Search results for: sequential dependence model

Authors: Mikhail S. Zastrozhin, Valery V. Smirnov, Dmitry A. Sychev, Ludmila M. Savchenko, Evgeny A. Bryun, Mark O. Nechaev

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Cytochrome P-450 isoenzyme 3A4 takes part in the biotransformation of medical drugs. The activity of CYP isoenzymes depends on genetic (polymorphisms of genes which encoded it) and phenotypic factors (a kind of food, a concomitant drug therapy). The aim of the study was to evaluate a carbamazepine effect on the CYP3A4 activity in patients with alcohol addiction. The study included 25 men with alcohol dependence, who received haloperidol during the exacerbation of the addiction. CYP3A4 activity was assessed by urinary 6-beta-hydroxycortisol/cortisol ratios measured by high performance liquid chromatography with mass spectrometry. The study modeled a graph and an equation of the logarithmic regression, that reflects the dependence of CYP3A4 activity on a dose of carbamazepine: y = 5,5 * 9,1 * 10-5 * x2. The study statistically significant demonstrates the effect of carbamazepine on CYP2D6 isozyme activity in patients with alcohol addiction.

Keywords: CYP3A4, biotransformation, carbamazepine, alcohol abuse

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Authors: G. Medkour Ishak-Boushaki, A. Taibi, M. Allab

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Quantitative environmental radioactivity measurements are needed to determine the level of exposure of a population to ionizing radiations and for the assessment of the associated risks. Gamma spectrometry remains a very powerful tool for the analysis of radionuclides present in an environmental sample but the basic problem in such measurements is the low rate of detected events. Using large environmental samples could help to get around this difficulty but, unfortunately, new issues are raised by gamma rays attenuation and self-absorption. Recently, a new method has been suggested, to detect and identify without quantification, in a short time, a gamma ray of a low count source. This method does not require, as usually adopted in gamma spectrometry measurements, a pulse height spectrum acquisition. It is based on a chronological record of each detected photon by simultaneous measurements of its energy ε and its arrival time τ on the detector, the pair parameters [ε,τ] defining an event mode sequence (EMS). The EMS serials are analyzed sequentially by a Bayesian approach to detect the presence of a given radioactive source. The main object of the present work is to test the applicability of this sequential approach in radioactive environmental materials detection. Moreover, for an appropriate health oversight of the public and of the concerned workers, the analysis has been extended to get a reliable quantification of the radionuclides present in environmental samples. For illustration, we consider as an example, the problem of detection and quantification of 238U. Monte Carlo simulated experience is carried out consisting in the detection, by a Ge(Hp) semiconductor junction, of gamma rays of 63 keV emitted by 234Th (progeny of 238U). The generated EMS serials are analyzed by a Bayesian inference. The application of the sequential Bayesian approach, in environmental radioactivity analysis, offers the possibility of reducing the measurements time without requiring large environmental samples and consequently avoids the attached inconvenient. The work is still in progress.

Keywords: Bayesian approach, event mode sequence, gamma spectrometry, Monte Carlo method

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Authors: Raj K. Gupta, X. Gary Tan, Andrzej Przekwas

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Bomb blasts from Improvised Explosive Devices (IEDs) account for vast majority of terrorist attacks worldwide. Injuries caused by IEDs result from a combination of the primary blast wave, penetrating fragments, and human body accelerations and impacts. This paper presents a multiscale computational model of coupled blast physics, whole human body biodynamics and injury biomechanics of sensitive organs. The disparity of the involved space- and time-scales is used to conduct sequential modeling of an IED explosion event, CFD simulation of blast loads on the human body and FEM modeling of body biodynamics and injury biomechanics. The paper presents simulation results for blast-induced brain injury coupling macro-scale brain biomechanics and micro-scale response of sensitive neuro-axonal structures. Validation results on animal models and physical surrogates are discussed. Results of our model can be used to 'replicate' filed blast loadings in laboratory controlled experiments using animal models and in vitro neuro-cultures.

Keywords: blast waves, improvised explosive devices, injury biomechanics, mathematical models, traumatic brain injury

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Authors: Nithipattara Balsiri

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The purposes of this research was to develop instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge of undergraduate students. The sample consisted of 307 undergraduate students. Critical thinking and cognitive skills test were employed for data collection. Second-order confirmatory factor analysis, t-test, and one-way analysis of variance were employed for data analysis using SPSS and LISREL programs. The major research results were as follows; 1) the instructional model by using research-based learning enhancing critical thinking, cognitive skills, and culture and local wisdom knowledge should be consists of 6 sequential steps, namely (1) the setting research problem (2) the setting research hypothesis (3) the data collection (4) the data analysis (5) the research result conclusion (6) the application for problem solving, and 2) after the treatment undergraduate students possessed a higher scores in critical thinking and cognitive skills than before treatment at the 0.05 level of significance.

Keywords: critical thinking, cognitive skills, culture and local wisdom knowledge

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Authors: Wael Elsaady, S. Olutunde Oyadiji, Adel Nasser

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The non-linear flow characteristics of magnetorheological (MR) fluids in MR dampers are studied via a coupled numerical approach that incorporates a two-phase flow model. The approach couples the Finite Element (FE) modelling of the damper magnetic circuit, with the Computational Fluid Dynamics (CFD) analysis of the flow field in the damper. The two-phase flow CFD model accounts for the effect of fluid compressibility due to the presence of liquid and gas in the closed domain of the damper. The dynamic mesh model included in ANSYS/Fluent CFD solver is used to simulate the movement of the MR damper piston in order to perform the fluid excitation. The two-phase flow analysis is studied by both Volume-Of-Fluid (VOF) model and mixture model that are included in ANSYS/Fluent. The CFD models show that the hysteretic behaviour of MR dampers is due to the effect of fluid compressibility. The flow field shows the distributions of pressure, velocity, and viscosity contours. In particular, it shows the high non-Newtonian viscosity in the affected fluid regions by the magnetic field and the low Newtonian viscosity elsewhere. Moreover, the dependence of gas volume fraction on the liquid pressure inside the damper is predicted by the mixture model. The presented approach targets a better understanding of the complicated flow characteristics of viscoplastic fluids that could be applied in different applications.

Keywords: viscoplastic fluid, magnetic FE analysis, computational fluid dynamics, two-phase flow, dynamic mesh, user-defined functions

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Authors: Khashayar Nasrifar

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Ionic liquids (ILs) exhibit particular properties exemplified by extremely low vapor pressure and high thermal stability. The properties of ILs can be tailored by proper selection of cations and anions. As such, ILs are appealing as potential solvents to substitute traditional solvents with high vapor pressure. One of the IL properties required in chemical and process design is density. In developing corresponding state liquid density correlations, scaling hypothesis is often used. The hypothesis expresses the temperature dependence of saturated liquid densities near the vapor-liquid critical point as a function of reduced temperature. Extending the temperature dependence, several successful correlations were developed to accurately correlate the densities of normal liquids from the triple point to a critical point. Applying mixing rules, the liquid density correlations are extended to liquid mixtures as well. ILs are not molecular liquids, and they are not classified among normal liquids either. Also, ILs are often used where the condition is far from equilibrium. Nevertheless, in calculating the properties of ILs, the use of corresponding state correlations would be useful if no experimental data were available. With well-known generalized saturated liquid density correlations, the accuracy in predicting the density of ILs is not that good. An average error of 4-5% should be expected. In this work, a data bank was compiled. A simplified and concise corresponding state saturated liquid density correlation is proposed by phenomena-logically modifying reduced temperature using the temperature-dependence for an interacting parameter of the Soave-Redlich-Kwong equation of state. This modification improves the temperature dependence of the developed correlation. Parametrization was next performed to optimize the three global parameters of the correlation. The correlation was then applied to the ILs in our data bank with satisfactory predictions. The correlation of IL density applied at 0.1 MPa and was tested with an average uncertainty of around 2%. No adjustable parameter was used. The critical temperature, critical volume, and acentric factor were all required. Methods to extend the predictions to higher pressures (200 MPa) were also devised. Compared to other methods, this correlation was found more accurate. This work also presents the chronological order of developing such correlations dealing with ILs. The pros and cons are also expressed.

Keywords: correlation, corresponding state principle, ionic liquid, density

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Authors: Michaela Dušková, Kateřina Šimůnková, Martin Hill, Hana Hruškovičová, Hana Pospíšilová, Eva Králíková, Luboslav Stárka

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Smoking represents the most widespread substance dependence in the world. Several studies show the nicotine's ability to alter women hormonal homeostasis. Women smokers have higher testosterone and lower estradiol levels throughout life compared to non-smoker women. We monitored the effect of smoking discontinuation on steroid spectrum with 40 premenopausal and 60 postmenopausal women smokers. These women had been examined before they discontinued smoking and also after 6, 12, 24, and 48 weeks of abstinence. At each examination, blood was collected to determine steroid spectrum (measured by GC-MS), LH, FSH, and SHBG (measured by IRMA). Repeated measures ANOVA model was used for evaluation of the data. The study has been approved by the local Ethics Committee. Given the small number of premenopausal women who endured not to smoke, only the first 6 week period data could be analyzed. A slight increase in androgens after the smoking discontinuation occurred. In postmenopausal women, an increase in testosterone, dihydrotestosterone, dehydroepiandrosterone, and other androgens occurred, too. Nicotine replacement therapy, weight changes, and age does not play any role in the androgen level increase. The higher androgens levels correlated with failure in smoking cessation. Women smokers have higher androgen levels, which might play a role in smoking dependence development. Women successful in smoking cessation, compared to the non-successful ones, have lower androgen levels initially and also after smoking discontinuation. The question is what androgen levels women have before they start smoking.

Keywords: addiction, smoking, cessation, androgens

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Authors: Pramod K. Prabhakar, Prem P. Srivastav

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Rohu (Labeo rohita) is an Indian major carp and highly relished freshwater food for its unique flavor, texture, and culinary properties. It is highly perishable and, spoilage occurs as a result of series of complicated biochemical changes brought about by enzymes which are the function of time and storage temperature also. The influence of storage temperature (5, 0, and -5 °C) on colour and texture of fish were studied during 14 days storage period in order to analyze kinetics of colour and textural changes. The rate of total colour change was most noticeable at the highest storage temperature (5°C), and these changes were well described by the first order reaction. Texture is an important variable of quality of the fish and is increasing concern to aquaculture industries. Textural parameters such as hardness, toughness and stiffness were evaluated on a texture analyzer for the different day of stored fish. The significant reduction (P ≤ 0.05) in hardness was observed after 2nd, 4th and 8th day for the fish stored at 5, 0, and -5 °C respectively. The textural changes of fish during storage followed a first order kinetic model and fitted well with this model (R2 > 0.95). However, the textural data with respect to time was also fitted to modified Maxwell model and found to be good fit with R2 value ranges from 0.96 to 0.98. Temperature dependence of colour and texture change was adequately modelled with the Arrhenius type equation. This fitted model may be used for the determination of shelf life of Rohu Rohu (Labeo rohita) Fish.

Keywords: first order kinetics, biochemical changes, Maxwell model, colour, texture, Arrhenius type equation

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Authors: Patikineti Sreenivasulu, K. srinivasa Rao, A. Vinaya Babu

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The demand for portability, performance and high functional integration density of digital devices leads to the scaling of complementary metal oxide semiconductor (CMOS) devices inevitable. The increase in power consumption, coupled with the increasing demand for portable/hand-held electronics, has made power consumption a dominant concern in the design of VLSI circuits today. MTCMOS technology provides low leakage and high performance operation by utilizing high speed, low Vt (LVT) transistors for logic cells and low leakage, high Vt (HVT) devices as sleep transistors. Sleep transistors disconnect logic cells from the supply and/or ground to reduce the leakage in the sleep mode. In this technology, energy consumption while doing the mode transition and minimum time required to turn ON the circuit upon receiving the wake up signal are issues to be considered because these can adversely impact the performance of VLSI circuit. In this paper we are introducing an enhancing method of MTCMOS technology to optimize the power in MTCMOS sequential circuits.

Keywords: power consumption, ultra-low power, leakage, sub threshold, MTCMOS

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Authors: Jun Sung Go, Jong Kang Park, Jong Tae Kim

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As semi-conductor manufacturing technology evolves; the single event transient problem becomes more significant issue. Single event transient has a critical impact on both combinational and sequential logic circuits, so it is important to evaluate the soft error tolerance of the circuits at the design stage. In this paper, we present a soft error detecting simulation using scan chain. The simulation model generates a single event transient randomly in the circuit, and detects the soft error during the execution of the test patterns. We verified this model by inserting a scan chain in an 8051 microprocessor using 65 nm CMOS technology. While the test patterns generated by ATPG program are passing through the scan chain, we insert a single event transient and detect the number of soft errors per sub-module. The experiments show that the soft error rates per cell area of the SFR module is 277% larger than other modules.

Keywords: scan chain, single event transient, soft error, 8051 processor

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Authors: Abolfazl Zaraki, Yoshikatsu Hayashi, Harry Thorpe, Vincent Strong, Gisle-Andre Larsen, William Holderbaum

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Thanks to the high maneuverability of the cable-driven hyper-redundant manipulators (HRMs), this class of robots has shown a superior capability in highly confined and unstructured space applications. Although the large number of degrees of freedom (DOF) of HRMs enhances the motion flexibility and the robot’s reachability range, it highly increases the complexity of the kinematic configuration which makes the kinematic control problem very challenging or even impossible to solve. This paper presents our current progress achieved on the development of a kinematic-based leader-follower control system which is designed to control not only the robot’s body posture but also to control the trajectory of the robot’s movement in a semi-autonomous manner (the human operator is retained in the robot’s control loop). To obtain the forward kinematic model, the coordinate frames are established by the classical Denavit–Hartenburg (D-H) convention for a hyper-redundant serial manipulator which has a controlled cables-driven mechanism. To solve the inverse kinematics of the robot, unlike the conventional methods, a leader-follower mechanism, based on the sequential inverse kinematic, is followed. Using this mechanism, the inverse kinematic problem is solved for all sequential joints starting from the head joint to the base joint of the robot. To verify the kinematic design and simulate the robot motion, the MATLAB robotic toolbox is used. The simulation result demonstrated the promising capability of the proposed leader-follower control system in controlling the robot motion and trajectory in our confined space application.

Keywords: hyper-redundant robots, kinematic analysis, semi-autonomous control, serial manipulators

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Authors: Emi̇ne Avşar Aydin, Nezahat Günenç Tuncel, A. Hami̇t Serbest

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The electromagnetic scattering from a canonical structure is an important issue in electromagnetic theory. In this study, the electromagnetic scattering from a dielectric sphere with oblique incidence is investigated. The incident field is considered as a plane wave with H polarized. The scattered and transmitted field expressions with unknown coefficients are written. The unknown coefficients are obtained by using exact boundary conditions. Then, the sphere is considered as having frequency dependent dielectric permittivity. The frequency dependence is shown by Cole-Cole model. The far scattered field expressions are found respect to different incidence angles in the 1-8 GHz frequency range. The observation point is the angular distance of pi from an incident wave. While an incident wave comes with a certain angle, observation point turns from 0 to 360 degrees. According to this, scattered field amplitude is maximum at the location of the incident wave, scattered field amplitude is minimum at the across incident wave. Also, the scattered fields are plotted versus frequency to show frequency-dependence explicitly. Graphics are shown for some incident angles compared with the Harrington's solution. Thus, the results are obtained faster and more reliable with reciprocal rotation. It is expected that when there is another sphere with different properties in the outer sphere, the presence and location of the sphere will be detected faster. In addition, this study leads to use for biomedical applications in the future.

Keywords: scattering, dielectric sphere, oblique incidence, reciprocal rotation

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Authors: Ipek Kivanc, Demet Ozgur-Unluakin

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Over the past years, technological innovations and advancements have played an important role in the industrial world. Due to technological improvements, the degree of complexity of the systems has increased. Hence, all systems are getting more uncertain that emerges from increased complexity, resulting in more cost. It is challenging to cope with this situation. So, implementing efficient planning of maintenance activities in such systems are getting more essential. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for stochastic sequential decision problems under uncertainty. Although maintenance optimization in a dynamic environment can be modeled as such a sequential decision problem, POMDPs are not widely used for tackling maintenance problems. However, they can be well-suited frameworks for obtaining optimal maintenance policies. In the classical representation of the POMDP framework, the system is denoted by a single node which has multiple states. The main drawback of this classical approach is that the state space grows exponentially with the number of state variables. On the other side, factored representation of POMDPs enables to simplify the complexity of the states by taking advantage of the factored structure already available in the nature of the problem. The main idea of factored POMDPs is that they can be compactly modeled through dynamic Bayesian networks (DBNs), which are graphical representations for stochastic processes, by exploiting the structure of this representation. This study aims to demonstrate how maintenance planning of dynamic systems can be modeled with factored POMDPs. An empirical maintenance planning problem of a dynamic system consisting of four partially observable components deteriorating in time is designed. To solve the empirical model, we resort to Symbolic Perseus solver which is one of the state-of-the-art factored POMDP solvers enabling approximate solutions. We generate some more predefined policies based on corrective or proactive maintenance strategies. We execute the policies on the empirical problem for many replications and compare their performances under various scenarios. The results show that the computed policies from the POMDP model are superior to the others. Acknowledgment: This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant no: 117M587.

Keywords: factored representation, maintenance, multi-component system, partially observable Markov decision processes

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Authors: Sahil Kumar, Rajaram Ghadge, Ramesh Bhujade

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Historically, lipid extraction from dried algal biomass remained a focus area of the algal research. It has been realized over the past few years that the lipid-centric approach and conversion technologies that require dry algal biomass have several challenges. Algal culture in cultivation systems contains more than 99% water, with algal concentrations of just a few hundred milligrams per liter ( < 0.05 wt%), which makes harvesting and drying energy intensive. Drying the algal biomass followed by extraction also entails the loss of water and nutrients. In view of these challenges, focus has shifted toward developing processes that will enable oil production from wet algal biomass without drying. Hydrothermal liquefaction (HTL), an emerging technology, is a thermo-chemical conversion process that converts wet biomass to oil and gas using water as a solvent at high temperature and high pressure. HTL processes wet algal slurry containing more than 80% water and significantly reduces the adverse cost impact owing to drying the algal biomass. HTL, being inherently feedstock agnostic, i.e., can convert carbohydrates and proteins also to fuels and recovers water and nutrients. It is most effective with low-lipid (10--30%) algal biomass, and bio-crude yield is two to four times higher than the lipid content in the feedstock. In the early 2010s, research remained focused on increasing the oil yield by optimizing the process conditions of HTL. However, various techno-economic studies showed that simply converting algal biomass to only oil does not make economic sense, particularly in view of low crude oil prices. Making the best use of every component of algae is a key for economic viability of algal to oil process. On investigation of HTL reactions at the molecular level, it has been observed that sequential HTL has the potential to recover value-added products along with biocrude and improve the overall economics of the process. This potential of sequential HTL makes it a most promising technology for converting wet waste to wealth. In this presentation, we will share our experience on the techno-economic and engineering aspects of sequential HTL for conversion of algal biomass to algal bio-oil and co-products.

Keywords: algae, biomass, lipid, protein

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Authors: Nato Kutaladze, George Mikuchadze, Giorgi Sokhadze

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Precipitation forecasts are one of the most demanding applications in numerical weather prediction (NWP). Georgia, as the whole Caucasian region, is characterized by very complex topography. The country territory is prone to flash floods and mudflows, quantitative precipitation estimation (QPE) and quantitative precipitation forecast (QPF) at any leading time are very important for Georgia. In this study, advanced research weather forecasting model’s skill in QPF is investigated over Georgia’s territory. We have analyzed several convection parameterization and microphysical scheme combinations for different rainy episodes and heavy rainy phenomena. We estimate errors and biases in accumulated 6 h precipitation using different spatial resolution during model performance verification for 12-hour and 24-hour lead time against corresponding rain gouge observations and satellite data. Various statistical parameters have been calculated for the 8-month comparison period, and some skills of model simulation have been evaluated. Our focus is on the formation and organization of convective precipitation systems in a low-mountain region. Several problems in connection with QPF have been identified for mountain regions, which include the overestimation and underestimation of precipitation on the windward and lee side of the mountains, respectively, and a phase error in the diurnal cycle of precipitation leading to the onset of convective precipitation in model forecasts several hours too early.

Keywords: extremal dependence index, false alarm, numerical weather prediction, quantitative precipitation forecasting

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Authors: Zakaria S. G. Hegazy, Walid M. A. Ahmed

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This paper examines the dependence structure of Islamic stock markets on Bitcoin’s realized volatility components in bear, normal, and bull market periods. A quantile regression approach is employed, after adjusting raw returns with respect to a broad set of relevant global factors and accounting for structural breaks in the data. The results reveal that upside volatility tends to exert negative influences on Islamic developed-market returns more in bear than in bull market conditions, while downside volatility positively affects returns during bear and bull conditions. For emerging markets, we find that the upside (downside) component exerts lagged negative (positive) effects on returns in bear (all) market regimes. By and large, the dependence structures turn out to be asymmetric. Our evidence provides essential implications for investors.

Keywords: cryptocurrency markets, bitcoin, realized volatility measures, asymmetry, quantile regression

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Authors: Fabiana Lucena Oliveira, Aristides da Rocha Oliveira Junior

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This article discusses the dependence on air transport mode of agile supply chains. The agile supply chains are the result of the analysis of the uncertainty supply chain model, which ranks the supply chain, according to the respective product. Thus, understanding the Uncertainty Model and life cycle of products considered standard and innovative is critical to understanding these. The innovative character in the intersection of supply chains arising from the uncertainty model with its most appropriate transport mode. Consider here the variables availability, security and freight as determinants for choosing these modes. Therefore, the research problem is: How agile supply chains maintains logistics competitiveness, as these are dependent on air transport mode? A case study in Manaus Industrial Pole (MIP), an agglomeration model that includes six hundred industries from different backgrounds and billings, located in the Brazilian Amazon. The sample of companies surveyed include those companies whose products are classified in agile supply chains , as innovative and therefore live with the variable uncertainty in the demand for inputs or the supply of finished products. The results confirm the hypothesis that the dependency level of air transport mode is greater than fifty percent. It follows then, that maintain agile supply chain away from suppliers base is expensive (1) , and continuity analysis needs to be remade on each twenty four months (2) , consider that additional freight, handling and storage as members of the logistics costs (3) , and the comparison with the upcoming agile supply chains the world need to consider the location effect (4).

Keywords: uncertainty model, air transport mode, competitiveness, logistics

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Authors: Yunhui Sun, Qingquan Liu, Xiaoliang Wang

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Dense granular flows widely exist in geological flows such as debris flow, landslide, or sheet flow, where both the interparticle and solid-liquid interactions are important to modify the flow. So, a two-phase approach with both phases correctly modelled is important for a better investigation of the saturated granular flows. However, a proper closure model covering a wide range of flowing states for the solid phase is still lacking. This study first employs a chute flow experiment based on the refractive index matching method, which makes it possible to obtain internal flow information such as velocity, shear rate, granular fluctuation, and volume fraction. The granular stress is obtained based on a steady assumption. The kinetic theory is found to describe the stress dependence on the flow state well. More importantly, the granular rheology is found to be frictionally dominated under weak shear and collisionally dominated under strong shear. The results presented thus provide direct experimental evidence on a possible frictional-collisional closure model for the granular phase. The data indicates that both frictional stresses exist over a wide range of the volume fraction, though traditional theory believes it vanishes below a critical volume fraction. Based on the findings, a two-phase model is used to simulate the chute flow. Both phases are modelled as continuum media, and the inter-phase interactions, such as drag force and pressure gradient force, are considered. The frictional-collisional model is used for the closure of the solid phase stress. The profiles of the kinematic properties agree well with the experiments. This model is further used to simulate immersed granular collapse, which is unsteady in nature, to study the applicability of this model, which is derived from steady flow.

Keywords: closure model, collision, friction, granular flow, two-phase model

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Authors: Stella O. Olubodun, George E. Eriyamremu

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The study assessed the effect of crude oil applied at rates, 0, 2, 5, and 10% on the fractional chemical forms and availability of some metals in soils from Usen, Edo State, with no known crude oil contamination and soil from a crude oil spill site in Ubeji, Delta State, Nigeria. Three methods were used to determine the bioavailability of metals in the soils: maize (Zea mays) plant, EDTA and BCR sequential extraction. The sequential extract acid soluble fraction of the BCR extraction (most labile fraction of the soils, normally associated with bioavailability) were compared with total metal concentration in maize seedlings as a means to compare the chemical and biological measures of bioavailability. Total Fe was higher in comparison to other metals for the crude oil contaminated soils. The metal concentrations were below the limits of 4.7% Fe, 190mg/kg Cu and 720mg/kg Zn intervention values and 36mg/kg Cu and 140mg/kg Zn target values for soils provided by the Department of Petroleum Resources (DPR) guidelines. The concentration of the metals in maize seedlings increased with increasing rates of crude oil contamination. Comparison of the metal concentrations in maize seedlings with EDTA extractable concentrations showed that EDTA extracted more metals than maize plant.

Keywords: availability, crude oil contamination, EDTA, maize, metals

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Authors: O. Benabdeljelil, A. Karioun, S. Amami, R. Rouger, M. Hamidine

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A model for preventing the risks related to climate conditions in the agricultural sector is presented. It will determine the yearly optimum premium to be paid by a producer in order to reach his required turnover. The model is based on both climatic stability and 'soft' responses of usually grown species to average climate variations at the same place and inside a safety ball which can be determined from past meteorological data. This allows the use of linear regression expression for dependence of production result in terms of driving meteorological parameters, the main ones of which are daily average sunlight, rainfall and temperature. By simple best parameter fit from the expert table drawn with professionals, optimal representation of yearly production is determined from records of previous years, and yearly payback is evaluated from minimum yearly produced turnover. The model also requires accurate pricing of commodity at N+1. Therefore, a pricing model is developed using 3 state variables, namely the spot price, the difference between the mean-term and the long-term forward price, and the long-term structure of the model. The use of historical data enables to calibrate the parameters of state variables, and allows the pricing of commodity. Application to beet sugar underlines pricer precision. Indeed, the percentage of accuracy between computed result and real world is 99,5%. Optimal premium is then deduced and gives the producer a useful bound for negotiating an offer by insurance companies to effectively protect its harvest. The application to beet production in French Oise department illustrates the reliability of present model with as low as 6% difference between predicted and real data. The model can be adapted to almost any agricultural field by changing state parameters and calibrating their associated coefficients.

Keywords: agriculture, production model, optimal price, meteorological factors, 3-factor model, parameter calibration, forward price

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Authors: Ella Sèdé Maforikan

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Sustained water management requires quantitative information and the knowledge of spatiotemporal dynamics of hydrological system within the basin. This can be achieved through the research. Several studies have investigated both surface water and groundwater in Beterou catchment. However, there are few published papers on the application of the SWAT modeling in Beterou catchment. The objective of this study was to evaluate the performance of SWAT to simulate the water balance within the watershed. The inputs data consist of digital elevation model, land use maps, soil map, climatic data and discharge records. The model was calibrated and validated using the Sequential Uncertainty Fitting (SUFI2) approach. The calibrated started from 1989 to 2006 with four years warming up period (1985-1988); and validation was from 2007 to 2020. The goodness of the model was assessed using five indices, i.e., Nash–Sutcliffe efficiency (NSE), the ratio of the root means square error to the standard deviation of measured data (RSR), percent bias (PBIAS), the coefficient of determination (R²), and Kling Gupta efficiency (KGE). Results showed that SWAT model successfully simulated river flow in Beterou catchment with NSE = 0.79, R2 = 0.80 and KGE= 0.83 for the calibration process against validation process that provides NSE = 0.78, R2 = 0.78 and KGE= 0.85 using site-based streamflow data. The relative error (PBIAS) ranges from -12.2% to 3.1%. The parameters runoff curve number (CN2), Moist Bulk Density (SOL_BD), Base Flow Alpha Factor (ALPHA_BF), and the available water capacity of the soil layer (SOL_AWC) were the most sensitive parameter. The study provides further research with uncertainty analysis and recommendations for model improvement and provision of an efficient means to improve rainfall and discharges measurement data.

Keywords: watershed, water balance, SWAT modeling, Beterou

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Authors: Shivani Saini

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The effect of vertical throughflow on the onset of convection in Rivlin-Ericksen Elastico-Viscous nanofluid with convective boundary condition is investigated. The flow is stimulated with modified Darcy model under the assumption that the nanoparticle volume fraction is not actively managed on the boundaries. The heat conservation equation is formulated by introducing the convective term of nanoparticle flux. A linear stability analysis based upon normal mode is performed, and an approximate solution of eigenvalue problems is obtained using the Galerkin weighted residual method. Investigation of the dependence of the Rayleigh number on various viscous and nanofluid parameter is performed. It is found that through flow and nanofluid parameters hasten the convection while capacity ratio, kinematics viscoelasticity, and Vadasz number do not govern the stationary convection. Using the convective component of nanoparticle flux, critical wave number is the function of nanofluid parameters as well as the throughflow parameter. The obtained solution provides important physical insight into the behavior of this model.

Keywords: Darcy model, nanofluid, porous layer, throughflow

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Authors: Nisha Singh, Neeru Adlakha

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Calcium signalling is one of the most important intracellular signalling mechanisms. A lot of approaches and investigators have been made in the study of calcium signalling in various cells to understand its mechanisms over recent decades. However, most of existing investigators have mainly focussed on the study of calcium signalling in various cells without paying attention to the dependence of calcium signalling on other chemical ions like inositol-1; 4; 5 triphosphate ions, etc. Some models for the independent study of calcium signalling and inositol-1; 4; 5 triphosphate signalling in various cells are present but very little attention has been paid by the researchers to study the interdependence of these two signalling processes in a cell. In this paper, we propose a coupled mathematical model to understand the interdependence of inositol-1; 4; 5 triphosphate dynamics and calcium dynamics in a myocyte cell. Such studies will provide the deeper understanding of various factors involved in calcium signalling in myocytes, which may be of great use to biomedical scientists for various medical applications.

Keywords: calcium signalling, coupling, finite difference method, inositol 1, 4, 5-triphosphate

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Authors: Rajeev Ravindran, Amit K. Jaiswal

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Waste from the food-processing industry is produced in large amount and contains high levels of lignocellulose. Due to continuous accumulation throughout the year in large quantities, it creates a major environmental problem worldwide. The chemical composition of these wastes (up to 75% of its composition is contributed by polysaccharide) makes it inexpensive raw material for the production of value-added products such as biofuel, bio-solvents, nanocrystalline cellulose and enzymes. In order to use lignocellulose as the raw material for the microbial fermentation, the substrate is subjected to enzymatic treatment, which leads to the release of reducing sugars such as glucose and xylose. However, the inherent properties of lignocellulose such as presence of lignin, pectin, acetyl groups and the presence of crystalline cellulose contribute to recalcitrance. This leads to poor sugar yields upon enzymatic hydrolysis of lignocellulose. A pre-treatment method is generally applied before enzymatic treatment of lignocellulose that essentially removes recalcitrant components in biomass through structural breakdown. Present study is carried out to find out the best pre-treatment method for the maximum liberation of reducing sugars from spent coffee waste (SPW). SPW was subjected to a range of physical, chemical and physico-chemical pre-treatment followed by a sequential, combinatorial pre-treatment strategy is also applied on to attain maximum sugar yield by combining two or more pre-treatments. All the pre-treated samples were analysed for total reducing sugar followed by identification and quantification of individual sugar by HPLC coupled with RI detector. Besides, generation of any inhibitory compounds such furfural, hydroxymethyl furfural (HMF) which can hinder microbial growth and enzyme activity is also monitored. Results showed that ultrasound treatment (31.06 mg/L) proved to be the best pre-treatment method based on total reducing content followed by dilute acid hydrolysis (10.03 mg/L) while galactose was found to be the major monosaccharide present in the pre-treated SPW. Finally, the results obtained from the study were used to design a sequential lignocellulose pre-treatment protocol to decrease the formation of enzyme inhibitors and increase sugar yield on enzymatic hydrolysis by employing cellulase-hemicellulase consortium. Sequential, combinatorial treatment was found better in terms of total reducing yield and low content of the inhibitory compounds formation, which could be due to the fact that this mode of pre-treatment combines several mild treatment methods rather than formulating a single one. It eliminates the need for a detoxification step and potential application in the valorisation of lignocellulosic food waste.

Keywords: lignocellulose, enzymatic hydrolysis, pre-treatment, ultrasound

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Authors: Alexey V. Klyuev, Arkady V. Yakimov, Mikhail I. Ryzhkin, Andrey V. Klyuev

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Fluctuations of Schottky diode parameters in a structure of the mixer are investigated. These fluctuations are manifested in two ways. At the first, they lead to fluctuations in the transfer factor that is lead to the amplitude fluctuations in the signal of intermediate frequency. On the basis of the measurement data of 1/f noise of the diode at forward current, the estimation of a spectrum of relative fluctuations in transfer factor of the mixer is executed. Current dependence of the spectrum of relative fluctuations in transfer factor of the mixer and dependence of the spectrum of relative fluctuations in transfer factor of the mixer on the amplitude of the heterodyne signal are investigated. At the second, fluctuations in parameters of the diode lead to the occurrence of 1/f noise in the output signal of the mixer. This noise limits the sensitivity of the mixer to the value of received signal.

Keywords: current-voltage characteristic, fluctuations, mixer, Schottky diode, 1/f noise

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

Procedia PDF Downloads 223

Authors: Bouras Zine Eddine, Talai Abdelouaheb

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The need to merge software artifacts seems inherent to modern software development. Distribution of development over several teams and breaking tasks into smaller, more manageable pieces are an effective means to deal with the kind of complexity. In each case, the separately developed artifacts need to be assembled as efficiently as possible into a consistent whole in which the parts still function as described. Also, earlier changes are introduced into the life cycle and easier is their management by designers. Interaction-based specifications such as UML sequence diagrams have been found effective in this regard. As a result, sequence diagrams can be used not only for capturing system behaviors but also for merging changes in order to create a new version. The objective of this paper is to suggest a new approach to deal with the problem of software merging at the level of sequence diagrams by using the concept of dependence analysis that captures, formally, all mapping and differences between elements of sequence diagrams and serves as a key concept to create a new version of sequence diagram.

Keywords: system behaviors, sequence diagram merging, dependence analysis, sequence diagram slicing

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Authors: Abdullah Eqal Al Mazrooei

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In this work, a new nonlinear model will be introduced. The model is in the state-space form. The nonlinearity of this model is in the state equation where the state vector is multiplied by its self. This technique makes our model generalizes many famous models as Lotka-Volterra model and Lorenz model which have many applications in the real life. We will apply our new model to estimate the wind speed by using a new nonlinear estimator which suitable to work with our model.

Keywords: nonlinear systems, state-space model, Kronecker product, nonlinear estimator

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Authors: N. R. Badurally Adam, S. R. Monebhurrun, M. Z. Dauhoo, A. Khoodaruth

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Transport energy demand is vital for the economic growth of any country. Globalisation and better standard of living plays an important role in transport energy demand. Recently, transport energy demand in Mauritius has increased significantly, thus leading to an abuse of natural resources and thereby contributing to global warming. Forecasting the transport energy demand is therefore important for controlling and managing the demand. In this paper, we develop a model to predict the transport energy demand. The model developed is based on a system of five stochastic differential equations (SDEs) consisting of five endogenous variables: fuel price, population, gross domestic product (GDP), number of vehicles and transport energy demand and three exogenous parameters: crude birth rate, crude death rate and labour force. An interval of seven years is used to avoid any falsification of result since Mauritius is a developing country. Data available for Mauritius from year 2003 up to 2009 are used to obtain the values of design variables by applying genetic algorithm. The model is verified and validated for 2010 to 2012 by substituting the values of coefficients obtained by GA in the model and using particle swarm optimisation (PSO) to predict the values of the exogenous parameters. This model will help to control the transport energy demand in Mauritius which will in turn foster Mauritius towards a pollution-free country and decrease our dependence on fossil fuels.

Keywords: genetic algorithm, modeling, particle swarm optimization, stochastic differential equations, transport energy demand

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Authors: Khawlh A. Alzubaidi, Khadijah B. Alziyadi, Amor M. Alsayari

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The discovery of a dilute magnetic semiconductor (DMS) in which ferromagnetism is carrier-mediated and persists above room temperature is a major step toward the implementation of spintronic devices for processing, transferring, and storing of information. Among the many types of DMS materials which have been investigated, Mn-doped GaAs has become one of the best candidates for technological application. However, despite major developments over the last few decades, the maximum Curie temperature (~200 K) remains well below room temperature. In this work, we have studied the effect of Mn content and strain on the GaMnAs effective masses of electron, heavy and light holes calculated in the different crystallographic direction. Also, the Curie temperature in the DMS GaMnAs alloy is determined. Compilation of GaMnAs band parameters have been carried out using the 8-band k.p model based on Lowdin perturbation theory where spin orbit, sp-d exchange interaction, and biaxial strain are taken into account. Our results show that effective masses, calculated along the different crystallographic directions, have a strong dependence on strain, ranging from -2% (tensile strain) to 2% (compressive strain), and Mn content increased from 1 to 5%. The Curie temperature is determined within the mean-field approach based on the Zener model.

Keywords: diluted magnetic semiconductors, k.p method, effective masses, curie temperature, strain

Procedia PDF Downloads 97