Search results for: Statistical package IBM SPSS 20

Authors: Pedram Saadati, Zahra Nazari

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Today, the role and importance of financial technology businesses in Iran have increased significantly. Although, in Iran, there is no Islamic or non-Islamic personal financial planning field of study in the universities or educational centers, the profession of personal financial planning is not defined, and there is no software introduced in this regard for advisors or consumers. The largest sales network of financial services in Iran belongs to the insurance industry, and there is an untapped market for international companies in Iran that can contribute to 130 thousand representatives in the insurance industry and 28 million families by providing training and personal financial advisory software. To the best of the author's knowledge, despite the lack of previous internal studies in this field, the present study investigates the level of readiness of the salesforce of the insurance industry to accept this career and its technology. The statistical population of the research is made up of managers, insurance sales representatives, assistants and heads of sales departments of insurance companies. An 18-minute video was prepared that introduced and taught the job of Islamic personal financial planning and explained its difference from its non-Islamic model. This video was provided to the respondents. The data collection tool was a research-made questionnaire. To investigate the factors affecting technology acceptance and job change, independent T descriptive statistics and Pearson correlation were used, and Friedman's test was used to rank the effective factors. The results indicate the mental perception and very positive attitude of the insurance industry activists towards the usefulness of this job and its technology, and the studied sample confirmed the intention of training in this knowledge. Based on research results, the change in the customer's attitude towards the insurance advisor and the possibility of increasing income are considered as the reasons for accepting. However, Restrictions on using investment opportunities due to Islamic financial services laws and the uncertainty of the position of the central insurance in this regard are considered as the most important obstacles.

Keywords: fintech, insurance, personal financial planning, wealth management

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Authors: Shanorfizah Mohd Safar, Shaizatulaqma Kamalul Ariffin

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Internationalization of halal small and medium-sized enterprises (SMEs) is necessary for SMEs to become more involved in regional trade and business cooperation. By internationalization, SMEs' profit can increase, and market expansion of SMEs is basic for rising economies of countries to contend all around in the halal industry globally. There are several modes of internationalization; exporting is one of the first steps for internationalization with less capital needed. The study examines the influential factors of export performance amongst halal SMEs in Malaysia. Specifically, this study examines the positive and significant relationships amongst human capital, managerial capability, Halal Assurance Management System (HAMS), digital transformation, government support, and networking capability on halal SMEs' export performance toward SMEs' competitive advantage. In addition, this study will examine innovation capabilities as a moderator in the relationship between independence variables and competitive advantage. Competitive advantage is the most compelling perspective that drives the export performance of halal SMEs in Malaysia. A quantitative method will be used: an online questionnaire survey distributed through emails and face-to-face toward selected halal-certificated SMEs registered in JAKIM, MATRADE website and SME Corp Malaysia website. Nevertheless, whether the halal SMEs practice global business, they will still be the potential respondents. The data were examined and obtained using the statistical software Smart PLS. The analysis used is reliability, correlation, and regression analysis to meet the research objectives. This study contributes significantly to the theory by integrating Resource Based View (RBV) theory, Technology–Organization–Environment (TOE) framework and Networking theory. In addition, this research extends the RBV by extending a variable, the Halal Assurance Management System. This study also examines a moderating role of innovation capabilities in the framework and competitive advantage as a mediator. This research aims to analyze the factors that will impact the internationalization of halal SMEs.

Keywords: internationalization, halal SMEs, competitive advantage, export performance

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Authors: Laura Piedra-Muñoz, Ángeles Godoy-Durán, Emilio Galdeano-Gómez, Juan C. Pérez-Mesa

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The current agricultural system in some arid and semi-arid areas is not sustainable in the long term. In southeast Spain, groundwater is the main water source and is overexploited, while alternatives like desalination are still limited. The Water Plan for the Mediterranean Basins 2015-2020 indicates a global deficit of 73.42 hm3 and an overexploitation of the aquifers of 205.58hm3. In order to solve this serious problem, two major actions can be taken: increasing available water, and/or improving the efficiency of its use. This study focuses on the latter. The main aim of this study is to present the major factors related to water usage efficiency in farming. It focuses on Almería province, southeast Spain, one of the most arid areas of the country, and in particular on family farms as the main direct managers of water use in this zone. Many of these farms are among the most water efficient in Spanish agriculture, but this efficiency is not generalized throughout the sector. This work conducts a comprehensive assessment of water performance in this area, using on-farm water-use, structural, socio-economic and environmental information. Two statistical techniques are used: descriptive analysis and cluster analysis. Thus, two groups are identified: the least and the most efficient farms regarding water usage. By analyzing both the common characteristics within each group and the differences between the groups with a one-way ANOVA analysis, several conclusions can be reached. The main differences between the two clusters center on the extent to which innovation and new technologies are used in irrigation. The most water efficient farms are characterized by more educated farmers, a greater degree of innovation, new irrigation technology, specialized production and awareness of water issues and environmental sustainability. The research shows that better practices and policies can have a substantial impact on achieving a more sustainable and efficient use of water. The findings of this study can be extended to farms in similar arid and semi-arid areas and contribute to foster appropriate policies to improve the efficiency of water usage in the agricultural sector.

Keywords: cluster analysis, family farms, Spain, water-use efficiency

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Authors: Louise Jones, Rafael De Andrade Moral, John C. Stephens

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Background: Minerals are an essential component of correct nutrition. Conserved hay/haylage is an important component of many horse's diets. Variations in the mineral content of conserved forage should be considered when assessing dietary intake. Objectives: This study describes the levels and differences in 15 commonly analysed minerals in conserved forage fed to horses in the United Kingdom (UK), Ireland (IRL), and France (FRA). Methods: Hay (FRA n=92, IRL n=168, UK n=152) and haylage samples (UK n=287, IRL n=49) were collected during 2017-2020. Mineral analysis was undertaken using inductively coupled plasma-mass spectrometry (ICP-MS). Statistical analysis was performed using beta regression, Gaussian, or gamma models, depending on the nature of the response variable. Results: There are significant differences in the mineral content of the UK, IRL, and FRA conserved forage samples. FRA hay samples had a significantly higher (p < 0.05) levels of Sulphur (0.16 ± 0.0051 %), Calcium (0.56 ± 0.0342%), Magnesium (0.16 ± 0.0069 mg/ kg DM), Iron (194 ± 23.0 mg/kg DM), Cobalt (0.21 ± 0.0244 mg/kg DM) and Copper (4.94 ± 0.196 mg/kg DM) content compared to hay from the other two countries. UK hay samples had significantly less (p < 0.05) Selenium (0.07 ± 0.0084 mg/kg DM), whilst IRL hay samples were significantly (p < 0.05) higher in Chloride (0.9 ± 0.026mg/kg DM) compared to hay from the other two countries. IRL haylage samples were significantly (p < 0.05) higher in Phosphorus (0.26 ± 0.0102 %), Sulphur (0.17 ± 0.0052 %), Chloride (1.01 ± 0.0519 %), Calcium (0.54 ± 0.0257 %), Selenium (0.17 ± 0.0322 mg/kg DM) and Molybdenum (1.47 ± 0.137 mg/kg DM) compared to haylage from the UK. Main Limitations: Forage samples were obtained from professional yards and may not be reflective of forages fed by most horse owners. Information regarding soil type, species of grass, fertiliser treatment, harvest, or storage conditions were not included in this study. Conclusions: At a DM intake of 2% body weight, conserved forage as sampled in this study will be insufficient to meet Zinc, Iodine, and Copper NRC maintenance requirements, and Se intake will also be insufficient for horses fed the UK conserved forage. Many horses receive hay/haylage as the main component of their diet; this study highlights the need to consider forage analysis when making dietary recommendations.

Keywords: conserved forage, hay, haylage, minerals

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Authors: Forouzan Salehi Fergeni

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Converting the movement intents of a person into commands for action employing brain signals like electroencephalogram signals is a brain-computer interface (BCI) system. When left or right-hand motions are imagined, different patterns of brain activity appear, which can be employed as BCI signals for control. To make better the brain-computer interface (BCI) structures, effective and accurate techniques for increasing the classifying precision of motor imagery (MI) based on electroencephalography (EEG) are greatly needed. Subject dependency and non-stationary are two features of EEG signals. So, EEG signals must be effectively processed before being used in BCI applications. In the present study, after applying an 8 to 30 band-pass filter, a car spatial filter is rendered for the purpose of denoising, and then, a method of analysis of variance is used to select more appropriate and informative channels from a category of a large number of different channels. After ordering channels based on their efficiencies, a sequential forward channel selection is employed to choose just a few reliable ones. Features from two domains of time and wavelet are extracted and shortlisted with the help of a statistical technique, namely the t-test. Finally, the selected features are classified with different machine learning and neural network classifiers being k-nearest neighbor, Probabilistic neural network, support-vector-machine, Extreme learning machine, decision tree, Multi-layer perceptron, and linear discriminant analysis with the purpose of comparing their performance in this application. Utilizing a ten-fold cross-validation approach, tests are performed on a motor imagery dataset found in the BCI competition III. Outcomes demonstrated that the SVM classifier got the greatest classification precision of 97% when compared to the other available approaches. The entire investigative findings confirm that the suggested framework is reliable and computationally effective for the construction of BCI systems and surpasses the existing methods.

Keywords: brain-computer interface, channel selection, motor imagery, support-vector-machine

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Authors: Csaba Kalman

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In spite of the existence of numerous second language (L2) motivation theories, the teacher’s role in motivating learners has remained an under-researched niche to this day. If we narrow down our focus on the teacher’s role on motivating adult learners of English in an English as a Foreign Language (EFL) context in corporate environments, empirical research is practically non-existent. This study fills the above research niche by exploring the most motivating aspects of the teacher’s personality, behaviour, and teaching practices that affect adult learners’ L2 motivation in corporate contexts in Hungary. The study was conducted in a wide range of industries in 18 organisations that employ over 250 people in Hungary. In order to triangulate the research, 21 human resources managers, 18 language teachers, and 466 adult learners of English were involved in the investigation by participating in interview studies, and quantitative questionnaire studies that measured ten scales related to the teacher’s role, as well as two criterion measure scales of intrinsic and extrinsic motivation. The qualitative data were analysed using a template organising style, while descriptive, inferential statistics, as well as multivariate statistical techniques, such as correlation and regression analyses, were used for analysing the quantitative data. The results showed that certain aspects of the teacher’s personality (thoroughness, enthusiasm, credibility, and flexibility), as well as preparedness, incorporating English for Specific Purposes (ESP) in the syllabus, and focusing on the present, proved to be the most salient aspects of the teacher’s motivating influence. The regression analyses conducted with the criterion measure scales revealed that 22% of the variance in learners’ intrinsic motivation could be explained by the teacher’s preparedness and appearance, and 23% of the variance in learners’ extrinsic motivation could be attributed to the teacher’s personal branding and incorporating ESP in the syllabus. The findings confirm the pivotal role teachers play in motivating L2 learners independent of the context they teach in; and, at the same time, call for further research so that we can better conceptualise the motivating influence of L2 teachers.

Keywords: adult learners, corporate contexts, motivation, teacher’s role

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Authors: Wale Agbaje

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The aim of this research study is to assess the impact of financial statement fraud on profitability of some selected Nigerian manufacturing firms covering (2002-2016). The specific objectives focused on to ascertain the effect of incorrect asset valuation on return on assets (ROA) and to ascertain the relationship between improper expense recognition and return on assets (ROA). To achieve these objectives, descriptive research design was used for the study while secondary data were collected from the financial reports of the selected firms and website of security and exchange commission. The analysis of covariance (ANCOVA) was used and STATA II econometric method was used in the analysis of the data. Altman model and operating expenses ratio was adopted in the analysis of the financial reports to create a dummy variable for the selected firms from 2002-2016 and validation of the parameters were ascertained using various statistical techniques such as t-test, co-efficient of determination (R2), F-statistics and Wald chi-square. Two hypotheses were formulated and tested using the t-statistics at 5% level of significance. The findings of the analysis revealed that there is a significant relationship between financial statement fraud and profitability in Nigerian manufacturing industry. It was revealed that incorrect assets valuation has a significant positive relationship and so also is the improper expense recognition on return on assets (ROA) which serves as a proxy for profitability. The implication of this is that distortion of asset valuation and expense recognition leads to decreasing profit in the long run in the manufacturing industry. The study therefore recommended that pragmatic policy options need to be taken in the manufacturing industry to effectively manage incorrect asset valuation and improper expense recognition in order to enhance manufacturing industry performance in the country and also stemming of financial statement fraud should be adequately inculcated into the internal control system of manufacturing firms for the effective running of the manufacturing industry in Nigeria.

Keywords: Althman's Model, improper expense recognition, incorrect asset valuation, return on assets

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Authors: Rowan Moore, Kai Scheffler, Eugen Damoc, Jennifer Sutton, Aaron Bailey, Stephane Houel, Simon Cubbon, Jonathan Josephs

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Purpose: MS analysis of monoclonal antibodies (mAbs) at the protein and peptide levels is critical during development and production of biopharmaceuticals. The compositions of current generation therapeutic proteins are often complex due to various modifications which may affect efficacy. Intact proteins analyzed by MS are detected in higher charge states that also provide more complexity in mass spectra. Protein analysis in native or native-like conditions with zero or minimal organic solvent and neutral or weakly acidic pH decreases charge state value resulting in mAb detection at higher m/z ranges with more spatial resolution. Methods: Three commercially available mAbs were used for all experiments. Intact proteins were desalted online using size exclusion chromatography (SEC) or reversed phase chromatography coupled on-line with a mass spectrometer. For streamlined use of the LC- MS platform we used a single SEC column and alternately selected specific mobile phases to perform separations in either denaturing or native-like conditions: buffer A (20 % ACN, 0.1 % FA) with Buffer B (100 mM ammonium acetate). For peptide analysis mAbs were proteolytically digested with and without prior reduction and alkylation. The mass spectrometer used for all experiments was a commercially available Thermo Scientific™ hybrid Quadrupole-Orbitrap™ mass spectrometer, equipped with the new BioPharma option which includes a new High Mass Range (HMR) mode that allows for improved high mass transmission and mass detection up to 8000 m/z. Results: We have analyzed the profiles of three mAbs under reducing and native conditions by direct infusion with offline desalting and with on-line desalting via size exclusion and reversed phase type columns. The presence of high salt under denaturing conditions was found to influence the observed charge state envelope and impact mass accuracy after spectral deconvolution. The significantly lower charge states observed under native conditions improves the spatial resolution of protein signals and has significant benefits for the analysis of antibody mixtures, e.g. lysine variants, degradants or sequence variants. This type of analysis requires the detection of masses beyond the standard mass range ranging up to 6000 m/z requiring the extended capabilities available in the new HMR mode. We have compared each antibody sample that was analyzed individually with mixtures in various relative concentrations. For this type of analysis, we observed that apparent native structures persist and ESI is benefited by the addition of low amounts of acetonitrile and formic acid in combination with the ammonium acetate-buffered mobile phase. For analyses on the peptide level we analyzed reduced/alkylated, and non-reduced proteolytic digests of the individual antibodies separated via reversed phase chromatography aiming to retrieve as much information as possible regarding sequence coverage, disulfide bridges, post-translational modifications such as various glycans, sequence variants, and their relative quantification. All data acquired were submitted to a single software package for analysis aiming to obtain a complete picture of the molecules analyzed. Here we demonstrate the capabilities of the mass spectrometer to fully characterize homogeneous and heterogeneous therapeutic proteins on one single platform. Conclusion: Full characterization of heterogeneous intact protein mixtures by improved mass separation on a quadrupole-Orbitrap™ mass spectrometer with extended capabilities has been demonstrated.

Keywords: disulfide bond analysis, intact analysis, native analysis, mass spectrometry, monoclonal antibodies, peptide mapping, post-translational modifications, sequence variants, size exclusion chromatography, therapeutic protein analysis, UHPLC

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Authors: Pinel Sebastien, Bourrin François, De Madron Du Rieu Xavier, Ludwig Wolfgang, Arnau Pedro

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Heavy precipitation constitutes a major meteorological threat in the western Mediterranean. Research has investigated the relationship between the states of the Mediterranean Sea and the atmosphere with the precipitation for short temporal windows. However, at a larger temporal scale, the precursor signals of heavy rainfall in the sea and atmosphere have drawn little attention. Moreover, despite ongoing improvements in numerical weather prediction, the medium-term forecasting of rainfall events remains a difficult task. Here, we aim to investigate the influence of early-spring environmental parameters on the following autumnal heavy precipitations. Hence, we develop a machine learning model to predict extreme autumnal rainfall with a 6-month lead time over the Spanish Catalan coastal area, based on i) the sea pattern (main current-LPC and Sea Surface Temperature-SST) at the mesoscale scale, ii) 4 European weather teleconnection patterns (NAO, WeMo, SCAND, MO) at synoptic scale, and iii) the hydrological regime of the main local river (Rhône River). The accuracy of the developed model classifier is evaluated via statistical analysis based on classification accuracy, logarithmic and confusion matrix by comparing with rainfall estimates from rain gauges and satellite observations (CHIRPS-2.0). Sensitivity tests are carried out by changing the model configuration, such as sea SST, sea LPC, river regime, and synoptic atmosphere configuration. The sensitivity analysis suggests a negligible influence from the hydrological regime, unlike SST, LPC, and specific teleconnection weather patterns. At last, this study illustrates how public datasets can be integrated into a machine learning model for heavy rainfall prediction and can interest local policies for management purposes.

Keywords: extreme hazards, sensitivity analysis, heavy rainfall, machine learning, sea-atmosphere modeling, precipitation forecasting

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Authors: Wenpeng You, Maciej Henneberg

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Background: Sugar consumption has been overwhelmingly advocated as a major dietary offender to obesity prevalence. Meat intake has been hypothesized as an obesity contributor in previous publications, but a moderate amount of meat to be included in our daily diet still has been suggested in many dietary guidelines. Comparable sugar and meat exposure data were obtained to assess the difference in relationships between the two major food groups and obesity prevalence at population level. Methods: Population level estimates of obesity and overweight rates, per capita per day exposure of major food groups (meat, sugar, starch crops, fibers, fats and fruits) and total calories, per capita per year GDP, urbanization and physical inactivity prevalence rate were extracted and matched for statistical analysis. Correlation coefficient (Pearson and partial) comparisons with Fisher’s r-to-z transformation and β range (β ± 2 SE) and overlapping in multiple linear regression (Enter and Stepwise) were used to examine potential differences in the relationships between obesity prevalence and sugar exposure and meat exposure respectively. Results: Pearson and partial correlations (controlled for total calories, physical inactivity prevalence, GDP and urbanization) analyses revealed that sugar and meat exposures correlated to obesity and overweight prevalence significantly. Fisher's r-to-z transformation did not show statistically significant difference in Pearson correlation coefficients (z=-0.53, p=0.5961) or partial correlation coefficients (z=-0.04, p=0.9681) between obesity prevalence and both sugar exposure and meat exposure. Both Enter and Stepwise models in multiple linear regression analysis showed that sugar and meat exposure were most significant predictors of obesity prevalence. Great β range overlapping in the Enter (0.289-0.573) and Stepwise (0.294-0.582) models indicated statistically sugar and meat exposure correlated to obesity without significant difference. Conclusion: Worldwide sugar and meat exposure correlated to obesity prevalence at the same extent. Like sugar, minimal meat exposure should also be suggested in the dietary guidelines.

Keywords: meat, sugar, obesity, energy surplus, meat protein, fats, insulin resistance

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Authors: Moses Mwangi, Geert Verbeke, Geert Molenberghs

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Cross-over designs are commonly used in randomized clinical trials to estimate efficacy of a new treatment with respect to a reference treatment (placebo or standard). The main advantage of using cross-over design over conventional parallel design is its flexibility, where every subject become its own control, thereby reducing confounding effect. Jones & Kenward, discuss in detail more recent developments in the analysis of cross-over trials. We revisit the simple piecewise linear mixed-effects model, proposed by Mwangi et. al, (in press) for its first application in the analysis of cross-over trials. We compared performance of the proposed piecewise linear mixed-effects model with two commonly cited statistical models namely, (1) Grizzle model; and (2) Jones & Kenward model, used in estimation of the treatment effect, in the analysis of randomized cross-over trial. We estimate two performance measurements (mean square error (MSE) and coverage probability) for the three methods, using data simulated from the proposed piecewise linear mixed-effects model. Piecewise linear mixed-effects model yielded lowest MSE estimates compared to Grizzle and Jones & Kenward models for both small (Nobs=20) and large (Nobs=600) sample sizes. It’s coverage probability were highest compared to Grizzle and Jones & Kenward models for both small and large sample sizes. A piecewise linear mixed-effects model is a better estimator of treatment effect than its two competing estimators (Grizzle and Jones & Kenward models) in the analysis of cross-over trials. The data generating mechanism used in this paper captures two time periods for a simple 2-Treatments x 2-Periods cross-over design. Its application is extendible to more complex cross-over designs with multiple treatments and periods. In addition, it is important to note that, even for single response models, adding more random effects increases the complexity of the model and thus may be difficult or impossible to fit in some cases.

Keywords: Evaluation, Grizzle model, Jones & Kenward model, Performance measures, Simulation

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Authors: L. Kolatorova, J. Vitku, K. Adamcova, M. Simkova, M. Hill, A. Parizek, M. Duskova

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Endocrine disruptors (EDs) are substances leaching from various industrial products, which are able to interfere with the endocrine system. Their harmful effects on human health are generally well-known, and exposure during fetal development may have lasting effects. Fetal exposure and transplacental transport of bisphenol A (BPA) have been recently studied; however, less is known about alternatives such as bisphenol S (BPS), bisphenol F (BPF) and bisphenol AF (BPAF), which have started to appear in consumer products. The human organism is usually exposed to the mixture of EDs, out of which parabens are otherwise known to transfer placenta. The usage of many cosmetic, pharmaceutical and consumer products during the pregnancy that may contain parabens and bisphenols has led to the need for investigation. The aim of the study was to investigate the transplacental transport of BPA, its alternatives, and parabens, and to study their relation to fetal steroidogenesis. BPA, BPS, BPF, BPAF, methylparaben, ethylparaben, propylparaben, butylparaben, benzylparaben and 15 steroids including estrogens, corticoids, androgens and immunomodulatory ones were determined in 27 maternal (37th week of gestation) and cord plasma samples using liquid chromatography - tandem mass spectrometry methods. The statistical evaluation of the results showed significantly higher levels of BPA (p=0.0455) in cord plasma compared to maternal plasma. The results from multiple regression models investigated that in cord plasma, methylparaben, propylparaben and the sum of all measured parabens were inversely associated with testosterone levels. To our best knowledge, this study is the first attempt to determine the levels of alternative bisphenols in the maternal and cord blood, and also the first study reporting the simultaneous detection of bisphenols, parabens, and steroids in these biological fluids. Our study confirmed the transplacental transport of BPA, with likely accumulation in the fetal compartment. The negative association of cord blood parabens and testosterone levels highlights their possible risks, especially for the development of male fetuses. Acknowledgements: This work was supported by the project MH CR 17-30528 A from the Czech Health Research Council, MH CZ - DRO (Institute of Endocrinology - EÚ, 00023761) and by the MEYS CR (OP RDE, Excellent research - ENDO.CZ).

Keywords: bisphenol, endocrine disruptor, paraben, pregnancy, steroid

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Authors: Vera Lukasova, Eva Filova, Jana Dankova, Vera Sovkova, Matej Daniel, Michala Rampichova

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Proper bone implants should promote fast adhesion of cells, stimulate cell differentiation and support the formation of bone tissue. Nowadays titanium is used as a biocompatible material capable of bone tissue integration. This study was focused on comparison of bioactive properties of two titanium alloys - beta titanium alloy Ti36Nb6Ta and standard medical titanium alloy Ti6A14V. The advantage of beta titanium alloy Ti36Nb6Ta is mainly that this material does not contain adverse elements like vanadium or aluminium. Titanium alloys were sterilized in ethanol, placed into 48 well plates and seeded with porcine mesenchymal stem cells. Cells were cultivated for 14 days in standard growth cultivation media with osteogenic supplements. Cell metabolic activity was quantified using MTS assay (Promega). Cell adhesion on day 1 and cell proliferation on further days were verified immunohistochemically using beta-actin monoclonal antibody and secondary antibody conjugated with AlexaFluor®488. Differentiation of cells was evaluated using alkaline phosphatase assay. Additionally, gene expression of collagen I was measured by qRT-PCR. Porcine mesenchymal stem cells adhered and spread well on beta titanium alloy Ti36Nb6Ta on day 1. During the 14 days’ time period the cells were spread confluently on the surface of the beta titanium alloy Ti36Nb6Ta. The metabolic activity of cells increased during the whole cultivation period. In comparison to standard medical titanium alloy Ti6A14V, we did not observe any differences. Moreover, the expression of collagen I gene revealed no statistical differences between both titanium alloys. Therefore, a beta titanium alloy Ti36Nb6Ta promotes cell adhesion, metabolic activity, proliferation and collagen I expression equally to standard medical titanium alloy Ti6A14V. Thus, beta titanium is a suitable material that provides sufficient biocompatible properties. This project was supported by the Czech Science Foundation: grant No. 16-14758S.

Keywords: beta titanium alloy, biocompatibility, differentiation, mesenchymal stem cells

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Authors: Helena Bolini, Erick Esmerino, Adriano Cruz, Juliana Paixao

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The currently concern for health has increased demand for low-calorie ingredients and functional foods as probiotics. Understand the reasons that infer on food choice, besides a challenging task, it is important step for development and/or reformulation of existing food products. The use of appropriate multivariate statistical techniques, such as External Preference Map (PrefMap), associated with regression by Partial Least Squares (PLS) can help in determining those factors. Thus, this study aimed to determine, through PLS regression analysis, the sensory attributes considered drivers of liking in probiotic petit suisse cheeses, strawberry flavor, sweetened with different sweeteners. Five samples in same equivalent sweetness: PROB1 (Sucralose 0.0243%), PROB2 (Stevia 0.1520%), PROB3 (Aspartame 0.0877%), PROB4 (Neotame 0.0025%) and PROB5 (Sucrose 15.2%) determined by just-about-right and magnitude estimation methods, and three commercial samples COM1, COM2 and COM3, were studied. Analysis was done over data coming from QDA, performed by 12 expert (highly trained assessors) on 20 descriptor terms, correlated with data from assessment of overall liking in acceptance test, carried out by 125 consumers, on all samples. Sequentially, results were submitted to PLS regression using XLSTAT software from Byossistemes. As shown in results, it was possible determine, that three sensory descriptor terms might be considered drivers of liking of probiotic petit suisse cheese samples added with sweeteners (p<0.05). The milk flavor was noticed as a sensory characteristic with positive impact on acceptance, while descriptors bitter taste and sweet aftertaste were perceived as descriptor terms with negative impact on acceptance of petit suisse probiotic cheeses. It was possible conclude that PLS regression analysis is a practical and useful tool in determining drivers of liking of probiotic petit suisse cheeses sweetened with artificial and natural sweeteners, allowing food industry to understand and improve their formulations maximizing the acceptability of their products.

Keywords: acceptance, consumer, quantitative descriptive analysis, sweetener

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Authors: Vandana Mishra, Niladri Sekhar Dash, Jayshree Charkraborty

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This present paper focuses on the application of corpus linguistics techniques for critical discourse analysis (CDA) of Hindi newspapers. While Corpus linguistics is the study of language as expressed in corpora (samples) of 'real world' text, CDA is an interdisciplinary approach to the study of discourse that views language as a form of social practice. CDA has mainly been studied from a qualitative perspective. However, we can say that recent studies have begun combining corpus linguistics with CDA in analyzing large volumes of text for the study of existing power relations in society. The corpus under our study is also of a sizable amount (1 million words of Hindi newspaper texts) and its analysis requires an alternative analytical procedure. So, we have combined both the quantitative approach i.e. the use of corpus techniques with CDA’s traditional qualitative analysis. In this context, we have focused on the Keyword Analysis Sorting Concordance Lines of the selected Keywords and calculating collocates of the keywords. We have made use of the Wordsmith Tool for all these analysis. The analysis starts with identifying the keywords in the political news corpus when compared with the main news corpus. The keywords are extracted from the corpus based on their keyness calculated through statistical tests like chi-squared test and log-likelihood test on the frequent words of the corpus. Some of the top occurring keywords are मोदी (Modi), भाजपा (BJP), कांग्रेस (Congress), सरकार (Government) and पार्टी (Political party). This is followed by the concordance analysis of these keywords which generates thousands of lines but we have to select few lines and examine them based on our objective. We have also calculated the collocates of the keywords based on their Mutual Information (MI) score. Both concordance and collocation help to identify lexical patterns in the political texts. Finally, all these quantitative results derived from the corpus techniques will be subjectively interpreted in accordance to the CDA’s theory to examine the ways in which political news discourse produces social and political inequality, power abuse or domination.

Keywords: critical discourse analysis, corpus linguistics, Hindi newspapers, power relations

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Authors: Andy S.K. Cheng, Samuel Leung, Cindy Kwok, Hector Tsang

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Background: Telephone counselling is one of the essential interventions that can be found in most of the Employee Assistance Programs (EAP). The purposes of this study were to (1) explore the trend of the telephone counselling from 2003-2016 in Hong Kong; (2) explore which EAP issue requires more follow-up; and 3) examine the relationship between the EAP issues and demographic data such as gender and job ranking. Method: Date of EAP services usage was collected from EAP providers in Hong Kong during 2003-2016. EAP issues were categorized into two domains, namely workplace issues and personal issues. Each domain has 12 sub-categories. Two hypotheses were formulated in this study (1) there was a gender difference in EAP issues and the follow-up hours; and (2) there was a significant difference between job ranking, EAP issues and follow-up hours. Results: A total of eight hundred and ninety-three valid cases were identified for analysis. Of them, three hundred and forty-three cases sought for follow-up. The duration of follow-up by hours was calculated for each of the follow-up cases. The results of the study shows that the top three workplace issues that required the longest duration of follow-up were (1) workload, (2) supervisor-subordinate relationship; and (3) team member’s relationship. On the other hand, the top three personal issues that required the longest duration of follow-up were (1) parenting/parent-child relationship, (2) family care, and (3) marital relationship. Two-way ANOVA was performed to compare the total follow-up hours (excluding first intake) between gender and EAP issues. There was no statistical significance for gender (p =.891), but a statistically significant main effect for EAP issues (p <.001) was found. Post-hoc analysis (Tukey’s test) showed that total follow-up hour in personal issues was statistically significant higher than that in handling workplace issues (p <.001). However, there was no statistically significant interaction effect between gender and EAP issues (p=.879) and between job ranking and EAP issues (p=.843). Conclusion: Telephone counselling is a very common intervention in addressing EAP issues arising from workplace and personal level in Hong Kong. It was frequently used to handle interpersonal relationships and the service usage was independent of gender and job ranking.

Keywords: employee assistance program, follow-up time, interpersonal relationships, telephone counselling

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Authors: Maria A. Castillo H., Andres R. Leandro, Jose F. Bienvenido B.

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In 2015, Guatemala officially adopted the Sustainable Development Goals (SDG) according to the 2030 Agenda agreed by the United Nations Organization. In 2016, these objectives and goals were reviewed, and the National Priorities were established within the K'atún 2032 National Development Plan. In 2019 and 2021, progress was evaluated with 120 defined indicators, and the need to improve quality and availability of statistical data necessary for the analysis of sustainability indicators was detected, so the values to be reached in 2024 and 2032 were adjusted. The need for greater agricultural technology is one of the priorities established within SDG 2 "Zero Hunger". Within this area, protected agricultural production provides greater productivity throughout the year, reduces the use of chemical products to control pests and diseases, reduces the negative impact of climate and improves product quality. During the crisis caused by Covid-19, there was an increase in exports of fruits and vegetables produced in greenhouses from Guatemala. However, this information has not been considered in the 2021 revision of the Plan. The objective of this study is to evaluate the information available on Greenhouse Agricultural Production and its integration into the Sustainability Indicators for Guatemala. This study was carried out in four phases: 1. Analysis of the Goals established for SDG 2 and the indicators included in the K'atún Plan. 2. Analysis of Environmental, Social and Economic Indicator Models. 3. Definition of territorial levels in 2 geographic scales: Departments and Municipalities. 4. Diagnosis of the available data on technological agricultural production with emphasis on Greenhouses at the 2 geographical scales. A summary of the results is presented for each phase and finally some recommendations for future research are added. The main contribution of this work is to improve the available data that allow the incorporation of some agricultural technology indicators in the established goals, to evaluate their impact on Food Security and Nutrition, Employment and Investment, Poverty, the use of Water and Natural Resources, and to provide a methodology applicable to other production models and other geographical areas.

Keywords: greenhouses, protected agriculture, sustainable indicators, Guatemala, sustainability, SDG

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Authors: Stelvin Sebastian, Andriya Annie Tom, Joyalanna Babu, Merin Joshy

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Introduction: The worldwide increase in the use of antibiotics in poultry and livestock industry to treat and prevent bacterial diseases and as growth promoters in feeds has led to the problem of development of antibiotic resistance both in animals and human population. Aim: To study the pattern of antibiotic use and prevalence of multidrug-resistant Escherichia coli in poultry chickens in selected farms in Muvattupuzha and to compare the spread of multidrug-resistant bacteria from poultry environment to UTI patients. Methodology: Two farms from each of 6 localities in Muvattupuzha were selected. A questionnaire on the pattern of antibiotic use and various farming practices were surveyed from farms. From each farm, 60samples of fresh fecal matter, litter from inside, litter from the outside shed, agricultural soil and control soil were collected, and antimicrobial susceptibility testing of E. coli was done. Antibiogram of UTI patients was collected from the secondary care hospital included in the study, and those were compared with resistance patterns of poultry samples. Results: From survey response antibiotics such as ofloxacin, enrofloxacin, levofloxacin, ciprofloxacin, colistin, ceftriaxone, neomycin, cephalexin, and oxytetracycline were used for treatment and prevention of infections in poultry. 31of 48 samples (51.66%) showed E. coli growth. 7 of 15 antibiotics (46.6%) showed resistance. Ampicillin, amoxicillin, meropenem, tetracycline showed 100% resistance to all samples. Statistical analysis confirmed similar resistance pattern in the poultry environment and UTI patients for antibiotics such as ampicillin, amoxicillin, amikacin, and ofloxacin. Conclusion: E. coli were resistant not only to extended-spectrum beta-lactams but also to carbapenems, which may be disseminated to the environment where litter was used as manure. This may due to irrational use of antibiotics in chicken or from their use in poultry feed as growth promoters. The study concludes the presence of multidrug-resistant E.coli in poultry and its spread to environment and humans, which may cause potentially serious implications for human health.

Keywords: multidrug resistance, escherichia coli, urinary tract infection, poultry

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Authors: Suraj Mehrotra

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The stock market is a volatile, bustling marketplace that is a cornerstone of economics. It defines whether companies are successful or in spiral. A thorough understanding of it is important - many companies have whole divisions dedicated to analysis of both their stock and of rivaling companies. Linking the world of finance and artificial intelligence (AI), especially the stock market, has been a relatively recent development. Predicting how stocks will do considering all external factors and previous data has always been a human task. With the help of AI, however, machine learning models can help us make more complete predictions in financial trends. Taking a look at the stock market specifically, predicting the open, closing, high, and low prices for the next day is very hard to do. Machine learning makes this task a lot easier. A model that builds upon itself that takes in external factors as weights can predict trends far into the future. When used effectively, new doors can be opened up in the business and finance world, and companies can make better and more complete decisions. This paper explores the various techniques used in the prediction of stock prices, from traditional statistical methods to deep learning and neural networks based approaches, among other methods. It provides a detailed analysis of the techniques and also explores the challenges in predictive analysis. For the accuracy of the testing set, taking a look at four different models - linear regression, neural network, decision tree, and naïve Bayes - on the different stocks, Apple, Google, Tesla, Amazon, United Healthcare, Exxon Mobil, J.P. Morgan & Chase, and Johnson & Johnson, the naïve Bayes model and linear regression models worked best. For the testing set, the naïve Bayes model had the highest accuracy along with the linear regression model, followed by the neural network model and then the decision tree model. The training set had similar results except for the fact that the decision tree model was perfect with complete accuracy in its predictions, which makes sense. This means that the decision tree model likely overfitted the training set when used for the testing set.

Keywords: machine learning, testing set, artificial intelligence, stock analysis

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Authors: Saidasanov Saidazal Shokhmurodovich, Topolnickiy Orest Zinovyevich, Afaunova Olga Arturovna

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Relevance: Bilateral congenital cleft is one of the most complex forms of all clefts, which makes it difficult to choose a surgical method of treatment. During primary operations to close the hard and soft palate, there is a shortage of soft tissues and their lack during standard uranoplasty, and these factors aggravate the period of rehabilitation of patients. Materials and methods: The results of surgical treatment of children with bilateral cleft, who underwent uranoplasty using a flap from the tongue, were analyzed. The study used methods: clinical and statistical, which allowed us to solve the tasks, based on the principles of evidence-based medicine. Results and discussion: in our study, 15 patients were studied, who underwent surgical treatment in the following volume: uranoplasty using a flap from the tongue in two stages. Of these, 9 boys and 6 girls aged 2.5 to 6 years. The first stage was surgical treatment in the volume: veloplasty. The second stage was a surgical intervention in volume: uranoplasty using a flap from the tongue. In all patients, the width of the cleft ranged from 1.6-2.8 cm. All patients in this group were orthodontically prepared. Using this method, the surgeon can achieve the following results: maximum narrowing of the palatopharyngeal ring, long soft palate, complete closure of the hard palate, alveolar process, and the mucous membrane of the nasal cavity is also sutured, which creates good conditions for the next stage of osteoplastic surgery. Based on the result obtained, patients have positive results of working with a speech therapist. In all patients, the dynamics were positive without complications. Conclusions: Based on our observation, tongue flap uranoplasty is one of the effective techniques for patients with wide clefts of the hard and soft palate. The use of a flap from the tongue makes it possible to reduce the number of repeated reoperations and improve the quality of social adaptation of this group of patients, which is one of the important stages of rehabilitation. Upon completion of the stages of rehabilitation, all patients had the maximum improvement in functional, anatomical and social indicators.

Keywords: congenital cleft lips and palate, bilateral cleft, child surgery, maxillofacial surgery

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Authors: Mohammed Y. Elsherbeny, Mohamed Salama, Ahmed Lotfy, Hossam Fareed, Nora Mohammed

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Background: Developmental neurotoxicity (DNT) entails the toxic effects imparted by various chemicals on brain during the early childhood when human brains are vulnerable during this period. DNT study in vivo cannot determine the effect of the neurotoxins, as it is not applicable, so using the neurosphere cells of lab animals as an alternative is applicable and time saving. Methods: Cell culture: Rat neural progenitor cells were isolated from rat embryos’ brain. The cortices were aseptically dissected out and the tissues were triturated. The dispersed tissues were allowed to settle. The supernatant was then transferred to a fresh tube and centrifuged. The pellet was placed in Hank’s balanced salt solution and cultured as free-floating neurospheres in proliferation medium. Differentiation was initiated by growth factor withdrawal in differentiation medium and plating onto a poly-d-lysine/ laminin matrix. Chemical Exposure: Neurospheres were treated for 2 weeks with papaverine in proliferation medium. Proliferation analyses: Spheres were cultured. After 0, 4, 5, 11 and 14 days, sphere size was determined by software analyses (CellProfiler, version 2.1; Broad Institute). Diameter of each neurosphere was measured and exported to excel file further to statistical analysis. Viability test: Trypsin-EDTA solution was added to neurospheres to dissociate neurospheres into single cells suspension, then viability evaluated by the Trypan Blue exclusion test. Result: As regards proliferation analysis and percentage of viable cells of papaverin treated groups: There was no significant change in cells proliferation compared to control at 0, 4, 5, 11 and 14 days with concentrations 1, 5 and 10 µM of papaverine, but there is a significant change in cell viability compared to control after 1 week and 2 weeks with the same concentrations of papaverine. Conclusion: Papaverine has toxic effect on viability of neural cell, not on their proliferation, so it may produce focal neural lesions not growth morphological changes.

Keywords: developmental neurotoxicity, neurotoxin, papaverine, neuroshperes

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Authors: Maffo Maffo Nicole Liliane, Mounmemi Kpoumie Hubert, Libalah Moses, Ouandji Angele, Zapfack Louis

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Forest degradation causes biodiversity and carbon loss and thus indirectly contributes to climate change. In order to assess the contribution of forests to climate change mitigation, the present study was conducted in the Ngambe-Ndom-Nyanon Communal Forest with the main objective of assessing the floristic diversity and estimating the carbon stock in the different reservoirs of the said forest. Nine plots of 2000 m² each were installed in 3 TOSs of the forest (young secondary forests, gallery forests and fallow lands) with a total area of 18,000 m² or 1,8 ha. All trees with a Diameter at Breast Height (DBH) ≥ 5 cm were inventoried at 1.30 m from the ground in each plot. Species richness, floristic diversity indices, and structural parameters were studied. 1542 trees divided into 162 species, 122 genera and 44 families were identified. The most important families were listed: Myristicaceae (30.22%), Apocynaceae (25.20%), Fabaceae (24.41%), Euphorbiaceae (22.91%) and Phyllanthaceae (20.23%). The richest genera are: Cola, Macaranga, Oncoba (4 species each); the genera Diospyros, Trichilia, Vitex and Zanthoxylum (3 species each). The ecologically important species within the forest studied are: Funtumia africana (26.14%), Coelocaryon preussii (18.46%), Pycnanthus angolensis (15.57%), Tabernaemontana crassa (14.85%) and Olax subscorpioidea (13.04%). Assessment of carbon stocks in the six forest reservoirs studied (living trees and roots, understorey, dead wood, litter and rootlets) shows that they vary according to the land-use types. It is 119.41 t.C.ha-¹ in gallery forest, 115.2 t.C.ha-¹ in young secondary forest and 90.56 t.C.ha-¹ in fallow. The Wilcoxon statistical test shows that the carbon in the young secondary forest is identical to that in the fallow, which is identical to the carbon in the gallery forest. At the individual species level, the largest diameter class [25-35[ sequesters the most carbon (232.94 tC/ha). This work shows that the quantity of carbon sequestered by a biotope is a function of the age of the stand.

Keywords: floristic diversity, carbon stocks, evergreen forests, communal forest, Ngambé-Ndom-Nyanon

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Authors: Joshua W. Edefo, Shafiul Azam, Murray D. Smith

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Introduction: In April 2022, the Welsh Government introduced the six goals for urgent and emergency care programs. One of these goals was to provide access to clinically safe alternatives, leading to the establishment of the Same Day Emergency Care (SDEC) program. The SDEC initiative aims to offer viable options that maintain patient safety while avoiding unnecessary hospital stays. The aim of the study is to determine the duration of patient stay in SDEC and compare it with that of Emergency department (ED) stay to ascertain if one of the objectives of SDEC is achieved. Methods: Patient stays and attendance datasets were constructed from Withybush SDEC and ED patient records. These records were provided by Hywel Dda University Health Board Informatics. Some hypothetical pathways were identified, notably SDEC visits involving a single attendance and ED visits then immediately transferred to SDEC. Descriptive statistics were used to summarise the data, and hypothesis tests for mean differences used the student t-test. Propensity scoring was employed to match a set of ED patient stays to SDEC patient stays which were then used to determine the average treatment effect (ATE) to compare durations of stay in SDEC with ED. Regression methods were used to model the natural logarithm of the duration of SDEC attendance, and the level of statistical significance was set to 0.05. Results: SDEC visits involving a single attendance (170 of 384; 44.3%) is the most frequently observed pathway with patient length of stay at 256 minutes (95%CI 237.4 - 275.1). The next most frequently observed pathway of patient stay was SDEC attendance after presenting to ED (80 of 384; 20.8%) and gave the length of stay of 440 minutes (95%CI 351.6 - 529.2). Time spent in this pathway significantly increased by 184 minutes (95%CI 118.0 - 250.2, support for no difference p<0.001) compared to the most seen pathway. When SDEC data were compared with ED, the estimate for the ATE from SDEC single attendance was -272 minutes (95%CI -334.1 - -210.5; p<0.001), while that of ED then SDEC pathway was -50.6 min (95%CI -182.7-81.5; p=0.453). Conclusion: When patients are admitted to SDEC and successfully discharged, their stays are significantly shorter, approximately 4.5 hours, compared to patients who spend their entire stay in the Emergency Department. That difference vanishes when the patient stay includes a period spent previously in ED before transfer to SDEC.

Keywords: attendance, emergency-department, patient-stay, same-day-emergency-care

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Authors: Dorottya Horváth, Andras Lang, Diana Varro-Horvath

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This research activity and study is part of a major research effort to gain an integrative, neuropsychological, and personality psychological understanding of Attention Deficit Hyperactivity Disorder (ADHD) and thus improve the specification of diagnostic and therapeutic care. In the past, the neuropsychology section has investigated working memory, executive function, attention, and behavioural manifestations in children. Currently, we are looking for personality psychological protective factors for ADHD and its symptomatic exacerbation. We hypothesise that secure attachment, adaptive emotion regulation, and high resilience are protective factors. The aim of this study is to measure and report the results of a Hungarian sample of the Cognitive Emotion Regulation Questionnaire for Children (CERQ-k) because before studying groups with different developmental differences, it is essential to know the average scores of groups with neurotypical devel-opment. Until now, there was no Hungarian version of the above test, so we used our own translation. This questionnaire has been developed to assess children's thoughts after experiencing negative life events. It consists of 4-4 items per subscale, for a total of 36 items. The response categories for each item range from 1 (almost never) to 5 (almost always). The subscales were self-blame, blaming others, acceptance, planning, positive refocusing, rumination or thought-focusing, positive reappraisal, putting into perspective, and catastrophizing. The data for this study were collected from 120 children aged 9-14 years. It was analysed using descriptive statistical analysis, where the mean and standard deviation values for each age group, as well as the Cronbach's alpha value, were significant in testing the reliability of the questionnaire. The results showed that the questionnaire is a reliable and valid measuring instrument also on a Hungarian sample. These developments and results will allow the use of a version of the Cognitive Emotion Regulation Questionnaire for children in Hungarian and pave the way for the study of different developmental groups such as children with learning disabilities and/or with ADHD.

Keywords: neurotypical development, emotion regulation, negative life events, CERQ-k, Hungarian average scores

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Authors: Daniel Gebreslassie Mekonnen

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Effective leadership has a crucial role in excelling in the overall success of a school. Today there is much attention given to school leadership, without which schools can never be successful. Therefore, the study was aimed at investigating the role of principals’ leadership styles and their emotional intelligence on the work motivation and job performance of teachers in Addis Ababa, Ethiopia. The study, thus, first examined the relationship between work motivation and job performance of the teachers in relation to the perceived leadership styles and emotional intelligence of principals. Second, it assessed the mean differences and the interaction effects of the principals’ leadership styles and emotional intelligence on the work motivation and job performance of the teachers. Finally, the study investigated whether principals’ leadership styles and emotional intelligence variables had significantly predicted the work motivation and job performance of teachers. As a means, a quantitative approach and descriptive research design were employed to conduct the study. Three hundred sixteen teachers were selected using multistage sampling techniques as participants of the study from the eight sub-cities in Addis Ababa. The main data-gathering instruments used in this study were the path-goal leadership questionnaire, emotional competence inventory, multidimensional work motivation scale, and job performance appraisal scale. The quantitative data were analyzed by using the statistical techniques of Pearson–product-moment correlation analysis, two-way analysis of variance, and stepwise multiple regression analysis. Major findings of the study have revealed that the work motivation and job performance of the teachers were significantly correlated with the perceived participative leadership style, achievement-oriented leadership style, and emotional intelligence of principals. Moreover, the emotional intelligence of the principals was found to be the best predictor of the teachers’ work motivation, whereas the achievement-oriented leadership style of the principals was identified as the best predictor of the job performance of the teachers. Furthermore, the interaction effects of all four path-goal leadership styles vis-a-vis the emotional intelligence of the principals have shown differential effects on the work motivation and job performance of teachers. Thus, it is reasonable to conclude that emotional intelligence is the sine qua non of effective school leadership. Hence, this study would be useful for policymakers and educational leaders to come up with policies that would enhance the role of emotional intelligence on school leadership effectiveness. Finally, pertinent recommendations were drawn from the findings and the conclusions of the study.

Keywords: emotional intelligence, leadership style, job performance, work motivation

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Authors: Randa Alharbi, Vladislav Vyshemirsky

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Systems biology is an important field in science which focuses on studying behaviour of biological systems. Modelling is required to produce detailed description of the elements of a biological system, their function, and their interactions. A well-designed model requires selecting a suitable mechanism which can capture the main features of the system, define the essential components of the system and represent an appropriate law that can define the interactions between its components. Complex biological systems exhibit stochastic behaviour. Thus, using probabilistic models are suitable to describe and analyse biological systems. Continuous-Time Markov Chain (CTMC) is one of the probabilistic models that describe the system as a set of discrete states with continuous time transitions between them. The system is then characterised by a set of probability distributions that describe the transition from one state to another at a given time. The evolution of these probabilities through time can be obtained by chemical master equation which is analytically intractable but it can be simulated. Uncertain parameters of such a model can be inferred using methods of Bayesian inference. Yet, inference in such a complex system is challenging as it requires the evaluation of the likelihood which is intractable in most cases. There are different statistical methods that allow simulating from the model despite intractability of the likelihood. Approximate Bayesian computation is a common approach for tackling inference which relies on simulation of the model to approximate the intractable likelihood. Particle Markov chain Monte Carlo (PMCMC) is another approach which is based on using sequential Monte Carlo to estimate intractable likelihood. However, both methods are computationally expensive. In this paper we discuss the efficiency and possible practical issues for each method, taking into account the computational time for these methods. We demonstrate likelihood-free inference by performing analysing a model of the Repressilator using both methods. Detailed investigation is performed to quantify the difference between these methods in terms of efficiency and computational cost.

Keywords: Approximate Bayesian computation(ABC), Continuous-Time Markov Chains, Sequential Monte Carlo, Particle Markov chain Monte Carlo (PMCMC)

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Authors: Syed Afrozuddin Ahmed, Junaid Saghir Siddiqi, Sabah Quaiser

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Various studies have reported that global warming causes unstable climate and many serious impact to physical environment and public health. The increasing incidence of dengue incidence is now a priority health issue and become a health burden of Pakistan. In this study it has been investigated that spatial pattern of environment causes the emergence or increasing rate of dengue fever incidence that effects the population and its health. The climatic or environmental structure data and the Dengue Fever (DF) data was processed by coding, editing, tabulating, recoding, restructuring in terms of re-tabulating was carried out, and finally applying different statistical methods, techniques, and procedures for the evaluation. Five climatic variables which we have studied are precipitation (P), Maximum temperature (Mx), Minimum temperature (Mn), Humidity (H) and Wind speed (W) collected from 1980-2012. The dengue cases in Karachi from 2010 to 2012 are reported on weekly basis. Principal component analysis is applied to explore the climatic variables and/or the climatic (structure) which may influence in the increase or decrease in the number of dengue fever cases in Karachi. PC1 for all the period is General atmospheric condition. PC2 for dengue period is contrast between precipitation and wind speed. PC3 is the weighted difference between maximum temperature and wind speed. PC4 for dengue period contrast between maximum and wind speed. Negative binomial and Poisson regression model are used to correlate the dengue fever incidence to climatic variable and principal component score. Relative humidity is estimated to positively influence on the chances of dengue occurrence by 1.71% times. Maximum temperature positively influence on the chances dengue occurrence by 19.48% times. Minimum temperature affects positively on the chances of dengue occurrence by 11.51% times. Wind speed is effecting negatively on the weekly occurrence of dengue fever by 7.41% times.

Keywords: principal component analysis, dengue fever, negative binomial regression model, poisson regression model

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Authors: Ahlem Bouziri, Chiraz Latiri, Eric Gaussier

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The steady growth in the size of textual document collections is a key progress-driver for modern information retrieval techniques whose effectiveness and efficiency are constantly challenged. Given a user query, the number of retrieved documents can be overwhelmingly large, hampering their efficient exploitation by the user. In addition, retaining only relevant documents in a query answer is of paramount importance for an effective meeting of the user needs. In this situation, the query expansion technique offers an interesting solution for obtaining a complete answer while preserving the quality of retained documents. This mainly relies on an accurate choice of the added terms to an initial query. Interestingly enough, query expansion takes advantage of large text volumes by extracting statistical information about index terms co-occurrences and using it to make user queries better fit the real information needs. In this respect, a promising track consists in the application of data mining methods to extract dependencies between terms, namely a generic basis of association rules between terms. The key feature of our approach is a better trade off between the size of the mining result and the conveyed knowledge. Thus, face to the huge number of derived association rules and in order to select the optimal combination of query terms from the generic basis, we propose to model the problem as a classification problem and solve it using a supervised learning algorithm such as SVM or k-means. For this purpose, we first generate a training set using a genetic algorithm based approach that explores the association rules space in order to find an optimal set of expansion terms, improving the MAP of the search results. The experiments were performed on SDA 95 collection, a data collection for information retrieval. It was found that the results were better in both terms of MAP and NDCG. The main observation is that the hybridization of text mining techniques and query expansion in an intelligent way allows us to incorporate the good features of all of them. As this is a preliminary attempt in this direction, there is a large scope for enhancing the proposed method.

Keywords: supervised leaning, classification, query expansion, association rules

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Authors: Frederick M. Dumisani Xaba, Nokuthula G. Khanyile

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There is a growing demand for greater accountability, transparency and ethical conduct based on sound governance principles in the developing world. Funders, donors and sponsors are increasingly demanding more transparency, better value for money and adherence to good governance standards. The drive towards improved governance measures is largely influenced by the need to ‘plug the leaks’, deal with malfeasance, engender greater levels of accountability and good governance and to ultimately attract further funding or investment. This is the case with the Non-Profit Organizations (NPOs) in South Africa in general, and in the province of KwaZulu-Natal in particular. The paper draws from the good governance theory, stakeholder theory and systems thinking to critically examine the requirements for good governance for the NPO sector from a theoretical and legislative point and to systematically looks at the contours of governance currently among the NPOs. The paper did this through the rigorous examination of the vignettes of cases of governance among selected NPOs based in KwaZulu-Natal. The study used qualitative and quantitative research methodologies through document analysis, literature review, semi-structured interviews, focus groups and statistical analysis from the various primary and secondary sources. It found some good cases of good governance but also found frightening levels of poor governance. There was an exponential growth of NPOs registered during the period under review, equally so there was an increase in cases of non-compliance to good governance practices. NPOs operate in an increasingly complex environment. There is contestation for influence and access to resources. Stakeholder management is poorly conceptualized and executed. Recognizing that the NPO sector operates in an environment characterized by complexity, constant changes, unpredictability, contestation, diversity and divergent views of different stakeholders, there is a need to apply legislative and systems thinking approaches to strengthen governance to withstand this turbulence through a capacity development model that recognizes these contextual and environmental challenges.

Keywords: good governance, non-profit organizations, stakeholder theory, systems theory

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Authors: L. Musak, J. Valachova, T. Vasicko, O. Osina

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Stainless steel is resistant to electrochemical corrosion by passivation. Welders are greatly exposed to welding fumes of toxic metals, which added to this steel. The content of chromium (Cr) is above 11.5%, Ni and Mo from 2 to 6.5%. The aim of the study was the evaluation of occupational exposure to Cr, chromosome analysis and valuation of individual susceptibility polymorphism of gene CCND1 c.870 G>A. The exposed group was consisted from 117 welders of stainless steels. The average age was 38.43 years and average exposure time 7.14 years. Smokers represented 40.17%. The control group consisted of 123 non-exposed workers with an average age of 39.74 years and time employment 16.67 years. Smokers accounted for 22.76%. Analysis of Cr in blood and urine was performed by atomic absorption spectrophotometry (AAS Varian SpectraAA 30P) with electrothermal decomposition of the sample in the graphite furnace. For the evaluation of chromosomal aberrations (CA) cytogenetic analysis of peripheral blood lymphocytes was used. Gene polymorphism was determined by PCR-RFLP reaction using appropriate primers and restriction enzymes. For statistic analysis the Mann-Whitney U-test was used. The mean Cr level in blood of exposed group was 0.095 µmol/l (0.019 min - max 0.504). No value exceeds the average normal value. The mean value Cr in urine was 7.9 µmol/mol creatinine (min 0.026 to max 19.26). The total number of CA was 1.86% in compared to 1.70% controls. (CTA-type 0.90% vs. 0.80% and CSA-type 0.96% vs. 0.90%). In the number of total CA statistical difference was observed between smokers and non-smokers of exposed group (S-1.57% vs. NS-2.04%, P<0.05). In CCND1 gene polymorphisms was observed the increasing of the total CA with wild-type allele (WT) via heterozygous to the VAR genotype (1.44% <1.82% <2.13%). A statistically higher incidence of CTA-type aberrations in variant genotypes between exposed and control groups was observed (1.22% vs. 0.59%, P <0.05). The work place is usually higher source of exposure to harmful factors. Workers need consistent and frequent health control. In assessing the risk of adverse effects of metals it is important to consider their persistence, behavior and bioavailability. Prolonged exposure to carcinogens may not manifest symptoms of poisoning, but delayed effects may occur, which resulted in a higher incidence of malignant tumors.

Keywords: CCND1, genotoxicity, polymorphism, stainless steel, welders

Procedia PDF Downloads 333