Search results for: empirical marker method

Authors: Somayeh Akrami, Habib Onsori, Elham Tahmassebian

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Species of Anemone narcissiflora is belonged to Anemone genus of Ranunculaceae family. This species has two subspecies named narcissiflora and willdenowii which the latest is recorded in Iran in 2010. Some samples of A. narcissiflora is gathered from kuhkamar-zonouz region of East -Azerbaijan province, Iran to study the genetic diversity of the species by using RAPD molecular markers, and estimation of genetic diversity were evaluated with the using 10mer RAPD primers by PCR-RAPD method. 39 polymorphic bands were produced from the six primers used in this technique that the maximum band is related to the RP1 primer, the lowest band is related to the RP7 and the average band for all primers were 6.5 polymorphic bands. Cluster analysis of samples in done by UPGMA method in NTSYSpc 2.02 software. Dendrogram resulting from migrating bands showed that the studied samples can be divided into two groups. The first group includes samples with 1-2 flowers and the second group consists of two sub-groups which the first subgroup consists of samples with 3-5 flowers, and the second subgroup consists of samples with 6-7 flowers. The results of the comparison and analysis of the data obtained from RAPD technique and similarity matrix represents the genetic variation between collected samples. This study shows that RAPD markers can determine the polymorphisms between different genotypes of A. narcissiflora and their hybrids. So RAPD technique can serve as a suitable molecular method to determine the genetic diversity of samples.

Keywords: Anemone narcissiflora, genetic diversity, RAPD-PCR

Procedia PDF Downloads 450

Authors: Mashood C., Abdul Vahid K., Ashique C. K.

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The technology is growing beyond human expectation. Internet is one of very sophisticated product of the information technology. It has various advantages like connecting the world, simplifying the difficult tasks done in past etc. Simultaneously it has demerits also; that is lack of authenticity and internet addiction. To find out the problems of internet addiction, a study conducted among the Postgraduate students of Pondicherry University and collected 454 samples. The study strictly focused to identify the internet addiction among students, influence and interdependence of personality on internet addiction among first years and second years. To evaluate this, we used two major analysis, these are Confirmatory Factor Analysis (CFA) to predict the internet addiction with the observed data and Logistic Regression to identify the difference between first years and second years in the case of internet addiction. Before applying to the core analysis, the data applied to some preliminary tests to check the model fit. The empirical findings shows that , the students of Pondicherry University are very much addicted to the internet, But there is no such huge difference between first years and second years in case of internet addiction.

Keywords: internet addiction, students, Pondicherry University, empirical study

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Authors: K. A. Tharanga, K. H. H. Damayanthi

Abstract:

Perception is an epistemological concept discussed in Philosophy. Perception, in other word, vision, is one of the ways that human beings get empirical knowledge after five senses. However, we face innumerable problems when achieving knowledge from perception, and therefore the knowledge gained through perception is uncertain. what we see in the external world is not real. These are the major issues that we face when receiving knowledge through perception. Sometimes there is no physical existence of what we really see. In such cases, the perception is relative. The following frames will be taken into consideration when perception is analyzed illusions and delusions, the figure of a physical object, appearance and the reality of a physical object, time factor, and colour of a physical object.seeing and knowing become vary according to the above conceptual frames. We cannot come to a proper conclusion of what we see in the empirical world. Because the things that we see are not really there. Hence the scientific knowledge which is gained from observation is doubtful. All the factors discussed in science remain in the physical world. There is a leap from ones existence to the existence of a world outside his/her mind. Indeed, one can suppose that what he/she takes to be real is just anmassive deception. However, depending on the above facts, if someone begins to doubt about the whole world, it is unavoidable to become his/her view a scepticism or nihilism. This is a certain reality.

Keywords: empirical, perception, sceptisism, nihilism

Procedia PDF Downloads 64

Authors: Jehad Al Dallal

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The design of the internal relationships among object-oriented class members (i.e., attributes and methods) and the external relationships among classes affects the overall quality of the object-oriented software. The degree of relatedness among class members is referred to as class cohesion and the degree to which a class is related to other classes is called class coupling. Well designed classes are expected to exhibit high cohesion and low coupling values. In this paper, using classes of three open-source Java systems, we empirically investigate the relation between class cohesion and coupling. In the empirical study, five lack-of-cohesion metrics and eight coupling metrics are considered. The empirical study results show that class cohesion and coupling internal quality attributes are inversely correlated. The strength of the correlation highly depends on the cohesion and coupling measurement approaches.

Keywords: class cohesion measure, class coupling measure, object-oriented class, software quality

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Authors: Naso Isaiah Thanavisuth

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Medical cannabis can be used for treatment including pain, multiple sclerosis, Parkinson's disease, and cancer. However, medical cannabis leads to adverse effects (AEs), which is delta-9-tetrahydrocannabinol (THC). In previous studies, the major of THC metabolism enzymes are CYP2C9. Especially, the variation of CYP2C9 gene consist of CYP2C9*2 on exon 3 and CYP2C9*3 on exon 7 to decrease enzyme activity. Notwithstanding, there is no data describing whether the variant of CYP2C9 genes are apharmacogenetics marker for the prediction of THC-induced AEs in Thai patients. We want to investigate the association between CYP2C9 gene and THC-induced AEs in Thai patients. We enrolled 39 Thai patients with medical cannabis treatment who were classified by clinical data. The CYP2C9*2 and *3 genotyping were conducted using the TaqMan real time PCR assay. All Thai patients who received the medical cannabis consist of twenty-four (61.54%) patients were female, and fifteen (38.46%) were male, with age range 27- 87 years. Moreover, the most AEs in Thai patients who were treated with medical cannabis between cases and controls were tachycardia, arrhythmia, dry mouth, and nausea. Particularly, thirteen (72.22%) medical cannabis-induced AEs were female and age range 33 – 69 years. In this study, none of the medical cannabis groups carried CYP2C9*2 variants in Thai patients. The CYP2C9*3 variants (*1/*3, intermediate metabolizer, IM) and (*3/*3, poor metabolizer, PM) were found, three of thirty-nine (7.69%) and one of thirty-nine (2.56%), respectively. Although, our results indicate that there is no found the CYP2C9*2. However, the variation of CYP2C9 allele might serve as a pharmacogenetics marker for screening before initiating the therapy with medical cannabis for the prevention of medical cannabis-induced AEs.

Keywords: CYP2C9, medical cannabis, adverse effects, THC, P450

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Authors: Wajih Abbassi, Zouhaier Ben Khelifa

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The present research points towards the empirical validation of three options valuation models, the ad-hoc Black-Scholes model as proposed by Berkowitz (2001), the constant elasticity of variance model of Cox and Ross (1976) and the Kou jump-diffusion model (2002). Our empirical analysis has been conducted on a sample of 26,974 options written on three indexes, the S&P 500, Nasdaq 100 and the Russell 2000 that were negotiated during the year 2007 just before the sub-prime crisis. We start by presenting the theoretical foundations of the models of interest. Then we use the technique of trust-region-reflective algorithm to estimate the structural parameters of these models from cross-section of option prices. The empirical analysis shows the superiority of the Kou jump-diffusion model. This superiority arises from the ability of this model to portray the behavior of market participants and to be closest to the true distribution that characterizes the evolution of these indices. Indeed the double-exponential distribution covers three interesting properties that are: the leptokurtic feature, the memory less property and the psychological aspect of market participants. Numerous empirical studies have shown that markets tend to have both overreaction and under reaction over good and bad news respectively. Despite of these advantages there are not many empirical studies based on this model partly because probability distribution and option valuation formula are rather complicated. This paper is the first to have used the technique of nonlinear curve-fitting through the trust-region-reflective algorithm and cross-section options to estimate the structural parameters of the Kou jump-diffusion model.

Keywords: jump-diffusion process, Kou model, Leptokurtic feature, trust-region-reflective algorithm, US index options

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Authors: Bita Mashayekhi, Mohammad Ara

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The purpose of this study is to provide some empirical evidence about implementing Activity-Based Costing (ABC) in the hospitality industry in Iran. For this purpose, we consider the Tabriz International Hotel as our sample hotel and then gather the relevant data from its cost accounting system in 2012. Then, we use ABC as our costing method and compare the cost of each service unit with that cost which had been extracted for the traditional costing method. The results show a different cost per unit for two methods. Also, because of its more precise and detailed provided information, an ABC system facilitates the decision-making process for managers on decisions related to profitability analysis, budgeting, pricing, and so on.

Keywords: Activity-Based Costing (ABC), activity, cost driver, hospitality industry

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Authors: Hala Alshamlan, Ghada Badr, Yousef Alohali

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Cancer is one of the dreadful diseases, which causes considerable death rate in humans. DNA microarray-based gene expression profiling has been emerged as an efficient technique for cancer classification, as well as for diagnosis, prognosis, and treatment purposes. In recent years, a DNA microarray technique has gained more attraction in both scientific and in industrial fields. It is important to determine the informative genes that cause cancer to improve early cancer diagnosis and to give effective chemotherapy treatment. In order to gain deep insight into the cancer classification problem, it is necessary to take a closer look at the proposed gene selection methods. We believe that they should be an integral preprocessing step for cancer classification. Furthermore, finding an accurate gene selection method is a very significant issue in a cancer classification area because it reduces the dimensionality of microarray dataset and selects informative genes. In this paper, we classify and review the state-of-art gene selection methods. We proceed by evaluating the performance of each gene selection approach based on their classification accuracy and number of informative genes. In our evaluation, we will use four benchmark microarray datasets for the cancer diagnosis (leukemia, colon, lung, and prostate). In addition, we compare the performance of gene selection method to investigate the effective gene selection method that has the ability to identify a small set of marker genes, and ensure high cancer classification accuracy. To the best of our knowledge, this is the first attempt to compare gene selection approaches for cancer classification using microarray gene expression profile.

Keywords: gene selection, feature selection, cancer classification, microarray, gene expression profile

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Authors: Chaudhuri Manoj Kumar Swain, Susmita Das

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This paper explores a detailed procedure of predicting a path loss (PL) model and its application in estimating the coverage probability in a WiMAX network. For this a hybrid approach is followed in predicting an empirical PL model of a 2.65 GHz WiMAX network deployed in a suburban environment. Data collection, statistical analysis, and regression analysis are the phases of operations incorporated in this approach and the importance of each of these phases has been discussed properly. The procedure of collecting data such as received signal strength indicator (RSSI) through experimental set up is demonstrated. From the collected data set, empirical PL and RSSI models are predicted with regression technique. Furthermore, with the aid of the predicted PL model, essential parameters such as PL exponent as well as the coverage probability of the network are evaluated. This research work may assist in the process of deployment and optimisation of any cellular network significantly.

Keywords: WiMAX, RSSI, path loss, coverage probability, regression analysis

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Authors: Tamanna Rimi

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A large body of literature has discussed the determinants of migration decision. However, the potential role of individual risk attitudes on migration decision has so far been overlooked. The research on migration literature has studied how the expected income differential influences migration flows for a risk neutral individual. However, migration takes place when there is no expected income differential or even the variability of income appears as lower than in the current location. This migration puzzle motivates a recent trend in the literature that analyzes how attitudes towards risk influence the decision to migrate. However, the significance of risk attitudes on migration decision has been addressed mostly in a theoretical perspective in the mainstream migration literature. The efficient outcome of labor market and overall economy are largely influenced by migration in many countries. Therefore, attitudes towards risk as a determinant of migration should get more attention in empirical studies. To author’s best knowledge, this is the first study that has examined the relationship between relative risk aversion and migration decision in US market. This paper considers movement across United States as a means of migration. In addition, this paper also explores the network effect due to the increasing size of one’s own ethnic group to a source location on the migration decision and how attitudes towards risk vary with network effect. Two ethnic groups (i.e. Asian and Hispanic) have been considered in this regard. For the empirical estimation, this paper uses two sources of data: 1) U.S. census data for social, economic, and health research, 2010 (IPUMPS) and 2) University of Michigan Health and Retirement Study, 2010 (HRS). In order to measure relative risk aversion, this study uses the ‘Two Sample Two-Stage Instrumental Variable (TS2SIV)’ technique. This is a similar method of Angrist (1990) and Angrist and Kruegers’ (1992) ‘Two Sample Instrumental Variable (TSIV)’ technique. Using a probit model, the empirical investigation yields the following results: (i) risk attitude has a significantly large impact on migration decision where more risk averse people are less likely to migrate; (ii) the impact of risk attitude on migration varies by other demographic characteristics such as age and sex; (iii) people with higher concentration of same ethnic households living in a particular place are expected to migrate less from their current place; (iv) the risk attitudes on migration vary with network effect. The overall findings of this paper relating risk attitude, migration decision and network effect can be a significant contribution addressing the gap between migration theory and empirical study in migration literature.

Keywords: migration, network effect, risk attitude, U.S. market

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Authors: Lavinia Ruta, Ileana Farcasanu

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The yeast surface display (YSD) technique enables the expression of proteins on yeast cell surfaces, facilitating the identification and isolation of proteins with targeted binding properties, such as nanobodies. Nanobodies, derived from camelid species, are single-domain antibody fragments renowned for their high affinity and specificity towards target proteins, making them valuable in research and potentially in therapeutics. Their advantages include a compact size (~15 kDa), robust stability, and the ability to target challenging epitopes. The project endeavors to establish and validate a platform for producing Green Fluorescent Protein (GFP) and mCherry nanobodies using the yeast surface display method. mCherry, a prevalent red fluorescent protein sourced from coral species, is commonly utilized as a genetic marker in biological studies due to its vibrant red fluorescence. The GFP-nanobody, a single variable domain of heavy-chain antibodies (VHH), exhibits specific binding to GFP, offering a potent means for isolating and engineering fluorescent protein fusions across various biological research domains. Both GFP and mCherry nanobodies find specific utility in cellular imaging and protein analysis applications.

Keywords: YSD, nanobodies, GFP, Saccharomyces cerevisiae

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Authors: Mehdi Jalalpour, Mazdak Tootkaboni

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We present a computationally efficient method for reliability-based topology optimization under material properties uncertainty, which is assumed to be lognormally distributed and correlated within the domain. Computational efficiency is achieved through estimating the response statistics with stochastic perturbation of second order, using these statistics to fit an appropriate distribution that follows the empirical distribution of the response, and employing an efficient gradient-based optimizer. The proposed algorithm is utilized for design of new structures and the changes in the optimized topology is discussed for various levels of target reliability and correlation strength. Predictions were verified thorough comparison with results obtained using Monte Carlo simulation.

Keywords: material uncertainty, stochastic perturbation, structural reliability, topology optimization

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Authors: Arun Goel

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Prediction of maximum local scour is necessary for the safety and economical design of the bridges. A number of equations have been developed over the years to predict local scour depth using laboratory data and a few pier equations have also been proposed using field data. Most of these equations are empirical in nature as indicated by the past publications. In this paper, attempts have been made to compute local depth of scour around bridge pier in dimensional and non-dimensional form by using linear regression, simple regression and SVM (Poly and Rbf) techniques along with few conventional empirical equations. The outcome of this study suggests that the SVM (Poly and Rbf) based modeling can be employed as an alternate to linear regression, simple regression and the conventional empirical equations in predicting scour depth of bridge piers. The results of present study on the basis of non-dimensional form of bridge pier scour indicates the improvement in the performance of SVM (Poly and Rbf) in comparison to dimensional form of scour.

Keywords: modeling, pier scour, regression, prediction, SVM (Poly and Rbf kernels)

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Authors: Adrian O'Hagan, Robert McLoughlin

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Considerable focus in the world of insurance risk quantification is placed on modeling loss values from lines of business (LOBs) that possess upper tail dependence. Copulas such as the Joe, Gumbel and Student-t copula may be used for this purpose. The copula structure imparts a desired level of tail dependence on the joint distribution of claims from the different LOBs. Alternatively, practitioners may possess historical or simulated data that already exhibit upper tail dependence, through the impact of catastrophe events such as hurricanes or earthquakes. In these circumstances, it is not desirable to induce additional upper tail dependence when modeling the joint distribution of the loss values from the individual LOBs. Instead, it is of interest to accurately assess the degree of tail dependence already present in the data. The empirical copula and its associated upper tail dependence coefficient are presented in this paper as robust, efficient means of achieving this goal.

Keywords: empirical copula, extreme events, insurance loss reserving, upper tail dependence coefficient

Procedia PDF Downloads 263

Authors: Zuzana Chaloupková, Zdeňka Marková, Václav Ranc, Radek Zbořil

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Prostate cancer is now one of the most serious oncological diseases in men with an incidence higher than that of all other solid tumors combined. Diagnosis of prostate cancer usually involves detection of related genes or detection of marker proteins, such as PSA. One of the new potential markers is PSMA (prostate specific membrane antigen). PSMA is a unique membrane bound glycoprotein, which is considerably overexpressed on prostate cancer as well as neovasculature of most of the solid tumors. Commonly applied methods for a detection of proteins include techniques based on immunochemical approaches, including ELISA and RIA. Magnetically assisted surface enhanced Raman spectroscopy (MA-SERS) can be considered as an interesting alternative to generally accepted approaches. This work describes a utilization of MA-SERS in a detection of PSMA in human blood. This analytical platform is based on magnetic nanocomposites Fe3O4@Ag, functionalized by a low-molecular selector labeled as JB303. The system allows isolating the marker from the complex sample using application of magnetic force. Detection of PSMA is than performed by SERS effect given by a presence of silver nanoparticles. This system allowed us to analyze PSMA in clinical samples with limits of detection lower than 1 ng/mL.

Keywords: diagnosis, cancer, PSMA, MA-SERS, Ag nanoparticles

Procedia PDF Downloads 202

Authors: K. A.Tharanga, K. H. H. Damayanthi

Abstract:

Perception is an epistemological concept discussed in Philosophy. Perception, in other word, vision, is one of the ways that human beings get empirical knowledge after five senses. However, we face innumerable problems when achieving knowledge from perception, and therefore the knowledge gained through perception is uncertain. what we see in the external world is not real. These are the major issues that we face when receiving knowledge through perception. Sometimes there is no physical existence of what we really see. In such cases, the perception is relative. The following frames will be taken into consideration when perception is analyzed illusions and delusions, the figure of a physical object, appearance and the reality of a physical object, time factor, and colour of a physical object. seeing and knowing become vary according to the above conceptual frames. We cannot come to a proper conclusion of what we see in the empirical world. Because the things that we see are not really there. Hence the scientific knowledge which is gained from observation is doubtful. All the factors discussed in science remain in the physical world. There is a leap from ones existence to the existence of a world outside his/her mind. Indeed, one can suppose that what he/she takes to be real is just a massive deception. However, depending on the above facts, if someone begins to doubt about the whole world, it is unavoidable to become his/her view a scepticism or nihilism. This is a certain reality.

Keywords: empirical, perception, sceptisism, nihilism

Procedia PDF Downloads 109

Authors: Sourour Khouaja, Hejer Jlassi, Nadia Feddaoui, Kamel Hamrouni

Abstract:

Most medical images, and especially mammographies, are now stored in large databases. Retrieving a desired image is considered of great importance in order to find previous similar cases diagnosis. Our method is implemented to assist radiologists in retrieving mammographic images containing breast with similar density aspect as seen on the mammogram. This is becoming a challenge seeing the importance of density criteria in cancer provision and its effect on segmentation issues. We used the BEMD (Bidimensional Empirical Mode Decomposition) to characterize the content of images and Euclidean distance measure similarity between images. Through the experiments on the MIAS mammography image database, we confirm that the results are promising. The performance was evaluated using precision and recall curves comparing query and retrieved images. Computing recall-precision proved the effectiveness of applying the CBIR in the large mammographic image databases. We found a precision of 91.2% for mammography with a recall of 86.8%.

Keywords: BEMD, breast density, contend-based, image retrieval, mammography

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Authors: L. Rakesh, T. Y. Heblekar

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This study entails the development and optimization of a mathematical model for a floating drum biogas reactor from first principles using thermal and empirical considerations. The model was derived on the basis of mass conservation, lumped mass heat transfer formulations and empirical biogas formation laws. The treatment leads to a system of coupled nonlinear ordinary differential equations whose solution mapped four-time independent controllable parameters to five output variables which adequately serve to describe the reactor performance. These equations were solved numerically using fourth order Runge-Kutta method for a range of input parameter values. Using the data so obtained an Artificial Neural Network with a single hidden layer was trained using Levenberg-Marquardt Damped Least Squares (DLS) algorithm. This network was then fine-tuned for optimal mapping by varying hidden layer size. This fast forward model was then employed as a health score generator in the Bacterial Foraging Optimization code. The optimal operating state of the simplified Biogas reactor was thus obtained.

Keywords: biogas, floating drum reactor, neural network model, optimization

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Authors: Cinzia Russi, Chiyo Nishida

Abstract:

Using data from online corpora (Spanish CREA, Italian CORIS), this paper examines the relatively understudied use of Spanish se and Italian si exemplified in (1) and (2), respectively. (1) El rojo es … el que se come a los demás. ‘The red (bottle) is the one that outshines/*eats the rest.’(2) … ebbe anche la saggezza di mangiarsi tutto il suo patrimonio. ‘… he even had the wisdom to squander/*eat all his estate.’ In these sentences, se/si accompanies the consumption verb comer/mangiare ‘to eat’, without which the sentences would not be interpreted appropriately. This se/si cannot readily be attributed to any of the multiple functions so far identified in the literature: reflexive, ergative, middle/passive, inherent, benefactive, and complete consumptive. In particular, this paper argues against the feasibility of a recent construction-based analysis of sentences like (1) and (2), which situates se/si within a prototype-based network of meanings all deriving from the central meaning of 'COMPLETE CONSUMPTION' (e.g., Alice se comió toda la torta/Alicesi è mangiata tutta la torta ‘John ate the whole cake’). Clearly, the empirical adequacy of such an account is undermined by the fact that the events depicted in the se/si-sentences at issue do not always entail complete consumption because they may lack an INCREMENTAL THEME, the distinguishing property of complete consumption. Alternatively, it is proposed that the sentences under analysis represent instances of verbal METAPHORICAL EXTENSION: se/si represents an explicit marker of this cognitive process, which has independently developed from the complete consumptive se/si, and the meaning extension is captured by the general tenets of Conceptual Metaphor Theory (CMT). Two conceptual domains, Source (DS) and target (DT), are related by similarity, assigning an appropriate metaphorical interpretation to DT. The domains paired here are comer/mangiare (DS) and comerse/mangiarsi (DT). The eating event (DS) involves (a) the physical process of xEATER grinding yFOOD-STUFF into pieces and swallowing it; and (b) the aspect of xEATER savoring yFOOD-STUFF and being nurtured by it. In the physical act of eating, xEATER has dominance and exercises his force over yFOOD-STUFF. This general sense of dominance and force is mapped onto DT and is manifested in the ways exemplified in (1) and (2), and many others. According to CMT, two other properties are observed in each pair of DS & DT. First, DS tends to be more physical and concrete and DT more abstract, and systematic mappings are established between constituent elements in DS and those in DT: xEATER corresponds to the element that destroys and yFOOD-STUFF to the element that is destroyed in DT, as exemplified in (1) and (2). Though the metaphorical extension marker se/si appears by far most frequently with comer/mangiare in the corpora, similar systematic mappings are observed in several other verb pairs, for example, jugar/giocare ‘to play (games)’ and jugarse/giocarsi ‘to jeopardize/risk (life, reputation, etc.)’, perder/perdere ‘to lose (an object)’ and perderse/perdersi ‘to miss out on (an event)’, etc. Thus, this study provides evidence that languages may indeed formally mark metaphor using means available to them.

Keywords: complete consumption value, conceptual metaphor, Italian si/Spanish se, metaphorical extension.

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Authors: Fayyaz Rasool, Shakeela Parveen

Abstract:

The studies on genetic diversity of Labeo rohita by using molecular markers were carried out to investigate the genetic structure by RAPAD marker and the levels of polymorphism and similarity amongst the different groups of five populations of wild and farmed types. The samples were collected from different five locations as representatives of wild and hatchery raised populations. RAPAD data for Jaccard’s coefficient by following the un-weighted Pair Group Method with Arithmetic Mean (UPGMA) for Hierarchical Clustering of the similar groups on the basis of similarity amongst the genotypes and the dendrogram generated divided the randomly selected individuals of the five populations into three classes/clusters. The variance decomposition for the optimal classification values remained as 52.11% for within class variation, while 47.89% for the between class differences. The Principal Component Analysis (PCA) for grouping of the different genotypes from the different environmental conditions was done by Spearman Varimax rotation method for bi-plot generation of the co-occurrence of the same genotypes with similar genetic properties and specificity of different primers indicated clearly that the increase in the number of factors or components was correlated with the decrease in eigenvalues. The Kaiser Criterion based upon the eigenvalues greater than one, first two main factors accounted for 58.177% of cumulative variability.

Keywords: variation, clustering, PCA, wild, hatchery, RAPAD, Labeo rohita

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Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

Abstract:

Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Amin AminiKhafri, James M. Dawson-Edwards, Ryan M. Simpson, Simaan M. AbouRizk

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Earned value management (EVM) has been introduced as an integrated method to combine schedule, budget, and work breakdown structure (WBS). EVM provides various indices to demonstrate project performance including the cost performance index (CPI). CPI is also used to forecast final project cost at completion based on the cost performance during the project execution. Knowing the final project cost during execution can initiate corrective actions, which can enhance project outputs. CPI, however, is not constant during the project, and calculating the final project cost using a variable index is an inaccurate and challenging task for practitioners. Since CPI is based on the cumulative progress values and because of the learning curve effect, CPI variation dampens and stabilizes as project progress. Although various definitions for the CPI stability have been proposed in literature, many scholars have agreed upon the definition that considers a project as stable if the CPI at 20% completion varies less than 0.1 from the final CPI. While 20% completion point is recognized as the stability point for military development projects, construction projects stability have not been studied. In the current study, an empirical study was first conducted using construction project data to determine the stability point for construction projects. Early findings have demonstrated that a majority of construction projects stabilize towards completion (i.e., after 70% completion point). To investigate the effect of CPI stability on cost forecast accuracy, the correlation between CPI stability and project cost at completion forecast accuracy was also investigated. It was determined that as projects progress closer towards completion, variation of the CPI decreases and final project cost forecast accuracy increases. Most projects were found to have 90% accuracy in the final cost forecast at 70% completion point, which is inlined with findings from the CPI stability findings. It can be concluded that early stabilization of the project CPI results in more accurate cost at completion forecasts.

Keywords: cost performance index, earned value management, empirical study, final project cost

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Authors: Ping Bo, Meng Yunshan

Abstract:

Satellite-derived sea surface temperature (SST) is a key parameter for many operational and scientific applications. However, the disadvantage of SST data is a high percentage of missing data which is mainly caused by cloud coverage. Data Interpolating Empirical Orthogonal Function (DINEOF) algorithm is an EOF-based technique for reconstructing the missing data and has been widely used in oceanographic field. The reconstruction of SST images within a long time series using DINEOF can cause large discontinuities and one solution for this problem is to filter the temporal covariance matrix to reduce the spurious variability. Based on the previous researches, an algorithm is presented in this paper to improve the temporal correlations in EOF expansion. Similar with the previous researches, a filter, such as Laplacian filter, is implemented on the temporal covariance matrix, but the temporal relationship between two consecutive images which is used in the filter is considered in the presented algorithm, for example, two images in the same season are more likely correlated than those in the different seasons, hence the latter one is less weighted in the filter. The presented approach is tested for the monthly nighttime 4-km Advanced Very High Resolution Radiometer (AVHRR) Pathfinder SST for the long-term period spanning from 1989 to 2006. The results obtained from the presented algorithm are compared to those from the original DINEOF algorithm without filtering and from the DINEOF algorithm with filtering but without taking temporal relationship into account.

Keywords: data interpolating empirical orthogonal function, image reconstruction, sea surface temperature, temporal filter

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Authors: T. Almutairi, K. Naudi, N. Nairn, X. Ju, B. Eng, J. Whitters, A. Ayoub

Abstract:

Purpose: At present Cone Beam Computed Tomography (CBCT) imaging does not record dental morphology accurately due to the scattering produced by metallic restorations and the reported magnification. The aim of this pilot study is the development and validation of a new method for the replacement of the distorted dentition of CBCT scans with the dental image captured by the digital intraoral camera. Materials and Method: Six dried skulls with orthodontics brackets on the teeth were used in this study. Three intra-oral markers made of dental stone were constructed which were attached to orthodontics brackets. The skulls were CBCT scanned, and occlusal surface was captured using TRIOS® 3D intraoral scanner. Marker based and surface based registrations were performed to fuse the digital intra-oral scan(IOS) into the CBCT models. This produced a new composite digital model of the skull and dentition. The skulls were scanned again using the commercially accurate Laser Faro® arm to produce the 'gold standard' model for the assessment of the accuracy of the developed method. The accuracy of the method was assessed by measuring the distance between the occlusal surfaces of the new composite model and the 'gold standard' 3D model of the skull and teeth. The procedure was repeated a week apart to measure the reproducibility of the method. Results: The results showed no statistically significant difference between the measurements on the first and second occasions. The absolute mean distance between the new composite model and the laser model ranged between 0.11 mm to 0.20 mm. Conclusion: The dentition of the CBCT can be accurately replaced with the dental image captured by the intra-oral scanner to create a composite model. This method will improve the accuracy of orthognathic surgical prediction planning, with the final goal of the fabrication of a physical occlusal wafer without to guide orthognathic surgery and eliminate the need for dental impression.

Keywords: orthognathic surgery, superimposition, models, cone beam computed tomography

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Authors: Norimichi Nagano, Yoshio Hirano, Tsutomu Yasukawa

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Mesenchymal stem cells are thought to confer neuroprotection, facilitate tissue regeneration and exert their effects on retinal degenerative diseases, however, adverse events such as proliferative vitreoretinopathy and preretinal membrane disease associated with cell suspension transplantation have also been reported. We have recently developed human (allogeneic) adipose tissue-derived mesenchymal stem cell (adMSC) sheets through our proprietary sheet transformation technique, which could potentially mitigate these adverse events. To clarify the properties of our adMSC sheets named PAL-222, we performed in vitro studies such as viability testing, cytokine secretions by ELISA, immunohistochemical study, and migration assay. The viability of the cells exceeded 70%. Vascular Endothelial Growth Factor (VEGF) and Pigment Epithelium-Derived Factor (PEDF), which are quite important cytokines for the retinal area, were observed. PAL-222 expressed type I collagen, a strength marker, type IV collagen, a marker of the basement membrane, and elastin, an elasticity marker. Finally, the migration assay was performed and showed negative, which means that PAL-222 is stably kept in the topical area and does not come to pieces. Next, to evaluate the efficacy in vivo, we transplanted PAL-222 into the subretinal space of the eye of Royal College of Surgeons rats with congenital retinal degeneration and assessed it for three weeks after transplantation. We confirmed that PAL-222 suppressed the decrease in the thickness of the outer nuclear layer, which means that the photoreceptor protective effect treated with PAL-222 was significantly higher than that in the sham group. (p < 0.01). This finding demonstrates that PAL-222 showed their retinoprotective effect in a model of congenital retinal degeneration. As the study suggested the efficacy of PAL-222 in both in vitro and in vivo studies, we are presently engaged in clinical trials of PAL-222 for myopic chorioretinal atrophy, which is one of the retinal degenerative diseases, for the purpose of regenerative medicine.

Keywords: cell sheet, clinical trial, mesenchymal stem cell, myopic chorioretinal atrophy

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Authors: Abouamama Sidaoui, Noureddine Karkachi, Mebrouk Kihal

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The characteristics of Fusarium oxysporium f.sp. albedinis (Foa) isolates were investigated using electrophoretic studies of isozymes systems (esterase and phosphatase). All the (F.o.a) isolates were pathogenic to the date palm seedlings cultivar Deglet Nour, but they did not induce any disease symptoms on control plants. Fusarium sp. isolated from soil did not show aggression against these seedlings. The isoenzymes profiles revealed polymorphic bands. The data were subjected to analysis with the JMP method. The isolates were delineated into two main groups A and B which were divided into sub-groups. 19 isolates create the group A, and four isolates (E1, E2, E3 and M15A) formed the group B. Analysis of isozyme banding patterns was found to be a reliable marker technology, efficient, and effective tools to find the genetic variability among isolates isolated in different geographical areas.

Keywords: genetic diversity, Fusarium oxysporium f. sp. albedinis, isozyme analysis, pathogenicity

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Authors: Abdollah Ghasempour, Mohammad Reza Kavianpour, Majid Galoie

Abstract:

This study has investigated the fundamental parameters which have effective role on energy dissipation of nappe flows on stepped chutes in order to estimate an empirical relationship using dimensional analysis. To gain this goal, comprehensive experimental study on some large-scale physical models with various step geometries, slopes, discharges, etc. were carried out. For all models, hydraulic parameters such as velocity, pressure, water depth, flow regime and etc. were measured precisely. The effective parameters, then, could be determined by analysis of experimental data. Finally, a dimensional analysis was done in order to estimate an empirical relationship for evaluation of energy dissipation of nappe flows on stepped chutes. Because of using the large-scale physical models in this study, the empirical relationship is in very good agreement with the experimental results.

Keywords: nappe flow, energy dissipation, stepped chute, dimensional analysis

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Authors: Arnab Hazra

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Breath analysis is a quick, noninvasive and inexpensive technique for disease diagnosis can be used on people of all ages without any risk. Only a limited number of volatile organic compounds (VOCs) can be associated with the occurrence of specific diseases. These VOCs can be considered as disease markers or breath markers. Selective detection with specific concentration of breath marker in exhaled human breath is required to detect a particular disease. For example, acetone (C₃H₆O), ethanol (C₂H₅OH), ethane (C₂H₆) etc. are the breath markers and abnormal concentrations of these VOCs in exhaled human breath indicates the diseases like diabetes mellitus, renal failure, breast cancer respectively. Nanomaterial-based vapor sensors are inexpensive, small and potential candidate for the detection of breath markers. In practical measurement, selectivity is the most crucial issue where trace detection of breath marker is needed to identify accurately in the presence of several interfering vapors and gases. Current article concerns a novel technique for selective and lower ppb level detection of breath markers at very low temperature based on TiO₂ nanotube array based vapor sensor devices. Highly ordered and oriented TiO₂ nanotube array was synthesized by electrochemical anodization of high purity tatinium (Ti) foil. 0.5 wt% NH₄F, ethylene glycol and 10 vol% H₂O was used as the electrolyte and anodization was carried out for 90 min with 40 V DC potential. Au/TiO₂ Nanotube/Ti, sandwich type sensor device was fabricated for the selective detection of VOCs in low concentration range. Initially, sensor was characterized where resistive and capacitive change of the sensor was recorded within the valid concentration range for individual breath markers (or organic vapors). Sensor resistance was decreased and sensor capacitance was increased with the increase of vapor concentration. Now, the ratio of resistive slope (mR) and capacitive slope (mC) provided a concentration independent constant term (M) for a particular vapor. For the detection of unknown vapor, ratio of resistive change and capacitive change at any concentration was same to the previously calculated constant term (M). After successful identification of the target vapor, concentration was calculated from the straight line behavior of resistance as a function of concentration. Current technique is suitable for the detection of particular vapor from a mixture of other interfering vapors.

Keywords: breath marker, vapor sensors, selective detection, TiO₂ nanotube array

Procedia PDF Downloads 134

Authors: Ateba Benedict Belobo, Faan Pelser, Ambe Marcus

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Aims: This study arise from repeated complaints from both electronic mails about the underperformance of Mafikeng Small and Medium-Size enterprises after the global financial crisis. The authors were on the view that, this poor performance experienced could be as a result of the negative effects on the cash flow of these businesses due to volatilities in the business environment in general prior to the global crisis. Thus, the paper was mainly aimed at determining the shortcomings experienced by these SMEs with regards to cash flow management. It was also aimed at suggesting possible measures to improve cash flow management of these SMEs in this tough time. Methods: A case study was conducted on 3 beverage suppliers, 27 bottle stores, 3 largest fast consumer goods super markets and 7 automobiles enterprises in the Mafikeng local municipality. A mixed method research design was employed and a purposive sampling was used in selecting SMEs that participated. Views and experiences of participants of the paper were captured through in-depth interviews. Data from the empirical investigation were interpreted using open coding and a simple percentage formula. Results: Findings from the empirical research reflected that majority of Mafikeng SMEs suffer poor operational performance prior to the global financial crisis primarily as a result of poor cash flow management. However, the empirical outcome also indicted other secondary factors contributing to this poor operational performance. Conclusion: Finally, the authorsproposed possible measures that could be used to improve cash flow management and to solve other factors affecting operational performance of SMEs in the Mafikeng local municipality in other to achieve a better business performance.

Keywords: cash flow, business performance, global financial crisis, SMEs

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Authors: Jehad Al Dallal

Abstract:

Attributes and methods are the basic contents of an object-oriented class. The connectivity among these class members and the relationship between the class and other classes play an important role in determining the quality of an object-oriented system. Class cohesion evaluates the degree of relatedness of class attributes and methods, whereas class coupling refers to the degree to which a class is related to other classes. Researchers have proposed several class cohesion and class coupling measures. However, the correlation between class coupling and class cohesion measures have not been thoroughly studied. In this paper, using classes of three open-source Java systems, we empirically investigate the correlation between several measures of connectivity-based class cohesion and coupling. Four connectivity-based cohesion measures and eight coupling measures are considered in the empirical study. The empirical study results show that class connectivity-based cohesion and coupling internal quality attributes are inversely correlated. The strength of the correlation depends highly on the cohesion and coupling measurement approaches.

Keywords: object-oriented class, software quality, class cohesion measure, class coupling measure

Procedia PDF Downloads 295