Search results for: panel data analysis
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 42458

Search results for: panel data analysis

37328 Design and Implementation a Virtualization Platform for Providing Smart Tourism Services

Authors: Nam Don Kim, Jungho Moon, Tae Yun Chung

Abstract:

This paper proposes an Internet of Things (IoT) based virtualization platform for providing smart tourism services. The virtualization platform provides a consistent access interface to various types of data by naming IoT devices and legacy information systems as pathnames in a virtual file system. In the other words, the IoT virtualization platform functions as a middleware which uses the metadata for underlying collected data. The proposed platform makes it easy to provide customized tourism information by using tourist locations collected by IoT devices and additionally enables to create new interactive smart tourism services focused on the tourist locations. The proposed platform is very efficient so that the provided tourism services are isolated from changes in raw data and the services can be modified or expanded without changing the underlying data structure.

Keywords: internet of things (IoT), IoT platform, serviceplatform, virtual file system (VSF)

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37327 Identification, Isolation and Characterization of Unknown Degradation Products of Cefprozil Monohydrate by HPTLC

Authors: Vandana T. Gawande, Kailash G. Bothara, Chandani O. Satija

Abstract:

The present research work was aimed to determine stability of cefprozil monohydrate (CEFZ) as per various stress degradation conditions recommended by International Conference on Harmonization (ICH) guideline Q1A (R2). Forced degradation studies were carried out for hydrolytic, oxidative, photolytic and thermal stress conditions. The drug was found susceptible for degradation under all stress conditions. Separation was carried out by using High Performance Thin Layer Chromatographic System (HPTLC). Aluminum plates pre-coated with silica gel 60F254 were used as the stationary phase. The mobile phase consisted of ethyl acetate: acetone: methanol: water: glacial acetic acid (7.5:2.5:2.5:1.5:0.5v/v). Densitometric analysis was carried out at 280 nm. The system was found to give compact spot for cefprozil monohydrate (0.45 Rf). The linear regression analysis data showed good linear relationship in the concentration range 200-5.000 ng/band for cefprozil monohydrate. Percent recovery for the drug was found to be in the range of 98.78-101.24. Method was found to be reproducible with % relative standard deviation (%RSD) for intra- and inter-day precision to be < 1.5% over the said concentration range. The method was validated for precision, accuracy, specificity and robustness. The method has been successfully applied in the analysis of drug in tablet dosage form. Three unknown degradation products formed under various stress conditions were isolated by preparative HPTLC and characterized by mass spectroscopic studies.

Keywords: cefprozil monohydrate, degradation products, HPTLC, stress study, stability indicating method

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37326 Changing the Landscape of Fungal Genomics: New Trends

Authors: Igor V. Grigoriev

Abstract:

Understanding of biological processes encoded in fungi is instrumental in addressing future food, feed, and energy demands of the growing human population. Genomics is a powerful and quickly evolving tool to understand these processes. The Fungal Genomics Program of the US Department of Energy Joint Genome Institute (JGI) partners with researchers around the world to explore fungi in several large scale genomics projects, changing the fungal genomics landscape. The key trends of these changes include: (i) rapidly increasing scale of sequencing and analysis, (ii) developing approaches to go beyond culturable fungi and explore fungal ‘dark matter,’ or unculturables, and (iii) functional genomics and multi-omics data integration. Power of comparative genomics has been recently demonstrated in several JGI projects targeting mycorrhizae, plant pathogens, wood decay fungi, and sugar fermenting yeasts. The largest JGI project ‘1000 Fungal Genomes’ aims at exploring the diversity across the Fungal Tree of Life in order to better understand fungal evolution and to build a catalogue of genes, enzymes, and pathways for biotechnological applications. At this point, at least 65% of over 700 known families have one or more reference genomes sequenced, enabling metagenomics studies of microbial communities and their interactions with plants. For many of the remaining families no representative species are available from culture collections. To sequence genomes of unculturable fungi two approaches have been developed: (a) sequencing DNA from fruiting bodies of ‘macro’ and (b) single cell genomics using fungal spores. The latter has been tested using zoospores from the early diverging fungi and resulted in several near-complete genomes from underexplored branches of the Fungal Tree, including the first genomes of Zoopagomycotina. Genome sequence serves as a reference for transcriptomics studies, the first step towards functional genomics. In the JGI fungal mini-ENCODE project transcriptomes of the model fungus Neurospora crassa grown on a spectrum of carbon sources have been collected to build regulatory gene networks. Epigenomics is another tool to understand gene regulation and recently introduced single molecule sequencing platforms not only provide better genome assemblies but can also detect DNA modifications. For example, 6mC methylome was surveyed across many diverse fungi and the highest among Eukaryota levels of 6mC methylation has been reported. Finally, data production at such scale requires data integration to enable efficient data analysis. Over 700 fungal genomes and other -omes have been integrated in JGI MycoCosm portal and equipped with comparative genomics tools to enable researchers addressing a broad spectrum of biological questions and applications for bioenergy and biotechnology.

Keywords: fungal genomics, single cell genomics, DNA methylation, comparative genomics

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37325 3D Classification Optimization of Low-Density Airborne Light Detection and Ranging Point Cloud by Parameters Selection

Authors: Baha Eddine Aissou, Aichouche Belhadj Aissa

Abstract:

Light detection and ranging (LiDAR) is an active remote sensing technology used for several applications. Airborne LiDAR is becoming an important technology for the acquisition of a highly accurate dense point cloud. A classification of airborne laser scanning (ALS) point cloud is a very important task that still remains a real challenge for many scientists. Support vector machine (SVM) is one of the most used statistical learning algorithms based on kernels. SVM is a non-parametric method, and it is recommended to be used in cases where the data distribution cannot be well modeled by a standard parametric probability density function. Using a kernel, it performs a robust non-linear classification of samples. Often, the data are rarely linearly separable. SVMs are able to map the data into a higher-dimensional space to become linearly separable, which allows performing all the computations in the original space. This is one of the main reasons that SVMs are well suited for high-dimensional classification problems. Only a few training samples, called support vectors, are required. SVM has also shown its potential to cope with uncertainty in data caused by noise and fluctuation, and it is computationally efficient as compared to several other methods. Such properties are particularly suited for remote sensing classification problems and explain their recent adoption. In this poster, the SVM classification of ALS LiDAR data is proposed. Firstly, connected component analysis is applied for clustering the point cloud. Secondly, the resulting clusters are incorporated in the SVM classifier. Radial basic function (RFB) kernel is used due to the few numbers of parameters (C and γ) that needs to be chosen, which decreases the computation time. In order to optimize the classification rates, the parameters selection is explored. It consists to find the parameters (C and γ) leading to the best overall accuracy using grid search and 5-fold cross-validation. The exploited LiDAR point cloud is provided by the German Society for Photogrammetry, Remote Sensing, and Geoinformation. The ALS data used is characterized by a low density (4-6 points/m²) and is covering an urban area located in residential parts of the city Vaihingen in southern Germany. The class ground and three other classes belonging to roof superstructures are considered, i.e., a total of 4 classes. The training and test sets are selected randomly several times. The obtained results demonstrated that a parameters selection can orient the selection in a restricted interval of (C and γ) that can be further explored but does not systematically lead to the optimal rates. The SVM classifier with hyper-parameters is compared with the most used classifiers in literature for LiDAR data, random forest, AdaBoost, and decision tree. The comparison showed the superiority of the SVM classifier using parameters selection for LiDAR data compared to other classifiers.

Keywords: classification, airborne LiDAR, parameters selection, support vector machine

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37324 Teachers Engagement to Teaching: Exploring Australian Teachers’ Attribute Constructs of Resilience, Adaptability, Commitment, Self/Collective Efficacy Beliefs

Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

Abstract:

Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

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37323 Study on Two Way Reinforced Concrete Slab Using ANSYS with Different Boundary Conditions and Loading

Authors: A. Gherbi, L. Dahmani, A. Boudjemia

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This paper presents the Finite Element Method (FEM) for analyzing the failure pattern of rectangular slab with various edge conditions. Non-Linear static analysis is carried out using ANSYS 15 Software. Using SOLID65 solid elements, the compressive crushing of concrete is facilitated using plasticity algorithm, while the concrete cracking in tension zone is accommodated by the nonlinear material model. Smeared reinforcement is used and introduced as a percentage of steel embedded in concrete slab. The behavior of the analyzed concrete slab has been observed in terms of the crack pattern and displacement for various loading and boundary conditions. The finite element results are also compared with the experimental data. One of the other objectives of the present study is to show how similar the crack path found by ANSYS program to those observed for the yield line analysis. The smeared reinforcement method is found to be more practical especially for the layered elements like concrete slabs. The value of this method is that it does not require explicit modeling of the rebar, and thus a much coarser mesh can be defined.

Keywords: ANSYS, cracking pattern, displacements, reinforced concrete slab, smeared reinforcements

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37322 Structural Damage Detection via Incomplete Model Data Using Output Data Only

Authors: Ahmed Noor Al-qayyim, Barlas Özden Çağlayan

Abstract:

Structural failure is caused mainly by damage that often occurs on structures. Many researchers focus on obtaining very efficient tools to detect the damage in structures in the early state. In the past decades, a subject that has received considerable attention in literature is the damage detection as determined by variations in the dynamic characteristics or response of structures. This study presents a new damage identification technique. The technique detects the damage location for the incomplete structure system using output data only. The method indicates the damage based on the free vibration test data by using “Two Points - Condensation (TPC) technique”. This method creates a set of matrices by reducing the structural system to two degrees of freedom systems. The current stiffness matrices are obtained from optimization of the equation of motion using the measured test data. The current stiffness matrices are compared with original (undamaged) stiffness matrices. High percentage changes in matrices’ coefficients lead to the location of the damage. TPC technique is applied to the experimental data of a simply supported steel beam model structure after inducing thickness change in one element. Where two cases are considered, the method detects the damage and determines its location accurately in both cases. In addition, the results illustrate that these changes in stiffness matrix can be a useful tool for continuous monitoring of structural safety using ambient vibration data. Furthermore, its efficiency proves that this technique can also be used for big structures.

Keywords: damage detection, optimization, signals processing, structural health monitoring, two points–condensation

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37321 Spontaneous Message Detection of Annoying Situation in Community Networks Using Mining Algorithm

Authors: P. Senthil Kumari

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Main concerns in data mining investigation are social controls of data mining for handling ambiguity, noise, or incompleteness on text data. We describe an innovative approach for unplanned text data detection of community networks achieved by classification mechanism. In a tangible domain claim with humble secrecy backgrounds provided by community network for evading annoying content is presented on consumer message partition. To avoid this, mining methodology provides the capability to unswervingly switch the messages and similarly recover the superiority of ordering. Here we designated learning-centered mining approaches with pre-processing technique to complete this effort. Our involvement of work compact with rule-based personalization for automatic text categorization which was appropriate in many dissimilar frameworks and offers tolerance value for permits the background of comments conferring to a variety of conditions associated with the policy or rule arrangements processed by learning algorithm. Remarkably, we find that the choice of classifier has predicted the class labels for control of the inadequate documents on community network with great value of effect.

Keywords: text mining, data classification, community network, learning algorithm

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37320 Stress, Anxiety and Its Associated Factors Within the Transgender Population of Delhi: A Cross-Sectional Study

Authors: Annie Singh, Ishaan Singh

Abstract:

Background: Transgenders are people who have a gender identity different from their sex assigned at birth. Their gender behaviour doesn’t match their body anatomy. The community faces discrimination due to their gender identity all across the world. The term transgender is an umbrella term for many people non-conformal to their biological identity; note that the term transgender is different from gender dysphoria, which is a DSM-5 disorder defined as problems faced by an individual due to their non-conforming gender identity. Transgender people have been a part of Indian culture for ages yet have continued to face exclusion and discrimination in society. This has led to the low socio-economic status of the community. Various studies done across the world have established the role of discrimination, harassment and exclusion in the development of psychological disorders. The study is aimed to assess the frequency of stress and anxiety in the transgender population and understand the various factors affecting the same. Methodology: A cross-sectional survey of self consenting transgender individuals above the age of 18 residing in Delhi was done to assess their socioeconomic status and experiential ecology. Recruitment of participants was done with the help of NGOs. The survey was constructed GAD-7 and PSS-10, two well-known scales were used to assess the stress and anxiety levels. Medians, means and ranges are used for reporting continuous data wherever required, while frequencies and percentages are used for categorical data. For associations and comparison between groups in categorical data, the Chi-square test was used, while the Kruskal-Wallis H test was employed for associations involving multiple ordinal groups. SPSS v28.0 was used to perform the statistical analysis for this study. Results: The survey showed that the frequency of stress and anxiety is high in the transgender population. A demographic survey indicates a low socio-economic background. 44% of participants reported facing discrimination on a daily basis; the frequency of discrimination is higher in transwomen than in transmen. Stress and anxiety levels are similar among both transmen and transwomen. Only 34.5% of participants said they had receptive family or friends. The majority of participants (72.7%) reported a positive or neutral experience with healthcare workers. The prevalence of discrimination is significantly lower in the higher educated groups. Analysis of data shows a positive impact of acceptance and reception on mental health, while discrimination is correlated with higher levels of stress and anxiety. Conclusion: The prevalence of widespread transphobia and discrimination faced by the transgender community has culminated in high levels of stress and anxiety in the transgender population and shows variance according to multiple socio-demographic factors. Educating people about the LGBT community formation of support groups, policies and laws are required to establish trust and promote integration.

Keywords: transgender, gender, stress, anxiety, mental health, discrimination, exclusion

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37319 Factors Relating to Travel Behavior at the Floating Market of Thai Tourists

Authors: Siri-orn Champatong

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The purpose of this research was to study factors that were related with travel behaviors of Thai tourists at the Ayothaya Floating Market, Phra Nakhon Sri Ayutthaya. The quantitative research was conducted with 400 samples of Thai tourists traveling to the Ayothaya Floating Market. The Questionnaire was a tool used to collect data, and the statistics used for data analysis were mean and Pearson product moment correlation coefficient. The results found that Thai tourists focused on attraction, easy access and facilities of the tourist spot at a high level. In addition, they gave priority to the marketing mix in the dimension of products, price, and distribution channels at a high level as well. For marketing promotion, it was at the moderate level. The results of hypothesis testing revealed that factors related to the attractions of the tourist destination, easy access to the tourist destination, the facilities of the tourist spot, and product and price of the marketing mix were associated with travel behaviors in the aspect of the number of visits used and the budget on tourism.

Keywords: floating market, marketing mix, tourism attractions, travelling behavior

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37318 The Effect of Acute Creatine Supplementation on Physiological Variables of Continuous and Intermittent Soccer Activities of Men Soccer Players

Authors: Abdolrasoul Daneshjoo

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The aim of this study was studying the effect of acute creatine supplementation on physiological variables of continuous and intermittent soccer activities of men soccer players. 32 soccer players from Tarbiat Moalem University aged (22/3+-1/6) volunteered for this research and were divided into two groups randomly. Both experimental and control groups after 6 days taking supplementation were tested. For measuring height and weight meter and balance were used. Questionnaire for health background, lactate electro, heart beat measuring polar electro, continuous and intermittent training program and time recorder were used for data collection. For data analysis descriptive statistical techniques, two-way ANOVA and F test were used. The result of this study showed increased significantly in heart rate in control group. For control group heart beat was (71/6 +- 3/5) and for experimental group it was (75/3 +- 4/9). No significant differences were observed in players weight after taking creatine.

Keywords: heartbeat, lactate Blood, creatine, soccer players of Tarbiat Moalem University

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37317 There's No End in Sight: An Interpretative Phenomenological Analysis of Quality of Life in Burning Syndrome Sufferers

Authors: R. McGrath, A. Trace, S. Curtin, C. McCreary

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Introduction: Although, in relation to Burning Mouth Syndrome (BMS), much energy has been expended on its definition and etiology, it still remains a contentious issue. There is agreement on the symptoms, but on little else; and approaches to treatment vary widely. However, it has been established that the condition has a detrimental effect on the sufferer’s quality of life. Much research focus has been put on the physical impact of the syndrome. Recently, some literature has turned the focus to social, functional, and psychological factors. However, there is very little qualitative research on how burning mouth syndrome affects the lives of sufferer’s and the present study seeks to remedy this. Method: The study recruited five male participants who took part in semi-structured interviews lasting between 30 and 50 minutes. Data was analysed using Interpretative Phenomenological Analysis. Results: The study identified four super-ordinate themes: Lack of Control due to Uncertainty about Condition; Disruption to Internal Sense of Self; Negative Future Expectation due to Chronic Symptoms; and Sense of BMS as an Intrusive Force. Aspects of these themes reflect areas of reduction in quality of life. Conclusion: BMS damages an individual’s quality of life in ways that have not been reflected in self-report surveys of health-related quality of life. The condition has serious implications for the individual's sense of self, identity, and future. The study recommends that further qualitative research be carried out in this area. Also, the use of therapeutic interventions with sufferers from BMS is recommended, which would help not only sufferers but best practice in relation to their treatment.

Keywords: burning mouth syndrome, interpretative phenomenological analysis, qualitative research, quality of life

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37316 The Analysis of Movement Pattern during Reach and Grasp in Stroke Patients: A Kinematic Approach

Authors: Hyo Seon Choi, Ju Sun Kim, DY Kim

Abstract:

Introduction: This study was aimed to evaluate temporo-spatial patterns during the reach and grasp task in hemiplegic stroke patients and to identify movement pattern according to severity of motor impairment. Method: 29 subacute post-stroke patients were enrolled in this study. The temporo-spatial and kinematic data were obtained during reach and grasp task through 3D motion analysis (VICON). The reach and grasp task was composed of four sub-tasks: reach (T1), transport to mouth (T2), transport back to table (T3) and return (T4). The movement time, joint angle and sum of deviation angles from normative data were compared between affected side and unaffected side. They were also compared between two groups (mild to moderate group: 28~66, severe group: 0~27) divided by upper-Fugl-Meyer Assessment (FMA) scale. Result: In affected side, total time and durations of all four tasks were significantly longer than those in unaffected side (p < 0.001). The affected side demonstrated significant larger shoulder abduction, shoulder internal rotation, wrist flexion, wrist pronation, thoracic external rotation and smaller shoulder flexion during reach and grasp task (p < 0.05). The significant differences between mild to moderate group and severe group were observed in total duration, durations of T1, T2, and T3 in reach and grasp task (p < 0.01). The severe group showed significant larger shoulder internal rotation during T2 (p < 0.05) and wrist flexion during T2, T3 (p < 0.05) than mild to moderate group. In range of motion during each task, shoulder abduction-adduction during T2 and T3, shoulder internal-external rotation during T2, elbow flexion-extension during T1 showed significant difference between two groups (p < 0.05). The severe group had significant larger total deviation angles in shoulder internal-external rotation and wrist extension-flexion during reach and grasp task (p < 0.05). Conclusion: This study suggests that post-stroke hemiplegic patients have an unique temporo-spatial and kinematic patterns during reach and grasp task, and the movement pattern may be related to affected upper limb severity. These results may be useful to interpret the motion of upper extremity in stroke patients.

Keywords: Fugl-Meyer Assessment (FMA), motion analysis, reach and grasp, stroke

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37315 Authorship Attribution Using Sociolinguistic Profiling When Considering Civil and Criminal Cases

Authors: Diana A. Sokolova

Abstract:

This article is devoted to one of the possibilities for identifying the author of an oral or written text - sociolinguistic profiling. Sociolinguistic profiling is utilized as a forensic linguistics technique to identify individuals through language patterns, particularly in criminal cases. It examines how social factors influence language use. This study aims to showcase the significance of linguistic profiling for attributing authorship in texts and emphasizes the necessity for its continuous enhancement while considering its strengths and weaknesses. The study employs semantic-syntactic, lexical-semantic, linguopragmatic, logical, presupposition, authorization, and content analysis methods to investigate linguistic profiling. The research highlights the relevance of sociolinguistic profiling in authorship attribution and underscores the importance of ongoing refinement of the technique, considering its limitations. This study emphasizes the practical application of linguistic profiling in legal settings and underscores the impact of social factors on language use, contributing to the field of forensic linguistics. Data collection involves collecting oral and written texts from criminal and civil court cases to analyze language patterns for authorship attribution. The collected data is analyzed using various linguistic analysis methods to identify individual characteristics and patterns that can aid in authorship attribution. The study addresses the effectiveness of sociolinguistic profiling in identifying authors of texts and explores the impact of social factors on language use in legal contexts. In spite of advantages challenges in linguistics profiling have spurred debates and controversies in academic circles, legal environments, and the public sphere. So, this research highlights the significance of sociolinguistic profiling in authorship attribution and emphasizes the need for further development of this method, considering its strengths and weaknesses.

Keywords: authorship attribution, detection of identifying, dialect, features, forensic linguistics, social influence, sociolinguistics, unique speech characteristics

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37314 Dietary Patterns and Hearing Loss in Older People

Authors: N. E. Gallagher, C. E. Neville, N. Lyner, J. Yarnell, C. C. Patterson, J. E. Gallacher, Y. Ben-Shlomo, A. Fehily, J. V. Woodside

Abstract:

Hearing loss is highly prevalent in older people and can reduce quality of life substantially. Emerging research suggests that potentially modifiable risk factors, including risk factors previously related to cardiovascular disease risk, may be associated with a decreased or increased incidence of hearing loss. This has prompted investigation into the possibility that certain nutrients, foods or dietary patterns may also be associated with incidence of hearing loss. The aim of this study was to determine any associations between dietary patterns and hearing loss in men enrolled in the Caerphilly study. The Caerphilly prospective cohort study began in 1979-1983 with recruitment of 2512 men aged 45-59 years. Dietary data was collected using a self-administered, semi-quantitative, 56-item food frequency questionnaire (FFQ) at baseline (1979-1983), and 7-day weighed food intake (WI) in a 30% sub-sample, while pure-tone unaided audiometric threshold was assessed at 0.5, 1, 2 and 4 kHz, between 1984 and 1988. Principal components analysis (PCA) was carried out to determine a posteriori dietary patterns and multivariate linear and logistic regression models were used to examine associations with hearing level (pure tone average (PTA) of frequencies 0.5, 1, 2 and 4 kHz in decibels (dB)) for linear regression and with hearing loss (PTA>25dB) for logistic regression. Three dietary patterns were determined using PCA on the FFQ data- Traditional, Healthy, High sugar/Alcohol avoider. After adjustment for potential confounding factors, both linear and logistic regression analyses showed a significant and inverse association between the Healthy pattern and hearing loss (P<0.001) and linear regression analysis showed a significant association between the High sugar/Alcohol avoider pattern and hearing loss (P=0.04). Three similar dietary patterns were determined using PCA on the WI data- Traditional, Healthy, High sugar/Alcohol avoider. After adjustment for potential confounding factors, logistic regression analyses showed a significant and inverse association between the Healthy pattern and hearing loss (P=0.02) and a significant association between the Traditional pattern and hearing loss (P=0.04). A Healthy dietary pattern was found to be significantly inversely associated with hearing loss in middle-aged men in the Caerphilly study. Furthermore, a High sugar/Alcohol avoider pattern (FFQ) and a Traditional pattern (WI) were associated with poorer hearing levels. Consequently, the role of dietary factors in hearing loss remains to be fully established and warrants further investigation.

Keywords: ageing, diet, dietary patterns, hearing loss

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37313 Climate Change and Food Security in Nigeria: The World Bank Assisted Third National Fadama Development Programme (Nfdp Iii) Approach in Rivers State, Niger Delta, Nigeria

Authors: Temple Probyne Abali

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Port Harcourt, Rivers State in the Niger Delta region of Nigeria is bedeviled by the phenomenon of climatechange, posing threat to food security and livelihood. This study examined a 4 decadel (1980-2020) trend of climate change as well as its socio-economic impact on food security in the region. Furthermore, to achieve sustainable food security and livelihood amidst the phenomenon, the study adopted the World Bank Assisted Third National Fadama Development Programme approach. The data source for climate change involved secondary data from Nigeria Meteorological Agency (NIMET). Consequently, the results for climate change over the 4decade period were displayed in tables, charts and maps for the expected changes. Data sources on socio-economic impact of food security and livelihood were acquired through questionnairedesign. A purposive random sampling technique was used in selecting 5 coastal communities inthe region known for viable economic potentials for agricultural development and the resultswere analyzed using Analysis of Variance (ANOVA). The Participatory Rural Appraisal (PRA) technique of the World Bank for needs assessment wasadopted in selecting 5 agricultural sub-project proposals/activities based on groups’ commoneconomic interest from a total of 1,000 farmers each drawn from the 5 communities of differentage groups including men, women, youths and the vulnerable. Based on the farmers’ sub-projectinterests, the various groups’ Strength, Weakness, Opportunities and Threats (SWOT), Problem Listing Matrix, Skill Gap Analysis as well as EIAson their sub-project proposals/activities were analyzed with substantialMonitoring and Evaluation (M & E), using the Specific, Measurable, Attribute, Reliable and Time bound (SMART)approach. Based on the findings from the PRA technique, the farmers recorded considerableincreaseinincomeofover200%withinthe5yearprojectplan(2008-2013).Thestudyrecommends capacity building and advisory services on this PRA innovation. By so doing, there would be a sustainable increase in agricultural production and assured food security in an environmental friendly manner, in line with the United Nation’s Sustainable Development Goals(SDGs).

Keywords: climate change, food security, fadama, world bank, agriculture, sdgs

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37312 Monthly River Flow Prediction Using a Nonlinear Prediction Method

Authors: N. H. Adenan, M. S. M. Noorani

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River flow prediction is an essential to ensure proper management of water resources can be optimally distribute water to consumers. This study presents an analysis and prediction by using nonlinear prediction method involving monthly river flow data in Tanjung Tualang from 1976 to 2006. Nonlinear prediction method involves the reconstruction of phase space and local linear approximation approach. The phase space reconstruction involves the reconstruction of one-dimensional (the observed 287 months of data) in a multidimensional phase space to reveal the dynamics of the system. Revenue of phase space reconstruction is used to predict the next 72 months. A comparison of prediction performance based on correlation coefficient (CC) and root mean square error (RMSE) have been employed to compare prediction performance for nonlinear prediction method, ARIMA and SVM. Prediction performance comparisons show the prediction results using nonlinear prediction method is better than ARIMA and SVM. Therefore, the result of this study could be used to developed an efficient water management system to optimize the allocation water resources.

Keywords: river flow, nonlinear prediction method, phase space, local linear approximation

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37311 Expanding the Evaluation Criteria for a Wind Turbine Performance

Authors: Ivan Balachin, Geanette Polanco, Jiang Xingliang, Hu Qin

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The problem of global warming raised up interest towards renewable energy sources. To reduce cost of wind energy is a challenge. Before building of wind park conditions such as: average wind speed, direction, time for each wind, probability of icing, must be considered in the design phase. Operation values used on the setting of control systems also will depend on mentioned variables. Here it is proposed a procedure to be include in the evaluation of the performance of a wind turbine, based on the amplitude of wind changes, the number of changes and their duration. A generic study case based on actual data is presented. Data analysing techniques were applied to model the power required for yaw system based on amplitude and data amount of wind changes. A theoretical model between time, amplitude of wind changes and angular speed of nacelle rotation was identified.

Keywords: field data processing, regression determination, wind turbine performance, wind turbine placing, yaw system losses

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37310 A Prediction Model for Dynamic Responses of Building from Earthquake Based on Evolutionary Learning

Authors: Kyu Jin Kim, Byung Kwan Oh, Hyo Seon Park

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The seismic responses-based structural health monitoring system has been performed to prevent seismic damage. Structural seismic damage of building is caused by the instantaneous stress concentration which is related with dynamic characteristic of earthquake. Meanwhile, seismic response analysis to estimate the dynamic responses of building demands significantly high computational cost. To prevent the failure of structural members from the characteristic of the earthquake and the significantly high computational cost for seismic response analysis, this paper presents an artificial neural network (ANN) based prediction model for dynamic responses of building considering specific time length. Through the measured dynamic responses, input and output node of the ANN are formed by the length of specific time, and adopted for the training. In the model, evolutionary radial basis function neural network (ERBFNN), that radial basis function network (RBFN) is integrated with evolutionary optimization algorithm to find variables in RBF, is implemented. The effectiveness of the proposed model is verified through an analytical study applying responses from dynamic analysis for multi-degree of freedom system to training data in ERBFNN.

Keywords: structural health monitoring, dynamic response, artificial neural network, radial basis function network, genetic algorithm

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37309 Report of a Realistic Simulation Training in Using Bougie Guide for Endotracheal Intubation

Authors: Cleto J. Sauer Jr., Rita C. Sauer, Chaider G. Andrade, Dóris F. Rabelo

Abstract:

Some patients with COVID-19 disease and difficult airway characteristics undergo to endotracheal intubation (ETI) procedure. The tracheal introducer, known as the bougie guide, can aid ETI in patients with difficult airway pattern. Realistic simulation (RS) is a methodology utilized for healthcare professionals training. To improve skills in using the bougie guide of physicians from Recôncavo da Bahia region in Brazil, during COVID-19 outbreak, RS training was carried out. Simulated scenario included the Nasco Lifeform realistic simulator for ETI and a bougie guide introducer. Training was a capacitation program organized by the Health Department of Bahia State. Objective: To report effects in participants´ self-confidence perception for using bougie guide after a RS based training. Methods: Descriptive study, secondary data extracted from questionnaires. Priority workplace and previous knowledge about bougie were reported on a preparticipation formulary. Participants also completed pre- and post-training qualitative self-assessment (10-point Likert scale) regarding to self-confidence in using bougie guide. Distribution analysis for qualitative data was performed with Wilcoxon Signed Rank Test, and self-confidence increase analysis in frequency contingency tables with Fisher's exact test. Results: From May to June 2020 a total of 36 physicians participated of training, 25 (69%) from primary care setting, 32 (89%) with no previous knowledge about the bougie guide utilization. For those who had previous knowledge about bougie pre-training self-confidence median was 6,5, and 2 for participants who had not. In overall there was an increase in self-confidence median for bougie utilization. Median (variation) before and after training was 2.5 (1-7) vs. 8 (4-10) (p <0.0001). Among those who had no previous knowledge about bougie (n = 32) an increase in self-confidence greater than 3 points for bougie utilization was reported by 31 vs. 1 participants (p = 0.71). Conclusions: Most of participants had no previous knowledge about using the bougie guide. RS training contributed to self-confidence increase for using bougie for ETI procedure. RS methodology can contribute for training in using the bougie guide for ETI procedure during COVID-19 outbreak.

Keywords: bougie, confidence, COVID-19, endotracheal intubation, realistic simulation

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37308 The Effect of Aerobic Training and Consumption of Apple Vinegar on Cardiovascular Risk Factor in Older Women

Authors: S. Fazelifar, M. Ghasemi

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Aim: Recent studies on cardiovascular risk factors have been focused on the new markers of inflammatory diseases such as C-reactive protein (CRP). Research evidence shows that physical activity along with other factors such as reduced smoking, controlling blood pressure, control blood lipids TC, LDL-c, HDL-c and having a healthy weight can reduce the risk of chronic heart disease (CHD) .Therefore, the aim of this study was to determine the effect of twelve weeks aerobic exercise and consumption of apple vinegar on cardiovascular risk factor in older women. Methodology: 28 inactive women (mean body weight 72.13 ± 8.6 kg, height 157 ± 7.4cm, age 48.06 ± 5.18 years and BMI 28.2 ± 3.2 kg/m2) by recall and notice of investigation, among of the eligible voters recruited and randomly divided in 4 groups: control, apple vinegar, exercise, exercise + apple vinegar. The training program includes a 20-minute warm-up and stretching, running for 15 minutes in the first session with an intensity of 80% of maximum heart rate and an increase in one-minute run time in next training session. Also, subjects in experimental groups received daily specified amount of 50 ml apple vinegar. Blood samples were collected from the brachial vein in before and after training to measure CRP and blood lipids (cholesterol, HDL, VLDL, LDL). The levels of CRP were measured by ELISA way. K-S test to determine the normality of the data and analysis of variance for repeated measures was used to analyze the data. A significant difference in the p < 0/05 accepted. Results: The results indicated that individual characteristics including height, weight, age, and body mass index were not significantly different among the four groups. The results showed that levels of CRP and LDL cholesterol were significantly reduced in all groups at post-test compared to the pre-test. The HDL levels increased significantly in all groups in post-test compared to the pre-test. Analysis of the data indicates that levels of CRP, TC, and LDL were significantly reduced in all groups compared to the control group, while the changes in the other groups were not significant relative to each other. Conclusion: Results of this study showed that twelve weeks of aerobic exercise with apple vinegar cause a significant decrease in CRP, cholesterol, LDL, and significantly increased HDL levels. According to the results of this study, it is possible that aerobic exercise with apple vinegar can inhibit CRP and undesirable fats. Considering the strong association between the inflammatory indices and the prevalence of cardiovascular diseases, every factor that decreases these indices can reduce the cardiovascular complications.

Keywords: aerobic exercise, apple vinegar, CRP, older women

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37307 Improvement in Oral Health-Related Quality of Life of Adult Patients After Rehabilitation With Partial Dentures: A Systematic Review and Meta-Analysis

Authors: Adama NS Bah

Abstract:

Background: Loss of teeth has a negative influence on essential oral functions such as phonetics, mastication, and aesthetics. Dentists treat people with prosthodontic rehabilitation to recover essential oral functions. The oral health quality of life inventory reflects the success of prosthodontic rehabilitation. In many countries, the current conventional care delivered to replace missing teeth for adult patients involves the provision of removable partial dentures. Aim: The aim of this systematic review and meta-analysis is to gather the best available evidence to determine patients’ oral health-related quality of life improvement after treatment with partial dentures. Methods: We searched electronic databases from January 2010 to September 2019, including PubMed, ProQuest, Science Direct, Scopus and Google Scholar. In this paper, studies were included only if the average age was 30 years and above and also published in English. Two reviewers independently screened and selected all the references based on inclusion criteria using the PRISMA guideline, and assessed the quality of the included references using the Joanna Briggs Institute quality assessment tools. Data extracted were analyzed in RevMan 5.0 software, the heterogeneity between the studies was assessed using Forest plot, I2 statistics and chi-square test with a statistical P value less than 0.05 to indicate statistical significance. Random effect models were used in case of moderate or high heterogeneity. Four studies were included in the systematic review and three studies were pooled for meta-analysis. Results: Four studies included in the systematic review and three studies included in the meta-analysis with a total of 285 patients comparing the improvement in oral health-related quality of life before and after rehabilitation with partial denture, the pooled results showed a better improvement of oral health-related quality of life after treatment with partial dentures (mean difference 5.25; 95% CI [3.81, 6.68], p < 0.00001) favoring the wearing of partial dentures. In order to ascertain the reliability of the included studies for meta-analysis risk of bias was assessed and found to be low in all included studies for meta-analysis using the Cochrane collaboration tool for risk of bias assessment. Conclusion: There is high evidence that rehabilitation with partial dentures can improve the patient’s oral health-related quality of life measured with Oral Health Impact Profile 14. This review has clinical evidence value for dentists treating the expanding vulnerable adult population.

Keywords: meta-analysis, oral health impact profile, partial dentures, systematic review

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37306 Prediction of Sepsis Illness from Patients Vital Signs Using Long Short-Term Memory Network and Dynamic Analysis

Authors: Marcio Freire Cruz, Naoaki Ono, Shigehiko Kanaya, Carlos Arthur Mattos Teixeira Cavalcante

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The systems that record patient care information, known as Electronic Medical Record (EMR) and those that monitor vital signs of patients, such as heart rate, body temperature, and blood pressure have been extremely valuable for the effectiveness of the patient’s treatment. Several kinds of research have been using data from EMRs and vital signs of patients to predict illnesses. Among them, we highlight those that intend to predict, classify, or, at least identify patterns, of sepsis illness in patients under vital signs monitoring. Sepsis is an organic dysfunction caused by a dysregulated patient's response to an infection that affects millions of people worldwide. Early detection of sepsis is expected to provide a significant improvement in its treatment. Preceding works usually combined medical, statistical, mathematical and computational models to develop detection methods for early prediction, getting higher accuracies, and using the smallest number of variables. Among other techniques, we could find researches using survival analysis, specialist systems, machine learning and deep learning that reached great results. In our research, patients are modeled as points moving each hour in an n-dimensional space where n is the number of vital signs (variables). These points can reach a sepsis target point after some time. For now, the sepsis target point was calculated using the median of all patients’ variables on the sepsis onset. From these points, we calculate for each hour the position vector, the first derivative (velocity vector) and the second derivative (acceleration vector) of the variables to evaluate their behavior. And we construct a prediction model based on a Long Short-Term Memory (LSTM) Network, including these derivatives as explanatory variables. The accuracy of the prediction 6 hours before the time of sepsis, considering only the vital signs reached 83.24% and by including the vectors position, speed, and acceleration, we obtained 94.96%. The data are being collected from Medical Information Mart for Intensive Care (MIMIC) Database, a public database that contains vital signs, laboratory test results, observations, notes, and so on, from more than 60.000 patients.

Keywords: dynamic analysis, long short-term memory, prediction, sepsis

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37305 RNA-Seq Based Transcriptomic Analysis of Wheat Cultivars for Unveiling of Genomic Variations and Isolation of Drought Tolerant Genes for Genome Editing

Authors: Ghulam Muhammad Ali

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Unveiling of genes involved in drought and root architecture using transcriptomic analyses remained fragmented for further improvement of wheat through genome editing. The purpose of this research endeavor was to unveil the variations in different genes implicated in drought tolerance and root architecture in wheat through RNA-seq data analysis. In this study seedlings of 8 days old, 6 cultivars of wheat namely, Batis, Blue Silver, Local White, UZ888, Chakwal 50 and Synthetic wheat S22 were subjected to transcriptomic analysis for root and shoot genes. Total of 12 RNA samples was sequenced by Illumina. Using updated wheat transcripts from Ensembl and IWGC references with 54,175 gene models, we found that 49,621 out of 54,175 (91.5%) genes are expressed at an RPKM of 0.1 or more (in at least 1 sample). The number of genes expressed was higher in Local White than Batis. Differentially expressed genes (DEG) were higher in Chakwal 50. Expression-based clustering indicated conserved function of DRO1and RPK1 between Arabidopsis and wheat. Dendrogram showed that Local White is sister to Chakwal 50 while Batis is closely related to Blue Silver. This study flaunts transcriptomic sequence variations in different cultivars that showed mutations in genes associated with drought that may directly contribute to drought tolerance. DRO1 and RPK1 genes were fetched/isolated for genome editing. These genes are being edited in wheat through CRISPR-Cas9 for yield enhancement.

Keywords: transcriptomic, wheat, genome editing, drought, CRISPR-Cas9, yield enhancement

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37304 Allele Mining for Rice Sheath Blight Resistance by Whole-Genome Association Mapping in a Tail-End Population

Authors: Naoki Yamamoto, Hidenobu Ozaki, Taiichiro Ookawa, Youming Liu, Kazunori Okada, Aiping Zheng

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Rice sheath blight is one of the destructive fungal diseases in rice. We have thought that rice sheath blight resistance is a polygenic trait. Host-pathogen interactions and secondary metabolites such as lignin and phytoalexins are likely to be involved in defense against R. solani. However, to our knowledge, it is still unknown how sheath blight resistance can be enhanced in rice breeding. To seek for an alternative genetic factor that contribute to sheath blight resistance, we mined relevant allelic variations from rice core collections created in Japan. Based on disease lesion length on detached leaf sheath, we selected 30 varieties of the top tail-end and the bottom tail-end, respectively, from the core collections to perform genome-wide association mapping. Re-sequencing reads for these varieties were used for calling single nucleotide polymorphisms among the 60 varieties to create a SNP panel, which contained 1,137,131 homozygous variant sites after filitering. Association mapping highlighted a locus on the long arm of chromosome 11, which is co-localized with three sheath blight QTLs, qShB11-2-TX, qShB11, and qSBR-11-2. Based on the localization of the trait-associated alleles, we identified an ankyryn repeat-containing protein gene (ANK-M) as an uncharacterized candidate factor for rice sheath blight resistance. Allelic distributions for ANK-M in the whole rice population supported the reliability of trait-allele associations. Gene expression characteristics were checked to evaluiate the functionality of ANK-M. Since an ANK-M homolog (OsPIANK1) in rice seems a basal defense regulator against rice blast and bacterial leaf blight, ANK-M may also play a role in the rice immune system.

Keywords: allele mining, GWAS, QTL, rice sheath blight

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37303 Visualisation in Health Communication: Taking Weibo Interaction in COVD19 as the Example

Authors: Zicheng Zhang, Linli Zhang

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As China's biggest social media platform, Weibo has taken on essential health communication responsibilities during the pandemic. This research takes 105 posters in 15 health-related official Weibo accounts as the analysis objects to explore COVID19 health information communication and visualisation. First, the interaction between the audiences and Weibo, including forwarding, comments, and likes, is statistically analysed. The comments about the information design are extracted manually, and then the sentiment analysis is carried out to verdict audiences' views about the poster's design. The forwarding and comments are quantified as the attention index for a reference to the degree of likes. In addition, this study also designed an evaluation scale based on the standards of Health Literacy Resource by the Centers for Medicare& Medicaid Services (US). Then designers scored all selected posters one by one. Finally, combining the data of the two parts, concluded that: 1. To a certain extent, people think that the posters do not deliver substantive and practical information; 2. Non-knowledge posters(i.e., cartoon posters) gained more Forwarding and Likes, such as Go, Wuhan poster; 3. The analysis of COVID posters is still mainly picture-oriented, mainly about encouraging people to overcome difficulties; 4. Posters for pandemic prevention usually contain more text and fewer illustrations and do not clearly show cultural differences. In conclusion, health communication usually involves a lot of professional knowledge, so visualising that knowledge in an accessible way for the general public is challenging. The relevant posters still have the problems of lack of effective communication, superficial design, and insufficient content accessibility.

Keywords: weibo, visualisation, covid posters, poster design

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37302 Reading Informational or Fictional Texts to Students: Choices and Perceptions of Preschool and Primary Grade Teachers

Authors: Anne-Marie Dionne

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Teacher reading aloud to students is a practice that is well established in preschool and primary classrooms. Many benefits of this pedagogical activity have been highlighted in multiple studies. However, it has also been shown that teachers are not keen on choosing informational texts for their read aloud, as their selections for this venue are mainly fictional stories, mostly written in a unique narrative story-like structure. Considering that students soon have to read complex informational texts by themselves as they go from one grade to another, there is cause for concern because those who do not benefit from an early exposure to informational texts could be lacking knowledge of informational text structures that they will encounter regularly in their reading. Exposing students to informational texts could be done in different ways in classrooms. However, since read aloud appears to be such a common and efficient practice in preschool and primary grades, it is important to examine more deeply the factors taken into account by teachers when they are selecting their readings for this important teaching activity. Moreover, it seems critical to know why teachers are not inclined to choose more often informational texts when they are reading aloud to their pupils. A group of 22 preschool or primary grade teachers participated in this study. The data collection was done by a survey and an individual semi-structured interview. The survey was conducted in order to get quantitative data on the read-aloud practices of teachers. As for the interviews, they were organized around three categories of questions (exploratory, analytical, opinion) regarding the process of selecting the texts for the read-aloud sessions. A statistical analysis was conducted on the data obtained by the survey. As for the interviews, they were subjected to a content analysis aiming to classify the information collected in predetermined categories such as the reasons given to favor fictional texts over informative texts, the reasons given for avoiding informative texts for reading aloud, the perceptions of the challenges that the informative texts could bring when they are read aloud to students, and the perceived advantages that they would present if they were chosen more often for this activity. Results are showing variable factors that are guiding the teachers when they are making their selection of the texts to be read aloud. As for example, some of them are choosing solely fictional texts because of their convictions that these are more interesting for their students. They also perceive that the informational texts are not good choices because they are not suitable for pleasure reading. In that matter, results are pointing to some interesting elements. Many teachers perceive that read aloud of fictional or informational texts have different goals: fictional texts are read for pleasure and informational texts are read mostly for academic purposes. These results bring out the urgency for teachers to become aware of the numerous benefits that the reading aloud of each type of texts could bring to their students, especially the informational texts. The possible consequences of teachers’ perceptions will be discussed further in our presentation.

Keywords: fictional texts, informational texts, preschool or primary grade teachers, reading aloud

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37301 Temporal Changes Analysis (1960-2019) of a Greek Rural Landscape

Authors: Stamatia Nasiakou, Dimitrios Chouvardas, Michael Vrahnakis, Vassiliki Kleftoyanni

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Recent research in the mountainous and semi-mountainous rural landscapes of Greece shows that they have been significantly changed over the last 80 years. These changes have the form of structural modification of land cover/use patterns, with the main characteristic being the extensive expansion of dense forests and shrubs at the expense of grasslands and extensive agricultural areas. The aim of this research was to study the 60-year changes (1960-2019) of land cover/ use units in the rural landscape of Mouzaki (Karditsa Prefecture, central Greece). Relevant cartographic material such as forest land use maps, digital maps (Corine Land Cover -2018), 1960 aerial photos from Hellenic Military Geographical Service, and satellite imagery (Google Earth Pro 2014, 2016, 2017 and 2019) was collected and processed in order to study landscape evolution. ArcGIS v 10.2.2 software was used to process the cartographic material and to produce several sets of data. Main product of the analysis was a digitized photo-mosaic of the 1960 aerial photographs, a digitized photo-mosaic of recent satellite images (2014, 2016, 2017 and 2019), and diagrams and maps of temporal transformation of the rural landscape (1960 – 2019). Maps and diagrams were produced by applying photointerpretation techniques and a suitable land cover/ use classification system on the two photo-mosaics. Demographic and socioeconomic inventory data was also collected mainly from diachronic census reports of the Hellenic Statistical Authority and local sources. Data analysis of the temporal transformation of land cover/ use units showed that they are mainly located in the central and south-eastern part of the study area, which mainly includes the mountainous part of the landscape. The most significant change is the expansion of the dense forests that currently dominate the southern and eastern part of the landscape. In conclusion, the produced diagrams and maps of the land cover/ use evolution suggest that woody vegetation in the rural landscape of Mouzaki has significantly increased over the past 60 years at the expense of the open areas, especially grasslands and agricultural areas. Demographic changes, land abandonment and the transformation of traditional farming practices (e.g. agroforestry) were recognized as the main cause of the landscape change. This study is part of a broader research project entitled “Perspective of Agroforestry in Thessaly region: A research on social, environmental and economic aspects to enhance farmer participation”. The project is funded by the General Secretariat for Research and Technology (GSRT) and the Hellenic Foundation for Research and Innovation (HFRI).

Keywords: Agroforestry, Forest expansion, Land cover/ use changes, Mountainous and semi-mountainous areas

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37300 Analysis of Shallow Foundation Using Conventional and Finite Element Approach

Authors: Sultan Al Shafian, Mozaher Ul Kabir, Khondoker Istiak Ahmad, Masnun Abrar, Mahfuza Khanum, Hossain M. Shahin

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For structural evaluation of shallow foundation, the modulus of subgrade reaction is one of the most widely used and accepted parameter for its ease of calculations. To determine this parameter, one of the most common field method is Plate Load test method. In this field test method, the subgrade modulus is considered for a specific location and according to its application, it is assumed that the displacement occurred in one place does not affect other adjacent locations. For this kind of assumptions, the modulus of subgrade reaction sometimes forced the engineers to overdesign the underground structure, which eventually results in increasing the cost of the construction and sometimes failure of the structure. In the present study, the settlement of a shallow foundation has been analyzed using both conventional and numerical analysis. Around 25 plate load tests were conducted on a sand fill site in Bangladesh to determine the Modulus of Subgrade reaction of ground which is later used to design a shallow foundation considering different depth. After the collection of the field data, the field condition was appropriately simulated in a finite element software. Finally results obtained from both the conventional and numerical approach has been compared. A significant difference has been observed in the case of settlement while comparing the results. A proper correlation has also been proposed at the end of this research work between the two methods of in order to provide the most efficient way to calculate the subgrade modulus of the ground for designing the shallow foundation.

Keywords: modulus of subgrade reaction, shallow foundation, finite element analysis, settlement, plate load test

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37299 An Evaluative Study of Services Provided in Community Based Rehabilitation Centres in Jordan

Authors: Wesam Darawsheh

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Purpose: There is an absence of studies directed to evaluate the effectiveness of Community Based Rehabilitation (CBR) programs in Jordan. This research study is aimed at investigating the effectiveness of the services of CBR programmes in Jordan. Method: A questionnaire anonymized survey was carried out with forty-seven participants (stakeholders and volunteers) from four CBR centres in Jordan. It comprised eighteen questions that collected both qualitative and quantitative data with both closed- and open-ended questions. The survey assessed participants’ knowledge of CBR and perception of the effectiveness of services provided. The quantitative data were analyzed using SPSS Version 22.0 (2016, IBM Corporation New York). Qualitative data were analyzed through thematic content and analysis and open coding to identify emergent themes. Results: The ROC curve revealed that the AUC for questions of the survey to be (AUC=0.846) which indicated a good specificity and sensitivity of the questions of the survey. The MANOVA revealed insignificant results in the effect of the CBR site (p= 0.157), and the level of education of participants (p=0.549), on the perception of the effectiveness of CBR services. There were insignificant differences between the scores of PWDs and volunteers (p=0.781). 40.4% evaluated the effectiveness of CBR services to be low. This mainly stemmed out from the lack of efforts of the CBR programmes to raise the knowledge of the local community about CBR, disability and the role toward PWDs. Conclusions: A speculation for priorities of CBR programmes in Jordan was offered where efforts need to be directed at promoting livelihood and the empowerment components, in order to actualize the main three principles of CBR mainly by promoting multispectral collaboration as a way of operation.

Keywords: community based rehabilitation (CBR), people with disabilities (PWDS), CBR centres, rehabilitation services, Jordan, mixed-methods, evaluative study

Procedia PDF Downloads 253