Search results for: conditional proportional reversed hazard rate model

Authors: Darrol Stanley, Levan Efremidze, Jannie Rossouw

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We investigate the predictability of the USD/ZAR (South African Rand) exchange rate with sample entropy analytics for the period of 2004-2015. We calculate sample entropy based on the daily data of the exchange rate and conduct empirical implementation of several market timing rules based on these entropy signals. The dynamic investment portfolio based on entropy signals produces better risk adjusted performance than a buy and hold strategy. The returns are estimated on the portfolio values in U.S. dollars. These results are preliminary and do not yet account for reasonable transactions costs, although these are very small in currency markets.

Keywords: currency trading, entropy, market timing, risk factor model

Procedia PDF Downloads 249

Authors: Burak Bal, Demircan Canadinc

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Dynamic strain aging (DSA), resulting from the reorientation of C-Mn clusters in the core of dislocations, can provide a strain hardening mechanism. In addition, in Hadfield steel, negative strain rate sensitivity is observed due to the DSA. In our study, we incorporated dynamic strain aging onto crystal plasticity computations to predict the local instabilities and corresponding negative strain rate sensitivity. Specifically, the material response of Hadfield steel was obtained from monotonic and strain-rate jump experiments under tensile loading. The strain rate range was adjusted from 10⁻⁴ to 10⁻¹s ⁻¹. The crystal plasticity modeling of the material response was carried out based on Voce-type hardening law and corresponding Voce hardening parameters were determined. The solute pinning effect of carbon atom was incorporated to crystal plasticity simulations at microscale level by computing the shear stress contribution imposed on an arrested dislocation by carbon atom. After crystal plasticity simulations with modifying hardening rule, which takes into account the contribution of DSA, it was seen that the model successfully predicts both the role of DSA and corresponding strain rate sensitivity.

Keywords: crystal plasticity, dynamic strain aging, Hadfield steel, negative strain rate sensitivity

Procedia PDF Downloads 237

Authors: S. Benchelha, H. C. Aoudjehane, M. Hakdaoui, R. El Hamdouni, H. Mansouri, T. Benchelha, M. Layelmam, M. Alaoui

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The logistic regression (LR) and multivariate adaptive regression spline (MarSpline) are applied and verified for analysis of landslide susceptibility map in Oudka, Morocco, using geographical information system. From spatial database containing data such as landslide mapping, topography, soil, hydrology and lithology, the eight factors related to landslides such as elevation, slope, aspect, distance to streams, distance to road, distance to faults, lithology map and Normalized Difference Vegetation Index (NDVI) were calculated or extracted. Using these factors, landslide susceptibility indexes were calculated by the two mentioned methods. Before the calculation, this database was divided into two parts, the first for the formation of the model and the second for the validation. The results of the landslide susceptibility analysis were verified using success and prediction rates to evaluate the quality of these probabilistic models. The result of this verification was that the MarSpline model is the best model with a success rate (AUC = 0.963) and a prediction rate (AUC = 0.951) higher than the LR model (success rate AUC = 0.918, rate prediction AUC = 0.901).

Keywords: landslide susceptibility mapping, regression logistic, multivariate adaptive regression spline, Oudka, Taounate

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Authors: Mohammad Javad Seddighi, Avar Almukhtar

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The occurrence of natural disasters, such as floods and earthquakes, can cause significant damage to heritage sites and surrounding areas. In Iran, the city of Bam was devastated by an earthquake in 2003, which had a major impact on the rivers and watercourses around the city. This study aims to investigate the environmental design techniques and sustainable hazard mitigation strategies that can be employed to preserve heritage sites in the face of natural disasters, using the Bam experience as a case study. The research employs a mixed-methods approach, combining both qualitative and quantitative data collection and analysis methods. The study begins with a comprehensive literature review of recent publications on environmental design techniques and sustainable hazard mitigation strategies in heritage conservation. This is followed by a field study of the rivers and watercourses around Bam, including the Adoori River (Talangoo) and other watercourses, to assess the current conditions and identify potential hazards. The data collected from the field study is analysed using statistical methods and GIS mapping techniques. The findings of this study reveal the importance of sustainable hazard mitigation strategies and environmental design techniques in preserving heritage sites during natural disasters. The study suggests that these techniques can be used to prevent the outbreak of another natural disaster in Bam and the surrounding areas. Specifically, the study recommends the establishment of a comprehensive early warning system, the creation of flood-resistant landscapes, and the use of eco-friendly building materials in the reconstruction of heritage sites. These findings contribute to the current knowledge of sustainable hazard mitigation and environmental design in heritage conservation.

Keywords: natural disasters, heritage conservation, sustainable hazard mitigation, environmental design, landscape architecture, flood management, disaster resilience

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Authors: Walid Chkili

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This paper investigates the dynamic relationship between gold and stock markets using data for BRICS counties. For this purpose, we estimate three multivariate GARCH models (namely CCC, DCC and BEKK) for weekly stock and gold data. Our main objective is to examine time variations in conditional correlations between the two assets and to check the effectiveness use of gold as a hedge for equity markets. Empirical results reveal that dynamic conditional correlations switch between positive and negative values over the period under study. This correlation is negative during the major financial crises suggesting that gold can act as a safe haven during the major stress period of stock markets. We also evaluate the implications for portfolio diversification and hedging effectiveness for the pair gold/stock. Our findings suggest that adding gold in the stock portfolio enhance its risk-adjusted return.

Keywords: gold, financial markets, hedge, multivariate GARCH

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Authors: Adrian Szczyrba, Aneta Halka-Grysinska, Tomasz Baj, Tadeusz H. Dzido

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Since prehistory, plants were constituted as an essential source of biologically active substances in folk medicine. One of the examples of medicinal plants is Ruta graveolens L. For a long time, Ruta g. herb has been famous for its spasmolytic, diuretic, or anti-inflammatory therapeutic effects. The wide spectrum of secondary metabolites produced by Ruta g. includes flavonoids (eg. rutin, quercetin), coumarins (eg. bergapten, umbelliferone) phenolic acids (eg. rosmarinic acid, chlorogenic acid), and limonoids. Unfortunately, the presence of produced substances is highly dependent on environmental factors like temperature, humidity, or soil acidity; therefore standardization is necessary. There were many attempts of characterization of various phytochemical groups (eg. coumarins) of Ruta graveolens using the normal – phase thin-layer chromatography (TLC). However, due to the so-called general elution problem, usually, some components remained unseparated near the start or finish line. Therefore Ruta graveolens is a very good model plant. Methanol and petroleum ether extract from its aerial parts were used to demonstrate the capabilities of the new device for gradient thin-layer chromatogram development. The development of gradient thin-layer chromatograms in the reversed-phase system in conventional horizontal chambers can be disrupted by problems associated with an excessive flux of the mobile phase to the surface of the adsorbent layer. This phenomenon is most likely caused by significant differences between the surface tension of the subsequent fractions of the mobile phase. An excessive flux of the mobile phase onto the surface of the adsorbent layer distorts the flow of the mobile phase. The described effect produces unreliable, and unrepeatable results, causing blurring and deformation of the substance zones. In the prototype device, the mobile phase solution is delivered onto the surface of the adsorbent layer with controlled velocity (by moving pipette driven by 3D machine). The delivery of the solvent to the adsorbent layer is equal to or lower than that of conventional development. Therefore chromatograms can be developed with optimal linear mobile phase velocity. Furthermore, under such conditions, there is no excess of eluent solution on the surface of the adsorbent layer so the higher performance of the chromatographic system can be obtained. Directly feeding the adsorbent layer with eluent also enables to perform convenient continuous gradient elution practically without the so-called gradient delay. In the study, unique fingerprints of methanol and petroleum ether extracts of Ruta graveolens aerial parts were obtained with stepwise gradient reversed-phase thin-layer chromatography. Obtained fingerprints under different chromatographic conditions will be compared. The advantages and disadvantages of the proposed approach to chromatogram development with controlled solvent velocity will be discussed.

Keywords: fingerprints, gradient thin-layer chromatography, reversed-phase TLC, Ruta graveolens

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Authors: Jingwen Shi, Qi Wu

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We study the role played interest rate risk in carry trade return in order to understand the forward premium puzzle. In this study, our goal is to investigate to what extent carry trade return is indeed due to compensation for risk taking and, more important, to reveal the nature of these risks. Using option data not only on exchange rates but also on interest rate swaps (swaptions), our first finding is that, besides the consensus currency risks, interest rate risks also contribute a non-negligible portion to the carry trade return. What strikes us is our second finding. We find that large downside risks of future exchange rate movements are, in fact, priced significantly in option market on interest rates. The role played by interest rate risk differs structurally from the currency risk. There is a unique premium associated with interest rate risk, though seemingly small in size, which compensates the tail risks, the left tail to be precise. On the technical front, our study relies on accurately retrieving implied distributions from currency options and interest rate swaptions simultaneously, especially the tail components of the two. For this purpose, our major modeling work is to build a new international asset pricing model where we use an orthogonal setup for pricing kernels and specify non-Gaussian dynamics in order to capture three sets of option skew accurately and consistently across currency options and interest rate swaptions, domestic and foreign, within one model. Our results open a door for studying forward premium anomaly through implied information from interest rate derivative market.

Keywords: carry trade, forward premium anomaly, FX option, interest rate swaption, implied volatility skew, uncovered interest rate parity

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Authors: Shahlan Surat, Saemah Rahman, Saadiah Kummin

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When teachers reflect and evaluate whether their teaching methods actually have an impact on students’ learning, they will adjust their practices accordingly. This inevitably improves their students’ learning and performance. The approach in meta-teaching can invigorate and create a passion for teaching. It thus helps to increase the commitment and love for the teaching profession. This study was conducted to determine the level of metacognitive thinking of teachers in the process of teaching and learning in the classroom. Metacognitive thinking teachers include the use of metacognitive knowledge which consists of different types of knowledge: declarative, procedural and conditional. The ability of the teachers to plan, monitor and evaluate the teaching process can also be determined. This study was conducted on 377 graduate teachers in Klang Valley, Malaysia. The stratified sampling method was selected for the purpose of this study. The metacognitive teaching inventory consisting of 24 items is called InKePMG (Teacher Indicators of Effectiveness Meta-Teaching). The results showed the level of mean is high for two components of metacognitive knowledge; declarative knowledge (mean = 4.16) and conditional (mean = 4.11) whereas, the mean of procedural knowledge is 4.00 (moderately high). Similarly, the level of knowledge in monitoring (mean = 4.11), evaluating (mean = 4.00) which indicate high score and planning (mean = 4.00) are moderately high score among teachers. In conclusion, this study shows that the planning and procedural knowledge is an important element in improving the quality of teachers teaching in the classroom. Thus, the researcher recommended that further studies should focus on training programs for teachers on metacognitive skills and also on developing creative thinking among teachers.

Keywords: metacognitive thinking skills, procedural knowledge, conditional knowledge, meta-teaching and regulation of cognitive

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Authors: Maha Zouaoui Khalifa, Hakim Ben Othman, Hussaney Khaled

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Prior empirical studies have investigated the economic consequences of accounting conservatism by examining its impact on the cost of equity capital (COEC). However, findings are not conclusive. We assume that inconsistent results of such association may be attributed to the regression models used in data analysis. To address this issue, we re-examine the effect of different dimension of accounting conservatism: unconditional conservatism (U_CONS) and conditional conservatism (C_CONS) on the COEC for a sample of listed firms from Middle Eastern and North Africa (MENA) countries, applying quantile regression (QR) approach developed by Koenker and Basset (1978). While classical ordinary least square (OLS) method is widely used in empirical accounting research, however it may produce inefficient and bias estimates in the case of departures from normality or long tail error distribution. QR method is more powerful than OLS to handle this kind of problem. It allows the coefficient on the independent variables to shift across the distribution of the dependent variable whereas OLS method only estimates the conditional mean effects of a response variable. We find as predicted that U_CONS has a significant positive effect on the COEC however, C_CONS has a negative impact. Findings suggest also that the effect of the two dimensions of accounting conservatism differs considerably across COEC quantiles. Comparing results from QR method with those of OLS, this study throws more lights on the association between accounting conservatism and COEC.

Keywords: unconditional conservatism, conditional conservatism, cost of equity capital, OLS, quantile regression, emerging markets, MENA countries

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Authors: Ankit Tyagi, Reet Kamal Tiwari, Naveen James

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In India, landslides are the most frequently occurring disaster in the regions of the Himalayas and the Western Ghats. The steep slopes and land use in these areas are quite apprehensive. In the recent past, many landslide hazard zonation (LHZ) works have been carried out in the Himalayas. However, the preparation of LHZ maps considering temporal factors such as seismic ground shaking, seismic amplification at surface level, and rainfall are limited. Hence this study presents a comprehensive use of the multi-criteria decision-making (MCDM) method in landslide risk assessment. In this research, we conducted both geospatial and geotechnical analysis to minimize the danger of landslides. Geospatial analysis is performed using high-resolution satellite data to produce landslide causative factors which were given weightage using the MCDM method. The geotechnical analysis includes a slope stability check, which was done to determine the potential landslide slope. The landslide risk map can provide useful information which helps people to understand the risk of living in an area.

Keywords: landslide hazard zonation, PHA, AHP, GIS

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Authors: T. Bouchabchoub, A. Bendahmane, A. Haouriqui, N. Attou

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This paper presents simulation results of Forex predicting model equations in order to give approximately a prevision of interest rates. First, Hall-Taylor (HT) equations have been used with Taylor rule (TR) to adapt them to European and American Forex Markets. Indeed, initial Taylor Rule equation is conceived for all Forex transactions in every States: It includes only one equation and six parameters. Here, the model has been used with Hall-Taylor equations, initially including twelve equations which have been reduced to only three equations. Analysis has been developed on the following base macroeconomic variables: Real change rate, investment wages, anticipated inflation, realized inflation, real production, interest rates, gap production and potential production. This model has been used to specifically study the impact of an inflation shock on macroeconomic director interest rates.

Keywords: interest rate, Forex, Taylor rule, production, European Central Bank (ECB), Federal Reserve System (FED).

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Authors: Goodness C. Aye

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This paper examines the effect of the volatility of oil prices on food price in South Africa using monthly data covering the period 2002:01 to 2014:09. Food price is measured by the South African consumer price index for food while oil price is proxied by the Brent crude oil. The study employs the GARCH-in-mean VAR model, which allows the investigation of the effect of a negative and positive shock in oil price volatility on food price. The model also allows the oil price uncertainty to be measured as the conditional standard deviation of a one-step-ahead forecast error of the change in oil price. The results show that oil price uncertainty has a positive and significant effect on food price in South Africa. The responses of food price to a positive and negative oil price shocks is asymmetric.

Keywords: oil price volatility, food price, bivariate, GARCH-in-mean VAR, asymmetric

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: Eun-Taek Sin, Hyun-Ju Jang, Chang Geun Song, Yong-Sik Han

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Due to the climate change, the coastal urban area repeatedly suffers from the loss of property and life by flooding. There are three main causes of inland submergence. First, when heavy rain with high intensity occurs, the water quantity in inland cannot be drained into rivers by increase in impervious surface of the land development and defect of the pump, storm sewer. Second, river inundation occurs then water surface level surpasses the top of levee. Finally, Coastal inundation occurs due to rising sea water. However, previous studies ignored the complex mechanism of flooding, and showed discrepancy and inadequacy due to linear summation of each analysis result. In this study, inland flooding and river inundation were analyzed together by HDM-2D model. Petrov-Galerkin stabilizing method and flux-blocking algorithm were applied to simulate the inland flooding. In addition, sink/source terms with exponentially growth rate attribute were added to the shallow water equations to include the inland flooding analysis module. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. The applications of developed model gave satisfactory results, and provided accurate prediction in comprehensive flooding analysis. To consider the coastal surge, another module was developed by adding seawater to the existing Inland Flooding-River Inundation binding module for comprehensive flooding analysis. Based on the combined modules, the Coastal Inundation – Inland & River Flow Interface was simulated by inputting the flow rate and depth data in artificial flume. Accordingly, it was able to analyze the flood patterns of coastal cities over time. This study is expected to help identify the complex causes of flooding in coastal areas where complex flooding occurs, and assist in analyzing damage to coastal cities. Acknowledgements—This research was supported by a grant ‘Development of the Evaluation Technology for Complex Causes of Inundation Vulnerability and the Response Plans in Coastal Urban Areas for Adaptation to Climate Change’ [MPSS-NH-2015-77] from the Natural Hazard Mitigation Research Group, Ministry of Public Safety and Security of Korea.

Keywords: flooding analysis, river inundation, inland flooding, 2D hydrodynamic model

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Authors: Njabulo Ncube, Elena Kulinskaya, Nicholas Steel, Dmitry Pshezhetskiy

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Life expectancy in the United Kingdom (UK) has been near constant since 2010, particularly for the individuals of 65 years and older. This trend has been also noted in several other countries. This slowdown in the increase of life expectancy was concurrent with the increase in the number of deaths caused by non-communicable diseases. Of particular concern is the world-wide exponential increase in the number of diabetes related deaths. Previous studies have reported increased mortality hazards among diabetics compared to non-diabetics, and on the differing effects of antidiabetic drugs on mortality hazards. This study aimed to estimate the all-cause mortality hazards and related life expectancies among type 2 diabetes (T2DM) patients in the UK using the time-variant Gompertz-Cox model with frailty. The study also aimed to understand the major causes of the change in life expectancy growth in the last decade. A total of 221 182 (30.8% T2DM, 57.6% Males) individuals aged 50 years and above, born between 1930 and 1960, inclusive, and diagnosed between 2000 and 2016, were selected from The Health Improvement Network (THIN) database of the UK primary care data and followed up to 31 December 2016. About 13.4% of participants died during the follow-up period. The overall all-cause mortality hazard ratio of T2DM compared to non-diabetic controls was 1.467 (1.381-1.558) and 1.38 (1.307-1.457) when diagnosed between 50 to 59 years and 60 to 74 years, respectively. The estimated life expectancies among T2DM individuals without further comorbidities diagnosed at the age of 60 years were 2.43 (1930-1939 birth cohort), 2.53 (1940-1949 birth cohort) and 3.28 (1950-1960 birth cohort) years less than those of non-diabetic controls. However, the 1950-1960 birth cohort had a steeper hazard function compared to the 1940-1949 birth cohort for both T2DM and non-diabetic individuals. In conclusion, mortality hazards for people with T2DM continue to be higher than for non-diabetics. The steeper mortality hazard slope for the 1950-1960 birth cohort might indicate the sub-population contributing to a slowdown in the growth of the life expectancy.

Keywords: T2DM, Gompetz-Cox model with frailty, all-cause mortality, life expectancy

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Authors: Fatih Suleyman Taskincan, Ahmet Karaarslan

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In this article, the study and analysis of Single Ended Primary Inductance Converter (SEPIC) are presented for battery charging applications that will be used in military applications. The usage of this kind of converters come from its advantage of non-reverse polarity at outputs. As capacitors charge and discharge through inductance, peak current does not occur on capacitors. Therefore, the efficiency will be high compared to buck-boost converters. In this study, the converter (SEPIC) is designed to be operated with Internal Model Controller (IMC). The traditional controllers like Proportional Integral Controller are not preferred as its linearity behavior. Hence IMC is designed for this converter. This controller is a model-based control and provides more robustness and better set point monitoring. Moreover, it can be used for an unstable process where the conventional controller cannot handle the dynamic operation. Matlab/Simulink environment is used to simulate the converter and its controller, then, the results are shown and discussed.

Keywords: DC/DC converter, single ended primary inductance converter, SEPIC, internal model controller, IMC, switched mode power supply

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Authors: Ashim Sattar, Ajanta Goswami, Anil V. Kulkarni

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Glacial lake outburst floods (GLOF) highly contributes to mountain hazards in the Himalaya. Over the past decade, high altitude lakes in the Himalaya has been showing notable growth in their size and number. The key reason is rapid retreat of its glacier front. Hydrodynamic modeling GLOF using shallow water equations (SWE) would result in understanding its impact in the downstream region. The present study incorporates remote sensing based ice thickness modeling to determine the future extent of the Dhauliganga Lake to map the over deepening extent around the highest lake in the Dhauliganga basin. The maximum future volume of the lake calculated using area-volume scaling is used to model a GLOF event. The GLOF hydrograph is routed along the channel using one dimensional and two dimensional model to understand the flood wave propagation till it reaches the 1st hydropower station located 72 km downstream of the lake. The present extent of the lake calculated using SENTINEL 2 images is 0.13 km². The maximum future extent of the lake, mapped by investigating the glacier bed has a calculated scaled volume of 3.48 x 106 m³. The GLOF modeling releasing the future volume of the lake resulted in a breach hydrograph with a peak flood of 4995 m³/s at just downstream of the lake. Hydraulic routing

Keywords: GLOF, glacial lake outburst floods, mountain hazard, Central Himalaya, future projection

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Authors: Abdullah M. Alzahrani

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Our physiopathological assumption is that u-PA, t-PA, and PAI-1 are released by calcified aortic valves and play a role in the calcification of these valves. Sixty-five calcified aortic valves were collected from patients suffering from aortic stenosis. Each valve was incubated for 24 hours in culture medium. The supernatants were used to measure u-PA, t-PA, and PAI-1 concentrations; the valve calcification was evaluated using biphotonic absorptiometry. Aortic stenosis valves expressed normal plasminogen activators concentrations and overexpressed PAI-1 (u-PA, t-PA, and PAI-1 mean concentrations were, resp., 1.69 ng/mL ± 0.80, 2.76 ng/mL ± 1.33, and 53.27 ng/mL ± 36.39). There was no correlation between u-PA and PAI-1 (r = 0.3) but t-PA and PAI-1 were strongly correlated with each other (r = 0.6). Over expression of PAI-1 was proportional to the calcium content of theAS valves. Our results demonstrate a consistent increase of PAI-1 proportional to the calcification. The over expression of PAI-1 may be useful as a predictive indicator in patients with aortic stenosis.

Keywords: aortic valve, PAI-1, tPA gene, uPA gene

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Authors: Tengqin Han

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Delinquency has been a crucial factor in economics throughout the years. Commonly seen in credit card and mortgage, it played one of the crucial roles in causing the most recent financial crisis in 2008. In each case, a delinquency is a sign of the loaner being unable to pay off the debt, and thus may cause a lost of property in the end. Individually, one case of delinquency seems unimportant compared to the entire credit system. China, as an emerging economic entity, the national strength and economic strength has grown rapidly, and the gross domestic product (GDP) growth rate has remained as high as 8% in the past decades. However, potential risks exist behind the appearance of prosperity. Among the risks, the credit system is the most significant one. Due to long term and a large amount of balance of the mortgage, it is critical to monitor the risk during the performance period. In this project, about 300,000 mortgage account data are analyzed in order to develop a predictive model to predict the probability of delinquency. Through univariate analysis, the data is cleaned up, and through bivariate analysis, the variables with strong predictive power are detected. The project is divided into two parts. In the first part, the analysis data of 2005 are split into 2 parts, 60% for model development, and 40% for in-time model validation. The KS of model development is 31, and the KS for in-time validation is 31, indicating the model is stable. In addition, the model is further validation by out-of-time validation, which uses 40% of 2006 data, and KS is 33. This indicates the model is still stable and robust. In the second part, the model is improved by the addition of macroeconomic economic indexes, including GDP, consumer price index, unemployment rate, inflation rate, etc. The data of 2005 to 2010 is used for model development and validation. Compared with the base model (without microeconomic variables), KS is increased from 41 to 44, indicating that the macroeconomic variables can be used to improve the separation power of the model, and make the prediction more accurate.

Keywords: delinquency, mortgage, model development, model validation

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Authors: Jianming Cai

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Exposure to ionizing radiation causes severe damage to human body and an safe and effective radioprotector is urgently required for alleviating radiation damage. In 2008, flagellin, an agonist of TLR5, was found to exert radioprotective effects on radiation injury through activating NF-kB signaling pathway. From then, the radioprotective effects of TLR ligands has shed new lights on radiation protection. CpG-ODN is an unmethylated oligonucleotide which activates TLR9 signaling pathway. In this study, we demonstrated that CpG-ODN has therapeutic effects on radiation injuries induced by γ ray and 12C6+ heavy ion particles. Our data showed that CpG-ODN increased the survival rate of mice after whole body irradiation and increased the number of leukocytes as well as the bone marrow cells. CpG-ODN also alleviated radiation damage on intestinal crypt through regulating apoptosis signaling pathway including bcl2, bax, and caspase 3 etc. By using a radiation-induced pulmonary fibrosis model, we found that CpG-ODN could alleviate structural damage, within 20 week after whole–thorax 15Gy irradiation. In this model, Th1/Th2 imbalance induced by irradiation was also reversed by CpG-ODN. We also found that TGFβ-Smad signaling pathway was regulated by CpG-ODN, which accounts for the therapeutic effects of CpG-ODN in radiation-induced pulmonary injury. On another hand, for high LET radiation protection, we investigated protective effects of CpG-ODN against 12C6+ heavy ion irradiation and found that after CpG-ODN treatment, the apoptosis and cell cycle arrest induced by 12C6+ irradiation was reduced. CpG-ODN also reduced the expression of Bax and caspase 3, while increased the level of bcl2. Then we detected the effect of CpG-ODN on heavy ion induced immune dysfunction. Our data showed that CpG-ODN increased the survival rate of mice and also the leukocytes after 12C6+ irradiation. Besides, the structural damage of immune organ such as thymus and spleen was also alleviated by CpG-ODN treatment. In conclusion, we found that TLR9 ligand, CpG-ODN reduced radiation injuries in response to γ ray and 12C6+ heavy ion irradiation. On one hand, CpG-ODN inhibited the activation of apoptosis induced by radiation through regulating bcl2, bax and caspase 3. On another hand, through activating TLR9, CpG-ODN recruit MyD88-IRAK-TRAF6 complex, activating TAK1, IRF5 and NF-kB pathway, and thus alleviates radiation damage. This study provides novel insights into protection and therapy of radiation damages.

Keywords: TLR9, CpG-ODN, radiation injury, high LET radiation

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Authors: Mohadeseh Shojaei Shahrokhabadi, Ding-Geng (Din) Chen

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Positive continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical cost data. To jointly model semi-continuous longitudinal cost data and survival data and to provide marginalized covariate effect estimates, a marginalized two-part joint model (MTJM) has been developed for outcome variables with lognormal distributions. In this paper, we propose MTJM models for outcome variables from a generalized gamma (GG) family of distributions. The GG distribution constitutes a general family that includes approximately all of the most frequently used distributions like the Gamma, Exponential, Weibull, and Log Normal. In the proposed MTJM-GG model, the conditional mean from a conventional two-part model with a three-parameter GG distribution is parameterized to provide the marginal interpretation for regression coefficients. In addition, MTJM-gamma and MTJM-Weibull are developed as special cases of MTJM-GG. To illustrate the applicability of the MTJM-GG, we applied the model to a set of real electronic health record data recently collected in Iran, and we provided SAS code for application. The simulation results showed that when the outcome distribution is unknown or misspecified, which is usually the case in real data sets, the MTJM-GG consistently outperforms other models. The GG family of distribution facilitates estimating a model with improved fit over the MTJM-gamma, standard Weibull, or Log-Normal distributions.

Keywords: marginalized two-part model, zero-inflated, right-skewed, semi-continuous, generalized gamma

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: Li Chen, Alex Skvortsov, Chris Norwood

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Gas releasing into water can be found in for many industrial situations. This process results in the formation of bubbles and acoustic emission which depends upon the bubble characteristics. If the bubble creation rates (bubble volume flow rate) are of interest, an inverse method has to be used based on the measurement of acoustic emission. However, there will be sound attenuation through the bubbly plume which will influence the measurement and should be taken into consideration in the model. The sound transmission through the bubbly plume depends on the characteristics of the bubbly plume, such as the shape and the bubble distributions. In this study, the bubbly plume shape is modelled using a self-similarity model, which has been normally applied for a single phase buoyant plume. The prediction is compared with the experimental data. It has been found the model can be applied to a buoyant plume of gas-liquid mixture. The influence of the gas flow rate and discharge nozzle size is studied.

Keywords: bubbly plume, buoyant plume, bubble acoustics, self-similarity model

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Authors: Lawrence Koech, Hilary Rutto, Olga Mothibedi

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Worldwide demand for copper has led to intensive search for methods of extraction and recovery of copper from different sources. The study investigates the leaching properties of a low-grade copper ore by optimizing the leaching variables using response surface methodology. The effects of key parameters, i.e., temperature, solid to liquid ratio, stirring speed and pH, on the leaching rate constant was investigated using a pH stat apparatus. A Central Composite Design (CCD) of experiments was used to develop a quadratic model which specifically correlates the leaching variables and the rate constant. The results indicated that the model is in good agreement with the experimental data with a correlation coefficient (R2) of 0.93. The temperature and solid to liquid ratio were found to have the most substantial influence on the leaching rate constant. The optimum operating conditions for copper leaching from the ore were identified as temperature at 65C, solid to liquid ratio at 1.625 and stirring speed of 325 rpm which yielded an average leaching efficiency of 93.16%.

Keywords: copper, leaching, CCD, rate constant

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Authors: J. Fernandez de Canete, S. Fernandez-Calvo, I. García-Moral

Abstract:

This paper presents and discusses the application of the object-oriented modelling software SIMSCAPE to hydraulic systems, with particular reference to multivariable proportional-integral-derivative (PID) control. As a result, a particular modelling approach of a double cylinder-piston coupled system is proposed and motivated, and the SIMULINK based PID tuning tool has also been used to select the proper controller parameters. The paper demonstrates the usefulness of the object-oriented approach when both physical modelling and control are tackled.

Keywords: object-oriented modeling, multivariable hydraulic system, multivariable PID control, computer simulation

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Authors: Sana Dridi, Jalel Aouissi, Rafla Attia, Taoufik Hermassi, Thouraya Sahli

Abstract:

Soil erosion is an increasing issue in Mediterranean countries. In Tunisia, the capacity of dam reservoirs continues to decrease as a consequence of soil erosion. This study aims to predict sediment yield to enrich soil management practices using Soil and Water Assessment Tools model (SWAT) in the Siliana watershed (1041.6 km²), located in the northwest of Tunisia. A database was constructed using remote sensing and Geographical Information System. Climatic and flow data were collected from water resources directorates in Tunisia. The SWAT model was built to simulate hydrological processes and sediment transport. A sensitivity analysis, calibration, and validation were performed using SWAT-CUP software. The model calibration of stream flow simulations shows a good performance with NSE and R² values of 0.77 and 0.79, respectively. The model validation shows a very good performance with values of NSE and R² for 0.8 and 0.88, respectively. After calibration and validation of stream flow simulation, the model was used to simulate the soil erosion and sediment load transport. The spatial distributions of soil loss rate for determining the critical sediment source areas show that 63 % of the study area has a low soil loss rate less than 7 t ha⁻¹y⁻¹. The annual average soil loss rate simulated with the SWAT model in the Siliana watershed is 4.62 t ha⁻¹y⁻¹.

Keywords: water erosion, SWAT model, streamflow, SWATCUP, sediment yield

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Authors: Ahmed M. Gamal, Adel M. Belal, S. A. Elsoud

Abstract:

This article aims to study the effect of reinforcement inclusions (geogrids) on the sand dunes bearing capacity under strip footings. In this research experimental physical model was carried out to study the effect of the first geogrid reinforcement depth (u/B), the spacing between the reinforcement (h/B) and its extension relative to the footing length (L/B) on the mobilized bearing capacity. This paper presents the numerical modeling using the commercial finite element package (PLAXIS version 8.2) to simulate the laboratory physical model, studying the same parameters previously handled in the experimental work (u/B, L/B & h/B) for the purpose of validation. In this study the soil, the geogrid, the interface element and the boundary condition are discussed with a set of finite element results and the validation. Then the validated FEM used for studying real material and dimensions of strip foundation. Based on the experimental and numerical investigation results, a significant increase in the bearing capacity of footings has occurred due to an appropriate location of the inclusions in sand. The optimum embedment depth of the first reinforcement layer (u/B) is equal to 0.25. The optimum spacing between each successive reinforcement layer (h/B) is equal to 0.75 B. The optimum Length of the reinforcement layer (L/B) is equal to 7.5 B. The optimum number of reinforcement is equal to 4 layers. The study showed a directly proportional relation between the number of reinforcement layer and the Bearing Capacity Ratio BCR, and an inversely proportional relation between the footing width and the BCR.

Keywords: reinforced soil, geogrid, sand dunes, bearing capacity

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Authors: T. N. Mac, B. Shahbodaghkhan, N. Khalili

Abstract:

A new elastic-viscoplastic (EVP) constitutive model is proposed for the analysis of time-dependent behavior of clay. The proposed model is based on the bounding surface plasticity and the concept of viscoplastic consistency framework to establish continuous transition from plasticity to rate dependent viscoplasticity. Unlike the overstress based models, this model will meet the consistency condition in formulating the constitutive equation for EVP model. The procedure of deriving the constitutive relationship is also presented. Simulation results and comparisons with experimental data are then presented to demonstrate the performance of the model.

Keywords: bounding surface, consistency theory, constitutive model, viscosity

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Authors: M. F. Wu, F. T. Cheng

Abstract:

Leather industry is the most important traditional industry to provide the leather products in the world for thousand years. The fierce global competitive environment and common awareness of global carbon reduction make livestock supply quantities falling, salt and wet blue leather material reduces and the price skyrockets significantly. Exchange rate fluctuation led sales revenue decreasing which due to the differences of export exchanges and compresses the overall profitability of leather industry. This paper applies activity-based benefit assessment approach to build up fitness fur input mixed model, fur is Wet Blue, which concerned with four key factors: the output rate of wet blue, unit cost of wet blue, yield rate and grade level of Wet Blue to achieve the low cost strategy under given unit price of leather product condition of the company. The research findings indicate that applying this model may improve the input cost structure, decrease numbers of leather product inventories and to raise the competitive advantages of the enterprise in the future.

Keywords: activity-based benefit assessment approach, input mixed, output rate, wet blue

Procedia PDF Downloads 355

Authors: Rachid Belhachemi, Pierre Rostan, Alexandra Rostan

Abstract:

This paper develops a discrete-time option pricing model for index options. The model consists of two key ingredients. First, daily stock return innovations are driven by a continuous hidden threshold mixed skew-normal (HTSN) distribution which generates conditional non-normality that is needed to fit daily index return. The most important feature of the HTSN is the inclusion of a latent state variable with a continuum of states, unlike the traditional mixture distributions where the state variable is discrete with little number of states. The HTSN distribution belongs to the class of univariate probability distributions where parameters of the distribution capture the dependence between the variable of interest and the continuous latent state variable (the regime). The distribution has an interpretation in terms of a mixture distribution with time-varying mixing probabilities. It has been shown empirically that this distribution outperforms its main competitor, the mixed normal (MN) distribution, in terms of capturing the stylized facts known for stock returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence. Second, heteroscedasticity in the model is captured by a threeexogenous-factor GARCH model (GARCHX), where the factors are taken from the principal components analysis of various world indices and presents an application to option pricing. The factors of the GARCHX model are extracted from a matrix of world indices applying principal component analysis (PCA). The empirically determined factors are uncorrelated and represent truly different common components driving the returns. Both factors and the eight parameters inherent to the HTSN distribution aim at capturing the impact of the state of the economy on price levels since distribution parameters have economic interpretations in terms of conditional volatilities and correlations of the returns with the hidden continuous state. The PCA identifies statistically independent factors affecting the random evolution of a given pool of assets -in our paper a pool of international stock indices- and sorting them by order of relative importance. The PCA computes a historical cross asset covariance matrix and identifies principal components representing independent factors. In our paper, factors are used to calibrate the HTSN-GARCHX model and are ultimately responsible for the nature of the distribution of random variables being generated. We benchmark our model to the MN-GARCHX model following the same PCA methodology and the standard Black-Scholes model. We show that our model outperforms the benchmark in terms of RMSE in dollar losses for put and call options, which in turn outperforms the analytical Black-Scholes by capturing the stylized facts known for index returns, namely, volatility clustering, leverage effect, skewness, kurtosis and regime dependence.

Keywords: continuous hidden threshold, factor models, GARCHX models, option pricing, risk-premium

Procedia PDF Downloads 283