Search results for: root uptake models

Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Samuel E. Okere, Anthony E. Ataga

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Introduction: This paper evaluated the mineral compositions, disease resistance elicitors in Pleurotus ostratus (POWESMS), and Pleurotus tuber-regium water extract spent mushroom substrate (PTWESMS) on the growth, yield, and management of cassava mosaic disease. Materials and Methods: The cassava plantlet (tms 98/0505) were generated through meristem tip culture at the Tissue Culture Laboratory, National Root Crop Research Institute, Umudike before they were transferred to the screen house, University of Port Harcourt Research Farm. The minerals and elicitors contained in the two spent mushroom substrates were evaluated using standard procedures. The treatments for this investigation comprised cassava plants treated with POWESMS, PTWESMS, and untreated cassava as control, which were inoculated with viral inoculum seven days after treatment application. The experiment was laid out in a completely randomized block design with 3 replicates. The data generated were subjected to analysis of variance (ANOVA). Means were separated using Fishers Least Significant Difference at p=0.05. Results: The results obtained revealed that POWESMS contained 19.3, 0.52, and 0.1g/200g substrate of carbohydrate polymers, glycoproteins, and lipid molecules elicitors respectively while it also contained 3.17, 212.1, 17.9,21.8, 58.8 and 111.0 mg/100g substrate for N, P, K, Na, Mg and Ca respectively. Further, PTWESMS contain 1.6, 0.04, and 0.2g/200g of the substrate as carbohydrate polymers, glycoprotein, and lipid respectively; the minerals contained in this substrate were 3.4, 204.8, 8.9, 24.2, 32.2 and 105.5 mg respectively for N, P, K, Na, and Ca. There were also significant differences in the mean values of the number of storage roots, root length, fresh root weight, fresh weight plant biomass, root girth, and whole plant dry biomass, but no significant difference was recorded for harvest index. The result also revealed significant differences in mean values of disease severity index evaluated at 4, 8, 12, 16, 20, 24, and 28 weeks after inoculation (WAI). Conclusion: The aqueous extract of these spent mushrooms substrate have shown outstanding prospect in managing cassava mosaic disease and also improvement in growth and yield of cassava due to the high level of the minerals and elicitors they contain when compared with the control. However, more work is recommended, especially in understanding the mechanism of this induced resistance.

Keywords: characterization, elicitors, mosaic, mushroom

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Authors: Matthew Ocheleka Itodo, Ogo Agbo Ogo, Agnes Ogbene Abutu, Bawa Inalegwu

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Hyperlipidemia is characterised by elevated serum total cholesterol and low density and very low-density lipoprotein cholesterol and decreased high-density lipoprotein are the risk factor for coronary heart diseases. There are claims by traditional medicine practitioners in Nigeria that Moringa oleifera plants are used for the treatment of cardiovascular diseases, but it appears there is no scientific research and, publication or documented work to verify these claims. This study aimed to determine the effect of methanol root extracts of Moringa oleifera on Lipid profile, Atherogenic indices and 3 hydroxyl 3 methylglutaryl Coenzyme A reductase activity of poloxamer 407-induced hyperlipidemic rats. The animals were grouped into 8; Group 1: Normal control, Group 2: Hyperlipidemic control. Groups 2 to 8 were induced with Poloxamer 407 1000 mg/Kg body weight. However, group 3 were treated with standard drugs (atorvastatin). Group 4 was treated with crude extract, and groups 5 to 8 were treated with purified fractions from column chromatography. The preliminary antihyperlipidemic study showed Methanol root extract at 200 mg/kg body weight significantly (p≤0.05) decreased total cholesterol, low-density lipoprotein, triacylglyceride, 3 hydroxyls 3 methylglutaryl Coenzyme A reductase, and increase high-density lipoprotein of hyperlipidemic treated groups. Screening the extracts for the most potent anti-hyperlipidemic activity reveals that fraction 1 of Total Cholesterol and Fraction 3 of Triacylglyceride have the highest percentage reduction of 56% and 51%, respectively. The atherogenic risk factor of all induced treated rats shows a significant (p<0.05) decrease in levels of Castelli’s risk index II, atherogenic index of plasma and a significant (p<0.05) higher level of Castelli’s risk index I ratio. The study shows that the methanol extract of root possesses antihyperlipidemic effects and may explain why it has been found to be useful in the management of cardiovascular diseases by traditional medicine practitioners.

Keywords: hyperlipidemia, moringa oleifera, poloxamer 407, lipid profile

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Authors: Farrukh Javed, Krzysztof Podgórski

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

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

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Authors: Hashim Bashir

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The Vortex generated at the edges of the wing of an Aircraft are called the Wing Tip Vortex. The Wing Tip Vortices are associated with induced drag. The induced drag is responsible for nearly 50% of aircraft total drag and can be reduced through modifications to the wing tip. Some models displace wingtips vortices outwards diminishing the induced drag. Concerning agricultural aircrafts, wing tip vortex position is really important, while spreading products over a plantation. In this work, theoretical calculations were made in order to study the influence in aerodynamic characteristics and vortex position, over Sudanese agricultural aircraft, by the following types of wing tips: delta tip, winglet and down curved. The down curved tip was better for total drag reduction, but not good referring to vortex position. The delta tip gave moderate improvement on aerodynamic characteristic and on vortex position. The winglet had a better vortex position and lift increment, but caused an undesirable result referring to the wing root bending moment. However, winglet showed better development potential for agricultural aircraft.

Keywords: wing tip device, wing tip vortice, agricultural aircaft, winglet

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Authors: Kgabo Pofu, Hintsa Araya, Dean Oelofse, Sonja Venter, Christian Du Plooy, Phatu Mashela

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Nematode resistance to the tropical root-knot (Meloidogyne species) nematodes is one of the most preferred nematode management strategies in development of smallholder resource-poor farming systems. Due to its pharmacological and ethnomedicinal applications, Artemisia annua is one of the underutilised crops that have attracted attention of policy-makers in rural agrarian development in South Africa. However, the successful introduction of this crop in smallholder resource-poor farming systems could be upset by the widespread aggressive Meloidogyne species, which have limited management options. The objective of this study therefore was to determine the degree of nematode resistance to the South African M. incognita and M. javanica population densities on A. annua seedlings. Uniform three-week-old seedlings in pots containing pasteurised growing medium under greenhouse conditions were inoculated using a series of eggs and second-stage juveniles of two Meloidogyne species in separate trials. At 56 days after inoculation, treatments were highly significant on reproductive factor (RF) for M. incognita and M. javanica on A. annua, contributing 87 and 89% in total treatment variation of the variables, respectively. At all levels of inoculation, RF values for M. incognita (0.17-0.79) and M. javanica (0.02-0.29) were below unity, without any noticeable root galls. Infection of A. annua by both Meloidogyne species had no significant effects on growth variables. In conclusion, A. annua seedlings are resistant to the South African M. incognita and M. javanica population densities and could therefore be explored further for use in smallholder resource-poor farming systems.

Keywords: ethnomedicial plants, medicinal plants, underutilised crops, plant parasitic nematodes

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Authors: Laura Mclean

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A recurring point of interest in computational phylogenetic analysis of Indo-European family trees is the inference of a Germano-Italo-Celtic clade in some versions of the trees produced. The presence of this clade in the models is intriguing as there is little evidence for innovations shared among Germanic, Italic, and Celtic, the evidence generally used in the traditional method to construct a subgroup. One source of this unexpected outcome could be the input to the models. The datasets in the various models used so far, for the most part, take as their basis the Swadesh list, a list compiled by Morris Swadesh and then revised several times, containing up to 207 words that he believed were resistant to change among languages. The judgments made by Swadesh for this list, however, were subjective and based on his intuition rather than rigorous analysis. Some scholars used the Swadesh 200 list as the basis for their Indo-European dataset and made cognacy judgements for each of the words on the list. Another dataset is largely based on the Swadesh 207 list as well although the authors include additional lexical and non-lexical data, and they implement ‘split coding’ to deal with cases of polymorphic characters. A different team of scholars uses a different dataset, IECoR, which combines several different lists, one of which is the Swadesh 200 list. In fact, the Swadesh list is used in some form in every study surveyed and each dataset has three words that, when they are coded as cognates, seemingly contribute to the inference of a Germano-Italo-Celtic clade which could happen due to these clades sharing three words among only themselves. These three words are ‘fish’, ‘flower’, and ‘man’ (in the case of ‘man’, one dataset includes Lithuanian in the cognacy coding and removes the word ‘man’ from the screened data). This collection of cognates shared among Germanic, Italic, and Celtic that were deemed important enough to be included on the Swadesh list, without the ability to account for possible reasons for shared cognates that are not shared innovations, gives an impression of affinity between the Germanic, Celtic, and Italic branches without adequate methodological support. However, by changing how cognacy is defined (ie. root cognates, borrowings vs inherited cognates etc.), we will be able to identify whether these three cognates are significant enough to infer a clade for Germanic, Celtic, and Italic. This paper examines the question of what definition of cognacy should be used for phylogenetic datasets by examining the Germano-Italo-Celtic clade as a case study and offers insights into the reconstruction of a Germano-Italo-Celtic clade.

Keywords: historical, computational, Italo-Celtic, Germanic

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Authors: Minttu Laukkanen, Janne Huiskonen

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This study investigates the sharing economy business models as examples of the sustainable business models. The aim is to contribute to the limited literature on sharing economy in connection with sustainable business models by explaining sharing economy business models value capturing. Specifically, this research answers the following question: How business model choices affect captured sustainable value? A multiple case study approach is applied in this study. Twenty different successful sharing economy business models focusing on consumer business and covering four main areas, accommodation, mobility, food, and consumer goods, are selected for analysis. The secondary data available on companies’ websites, previous research, reports, and other public documents are used. All twenty cases are analyzed through the sharing economy business model framework and sustainable value analysis framework using qualitative data analysis. This study represents general sharing economy business model value attributes and their specifications, i.e. sustainable value propositions for different stakeholders, and further explains the sustainability impacts of different sharing economy business models through captured and uncaptured value. In conclusion, this study represents how business model choices affect sustainable value capturing through eight business model attributes identified in this study. This paper contributes to the research on sustainable business models and sharing economy by examining how business model choices affect captured sustainable value. This study highlights the importance of careful business model and sustainability impacts analyses including the triple bottom line, multiple stakeholders and value captured and uncaptured perspectives as well as sustainability trade-offs. It is not self-evident that sharing economy business models advance sustainability, and business model choices does matter.

Keywords: sharing economy, sustainable business model innovation, sustainable value, value capturing

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Authors: Manoj Reghu, Prabhu Rajagopal, C. V. Krishnamurthy, Krishnan Balasubramaniam

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A thorough understanding of guided ultrasonic wave behavior in structures is essential for the application of existing Non Destructive Evaluation (NDE) technologies, as well as for the development of new methods. However, the analysis of guided wave phenomena is challenging because of their complex dispersive and multimodal nature. Although numerical solution procedures have proven to be very useful in this regard, the increasing complexity of features and defects to be considered, as well as the desire to improve the accuracy of inspection often imposes a large computational cost. Hybrid models that combine numerical solutions for wave scattering with faster alternative methods for wave propagation have long been considered as a solution to this problem. However usually such models require modification of the base code of the solution procedure. Here we aim to develop Generic Hybrid models that can be directly applied to any two different solution procedures. With this goal in mind, a Numerical Hybrid model and an Analytical-Numerical Hybrid model has been developed. The concept and implementation of these Hybrid models are discussed in this paper.

Keywords: guided ultrasonic waves, Finite Element Method (FEM), Hybrid model

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Authors: Ibrahim Elnour Abdelrahman Eltayeb

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Computational modelling is a method used to investigate joint forces during a movement. It can get high accuracy in the joint forces via subject-specific models. However, the construction of subject-specific models remains time-consuming and expensive. The purpose of this paper was to identify what alterations we can make to generic computational models to get a better estimation of the joint forces. It appraised the impact of these alterations on the accuracy of the estimated joint forces. It found different strategies of alterations: joint model, muscle model, and an optimisation problem. All these alterations affected joint contact force accuracy, so showing the potential for improving the model predictions without involving costly and time-consuming medical images.

Keywords: joint force, joint model, optimisation problem, validation

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Authors: Leah Wright, Trevor Townsend

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Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

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Authors: A. Nabhan, Mohamed R. El-Sharkawy, A. Rashed

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The main aim of this paper is to dedicate the belt drive system faults like cogs missing, misalignment and belt worm using vibration analysis technique. Experimentally, the belt drive test-rig is equipped to measure vibrations signals under different operating conditions. Finite element 3D model of belt drive system is created and vibration response analyzed using commercial finite element software ABAQUS/CAE.  Root mean square (RMS) and Crest Factor will serve as indicators of average amplitude of envelope analysis signals. The vibration signals pattern obtained from the simulation model and experimental data have the same characteristics. It can be concluded that each case of the RMS is more effective in detecting the defect for acceleration response. While Crest Factor parameter has a response with the displacement and velocity of vibration signals. Also it can be noticed that the model has difficulty in completing the solution when the misalignment angle is higher than 1 degree.

Keywords: simulation model, misalignment, cogs missing, vibration analysis

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Authors: H. Zormati, J. Chebil, J. Bel Hadj Tahar

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Next generation wireless transmission technology (5G) is expected to support the development of channel models for higher frequency bands, so clarification of high frequency bands is the most important issue in radio propagation research for 5G, multiple urban microcellular measurements have been carried out at 60 GHz. In this paper, the collected data is uniformly analyzed with focus on the path loss (PL), the objective is to compare simulation results of some studied channel models with the purpose of testing the performance of each one.

Keywords: 5G, channel model, 60GHz channel, millimeter-wave, urban microcell

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Authors: Anjani Kumar Tiwari, Neelam Kumari, Anil Mishra

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The 18-kDa translocator protein (TSPO) previously called as peripheral benzodiazepine receptor, is proven biomarker for variety of neuroinflammation. TSPO is tryptophane rich five transmembranal protein found on outer mitochondrial membrane of steroid synthesising and immunomodulatory cells. In case of neuronal damage or inflammation the expression level of TSPO get upregulated as an immunomodulatory response. By utilizing Benzoxazolone as a basic scaffold, series of TSPO ligands have been designed followed by their screening through in silico studies. Synthesis has been planned by employing convergent methodology in six high yielding steps. For the synthesized ligands the ‘in vitro’ assay was performed to determine the binding affinity in term of Ki. On ischemic rat brain, autoradiography studies were also carried to check the specificity and affinity of the designed radiolabelled ligand for TSPO.Screening was performed on the basis of GScore of CADD based schrodinger software. All the modified and better prospective compound were successfully carried out and characterized by spectroscopic techniques (FTIR, NMR and HRMS). In vitro binding assay showed best binding affinity Ki = 6.1+ 0.3 for TSPO over central benzodiazepine receptor (CBR) Ki > 200. ARG studies indicated higher uptake of two analogues on the lesion side compared with that on the non-lesion side of ischemic rat brains. Displacement experiments with unlabelled ligand had minimized the difference in uptake between the two sides which indicates the specificity of the ligand towards TSPO receptor.

Keywords: TSPO, PET, imaging, Acetamidobenzoxazolone

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Authors: Tasir Khan, Ishfaq Ahmad, Yejuan Wang, Muhammad Salam

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Distribution models of the wind speed data are essential to assess the potential wind speed energy because it decreases the uncertainty to estimate wind energy output. Therefore, before performing a detailed potential energy analysis, the precise distribution model for data relating to wind speed must be found. In this research, material from numerous criteria goodness-of-fits, such as Kolmogorov Simonov, Anderson Darling statistics, Chi-Square, root mean square error (RMSE), AIC and BIC were combined finally to determine the wind speed of the best-fitted distribution. The suggested method collectively makes each criterion. This method was useful in a circumstance to fitting 14 distribution models statistically with the data of wind speed together at four sites in Pakistan. The consequences show that this method provides the best source for selecting the most suitable wind speed statistical distribution. Also, the graphical representation is consistent with the analytical results. This research presents three estimation methods that can be used to calculate the different distributions used to estimate the wind. In the suggested MLM, MOM, and MLE the third-order moment used in the wind energy formula is a key function because it makes an important contribution to the precise estimate of wind energy. In order to prove the presence of the suggested MOM, it was compared with well-known estimation methods, such as the method of linear moment, and maximum likelihood estimate. In the relative analysis, given to several goodness-of-fit, the presentation of the considered techniques is estimated on the actual wind speed evaluated in different time periods. The results obtained show that MOM certainly provides a more precise estimation than other familiar approaches in terms of estimating wind energy based on the fourteen distributions. Therefore, MOM can be used as a better technique for assessing wind energy.

Keywords: wind-speed modeling, goodness of fit, maximum likelihood method, linear moment

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Authors: Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

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Emerging Markets return distributions have shown significance departure from normality were they are characterized by fatter tails relative to the normal distribution and exhibit levels of skewness and kurtosis that constitute a significant departure from normality. Therefore, the classical Markowitz Mean-Variance is not applicable for emerging markets since it assumes normally-distributed returns (with zero skewness and kurtosis) and a quadratic utility function. Moreover, the Markowitz mean-variance analysis can be used in cases of moderate non-normality and it still provides a good approximation of the expected utility, but it may be ineffective under large departure from normality. Higher moments models and median models have been suggested in the literature for asset allocation in this case. Higher moments models have been introduced to account for the insufficiency of the description of a portfolio by only its first two moments while the median model has been introduced as a robust statistic which is less affected by outliers than the mean. Tail risk measures such as Value-at Risk (VaR) and Conditional Value-at-Risk (CVaR) have been introduced instead of Variance to capture the effect of risk. In this research, higher moment models including the Mean-Variance-Skewness (MVS) and Mean-Variance-Skewness-Kurtosis (MVSK) are formulated as single-objective non-linear programming problems (NLP) and median models including the Median-Value at Risk (MedVaR) and Median-Mean Absolute Deviation (MedMAD) are formulated as a single-objective mixed-integer linear programming (MILP) problems. The higher moment models and median models are compared to some benchmark portfolios and tested on real financial data in the Egyptian main Index EGX30. The results show that all the median models outperform the higher moment models were they provide higher final wealth for the investor over the entire period of study. In addition, the results have confirmed the inapplicability of the classical Markowitz Mean-Variance to the Egyptian stock market as it resulted in very low realized profits.

Keywords: Egyptian stock exchange, emerging markets, higher moment models, median models, mixed-integer linear programming, non-linear programming

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Authors: Celina Pestano-Gabino, Concepcion Gonzalez-Concepcion, M. Candelaria Gil-Fariña

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Some estimation methods for VARMA models, and Multivariate Time Series Models in general, rely on the use of a Hankel matrix. It is known that if the data sample is populous enough and the dimension of the Hankel matrix is unnecessarily large, this may result in an unnecessary number of computations as well as in numerical problems. In this sense, the aim of this paper is two-fold. First, we provide some theoretical results for these matrices which translate into a lower dimension for the matrices normally used in the algorithms. This contribution thus serves to improve those methods from a numerical and, presumably, statistical point of view. Second, we have chosen an estimation algorithm to illustrate in practice our improvements. The results we obtained in a simulation of VARMA models show that an increase in the size of the Hankel matrix beyond the theoretical bound proposed as valid does not necessarily lead to improved practical results. Therefore, for future research, we propose conducting similar studies using any of the linear system estimation methods that depend on Hankel matrices.

Keywords: covariances Hankel matrices, Kronecker indices, system identification, VARMA models

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Authors: Raphael Naryongo, Philip Ngare, Anthony Waititu

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This paper deals with numerical simulation of Wishart processes for a single asset risky pricing model whose volatility is described by Wishart affine diffusion processes. The multi-factor specification of volatility will make the model more flexible enough to fit the stock market data for short or long maturities for better returns. The Wishart process is a stochastic process which is a positive semi-definite matrix-valued generalization of the square root process. The aim of the study is to model the log asset stock returns under the double Wishart stochastic volatility model. The solution of the log-asset return dynamics for Bi-Wishart processes will be obtained through Euler-Maruyama discretization schemes. The numerical results on the asset returns are compared to the existing models returns such as Heston stochastic volatility model and double Heston stochastic volatility model

Keywords: euler schemes, log-asset return, infinitesimal generator, wishart diffusion affine processes

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Authors: Nighat Zia-ud-Den, Shazia Anwer Bukhari

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In the present study, sunflower seeds were exposed to magnetic bio-stimulation at different milli Tesla, and their effects were studied. The present study addressed to establish the effectiveness of magnetic bio-stimulation on seed germination, growth, and other dynamics of crop growth. The changes in physiological characters, i.e. the growth parameters of seedlings (biomass, root and shoot length, fresh and dry weight of root shoot leaf and fruit, leaf area, the height of plants, number of leaves, and number of fruits per plant) and antioxidant activities were measured. The parameters related to germination and growth were measured under controlled conditions while they changed significantly compared with that of the control. These changes suggested that magnetic seed stimulator enhanced the inner energy of seeds, which contributed to the acceleration of the growth and development of seedlings. Moreover, pretreatment with a magnetic field was found to be a positive impact on sunflower seeds germination, growth, and other biochemical parameters.

Keywords: sunflower seeds, physical priming method, biochemical parameters, antioxidant activities

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Authors: I. Sagaama, A. Kechiche, W. Trojet, F. Kamoun

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Replacing combustion engine vehicles by electric vehicles (EVs) is a major step in recent years due to their potential benefits. Battery autonomy and charging processes are still a big issue for that kind of vehicles. Therefore, reducing the energy consumption of electric vehicles becomes a necessity. Many researches target introducing recent information and communication technologies in EVs in order to propose reducing energy consumption services. Evaluation of realistic scenarios is a big challenge nowadays. In this paper, we will elaborate a state of the art of different proposed energy consumption models in the literature, then we will present a comparative study of these models, finally, we will extend previous works in order to propose an accurate and realistic energy model for calculating instantaneous power consumption of electric vehicles.

Keywords: electric vehicle, vehicular networks, energy models, traffic simulation

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Authors: Julio Manuel De Luis Ruiz, Javier Sedano Cibrián, RubéN Pérez Álvarez, Raúl Pereda García, Felipe Piña García

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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In this sense, the classic 3D models are being applied to investigate the direction towards which the generally subterranean structures of an archaeological site may continue and therefore, to help in making the decisions that define the location of new excavations. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimise the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain).

Keywords: process optimization, RGB models, thermal models, , UAV, workflow

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Authors: Rabi Mouhcine, Amrouch Mustapha, Mahani Zouhir, Mammass Driss

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In this paper, we present a system for offline recognition cursive Arabic handwritten text based on Hidden Markov Models (HMMs). The system is analytical without explicit segmentation used embedded training to perform and enhance the character models. Extraction features preceded by baseline estimation are statistical and geometric to integrate both the peculiarities of the text and the pixel distribution characteristics in the word image. These features are modelled using hidden Markov models and trained by embedded training. The experiments on images of the benchmark IFN/ENIT database show that the proposed system improves recognition.

Keywords: recognition, handwriting, Arabic text, HMMs, embedded training

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Authors: Hong Li, Tingxian Li, Xudong Wang, Weibo Yang

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Co-limitation of iron (Fe) deficiency in legume nitrogen fixation process is not well understood. Our objectives were to examine how peanut plants cope with Fe deficiency with the rhizobial inoculants and N-nutrient treatments. The study was conducted in the tropical Hainan Island during 2012-2013. The soil was strongly acidic (pH 4.6±0.7) and deficient in Fe (9.2±2.3 mg/kg). Peanut plants were intercropped with cassava. The inoculants and N treatments were arranged in a split-plot design with three blocks. Peanut root nodulation, stem allantoin, amino acids and plant N derived from fixation (P) reduced with declining soil Fe concentrations. The treatment interactions were significant on relative ureide % and peanut yields (P<0.05). Residual fixed N from peanut plants was beneficial to cassava plants. It was concluded that co-variance of Fe deficiency could influence peanut N fixation efficiency and rhizobia and N inputs could help improving peanut tolerance to Fe deficiency stress.

Keywords: amino acids, plant N derived from N fixation, root nodulation, soil Fe co-variance, stem ureide, peanuts, cassava

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Authors: Farah Ali, Tehreem Fiayyaz, Laeeq Akbar Lodhi, Imran Mirza

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The present work was undertaken to investigate effects of various extracts of W. somnifera (WS) for anti-diabetic activity in alloxan induced diabetic rabbits. Animals were divided into nine groups of six rabbits each. The animals of group 1 and 2 were given lactose (250 mg/kg, p.o) and WS root powder (100 mg/kg, p.o) respectively daily from day 1-20. Animals of group 3 were given alloxan (100 mg/kg, i.v) as a single dose on day 1. Powdered root of WS in the doses of 100, 150, 200 mg/kg and its aqueous (AWS) and ethanol extracts (EWS) (equivalent to 200 mg/kg of crude drug) were given to the treated animals (groups 4-8), respectively orally for three weeks (day 1-20 o.d), along with alloxan (100 mg/kg, i.v) as a single dose on day 1. Group 9 was given metformin (200 mg/kg) daily from day 1-20, along with a single dose of alloxan (100 mg/ kg, i.v) on day 1. Fasting serum glucose concentration in groups 3-9 was increased significantly (p<0.05) on day 3 as compared to normal control (NC) group (1). WS (100, 150, 200 mg/kg, p.o) decreased the fasting serum glucose concentration, with a maximum decrease (88.3 mg/dl) in group 2 (treated control) on day 21 of the experiment. These results indicate that metformin (reference control), (AWS) and (EWS) significantly antagonized the diabetic effects of alloxan.

Keywords: diabetes, serum, glucose, blood, sugar, rabbits

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Authors: Nisha Khatik, Ramesh Joshi

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An in vitro plant regeneration system was developed via direct somatic embryogenesis from different seedling explants of an important medicinal plant Murraya koenigii (L) Spreng. Cotyledons (COT), Hypocotyle (HYP)(10 to 15 mm) and Root (RT) segments (10 to 20 mm) were excised from 60 days old seedlings as explants. The somatic embryos induction was achieved on MS basal medium augmented with different concentrations of BAP 1.33 to 8.40 µM and TDZ 1.08 to 9.82 µM. The globular embryos originated from cut ends and entire surface of the root, hypocotyle explants and margins of cotyledons within 30-40days. The percentage of somatic embryos induction per explant was significantly higher in HYP explants (94.21±5.77%) in the MS basal medium supplemented with 6.20 µM BAP and 8.64 µM TDZ. The highest rate of conversion of torpedo, heart and cotyledonary stages from globular stage was obtained in MS medium supplemented with 8.64 µM TDZ. The matured somatic embryos were transferred to the MS basal medium without PGRs. Highest 88% of the matured embryos were germinated on transfer to the PGR free medium where they grew for a further 3-4 weeks. Out of seventy six hardened plants seventy (92%) plantlets were found healthy under field conditions.

Keywords: Murraya koenigii, somatic embryogenesis, thidiazuron, regeneration, rutaceae

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Authors: Arcady Ponosov

Abstract:

Many well-known age-structured population models are derived from the celebrated McKendrick-von Foerster equation (MFE), also called the biological conservation law. A similar technique is suggested for the stochastically perturbed MFE. This technique is shown to produce stochastic versions of the deterministic population models, which appear to be very different from those one can construct by simply appending additive stochasticity to deterministic equations. In particular, it is shown that stochastic Nicholson’s blowflies model should contain both additive and multiplicative stochastic noises. The suggested transformation technique is similar to that used in the deterministic case. The difference is hidden in the formulas for the exact solutions of the simplified boundary value problem for the stochastically perturbed MFE. The analysis is also based on the theory of stochastic delay differential equations.

Keywords: boundary value problems, population models, stochastic delay differential equations, stochastic partial differential equation

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Authors: Rami El-Hajj Mohamad, Mahmoud Skafi, Ali Massoud Haidar

Abstract:

Several meteorological parameters were used for the prediction of monthly average daily global solar radiation on horizontal using recurrent neural networks (RNNs). Climatological data and measures, mainly air temperature, humidity, sunshine duration, and wind speed between 1995 and 2007 were used to design and validate a feed forward and recurrent neural network based prediction systems. In this paper we present our reference system based on a feed-forward multilayer perceptron (MLP) as well as the proposed approach based on an RNN model. The obtained results were promising and comparable to those obtained by other existing empirical and neural models. The experimental results showed the advantage of RNNs over simple MLPs when we deal with time series solar radiation predictions based on daily climatological data.

Keywords: recurrent neural networks, global solar radiation, multi-layer perceptron, gradient, root mean square error

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Authors: Ruth Nsibirano

Abstract:

Online mode of delivery in higher institutions of learning, popularly known in some circles as e-Learning or distance education is a new phenomenon that is steadily taking root in African universities but specifically at Makerere University. For slightly over a decade, the Department of Open and Distance Learning has been offering the first generation mode of distance education. In this, learning and teaching experiences were based on the use of hard copy materials circulated through postal services in a rather correspondence mode. There were more challenges to this including high dropout rates, limited support to the learners and sustainability issues. Fortunately, the Department was supported by the Norwegian Government through a NORHED grant to “leapfrog” to the fifth generation of distance education that makes more use of educational technologies and tools. The capacity of faculty staff was gradually enhanced through a series of training to handle the upgraded structure of fifth generation distance education. The trained staff was then tasked to develop modules befitting an online delivery mode, for use on the program. This paper will present attitudes, experiences of the course writers with a view of sharing the good practices that enabled them leap from e-faculty trainees to distinct online course writers. This perspective will hopefully serve as building blocks to enhance the capacity of other upcoming distance education programs in low capacity universities and also promote the uptake of e-Education on the continent and beyond. Methodologically the findings were collected through individual interviews with the 30 course writers. In addition, semi structured questionnaires were designed to collect data on the profile, challenges and lessons from the writers. Findings show that the attitudes of course writers on project supported activities are so much tagged to the returns from their committed efforts. In conclusion, therefore, it is strategically useful to assess and selectively choose which individual to nominate for involvement at the initial stages.

Keywords: distance education, online course content, staff attitudes, best practices in online learning

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Authors: Emily J. Morey, Kevin Galvin, Thomas Riley, R. Eddie Wilson

Abstract:

The key challenges faced by integrating autonomous rail operations into the existing mainline railway environment have been identified through the understanding and framing of the problem space and stakeholder analysis. This was achieved through the completion of the first four steps of Soft Systems Methodology, where the problem space has been expressed via conceptual models. Having identified these challenges, we investigated one of them, namely capacity, via the use of models and simulation. This paper examines the approach used to move from the conceptual models to a simulation which can determine whether the integration of autonomous trains can plausibly increase capacity. Within this approach, we developed an architecture and converted logical models into physical resource models and associated design features which were used to build a simulator. From this simulator, we are able to analyse mixtures of legacy-autonomous operations and produce fundamental diagrams and trajectory plots to describe the dynamic behaviour of mixed mainline railway operations.

Keywords: autonomy, executable architecture, modelling and simulation, railway capacity

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Authors: Rebecca Hafner, Daniel Read, David Elmes

Abstract:

The persuasive potential of normative and feedback (financial vs. environmental) information in ‘nudging’ people towards making environmentally sound decisions was explored in a hypothetical choice experiment. The research was specifically focused on determining how subtle variations in the decision frame could be used to increase the selection of energy efficient vs. standard technologies, using the context of home heating choice. Participants were given a choice of a standard heating system (a gas boiler) and a relatively more-energy efficient option (a heat pump). The experiment had a 2 (normative vs. no normative information) by 3 feedback type (financial, environmental, none) design. The last group constituted the control. Half of the participants were given normative information about what the majority of others in their neighbourhood had opted to do when faced with the same choice set, prior to making their decision. The other half received no such information. Varying feedback frames were incorporated by providing participants with information on either financial or environmental savings that could be achieved by choosing the heat pump. No such information was provided in the control group. A significant interaction was found between normative information and feedback frame type. Specifically, the impact of feedback frames was found to be reduced when normative information was provided; illustrating the overriding influence of normative information on option preference. Participants were significantly more likely to select the heat pump if they were vs. were not given normative information. Yet when no normative information was provided, the persuasive influence of the financial frame was increased – highlighting this as an effective means of encouraging uptake of new technologies in this instance. Conversely, the environmental frame was not found to differ significantly from the control. Marginal carryover effects were also found for stated future real-life decision-making behaviour, with participants who were versus were not given normative information being marginally more likely to state they would consider installing a heat pump when they next need to replace their heating system in real life. We conclude that normative and financial feedback framing techniques are highly effective in increasing uptake of new, energy efficient heating technologies involving significant upfront financial outlay. The implications for researchers looking to promote ‘green’ choice in the context of new technology adoption are discussed.

Keywords: energy-efficient technology adoption, environmental decision making, financial vs. environmental feedback framing techniques, social norms

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