Search results for: the health belief model

Authors: Gracia V. Navarro, Maria V. Gonzalez, Carlos G. Reed

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The eudaimonic perspective in philosophy and psychology suggests that a good life is closely related to developing oneself in order to contribute to the well-being and happiness of other people and of the world as a whole. Educational psychology can help to achieve this through the design and validation of educative models. Since 2004, the University of Concepcion and other Chilean universities apply an educative model to train socially responsible professionals, people that in the exercise of their profession contribute to generate equity for the development and assess the impacts of their decisions, opting for those that serve the common good. The main aim is to identify if a relationship exists between achieved learning, attitudes toward social responsibility, self-attribution of socially responsible behavior, value type, professional behavior observed and, participation in a specific model to train socially responsible (SR) professionals. The Achieved Learning and Attitudes Toward Social Responsibility Questionnaire, interview with employers and Values Questionnaire and Self-attribution of SR Behavior Questionnaire is applied to 394 students and graduates, divided into experimental and control groups (trained and not trained under the educative model), in order to identify the professional behavior of the graduates. The results show that students and graduates perceive cognitive, affective and behavioral learning, with significant differences in attitudes toward social responsibility and self-attribution of SR behavior, between experimental and control. There are also differences in employers' perceptions about the professional practice of those who were trained under the model and those who were not. It is concluded that the educative model has an impact on the learning of social responsibility and educates for a full life. It is also concluded that it is necessary to identify mediating variables of the model effect.

Keywords: educative model, good life, professional social responsibility, values

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Authors: Hang Lo Lee, Ki Il Song, Hee Hwan Ryu

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An accurate prediction of TBM(Tunnel Boring Machine) performance is very difficult for reliable estimation of the construction period and cost in preconstruction stage. For this purpose, the aim of this study is to analyze the evaluation process of various prediction models published since 2000 for TBM performance, and to select the optimal input parameters for the prediction model. A classification system of TBM performance prediction model and applied methodology are proposed in this research. Input and output parameters applied for prediction models are also represented. Based on these results, a statistical analysis is performed using the collected data from shield TBM tunnel in South Korea. By performing a simple regression and residual analysis utilizinFg statistical program, R, the optimal input parameters are selected. These results are expected to be used for development of prediction model of TBM performance.

Keywords: TBM performance prediction model, classification system, simple regression analysis, residual analysis, optimal input parameters

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Authors: Muhammad Naveed Tahir, Wang Yingkuan, Huang Wenjiang, Raheel Osman

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Numerous models used in prediction and decision-making process but most of them are linear in natural environment, and linear models reach their limitations with non-linearity in data. Therefore accurate estimation is difficult. Artificial Neural Networks (ANN) found extensive acceptance to address the modeling of the complex real world for the non-linear environment. ANN’s have more general and flexible functional forms than traditional statistical methods can effectively deal with. The link between information technology and agriculture will become more firm in the near future. Monitoring crop biophysical properties non-destructively can provide a rapid and accurate understanding of its response to various environmental influences. Crop chlorophyll content is an important indicator of crop health and therefore the estimation of crop yield. In recent years, remote sensing has been accepted as a robust tool for site-specific management by detecting crop parameters at both local and large scales. The present research combined the ANN model with satellite-derived chlorophyll indices from LANDSAT 8 imagery for predicting real-time wheat chlorophyll estimation. The cloud-free scenes of LANDSAT 8 were acquired (Feb-March 2016-17) at the same time when ground-truthing campaign was performed for chlorophyll estimation by using SPAD-502. Different vegetation indices were derived from LANDSAT 8 imagery using ERADAS Imagine (v.2014) software for chlorophyll determination. The vegetation indices were including Normalized Difference Vegetation Index (NDVI), Green Normalized Difference Vegetation Index (GNDVI), Chlorophyll Absorbed Ratio Index (CARI), Modified Chlorophyll Absorbed Ratio Index (MCARI) and Transformed Chlorophyll Absorbed Ratio index (TCARI). For ANN modeling, MATLAB and SPSS (ANN) tools were used. Multilayer Perceptron (MLP) in MATLAB provided very satisfactory results. For training purpose of MLP 61.7% of the data, for validation purpose 28.3% of data and rest 10% of data were used to evaluate and validate the ANN model results. For error evaluation, sum of squares error and relative error were used. ANN model summery showed that sum of squares error of 10.786, the average overall relative error was .099. The MCARI and NDVI were revealed to be more sensitive indices for assessing wheat chlorophyll content with the highest coefficient of determination R²=0.93 and 0.90 respectively. The results suggested that use of high spatial resolution satellite imagery for the retrieval of crop chlorophyll content by using ANN model provides accurate, reliable assessment of crop health status at a larger scale which can help in managing crop nutrition requirement in real time.

Keywords: ANN, chlorophyll content, chlorophyll indices, satellite images, wheat

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Authors: Hameed Olalekan Bolaji

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The digital natives are driving the trends of literacy in the use of electronic devices for learning purposes. This has reconfigured the context of learning in the exploration of knowledge in a social learning environment. This study explores the impact of Ubiquitous Collaborative Mobile Learning (UCML) instructional design model in a quantitative designed-based research approach. The UCML model was a synergetic blend of four models that are relevant to the design of instructional content for a social learning environment. The UCML model serves as the treatment and instructions were transmitted via mobile device based on the principle of ‘bring your own device’ (BYOD) to promote social learning. Three research questions and two hypotheses were raised to guide the conduct of this study. A researcher-designed questionnaire was used to collate data and the it was subjected to reliability of Cronbach Alpha which yielded 0.91. Descriptive statistics of mean and standard deviation were used to answer research questions while inferential statistics of independent sample t-test was used to analyze the hypotheses. The findings reveal that the UCML model was adequately evolved and it promotes social learning its design principles through the use of mobile devices.

Keywords: collaboration, mobile device, social learning, ubiquitous

Procedia PDF Downloads 157

Authors: Kim Byeong-Gon, Lee Pureun-Haneul, Hong Jisu, Jang An-Soo

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Background: Diesel exhaust particles (DEPs) lead to trigger airway hyperresponsiveness (AHR) and airway dysfunction or inflammation in respiratory systems. Whether tight junction protein changes can contribute to development or exacerbations of airway diseases remain to be clarified. Objective: The aim of this study was to observe the effect of DEP on tight junction proteins in one airway both nose and lung in a mouse model. Methods: Mice were treated with saline (Sham) and exposed to 100 μg/m³ DEPs 1 hour a day for 5 days a week for 4 weeks and 8 weeks in a closed-system chamber attached to a ultrasonic nebulizer. Airway hyperresponsiveness (AHR) was measured and bronchoalveolar lavage (BAL) fluid, nasal lavage (NAL) fluid, lung and nasal tissue was collected. The effects of DEP on tight junction proteins were estimated using western blot, immunohistochemical in lung and nasal tissue. Results: Airway hyperresponsiveness and number of inflammatory cells were higher in DEP exposure group than in control group, and were higher in 4 and 8 weeks model than in control group. The expression of tight junction proteins CLND4, -5, and -17 in both lung and nasal tissue were significantly increased in DEP exposure group than in the control group. Conclusion: These results suggesting that CLDN4, -5 and -17 may be involved in the airway both nose and lung, suggesting that air pollutants cause to disruption of epithelial and endothelial cell barriers. Acknowledgment: This research was supported by Korea Ministry of Environment (MOE) as 'The Environmental Health Action Program' (2016001360009) and Soonchunhyang University Research Fund.

Keywords: diesel exhaust particles, air pollutant, tight junction, Claudin, Airway inflammation

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Authors: Abebe Mulugojam Negash, Yongbin Yu, Ekong Favour, Bekalu Nigus Dawit, Molla Woretaw Teshome, Aynalem Birtukan Yirga

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Breast cancer remains a significant health concern, necessitating advancements in diagnostic methodologies. Addressing this, our paper confronts the notable challenges in breast cancer classification, particularly the imbalance in datasets and the constraints in the accuracy and interpretability of prevailing deep learning approaches. We proposed an attention-based residual neural network (ResNet), which effectively combines the robust features of ResNet with an advanced attention mechanism. Enhanced through strategic data augmentation and positive weight adjustments, this approach specifically targets the issue of data imbalance. The proposed model is tested on the BreakHis dataset and achieved accuracies of 99.00%, 99.04%, 98.67%, and 98.08% in different magnifications (40X, 100X, 200X, and 400X), respectively. We evaluated the performance by using different evaluation metrics such as precision, recall, and F1-Score and made comparisons with other state-of-the-art methods. Our experiments demonstrate that the proposed model outperforms existing approaches, achieving higher accuracy in breast cancer classification.

Keywords: residual neural network, attention mechanism, positive weight, data augmentation

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Authors: Ali Nadi, Ali Edrissi

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Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: disaster management, real-time demand, reinforcement learning, relief demand

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Authors: L. Yettou

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In this study, the calculations of proton emission spectra produced by ⁶³Cu(n,xp) and ⁶⁵Cu(n,xp) reactions are used in the framework of preequilibrium models using the EMPIRE code and TALYS code. Exciton Model predidtions combined with the Kalbach angular distribution systematics and the Hybrid Monte Carlo Simulation (HMS) were used. The effects of levels densities and those of a-parameter have been investigated for our calculations. The comparison with experimental data shows clear improvement over the Exciton Model and HMS calculations.

Keywords: Preequilibrium models , level density, level density a-parameter., Empire code, Talys code.

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Authors: Eyob Seife, Tesfalem Teshome, Bereket Seyoum, Behailu Getachew, Yohans Demis

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Developing countries continue to face preventable communicable diseases, such as vaccine-preventable diseases. The Expanded Programme on Immunization (EPI) was established by the World Health Organization in 1974 to control these diseases. Health data use is crucial in decision-making, but ensuring data quality remains challenging. The study aimed to assess the accuracy ratio, timeliness, and quality index of regular immunization programme data in the Birkod district of the Somali Region, Ethiopia. For poor data quality, technical, contextual, behavioral, and organizational factors are among contributors. The study used a quantitative cross-sectional design conducted in September 2022GC using WHO-recommended data quality self-assessment tools. The accuracy ratio and timeliness of reports on regular immunization programmes were assessed for two health centers and three health posts in the district for one fiscal year. Moreover, the quality index assessment was conducted at the district level and health facilities by trained assessors. The study found poor data quality in the accuracy ratio and timeliness of reports at all health units, which includes zeros. Overreporting was observed for most facilities, particularly at the health post level. Health centers showed a relatively better accuracy ratio than health posts. The quality index assessment revealed poor quality at all levels. The study recommends that responsible bodies at different levels improve data quality using various approaches, such as the capacitation of health professionals and strengthening the quality index components. The study highlighted the need for attention to data quality in general, specifically at the health post level, and improving the quality index at all levels, which is essential.

Keywords: Birkod District, data quality, quality index, regular immunization programme, Somali Region-Ethiopia

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Authors: Likewin Thomas, M. V. Manoj Kumar, B. Annappa

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The aim of this study was to develop an Artificial Neural Network0 s recommendation model for an online process using the complexity of load, performance, and average servicing time of the resources. Here, the proposed model investigates the resource performance using stochastic gradient decent method for learning ranking function. A probabilistic cost function is implemented to identify the optimal θ values (load) on each resource. Based on this result the recommendation of resource suitable for performing the currently executing task is made. The test result of CoSeLoG project is presented with an accuracy of 72.856%.

Keywords: ADALINE, neural network, gradient decent, process mining, resource behaviour, polynomial regression model

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Authors: Bowei Yuan, Shi Li, Liuyang Song, Huaqing Wang, Lingli Cui

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Convolutional neural networks (CNN) have received extensive attention in the field of fault diagnosis. Many fault diagnosis methods use CNN for fault type identification. However, when the amount of raw data collected by sensors is massive, the neural network needs to perform a time-consuming classification task. In this paper, a mechanical fault diagnosis method based on vibration signal down-sampling and the improved one-dimensional convolutional neural network is proposed. Through the robust principal component analysis, the low-rank feature matrix of a large amount of raw data can be separated, and then down-sampling is realized to reduce the subsequent calculation amount. In the improved one-dimensional CNN, a smaller convolution kernel is used to reduce the number of parameters and computational complexity, and regularization is introduced before the fully connected layer to prevent overfitting. In addition, the multi-connected layers can better generalize classification results without cumbersome parameter adjustments. The effectiveness of the method is verified by monitoring the signal of the centrifugal pump test bench, and the average test accuracy is above 98%. When compared with the traditional deep belief network (DBN) and support vector machine (SVM) methods, this method has better performance.

Keywords: fault diagnosis, vibration signal down-sampling, 1D-CNN

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Authors: S. M. T. Mustafa, D. Raes, M. Huysmans

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Proper utilization of water resource is very important in agro-based Bangladesh. Irrigation schedule based on local environmental conditions, soil type and water availability will allow a sustainable use of water resources in agriculture. In this study, the FAO crop water model (AquaCrop) was used to simulate the different water and fertilizer management strategies in different location of Bangladesh to obtain a management guideline for the farmer. Model was calibrated and validated for wheat (Triticum aestivum L.). The statistical indices between the observed and simulated grain yields obtained were very good with R2, RMSE, and EF values of 0.92, 0.33, and 0.83, respectively for model calibration and 0.92, 0.68 and 0.77, respectively for model validations. Stem elongation (jointing) to booting and flowering stage were identified as most water sensitive for wheat. Deficit irrigation on water sensitive stage could increase the grain yield for increasing soil fertility levels both for loamy and sandy type soils. Deficit irrigation strategies provides higher water productivity than full irrigation strategies and increase the yield stability (reduce the standard deviation). The practical deficit irrigation schedule for wheat for four different stations and two different soils were designed. Farmer can produce more crops by using deficit irrigation schedule under water stress condition. Practical application and validation of proposed strategies will make them more credible.

Keywords: crop-water model, deficit irrigation, irrigation scheduling, wheat

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Authors: Jiajia Pan, Hung Tao Shen

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Freeze and thaw occurs seasonally in river banks in northern countries. Little is known on how the riverbank soil temperature responds to air temperature changes and how freeze and thaw develops in a river bank seasonally. This study presents a two-dimensional heat conduction model for numerical investigations of seasonal freeze and thaw processes in an idealized river bank. The model uses the finite difference method and it is convenient for applications. The model is validated with an analytical solution and a field case with soil temperature distributions. It is then applied to the idealized river bank in terms of partially and fully saturated conditions with or without ice cover influence. Simulated results illustrate the response processes of the river bank to seasonal air temperature variations. It promotes the understanding of freeze and thaw processes in river banks and prepares for further investigation of frost and thaw impacts on riverbank stability.

Keywords: freeze and thaw, riverbanks, 2D model, heat conduction

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Authors: Panisa Harnpathananun

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This paper is 'Practical Experience Analysis' which aims to analyze critical obstacles hampering the growth of the functional milk industry and suggest recommendations to overcome those obstacles. Using the Sectoral Innovation System (SIS) along value chain analysis, it is found that restriction in regulation of milk disinfection process, difficulty of dairy entrepreneurs for health claim approval of functional food and beverage and lack of intermediary between entrepreneurs and certified units for certification of functional foods and milk are major causes that needed to be resolved. Consequently, policy recommendations are proposed to tackle the problems occurring throughout the value chain. For the upstream, a collaborative platform using the quadruple helix model is proposed in a pattern of effective dairy cooperatives. For the midstream, regulation issues of new process, extended shelf life (ESL) milk, or prolonged milk are necessary, which can be extended the global market opportunity. For the downstream, mechanism of intermediary between entrepreneurs and certified units can be assisted in certified process of functional milk, especially a process of 'health claim' approval.

Keywords: Thailand, functional milk, supply chain, quadruple helix, intermediary, functional food

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Authors: Zena Ebrahim, Susan Woodhouse

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Previous research shows that mothers’ experiences of trauma are linked to their child’s later socioemotional functioning. However, the mechanisms involved are not well understood. One potential mediator is maternal insensitive responses to child distress. This study examined the link between maternal trauma, mothers’ responses to toddler distress, and toddlers’ socioemotional outcomes among a socioeconomically diverse sample of 110 mothers and their 12- to 35-month-old toddlers. It was hypothesized that a mother’s difficulty in responding sensitively to her child’s distress would mediate the relations between maternal trauma and child internalizing and externalizing behaviors. Two mediational models were tested to examine non-supportive responses to distress as a potential mediator of the relation between maternal trauma and toddler mental health outcomes; one model focused on predicting child internalizing symptoms and the other focused on predicting child externalizing symptoms. Measures included assessment of maternal trauma (Life Stressor Checklist-Revised), mothers’ responses to child distress (Coping with Toddlers’ Negative Emotions Scale), and toddler socioemotional functioning (Infant-Toddler Social and Emotional Assessment). Results revealed that the relations between maternal trauma and toddler symptoms (internalizing and externalizing symptoms) were mediated by maternal non-supportive response to child distress for both internalizing and externalizing domains of child mental health. Findings suggest the importance of early intervention for trauma-exposed mothers and target areas for parenting interventions.

Keywords: trauma, parenting, child mental health, transgenerational effects of trauma

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Authors: Shahnaz Bashir, Abel Usoro, Imran Khan

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Hofstede’s culture model is an important model to study culture between different societies. He collected data from world-wide and performed a comprehensive study. Hofstede’s cultural model is widely accepted and has been used to study cross cultural influences in different areas like cross-cultural psychology, cross cultural management, information technology, and intercultural communication. This study investigates the societal cultural aspects of knowledge sharing in virtual communities.

Keywords: knowledge management, knowledge sharing, societal culture, virtual communities

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Authors: Shoji Katagiri, Hugang Han

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This paper clarifies the role of ICT capital in Economic Growth. Albeit ICT remarkably contributes to economic growth, there are few studies on ICT capital in ICT sector from theoretical point of view. In this paper, production function of ICT which is used as input of intermediate good in final good and ICT sectors is incorporated into our model. In this setting, we analyze the role of ICT on balance growth path and show the possibility of general equilibrium solutions for this model. Through the simulation of the equilibrium solutions, we find that when ICT impacts on economy and economic growth increases, it is necessary that increases of efficiency at ICT sector and of accumulation of non-ICT and ICT capitals occur simultaneously.

Keywords: endogenous economic growth, ICT, intensity, capital accumulation

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Authors: Yuta Moriyama, Etsuo Morishita

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Plasma actuator is very effective to recover stall flows over an upper airfoil surface. We first manufacture the actuator, test the stability of the device by trial and error basis and find the conditions for steady operations. We visualize the flow around an airfoil in the smoke tunnel and observe the stall recovery. The plasma actuator is stationary device and has no moving parts, and it might be an ideal device to control a model aircraft. We can use the actuator not only as a stall recovery device but also as a spoiler. We put the actuator near the leading edge of an elevator of a model aircraft as a spoiler, and measure the aerodynamic forces by a three-component balance. We observe the effect of the plasma actuator on the aerodynamic forces and the device effectiveness changes depending on the angle of attack whether it is positive or negative. We also visualize the flow caused by the plasma actuator by a desk-top Schlieren photography which is otherwise very difficult in a low-speed wind tunnel experiment.

Keywords: aerodynamics, plasma actuator, model aircraft, wind tunnel

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Authors: Hecson Christian, Joel Macwan

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Landfill site selection in an urban area is a critical issue in the planning process. With the growth of the urbanization, it has a mammoth impact on the economy, ecology, and environmental health of the region. Outsized amount of wastes are produced and the problem gets soared every day. Hence, selection of ideal site for sanitary landfill is a challenge for urban planners and solid waste managers. Disposal site is a function of many parameters. Among all, Geotechnical parameters are very vital as the same is related to surrounding open land. Moreover, the accessible safe and acceptable land is also scarce. Therefore, in this paper geotechnical parameters are used to develop a GIS model to identify an ideal location for landfill purpose. Metropolitan city of Surat is highly populated and fastest growing urban area in India. The research objectives are to conduct field experiments to collect data and to transfer the facts in GIS platform to evolve a model, to find ideal location. Planners’ preferences were obtained to use analytical hierarchical process (AHP) to find weights of each parameter. Integration of GIS and Multi-Criteria Decision Analysis (MCDA) techniques are applied to improve decision-making. It augments an environment for transformation and combination of geographical data and planners’ preferences. GIS performs deterministic overlay and buffer operations. MCDA methods evaluate alternatives based on the decision makers’ subjective values and priorities. Research results have shown many alternative locations. Economic analysis of selected site from actual operations point of view is not included in this research.

Keywords: GIS, AHP, MCDA, Geo-technical

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Authors: Amaba, Marinela C., Espino, Gianne Ericka S. J. Valencia, Zeia Beatriz C.

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This study aims to determine the moderating role of attachment style on the relationship between psychological symptoms and well-being of mental health practitioners in rehabilitation centers that are accredited of the Department of Health in Pampanga. Using the data gathered from 46 mental health practitioners, multiple regression models were conducted to test the main and moderating effects of attachment styles. The findings show that all three psychological symptoms namely depression, anxiety, and stress have main effects on their general well-being on a negative direction. However, attachment style did not moderate the relationship between the psychological symptoms and general well-being. On one hand, results about the relationship of psychological symptoms and well-being are consistent to previous findings of other studies while on the other hand, results in moderation were contradicting.

Keywords: attachment style, psychological symptoms, well-being, mental health practitioners, rehabilitation centers

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Authors: Paul R Armstrong

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Doubled haploids (DHs) have become an important breeding tool for creating maize inbred lines, although several bottlenecks in the DH production process limit wider development, application, and adoption of the technique. DH kernels are typically sorted manually and represent about 10% of the seeds in a much larger pool where the remaining 90% are hybrid siblings. This introduces time constraints on DH production and manual sorting is often not accurate. Automated sorting based on the chemical composition of the kernel can be effective, but devices, namely NMR, have not achieved the sorting speed to be a cost-effective replacement to manual sorting. This study evaluated a single kernel near-infrared reflectance spectroscopy (skNIR) platform to accurately identify DH kernels based on oil content. The skNIR platform is a higher-throughput device, approximately 3 seeds/s, that uses spectra to predict oil content of each kernel from maize crosses intentionally developed to create larger than normal oil differences, 1.5%-2%, between DH and hybrid kernels. Spectra from the skNIR were used to construct a partial least squares regression (PLS) model for oil and for a categorical reference model of 1 (DH kernel) or 2 (hybrid kernel) and then used to sort several crosses to evaluate performance. Two approaches were used for sorting. The first used a general PLS model developed from all crosses to predict oil content and then used for sorting each induction cross, the second was the development of a specific model from a single induction cross where approximately fifty DH and one hundred hybrid kernels used. This second approach used a categorical reference value of 1 and 2, instead of oil content, for the PLS model and kernels selected for the calibration set were manually referenced based on traditional commercial methods using coloration of the tip cap and germ areas. The generalized PLS oil model statistics were R2 = 0.94 and RMSE = .93% for kernels spanning an oil content of 2.7% to 19.3%. Sorting by this model resulted in extracting 55% to 85% of haploid kernels from the four induction crosses. Using the second method of generating a model for each cross yielded model statistics ranging from R2s = 0.96 to 0.98 and RMSEs from 0.08 to 0.10. Sorting in this case resulted in 100% correct classification but required models that were cross. In summary, the first generalized model oil method could be used to sort a significant number of kernels from a kernel pool but was not close to the accuracy of developing a sorting model from a single cross. The penalty for the second method is that a PLS model would need to be developed for each individual cross. In conclusion both methods could find useful application in the sorting of DH from hybrid kernels.

Keywords: NIR, haploids, maize, sorting

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Authors: Kornelius Ronald Demu, Dewi Retno Sari Saputro, Purnami Widyaningsih

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Human Development Index (HDI) is a standard measurement for a country's human development. Several factors may have influenced it, such as life expectancy, gross domestic product (GDP) based on the province's annual expenditure, the number of poor people, and the percentage of an illiterate people. The scatter plot between HDI and the influenced factors show that the plot does not follow a specific pattern or form. Therefore, the HDI's data in Indonesia can be applied with a nonparametric regression model. The estimation of the regression curve in the nonparametric regression model is flexible because it follows the shape of the data pattern. One of the nonparametric regression's method is a truncated spline. Truncated spline regression is one of the nonparametric approach, which is a modification of the segmented polynomial functions. The estimator of a truncated spline regression model was affected by the selection of the optimal knots point. Knot points is a focus point of spline truncated functions. The optimal knots point was determined by the minimum value of generalized cross validation (GCV). In this article were applied the data of Human Development Index with a truncated spline nonparametric regression model. The results of this research were obtained the best-truncated spline regression model to the HDI's data in Indonesia with the combination of optimal knots point 5-5-5-4. Life expectancy and the percentage of an illiterate people were the significant factors depend to the HDI in Indonesia. The coefficient of determination is 94.54%. This means the regression model is good enough to applied on the data of HDI in Indonesia.

Keywords: generalized cross validation (GCV), Human Development Index (HDI), knots point, nonparametric regression, truncated spline

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Authors: Seyed Abolhasan Naeini, Eisa Aliagahei

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Today, the use of geosynthetic materials in geotechnical activities is increasing significantly. One of the main uses of these materials is to increase the compressive strength of clay reinforced by geotextile layers. In the present study, the effect of clay reinforcement by geotextile layers in increasing the compressive strength of clay has been investigated using modeling in ABAQUS 6.11.3 software. For this purpose, the modified Drager Prager model has been chosen to simulate the stress-strain behavior of soil layers and the linear elastic model for the geotextile layer. Unreinforced samples and reinforced samples are modeled by geotextile layers (1, 2 and 3 geotextile layers) by software. In order to validate the results, an article in the same field was used and the numerical modeling results were calibrated with the laboratory results. Based on the obtained results, the software has a suitable capability for modeling and the results of the numerical model overlap with the laboratory results to a very acceptable extent, by increasing the number of geotextile layers, the error between the results of the laboratory sample and the software model increases. The highest amount of error is related to the sample reinforced with three layers of geotextile and is 7.3%.

Keywords: Abaqus, cap model, clay, geotextile layer, reinforced soil

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Authors: Sally Kafelghazal

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Introduction: Arab Americans, who include immigrants, refugees, or U.S. born persons of Middle Eastern or North African descent, may experience significant difficulties during acculturation to Western society. Influential stressors include relocation, loss of social support, language barriers, and economic factors, all of which can impact mental health. There is limited research investigating the effects of acculturation on the mental health of the Arab American population. Objectives: The purpose of this study is to identify ways in which acculturation impacts the mental health of Arab Americans, specifically the development of depression and anxiety. Method: A literature search was conducted using PubMed and PsycArticles (ProQuest), utilizing the following search terms: “Arab Americans,” “Arabs,” “mental health,” “depression,” “anxiety,” “acculturation.” Thirty-nine articles were identified and of those, nine specifically investigated the relationship between acculturation and mental health in Arab Americans. Three of the nine focused exclusively on depression. Results: Several risk factors were identified that contribute to poor mental health associated with acculturation, which include immigrant or refugee status, facing discrimination, and religious ideology. Protective factors include greater levels of acculturation, being U.S. born, and greater heritage identity. Greater mental health disorders were identified in Arab Americans compared to normative samples, perhaps particularly depression; none of the articles specifically addressed anxiety. Conclusion: The current research findings support the potential association between the process of acculturation and greater levels of mental health disorders in Arab Americans. However, the diversity of the Arab American population makes it difficult to draw consistent conclusions. Further research needs to be conducted in order to assess which subgroups in the Arab American population are at highest risk for developing new or exacerbating existing mental health disorders in order to devise more effective interventions.

Keywords: arab americans, arabs, mental health, anxiety, depression, acculturation

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Authors: Janine Sommer, Mariana Daus, Mariana Simon, Maria Smith, Daniel Luna

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The technologies and communication advances contributed to new tools development which allows patients to have an active role in their own health. In the light of information needs and paradigms changes about health, the patient self-manages their care. This line of care focuses on patients; specific portals come up to people with particular requirements like pregnant women. Thinking of a portal design to this sector of the population, in September 2016 a survey was made to users with the objective to knowing and understanding information’s needs at the moment to use an application for pregnant. Also, prototypes of the portal´s features were designed to try and validate with users, using the methodology of human-centered design. Investigations have made possible the identification of needs of this population and develop a tool who try to satisfy, providing timely information for each part of pregnancy and allowing the patients to make a physical check and the follow up of pregnancy seeking advice from our obstetricians.

Keywords: electronic health record, health personal record, mobile applications, pregnant women

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Authors: Maryam Safrai, Tewfik Mahdi

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This article presents the stochastic modeling of the Richelieu River flood in Quebec, Canada, occurred in the spring of 2011. With the aid of the one-dimensional Watershed Modeling System (WMS (v.10.1) and HEC-RAS (v.4.1) as a flood simulator, the delineation of the probabilistic flooded areas was considered. Based on the Monte Carlo method, WMS (v.10.1) delineated the probabilistic flooded areas with corresponding occurrence percentages. Furthermore, results of this one-dimensional model were compared with the results of two-dimensional model (SRH-2D) for the evaluation of efficiency and precision of each applied model. Based on this comparison, computational process in two-dimensional model is longer and more complicated versus brief one-dimensional one. Although, two-dimensional models are more accurate than one-dimensional method, but according to existing modellers, delineation of probabilistic flooded areas based on Monte Carlo method is achievable via one-dimensional modeler. The applied software in this case study greatly responded to verify the research objectives. As a result, flood risk maps of the Richelieu River with the two applied models (1d, 2d) could elucidate the flood risk factors in hydrological, hydraulic, and managerial terms.

Keywords: flood modeling, HEC-RAS, model comparison, Monte Carlo simulation, probabilistic flooded area, SRH-2D, WMS

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Authors: Safia Hocine, Zina Benouaret, Djamil A¨ıssani

Abstract:

In this paper, we study the performance of the strong stability method of the univariate classical risk model. We interest to the stability bounds established using two approaches. The first based on the strong stability method developed for a general Markov chains. The second approach based on the regenerative processes theory . By adopting an algorithmic procedure, we study the performance of the stability method in the case of exponential distribution claim amounts. After presenting numerically and graphically the stability bounds, an interpretation and comparison of the results have been done.

Keywords: Marcov chain, regenerative process, risk model, ruin probability, strong stability

Procedia PDF Downloads 324

Authors: Suchada Wongsawat

Abstract:

The objectives of this quasi-experiment were: 1) to compare pretest and posttest scores of the experimental group who were given health education on the “Fruit Diets for Elderly Patients with Type 2 Diabetes Mellitus”; and 2) to compare the posttest scores between experimental group and controlled group. The samples of this study were elderly patients with type 2 Diabetes Mellitus at Tambon Kanai Health Promoting Hospital, Thailand. The samples were randomly assigned to experimental and controlled groups, with 30 patients in each group. Statistics used in the data analysis included frequency, percentage, average, standard deviation, paired t-test and independent t-test. The study revealed that the patients in the experimental group had significantly higher posttest scores than the pretest scores in the health education at the .05 statistical level. The posttest scores of the experimental group in the health education were significantly higher than the controlled group at the .05 statistical level.

Keywords: fruit, health education, elderly, diabetes

Procedia PDF Downloads 283

Authors: Tünde Puskás, Anita Andersson

Abstract:

This study is part of a research project about whether religion is considered as part of Swedish cultural heritage in Swedish preschools. Our aim in this paper is to explore how a Swedish preschool balance between keeping the education non-confessional and at the same time teaching children about a particular tradition, Easter.The paper explores how in a Swedish preschool with a religious profile teachers balance between keeping education non-confessional and teaching about a tradition with religious roots. The point of departure for the theoretical frame of our study is that practical considerations in pedagogical situations are inherently dilemmatic. The dilemmas that are of interest for our study evolve around formalized, intellectual ideologies, such us multiculturalism and secularism that have an impact on everyday practice. Educational dilemmas may also arise in the intersections of the formalized ideology of non-confessionalism, prescribed in policy documents and the common sense understandings of what is included in what is understood as Swedish cultural heritage. In this paper, religion is treated as a human worldview that, similarly to secular ideologies, can be understood as a system of thought. We make use of Ninian Smart's theoretical framework according to which in modern Western world religious and secular ideologies, as human worldviews, can be studied from the same analytical framework. In order to be able to study the distinctive character of human worldviews Smart introduced a multi-dimensional model within which the different dimensions interact with each other in various ways and to different degrees. The data for this paper is drawn from fieldwork carried out in 2015-2016 in the form of video ethnography. The empirical material chosen consists of a video recording of a specific activity during which the preschool group took part in an Easter play performed in the local church. The analysis shows that the policy of non-confessionalism together with the idea that teaching covering religious issues must be purely informational leads in everyday practice to dilemmas about what is considered religious. At the same time what the adults actually do with religion fulfills six of seven dimensions common to religious traditions as outlined by Smart. What we can also conclude from the analysis is that whether it is religion or a cultural tradition that is thought through the performance the children watched in the church depends on how the concept of religion is defined. The analysis shows that the characters of the performance themselves understood religion as the doctrine of Jesus' resurrection from the dead. This narrow understanding of religion enabled them indirectly to teach about the traditions and narratives surrounding Easter while avoiding teaching religion as a belief system.

Keywords: non-confessional education, preschool, religion, tradition

Procedia PDF Downloads 159

Authors: M. J. Uddin, M. M. Rahman

Abstract:

Transient natural convective flow dynamics of nanofluids in a horizontal homocentric annulus using nonhomogeneous dynamic model has been experimented numerically. The simulation is carried out for four different shapes of the inner wall, which is either cylindrical, elliptical, square or triangular. The outer surface of the annulus is maintained at constant low temperature while the inner wall is maintained at a uniform temperature; higher than the outer one. The enclosure is permeated by a uniform magnetic field having variable orientation. The Brownian motion and thermophoretic deposition phenomena of the nanoparticles are taken into account in model construction. The governing nonlinear momentum, energy, and concentration equations are solved numerically using Galerkin weighted residual finite element method. To find the best performer, the local Nusselt number is demonstrated for different shapes of the inner wall. The heat transfer enhancement for different nanofluids for four different shapes of the inner wall is exhibited.

Keywords: nanofluids, annulus, nonhomogeneous dynamic model, heat transfer

Procedia PDF Downloads 170