Search results for: ANOVA score model

Authors: Motalleb Byzedi, Seyedeh Chaman Naderi Korvandan

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Regarding annual statistics of groundwater level resources about current piezometers at Qorveh plains, both ARMA & PARMA modeling methods were applied in this study by the using of SAMS software. Upon performing required tests, a model was used with minimum amount of Akaike information criteria and suitable model was selected for piezometers. Then it was possible to make necessary estimations by using these models for future fluctuations in each piezometer. According to the results, ARMA model had more facilities for modeling of aquifer. Also it was cleared that eastern parts of aquifer had more failures than other parts. Therefore it is necessary to prohibit critical parts along with more supervision on taking rates of wells.

Keywords: qorveh plain, groundwater level, ARMA, PARMA

Procedia PDF Downloads 276

Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Yi Wang, Xun Liang

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This paper introduces a model of internet public opinion waves, which describes the message propagation and measures the influence of a detected event. We collect data on public opinion propagation from different platforms on the internet, including micro-blogs and news. Then, we compare the spread of public opinion to the seismic waves and correspondently define the P-wave and S-wave and other essential attributes and characteristics in the process. Further, a model is established to evaluate the magnitude scale of the events. In the end, a practical example is used to analyze the influence of network public opinion and test the reasonability and effectiveness of the proposed model.

Keywords: internet public opinion waves (IPOW), magnitude scale, cross-platform, information propagation

Procedia PDF Downloads 279

Authors: Subrat Kumar Bhattamisra, Vivian Lee Yean Yan, Chin Koh Lee, Chew Hui Kuean, Yun Khoon Liew, Mayuren Candasamy

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Geraniol, an acyclic monoterpenoid is the main active constituent in the essential oils of rose and palmorosa. Antioxidant, antibacterial, anticancer and antiulcer activity of geraniol was reported by many researchers. The present investigation was designed to study in vivo antiulcer and anti-Helicobacter pylori activity of geraniol. Antiulcer and anti-H. pylori activity of geraniol was evaluated on acetic acid plus H. pylori induced ulcer in rats. Acetic acid (0.03 mL) was injected to the sub-serosal layer of the stomach through laparotomy under anaesthesia. Orogastric inoculation of H. pylori (ATCC 43504) was done twice daily for 7 days. Geraniol (15 and 30 mg/kg), vehicle and standard drugs (Amoxicillin, 50 mg/kg; clarithromycin, 25 mg/kg & omeprazole, 20 mg/kg) was administered twice daily for 14 days. Antiulcer activity of geraniol was examined by the determination of gastric ulcer index, measuring the volume of gastric juice, pH and total acidity, myeloperoxidase activity and histopathological examination. Histopathological investigation for the presence of inflammation, white blood cell infiltration, edema, the mucosal damage was studied. The presence of H. pylori was detected by placing a biopsy sample from antral part of the stomach into rapid urease test. Ulcer index in H. pylori inoculated control group was 4.13 ± 0.85 and was significantly (P < 0.05) lowered in geraniol (30 mg/kg) and reference drug treated group. Geraniol increase the pH of the gastric juice (2.18 ± 0.13 in control vs. 4.14 ± 0.57 in geraniol 30mg/kg) and lower total acidity significantly (P < 0.01) in geraniol (15 & 30 mg/kg). Myeloperoxidase (MPO) activity was measured in stomach homogenate of all the groups. H. pylori control group has significant (P < 0.05) increase in MPO activity compared to normal control group. Geraniol (30 mg/kg) was showed significant (P < 0.05) and most effective among all the groups. Histopathological examination of rat stomach was scored and the total score for H. pylori control group was 8. After geraniol (30 mg/kg) and reference drug treatment, the histopathological score was significantly decreased and it was observed to be 3.5 and 2.0 respectively. Percentage inhibition of H. pylori infection in geraniol (30 mg/kg) and reference drug were found to be 40% and 50% respectively whereas, 100% infection in H. pylori control group was observed. Geraniol exhibited significant antiulcer and anti- H. pylori activity in the rats. Thus, geraniol has the potential for the further development as an effective medication in treating H. pylori associated ulcer.

Keywords: geraniol, helicobacter pylori atcc 43504, myeloperoxidase, ulcer

Procedia PDF Downloads 334

Authors: Yiqi Wu, Simon Tait, Andrew Nichols

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Management of UK railway drainage assets is challenging due to the large amounts of historical assets with long asset life cycles. A major concern for asset managers is to maintain the required performance economically and efficiently while complying with the relevant regulation and legislation. As the majority of the drainage assets are buried underground and are often difficult or costly to examine, it is important for asset managers to understand and model the degradation process in order to foresee the upcoming reduction in asset performance and conduct proactive maintenance accordingly. In this research, a Markov chain approach is used to model the deterioration process of rail drainage assets. The study is based on historical condition scores and characteristics of drainage assets across the whole railway network in England, Scotland, and Wales. The model is used to examine the effect of various characteristics on the probabilities of degradation, for example, the regional difference in probabilities of degradation, and how material and shape can influence the deterioration process for chambers, channels, and pipes.

Keywords: deterioration, degradation, markov models, probability, railway drainage

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Authors: Boukli Hacene Faiza, Soufi Wassila, Ghalem Said

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The oral antidiabetics drugs such as alpha glucosidase inhibitors present undesirable effects like acarbose. Flavonoids are class of molecules widely distributed in plants, for this reason we are interested in our work to study the inhibition in silico of alpha glucosidase by natural ligands ( flavonoids analogues) using molecular modeling methods using MOE (Molecular Operating Environment) software to predict their interaction with this enzyme with score energy, ADME /T tests and druglikeness properties experiments. Two flavonoids Beicalein and Apigenin have high binding affinity with alpha glucosidase with lower IC50 supposed potent inhibitors.

Keywords: alpha glucosidase, flavonoides analogues, drug research, molecular modeling

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Authors: Natalia Ortega

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Safety Culture (SCU) involves various perceptual, psychological, behavioral, and managerial factors. It has been shown that creating and maintaining an SCU is one way to reduce and prevent accidents and fatalities. In the construction sector, safety attitude, knowledge, and a supportive environment are predictors of safety behavior. The highest possible proportion of safety behavior among employees can be achieved by improving their safety attitude and knowledge. Accordingly, top management's commitment to safety is vital in shaping employees' safety attitude; therefore, the first step to improving employees' safety attitude is the genuine commitment of top management to safety. One of the factors affecting the successful implementation of health and safety promotion programs is the construction industry's subcontracting model. The contractual model's complexity, combined with the need for coordination among diverse stakeholders, makes it challenging to implement, manage, and follow up on health and well-being initiatives. The Systems theoretic accident model and process (STAMP) concept has expanded global consideration in recent years, increasing research attention. STAMP focuses attention on the role of constraints in safety management. The findings discover a growth of the research field from the definition in 2004 by Leveson and is being used across multiple domains. A systematic literature review of this novel model aims to meet the safety goals for human space exploration with a powerful and different approach to safety management, safety-driven design, and decision-making. Around two hundred studies have been published about applying the model. However, every single model for safety requires time to transform into research and practice, be tested and debated, and grow further and mature.

Keywords: stamp, risk management, accident prevention, safety culture, systems thinking, construction industry, safety

Procedia PDF Downloads 69

Authors: Samar Alkindy

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Purpose: The BIM model has been used to support the planning of different construction projects in the industry by showing the different stages of the construction process. The model has been instrumental in identifying some of the common errors in the construction process through the spatial arrangement. The continuous use of the BIM model in the construction industry has resulted in various radical changes such as virtual prototyping. Construction virtual prototyping is a highly advanced technology that incorporates a BIM model with realistic graphical simulations, and facilitates the simulation of the project before a product is built in the factory. The paper presents virtual prototyping in the construction industry by examining its application, challenges and benefits to a construction project. Methodology approach: A case study was conducted for this study in four major construction projects, which incorporate virtual construction prototyping in several stages of the construction project. Furthermore, there was the administration of interviews with the project manager and engineer and the planning manager. Findings: Data collected from the methodological approach shows a positive response for virtual construction prototyping in construction, especially concerning communication and visualization. Furthermore, the use of virtual prototyping has increased collaboration and efficiency between construction experts handling a project. During the planning stage, virtual prototyping has increased accuracy, reduced planning time, and reduced the amount of rework during the implementation stage. Irrespective of virtual prototyping being a new concept in the construction industry, the findings outline that the approach will benefit the management of construction projects.

Keywords: construction operations, construction planning, process simulation, virtual prototyping

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Authors: Shahbaz Ahmed

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This study is conducted to demonstrate the knowledge of intentional learning and incidental learning. Hypothesis of this experiment is intentional learning is better than incidental learning, participants were demonstrated and were asked to learn the 10 nonsense syllables in a specific sequence from the colored cards in the end they were asked to recall the background color of each card instead of nonsense syllables. Independent variables of the experiment are the colored cards containing nonsense syllables which are to be memorized by the participants, dependent variables are the number of correct responses made by the participant. The findings of the experiment concluded that intentional learning is better than incidental learning, hence hypothesis is proved.

Keywords: intentional learning, incidental learning, non-sense syllable cards, score sheets

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Authors: Baya Takhedmit, Karim Abbas, Sofiane Ouazine

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The vacations queues are often employed to model many real situations such as computer systems, communication networks, manufacturing and production systems, transportation systems and so forth. These queueing models are solved at fixed parameters values. However, the parameter values themselves are determined from a finite number of observations and hence have uncertainty associated with them (epistemic uncertainty). In this paper, we consider the M/G/1/N queue with server vacation and exhaustive discipline where we assume that the vacation parameter values have uncertainty. We use the Taylor series expansions approach to estimate the expectation and variance of model output, due to epistemic uncertainties in the model input parameters.

Keywords: epistemic uncertainty, M/G/1/N queue with vacations, non-parametric sensitivity analysis, Taylor series expansion

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Authors: H. Mohammadi Majd, M. Jalali Azizpour, V. Tavaf, A. Jaderi

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In upsetting processes contact friction significantly influence metal flow, stress-strain state and process parameters. Furthermore, tribological conditions influence workpiece deformation and its dimensional precision. A viscoplastic constitutive law, the Anand model, was applied to represent the inelastic deformation behavior in upsetting process. This paper presents research results of the influence of contact friction coefficient on a workpiece deformation in upsetting process.finite element parameters. This technique was tested for three different specimens simulations of the upsetting and the corresponding material and can be successfully employed to predict the deformation of the upsetting process.

Keywords: friction, upsetting, barreling, Anand model

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Authors: Grienggrai Rajchakit

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As we all know that coronavirus is announced as a pandemic in the world by WHO. It is speeded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self-preventive measures are the best strategies. As of now, many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the coronavirus disease behaves in an exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To make this prediction of active cases, we need a database. The database of COVID-19 is downloaded from the KAGGLE website and is analyzed by applying a recurrent LSTM neural network with univariant features to predict the number of active cases of patients suffering from the corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with a testing dataset to predict the number of active cases in a particular state; here, we have concentrated on Andhra Pradesh state.

Keywords: COVID-19, coronavirus, KAGGLE, LSTM neural network, machine learning

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Authors: Asrat M.Belachew, Tiago Pereira, Institute of Mathematics, Computer Sciences, Avenida Trabalhador São Carlense, 400, São Carlos, 13566-590, Brazil

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Infectious diseases are among the most prominent threats to human beings. They cause morbidity and mortality to an individual and collapse the social, economic, and political systems of the whole world collectively. Mathematical models are fundamental tools and provide a comprehensive understanding of how infectious diseases spread and designing the control strategy to mitigate infectious diseases from the host population. Modeling the spread of infectious diseases using a compartmental model of inhomogeneous populations is good in terms of complexity. However, in the real world, there is a situation that accounts for heterogeneity, such as ages, locations, and contact patterns of the population which are ignored in a homogeneous setting. In this work, we study how classical an SEIR infectious disease spreading of the compartmental model can be extended by incorporating the mobility of population between heterogeneous cities during an outbreak of infectious disease. We have formulated an SEIR multi-cities epidemic spreading model using a system of 4k ordinary differential equations to describe the disease transmission dynamics in k-cities during the day and night. We have shownthat the model is epidemiologically (i.e., variables have biological interpretation) and mathematically (i.e., a unique bounded solution exists all the time) well-posed. We constructed the next-generation matrix (NGM) for the model and calculated the basic reproduction number R0for SEIR-epidemic spreading model with cities mobility. R0of the disease depends on the spectral radius mobility operator, and it is a threshold between asymptotic stability of the disease-free equilibrium and disease persistence. Using the eigenvalue perturbation theorem, we showed that sending a fraction of the population between cities decreases the reproduction number of diseases in interconnected cities. As a result, disease transmissiondecreases in the population.

Keywords: SEIR-model, mathematical model, city mobility, epidemic spreading

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Authors: Jingling Li, Yi Zhang, Wei Liang, Tao Cui, Jun Li

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Compared with terrestrial network, the traffic of spatial information network has both self-similarity and short correlation characteristics. By studying its traffic prediction method, the resource utilization of spatial information network can be improved, and the method can provide an important basis for traffic planning of a spatial information network. In this paper, considering the accuracy and complexity of the algorithm, the spatial information network traffic is decomposed into approximate component with long correlation and detail component with short correlation, and a time series hybrid prediction model based on wavelet decomposition is proposed to predict the spatial network traffic. Firstly, the original traffic data are decomposed to approximate components and detail components by using wavelet decomposition algorithm. According to the autocorrelation and partial correlation smearing and truncation characteristics of each component, the corresponding model (AR/MA/ARMA) of each detail component can be directly established, while the type of approximate component modeling can be established by ARIMA model after smoothing. Finally, the prediction results of the multiple models are fitted to obtain the prediction results of the original data. The method not only considers the self-similarity of a spatial information network, but also takes into account the short correlation caused by network burst information, which is verified by using the measured data of a certain back bone network released by the MAWI working group in 2018. Compared with the typical time series model, the predicted data of hybrid model is closer to the real traffic data and has a smaller relative root means square error, which is more suitable for a spatial information network.

Keywords: spatial information network, traffic prediction, wavelet decomposition, time series model

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Authors: Ciwang Teyra, A. H. Y. Lai

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Introduction: Indigenous LGBTQ individuals face with significant life stress such as racial and gender discrimination and microaggressions, which may lead to negative impacts of their mental health. Although studies relevant to Taiwanese indigenous LGBTQpeople gradually increase, most of them are primarily conceptual or qualitative in nature. This research aims to fulfill the gap by offering empirical quantitative evidence, especially investigating the impact of racial and gender microaggressions on mental health among Taiwanese indigenous LGBTQindividuals with an intersectional perspective, as well as examine whether social support can help them to cope with microaggressions. Methods: Participants were (n=200; mean age=29.51; Female=31%, Male=61%, Others=8%). A cross-sectional quantitative design was implemented using data collected in the year 2020. Standardised measurements was used, including Racial Microaggression Scale (10 items), Gender Microaggression Scale (9 items), Social Support Questionnaire-SF(6 items); Patient Health Questionnaire(9-item); and Generalised Anxiety Disorder(7-item). Covariates were age, gender, and perceived economic hardships. Structural equation modelling (SEM) was employed using Mplus 8.0 with the latent variables of depression and anxiety as outcomes. A main effect SEM model was first established (Model1).To test the moderation effects of perceived social support, an interaction effect model (Model 2) was created with interaction terms entered into Model1. Numerical integration was used with maximum likelihood estimation to estimate the interaction model. Results: Model fit statistics of the Model 1:X2(df)=1308.1 (795), p<.05; CFI/TLI=0.92/0.91; RMSEA=0.06; SRMR=0.06. For Model, the AIC and BIC values of Model 2 improved slightly compared to Model 1(AIC =15631 (Model1) vs. 15629 (Model2); BIC=16098 (Model1) vs. 16103 (Model2)). Model 2 was adopted as the final model. In main effect model 1, racialmicroaggressionand perceived social support were associated with depression and anxiety, but not sexual orientation microaggression(Indigenous microaggression: b = 0.27 for depression; b=0.38 for anxiety; Social support: b=-0.37 for depression; b=-0.34 for anxiety). Thus, an interaction term between social support and indigenous microaggression was added in Model 2. In the final Model 2, indigenous microaggression and perceived social support continues to be statistically significant predictors of both depression and anxiety. Social support moderated the effect of indigenous microaggression of depression (b=-0.22), but not anxiety. All covariates were not statistically significant. Implications: Results indicated that racial microaggressions have a significant impact on indigenous LGBTQ people’s mental health. Social support plays as a crucial role to buffer the negative impact of racial microaggression. To promote indigenous LGBTQ people’s wellbeing, it is important to consider how to support them to develop social support network systems.

Keywords: microaggressions, intersectionality, indigenous population, mental health, social support

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Authors: L. Torchane

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This study is devoted to defining the optimal conditions for the nitriding of pure iron at atmospheric pressure by using NH3-Ar-C3H8 gas mixtures. After studying the mechanisms of phase formation and mass transfer at the gas-solid interface, a mathematical model is developed in order to predict the nitrogen transfer rate in the solid, the ε-carbonitride layer growth rate and the nitrogen and carbon concentration profiles. In order to validate the model and to show its possibilities, it is compared with thermogravimetric experiments, analyses and metallurgical observations (X-ray diffraction, optical microscopy and electron microprobe analysis). Results obtained allow us to demonstrate the sound correlation between the experimental results and the theoretical predictions.

Keywords: gaseous nitrocarburizing, kinetic model, diffusion, layer growth kinetic

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Authors: Vinko Viducic, Jelena Žanic Mikulicic, Maja Racic, Kristina Sladojevic

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The research presented in this paper has been focused on analyzing the impact of traffic on the sustainable development of tourism in Croatia's Dubrovacko-Neretvanska County by the year 2020, based on the figures and trends reported in 2014 and using the relevant variables that characterise the synergy of traffic and tourism in, speaking from the geographic viewpoint, the most problematic county in the Republic of Croatia. The basic hypothesis has been confirmed through scientifically obtained research results, through the quantification of the model's variables and the direct growth rates of the designed model. On the basis of scientific insights into the sustainable development of traffic and tourism in Dubrovacko-Neretvanska County, it is possible to propose a new information model for traffic at the service of the sustainable development of tourism in the County for the period 2014-2020.

Keywords: environment protection, hotel industry, private sector, quantification

Procedia PDF Downloads 269

Authors: Ka'abu Mu'azu

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The study examines the effect of varied intensities of aerobic exercise on Systolic Blood Pressure (SBP) among HIV/AIDS positive patients. Participants of mean age of 20.4 years were randomized into four groups. High Intensity Group (HIG), Moderate Intensity Group (MIG), Low Intensity Group (LIG) and Control Group (COG). SBP was measured at baseline (pre-exercise) and post-exercise (8 weeks). Analysis of variance (ANOVA) indicates a significant training effect on resting values of SBP (F [3, 15] = 8.9, P < 0.05). Sheffe post hoc analysis indicated that both HIG and MIG significantly differ from control (P < 0.05). Dependent t- test indicates difference in HIG (t [7] = 6.5, P < 0.05) and slightly in MIG (t [7] = 5.4, P < 0.05). The study concluded that aerobic exercise is effective in reducing resting values of SBP particularly the activities that are high intensity in nature. The study recommends that high and moderate intensity aerobic exercise should be used for improving health condition of HIV/AIDS patients as regard to decrease in resting value of SBP.

Keywords: systolic blood pressure, aerobic exercise, HIV patients, health sciences

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Authors: Abdulwahab Alalyani, Mahbub Rashid

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Public green space promotes community health including daily activities, but these resources may not be available enough or may not equitably be distributed. This paper measures and compares the availability of public green spaces (PGS) among low, middle, and high-income neighborhoods in the Riyadh city. Additionally, it compares the total availability of PGS to WHO standard and Dubai availability of PGS per person. All PGS were mapped using geographical information systems, and total area availability of PGS compared to WHO and Dubai standards. To evaluate the significant differences in PGS availability across low, medium, and high-income Riyadh neighborhoods, we used a One-way ANOVA analysis of covariance to test the differences. As a result, by comparing PGS of Riyadh neighborhoods to WHO and Dubai-availability, it was found that Riyadh PGS were lower than the minimum standard of WHO and as well as Dubai. Riyadh has only 1.13 m² per capita of PGS. The second finding, the availability of PGS, was significantly different among Riyadh neighborhoods based on socioeconomic status. The future development of PGS should be focused on increasing PGS availability and should be given priority to those low-income and unhealthy communities.

Keywords: spatial equity, green space, quality of life, built environment

Procedia PDF Downloads 118

Authors: Liudmila Garzanova, Lidia Ananyeva, Olga Koneva, Olga Ovsyannikova, Oxana Desinova, Mayya Starovoytova, Rushana Shayahmetova, Anna Khelkovskaya-Sergeeva

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Abstract Objectives. Rituximab (RTX) shown a positive effect in the treatment of systemic sclerosis (SSc). But there is still not enough data on comparing the effectiveness of RTX with immunosuppressants (IS). The aim of our study was to compare changes of lung function and skin score in SSc between two groups of patients (pts) - on RXT therapy (prescribed after ineffectiveness of previous therapy with IS) and on therapy with IS only. Methods. This study included 103 pts received RTX as an addition to previous therapy (group 1) and 65 pts received therapy with IS and prednisolone (group 2). The mean follow-up period was 12.6±10.7months. In group 1 the mean age was 47±12.9 years, female – 88 pts (84%), the diffuse cutaneous subset of the disease had 55 pts (53%). The mean disease duration was 6.2±5.5 years. 82% pts had interstitial lung disease (ILD) and 92% were positive for ANA, 67% of them were positive for antitopoisomerase-1. All pts received prednisolone at a dose of 11.3±4.5 mg/day, IS at inclusion received 47% of them. The cumulative mean dose of RTX was 1.7±0.6 g. In group 2 the mean age was 50.8±13.8 years, female-53 pts (82%), the diffuse cutaneous subset of the disease had 44 pts (68%). The mean disease duration was 8.8±7.7 years. 81% pts had ILD and 88% were positive for ANA, 58% of them were positive for antitopoisomerase-1. All pts received prednisolone at a dose of 8.69±4.28 mg/day, IS received 57% of them. Cyclophosphamide (CP) received 45% of pts. The cumulative mean dose of CP was 10.2±15.1g. D-penicillamine received 30% of pts. Other pts was on mycophenolate mofetil or methotrexate therapy in single cases. The pts of the compared groups did not differ in the main demographic and clinical parameters. The results are presented as delta (Δ) - difference between the baseline parameter and follow up point. Results. In group 1 there was an improvement of all outcome parameters: increased of forced vital capacity, % predicted - ΔFVC=4% (p=0.0004); Diffusing capacity for carbon monoxide, % predicted remained stable (ΔDLCO=0.1%); improvement of the Rodnan skin score-ΔmRss=3.4 (p=0.001); decrease of Activity index (EScSG-AI) - ΔActivity index=1.7 (p=0.001). In group 2 the changes was insignificant: ΔFVC=-2.3%, ΔmRss=0.87, ΔActivity index=0.3. But there was a significant decrease of DLCO: ΔDLCO=-5.1% (p=0.001). Conclusion. The results of our study confirm the data on the positive effect of RTX in complex therapy in pts with SSc (decrease of skin induration, increase of FVC, stabilization of DLCO). Meantime, pts on IS and prednisolone therapy shown the worsening of lung function and insignificant changes of other clinical parameters. RTX could be considered as a more effective option in complex treatment of SSc in comparison with IS therapy

Keywords: immunosuppressants, interstitial lung disease, systemic sclerosis, rituximab

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Authors: Hamid Tavakolipour, Mohsen Mokhtarian, Ahmad Kalbasi Ashtari

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In this study, the effect of various drying methods (sun drying, shade drying and industrial drying) on final moisture content, shell splitting degree, shrinkage and color change were studied. Sun drying resulted higher degree of pistachio nuts shell splitting on pistachio nuts relative other drying methods. The ANOVA results showed that the different drying methods did not significantly effects on color change of dried pistachio nut. The results illustrated that pistachio nut dried by industrial drying had the lowest moisture content. After the end of drying process, initially, the experimental drying data were fitted with five famous drying models namely Newton, Page, Silva et al., Peleg and Henderson and Pabis. The results indicated that Peleg and Page models gave better results compared with other models to monitor the moisture ratio’s pistachio nut in industrial drying and open sun (or shade drying) methods, respectively.

Keywords: industrial drying, pistachio, quality properties, traditional drying

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Authors: Yuan-Jye Tseng, Ching-Yen Chen

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In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: cluster analysis, customer preferences, design evaluation, design for customer preferences, product design

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Authors: Zhou Hong, Gu Xiao-Qing, Lıu Hong-Jiao, Leng Jing

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Seamless learning is becoming a research hotspot in recent years, and the emerging of micro-lectures, flipped classroom has strengthened the development of seamless learning. Based on the characteristics of the seamless learning across time and space and the course structure of the flipped classroom, and the theories of language learning, we put forward the language learning model which can support ‘seamless flipped’ environment (abbreviated as ‘S-F’). Meanwhile, the characteristics of the ‘S-F’ learning environment, the corresponding framework construction and the activity design of diversified corpora were introduced. Moreover, a language learning app named ‘Daily Speaking’ was developed to facilitate the practice of the language learning model in ‘S-F’ environment. In virtue of the learning case of Shanghai language, the rationality and feasibility of this framework were examined, expecting to provide a reference for the design of ‘S-F’ learning in different situations.

Keywords: seamless learning, flipped classroom, seamless-flipped environment, language learning model

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Authors: Hoyeon Park, Kyoung-jae Kim

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The product recommendation is a field of research that has received much attention in the recent information overload phenomenon. The proliferation of the mobile environment and social media cannot help but affect the results of the recommendation depending on how the factors of the user's situation are reflected in the recommendation process. Recently, research has been spreading attention to the context-aware recommender system which is to reflect user's contextual information in the recommendation process. However, until now, most of the context-aware recommender system researches have been limited in that they reflect the passive context of users. It is expected that the user will be able to express his/her contextual information through his/her active behavior and the importance of the context-aware recommender system reflecting this information can be increased. The purpose of this study is to propose a context-aware recommender system that can reflect the user's emotional state as an active context information to recommendation process. The context-aware recommender system is a recommender system that can make more sophisticated recommendations by utilizing the user's contextual information and has an advantage that the user's emotional factor can be considered as compared with the existing recommender systems. In this study, we propose a method to infer the user's emotional state, which is one of the user's context information, by using the user's facial expression data and to reflect it on the recommendation process. This study collects the facial expression data of a user who is looking at a specific product and the user's product preference score. Then, we classify the facial expression data into several categories according to the previous research and construct a model that can predict them. Next, the predicted results are applied to existing collaborative filtering with contextual information. As a result of the study, it was shown that the recommended results of the context-aware recommender system including facial expression information show improved results in terms of recommendation performance. Based on the results of this study, it is expected that future research will be conducted on recommender system reflecting various contextual information.

Keywords: context-aware, emotional state, recommender systems, business analytics

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Authors: Hassnen M. Jafer, Khalid S. Hashim, W. Atherton, Ali W. Alattabi

Abstract:

This study investigates the effect of two important parameters (length of curing period and percentage of the added binder) on the strength of soil treated with OPC. An intermediate plasticity silty clayey soil with medium organic content was used in this study. This soft soil was treated with different percentages of a commercially available cement type 32.5-N. laboratory experiments were carried out on the soil treated with 0, 1.5, 3, 6, 9, and 12% OPC by the dry weight to determine the effect of OPC on the compaction parameters, consistency limits, and the compressive strength. Unconfined compressive strength (UCS) test was carried out on cement-treated specimens after exposing them to different curing periods (1, 3, 7, 14, 28, and 90 days). The results of UCS test were used to develop a non-linear multi-regression model to find the relationship between the predicted and the measured maximum compressive strength of the treated soil (qu). The results indicated that there was a significant improvement in the index of plasticity (IP) by treating with OPC; IP was decreased from 20.2 to 14.1 by using 12% of OPC; this percentage was enough to increase the UCS of the treated soil up to 1362 kPa after 90 days of curing. With respect to the statistical model of the predicted qu, the results showed that the regression coefficients (R2) was equal to 0.8534 which indicates a good reproducibility for the constructed model.

Keywords: cement admixtures, soft soil stabilisation, geotechnical parameters, multi-regression model

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Authors: Rebeca V. Tholen, Elaine Bundy

Abstract:

Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease Background: Liver transplantation (LT) is considered the only curative treatment for end-stage liver disease (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving an LT. Methods: The HRAR Scale is a predictive tool designed to determine the severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients. (ESLD). The effects of alcoholism can cause irreversible liver damage, cirrhosis and subsequent liver failure. Alcohol relapse after transplant occurs in 20-50% of patients, and increases the risk for recurrent cirrhosis, organ rejection, and graft failure. Alcohol relapse after transplant has been identified as a problem among liver transplant recipients at a large urban academic transplant center in the United States. Transplantation will reverse the complications of ESLD, but it does not treat underlying alcoholism or reduce the risk of relapse after transplant. The purpose of this quality improvement project is to implement and evaluate the effectiveness of a High-Risk Alcoholism Relapse (HRAR) Scale to screen and identify patients at high-risk for alcohol relapse after receiving a LT. Methods: The HRAR Scale is a predictive tool designed to determine severity of alcoholism and risk of relapse after transplant. The scale consists of three variables identified as having the highest predictive power for early relapse including, daily number of drinks, history of previous inpatient treatment for alcoholism, and the number of years of heavy drinking. All adult liver transplant recipients at a large urban transplant center were screened with the HRAR Scale prior to hospital discharge. A zero to two ordinal score is ranked for each variable, and the total score ranges from zero to six. High-risk scores are between three to six. Results: Descriptive statistics revealed 25 patients were newly transplanted and discharged from the hospital during an 8-week period. 40% of patients (n=10) were identified as being high-risk for relapse and 60% low-risk (n=15). The daily number of drinks were determined by alcohol content (1 drink = 15g of ethanol) and number of drinks per day. 60% of patients reported drinking 9-17 drinks per day, and 40% reported ≤ 9 drinks. 50% of high-risk patients reported drinking ≥ 25 years, 40% for 11-25 years, and 10% ≤ 11 years. For number of inpatient treatments for alcoholism, 50% received inpatient treatment one time, 20% ≥ 1, and 30% reported never receiving inpatient treatment. Findings reveal the importance and value of a validated screening tool as a more efficient method than other screening methods alone. Integration of a structured clinical tool will help guide the drinking history portion of the psychosocial assessment. Targeted interventions can be implemented for all high-risk patients. Conclusions: Our findings validate the effectiveness of utilizing the HRAR scale to screen and identify patients who are a high-risk for alcohol relapse post-LT. Recommendations to help maintain post-transplant sobriety include starting a transplant support group within the organization for all high-risk patients.

Keywords: alcoholism, liver transplant, quality improvement, substance abuse

Procedia PDF Downloads 106

Authors: Lotfi O. Gargab, Ruichong R. Zhang

Abstract:

A wave-based framework is presented for modeling seismic motion in multistory buildings and using measured response for system identification which can be utilized to extract important information regarding structure integrity. With one pair of building response at two locations, a generalized model response is formulated based on wave propagation features and expressed as frequency and time response functions denoted, respectively, as GFRF and GIRF. In particular, GIRF is fundamental in tracking arrival times of impulsive wave motion initiated at response level which is dependent on local model properties. Matching model and measured-structure responses can help in identifying model parameters and infer building properties. To show the effectiveness of this approach, the Millikan Library in Pasadena, California is identified with recordings of the Yorba Linda earthquake of September 3, 2002.

Keywords: system identification, continuous-discrete mass modeling, damage detection, post-earthquake

Procedia PDF Downloads 366

Authors: Sonia Besbes, Mahmoud El Hajem, Habib Ben Aissia, Jean Yves Champagne, Jacques Jay

Abstract:

In this work, we present a computational study for the characterization of the flow in a rectangular bubble column. To simulate the dynamic characteristics of the flow, a three-dimensional transient numerical simulations based on a coupled discrete phase model (DPM) and Volume of Fluid (VOF) model are performed. Modeling of bubble column reactor is often carried out under the assumption of a flat liquid surface with a degassing boundary condition. However, the dynamic behavior of the top surface surmounting the liquid phase will to some extent influence the meandering oscillations of the bubble plume. Therefore it is important to capture the surface behavior, and the assumption of a flat surface may not be applicable. So, the modeling approach needs to account for a dynamic liquid surface induced by the rising bubble plume. The volume of fluid (VOF) model was applied for the liquid and top gas which both interacts with bubbles implemented with a discrete phase model. This model treats the bubbles as Lagrangian particles and the liquid and the top gas as Eulerian phases with a sharp interface. Two-way coupling between Eulerian phases and Lagrangian bubbles are accounted for in a single set continuous phase momentum equation for the mixture of the two Eulerian phases. The effect of gas flow rate on the dynamic and time-averaged flow properties was studied. The time averaged liquid velocity field predicted from simulations and from our previous PIV measurements shows that the liquid is entrained up flow in the wake of the bubbles and down flow near the walls. The simulated and measured vertical velocity profiles exhibit a reasonable agreement looking at the minimum velocity values near the walls and the maximum values at the column center.

Keywords: bubble column, computational fluid dynamics (CFD), coupled DPM and VOF model, hydrodynamics

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Authors: Jae-Young Lee, Woo-Young Jung, Myeong-Jun Nam

Abstract:

Water hammer is a hydraulic transient problem which is commonly encountered in the penstocks of hydropower plants. The numerical model was developed to estimate the transient behavior of pressure waves in pipe systems. The computational algorithm was proposed to model the water hammer phenomenon in a pipe system with pump shutdown at midstream and sudden valve closure at downstream. To predict the pressure head and flow velocity as a function of time as a result of rapidly closing a valve and pump shutdown, two boundary conditions at the ends considering pump operation and valve control can be implemented as specified equations of the pressure head and flow velocity based on the characteristics method. It was shown that the effects of transient flow make it determine the needs for protection devices, such as surge tanks, surge relief valves, or air valves, at various points in the system against overpressure and low pressure. It produced reasonably good performance with the results of the proposed transient model for pipeline systems. The proposed numerical model can be used as an efficient tool for the safety assessment of hydropower plants due to water hammer.

Keywords: water hammer, hydraulic transient, pipe systems, characteristics method

Procedia PDF Downloads 126

Authors: Muluken Z. Getie, Francois Lanzetta, Sylvie Begot, Bimrew T. Admassu

Abstract:

This study is aimed at the numerical analysis of the effects of phase angle and losses (shuttle heat loss and gas leakage to the crankcase) that could have an impact on the pressure and temperature of working fluid for a β-type Stirling cycle refrigerating machine. First, the developed numerical model incorporates into the ideal adiabatic analysis, the shuttle heat transfer (heat loss from compression space to expansion space), and gas leakage from the working space to the buffer space into the crankcase. The other losses that may not have a direct effect on the temperature and pressure of working fluid are simply incorporated in a simple analysis. The model is then validated by reversing the model to the engine model and compared with other literature results using (GPU-3) engine. After validating the model with other engine model and experiment results, analysis of the effect of phase angle, shuttle heat lose and gas leakage on temperature, pressure, and performance (power requirement, cooling capacity and coefficient of performance) of refrigerating machine considering the FEMTO 60 Stirling engine as a case study have been conducted. Shuttle heat loss has a greater effect on the temperature of working gas; gas leakage to the crankcase has more effect on the pressure of working spaces and hence both have a considerable impact on the performance of the Stirling cycle refrigerating machine. The optimum coefficient of performance exists between phase angles of 900-950, and optimum cooling capacity could be found between phase angles of 950-980.

Keywords: beta configuration, engine model, moderate cooling, stirling refrigerator, and validation

Procedia PDF Downloads 92