authors: Stefano M. Spagocci

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The efficiency of photovoltaic panels can be calculated with such software packages as RETScreen that allow design engineers to take financial as well as technical considerations into account. RETScreen is interfaced with meteorological databases, so that efficiency calculations can be realistically carried out. The author has recently contributed to the development of solar modules with accumulation capability and an embedded water purifier, aimed at off-grid users such as users in developing countries. The software packages examined do not allow to take ancillary equipment into account, hence the decision to implement a technical and financial model of the system. The author realized that, rather than re-implementing the quite sophisticated model of RETScreen - a mathematical description of which is anyway not publicly available - it was possible to drastically simplify it, including the meteorological factors which, in RETScreen, are presented in a numerical form. The day-by-day efficiency of a photovoltaic solar panel was parametrized by the product of factors expressing, respectively, daytime duration, solar right ascension motion, solar declination motion, cloudiness, temperature. For the sun-motion-dependent factors, positional astronomy formulae, simplified by the author, were employed. Meteorology-dependent factors were fitted by simple trigonometric functions, employing numerical data supplied by RETScreen. The accuracy of our model was tested by comparing it to the predictions of RETScreen; the accuracy obtained was 11%. In conclusion, our study resulted in a model that can be easily implemented in a spreadsheet - thus being easily manageable by non-specialist personnel - or in more sophisticated software packages. The model was used in a number of design exercises, concerning photovoltaic solar panels and ancillary equipment like the above-mentioned water purifier.

Keywords: clean energy, energy engineering, mathematical modelling, photovoltaic panels, solar energy

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Authors: S. Balubaid, M. Z. Abd Majid, R. Zakaria

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Energy efficiency is one of the most important issues for green buildings and their sustainability. This is not only due to the environmental impacts, but also because of significantly high energy cost. The aim of this study is to identify the potential actions required for toll plaza that lead to energy reduction. The data were obtained through set of questionnaire and interviewing targeted respondents, including the employees at toll plaza, and architects and engineers who are directly involved in design of highway projects. The data was analyzed using descriptive statistics analysis method. The findings of this study are the critical elements that influence the energy usage and factors that lead to energy wastage. Finally, potential actions are recommended to reduce energy consumption in toll plazas.

Keywords: energy efficiency, toll plaza, energy consumption

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Authors: Ashraf Mohammed M. Eid, Hossam El Badry

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The bored pile friction resistance may be affected by many factors such as the method of construction, pile length and diameter, the soil properties, as well as the depth below ground level. These factors can be represented analytically to study the influence of diameter on the unit skin friction. In this research, the Egyptian Code of soil mechanics is used to assess the skin friction capacity for either the ordinary pile diameter as well as for the large pile diameter. The later is presented in the code and through the work of some researchers based on the results of investigations adopted for a sufficient number of field tests. The comparative results of these researchers with respect to the Egyptian Code are used to check the adequacy of both methods. Based on the results of this study, the traditional static formula adopted for piles of diameter less than 60 cm may be continually used for larger piles by correlating the analyzed formulae. Accordingly, the corresponding modified angle of internal friction is concluded demonstrating a reduction of shear strength due to soil disturbance along the pile shaft. Based on this research the difference between driven piles and bored piles constructed in same soil can be assessed and a better understanding can be evaluated for the effect of different factors on pile skin friction capacity.

Keywords: large piles, static formula, friction piles, sandy soils

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Authors: Shemroy Roberts

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Despite minor theoretical contributions in slavery heritage tourism research that have commented on the demand-side perspective, visitor behavior and engagement with slavery heritage attractions remain unexplored. Thus, there is a need for empirical studies and theoretical knowledge to understand visitor engagement with slavery heritage attractions, particularly U.K. slavery heritage museums. The purpose of this paper is to critically evaluate the factors that influence visitor engagement with U.K. slavery heritage museums. This qualitative research utilizes a passive symbolic ethnographic methodology. Seven U.K. slavery heritage museums will be used to collect data through unobtrusive internet-mediated observations of TripAdvisor reviews and online semi-structured interviews with managers and curators. Preliminary findings indicate that social media, prior knowledge, multiple motivations, cultural capital, and the design and layout of exhibits influence visitor engagement with slavery heritage museums. This research contributes to an understanding of visitor engagement with U.K. slavery heritage museums. The findings of this paper will provide insights into the factors that influence visitor engagement with U.K. slavery heritage museums to managers, curators, and decision-makers responsible for designing and managing those attractions. Therefore, the results of this paper will enable museum professionals to better manage visitor engagement with slavery heritage museums.

Keywords: museums, netnography, slavery, visitor engagement

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Authors: Panaya Sudta, Wanchalerm Patanacharoenwong, Prachya Bumrungkun

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As With the evolution of smart grids, ensuring the reliability and efficiency of electrical systems in smart cities has become crucial. This paper proposes a distinct approach that combines advanced machine learning techniques to accurately predict electrical failures and address voltage reliability issues. This approach aims to improve the accuracy and efficiency of reliability evaluations in smart cities. The aim of this research is to develop a comprehensive predictive model that accurately predicts electrical failures and voltage reliability in smart cities. This model integrates RFM analysis, K-means clustering, and LSTM networks to achieve this objective. The research utilizes RFM analysis, traditionally used in customer value assessment, to categorize and analyze electrical components based on their failure recency, frequency, and monetary impact. K-means clustering is employed to segment electrical components into distinct groups with similar characteristics and failure patterns. LSTM networks are used to capture the temporal dependencies and patterns in customer data. This integration of RFM, K-means, and LSTM results in a robust predictive tool for electrical failures and voltage reliability. The proposed model has been tested and validated on diverse electrical utility datasets. The results show a significant improvement in prediction accuracy and reliability compared to traditional methods, achieving an accuracy of 92.78% and an F1-score of 0.83. This research contributes to the proactive maintenance and optimization of electrical infrastructures in smart cities. It also enhances overall energy management and sustainability. The integration of advanced machine learning techniques in the predictive model demonstrates the potential for transforming the landscape of electrical system management within smart cities. The research utilizes diverse electrical utility datasets to develop and validate the predictive model. RFM analysis, K-means clustering, and LSTM networks are applied to these datasets to analyze and predict electrical failures and voltage reliability. The research addresses the question of how accurately electrical failures and voltage reliability can be predicted in smart cities. It also investigates the effectiveness of integrating RFM analysis, K-means clustering, and LSTM networks in achieving this goal. The proposed approach presents a distinct, efficient, and effective solution for predicting and mitigating electrical failures and voltage issues in smart cities. It significantly improves prediction accuracy and reliability compared to traditional methods. This advancement contributes to the proactive maintenance and optimization of electrical infrastructures, overall energy management, and sustainability in smart cities.

Keywords: electrical state prediction, smart grids, data-driven method, long short-term memory, RFM, k-means, machine learning

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Authors: Bader Al-Mannai, Saad Sulieman, Yaser Al-Alawi

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Research studies worldwide undoubtedly demonstrated that the implementation of Total Quality Management (TQM) program can improve organizations competitive abilities and provide strategic quality advances. However, limited empirical studies and research are directed to measure the effectiveness of TQM implementation on the industrial and manufacturing organizations performance. Accordingly, this paper is aimed at discussing “the degree of TQM implementation in Bahrain industries and its effect on their performance”. The paper will present the measurement indicators and success factors that were used to assess the degree of TQM implementation in Bahrain industry, and the main performance indicators that were affected by TQM implementation. The adopted research methodology in this study was a survey that was based on self-completion questionnaire. The sample population represented the industrial and manufacturing organizations in Bahrain. The study led to the identification of the operational and strategic measurement indicators and success factors that assist organizations in realizing successful TQM implementation and performance improvement. Furthermore, the research analysis confirmed a positive and significant relationship between the examined performance indicators in Bahrain industry and TQM implementation. In conclusion the investigation of the relationship revealed that the implementation of TQM program has resulted into remarkable improvements on workforce, sales performance, and quality performance indicators in Bahrain industry.

Keywords: performance indicators, success factors, TQM implementation, Bahrain

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Authors: Sina Aghili, Ali Arasteh Nodeh

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Tamarisk usage as a new group of lignocelluloses material to produce fermentable sugars in bio-ethanol process was studied. The overall aim of this work was to establish the optimum condition for acid hydrolysis of this new material and a mathematical model predicting glucose release as a function of operation variable. Sulfuric acid concentration in the range of 20 to 60%(w/w), process temperature between 60 to 95oC, hydrolysis time from 120 to 240 min and solid content 5,10,15%(w/w) were used as hydrolysis conditions. HPLC was used to analysis of the product. This analysis indicated that glucose was the main fermentable sugar and was increased with time, temperature and solid content and acid concentration was a parabola influence in glucose production.The process was modeled by a quadratic equation. Curve study and model were found that 42% acid concentration, 15 % solid content and 90oC were in optimum condition.

Keywords: fermentable sugar, saccharification, wood, hydrolysis

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Authors: Halima Akhtar, Abhijeet Chandra

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The paper attempts to analyze the factors that influence the Consumer Behavior to purchase apparel through the internet. The intentions to buy apparels online were based on in terms of user style, orientation, size and reputation of the merchant, social influence, perceived information utility, perceived ease of use, perceived pleasure and attractiveness and perceived trust and risk. The basic framework used was Technology acceptance model to explain apparels acceptance. A survey was conducted to gather the data from 200 people. The measures and hypotheses were analyzed using Correlation testing and would be further validated by the Structural Equation Modelling. The implications of the findings for theory and practice could be used by marketers of online apparel websites. Based on the values obtained, we can conclude that the factors such as social influence, Perceived information utility, attractiveness and trust influence the decision for a user to buy apparels online. The major factors which are found to influence an online apparel buying decision are ease of use, attractiveness that a website can offer and the trust factor which a user shares with the website.

Keywords: E-tailers, consumer behaviour, technology acceptance model, structural modelling

Procedia PDF Downloads 186

Authors: Maryam Farzaneh, Seyyedeh Nafiseh Hassani, Hossein Baharvand

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Objective: Chicken gonadal tissue has a two population such primordial germ cells (PGCs) and stromal cells (somatic cells). PGCs and embryonic germ cells (EGCs) that is a pluripotent type of PGCs in long-term culture are suitable sources for the production of chicken pluripotent stem cell lines, transgenic birds, vaccine and recombinant protein production. In general, the effect of growth factors such bFGF and mouse LIF on derivation of PGCs in vitro are important and in this study we could see the unique effect of small molecules such PD032 and SB43 as a chemical, in comparison to growth factors. Materials and Methods: After incubation of fertilized chicken egg up to 6 days and isolation of primary gonadal tissues and culture of mixed cells like PGCs and stromal cells. PGCs proliferate in the present of fetal calf serum (FCS) and small molecules and in another group bFGF, that these factors are important for PGCs culture and derivation. Somatic cells produce a multilayer feeder under the PGCs in primary culture and PGCs make a small cluster under these cells. Results: In present of small molecules and high volume of FCS (15%), the present of EGCs as a pluripotent stem cells were clear four weeks, that they had a positive immune-staining and periodic acid-Schiff staining (PAS), but in present of growth factors like bFGF without any chemicals, the present of PGCs were clear but after 7 until 10 days, there were disappear. Conclusion: Until now we have seen many researches about derivation and maintenance of chicken PGCs, in the hope of understanding the mechanisms that occur during germline development and production of a therapeutic product by transgenic birds. There are still many unknowns in this area and this project will try to have efficient conditions for identification of suitable culture medium for long-term culture of PGCs in vitro without serum and feeder cells.

Keywords: chicken gonadal primordial germ cells, pluripotent stem cells, growth factors, small molecules, transgenic birds

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Authors: Luyin Liang

Abstract:

Although sibling relationship has been viewed as one of the most important family relationships that significantly impacted on the quality of life of both adults with Intellectual Disability (AWID) and their brothers/sisters, very few research have been done to investigate this relationship in China. This study investigated Chinese siblings of AWID’s relational motivations in sibling relationship and their determining factors. Quantitative research method has been adopted and 284 samples were recruited in this study. Siblings of AWID’s two types of relational motivations, including obligatory motivations and discretionary motivations were examined. Their emotional closeness, senses of responsibility, experiences of ID stigma, and expectancy of self-reward in sibling relationship were measured by validated scales. Personal, and familial-social demographic characteristics were also investigated. Linear correlation test and standard multiple regression analysis were the major statistical methods that have been used to analyze the data. The findings of this study showed that all the measured factors, including siblings of AWID’s emotional closeness, their senses of responsibility, experiences of ID stigma, and self-reward expectations had significant relationships with their both types of motivations. However, when these factors were grouped together to measure each type of these motivations, the prediction results were varied. The order of factors that best predict siblings of AWID’s obligatory motivations was: their senses of responsibility, emotional closeness, experiences of ID stigma, and their expectancy of self-reward, whereas the order of these factors that best determine siblings of AWID’s discretionary motivations was: their self-reward expectations, experiences of ID stigma, senses of responsibility, and emotional closeness. Among different demographic characteristics, AWID’s disability condition, their siblings’ age, gender, marital status, number of children, both siblings’ living arrangements and family financial status were found to have significant impacts on siblings of AWID’s both types of motivations in sibling relationship. The results of this study could enhance social work practitioners’ understandings about the needs and challenges of siblings of AWID. Suggestions on advocacies for policy changes and services improvements for these siblings were discussed in this study.

Keywords: sibling relationship, intellectual disability, adults, China

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Authors: Elham Sharifineyestani, Mohammad Farshchin

Abstract:

Tropical cyclones are one of the most expensive and deadliest natural disasters. They cause heavy rainfall and serious flash flooding that result in billions of dollars of damage and considerable mortality each year in the United States. Prediction of the frequency of tropical cyclone-induced rainfall events can be helpful in emergency planning and flood risk management. In this study, we have developed a machine-learning model to predict the exceedance frequencies of tropical cyclone-induced rainfall events in the United States. Model results show a satisfactory agreement with available observations. To examine the effectiveness of our approach, we also have compared the result of our predictions with the exceedance frequencies predicted using a physics-based rainfall model by Feldmann.

Keywords: flash flooding, tropical cyclones, frequencies, machine learning, risk management

Procedia PDF Downloads 247