Search results for: age grouping

Authors: Narek Margaryan, Zhozef Panosyan

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Due to their unique properties, carbon nanofilms have become the object of general attention and intensive research. In this case it plays a very important role to study surface properties of these films. It is also important to study processes of forming of this films, which is accompanied by a process of self-organization at the nano and micro levels. For more detailed investigation, we examined diamond-like carbon (DLC) layers deposited by chemical vapor deposition (CVD) method on Ge substrate and hydro-generated grapheme layers obtained on surface of colloidal solution using grouping method. In this report surface transformation of these CVD nanolayers is studied by atomic force microscopy (AFM) upon deposition time. Also, it can be successfully used to study surface properties of self-assembled grapheme layers. In turn, it is possible to sketch out their boundary line, which enables one to draw an idea of peculiarities of formation of these layers. Images obtained by AFM are investigated as a mathematical set of numbers and fractal and roughness analysis were done. Fractal dimension, Regne’s fractal coefficient, histogram, Fast Fourier transformation, etc. were obtained. The dependence of fractal parameters on the deposition duration for CVD films and on temperature of solution tribolayers was revealed. As an important surface parameter for our carbon films, surface energy was calculated as function of Regne’s fractal coefficient. Surface potential was also measured with Kelvin probe method using semi-contacting AFM. The dependence of surface potential on the deposition duration for CVD films and on temperature of solution for hydro-generated graphene was found as well. Results obtained by fractal analysis method was related with purly esperimental results for number of samples.

Keywords: nanostructured films, self-assembled grapheme, diamond-like carbon, surface potential, Kelvin probe method, fractal analysis

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Authors: Jing-Ma

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Digital transformation (DT) is an important way for manufacturing enterprises to shape new competitive advantages, and how to choose an effective DT strategy is crucial for enterprise growth and sustainable development. Rooted in strategic change theory, this paper incorporates the dimensions of managers' digital cognition, organizational conditions, and external environment into the same strategic analysis framework and integrates the dynamic QCA method and PSM method to study the antecedent grouping of the DT strategy mode of manufacturing enterprises and its impact on corporate profitability based on the data of listed manufacturing companies in China from 2015 to 2019. We find that the synergistic linkage of different dimensional elements can form six equivalent paths of high-level DT, which can be summarized as the proactive change mode of resource-capability dominated as well as adaptive response mode such as industry-guided resource replenishment. Capacity building under complex environments, market-industry synergy-driven, forced adaptation under peer pressure, and the managers' digital cognition play a non-essential but crucial role in this process. Except for individual differences in the market industry collaborative driving mode, other modes are more stable in terms of individual and temporal changes. However, it is worth noting that not all paths that result in high levels of DT can contribute to enterprise profitability, but only high levels of DT that result from matching the optimization of internal conditions with the external environment, such as industry technology and macro policies, can have a significant positive impact on corporate profitability.

Keywords: digital transformation, strategy mode, enterprise profitability, dynamic QCA, PSM approach

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Wern Lin Yeo, Choo Kim Tan, Sook Ling Lew

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Mathematics anxiety refers to the feeling of anxious when one having difficulties in solving mathematical problem. Mathematics anxiety is the most common type of anxiety among other types of anxiety which occurs among the students. However, level of anxiety among males and females are different. There were few past study were conducted to determine the relationship of anxiety and gender but there were still did not have an exact results. Hence, the purpose of this study is to determine the relationship of anxiety level between male and female undergraduates at a private university in Malaysia. Convenient sampling method used in this study in which the students were selected based on the grouping assigned by the faculty. There were 214 undergraduates who registered the probability courses had participated in this study. Mathematics Anxiety Rating Scale (MARS) was the instrument used in study which used to determine students’ anxiety level towards probability. Reliability and validity of instrument was done before the major study was conducted. In the major study, students were given briefing about the study conducted. Participation of this study were voluntary. Students were given consent form to determine whether they agree to participate in the study. Duration of two weeks were given for students to complete the given online questionnaire. The data collected will be analyzed using Statistical Package for the Social Sciences (SPSS) to determine the level of anxiety. There were three anxiety level, i.e., low, average and high. Students’ anxiety level were determined based on their scores obtained compared with the mean and standard deviation. If the scores obtained were below mean and standard deviation, the anxiety level was low. If the scores were at below and above the mean and between one standard deviation, the anxiety level was average. If the scores were above the mean and greater than one standard deviation, the anxiety level was high. Results showed that both of the gender were having average anxiety level. Males having high frequency of three anxiety level which were low, average and high anxiety level as compared to females. Hence, the mean values obtained for males (M = 3.62) was higher than females (M = 3.42). In order to be significant of anxiety level among the gender, the p-value should be less than .05. The p-value obtained in this study was .117. However, this value was greater than .05. Thus, there was no significant difference of anxiety level among the gender. In other words, there was no relationship of anxiety level with the gender.

Keywords: anxiety level, gender, mathematics anxiety, probability and statistics

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Authors: Chi-Hsuan Cheng

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This research aims to evaluate public-private partnerships against cyberattacks by comparing the UK and Taiwan. First, the study analyses major cyberattacks and factors influencing cybersecurity in both countries. Second, it assesses the effectiveness of current cyber defence strategies in combating cyberattacks by comparing the approaches taken in the UK and Taiwan, while also evaluating the cyber resilience of both nations. Lastly, the research evaluates existing public-private partnerships by comparing those in the UK and Taiwan, and proposes recommendations for enhancing cooperation and collaboration mechanisms in tackling cyberattacks. Grounded theory serves as the core research method. Theoretical sampling is used to recruit participants in both the UK and Taiwan, including investigators, police officers, and professionals from cybersecurity firms. Semi-structured interviews are conducted in English in the UK and Mandarin in Taiwan, recorded with consent, and pseudonymised for privacy. Data analysis involves open coding, grouping excerpts into codes, and categorising codes. Axial coding connects codes into categories, leading to the development of a codebook. The process continues iteratively until theoretical saturation is reached. Finally, selective coding identifies the core topic, evaluating public-private cooperation against cyberattacks and its implications for social and policing strategies in the UK and Taiwan, which highlights the current status of the cybersecurity industry, governmental plans for cybersecurity, and contributions to cybersecurity from both government sectors and cybersecurity firms, with a particular focus on public-private partnerships. In summary, this research aims to offer practical recommendations to law enforcement, private sectors, and academia for reflecting on current strategies and tailoring future approaches in cybersecurity

Keywords: cybersecurity, cybercrime, public private partnerships, cyberattack

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Authors: Liane Marcia Freitas Silva, Fernando Augusto Silva Marins, Maria Silene Alexandre Leite

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The adoption of a network structure, like in the supply chains, favors the increase of dependence between companies and, by consequence, their vulnerability. Environment disasters, sociopolitical and economical events, and the dynamics of supply chains elevate the uncertainty of their operation, favoring the occurrence of events that can generate break up in the operations and other undesired consequences. Thus, supply chains are exposed to various risks that can influence the profitability of companies involved, and there are several previous studies that have proposed risk classification models in order to categorize the risks and to manage them. The objective of this paper is to analyze and discuss thirty of these risk classification models by means a theoretical survey. The research method adopted for analyzing and discussion includes three phases: The identification of the types of risks proposed in each one of the thirty models, the grouping of them considering equivalent concepts associated to their definitions, and, the analysis of these risks groups, evaluating their similarities and differences. After these analyses, it was possible to conclude that, in fact, there is more than thirty risks types identified in the literature of Supply Chains, but some of them are identical despite of be used distinct terms to characterize them, because different criteria for risk classification are adopted by researchers. In short, it is observed that some types of risks are identified as risk source for supply chains, such as, demand risk, environmental risk and safety risk. On the other hand, other types of risks are identified by the consequences that they can generate for the supply chains, such as, the reputation risk, the asset depreciation risk and the competitive risk. These results are consequence of the disagreements between researchers on risk classification, mainly about what is risk event and about what is the consequence of risk occurrence. An additional study is in developing in order to clarify how the risks can be generated, and which are the characteristics of the components in a Supply Chain that leads to occurrence of risk.

Keywords: sisks classification, survey, supply chain management, theoretical discussion

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Authors: Omur F. Karakullukcu, Bilal Okudan, Yusuf Can

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The aim of this study is to analyze sports managers’ managerial competence levels and job satisfaction’s correlation with career satisfaction. In the study, it has also been analyzed if there is any significant difference in sports managers’ managerial competence, job and career satisfaction in terms of gender, age, duty status, year of service and level of education. 256 sports managers, who work at department of sports service’s central and field organization at least as a chief in the manager position, have been chosen with random sampling method and they have voluntarily participated in the study. In the study, the managerial competence scale which was developed by Cetinkaya (2009), job satisfaction scale developed by Weiss at al.(1967) and Career Satisfaction Scale developed by Vatansever (2008) have been used as a data collection tool. The questionnaire form used as a data collection tool in the study includes a personal information form consisting of 5 questions; questioning gender, age, duty status, years of service and level of education. In the study, pearson correlation analysis has been used for defining the correlation of managerial competence levels, job satisfaction, and career satisfaction levels of sports managers. T-test analysis for binary grouping and anova analysis for more than binary groups have been used in the level of self-efficacy, collective and managerial competence in terms of the participants’ duty status, year of service and level of education. According to the research results, it has been found that there is a positive correlation between sports managers’ managerial competence levels, job satisfaction, and career satisfaction levels. Also, the results show that there is a significant difference in managerial competence levels, job satisfaction and career satisfaction of sports managers in terms of duty status, year of service and level of education; however, the results reveal that there is no significant difference in terms of age groups and gender.

Keywords: sports manager, managerial competence, job satisfaction, career satisfaction

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Authors: Ana Belon Hercilla

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The study is developed in “Reactivos Jeans” company, in the city of Arequipa, whose main business is the laundry of garments at an industrial level. In 2012 the company initiated actions to provide a dry cleaning service of alpaca fiber garments, recognizing that this item is in a growth phase in Peru. Additionally this company took the initiative to use a new greenwashing technology which has not yet been developed in the country. To accomplish this, a redesign of both the process and the plant layout was required. For redesigning the plant, the methodology used was the Systemic Layout Planning, allowing this study divided into four stages. First stage is the information gathering and evaluation of the initial situation of the company, for which a description of the areas, facilities and initial equipment, distribution of the plant, the production process and flows of major operations was made. Second stage is the development of engineering techniques that allow the logging and analysis procedures, such as: Flow Diagram, Route Diagram, DOP (process flowchart), DAP (analysis diagram). Then the planning of the general distribution is carried out. At this stage, proximity factors of the areas are established, the Diagram Paths (TRA) is developed, and the Relational Diagram Activities (DRA). In order to obtain the General Grouping Diagram (DGC), further information is complemented by a time study and Guerchet method is used to calculate the space requirements for each area. Finally, the plant layout redesigning is presented and the implementation of the improvement is made, making it possible to obtain a model much more efficient than the initial design. The results indicate that the implementation of the new machinery, the adequacy of the plant facilities and equipment relocation resulted in a reduction of the production cycle time by 75.67%, routes were reduced by 68.88%, the number of activities during the process were reduced by 40%, waits and storage were removed 100%.

Keywords: redesign, time optimization, industrial laundry, greenwashing

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Authors: Babak Bahri, Fatemeh Yassaee Meybodi, Changiz Eslahchi

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In the pursuit of effective cancer therapies, the exploration of combinatorial drug regimens is crucial to leverage synergistic interactions between drugs, thereby improving treatment efficacy and overcoming drug resistance. However, identifying synergistic drug pairs poses challenges due to the vast combinatorial space and limitations of experimental approaches. This study introduces ClusterSyn, a machine learning (ML)-powered framework for classifying anti-cancer drug synergy scores. ClusterSyn employs a two-step approach involving drug clustering and synergy score prediction using a fully connected deep neural network. For each cell line in the training dataset, a drug graph is constructed, with nodes representing drugs and edge weights denoting synergy scores between drug pairs. Drugs are clustered using the Markov clustering (MCL) algorithm, and vectors representing the similarity of drug pairs to each cluster are input into the deep neural network for synergy score prediction (synergy or antagonism). Clustering results demonstrate effective grouping of drugs based on synergy scores, aligning similar synergy profiles. Subsequently, neural network predictions and synergy scores of the two drugs on others within their clusters are used to predict the synergy score of the considered drug pair. This approach facilitates comparative analysis with clustering and regression-based methods, revealing the superior performance of ClusterSyn over state-of-the-art methods like DeepSynergy and DeepDDS on diverse datasets such as Oniel and Almanac. The results highlight the remarkable potential of ClusterSyn as a versatile tool for predicting anti-cancer drug synergy scores.

Keywords: drug synergy, clustering, prediction, machine learning., deep learning

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Authors: David Ahiamadia, Ramilan Thiagarajah, Peter Tozer

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In Sub Saharan Africa, farm typologies have been used as a practical way to address heterogeneity among farming systems which is mostly done by grouping farms into subsets with similar characteristics. Due to the complexity in farming systems among farm households, it is not possible to formulate policy recommendations for individual farmers. As a result, this study employs a multivariate statistical approach using Principal Component Analysis (PCA) coupled with cluster analysis to reduce heterogeneity in a 615-household data set from the Africa Rising Baseline Evaluation Survey for 25 farming communities in Northern Ghana. Variables selected for the study were mostly socio-economic, production potential, production intensity, production orientation, crop diversity, food security, resource endowments, and climate risk variables. To avoid making some individuals in the subpopulation worse off when aclimate risk intervention is broadly implemented, the findings of the study also account for diversity in climate risk perception among the different farm types identified and their response strategies towards climate risk. The climate risk variables used in this study involve the most severeclimate shock types perceived by the household, household response to climate shock type, and reason for crop failure (i.e., maize, rice, and groundnut). Eventually, four farm types, each with an adequate level of homogeneity in climate risk perception and response strategies, were identified. Farm type 1 and 3 were wealthy with a lower degree of climate risk perception compared to farm type 2 and 4. Also, relatively wealthy farmers used asset liquidation as a climate risk management strategy, whereas poor farmers resorted to engaging in spiritual activities such as prayers, sacrifices, and divine consultations.

Keywords: smallholder, households, climate risk, variables, typologies

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Authors: Manana Lobzhanidze, Marine Kobalava, Lali Chikviladze

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The global pandemic crisis has had a significant impact on educational migration, substantially limiting young people’s access to education abroad. Therefore, it became necessary to study the economic, demographic, social, cultural and other factors associated with educational migration, to identify the economic and political challenges of educational migration and to develop recommendations. The aim of the research is to study the effects of the atypical crisis on educational migration and to make recommendations on effective migration opportunities based on the identification of economic and policy challenges in this area. Bibliographic research is used to assess the effects of the impact of the atypical crisis on educational migration presented in the papers of various scholars. Against the background of the restrictions imposed during the COVID19 pandemic, migration rates have been analyzed, endogenous and exogenous factors affecting educational migration have been identified. Quantitative and qualitative research of students and graduates of TSU Economics and Business Faculty is conducted, the results have been processed by SPSS program, the factors hindering educational migration and the challenges have been identified. The Internet and digital technologies have been shown to play a vital role in alleviating the challenges posed by the COVID-19 pandemic, however, lack of Internet access and limited financial resources have played a disruptive role in the educational migration process. The analysis of quantitative research materials revealed the problems of educational migration caused by the atypical crisis, while some issues were clarified during the focus group meetings. The following theoretical-methodological approaches were used during the research: a bibliographic research, analysis, synthesis, comparison, selection-grouping are used; Quantitative and qualitative research has been carried out, the results have been processed by SPSS program. The article presents the consequences of the atypical crisis for educational migration, identifies the main economic and policy challenges in the field of educational migration, and develops appropriate recommendations to overcome them.

Keywords: educational migration, atypical crisis, economic-political challenges, educational migration factors

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Authors: Krizette Ladera

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Fathers are there not only to provide the financial stability of a family but a father is also there to provide the love and support that usually people would see as the mother’s responsibility. To describe the lived experiences and how fathers make sense of their lived experiences with their children who have cerebral palsy is the main objective of the study. A qualitative research using a thematic analysis was used for the study. The qualitative research focused on the personal narratives, self-report and expression of the participant’s memory in terms of how they tell their stories. The interpretative phenomenological analysis was used to focus on the experience of the participants on how they will describe their experiences, and to also add on that the IPA will also attempt to describe and explain the meaning of human experiences using interview, specifically on the father who have a child that suffers from cerebral palsy. For the sampling technique, the snowball technique was used to gather participants from the referral of other participants. The five non-randomly selected fathers will be served as the participants for the research. A self-made interview with an open-ended question was used as the research instrument; it includes profiling of the respondent as well as their experiences in taking care of their child that suffers from cerebral palsy. In analyzing a data, the researcher used the thematic analysis where in the interview was made into a transcript, then it was organized and divided themes. After that, the relations of each themes, was identified and it was later documented and translated into written text format using thematic grouping. Finally, the researcher analyzed each data according to its themes and put it in a table to be presented in the result section of the study And as for the result of the study, the researcher was able to come up with the four (4) main themes that most of the participants experienced and those are: The experiences in finding out about the condition of the Child, disclosing the condition of the child to the family and its emotional effect, The experiences of living the day of day realities in providing the physical, financial, emotional and a well balanced environment to the child, and the religious perspectives of the fathers. Along with those four (4) themes comes the subtheme which explains the themes in a more detailed explanation.

Keywords: cerebral palsy, children, fathers, lived experiences

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Authors: Nino Paresashvili, Nino Abesadze

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The modern world faces huge challenges. Globalization changed the socio-economic conditions of many countries. The current processes in the global environment have a different impact on countries with different cultures. However, an alleviation of poverty and improvement of living conditions is still the basic challenge for the majority of countries, because much of the population still lives under the official threshold of poverty. It is very important to stimulate youth employment. In order to prepare young people for the labour market, it is essential to provide them with the appropriate professional skills and knowledge. It is necessary to plan efficient activities for decreasing an unemployment rate and for developing the perfect mechanisms for regulation of a labour market. Such planning requires thorough study and analysis of existing reality, as well as development of corresponding mechanisms. Statistical analysis of unemployment is one of the main platforms for regulation of the labour market key mechanisms. The corresponding statistical methods should be used in the study process. Such methods are observation, gathering, grouping, and calculation of the generalized indicators. Unemployment is one of the most severe socioeconomic problems in Georgia. According to the past as well as the current statistics, unemployment rates always have been the most problematic issue to resolve for policy makers. Analytical works towards to the above-mentioned problem will be the basis for the next sustainable steps to solve the main problem. The results of the study showed that the choice of young people is not often due to their inclinations, their interests and the labour market demand. That is why the wrong professional orientation of young people in most cases leads to their unemployment. At the same time, it was shown that there are a number of professions in the labour market with a high demand because of the deficit the appropriate specialties. To achieve healthy competitiveness in youth employment, it is necessary to formulate regional employment programs with taking into account the regional infrastructure specifications.

Keywords: unemployment, analysis, methods, tendencies, regulation mechanisms

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Authors: Ramin Ghasemi Shayan, Morteza Janebifam

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Tumors are regularly inhomogeneous. Provincial varieties in death, metabolic action, multiplication and body part are watched. There’s expanding proof that strong tumors may contain subpopulations of cells with various genotypes and phenotypes. These unmistakable populaces of malignancy cells can connect during a serious way and may contrast in affectability to medications. Most tumors show organic heterogeneity1–3 remembering heterogeneity for genomic subtypes, varieties inside the statement of development variables and genius, and hostile to angiogenic factors4–9 and varieties inside the tumoural microenvironment. These can present as contrasts between tumors in a few people. for instance, O6-methylguanine-DNA methyltransferase, a DNA fix compound, is hushed by methylation of the quality advertiser in half of glioblastoma (GBM), adding to chemosensitivity, and improved endurance. From the outset, there includes been specific enthusiasm inside the usage of dissemination weighted imaging (DWI) and dynamic complexity upgraded MRI (DCE-MRI). DWI sharpens MRI to water dispersion inside the extravascular extracellular space (EES) and is wiped out with the size and setup of the cell populace. Additionally, DCE-MRI utilizes dynamic obtaining of pictures during and after the infusion of intravenous complexity operator. Signal changes are additionally changed to outright grouping of differentiation permitting examination utilizing pharmacokinetic models. PET scan modality gives one of a kind natural particularity, permitting dynamic or static imaging of organic atoms marked with positron emanating isotopes (for example, 15O, 18F, 11C). The strategy is explained to a colossal radiation portion, which points of confinement rehashed estimations, particularly when utilized together with PC tomography (CT). At long last, it's of incredible enthusiasm to quantify territorial hemoglobin state, which could be joined with DCE-CT vascular physiology estimation to create significant experiences for understanding tumor hypoxia.

Keywords: heterogeneity, computerized tomography scan, magnetic resonance imaging, PET

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Authors: Magdalena Bury-Kaminska, Aneta Szudy-Szczyrek, Aleksandra Nowaczynska, Olga Jankowska-Lecka, Marek Hus, Klaudia Kot

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Introduction: The aim of the research was to determine the changes in cognitive functioning in patients with plasma cell myeloma by comparing patients’ state before the treatment and during chemotherapy as well as to determine the biological factors that can be used to predict patients’ cognitive state. Methods: The patients underwent the research procedure twice: before chemotherapy and after 4-6 treatment cycles. A psychological test and measurement of the following biological variables were carried out: TNF-α (tumor necrosis factor), IL-6 (interleukin 6), IL-10 (interleukin 10), BDNF (brain-derived neurotrophic factor). The following research methods were implemented: the Montreal Cognitive Assessment (MoCA), Battery of Tests for Assessing Cognitive Functions PU1, experimental and clinical trials based on the Choynowski’s Memory Scale, Stroop Color-Word Interference Test (SCWT), depression measurement questionnaire. Results: The analysis of the research showed better cognitive functions of patients during chemotherapy in comparison to the phase before it. Moreover, neurotrophin BDNF allows to predict the level of selected cognitive functions (semantic fluency and execution control) already at the diagnosis stage. After 4-6 cycles, it is also possible to draw conclusions concerning the extent of working memory based on the level of BDNF. Cytokine TNF-α allows us to predict the level of letter fluency during anti-cancer treatment. Conclusions: It is possible to presume that BDNF has a protective influence on patients’ cognitive functions and working memory and that cytokine TNF-α co-occurs with a diminished execution control and better material grouping in terms of phonological fluency. Acknowledgment: This work was funded by the National Science Center in Poland [grant no. 2017/27/N/HS6/02057.

Keywords: chemobrain, cognitive impairment, non−central nervous system cancers, hematologic diseases

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Authors: Espinosa Carlos, Nobrega Doris

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Children are at high risk for lead (Pb) exposure. The objective of this study was to identify risk factors that contribute to high blood lead (PbB) levels in Venezuelan children. The concentration of PbB was determined in 60 children (ages 4-9 years old), coming from the Michelena sector, Valencia District, Carabobo State. The relationship between these concentrations and socio-economical parameters (A: high quality life; B: fair quality life; C: critic poverty), Pb levels of faucet water (Pb-water) and dust Pb levels of floor (Pb-dust) of their houses, was established. Living areas were classified according to sectors and socio-economical status. Forty [40=66.7%] children resulted with PbB levels above the permissible concentration (LAPC). Average PbB was not significantly higher than the permissible levels. Odds ratio proved that children from status C are 7.28 times more likely to have LAPC of PbB than the ones coming from A or B. Thirty-four percent (34%) of the children with LAPC come from status C which could be considered the most critical status from the exposure risk point of view. The 76,3% of the sampled houses reported VSLP of Pb-water, being the Pb-water average in 35 ± 25.5 ug/L. This average significantly went superior to the permissible limit established by Venezuela and international organisms (10 ug/L). When grouping the results of PbB and Pb-water by sex, were that 50,8% of the children who presented/displayed VSLP of Pb-water and PbB. Was a significant relation (p ≤ 0.05), between masculine sex and the VSLP of PbB and Pb-water (x² = 3,672). In relation to the Pb-Dust analyses, were not statistically significant differences with respect to their permissible limit value (40 ug/pie²). This study shows that by correlating geographical and health data, we can identify 'high risk' areas, leading to a proactive public health action. The results of this study are excellent, in order to take preventive measures for the care from the health. Later studies are suggested predicting main to determine of more conclusive form of levels elevated of PbB in the investigated population.

Keywords: demographic, lead, risk, socio-economical status

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Authors: Gloria Chen

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When offering conventional level-appropriate ESL classes for adults is not feasible, a multilevel adult ESL class can be formed to benefit those who need to learn English for daily function. This paper examines the rationale, the process, the contents, and the outcomes of a multilevel ESL class for adults. The action research discusses a variety of assessments, lesson plans, teaching strategies that facilitate lifelong language learning. In small towns where adult ESL learners are only a handful, often advanced students and inexperienced students have to be placed in one class. Such class might not be viewed as desirable, but with on-going assessments, careful lesson plans, and purposeful strategies, a multilevel ESL class for adults can overcome the obstacles and help learners to reach a higher level of English proficiency. This research explores some hand-on strategies, such as group rotating, cooperative learning, and modifying textbook contents for practical purpose, and evaluate their effectiveness. The data collected in this research include Needs Assessment (beginning of class term), Mid-term Self-Assessment (5 months into class term), End-of-term Student Reflection (10 months into class), and End-of-term Assessment from the Instructor (10 months into class). A descriptive analysis of the data explains the practice of this particular learning community, and reveal the areas for improvement and enrichment. This research answers the following questions: (1) How do the assessments positively help both learners and instructors? (2) How do the learning strategies prepare students to become independent, life-long English learners? (3) How do materials, grouping, and class schedule enhance the learning? The result of the research contributes to the field of teaching and learning in language, not limited in English, by (a) examining strategies of conducting a multilevel adult class, (b) involving adult language learners with various backgrounds and learning styles for reflection and feedback, and (c) improving teaching and learning strategies upon research methods and results. One unique feature of this research is how students can work together with the instructor to form a learning community, seeking and exploring resources available to them, to become lifelong language learners.

Keywords: adult language learning, assessment, multilevel, teaching strategies

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Authors: Anderson S. Fonseca, Italo F. S. Da Silva, Robert D. A. Santos, Mayara G. Da Silva, Pedro H. C. Vieira, Antonio M. S. Sobrinho, Victor H. B. Lemos, Petterson S. Diniz, Anselmo C. Paiva, Eliana M. G. Monteiro

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In Brazil, the National Electric Energy Agency (ANEEL) establishes that electrical energy companies are responsible for measuring and billing their customers. Among these regulations, it’s defined that a company must bill your customers within 27-33 days. If a relocation or a change of period is required, the consumer must be notified in writing, in advance of a billing period. To make it easier to organize a workday’s measurements, these companies create a reading plan. These plans consist of grouping customers into reading groups, which are visited by an employee responsible for measuring consumption and billing. The creation process of a plan efficiently and optimally is a capacitated clustering problem with constraints related to homogeneity and compactness, that is, the employee’s working load and the geographical position of the consuming unit. This process is a work done manually by several experts who have experience in the geographic formation of the region, which takes a large number of days to complete the final planning, and because it’s human activity, there is no guarantee of finding the best optimization for planning. In this paper, the GBKMeans method presents a technique based on K-Means and genetic algorithms for creating a capacitated cluster that respects the constraints established in an efficient and balanced manner, that minimizes the cost of relocating consumer units and the time required for final planning creation. The results obtained by the presented method are compared with the current planning of a real city, showing an improvement of 54.71% in the standard deviation of working load and 11.97% in the compactness of the groups.

Keywords: capacitated clustering, k-means, genetic algorithm, districting problems

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Authors: M. Lobzhanidze, N. Damenia

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The article analyzes the current structural changes in the economy of Georgia, liberalization and integration processes of the economy. In accordance with this analysis, the peculiarities and the problems of youth employment are revealed. In the paper, the Georgian labor market and its contradictions are studied. Based on the analysis of materials, the socio-economic losses caused by the long-term and mass unemployment of young people are revealed, the objective and subjective circumstances of getting higher education are studied. The youth employment and unemployment rates are analyzed. Based on the research, the factors that increase unemployment are identified. According to the analysis of the youth employment, it has appeared that the unemployment share in the number of economically active population has increased in the younger age group. It demonstrates the high requirements of the labour market in terms of the quality of the workforce. Also, it is highlighted that young people are exposed to a highly paid job. The following research methods are applied in the presented paper: statistical (selection, grouping, observation, trend, etc.) and qualitative research (in-depth interview), as well as analysis, induction and comparison methods. The article presents the data by the National Statistics Office of Georgia and the Ministry of Agriculture of Georgia, policy documents of the Parliament of Georgia, scientific papers by Georgian and foreign scientists, analytical reports, publications and EU research materials on similar issues. The work estimates the students and graduates employment problems existing in the state development strategy and priorities. The measures to overcome the challenges are defined. The article describes the mechanisms of state regulation of youth employment and the ways of improving this regulatory base. As for major findings, it should be highlighted that the main problems are: lack of experience and incompatibility of youth qualification with the requirements of the labor market. Accordingly, it is concluded that the unemployment rate of young people in Georgia is increasing.

Keywords: migration of youth, youth employment, migration management, youth employment and unemployment

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Authors: Angela Odero, Chrysoula Karathanasi, Michèle Baumann

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Integration of foreign communities has been a forefront issue in Luxembourg for some time now. The country’s continued progress depends largely on the successful integration of immigrants. The aim of our study was to analyze factors which intervene in the course of integration of Non-EU citizens through the discourse of Non-EU citizens residing in Luxembourg, who have signed the Welcome and Integration Contract (CAI). The two-year contract offers integration services to assist foreigners in getting settled in the country. Semi-structured focus group discussions with 50 volunteers were held in English, French, Spanish, Serbo-Croatian or Chinese. Participants were asked to talk about their integration experiences. Recorded then transcribed, the transcriptions were analyzed with the help of NVivo 10, a qualitative analysis software. A systematic and reiterative analysis of decomposing and reconstituting was realized through (1) the identification of predetermined categories (difficulties, challenges and integration needs) (2) initial coding – the grouping together of similar ideas (3) axial coding – the regrouping of items from the initial coding in new ways in order to create sub-categories and identify other core dimensions. Our results show that intervening factors include language acquisition, professional career and socio-cultural activities or events. Each of these factors constitutes different components whose weight shifts from person to person and from situation to situation. Connecting these three emergent factors are two elements essential to the success of the immigrant’s integration – the role of time and deliberate effort from the immigrants, the community, and the formal institutions charged with helping immigrants integrate. We propose a theoretical model where the factors described may be classified in terms of how they predispose, facilitate, and / or reinforce the process towards a successful integration. Measures currently in place propose one size fits all programs yet integrative measures which target the family unit and those customized to target groups based on their needs would work best.

Keywords: integration, integration services, non-eu citizens, qualitative analysis, third country nationals

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Authors: Johanna Bapela, Heino Heyman, Marion Meyer

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Regardless of the significant advances accomplished in reducing the burden of malaria and other tropical diseases in recent years, malaria remains a major cause of mortality in endemic countries. This is especially the case in sub-Saharan Africa where 99% of the estimated global malaria deaths occurs on an annual basis. The emergence of resistant Plasmodium species and the lack of diversified chemotherapeutic agents provide the rationale for bioprospecting for antiplasmodial scaffolds. Crude extracts from twenty indigenous antimalarial plant species were screened for antimalarial activity and then subjected to 1H NMR-based metabolomic analysis. Ten plant extracts exhibited significant in vitro antiplasmodial activity (IC50 ≤ 5 µg/ml). The Principal Component Analysis (PCA) of the acquired 1H NMR spectra could not separate the analyzed plant extracts according to the detected antiplasmodial bioactivity. Application of supervised Orthogonal Projections to Latent Structures–Discriminant Analysis (OPLS-DA) to the 1H NMR profiles resulted in a discrimination pattern that could be correlated to bioactivity. A contribution plot generated from the OPLS-DA scoring plot illustrated the classes of compounds responsible for the observed grouping. Given the preliminary in vitro results, Tabernaemontana elegans Stapf. (Apocynaceae) and Vangueria infausta Burch. subsp. infausta (Rubiaceae) were subjected to further phytochemical investigations. Two indole alkaloids, dregamine and tabernaemontanine possessing antiplasmodial activity were isolated from T. elegans. Two compounds were isolated from V. infausta subsp. infausta and identified as friedelin (IC50 = 3.01 µg/ml) and morindolide (IC50 = 18.5 µg/ml). While these compounds have been previously identified, this is the first account of their occurrence in the genus Vangueria and their antiplasmodial activity. Based on the results of the study, metabolomics can be used to globally identify classes of plant secondary metabolites that are responsible for antiplasmodial activity.

Keywords: ethnopharmacology, Malaria, medicinal plants, metabolomics

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Authors: Ismaila Olabisi Ogundiji, Hakeem Mayowa Olujide, Qasim Usamot

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The main reasons for site-specific management for agricultural inputs are to increase the profitability of crop production, to protect the environment and to improve products’ quality. Information about the variability of different soil attributes within a field is highly essential for the decision-making process. Lack of fast and accurate acquisition of soil characteristics remains one of the biggest limitations of precision agriculture due to being expensive and time-consuming. Adaptive sampling has been proven as an accurate and affordable sampling technique for planning within a field for site-specific management of agricultural inputs. This study employed spatial uncertainty of soil apparent electrical conductivity (ECa) estimates to identify adaptive re-survey areas in the field. The original dataset was grouped into validation and calibration groups where the calibration group was sub-grouped into three sets of different measurements pass intervals. A conditional simulation was performed on the field ECa to evaluate the ECa spatial uncertainty estimates by the use of the geostatistical technique. The grouping of high-uncertainty areas for each set was done using image segmentation in MATLAB, then, high and low area value-separate was identified. Finally, an adaptive re-survey was carried out on those areas of high-uncertainty. Adding adaptive re-surveying significantly minimized the time required for resampling whole field and resulted in ECa with minimal error. For the most spacious transect, the root mean square error (RMSE) yielded from an initial crude sampling survey was minimized after an adaptive re-survey, which was close to that value of the ECa yielded with an all-field re-survey. The estimated sampling time for the adaptive re-survey was found to be 45% lesser than that of all-field re-survey. The results indicate that designing adaptive sampling through spatial uncertainty models significantly mitigates sampling cost, and there was still conformity in the accuracy of the observations.

Keywords: soil electrical conductivity, adaptive sampling, conditional simulation, spatial uncertainty, site-specific management

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Authors: Sa’adu Mafara Abubakar, Muhammad Nuraddeen Danjuma, Adewole Tomiwa Adetunji, Richard Mundembe, Salisu Mohammed, Francis Bayo Lewu, Joseph I. Kiok

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Pearl millet is the most drought tolerant of all domesticated cereals, is cultivated extensively to feed millions of people who mainly live in hash agroclimatic zones. It serves as a major source of food for more than 40 million smallholder farmers living in the marginal agricultural lands of Northern Nigeria. Pearl millet grain is more nutritious than other cereals like maize, is also a principal source of energy, protein, vitamins, and minerals for millions of poorest people in the regions where it is cultivated. Pearl millet has recorded relatively little research attention compared with other crops and no sufficient work has analyzed its genetic diversity in north-western Nigeria. Therefore, this study was undertaken with the objectives to analyze the genetic diversity of pearl millet accessions using SSR marker and to analyze the extent of evolutionary relationship among pearl millet accessions at the molecular level. The result of the present study confirmed diversity among accessions of pearl millet in the study area. Simple Sequence Repeats (SSR) markers were used for genetic analysis and evolutionary relationship of the accessions of pearl millet. To analyze the level of genetic diversity, 8 polymorphic SSR markers were used to screen 69 accessions collected based on three maturity periods. SSR markers result reveal relationships among the accessions in terms of genetic similarities, evolutionary and ancestral origin, it also reveals a total of 53 alleles recorded with 8 microsatellites and an average of 6.875 per microsatellite, the range was from 3 to 9 alleles in PSMP2248 and PSMP2080 respectively. Moreover, both the factorial analysis and the dendrogram of phylogeny tree grouping patterns and cluster analysis were almost in agreement with each other that diversity is not clustering according to geographical patterns but, according to similarity, the result showed maximum similarity among clusters with few numbers of accessions. It has been recommended that other molecular markers should be tested in the same study area.

Keywords: pearl millet, genetic diversity, simple sequence repeat (SSR)

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Authors: Giorgi Gaganidze, Eter Kharaishvili

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The atypical crisis has created new challenges in the education system. Globally, including in Georgia, traditional methods of managing the education system have appeared particularly vulnerable. In addition, new opportunities for the introduction of innovative management of learning processes have emerged. The aim of the research is to identify the main challenges in the field of education management in the distance learning process in Georgia and to develop recommendations on the opportunities for the introduction of innovative management. The paper substantiates the relevance of the research, in particular, it notes that in Georgia, as in many countries, distance learning in higher education institutions became particularly crucial during the Covid-19 pandemic. What is more, theoretical and practical aspects of distance learning are less proven, and a number of problems have been identified in the field of education management in Georgia. The article justifies the need to study the challenges of distance learning for the formation of a sustainable education management system. Within the bibliographic research, there are grouped the opinions of researchers on the modern problems of distance learning and education management in the article. Based on scientific papers, the expectations formed about distance learning are studied, and the main focus is on the existing problems of education management during the atypical crisis. The article discusses the forms and opportunities of distance learning in different countries, evaluates different approaches and challenges to distance learning, and justifies the role of education management in effective distance learning. The paper uses various theoretical-methodological tools of research, including desk research on the research topic; Data selection-grouping, problem identification is carried out by analysis, synthesis, sampling, induction, and other methods;SWOT analysis is used to assess the strengths, weaknesses, opportunities, and threats of distance education and management; The level of student satisfaction with distance learning is determined through the Population-based / Census-based approach; The results of the research are processed by SPSS program. Quantitative research and semi-structured interviews with relevant focus groups were conducted to identify working directions for innovative management of distance learning and education. Research has shown that the demand for distance education is growing in Georgia, but the need to introduce innovative education management remains a particular challenge. Conclusions have been made on the introduction of innovative education management, and the relevant recommendations have been developed.

Keywords: distance learning, management challenges, education management, innovative management

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Authors: Ksenija Taški-Ajdukovic, Nevena Nagl, Živko Ćurčić, Dario Danojević

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Information about genetic diversity of sugar beet parental populations is of a great importance for hybrid breeding programs. The aim of this research was to evaluate genetic diversity among and within populations and lines of diploid sugar beet pollinators, by using SSR markers. As plant material were used eight pollinators originating from three USDA-ARS breeding programs and four pollinators from Institute of Field and Vegetable Crops, Novi Sad. Depending on the presence of self-fertility gene, the pollinators were divided into three groups: autofertile (inbred lines), autosterile (open-pollinating populations), and group with partial presence of autofertility gene. A total of 40 SSR primers were screened, out of which 34 were selected for the analysis of genetic diversity. A total of 129 different alleles were obtained with mean value 3.2 alleles per SSR primer. According to the results of genetic variability assessment the number and percentage of polymorphic loci was the maximal in pollinators NS1 and tester cms2 while effective number of alleles, expected heterozygosis and Shannon’s index was highest in pollinator EL0204. Analysis of molecular variance (AMOVA) showed that 77.34% of the total genetic variation was attributed to intra-varietal variance. Correspondence analysis results were very similar to grouping by neighbor-joining algorithm. Number of groups was smaller by one, because correspondence analysis merged IFVCNS pollinators with CZ25 into one group. Pollinators FC220, FC221 and C 51 were in the next group, while self-fertile pollinators CR10 and C930-35 from USDA-Salinas were separated. On another branch were self-sterile pollinators ЕL0204 and ЕL53 from USDA-East Lansing. Sterile testers cms1 and cms2 formed separate group. The presented results confirmed that SSR analysis can be successfully used in estimation of genetic diversity within and among sugar beet populations. Since the tested pollinator differed considering the presence of self-fertility gene, their heterozygosity differed as well. It was lower in genotypes with fixed self-fertility genes. Since the most of tested populations were open-pollinated, which rarely self-pollinate, high variability within the populations was expected. Cluster analysis grouped populations according to their origin.

Keywords: auto fertility, genetic diversity, pollinator, SSR, sugar beet

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Authors: Ana C. R. P. Ferreira, Adriano H. P. Pereira

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Given the frequent variation of mineral properties throughout the Araxá pyrochlore deposit, even if a good homogenization work has been carried out before feeding the processing plants, an operation with quality and performance’s high variety standard is expected. These results could be improved and standardized if the blend composition parameters that most influence the processing route are determined, and then the types of raw materials are grouped by them, finally presenting a great reference with operational settings for each group. Associating the physical and chemical parameters of a unit operation through benchmarking or even an optimal reference of metallurgical recovery and product quality reflects in the reduction of the production costs, optimization of the mineral resource, and guarantee of greater stability in the subsequent processes of the production chain that uses the mineral of interest. Conducting a comprehensive exploratory data analysis to identify which characteristics of the ore are most relevant to the process route, associated with the use of Machine Learning algorithms for grouping the raw material (ore) and associating these with reference variables in the process’ benchmark is a reasonable alternative for the standardization and improvement of mineral processing units. Clustering methods through Decision Tree and K-Means were employed, associated with algorithms based on the theory of benchmarking, with criteria defined by the process team in order to reference the best adjustments for processing the ore piles of each cluster. A clean user interface was created to obtain the outputs of the created algorithm. The results were measured through the average time of adjustment and stabilization of the process after a new pile of homogenized ore enters the plant, as well as the average time needed to achieve the best processing result. Direct gains from the metallurgical recovery of the process were also measured. The results were promising, with a reduction in the adjustment time and stabilization when starting the processing of a new ore pile, as well as reaching the benchmark. Also noteworthy are the gains in metallurgical recovery, which reflect a significant saving in ore consumption and a consequent reduction in production costs, hence a more rational use of the tailings dams and life optimization of the mineral deposit.

Keywords: mineral clustering, machine learning, process optimization, pyrochlore processing

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Authors: Reham Hajomer, Ikram Elsiddig, Amna Hamad

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Lepidium sativum (Garden Cress) belonging to Brassicaceae family is an annual herb locally known as El-rshad. In Ayurveda it is an important medicinal plant, traditionally used for the treatment of jaundice, liver problems, spleen diseases, gastrointestinal disorders, menstrual problems, fracture, arthritis, inflammatory conditions and for treatment of hypothyroidism. Hypothyroidism is a condition in which the thyroid gland does not produce enough thyroid hormones (Triiodithyronine T3 and Thyroxine T4) which are commonly caused by iodine deficiency. It’s divided into primary and secondary hypothyroidism, the primary caused by failure of thyroid function and secondary due to the failure of adequate thyroid-stimulating hormone (TSH) secretion from the pituitary gland or thyroid -releasing hormone (TRH) from the hypothalamus. The disease is most common in women over age 60. The objective regarding this study is to know whether Lepidium sativum would affect the level of thyroid hormones. The extract was prepared with 96% ethanol using Soxhlet apparatus. The anti-hypothyroidism activity was tested by using thirty male Wistar rats weighing (100-140 g) were used in the experiment. They were grouping into five groups, Group 1: Normal group= Administered only distilled water. Then 10 mg/kg Propylthiouracil was added to the drinking water of all other groups to induce hypothyroidism. Group 2: Negative control without any treatment; Group 3: Test group= treated with oral administration of 500mg/kg extract; Group 4: treated with oral administration of 250mg/kg of the extract; Group 5: Standard group (positive control) = treated with intraperitoneal Levothyroxine. All rats were incubated for 20 days at animal house with room temperature of proper ventilation provided with standard diet. The result show that the Lepidium sativum extract was found to increases the T3 and T4 in the propylthiouracil induced rats with values (0.29 ng/dl T3 and 0.57 U T4) for the 500mg/kg and (0.27 ng/dl T3 and 0.517 U T4) for the 250mg/kg in comparison with standard with values (0.241 ng/dl T3 and 0.516 U T4) so that Lepidium sativum can be stimulatory to thyroid function and possess significant anti-hypothyroidism effect with p-values ranges from (0.000006*-0.893472). In conclusion, from results obtained, Lepidium sativum plant extract was found to posses anti-hypothyroidism effects so its act as an agent that stimulates thyroid hormone secretion.

Keywords: anti-hypothyroidism, extract, lepidium, sativum

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Authors: Esra Polat

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Partial Least Squares Discriminant Analysis (PLSDA) is a statistical method for classification and consists a classical Partial Least Squares Regression (PLSR) in which the dependent variable is a categorical one expressing the class membership of each observation. PLSDA can be applied in many cases when classical discriminant analysis cannot be applied. For example, when the number of observations is low and when the number of independent variables is high. When there are missing values, PLSDA can be applied on the data that is available. Finally, it is adapted when multicollinearity between independent variables is high. The aim of this study is to determine the economic and/or demographic indicators, which are effective in grouping the 28 European Union (EU) member countries and 7 candidate countries (including potential candidates Bosnia and Herzegovina (BiH) and Kosova) by using the data set obtained from database of the World Bank for 2014. Leaving the political issues aside, the analysis is only concerned with the economic and demographic variables that have the potential influence on country’s eligibility for EU entrance. Hence, in this study, both the performance of PLSDA method in classifying the countries correctly to their pre-defined groups (candidate or member) and the differences between the EU countries and candidate countries in terms of these indicators are analyzed. As a result of the PLSDA, the value of percentage correctness of 100 % indicates that overall of the 35 countries is classified correctly. Moreover, the most important variables that determine the statuses of member and candidate countries in terms of economic indicators are identified as 'external balance on goods and services (% GDP)', 'gross domestic savings (% GDP)' and 'gross national expenditure (% GDP)' that means for the 2014 economical structure of countries is the most important determinant of EU membership. Subsequently, the model validated to prove the predictive ability by using the data set for 2015. For prediction sample, %97,14 of the countries are correctly classified. An interesting result is obtained for only BiH, which is still a potential candidate for EU, predicted as a member of EU by using the indicators data set for 2015 as a prediction sample. Although BiH has made a significant transformation from a war-torn country to a semi-functional state, ethnic tensions, nationalistic rhetoric and political disagreements are still evident, which inhibit Bosnian progress towards the EU.

Keywords: classification, demographic indicators, economic indicators, European Union, partial least squares discriminant analysis

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Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

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Authors: Oxana Lukoshus

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The methods of corpus linguistics, a well-established field of research, are being increasingly applied in cognitive linguistics. Corpora data are especially useful for different quantitative studies of grammatical and other aspects of language. The main objective of this paper is to demonstrate how present-day corpora can be applied in semantic studies in general and in semantic studies of adjectives in particular. Polysemantic adjectives have been the subject of numerous studies. But most of them have been carried out on dictionaries. Undoubtedly, dictionaries are viewed as one of the basic data sources, but only at the initial steps of a research. The author usually starts with the analysis of the lexicographic data after which s/he comes up with a hypothesis. In the research conducted three polysemantic synonyms true, loyal, faithful have been analyzed in terms of differences and similarities in their semantic structure. A corpus-based approach in the study of the above-mentioned adjectives involves the following. After the analysis of the dictionary data there was the reference to the following corpora to study the distributional patterns of the words under study – the British National Corpus (BNC) and the Corpus of Contemporary American English (COCA). These corpora are continually updated and contain thousands of examples of the words under research which make them a useful and convenient data source. For the purpose of this study there were no special needs regarding genre, mode or time of the texts included in the corpora. Out of the range of possibilities offered by corpus-analysis software (e.g. word lists, statistics of word frequencies, etc.), the most useful tool for the semantic analysis was the extracting a list of co-occurrence for the given search words. Searching by lemmas, e.g. true, true to, and grouping the results by lemmas have proved to be the most efficient corpora feature for the adjectives under the study. Following the search process, the corpora provided a list of co-occurrences, which were then to be analyzed and classified. Not every co-occurrence was relevant for the analysis. For example, the phrases like An enormous sense of responsibility to protect the minds and hearts of the faithful from incursions by the state was perceived to be the basic duty of the church leaders or ‘True,’ said Phoebe, ‘but I'd probably get to be a Union Official immediately were left out as in the first example the faithful is a substantivized adjective and in the second example true is used alone with no other parts of speech. The subsequent analysis of the corpora data gave the grounds for the distribution groups of the adjectives under the study which were then investigated with the help of a semantic experiment. To sum it up, the corpora-based approach has proved to be a powerful, reliable and convenient tool to get the data for the further semantic study.

Keywords: corpora, corpus-based approach, polysemantic adjectives, semantic studies

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